In [1]:
import classify_covs
import show_connectomes
import covariance
import matplotlib.pyplot as plt
from sklearn.covariance import EmpiricalCovariance, LedoitWolf
import itertools
from pval_correction import correct
#%matplotlib inline
In [2]:
def plot_results(t_df, p_th=.05, estim_title=None):
if estim_title is not None:
estim_title = " ({})".format(estim_title)
for ix_ in range(len(t_df)):
tstats = covariance.vec_to_sym(t_df["tstat"].iloc[ix_], isometry=False)
pvals = covariance.vec_to_sym(t_df["pval"].iloc[ix_], isometry=False)
tstats[pvals > p_th] = 0.
title = t_df["comparison"].iloc[ix_] + estim_title
show_connectomes.plot_adjacency(tstats, n_clusters=1,
title=title,
vmin=None, vmax=None, col_map="red_blue_r",
fig_name="/home/storage/workspace/parietal_retreat/covariance_learn/figures3/" +
title + ".pdf")
In [3]:
base_estimators = [EmpiricalCovariance(assume_centered=True),
LedoitWolf(assume_centered=True)]
estimators_ = list(itertools.product(["tangent", "precision", "correlation"], base_estimators))
est = ('kind', 'cov_estimator')
estimators = [dict(zip(*[est, e])) for e in estimators_]
t_test = list()
for est_ in estimators:
t_test.append(classify_covs.statistical_test(root_dir="/volatile/storage/workspace/brainpedia/preproc",
estimators=est_, p_correction=None, n_jobs=6))
#plot_results(t_test[-1], estim_title=est_["kind"] + " " + format(est_["cov_estimator"]).split("(")[0])
________________________________________________________________________________
[Memory] Calling setup_data_paths.run...
run(data_set='ds107', n_jobs=6, root_dir='/volatile/storage/workspace/brainpedia/preproc', dump_dir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107')
Loading all paths and variables into memory
preparing and running MultiNiftiMasker
[MultiNiftiMasker.fit] Loading data from [/volatile/storage/workspace/brainpedia/preproc/ds107/sub001/model/model001/BOLD/task001_run001/bold.nii.gz, /volatile/storage/workspace/brainpedia/preproc/ds107/sub001/model/model001/BOLD/task001_run
[MultiNiftiMasker.fit] Computing mask
[MultiNiftiMasker.transform] Resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9526490>, target_shape=(53, 63, 46), target_affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]]), copy=False, interpolation='nearest')
_____________________________________________________resample_img - 0.0s, 0.0min
preparing and running NiftiMapsMasker
/home/rphlypo/Projects/nilearn/nilearn/_utils/cache_mixin.py:206: UserWarning: memory_level is currently set to 0 but a Memory object has been provided. Setting memory_level to 1.
warnings.warn("memory_level is currently set to 0 but "
__________________________________________________________run - 4770.6s, 79.5min
Objects vs. Words: t_stat = [ 0.84963626 -0.65415794 3.58779391 ..., -2.5072905 -0.63393012
1.27594727], q-val = [ 0.39974532 0.51613216 0.00078015 ..., 0.01560362 0.52913597
0.20811408][NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub001/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub001/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub001/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub001/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub001/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub001/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9413f10>, <nibabel.nifti1.Nifti1Image object at 0x9413a50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x1b94e10>)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9413e10>, <nibabel.nifti1.Nifti1Image object at 0x9413b10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x1b94e10>)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9414e10>, <nibabel.nifti1.Nifti1Image object at 0x9414990>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x1b94e10>)[NiftiMapsMasker.fit_transform] cleaning extracted signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9412e10>, <nibabel.nifti1.Nifti1Image object at 0x9412bd0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x1b94e10>)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 13.8s, 0.2min_____________________________________________img_to_signals_maps - 14.1s, 0.2min_____________________________________________img_to_signals_maps - 15.2s, 0.3min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 14.3s, 0.2min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub001/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub001/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub002/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub002/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub002/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub002/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub002/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub002/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub003/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub003/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub003/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub003/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub002/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub002/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
Scrambled objects vs. Words: t_stat = [-0.21352666 -0.37835305 3.51978009 ..., -1.29234315 -0.23547469
-0.34937921], q-val = [ 0.83182059 0.70683658 0.000957 ..., 0.20242538 0.8148421
0.72833282][NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub004/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub004/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub004/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub004/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.519291, ..., 15.025761],
...,
[ 8.568972, ..., 15.07714 ]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.519291, ..., 15.025761],
...,
[ 8.568972, ..., 15.07714 ]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub003/model/model001/BOLD/task001_run001/bold.nii.gz
(166, 5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub003/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
(166, 5)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________________clean - 0.9s, 0.0min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub004/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub004/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________________clean - 0.9s, 0.0min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub005/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub005/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub003/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub003/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub005/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub005/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x99d3cd0>, <nibabel.nifti1.Nifti1Image object at 0x99d3b90>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x99d3d50>)[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 15.2s, 0.3min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c724d0>, <nibabel.nifti1.Nifti1Image object at 0x9c72390>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9c72550>)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x945f710>, <nibabel.nifti1.Nifti1Image object at 0x945f5d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x945f790>)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub006/model/model001/BOLD/task001_run002/bold.nii.gz
_____________________________________________img_to_signals_maps - 15.4s, 0.3min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)_____________________________________________img_to_signals_maps - 14.3s, 0.2min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub006/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub004/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub004/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub005/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub005/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.561394, ..., 17.623294],
...,
[ 9.445224, ..., 17.720995]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
Scrambled objects vs. Objects: t_stat = [-1.03456815 0.37491828 -0.42083063 ..., 1.62912607 0.6970941
-4.71402883], q-val = [ 3.06054984e-01 7.09372736e-01 6.75757067e-01 ..., 1.09832673e-01
4.89106539e-01 2.11931809e-05][NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] smoothing images________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.519291, ..., 15.025761],
...,
[ 8.568972, ..., 15.07714 ]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.519291, ..., 15.025761],
...,
[ 8.568972, ..., 15.07714 ]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
(164, 5)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals(166, 5)____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub006/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals(166, 5)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals____________________________________________________________clean - 0.7s, 0.0min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz____________________________________________________________clean - 0.8s, 0.0min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub007/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub006/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub005/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub005/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub006/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x943a850>, <nibabel.nifti1.Nifti1Image object at 0x943acd0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943ae90>)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub007/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 14.2s, 0.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9467910>, <nibabel.nifti1.Nifti1Image object at 0x94677d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9467990>)
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)_____________________________________________img_to_signals_maps - 14.0s, 0.2min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.576667, ..., 17.809232],
...,
[ 9.54877 , ..., 17.716154]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub007/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz(163, 5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub008/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub006/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x99d7a10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
____________________________________________________resample_img - 77.2s, 1.3min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub007/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub006/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9578390>, <nibabel.nifti1.Nifti1Image object at 0x9c65d50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x7f80b0346950>)[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub006/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images_____________________________________________img_to_signals_maps - 14.4s, 0.2min[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] cleaning extracted signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x99d79d0>, <nibabel.nifti1.Nifti1Image object at 0x99d7590>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x99d7750>)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 13.9s, 0.2min[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.561394, ..., 17.623294],
...,
[ 9.445224, ..., 17.720995]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub008/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub007/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
(164, 5)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x941df10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub008/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________resample_img - 44.2s, 0.7min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub007/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub009/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9450290>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] resampling images to fit maps
Consonant strings vs. Words: t_stat = [-2.68732555 -0.51653949 0.07119131 ..., -1.21047314 0.33701975
-0.89733287], q-val = [ 0.00986804 0.60784942 0.9435413 ..., 0.23202438 0.73757123
0.37402017]
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9449d90>, <nibabel.nifti1.Nifti1Image object at 0x94492d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x94494d0>)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943a850>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________resample_img - 44.1s, 0.7min________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x1e99390>, fwhm=5)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub007/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 13.2s, 0.2min____________________________________________________resample_img - 44.2s, 0.7min[NiftiMapsMasker.fit_transform] smoothing images
______________________________________________________smooth_img - 12.0s, 0.2min[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x1e99390>, fwhm=5)
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x943a290>, fwhm=5)______________________________________________________smooth_img - 17.7s, 0.3min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9521c90>, <nibabel.nifti1.Nifti1Image object at 0x941db10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x941de50>)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x94492d0>, <nibabel.nifti1.Nifti1Image object at 0x94498d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9449450>)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)______________________________________________________smooth_img - 13.0s, 0.2min[NiftiMapsMasker.fit_transform] extracting region signals
_____________________________________________img_to_signals_maps - 13.0s, 0.2min_____________________________________________img_to_signals_maps - 14.3s, 0.2min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9521e10>, <nibabel.nifti1.Nifti1Image object at 0x9450610>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9450590>)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub007/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub008/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x943aed0>, <nibabel.nifti1.Nifti1Image object at 0x943a390>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x7f80b0346950>)_____________________________________________img_to_signals_maps - 13.3s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.82289 , ..., 16.225963],
...,
[ 10.789743, ..., 16.317816]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x94298d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
_____________________________________________img_to_signals_maps - 13.4s, 0.2min[NiftiMapsMasker.fit_transform] cleaning extracted signals
(166, 5)
[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________resample_img - 44.5s, 0.7min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub008/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.819479, ..., 17.876599],
...,
[ 11.059188, ..., 17.667645]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9429f10>, fwhm=5)
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9429f10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
(166, 5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub008/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)______________________________________________________smooth_img - 44.7s, 0.7min____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub009/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________resample_img - 72.4s, 1.2min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub008/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x941dc50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9521f10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub010/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x7f80b0350050>, <nibabel.nifti1.Nifti1Image object at 0x9521e90>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9521b50>)____________________________________________________resample_img - 44.3s, 0.7min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x1e99350>, <nibabel.nifti1.Nifti1Image object at 0x9429550>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9429cd0>)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.862947, ..., 16.285701],
...,
[ 10.883166, ..., 16.29949 ]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________resample_img - 44.3s, 0.7min
_____________________________________________img_to_signals_maps - 14.0s, 0.2min[NiftiMapsMasker.fit_transform] smoothing images
_____________________________________________img_to_signals_maps - 13.3s, 0.2min
(164, 5)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943ab50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9521f10>, fwhm=5)
[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x1e99190>, fwhm=5)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 45.1s, 0.8min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
______________________________________________________smooth_img - 12.2s, 0.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)______________________________________________________smooth_img - 12.0s, 0.2min
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x943a590>, fwhm=5)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub009/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub009/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x941ded0>, <nibabel.nifti1.Nifti1Image object at 0x95219d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9521d10>)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub009/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
______________________________________________________smooth_img - 12.7s, 0.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9523190>, <nibabel.nifti1.Nifti1Image object at 0x9449510>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9449450>)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9429ad0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x99d3550>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')_____________________________________________img_to_signals_maps - 12.8s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9521f10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] extracting region signals
_____________________________________________img_to_signals_maps - 13.0s, 0.2min____________________________________________________resample_img - 58.4s, 1.0min
____________________________________________________resample_img - 78.2s, 1.3min[NiftiMapsMasker.fit_transform] cleaning extracted signals
Failed to save <type 'numpy.ndarray'> to .npy file:
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 241, in save
obj, filename = self._write_array(obj, filename)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 202, in _write_array
self.np.save(filename, array)
File "/home/rphlypo/.local/lib/python2.7/site-packages/numpy/lib/npyio.py", line 443, in save
fid = open(file, "wb")
IOError: [Errno 2] Aucun fichier ou dossier de ce type: '/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib/nilearn/image/resampling/resample_img/2f36f60589ec40858fdaf35db7ff0961/output.pkl_02.npy'
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x943ad10>, <nibabel.nifti1.Nifti1Image object at 0x943a7d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943ac90>)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.84497 , ..., 17.300974],
...,
[ 10.991606, ..., 17.64283 ]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
Failed to save <type 'numpy.ndarray'> to .npy file:
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 241, in save
obj, filename = self._write_array(obj, filename)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 202, in _write_array
self.np.save(filename, array)
File "/home/rphlypo/.local/lib/python2.7/site-packages/numpy/lib/npyio.py", line 443, in save
fid = open(file, "wb")
IOError: [Errno 2] Aucun fichier ou dossier de ce type: '/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib/nilearn/image/resampling/resample_img/2f36f60589ec40858fdaf35db7ff0961/output.pkl_02.npy'
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.862947, ..., 16.285701],
...,
[ 10.883166, ..., 16.29949 ]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 13.9s, 0.2min[NiftiMapsMasker.fit_transform] extracting region signals(165, 5)
____________________________________________________________clean - 0.0s, 0.0min
Consonant strings vs. Objects: t_stat = [-4.04318712 0.13684249 -3.72640129 ..., 0.58961558 1.92096767
-4.8608837 ], q-val = [ 1.90114009e-04 8.91727666e-01 5.11621680e-04 ..., 5.58213701e-01
6.06859285e-02 1.29261849e-05]____________________________________________________resample_img - 55.9s, 0.9min(164, 5)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9521f50>, <nibabel.nifti1.Nifti1Image object at 0x9429610>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9429b50>)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.514984, ..., 15.550023],
...,
[ 9.511389, ..., 15.397001]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 13.4s, 0.2min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
(166, 5)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub009/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x95212d0>, <nibabel.nifti1.Nifti1Image object at 0x9429b50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9429050>)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub008/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub010/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9414a50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')_____________________________________________img_to_signals_maps - 13.6s, 0.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x99d3650>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________resample_img - 44.0s, 0.7min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub009/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub010/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________resample_img - 86.8s, 1.4min[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9412d50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9521dd0>, <nibabel.nifti1.Nifti1Image object at 0x9521f50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9449150>)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 70.7s, 1.2min________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x941d090>, fwhm=5)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub010/model/model001/BOLD/task001_run001/bold.nii.gz
_____________________________________________img_to_signals_maps - 14.3s, 0.2min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
______________________________________________________smooth_img - 45.3s, 0.8min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x99d3510>, <nibabel.nifti1.Nifti1Image object at 0x99d3910>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x99d3790>)________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.819479, ..., 17.876599],
...,
[ 11.059188, ..., 17.667645]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9e0b390>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 15.7s, 0.3min(166, 5)
____________________________________________________resample_img - 67.9s, 1.1min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub009/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9e0b0d0>, <nibabel.nifti1.Nifti1Image object at 0x9deef10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9deef90>)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9cd53d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub010/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub010/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub011/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
_____________________________________________img_to_signals_maps - 21.0s, 0.3min____________________________________________________resample_img - 77.7s, 1.3min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub011/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c8ab10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x946b690>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9577410>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
____________________________________________________resample_img - 46.1s, 0.8min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9df9b50>, fwhm=5)
____________________________________________________resample_img - 47.7s, 0.8min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
____________________________________________________resample_img - 44.3s, 0.7min
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals______________________________________________________smooth_img - 47.0s, 0.8min
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9c8ad90>, fwhm=5)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x946b910>, fwhm=5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub010/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.84497 , ..., 17.300974],
...,
[ 10.991606, ..., 17.64283 ]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x1e99390>, fwhm=5)
______________________________________________________smooth_img - 18.9s, 0.3min[NiftiMapsMasker.fit_transform] resampling images to fit maps
______________________________________________________smooth_img - 13.5s, 0.2min
[NiftiMapsMasker.fit_transform] smoothing images(165, 5)
[NiftiMapsMasker.fit_transform] cleaning extracted signals______________________________________________________smooth_img - 12.1s, 0.2min
[NiftiMapsMasker.fit_transform] extracting region signals
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9e0b510>, fwhm=5)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c8a1d0>, <nibabel.nifti1.Nifti1Image object at 0x9c8a690>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9c8a850>)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x946b450>, <nibabel.nifti1.Nifti1Image object at 0x946b210>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x946b3d0>)
______________________________________________________smooth_img - 13.6s, 0.2min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9521c90>, <nibabel.nifti1.Nifti1Image object at 0x9577290>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9577a50>)
_____________________________________________img_to_signals_maps - 15.0s, 0.3min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
_____________________________________________img_to_signals_maps - 12.8s, 0.2min
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub010/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub011/model/model001/BOLD/task001_run002/bold.nii.gz
_____________________________________________img_to_signals_maps - 12.8s, 0.2min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.563387, ..., 15.527891],
...,
[ 9.46608 , ..., 15.352213]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] cleaning extracted signals________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9cd5ed0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x946cb50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] cleaning extracted signals
Consonant strings vs. Scrambled objects: t_stat = [-2.39572524 -0.21294722 -2.4833608 ..., -0.4418001 0.81223868
-1.17017552], q-val = [ 0.02053508 0.83226996 0.0165605 ..., 0.66061794 0.42066479
0.24770769]________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.339897, ..., 12.552148],
...,
[ 10.370548, ..., 12.749523]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.314643, ..., 12.530339],
...,
[ 10.29712 , ..., 12.643698]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
(166, 5)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.563387, ..., 15.527891],
...,
[ 9.46608 , ..., 15.352213]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)____________________________________________________resample_img - 87.1s, 1.5min____________________________________________________resample_img - 80.6s, 1.3min
(166, 5)
____________________________________________________________clean - 0.0s, 0.0min
(166, 5)
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
(166, 5)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9cd5c10>, <nibabel.nifti1.Nifti1Image object at 0x9cd5710>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9cd52d0>)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x946cb10>, <nibabel.nifti1.Nifti1Image object at 0x946c6d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x946c890>)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub011/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub011/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
_____________________________________________img_to_signals_maps - 14.4s, 0.2min_____________________________________________img_to_signals_maps - 13.9s, 0.2min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub011/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c81090>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub011/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x946bc90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x95779d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
____________________________________________________resample_img - 51.4s, 0.9min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b55b90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 43.2s, 0.7min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 55.3s, 0.9min
[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 90.0s, 1.5min
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9c8a190>, fwhm=5)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub011/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub012/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
______________________________________________________smooth_img - 47.7s, 0.8min[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9cea890>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9dfc2d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9b55b50>, <nibabel.nifti1.Nifti1Image object at 0x9b55710>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9b558d0>)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.314643, ..., 12.530339],
...,
[ 10.29712 , ..., 12.643698]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
____________________________________________________resample_img - 49.0s, 0.8min____________________________________________________resample_img - 65.4s, 1.1min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals_____________________________________________img_to_signals_maps - 13.7s, 0.2min
(166, 5)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.339897, ..., 12.552148],
...,
[ 10.370548, ..., 12.749523]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9ceab10>, fwhm=5)[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)(166, 5)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)______________________________________________________smooth_img - 48.3s, 0.8min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x946cf50>, <nibabel.nifti1.Nifti1Image object at 0x946ce50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x946cf10>)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub012/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________________clean - 3.6s, 0.1min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 13.4s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9413a90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub012/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub012/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 71.1s, 1.2min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b6e310>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943c690>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.339897, ..., 12.552148],
...,
[ 10.370548, ..., 12.749523]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub012/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________resample_img - 44.4s, 0.7min
[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________resample_img - 44.6s, 0.7min[NiftiMapsMasker.fit_transform] resampling images to fit maps
(166, 5)
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c87750>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________________clean - 3.1s, 0.1min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub013/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9b55850>, fwhm=5)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x943c910>, fwhm=5)____________________________________________________resample_img - 45.8s, 0.8min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9dfcb50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
______________________________________________________smooth_img - 33.7s, 0.6min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)______________________________________________________smooth_img - 12.5s, 0.2min[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 79.5s, 1.3min
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9c879d0>, fwhm=5)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub012/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub013/model/model001/BOLD/task001_run002/bold.nii.gz
______________________________________________________smooth_img - 22.5s, 0.4min[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x943c450>, <nibabel.nifti1.Nifti1Image object at 0x943c210>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943c3d0>)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9ceaed0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x99d7690>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.367059, ..., 19.68466 ],
...,
[ 10.272965, ..., 19.769169]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
Objects vs. Words: t_stat = [-8.0652917 3.26316656 -6.91733428 ..., -2.6040717 1.31698739
-1.64432517], q-val = [ 1.75496278e-10 2.03338990e-03 9.84499658e-09 ..., 1.22245747e-02
1.94095863e-01 1.06643679e-01][NiftiMapsMasker.fit_transform] cleaning extracted signals
_____________________________________________img_to_signals_maps - 14.9s, 0.2min
____________________________________________________resample_img - 45.1s, 0.8min
____________________________________________________resample_img - 73.1s, 1.2min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c87510>, <nibabel.nifti1.Nifti1Image object at 0x9c872d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9c87490>)(165, 5)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.543665, ..., 15.881436],
...,
[ 9.142935, ..., 15.545649]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.335297, ..., 19.708586],
...,
[ 10.51009 , ..., 19.724671]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)_____________________________________________img_to_signals_maps - 14.2s, 0.2min____________________________________________________________clean - 0.1s, 0.0min
(165, 5)
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x99d7d50>, fwhm=5)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9cead90>, fwhm=5)____________________________________________________________clean - 0.0s, 0.0min
(166, 5)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz______________________________________________________smooth_img - 12.4s, 0.2min____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
______________________________________________________smooth_img - 12.3s, 0.2min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub013/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x99d7050>, <nibabel.nifti1.Nifti1Image object at 0x99d7310>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x99d7a10>)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub012/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9412f90>, <nibabel.nifti1.Nifti1Image object at 0x9cea810>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9ceac10>)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub014/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub013/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b6e910>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] resampling images to fit maps
_____________________________________________img_to_signals_maps - 13.5s, 0.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
_____________________________________________img_to_signals_maps - 12.6s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9521f50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943cc90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
____________________________________________________resample_img - 44.4s, 0.7min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 78.3s, 1.3min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 57.4s, 1.0min
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.367059, ..., 19.68466 ],
...,
[ 10.272965, ..., 19.769169]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c87a10>, <nibabel.nifti1.Nifti1Image object at 0x9c87110>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9c87a90>)________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9b6eb90>, fwhm=5)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
(165, 5)________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x7f80b0350810>, fwhm=5)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 14.9s, 0.2min______________________________________________________smooth_img - 13.1s, 0.2min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub014/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________________clean - 0.6s, 0.0min______________________________________________________smooth_img - 12.1s, 0.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x943cc50>, <nibabel.nifti1.Nifti1Image object at 0x943c290>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943c9d0>)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x99ea210>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
_____________________________________________img_to_signals_maps - 17.4s, 0.3min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9b6e6d0>, <nibabel.nifti1.Nifti1Image object at 0x9b6e090>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9b6e650>)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
____________________________________________________resample_img - 56.7s, 0.9min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x1e99350>, <nibabel.nifti1.Nifti1Image object at 0x9412f50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9412d50>)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
_____________________________________________img_to_signals_maps - 21.5s, 0.4min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub013/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub012/model/model001/BOLD/task001_run002/bold.nii.gz
_____________________________________________img_to_signals_maps - 13.3s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x99d70d0>, fwhm=5)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa0fbb10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.543665, ..., 15.881436],
...,
[ 9.142935, ..., 15.545649]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] cleaning extracted signals
______________________________________________________smooth_img - 13.3s, 0.2min
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.757417, ..., 15.403952],
...,
[ 9.738373, ..., 15.26457 ]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 77.0s, 1.3min(165, 5)
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9521b10>, fwhm=5)
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub013/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
(166, 5)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz______________________________________________________smooth_img - 38.8s, 0.6min____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] cleaning extracted signals________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943c350>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.757417, ..., 15.403952],
...,
[ 9.738373, ..., 15.26457 ]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)____________________________________________________resample_img - 71.5s, 1.2min
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling mask
(166, 5)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub013/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub014/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.335297, ..., 19.708586],
...,
[ 10.51009 , ..., 19.724671]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b55ed0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')(166, 5)
[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.541521, ..., 15.504832],
...,
[ 9.572423, ..., 15.727041]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub014/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________resample_img - 45.9s, 0.8min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub014/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
Scrambled objects vs. Words: t_stat = [-3.61773098 0.74783485 -0.59275992 ..., -1.50287515 0.50341099
-1.10382763], q-val = [ 0.00071265 0.45820813 0.55612434 ..., 0.1394224 0.61697785 0.275171 ]
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9429c10>, <nibabel.nifti1.Nifti1Image object at 0x9429e10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9521ed0>)[NiftiMapsMasker.fit_transform] resampling images to fit maps
(166, 5)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x941d150>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
_____________________________________________img_to_signals_maps - 14.1s, 0.2min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub013/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 78.9s, 1.3min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9b554d0>, <nibabel.nifti1.Nifti1Image object at 0x9b55e10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9b557d0>)[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x94139d0>, <nibabel.nifti1.Nifti1Image object at 0x9a0f250>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9a0f410>)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
_____________________________________________img_to_signals_maps - 13.3s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x945f1d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub014/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x941d190>, fwhm=5)
_____________________________________________img_to_signals_maps - 14.2s, 0.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 73.8s, 1.2min[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x946b190>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')______________________________________________________smooth_img - 24.8s, 0.4min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub015/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 77.3s, 1.3min[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x945f150>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9df9c10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x941d150>, <nibabel.nifti1.Nifti1Image object at 0x9521810>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9521950>)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub014/model/model001/BOLD/task001_run002/bold.nii.gz
______________________________________________________smooth_img - 12.3s, 0.2min___________________________________________________resample_img - 120.9s, 2.0min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub015/model/model001/BOLD/task001_run002/bold.nii.gz
_____________________________________________img_to_signals_maps - 15.5s, 0.3min
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9deef10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x945f190>, <nibabel.nifti1.Nifti1Image object at 0x945fe50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9521dd0>)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9577990>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.624405, ..., 15.572838],
...,
[ 9.760875, ..., 15.697762]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 44.0s, 0.7min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
_____________________________________________img_to_signals_maps - 13.4s, 0.2min
____________________________________________________resample_img - 45.1s, 0.8min(165, 5)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9deed10>, fwhm=5)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub015/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.541521, ..., 15.504832],
...,
[ 9.572423, ..., 15.727041]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9577550>, fwhm=5)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
______________________________________________________smooth_img - 12.3s, 0.2min
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x941d6d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
(166, 5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub016/model/model001/BOLD/task001_run002/bold.nii.gz
______________________________________________________smooth_img - 12.5s, 0.2min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub015/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________resample_img - 45.9s, 0.8min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9df9310>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9521f10>, <nibabel.nifti1.Nifti1Image object at 0x9e0b3d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9e0b750>)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x946b250>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 55.7s, 0.9min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x95771d0>, <nibabel.nifti1.Nifti1Image object at 0x9577810>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9577510>)
[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 14.2s, 0.2min[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 88.8s, 1.5min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub014/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
_____________________________________________img_to_signals_maps - 12.8s, 0.2min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x941d5d0>, <nibabel.nifti1.Nifti1Image object at 0x941d4d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x941dad0>)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.624405, ..., 15.572838],
...,
[ 9.760875, ..., 15.697762]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x945f8d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 13.4s, 0.2min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9df9fd0>, <nibabel.nifti1.Nifti1Image object at 0x9df9650>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9df9c90>)________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.521013, ..., 18.136959],
...,
[ 10.557556, ..., 18.013355]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
(165, 5)
____________________________________________________resample_img - 57.3s, 1.0min
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________________clean - 0.0s, 0.0min
_____________________________________________img_to_signals_maps - 13.0s, 0.2min(166, 5)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x945f450>, fwhm=5)[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________________clean - 0.4s, 0.0min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
______________________________________________________smooth_img - 13.7s, 0.2min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub015/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub015/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub016/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] smoothing images________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9429890>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub017/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub016/model/model001/BOLD/task001_run001/bold.nii.gz
Scrambled objects vs. Objects: t_stat = [ 5.74533912 -3.03722142 6.96055512 ..., 1.52467588 -1.47578962
1.62346741], q-val = [ 6.12571867e-07 3.85362740e-03 8.45163886e-09 ..., 1.33902263e-01
1.46530657e-01 1.11039626e-01]
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9450310>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________resample_img - 57.4s, 1.0min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9dfc350>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x941da50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 44.7s, 0.7min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9578ed0>, <nibabel.nifti1.Nifti1Image object at 0x9578790>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x941d850>)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 56.1s, 0.9min____________________________________________________resample_img - 59.5s, 1.0min
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] smoothing images
_____________________________________________img_to_signals_maps - 12.9s, 0.2min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9450850>, fwhm=5)
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub015/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x941d790>, fwhm=5)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
______________________________________________________smooth_img - 12.7s, 0.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.467268, ..., 18.01768 ],
...,
[ 10.587212, ..., 18.161113]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9cfd990>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9dfc510>, <nibabel.nifti1.Nifti1Image object at 0x9dfcd50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9dfc1d0>)______________________________________________________smooth_img - 12.0s, 0.2min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] extracting region signals
(165, 5)
____________________________________________________resample_img - 45.1s, 0.8min_____________________________________________img_to_signals_maps - 13.4s, 0.2min[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9450310>, <nibabel.nifti1.Nifti1Image object at 0x946b890>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x946b250>)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub016/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9cfdc10>, fwhm=5)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 13.4s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9578050>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.228777, ..., 14.816315],
...,
[ 10.304886, ..., 14.770992]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] resampling mask
______________________________________________________smooth_img - 12.2s, 0.2min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 83.6s, 1.4min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub016/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
(165, 5)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.342038, ..., 14.95414 ],
...,
[ 10.40973 , ..., 14.861308]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub018/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
(166, 5)
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x94296d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9cfd750>, <nibabel.nifti1.Nifti1Image object at 0x9cfd510>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9cfd6d0>)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9df02d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c65a90>, <nibabel.nifti1.Nifti1Image object at 0x95782d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9578ad0>)____________________________________________________resample_img - 43.5s, 0.7min_____________________________________________img_to_signals_maps - 13.0s, 0.2min____________________________________________________resample_img - 55.4s, 0.9min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub016/model/model001/BOLD/task001_run002/bold.nii.gz
_____________________________________________img_to_signals_maps - 13.2s, 0.2min[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9429490>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.467268, ..., 18.01768 ],
...,
[ 10.587212, ..., 18.161113]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x941d650>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub017/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
______________________________________________________smooth_img - 15.9s, 0.3min(165, 5)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9dfcf90>, <nibabel.nifti1.Nifti1Image object at 0x9dfc9d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9dfcf50>)____________________________________________________resample_img - 73.8s, 1.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9450d90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 13.2s, 0.2min[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 49.2s, 0.8min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub017/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x94296d0>, <nibabel.nifti1.Nifti1Image object at 0x9429c90>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9429b90>)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa0fb390>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')_____________________________________________img_to_signals_maps - 12.9s, 0.2min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub015/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9450a90>, <nibabel.nifti1.Nifti1Image object at 0x94502d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9450910>)____________________________________________________resample_img - 59.8s, 1.0min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.228777, ..., 14.816315],
...,
[ 10.304886, ..., 14.770992]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub018/model/model001/BOLD/task001_run002/bold.nii.gz
_____________________________________________img_to_signals_maps - 18.3s, 0.3min[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9cfdf50>, fwhm=5)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals(165, 5)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9df0b50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub017/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________________clean - 0.0s, 0.0min
______________________________________________________smooth_img - 55.7s, 0.9min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9578a10>, <nibabel.nifti1.Nifti1Image object at 0x9578750>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9578f10>)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 67.4s, 1.1min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x99d7dd0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals
_____________________________________________img_to_signals_maps - 22.1s, 0.4min
[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 52.8s, 0.9min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
Consonant strings vs. Words: t_stat = [-3.59688752 -0.39002894 -1.28588759 ..., -1.38050372 0.68795319
-1.17466764], q-val = [ 0.00075903 0.69824056 0.20465109 ..., 0.17382679 0.49479354
0.24592241][NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub018/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub016/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.521013, ..., 18.136959],
...,
[ 10.557556, ..., 18.013355]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] cleaning extracted signals________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x99d7150>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x941a050>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9449a90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
(166, 5)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.81959 , ..., 14.613187],
...,
[ 10.826439, ..., 14.213612]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)______________________________________________________smooth_img - 12.1s, 0.2min____________________________________________________resample_img - 44.2s, 0.7min[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 64.8s, 1.1min____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub017/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
(166, 5)
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x941ad50>, fwhm=5)[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
______________________________________________________smooth_img - 12.6s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0xa0fb050>, fwhm=5)[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub016/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals______________________________________________________smooth_img - 24.7s, 0.4min________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.342038, ..., 14.95414 ],
...,
[ 10.40973 , ..., 14.861308]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub019/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x941a790>, <nibabel.nifti1.Nifti1Image object at 0x941a350>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9450d50>)[NiftiMapsMasker.fit_transform] extracting region signals(166, 5)
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9435990>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9dff410>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub018/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
_____________________________________________img_to_signals_maps - 13.6s, 0.2min[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
______________________________________________________smooth_img - 41.2s, 0.7min____________________________________________________resample_img - 55.2s, 0.9min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x99d7a50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.075695, ..., 11.659736],
...,
[ 8.16197 , ..., 11.706861]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 44.4s, 0.7min________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.886925, ..., 14.623773],
...,
[ 10.862911, ..., 14.591821]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
(166, 5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub017/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
(165, 5)
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9dff0d0>, <nibabel.nifti1.Nifti1Image object at 0x9df0fd0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9df0ed0>)________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x99d7790>, fwhm=5)____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9449550>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)_____________________________________________img_to_signals_maps - 24.5s, 0.4min______________________________________________________smooth_img - 12.1s, 0.2min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 60.3s, 1.0min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub018/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub017/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub018/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x99d7650>, <nibabel.nifti1.Nifti1Image object at 0x99d7b10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x99d7250>)[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa0f1610>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9449790>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x945e250>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x941a890>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
_____________________________________________img_to_signals_maps - 12.9s, 0.2min
____________________________________________________resample_img - 63.2s, 1.1min______________________________________________________smooth_img - 12.4s, 0.2min____________________________________________________resample_img - 44.7s, 0.7min[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 49.8s, 0.8min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub020/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.81959 , ..., 14.613187],
...,
[ 10.826439, ..., 14.213612]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9435e50>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9dffc90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x946a250>, <nibabel.nifti1.Nifti1Image object at 0x9449290>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x94492d0>)
(166, 5)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
______________________________________________________smooth_img - 14.1s, 0.2min____________________________________________________resample_img - 74.2s, 1.2min____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x941ac90>, <nibabel.nifti1.Nifti1Image object at 0x941af10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x941abd0>)
_____________________________________________img_to_signals_maps - 13.1s, 0.2min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.886925, ..., 14.623773],
...,
[ 10.862911, ..., 14.591821]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)_____________________________________________img_to_signals_maps - 14.3s, 0.2min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
(165, 5)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.075695, ..., 11.659736],
...,
[ 8.16197 , ..., 11.706861]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9435d10>, <nibabel.nifti1.Nifti1Image object at 0x9435dd0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9435fd0>)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub019/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
(166, 5)
_____________________________________________img_to_signals_maps - 13.9s, 0.2min[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9a0f850>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
Consonant strings vs. Objects: t_stat = [ 3.18126334 -4.53597375 7.00130759 ..., 0.54050602 -1.4077164
0.95549354], q-val = [ 2.57073653e-03 3.83610359e-05 7.31925130e-09 ..., 5.91347496e-01
1.65658547e-01 3.44115799e-01][NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.060806, ..., 11.551971],
...,
[ 8.181433, ..., 11.709225]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 68.1s, 1.1min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub019/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub019/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
(165, 5)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa0f1d90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub018/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________________clean - 0.1s, 0.0min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub021/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x945c690>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________resample_img - 67.0s, 1.1min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9467510>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9449210>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9a0f8d0>, <nibabel.nifti1.Nifti1Image object at 0x9a0f2d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x99d76d0>)____________________________________________________resample_img - 44.9s, 0.7min
[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 44.5s, 0.7min[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 59.6s, 1.0min_____________________________________________img_to_signals_maps - 12.8s, 0.2min[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0xa0f1c50>, fwhm=5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub017/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x945c910>, fwhm=5)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
______________________________________________________smooth_img - 12.1s, 0.2min[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x945d850>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
______________________________________________________smooth_img - 12.1s, 0.2min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9449cd0>, <nibabel.nifti1.Nifti1Image object at 0x9449690>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9449710>)____________________________________________________resample_img - 65.0s, 1.1min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals_____________________________________________img_to_signals_maps - 13.9s, 0.2min[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.890009, ..., 12.392979],
...,
[ 9.973113, ..., 12.468269]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub020/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x945c450>, <nibabel.nifti1.Nifti1Image object at 0x945c210>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x945c3d0>)
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x945dad0>, fwhm=5)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
(165, 5)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x944c350>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')_____________________________________________img_to_signals_maps - 13.3s, 0.2min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
______________________________________________________smooth_img - 12.8s, 0.2min____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 45.4s, 0.8min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.003004, ..., 12.827704],
...,
[ 9.027971, ..., 12.805913]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub020/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub019/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9a0f690>, fwhm=5)(166, 5)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x941df90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub022/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9467890>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
______________________________________________________smooth_img - 34.1s, 0.6min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 50.3s, 0.8min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9449d90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
____________________________________________________resample_img - 44.6s, 0.7min
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 44.8s, 0.7min
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x941d090>, fwhm=5)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub018/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub020/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9467d90>, fwhm=5)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
______________________________________________________smooth_img - 12.1s, 0.2min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x94498d0>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.797445, ..., 16.34758 ],
...,
[ 8.880531, ..., 16.472191]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x945cc90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
______________________________________________________smooth_img - 14.8s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9cfdb50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] extracting region signals
______________________________________________________smooth_img - 14.1s, 0.2min(165, 5)
____________________________________________________resample_img - 66.9s, 1.1min
[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________resample_img - 65.3s, 1.1min
____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x941d550>, <nibabel.nifti1.Nifti1Image object at 0x941dd10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x941d8d0>)
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9467610>, <nibabel.nifti1.Nifti1Image object at 0x9467810>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9467850>)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
_____________________________________________img_to_signals_maps - 12.9s, 0.2min
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9521f90>, <nibabel.nifti1.Nifti1Image object at 0x9449950>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9449710>)
[NiftiMapsMasker.fit_transform] extracting region signals
_____________________________________________img_to_signals_maps - 16.7s, 0.3min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9cfd850>, <nibabel.nifti1.Nifti1Image object at 0x945d050>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x945db90>)_____________________________________________img_to_signals_maps - 13.1s, 0.2min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub020/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9521c10>, <nibabel.nifti1.Nifti1Image object at 0x945c290>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x945c9d0>)________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.797445, ..., 16.34758 ],
...,
[ 8.880531, ..., 16.472191]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.093659, ..., 12.922977],
...,
[ 9.064177, ..., 12.835486]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)_____________________________________________img_to_signals_maps - 13.0s, 0.2min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images_____________________________________________img_to_signals_maps - 13.2s, 0.2min(165, 5)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.294551, ..., 16.733308],
...,
[ 10.361443, ..., 16.917389]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
____________________________________________________________clean - 0.0s, 0.0min
(165, 5)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x944c850>, fwhm=5)
Consonant strings vs. Scrambled objects: t_stat = [-1.61830431 -1.1133798 -0.94202667 ..., -0.40833206 0.53661709
-0.18325607], q-val = [ 0.11215028 0.27108991 0.35089621 ..., 0.68484581 0.59401071
0.85536901][NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________________clean - 0.2s, 0.0min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
(165, 5)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________________clean - 0.0s, 0.0min
______________________________________________________smooth_img - 41.7s, 0.7min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub020/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub019/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub021/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling images to fit maps________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9521bd0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub019/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub022/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.00486 , ..., 16.954592],
...,
[ 9.143734, ..., 16.998998]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943c090>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________resample_img - 67.3s, 1.1min
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x94290d0>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9449590>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b6ea90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
(166, 5)
____________________________________________________resample_img - 44.3s, 0.7min[NiftiMapsMasker.fit_transform] smoothing images
______________________________________________________smooth_img - 31.0s, 0.5min____________________________________________________resample_img - 44.0s, 0.7min____________________________________________________________clean - 2.8s, 0.0min
[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________resample_img - 45.1s, 0.8min
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x943c890>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9521810>, <nibabel.nifti1.Nifti1Image object at 0x941db50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x941d490>)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] cleaning extracted signals
______________________________________________________smooth_img - 12.1s, 0.2min_____________________________________________img_to_signals_maps - 13.0s, 0.2min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9449750>, <nibabel.nifti1.Nifti1Image object at 0x9449ed0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9449610>)[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x94295d0>, <nibabel.nifti1.Nifti1Image object at 0x9467c10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9467f50>)________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.093659, ..., 12.922977],
...,
[ 9.064177, ..., 12.835486]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub021/model/model001/BOLD/task001_run002/bold.nii.gz[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] cleaning extracted signals
_____________________________________________img_to_signals_maps - 13.8s, 0.2min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 13.4s, 0.2min(165, 5)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x943c7d0>, <nibabel.nifti1.Nifti1Image object at 0x943cf90>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x946b750>)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9521f10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 13.4s, 0.2min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 45.0s, 0.7min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub021/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.890009, ..., 12.392979],
...,
[ 9.973113, ..., 12.468269]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9622290>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub019/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub023/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x1b94e10>, fwhm=5)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
(165, 5)
____________________________________________________resample_img - 44.6s, 0.7min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub020/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x945f790>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x94299d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')______________________________________________________smooth_img - 12.2s, 0.2min____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 62.3s, 1.0min____________________________________________________resample_img - 55.8s, 0.9min[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9e0ba90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9521bd0>, <nibabel.nifti1.Nifti1Image object at 0x944cf10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x944c790>)[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0xa0f1a50>, <nibabel.nifti1.Nifti1Image object at 0xa0f1f10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa0f1510>)____________________________________________________resample_img - 45.0s, 0.7min[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub021/model/model001/BOLD/task001_run002/bold.nii.gz
_____________________________________________img_to_signals_maps - 12.9s, 0.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps
_____________________________________________img_to_signals_maps - 12.8s, 0.2min[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x1e99350>, <nibabel.nifti1.Nifti1Image object at 0x9429cd0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9429a90>)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943cf50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9deea90>, fwhm=5)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.003004, ..., 12.827704],
...,
[ 9.027971, ..., 12.805913]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)_____________________________________________img_to_signals_maps - 14.3s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.924161, ..., 12.378417],
...,
[ 10.003869, ..., 12.504107]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)____________________________________________________resample_img - 46.2s, 0.8min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
______________________________________________________smooth_img - 12.1s, 0.2min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
(166, 5)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
(166, 5)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________________clean - 1.0s, 0.0min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub022/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9deed10>, <nibabel.nifti1.Nifti1Image object at 0x9deeb10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9deee90>)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9453b10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')_____________________________________________img_to_signals_maps - 12.6s, 0.2min
Objects vs. Words: t_stat = [-4.66309931 3.53198926 -5.34249658 ..., 0.99740633 4.10312082
-6.23704713], q-val = [ 2.51313091e-05 9.22661425e-04 2.48792833e-06 ..., 3.23569053e-01
1.57061036e-04 1.08809435e-07][NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub024/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.924161, ..., 12.378417],
...,
[ 10.003869, ..., 12.504107]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub022/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________resample_img - 89.4s, 1.5min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub020/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9523290>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling images to fit maps
(166, 5)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.00486 , ..., 16.954592],
...,
[ 9.143734, ..., 16.998998]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9577290>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________________clean - 8.1s, 0.1min[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x945fa90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________resample_img - 86.8s, 1.4min
[NiftiMapsMasker.fit_transform] extracting region signals(166, 5)
____________________________________________________resample_img - 69.9s, 1.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
____________________________________________________resample_img - 71.9s, 1.2min[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.294551, ..., 16.733308],
...,
[ 10.361443, ..., 16.917389]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x7f80b0350810>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x7f80b0350750>, <nibabel.nifti1.Nifti1Image object at 0x9429050>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9429190>)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub022/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps(165, 5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub021/model/model001/BOLD/task001_run001/bold.nii.gz
______________________________________________________smooth_img - 11.9s, 0.2min_____________________________________________img_to_signals_maps - 15.3s, 0.3min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x7f80b0350950>, <nibabel.nifti1.Nifti1Image object at 0x9577210>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9577d90>)
____________________________________________________________clean - 0.2s, 0.0min[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x99fea90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9e0b3d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] cleaning extracted signals
_____________________________________________img_to_signals_maps - 14.8s, 0.2min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 44.0s, 0.7min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 50.0s, 0.8min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.00486 , ..., 16.954592],
...,
[ 9.143734, ..., 16.998998]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x99fed10>, fwhm=5)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub023/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
(166, 5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub025/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
______________________________________________________smooth_img - 12.4s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c6a3d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9e0b7d0>, <nibabel.nifti1.Nifti1Image object at 0x9e0b050>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9e0b9d0>)____________________________________________________________clean - 3.6s, 0.1min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub023/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9dff090>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________resample_img - 47.1s, 0.8min_____________________________________________img_to_signals_maps - 13.5s, 0.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 44.1s, 0.7min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x99d7950>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x99fecd0>, <nibabel.nifti1.Nifti1Image object at 0x99fedd0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943c750>)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 45.9s, 0.8min_____________________________________________img_to_signals_maps - 13.3s, 0.2min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub021/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9dffdd0>, fwhm=5)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c6a090>, <nibabel.nifti1.Nifti1Image object at 0x9453f90>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x94537d0>)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9412a50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')______________________________________________________smooth_img - 11.9s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x99d7690>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.273415, ..., 16.801925],
...,
[ 10.362108, ..., 16.977793]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)_____________________________________________img_to_signals_maps - 14.4s, 0.2min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub021/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________resample_img - 63.0s, 1.0min[NiftiMapsMasker.fit_transform] extracting region signals______________________________________________________smooth_img - 15.4s, 0.3min(166, 5)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b55810>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9dffa50>, <nibabel.nifti1.Nifti1Image object at 0x9dff250>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9523090>)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 56.8s, 0.9min[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
_____________________________________________img_to_signals_maps - 12.5s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x99d7e50>, <nibabel.nifti1.Nifti1Image object at 0x99d79d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x99d7b50>)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub024/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
_____________________________________________img_to_signals_maps - 13.1s, 0.2min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub023/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.452554, ..., 14.097884],
...,
[ 10.450731, ..., 14.185061]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c6ac50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x945cb50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)(165, 5)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 11.020386, ..., 15.494692],
...,
[ 11.060833, ..., 15.788664]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
____________________________________________________resample_img - 43.6s, 0.7min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
____________________________________________________resample_img - 51.1s, 0.9min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
(165, 5)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub022/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9c6aed0>, fwhm=5)
Scrambled objects vs. Words: t_stat = [-2.80517015 1.15944823 -3.12485965 ..., -0.15157082 1.66756331
-2.16098107], q-val = [ 0.00724076 0.2520088 0.00301585 ..., 0.88016071 0.10191468
0.03571634][NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub022/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x945d250>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
______________________________________________________smooth_img - 29.2s, 0.5min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub025/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x945ccd0>, <nibabel.nifti1.Nifti1Image object at 0x945c110>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x99fee10>)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9467190>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________resample_img - 72.4s, 1.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa2c4710>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub023/model/model001/BOLD/task001_run002/bold.nii.gz
_____________________________________________img_to_signals_maps - 14.6s, 0.2min
____________________________________________________resample_img - 72.5s, 1.2min[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c6aa10>, <nibabel.nifti1.Nifti1Image object at 0x9c6a7d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9c6a990>)
____________________________________________________resample_img - 68.7s, 1.1min[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 12.9s, 0.2min[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x99d7c50>, fwhm=5)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9ceab50>, <nibabel.nifti1.Nifti1Image object at 0x9cea550>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9412c50>)[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9467a90>, <nibabel.nifti1.Nifti1Image object at 0x9b55a90>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9b55310>)
______________________________________________________smooth_img - 41.7s, 0.7min[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.25059 , ..., 11.06327 ],
...,
[ 10.130823, ..., 10.84299 ]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
_____________________________________________img_to_signals_maps - 13.1s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0xa2c46d0>, <nibabel.nifti1.Nifti1Image object at 0xa2c4490>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9dffc90>)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub023/model/model001/BOLD/task001_run002/bold.nii.gz
_____________________________________________img_to_signals_maps - 13.3s, 0.2min
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
(165, 5)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
_____________________________________________img_to_signals_maps - 14.5s, 0.2min
[NiftiMapsMasker.fit_transform] smoothing images____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9614450>, fwhm=5)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 11.240497, ..., 15.638734],
...,
[ 11.086465, ..., 15.852156]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
______________________________________________________smooth_img - 73.1s, 1.2min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub022/model/model001/BOLD/task001_run002/bold.nii.gz
(166, 5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub024/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub023/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x945de90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub026/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c9b290>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9466190>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________resample_img - 56.6s, 0.9min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa2c90d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
____________________________________________________resample_img - 56.6s, 0.9min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 45.0s, 0.7min[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 53.2s, 0.9min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub024/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x944c5d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9467550>, fwhm=5)[NiftiMapsMasker.fit_transform] cleaning extracted signals________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0xa2c4bd0>, fwhm=5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub024/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c6a850>, <nibabel.nifti1.Nifti1Image object at 0x9c6aa90>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9c6af10>)
____________________________________________________resample_img - 57.9s, 1.0min[NiftiMapsMasker.fit_transform] resampling images to fit maps
______________________________________________________smooth_img - 12.7s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.273415, ..., 16.801925],
...,
[ 10.362108, ..., 16.977793]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)______________________________________________________smooth_img - 14.1s, 0.2min
_____________________________________________img_to_signals_maps - 13.4s, 0.2min
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9614dd0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] extracting region signals(166, 5)
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________________clean - 2.8s, 0.0min
____________________________________________________resample_img - 44.4s, 0.7min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9467650>, <nibabel.nifti1.Nifti1Image object at 0x9467750>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x94675d0>)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0xa2c4fd0>, <nibabel.nifti1.Nifti1Image object at 0xa2c4cd0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa2c4e90>)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x944c9d0>, <nibabel.nifti1.Nifti1Image object at 0x944c7d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x99d7b10>)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
_____________________________________________img_to_signals_maps - 13.5s, 0.2min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)_____________________________________________img_to_signals_maps - 13.5s, 0.2min_____________________________________________img_to_signals_maps - 15.2s, 0.3min________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9614c90>, fwhm=5)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub025/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
______________________________________________________smooth_img - 12.6s, 0.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 11.240497, ..., 15.638734],
...,
[ 11.086465, ..., 15.852156]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub023/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.131655, ..., 14.774193],
...,
[ 10.185553, ..., 14.797346]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943cc50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals
(166, 5)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa085750>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')(166, 5)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
____________________________________________________resample_img - 47.2s, 0.8min____________________________________________________________clean - 0.0s, 0.0min
____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9614b90>, <nibabel.nifti1.Nifti1Image object at 0x9614950>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9614b10>)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 91.2s, 1.5min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz[NiftiMapsMasker.fit_transform] resampling mask
Scrambled objects vs. Objects: t_stat = [ 3.18991045 -2.40313413 3.74214336 ..., -1.41073654 -3.12828974
5.99481366], q-val = [ 2.50823755e-03 2.01685304e-02 4.87463152e-04 ..., 1.64770680e-01
2.98683077e-03 2.55346851e-07]
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub025/model/model001/BOLD/task001_run001/bold.nii.gz
_____________________________________________img_to_signals_maps - 14.4s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x943ced0>, fwhm=5)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943e350>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] cleaning extracted signals
______________________________________________________smooth_img - 13.4s, 0.2min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub024/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.292175, ..., 11.069734],
...,
[ 10.19984 , ..., 10.971797]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0xa085710>, <nibabel.nifti1.Nifti1Image object at 0xa0852d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa085490>)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub027/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________resample_img - 81.3s, 1.4min
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x94497d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] resampling images to fit maps
(166, 5)
_____________________________________________img_to_signals_maps - 12.9s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa2c4750>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x943ca10>, <nibabel.nifti1.Nifti1Image object at 0x943c7d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943c990>)____________________________________________________resample_img - 74.7s, 1.2min
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 44.8s, 0.7min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)_____________________________________________img_to_signals_maps - 13.7s, 0.2min[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x944cfd0>, <nibabel.nifti1.Nifti1Image object at 0x944c350>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x944cb90>)
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 13.6s, 0.2min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub025/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.362343, ..., 13.501881],
...,
[ 10.285949, ..., 13.641755]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9449790>, <nibabel.nifti1.Nifti1Image object at 0x9449350>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9449510>)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x944d410>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')(166, 5)
_____________________________________________img_to_signals_maps - 15.3s, 0.3min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub024/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.068286, ..., 16.906172],
...,
[ 9.106794, ..., 17.067794]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 73.8s, 1.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa085e90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
(166, 5)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 46.0s, 0.8min___________________________________________________________clean - 22.9s, 0.4min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub025/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub026/model/model001/BOLD/task001_run001/bold.nii.gz[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub024/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x943e4d0>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.452554, ..., 14.097884],
...,
[ 10.450731, ..., 14.185061]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x7f80b0350050>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b7e190>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0xa085e50>, <nibabel.nifti1.Nifti1Image object at 0xa085b50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa085d10>)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub028/model/model001/BOLD/task001_run001/bold.nii.gz
______________________________________________________smooth_img - 36.8s, 0.6min(165, 5)
____________________________________________________resample_img - 55.1s, 0.9min____________________________________________________resample_img - 81.3s, 1.4min_____________________________________________img_to_signals_maps - 14.5s, 0.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9429410>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 44.3s, 0.7min
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x7f80b0350950>, <nibabel.nifti1.Nifti1Image object at 0x943ca90>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943cf10>)[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.362343, ..., 13.501881],
...,
[ 10.285949, ..., 13.641755]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub026/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
_____________________________________________img_to_signals_maps - 12.9s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.292175, ..., 11.069734],
...,
[ 10.19984 , ..., 10.971797]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9429cd0>, fwhm=5)(166, 5)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x944dc90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub025/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
(166, 5)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
______________________________________________________smooth_img - 12.5s, 0.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 56.4s, 0.9min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa085790>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 49.8s, 0.8min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9521f50>, <nibabel.nifti1.Nifti1Image object at 0x9429e10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9429b10>)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub026/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub027/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x944dc50>, <nibabel.nifti1.Nifti1Image object at 0x944d810>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x944d9d0>)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub025/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 12.8s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x944d490>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x941d050>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling images to fit maps
_____________________________________________img_to_signals_maps - 13.5s, 0.2min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b8ba50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0xa0850d0>, <nibabel.nifti1.Nifti1Image object at 0xa085590>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa085910>)
Consonant strings vs. Words: t_stat = [ 1.19051856 -0.70080199 0.56409909 ..., 0.37048438 -0.13152272
-0.06615252], q-val = [ 0.23969722 0.48681008 0.57531314 ..., 0.71265155 0.89591156
0.94753117][NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 54.9s, 0.9min
____________________________________________________resample_img - 44.8s, 0.7min
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.901626, ..., 15.690785],
...,
[ 8.871776, ..., 15.311613]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 67.7s, 1.1min_____________________________________________img_to_signals_maps - 13.9s, 0.2min
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz[NiftiMapsMasker.fit_transform] smoothing images
(165, 5)
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x941d750>, fwhm=5)[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
______________________________________________________smooth_img - 12.2s, 0.2min[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.250751, ..., 15.049896],
...,
[ 10.162163, ..., 14.743852]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub026/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9b8b710>, <nibabel.nifti1.Nifti1Image object at 0x9b8b5d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9b8b790>)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub026/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub028/model/model001/BOLD/task001_run002/bold.nii.gz
(165, 5)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x99fef90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x941d690>, <nibabel.nifti1.Nifti1Image object at 0x941d3d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x941dad0>)_____________________________________________img_to_signals_maps - 13.3s, 0.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9429990>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 44.5s, 0.7min_____________________________________________img_to_signals_maps - 13.0s, 0.2min[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9521950>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 65.8s, 1.1min
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 45.0s, 0.8min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.068286, ..., 16.906172],
...,
[ 9.106794, ..., 17.067794]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub027/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x99fed10>, <nibabel.nifti1.Nifti1Image object at 0x1e99390>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x1b94e10>)(166, 5)
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9cea610>, fwhm=5)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x944dbd0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub026/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
_____________________________________________img_to_signals_maps - 14.3s, 0.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
______________________________________________________smooth_img - 17.6s, 0.3min
____________________________________________________resample_img - 68.8s, 1.1min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b55910>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.798385, ..., 15.382298],
...,
[ 8.836001, ..., 15.444913]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 56.4s, 0.9min
(166, 5)
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub027/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9523290>, <nibabel.nifti1.Nifti1Image object at 0x7f80b0350750>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9cea7d0>)____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x944db90>, <nibabel.nifti1.Nifti1Image object at 0x944d750>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x944d910>)[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa0f17d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 13.3s, 0.2min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub027/model/model001/BOLD/task001_run002/bold.nii.gz
_____________________________________________img_to_signals_maps - 12.8s, 0.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________resample_img - 62.3s, 1.0min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9b55350>, <nibabel.nifti1.Nifti1Image object at 0x9b55550>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x1e99350>)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x946b290>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.250751, ..., 15.049896],
...,
[ 10.162163, ..., 14.743852]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub029/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
_____________________________________________img_to_signals_maps - 13.5s, 0.2min
[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz____________________________________________________resample_img - 77.2s, 1.3min________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x941da90>, fwhm=5)
(165, 5)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9449650>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images
______________________________________________________smooth_img - 24.8s, 0.4min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x946b450>, fwhm=5)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 49.6s, 0.8min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub027/model/model001/BOLD/task001_run002/bold.nii.gz
______________________________________________________smooth_img - 12.3s, 0.2min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub027/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub026/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9449710>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9413c50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.069631, ..., 16.96932 ],
...,
[ 9.006393, ..., 16.84654 ]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9deebd0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x945f6d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')______________________________________________________smooth_img - 12.5s, 0.2min____________________________________________________resample_img - 60.0s, 1.0min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x946b0d0>, <nibabel.nifti1.Nifti1Image object at 0x946bd10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943cbd0>)
(165, 5)
____________________________________________________resample_img - 80.7s, 1.3min____________________________________________________resample_img - 46.7s, 0.8min[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
_____________________________________________img_to_signals_maps - 13.1s, 0.2min____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9449650>, <nibabel.nifti1.Nifti1Image object at 0x94498d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9449790>)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
Consonant strings vs. Objects: t_stat = [ 5.34563952 -3.51272075 5.48233192 ..., -0.44646387 -4.83230244
7.11317973], q-val = [ 2.46104337e-06 9.77407498e-04 1.53248408e-06 ..., 6.57269985e-01
1.42365718e-05 4.93238517e-09][NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x94139d0>, <nibabel.nifti1.Nifti1Image object at 0x1e99190>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x99ffe90>)________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.069631, ..., 16.96932 ],
...,
[ 9.006393, ..., 16.84654 ]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
_____________________________________________img_to_signals_maps - 12.9s, 0.2min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x7f80b0346950>, <nibabel.nifti1.Nifti1Image object at 0x9521d90>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9521e50>)
_____________________________________________img_to_signals_maps - 13.5s, 0.2min(165, 5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub028/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________________clean - 0.1s, 0.0min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 13.9s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.047342, ..., 19.654638],
...,
[ 10.081475, ..., 19.733337]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa0f1b50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
(165, 5)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
____________________________________________________resample_img - 65.9s, 1.1min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub028/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub028/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub028/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9429090>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9413910>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub027/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9577e10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] cleaning extracted signals____________________________________________________resample_img - 44.5s, 0.7min[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub030/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________resample_img - 50.7s, 0.8min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________resample_img - 65.5s, 1.1min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9429a50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9df9cd0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals
____________________________________________________resample_img - 78.1s, 1.3min____________________________________________________resample_img - 56.0s, 0.9min[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9429890>, <nibabel.nifti1.Nifti1Image object at 0x9429810>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9deee10>)
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub029/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x95775d0>, <nibabel.nifti1.Nifti1Image object at 0x9577c50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x99d7510>)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
_____________________________________________img_to_signals_maps - 13.0s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x945f0d0>, fwhm=5)[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.901626, ..., 15.690785],
...,
[ 8.871776, ..., 15.311613]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943c5d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
_____________________________________________img_to_signals_maps - 13.2s, 0.2min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
______________________________________________________smooth_img - 18.8s, 0.3min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9449410>, <nibabel.nifti1.Nifti1Image object at 0x9449f50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9449c50>)
(165, 5)
____________________________________________________resample_img - 67.2s, 1.1min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 19.3s, 0.3min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9429a50>, <nibabel.nifti1.Nifti1Image object at 0x945f750>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x945f450>)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub028/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x943c1d0>, <nibabel.nifti1.Nifti1Image object at 0x943c4d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa0f1a90>)[NiftiMapsMasker.fit_transform] resampling images to fit maps
_____________________________________________img_to_signals_maps - 13.2s, 0.2min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub029/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub029/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x94297d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps_____________________________________________img_to_signals_maps - 13.0s, 0.2min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 64.6s, 1.1min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub031/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x944da10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x95774d0>, fwhm=5)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9dff390>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
____________________________________________________resample_img - 43.8s, 0.7min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
______________________________________________________smooth_img - 37.5s, 0.6min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub028/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________resample_img - 44.8s, 0.7min
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9413d50>, fwhm=5)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub030/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x94290d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9df9fd0>, fwhm=5)[NiftiMapsMasker.fit_transform] cleaning extracted signals______________________________________________________smooth_img - 12.0s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c9b3d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 44.3s, 0.7min
______________________________________________________smooth_img - 13.7s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.10358 , ..., 18.884174],
...,
[ 10.153623, ..., 19.503935]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________resample_img - 44.0s, 0.7min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub029/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9429050>, fwhm=5)[NiftiMapsMasker.fit_transform] extracting region signals(166, 5)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9413950>, <nibabel.nifti1.Nifti1Image object at 0x9413c10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9413ad0>)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________________clean - 0.0s, 0.0min
Consonant strings vs. Scrambled objects: t_stat = [ 2.50222397 -1.81112837 2.93919233 ..., 0.59355116 -1.71404386
1.52417093], q-val = [ 0.01580192 0.07638122 0.00504692 ..., 0.5555992 0.09297222
0.13402812]
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9c9b650>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b8b850>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')______________________________________________________smooth_img - 12.0s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9df9310>, <nibabel.nifti1.Nifti1Image object at 0x9df98d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9df9250>)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 12.6s, 0.2min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
______________________________________________________smooth_img - 12.7s, 0.2min____________________________________________________resample_img - 49.8s, 0.8min[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 14.5s, 0.2min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.10358 , ..., 18.884174],
...,
[ 10.153623, ..., 19.503935]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9429b50>, <nibabel.nifti1.Nifti1Image object at 0x94296d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9429610>)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub029/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9b8bd90>, fwhm=5)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.948946, ..., 16.094844],
...,
[ 9.956578, ..., 16.159495]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] resampling images to fit maps
(166, 5)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c9b3d0>, <nibabel.nifti1.Nifti1Image object at 0x943c050>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943c350>)
_____________________________________________img_to_signals_maps - 12.9s, 0.2min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x944d950>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________________clean - 0.0s, 0.0min
______________________________________________________smooth_img - 37.8s, 0.6min
(166, 5)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 13.5s, 0.2min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________________clean - 0.0s, 0.0min
____________________________________________________resample_img - 62.7s, 1.0min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.798385, ..., 15.382298],
...,
[ 8.836001, ..., 15.444913]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.808184, ..., 16.726813],
...,
[ 9.824864, ..., 16.773839]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] cleaning extracted signals(166, 5)
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub029/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
(165, 5)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.047342, ..., 19.654638],
...,
[ 10.081475, ..., 19.733337]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub031/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9577b10>, <nibabel.nifti1.Nifti1Image object at 0x9577750>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9577e50>)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x944d9d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
(165, 5)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9dff550>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')_____________________________________________img_to_signals_maps - 16.6s, 0.3min____________________________________________________resample_img - 67.6s, 1.1min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub029/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________resample_img - 56.6s, 0.9min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub030/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9cfde90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x944d710>, <nibabel.nifti1.Nifti1Image object at 0x944d1d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x944d5d0>)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c9b9d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub030/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________resample_img - 76.4s, 1.3min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9dffb90>, <nibabel.nifti1.Nifti1Image object at 0x9dff450>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9dff310>)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub030/model/model001/BOLD/task001_run002/bold.nii.gz
_____________________________________________img_to_signals_maps - 13.8s, 0.2min____________________________________________________resample_img - 56.2s, 0.9min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b8bed0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 13.3s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x944d350>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 57.9s, 1.0min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9429090>, <nibabel.nifti1.Nifti1Image object at 0x9429d90>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9429490>)[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 50.6s, 0.8min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c9b990>, <nibabel.nifti1.Nifti1Image object at 0x9c9b110>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9c9b710>)[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 14.1s, 0.2min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub030/model/model001/BOLD/task001_run002/bold.nii.gz
_____________________________________________img_to_signals_maps - 13.3s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9b8be90>, <nibabel.nifti1.Nifti1Image object at 0x9b8b710>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9b8be50>)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub032/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x944d450>, <nibabel.nifti1.Nifti1Image object at 0x944db90>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x944d910>)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x941f550>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] cleaning extracted signals
_____________________________________________img_to_signals_maps - 13.9s, 0.2min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa2d1790>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')_____________________________________________img_to_signals_maps - 13.3s, 0.2min____________________________________________________resample_img - 53.0s, 0.9min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub030/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________resample_img - 76.3s, 1.3min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x941f7d0>, fwhm=5)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub031/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9cfd350>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
______________________________________________________smooth_img - 12.4s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c7f3d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub031/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________resample_img - 54.5s, 0.9min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0xa2d1750>, <nibabel.nifti1.Nifti1Image object at 0xa2d12d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa2d1490>)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub031/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________resample_img - 45.5s, 0.8min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b6da50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals
Objects vs. Words: t_stat = [ 5.7928603 -4.66773851 5.04269577 ..., 2.1295136 -2.3332621
2.32702791], q-val = [ 5.18699832e-07 2.47447272e-05 6.96949014e-06 ..., 3.83675007e-02
2.38714534e-02 2.42297307e-02]_____________________________________________img_to_signals_maps - 13.8s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x946c5d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x941f310>, <nibabel.nifti1.Nifti1Image object at 0x941f050>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x944de10>)[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 58.9s, 1.0min
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9c7f650>, fwhm=5)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9cfd750>, <nibabel.nifti1.Nifti1Image object at 0x9cfd990>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9cfd6d0>)[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 57.1s, 1.0min_____________________________________________img_to_signals_maps - 13.6s, 0.2min
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
______________________________________________________smooth_img - 12.5s, 0.2min[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 14.3s, 0.2min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.884154, ..., 16.860847],
...,
[ 9.847026, ..., 16.817871]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9b6da10>, <nibabel.nifti1.Nifti1Image object at 0x9b6d5d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9b6d790>)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub033/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals(166, 5)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c7f3d0>, <nibabel.nifti1.Nifti1Image object at 0x9c9bf90>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9c9b690>)_____________________________________________img_to_signals_maps - 13.5s, 0.2min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.948946, ..., 16.094844],
...,
[ 9.956578, ..., 16.159495]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 13.3s, 0.2min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa2d1d90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub030/model/model001/BOLD/task001_run002/bold.nii.gz
(166, 5)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________resample_img - 58.0s, 1.0min____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.932576, ..., 15.940955],
...,
[ 9.954786, ..., 16.070925]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa099610>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub031/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
(165, 5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub031/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________resample_img - 56.4s, 0.9min[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x941fb50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9dff810>, <nibabel.nifti1.Nifti1Image object at 0xa2d1b90>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa2d1d50>)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub032/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________resample_img - 45.1s, 0.8min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9b6df90>, fwhm=5)
_____________________________________________img_to_signals_maps - 13.2s, 0.2min
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x946ce50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub032/model/model001/BOLD/task001_run001/bold.nii.gz
______________________________________________________smooth_img - 24.8s, 0.4min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.884154, ..., 16.860847],
...,
[ 9.847026, ..., 16.817871]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 44.6s, 0.7min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x941fb10>, <nibabel.nifti1.Nifti1Image object at 0x941f1d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x941f890>)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c7f9d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
(166, 5)
[NiftiMapsMasker.fit_transform] smoothing images
_____________________________________________img_to_signals_maps - 14.5s, 0.2min____________________________________________________resample_img - 44.5s, 0.7min[NiftiMapsMasker.fit_transform] cleaning extracted signals____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x946cd10>, fwhm=5)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub034/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.932576, ..., 15.940955],
...,
[ 9.954786, ..., 16.070925]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
______________________________________________________smooth_img - 12.3s, 0.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x7f80b0350050>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
(165, 5)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c7f990>, <nibabel.nifti1.Nifti1Image object at 0x9c7f110>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9c7f710>)____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub031/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________resample_img - 44.0s, 0.7min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x946cc10>, <nibabel.nifti1.Nifti1Image object at 0x946c9d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x946cb90>)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub032/model/model001/BOLD/task001_run001/bold.nii.gz
_____________________________________________img_to_signals_maps - 14.5s, 0.2min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa099e90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 14.1s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x945c550>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub032/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________resample_img - 45.8s, 0.8min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x7f80b0350950>, <nibabel.nifti1.Nifti1Image object at 0x9df9c10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9df90d0>)[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 56.4s, 0.9min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.192643, ..., 11.823636],
...,
[ 9.246377, ..., 11.73476 ]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943fb90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] smoothing images
_____________________________________________img_to_signals_maps - 13.1s, 0.2min
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9cfdf90>, fwhm=5)
(166, 5)
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 58.5s, 1.0min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub033/model/model001/BOLD/task001_run001/bold.nii.gz
______________________________________________________smooth_img - 13.6s, 0.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x945c510>, <nibabel.nifti1.Nifti1Image object at 0x945c050>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x941ff90>)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9414810>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] extracting region signals
_____________________________________________img_to_signals_maps - 14.2s, 0.2min
Scrambled objects vs. Words: t_stat = [ 3.07160758 -2.1941334 1.01072979 ..., 1.1000823 -0.73115074
0.97599479], q-val = [ 0.00350178 0.03309887 0.31721382 ..., 0.27678291 0.46824143
0.33396039][NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 44.1s, 0.7min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9cfde10>, <nibabel.nifti1.Nifti1Image object at 0xa099a10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa099bd0>)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub035/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub032/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
_____________________________________________img_to_signals_maps - 13.9s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9429c10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9c62f90>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.192643, ..., 11.823636],
...,
[ 9.246377, ..., 11.73476 ]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 56.4s, 0.9min________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9452390>, fwhm=5)[NiftiMapsMasker.fit_transform] resampling mask
______________________________________________________smooth_img - 22.1s, 0.4min(166, 5)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub032/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images
______________________________________________________smooth_img - 42.4s, 0.7min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c657d0>, <nibabel.nifti1.Nifti1Image object at 0x9c9b6d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9c9b390>)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub032/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9412e10>, <nibabel.nifti1.Nifti1Image object at 0x9429950>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9429190>)
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x945c6d0>, fwhm=5)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals
_____________________________________________img_to_signals_maps - 13.9s, 0.2min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub033/model/model001/BOLD/task001_run001/bold.nii.gz
_____________________________________________img_to_signals_maps - 12.7s, 0.2min
______________________________________________________smooth_img - 64.8s, 1.1min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x945f0d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.188303, ..., 11.72375 ],
...,
[ 9.23797 , ..., 11.858504]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9429ed0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 44.4s, 0.7min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
(165, 5)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 43.5s, 0.7min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)___________________________________________________________clean - 11.8s, 0.2min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x945f4d0>, fwhm=5)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub034/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9429690>, fwhm=5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub035/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
______________________________________________________smooth_img - 12.6s, 0.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x941d810>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')______________________________________________________smooth_img - 23.0s, 0.4min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa2c4cd0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub033/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub033/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________resample_img - 45.0s, 0.7min[NiftiMapsMasker.fit_transform] extracting region signals
____________________________________________________resample_img - 81.4s, 1.4min[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x945fe90>, <nibabel.nifti1.Nifti1Image object at 0x945f910>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x1b94e10>)
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9deef10>, <nibabel.nifti1.Nifti1Image object at 0x94297d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9429310>)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x946bc90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9c65390>, fwhm=5)
_____________________________________________img_to_signals_maps - 12.6s, 0.2min[NiftiMapsMasker.fit_transform] extracting region signals
_____________________________________________img_to_signals_maps - 13.6s, 0.2min
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x95219d0>, fwhm=5)____________________________________________________resample_img - 50.1s, 0.8min______________________________________________________smooth_img - 13.3s, 0.2min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.188303, ..., 11.72375 ],
...,
[ 9.23797 , ..., 11.858504]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
______________________________________________________smooth_img - 21.3s, 0.4min[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.201 , ..., 15.379367],
...,
[ 10.325283, ..., 15.448583]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x946b910>, fwhm=5)
(165, 5)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x941db10>, <nibabel.nifti1.Nifti1Image object at 0x9c659d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9c65910>)(165, 5)
____________________________________________________________clean - 0.0s, 0.0min
______________________________________________________smooth_img - 11.9s, 0.2min
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9521950>, <nibabel.nifti1.Nifti1Image object at 0x94529d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9452b90>)
_____________________________________________img_to_signals_maps - 12.9s, 0.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub036/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
_____________________________________________img_to_signals_maps - 14.3s, 0.2min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa2c4d90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x946bd10>, <nibabel.nifti1.Nifti1Image object at 0x946b650>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x946bcd0>)________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.576773, ..., 14.97275 ],
...,
[ 9.572909, ..., 14.867193]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub033/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub033/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________resample_img - 48.9s, 0.8min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 13.4s, 0.2min(166, 5)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x945f9d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9429910>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 68.8s, 1.1min[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.285313, ..., 15.309595],
...,
[ 10.368426, ..., 15.374739]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 63.6s, 1.1min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub033/model/model001/BOLD/task001_run002/bold.nii.gz
Scrambled objects vs. Objects: t_stat = [-5.48111572 3.94649285 -5.35755111 ..., -1.09965054 2.43831428
-2.72781913], q-val = [ 1.53897126e-06 2.58106222e-04 2.36173454e-06 ..., 2.76969157e-01
1.85071389e-02 8.87969614e-03]
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0xa2c4c10>, <nibabel.nifti1.Nifti1Image object at 0xa2c4490>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa2c42d0>)[NiftiMapsMasker.fit_transform] resampling images to fit maps
(166, 5)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9413ad0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub034/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
_____________________________________________img_to_signals_maps - 13.2s, 0.2min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9521d90>, <nibabel.nifti1.Nifti1Image object at 0x945f2d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x945fc50>)
____________________________________________________resample_img - 63.2s, 1.1min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x941df90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
_____________________________________________img_to_signals_maps - 13.1s, 0.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 56.4s, 0.9min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub034/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] smoothing images________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x941d3d0>, fwhm=5)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub037/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub034/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.285313, ..., 15.309595],
...,
[ 10.368426, ..., 15.374739]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x943cd10>, fwhm=5)______________________________________________________smooth_img - 12.1s, 0.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa2d1790>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9e0b410>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub034/model/model001/BOLD/task001_run001/bold.nii.gz
(166, 5)
______________________________________________________smooth_img - 39.5s, 0.7min[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________resample_img - 64.3s, 1.1min____________________________________________________________clean - 0.0s, 0.0min
____________________________________________________resample_img - 43.8s, 0.7min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x7f80b0350950>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 82.6s, 1.4min________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0xa2d1450>, fwhm=5)
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9e0b290>, fwhm=5)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] smoothing images
______________________________________________________smooth_img - 60.8s, 1.0min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub034/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.576773, ..., 14.97275 ],
...,
[ 9.572909, ..., 14.867193]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
______________________________________________________smooth_img - 12.1s, 0.2min[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
(166, 5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub035/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x7f80b0350810>, <nibabel.nifti1.Nifti1Image object at 0x9412a10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9412c50>)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9452110>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0xa2d1710>, <nibabel.nifti1.Nifti1Image object at 0xa2c49d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa2c4910>)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x1e99350>, <nibabel.nifti1.Nifti1Image object at 0x9e0b150>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9e0b3d0>)_____________________________________________img_to_signals_maps - 12.8s, 0.2min
____________________________________________________resample_img - 44.6s, 0.7min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x7f80b0350910>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
_____________________________________________img_to_signals_maps - 27.2s, 0.5min
_____________________________________________img_to_signals_maps - 14.7s, 0.2min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 44.3s, 0.7min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9452550>, fwhm=5)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub034/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.481207, ..., 14.985843],
...,
[ 9.58509 , ..., 15.002046]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
______________________________________________________smooth_img - 28.4s, 0.5min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x7f80b0350750>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9521c50>, fwhm=5)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
(165, 5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub035/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________resample_img - 67.7s, 1.1min______________________________________________________smooth_img - 12.4s, 0.2min____________________________________________________________clean - 0.1s, 0.0min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa085190>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub038/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 44.0s, 0.7min
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.481207, ..., 14.985843],
...,
[ 9.58509 , ..., 15.002046]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x7f80b0350950>, <nibabel.nifti1.Nifti1Image object at 0x941dd50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x941db50>)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa2d1a90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x7f80b0350910>, <nibabel.nifti1.Nifti1Image object at 0x99fee90>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x99febd0>)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
(165, 5)
_____________________________________________img_to_signals_maps - 12.7s, 0.2min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub035/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0xa085490>, fwhm=5)___________________________________________________resample_img - 118.3s, 2.0min____________________________________________________________clean - 0.0s, 0.0min
_____________________________________________img_to_signals_maps - 13.4s, 0.2min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b55610>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')______________________________________________________smooth_img - 12.3s, 0.2min[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.466751, ..., 11.469034],
...,
[ 10.577253, ..., 11.742599]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 65.9s, 1.1min[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0xa2d1290>, fwhm=5)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)(166, 5)
Consonant strings vs. Words: t_stat = [ 3.1695512 -1.08147705 1.73899926 ..., 1.26107205 -0.99324792
1.00357305], q-val = [ 0.00265773 0.28488854 0.08844538 ..., 0.21337786 0.32557 0.32061698]
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub035/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0xa085110>, <nibabel.nifti1.Nifti1Image object at 0xa0859d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa085e10>)______________________________________________________smooth_img - 14.7s, 0.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9442210>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub035/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
_____________________________________________img_to_signals_maps - 13.8s, 0.2min[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 89.6s, 1.5min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x945c550>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0xa2d1f90>, <nibabel.nifti1.Nifti1Image object at 0xa2d14d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa2d1e50>)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub036/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.431621, ..., 11.493577],
...,
[ 10.450795, ..., 11.352542]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.431621, ..., 11.493577],
...,
[ 10.450795, ..., 11.352542]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 47.0s, 0.8min[NiftiMapsMasker.fit_transform] resampling images to fit maps
_____________________________________________img_to_signals_maps - 17.6s, 0.3min[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c7f390>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')(165, 5)
(165, 5)
[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________________clean - 0.0s, 0.0min
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________resample_img - 58.9s, 1.0min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.610077, ..., 12.254719],
...,
[ 8.562707, ..., 12.100594]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x945c410>, <nibabel.nifti1.Nifti1Image object at 0x945cc50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943c2d0>)[NiftiMapsMasker.fit_transform] smoothing images
(165, 5)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________________clean - 0.0s, 0.0min
_____________________________________________img_to_signals_maps - 12.9s, 0.2min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub036/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub035/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c7f3d0>, <nibabel.nifti1.Nifti1Image object at 0x9521f50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9521790>)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub036/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b55710>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa085890>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 23.8s, 0.4min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x944cbd0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
____________________________________________________resample_img - 44.5s, 0.7min____________________________________________________resample_img - 62.7s, 1.0min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub038/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________resample_img - 54.8s, 0.9min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub036/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9b55390>, fwhm=5)[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x946a650>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9a02410>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling mask
______________________________________________________smooth_img - 12.3s, 0.2min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub036/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________resample_img - 45.6s, 0.8min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x944cb90>, <nibabel.nifti1.Nifti1Image object at 0x944c750>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x944c910>)____________________________________________________resample_img - 56.1s, 0.9min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.466751, ..., 11.469034],
...,
[ 10.577253, ..., 11.742599]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
_____________________________________________img_to_signals_maps - 19.9s, 0.3min[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x95219d0>, <nibabel.nifti1.Nifti1Image object at 0x9b557d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9b55ad0>)(166, 5)
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
_____________________________________________img_to_signals_maps - 13.9s, 0.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9a020d0>, <nibabel.nifti1.Nifti1Image object at 0x945c850>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x945ca10>)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x943f690>, <nibabel.nifti1.Nifti1Image object at 0x943f550>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943f710>)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.610077, ..., 12.254719],
...,
[ 8.562707, ..., 12.100594]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
_____________________________________________img_to_signals_maps - 13.3s, 0.2min_____________________________________________img_to_signals_maps - 14.3s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.537302, ..., 15.225708],
...,
[ 9.579729, ..., 15.486506]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub036/model/model001/BOLD/task001_run002/bold.nii.gz
(165, 5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub037/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
(165, 5)
[NiftiMapsMasker.fit_transform] resampling images to fit maps____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9616490>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa099a90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
____________________________________________________resample_img - 44.5s, 0.7min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 45.7s, 0.8min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub037/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub037/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub039/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub036/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9616710>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9a02c90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c893d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0xa099d10>, fwhm=5)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943f390>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa2ca0d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')______________________________________________________smooth_img - 12.3s, 0.2min____________________________________________________resample_img - 55.9s, 0.9min____________________________________________________resample_img - 44.6s, 0.7min
Consonant strings vs. Objects: t_stat = [-4.34418703 5.82992092 -5.80222578 ..., -0.2058877 1.59016476
-1.03758602], q-val = [ 7.20804779e-05 4.55538263e-07 5.01960863e-07 ..., 8.37749397e-01
1.18363257e-01 3.04661677e-01]
______________________________________________________smooth_img - 15.8s, 0.3min
____________________________________________________resample_img - 57.8s, 1.0min
____________________________________________________resample_img - 45.2s, 0.8min[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9616250>, <nibabel.nifti1.Nifti1Image object at 0x944c890>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x944ced0>)
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0xa099110>, <nibabel.nifti1.Nifti1Image object at 0xa0996d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa099610>)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9a02c50>, <nibabel.nifti1.Nifti1Image object at 0x9a02810>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9a029d0>)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c89090>, <nibabel.nifti1.Nifti1Image object at 0x943ff50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943f9d0>)
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x946a3d0>, fwhm=5)_____________________________________________img_to_signals_maps - 13.5s, 0.2min
[NiftiMapsMasker.fit_transform] cleaning extracted signals_____________________________________________img_to_signals_maps - 14.4s, 0.2min
_____________________________________________img_to_signals_maps - 14.5s, 0.2min_____________________________________________img_to_signals_maps - 13.8s, 0.2min
______________________________________________________smooth_img - 12.1s, 0.2min[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.58369 , ..., 15.552658],
...,
[ 9.660641, ..., 15.493328]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 11.079261, ..., 16.419262],
...,
[ 11.182327, ..., 16.343243]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.58369 , ..., 15.552658],
...,
[ 9.660641, ..., 15.493328]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
(166, 5)
(166, 5)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________________clean - 0.0s, 0.0min
(166, 5)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0xa2c4410>, <nibabel.nifti1.Nifti1Image object at 0x946acd0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x946ae90>)____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 13.0s, 0.2min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub037/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub038/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9447550>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub037/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.136544, ..., 16.226159],
...,
[ 10.278073, ..., 16.269226]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub037/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c89b10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub037/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
___________________________________________________resample_img - 105.8s, 1.8min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943fb50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling images to fit maps
(166, 5)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9616a90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
___________________________________________________resample_img - 104.3s, 1.7min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9433390>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 62.9s, 1.0min
____________________________________________________________clean - 0.1s, 0.0min
____________________________________________________resample_img - 51.7s, 0.9min[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 46.6s, 0.8min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9c89d90>, fwhm=5)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x943fd10>, fwhm=5)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals
_____________________________________________________smooth_img - 135.2s, 2.3min
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.979732, ..., 16.280673],
...,
[ 11.299789, ..., 16.456208]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
______________________________________________________smooth_img - 13.8s, 0.2min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub040/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9616a50>, <nibabel.nifti1.Nifti1Image object at 0x9616110>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x96167d0>)
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x94330d0>, <nibabel.nifti1.Nifti1Image object at 0xa099790>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa099d50>)[NiftiMapsMasker.fit_transform] resampling images to fit maps
(165, 5)
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa2c4e50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')_____________________________________________img_to_signals_maps - 25.2s, 0.4min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c898d0>, <nibabel.nifti1.Nifti1Image object at 0x9c89690>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9c89850>)
_____________________________________________img_to_signals_maps - 15.6s, 0.3min
____________________________________________________________clean - 0.4s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x943ff50>, <nibabel.nifti1.Nifti1Image object at 0x943fc90>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943f450>)
____________________________________________________resample_img - 80.0s, 1.3min[NiftiMapsMasker.fit_transform] cleaning extracted signals
_____________________________________________img_to_signals_maps - 17.5s, 0.3min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.979732, ..., 16.280673],
...,
[ 11.299789, ..., 16.456208]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 74.0s, 1.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals(165, 5)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.363547, ..., 11.917958],
...,
[ 8.466741, ..., 12.07639 ]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.979732, ..., 16.280673],
...,
[ 11.299789, ..., 16.456208]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9412cd0>, <nibabel.nifti1.Nifti1Image object at 0xa2c49d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa2c4c50>)____________________________________________________________clean - 2.0s, 0.0min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub038/model/model001/BOLD/task001_run002/bold.nii.gz(165, 5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub038/model/model001/BOLD/task001_run001/bold.nii.gz
(165, 5)[NiftiMapsMasker.fit_transform] resampling images to fit maps
_____________________________________________img_to_signals_maps - 13.5s, 0.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps____________________________________________________________clean - 0.1s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9433d50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz____________________________________________________________clean - 2.0s, 0.0min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9447dd0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
___________________________________________________resample_img - 105.5s, 1.8min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub038/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________resample_img - 50.5s, 0.8min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9433fd0>, fwhm=5)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
Consonant strings vs. Scrambled objects: t_stat = [ 1.89188684 0.38916335 1.52470726 ..., 0.5720985 -0.50428058
0.41712094], q-val = [ 0.06454703 0.69887647 0.13389444 ..., 0.56992506 0.61637129
0.67844968][NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub038/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub041/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub038/model/model001/BOLD/task001_run001/bold.nii.gz
_____________________________________________________smooth_img - 133.4s, 2.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x99f2390>, fwhm=5)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x1e99190>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9447d90>, <nibabel.nifti1.Nifti1Image object at 0x9447950>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9447b10>)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa0f7050>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] extracting region signals
_____________________________________________________smooth_img - 161.2s, 2.7min
____________________________________________________resample_img - 68.0s, 1.1min
_____________________________________________img_to_signals_maps - 13.2s, 0.2min____________________________________________________resample_img - 56.7s, 0.9min________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9b5d590>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9433510>, <nibabel.nifti1.Nifti1Image object at 0x94338d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9433a90>)
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
_____________________________________________________smooth_img - 161.1s, 2.7min_____________________________________________img_to_signals_maps - 19.9s, 0.3min[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.363547, ..., 11.917958],
...,
[ 8.466741, ..., 12.07639 ]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.047744, ..., 11.97976 ],
...,
[ 9.113847, ..., 11.860703]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)(165, 5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub039/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
(166, 5)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9447dd0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub039/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 55.4s, 0.9min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub039/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub039/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub039/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c9b390>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9cea6d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9e0b210>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub042/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x99f2d10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
____________________________________________________resample_img - 57.1s, 1.0min
____________________________________________________resample_img - 45.0s, 0.8min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 59.8s, 1.0min
____________________________________________________resample_img - 60.6s, 1.0min
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9df90d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.056671, ..., 16.116321],
...,
[ 10.153978, ..., 16.201305]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9ceaad0>, fwhm=5)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals
____________________________________________________resample_img - 44.2s, 0.7min[NiftiMapsMasker.fit_transform] extracting region signals(165, 5)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c9b350>, <nibabel.nifti1.Nifti1Image object at 0x9c9b590>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9c9b090>)
______________________________________________________smooth_img - 12.7s, 0.2min
____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9523190>, <nibabel.nifti1.Nifti1Image object at 0x946a210>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9b55810>)
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x99f2cd0>, <nibabel.nifti1.Nifti1Image object at 0x99f2890>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x99f2a50>)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 13.1s, 0.2min
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x7f80b0346950>, fwhm=5)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
_____________________________________________img_to_signals_maps - 13.0s, 0.2min
_____________________________________________img_to_signals_maps - 13.3s, 0.2min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9412c90>, <nibabel.nifti1.Nifti1Image object at 0x7f80b0350810>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9523190>)______________________________________________________smooth_img - 12.1s, 0.2min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub040/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 13.2s, 0.2min[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943c5d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9521b10>, <nibabel.nifti1.Nifti1Image object at 0x9df9b10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9df9e10>)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub040/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.056671, ..., 16.116321],
...,
[ 10.153978, ..., 16.201305]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 85.4s, 1.4min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub039/model/model001/BOLD/task001_run002/bold.nii.gz
_____________________________________________img_to_signals_maps - 14.3s, 0.2min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub040/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] resampling images to fit maps
(165, 5)
[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9deee90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x943cb10>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9c7f450>, fwhm=5)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.272421, ..., 10.423187],
...,
[ 9.262055, ..., 10.459723]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x99d73d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
____________________________________________________resample_img - 61.8s, 1.0min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
______________________________________________________smooth_img - 12.4s, 0.2min______________________________________________________smooth_img - 52.1s, 0.9min
(165, 5)
____________________________________________________resample_img - 44.8s, 0.7min
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub039/model/model001/BOLD/task001_run002/bold.nii.gz
Objects vs. Words: t_stat = [-0.92500139 1.06392397 0.82229795 ..., -1.95795746 -0.04044167
0.28301966], q-val = [ 0.35959241 0.29268627 0.41497358 ..., 0.05606145 0.96790876
0.77837878][NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x99d7910>, fwhm=5)[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] cleaning extracted signals________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9521f50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] resampling mask
______________________________________________________smooth_img - 11.9s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.439109, ..., 14.296904],
...,
[ 10.501386, ..., 14.241486]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.439109, ..., 14.296904],
...,
[ 10.501386, ..., 14.241486]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 57.4s, 1.0min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub042/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals(165, 5)
(165, 5)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________________clean - 7.0s, 0.1min____________________________________________________________clean - 9.2s, 0.2min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x99d7650>, <nibabel.nifti1.Nifti1Image object at 0x99d7950>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9521950>)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub040/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9df9310>, fwhm=5)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals
_____________________________________________img_to_signals_maps - 12.6s, 0.2min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9429a90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
______________________________________________________smooth_img - 49.7s, 0.8min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.136544, ..., 16.226159],
...,
[ 10.278073, ..., 16.269226]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 64.8s, 1.1min
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.439109, ..., 14.296904],
...,
[ 10.501386, ..., 14.241486]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub040/model/model001/BOLD/task001_run002/bold.nii.gz
(166, 5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub041/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] cleaning extracted signals(165, 5)
[NiftiMapsMasker.fit_transform] resampling images to fit maps________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c7f110>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943c910>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________resample_img - 59.9s, 1.0min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 44.6s, 0.7min[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.396287, ..., 14.245409],
...,
[ 10.453547, ..., 14.120222]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub040/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub043/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub040/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
(163, 5)
[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x943ced0>, fwhm=5)[NiftiMapsMasker.fit_transform] cleaning extracted signals____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9cfda50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x99d7750>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x946a990>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
______________________________________________________smooth_img - 11.9s, 0.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 43.1s, 0.7min
____________________________________________________resample_img - 42.8s, 0.7min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
____________________________________________________resample_img - 50.2s, 0.8min
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub041/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9cfd4d0>, fwhm=5)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9521d10>, <nibabel.nifti1.Nifti1Image object at 0x943c3d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943c650>)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub041/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9dff710>, fwhm=5)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
______________________________________________________smooth_img - 12.1s, 0.2min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x99d7050>, <nibabel.nifti1.Nifti1Image object at 0x99d7fd0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x99d7e90>)_____________________________________________img_to_signals_maps - 12.8s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c892d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b6d150>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
______________________________________________________smooth_img - 14.2s, 0.2min
[NiftiMapsMasker.fit_transform] extracting region signals
_____________________________________________img_to_signals_maps - 13.0s, 0.2min[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 68.1s, 1.1min____________________________________________________resample_img - 48.8s, 0.8min
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.047744, ..., 11.97976 ],
...,
[ 9.113847, ..., 11.860703]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9cfdad0>, <nibabel.nifti1.Nifti1Image object at 0x9cfd150>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9cfd110>)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9dff7d0>, <nibabel.nifti1.Nifti1Image object at 0x9dff090>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9dffc50>)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
(166, 5)
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9429c90>, fwhm=5)_____________________________________________img_to_signals_maps - 12.7s, 0.2min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________________clean - 0.0s, 0.0min
_____________________________________________img_to_signals_maps - 13.8s, 0.2min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c89250>, <nibabel.nifti1.Nifti1Image object at 0x9c891d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9c89150>)______________________________________________________smooth_img - 12.3s, 0.2min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.396287, ..., 14.245409],
...,
[ 10.453547, ..., 14.120222]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub041/model/model001/BOLD/task001_run001/bold.nii.gz
_____________________________________________img_to_signals_maps - 12.6s, 0.2min[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.268929, ..., 16.000969],
...,
[ 9.324748, ..., 16.048502]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
(163, 5)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x942c490>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub041/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9429050>, <nibabel.nifti1.Nifti1Image object at 0x94297d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x94298d0>)____________________________________________________________clean - 0.0s, 0.0min
(165, 5)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 67.8s, 1.1min[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
Scrambled objects vs. Words: t_stat = [-1.84517374 -0.32792809 0. ..., -0.88367458 0.38235007 0. ], q-val = [ 0.07118627 0.74439218 1. ..., 0.38127665 0.70388948 1. ]_____________________________________________img_to_signals_maps - 13.0s, 0.2min
____________________________________________________________clean - 0.4s, 0.0min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x943cfd0>, fwhm=5)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub042/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.140192, ..., 12.0013 ],
...,
[ 9.072868, ..., 11.856299]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
______________________________________________________smooth_img - 36.9s, 0.6min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub041/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9465510>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')(165, 5)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9433210>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub044/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 75.7s, 1.3min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 61.2s, 1.0min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x946a210>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 57.3s, 1.0min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub042/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub042/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x94654d0>, <nibabel.nifti1.Nifti1Image object at 0x9465210>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9c89c10>)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x942cd10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b6de90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9cfd990>, <nibabel.nifti1.Nifti1Image object at 0x9cfd490>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9cfdd10>)[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling mask
_____________________________________________img_to_signals_maps - 27.0s, 0.4min
____________________________________________________resample_img - 68.3s, 1.1min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub042/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________resample_img - 85.7s, 1.4min_____________________________________________img_to_signals_maps - 13.7s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x946a050>, <nibabel.nifti1.Nifti1Image object at 0x946a890>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x946add0>)
[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
_____________________________________________img_to_signals_maps - 14.3s, 0.2min[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x94139d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x942ccd0>, <nibabel.nifti1.Nifti1Image object at 0x942c890>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x942ca50>)____________________________________________________resample_img - 44.6s, 0.7min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub043/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)_____________________________________________img_to_signals_maps - 13.6s, 0.2min[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.272421, ..., 10.423187],
...,
[ 9.262055, ..., 10.459723]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub041/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x946bcd0>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9465d90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
(165, 5)
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub044/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
______________________________________________________smooth_img - 12.6s, 0.2min____________________________________________________resample_img - 74.5s, 1.2min____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x94330d0>, fwhm=5)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
______________________________________________________smooth_img - 12.7s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x944f550>, fwhm=5)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub042/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9413d90>, <nibabel.nifti1.Nifti1Image object at 0x946b050>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x946b3d0>)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub043/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals______________________________________________________smooth_img - 48.0s, 0.8min[NiftiMapsMasker.fit_transform] smoothing images_____________________________________________img_to_signals_maps - 13.0s, 0.2min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.268929, ..., 16.000969],
...,
[ 9.324748, ..., 16.048502]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x94664d0>, fwhm=5)[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943f490>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.376113, ..., 10.66471 ],
...,
[ 9.343009, ..., 10.555007]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)(165, 5)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.140192, ..., 12.0013 ],
...,
[ 9.072868, ..., 11.856299]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] cleaning extracted signals______________________________________________________smooth_img - 12.3s, 0.2min
____________________________________________________________clean - 0.1s, 0.0min
____________________________________________________resample_img - 67.2s, 1.1min
(166, 5)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
(165, 5)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9b6d710>, fwhm=5)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub044/model/model001/BOLD/task001_run002/bold.nii.gz
______________________________________________________smooth_img - 32.8s, 0.5min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub045/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.376113, ..., 10.66471 ],
...,
[ 9.343009, ..., 10.555007]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub043/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9451650>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub042/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x944ff10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')(166, 5)
Scrambled objects vs. Objects: t_stat = [-0.91889522 -1.54328634 -0.66888775 ..., 1.46093369 0.50605068
-0.29701014], q-val = [ 0.36274508 0.12932915 0.5067715 ..., 0.15054916 0.61513745
0.7677403 ][NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________________clean - 0.0s, 0.0min
____________________________________________________resample_img - 77.0s, 1.3min[NiftiMapsMasker.fit_transform] cleaning extracted signals________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa08ced0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________resample_img - 79.7s, 1.3min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9a0e290>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.207831, ..., 15.89275 ],
...,
[ 9.269536, ..., 15.970849]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)____________________________________________________resample_img - 77.1s, 1.3min[NiftiMapsMasker.fit_transform] smoothing images
____________________________________________________resample_img - 67.2s, 1.1min________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x94518d0>, fwhm=5)
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
(165, 5)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub043/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
______________________________________________________smooth_img - 12.0s, 0.2min
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x944fed0>, <nibabel.nifti1.Nifti1Image object at 0x944fa50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x944fc10>)[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9413d50>, fwhm=5)
____________________________________________________________clean - 0.1s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9466e50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals_____________________________________________img_to_signals_maps - 22.7s, 0.4min
______________________________________________________smooth_img - 33.3s, 0.6min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
____________________________________________________resample_img - 74.1s, 1.2min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.754477, ..., 13.495542],
...,
[ 8.740415, ..., 13.495863]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub043/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9466d10>, fwhm=5)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
(166, 5)[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub043/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask______________________________________________________smooth_img - 14.4s, 0.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________________clean - 0.1s, 0.0min
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub046/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa09c4d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x943fcd0>, <nibabel.nifti1.Nifti1Image object at 0x943f5d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943fe90>)
[NiftiMapsMasker.fit_transform] smoothing images________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9466f90>, <nibabel.nifti1.Nifti1Image object at 0x94669d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9466b90>)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub044/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________resample_img - 67.2s, 1.1min
[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] resampling mask
_____________________________________________img_to_signals_maps - 13.8s, 0.2min
[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 14.6s, 0.2min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub045/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9a0e850>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0xa09c750>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9dffdd0>, <nibabel.nifti1.Nifti1Image object at 0x94331d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9dff990>)[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9451c50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 44.3s, 0.7min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)______________________________________________________smooth_img - 14.6s, 0.2min_____________________________________________img_to_signals_maps - 13.8s, 0.2min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
____________________________________________________resample_img - 44.1s, 0.7min
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9a0eb50>, fwhm=5)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub044/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub044/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9451ed0>, fwhm=5)[NiftiMapsMasker.fit_transform] resampling images to fit maps________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0xa09c290>, <nibabel.nifti1.Nifti1Image object at 0xa08c990>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa08cdd0>)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
______________________________________________________smooth_img - 12.4s, 0.2min
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943e490>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
______________________________________________________smooth_img - 11.9s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b5dad0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')_____________________________________________img_to_signals_maps - 16.3s, 0.3min[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub046/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________resample_img - 57.3s, 1.0min
[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________resample_img - 44.7s, 0.7min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9a0e610>, <nibabel.nifti1.Nifti1Image object at 0x9a0e4d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9a0e590>)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.207831, ..., 15.89275 ],
...,
[ 9.269536, ..., 15.970849]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9429850>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9451a10>, <nibabel.nifti1.Nifti1Image object at 0x94510d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9451990>)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 13.9s, 0.2min
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9b5dd10>, fwhm=5)(165, 5)
____________________________________________________resample_img - 62.0s, 1.0min
_____________________________________________img_to_signals_maps - 13.1s, 0.2min
____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x943e450>, <nibabel.nifti1.Nifti1Image object at 0x9466e50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9466d90>)[NiftiMapsMasker.fit_transform] cleaning extracted signals
______________________________________________________smooth_img - 12.5s, 0.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.714071, ..., 13.501119],
...,
[ 8.755981, ..., 13.499798]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9523310>, fwhm=5)_____________________________________________img_to_signals_maps - 14.6s, 0.2min
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.033784, ..., 14.926972],
...,
[ 9.097172, ..., 14.856032]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] extracting region signals
(165, 5)
[NiftiMapsMasker.fit_transform] resampling mask
______________________________________________________smooth_img - 11.9s, 0.2min[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________________clean - 0.1s, 0.0min
(165, 5)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9b5d450>, <nibabel.nifti1.Nifti1Image object at 0x9b5d890>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9b5d790>)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub043/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
Consonant strings vs. Words: t_stat = [-1.0970692 0.42325425 1.96396101 ..., -0.99471486 0.58981169
0.62076463], q-val = [ 0.27808449 0.67400023 0.05534017 ..., 0.32486319 0.55808328
0.53769112][NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 20.9s, 0.3min[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub045/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub044/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.754477, ..., 13.495542],
...,
[ 8.740415, ..., 13.495863]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.945999, ..., 13.345351],
...,
[ 8.939278, ..., 13.230104]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub046/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] resampling images to fit maps
(166, 5)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0xa09c890>, <nibabel.nifti1.Nifti1Image object at 0xa09c250>, mask_img=<nibabel.nifti1.Nifti1Image object at 0xa09c810>)(166, 5)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943ed10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9521ad0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________________clean - 0.0s, 0.0min
____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9a0ee10>, fwhm=5)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
_____________________________________________img_to_signals_maps - 13.9s, 0.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 45.3s, 0.8min
____________________________________________________resample_img - 75.5s, 1.3min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
______________________________________________________smooth_img - 20.8s, 0.3min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x943ef90>, fwhm=5)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub047/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub045/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
______________________________________________________smooth_img - 12.0s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9a0ecd0>, <nibabel.nifti1.Nifti1Image object at 0x9a0e7d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9a0ec50>)[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] resampling mask[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9429050>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] extracting region signals_____________________________________________img_to_signals_maps - 13.2s, 0.2min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub044/model/model001/BOLD/task001_run001/bold.nii.gz[NiftiMapsMasker.fit_transform] extracting region signals
____________________________________________________resample_img - 57.5s, 1.0min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x943ead0>, <nibabel.nifti1.Nifti1Image object at 0x943e890>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943ea50>)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9429a10>, <nibabel.nifti1.Nifti1Image object at 0x9429450>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x94291d0>)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa08c8d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
_____________________________________________img_to_signals_maps - 17.2s, 0.3min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
_____________________________________________img_to_signals_maps - 15.0s, 0.2min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub047/model/model001/BOLD/task001_run001/bold.nii.gz
___________________________________________________resample_img - 102.5s, 1.7min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9429690>, <nibabel.nifti1.Nifti1Image object at 0x9b5d5d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9429250>)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.060867, ..., 14.86267 ],
...,
[ 9.084129, ..., 14.605401]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub045/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c65b90>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
_____________________________________________img_to_signals_maps - 12.9s, 0.2min[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)(166, 5)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa6aa9d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________resample_img - 77.7s, 1.3min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________________clean - 0.2s, 0.0min
____________________________________________________resample_img - 60.8s, 1.0min[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub048/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.714071, ..., 13.501119],
...,
[ 8.755981, ..., 13.499798]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa2c42d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9c62fd0>, <nibabel.nifti1.Nifti1Image object at 0x9c9b990>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9c9b450>)[NiftiMapsMasker.fit_transform] resampling mask
(165, 5)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub045/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________resample_img - 46.2s, 0.8min
[NiftiMapsMasker.fit_transform] cleaning extracted signals_____________________________________________img_to_signals_maps - 14.1s, 0.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________________clean - 0.3s, 0.0min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub045/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9e0b550>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.060867, ..., 14.86267 ],
...,
[ 9.084129, ..., 14.605401]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9429b50>, fwhm=5)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9413c50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 89.1s, 1.5min
(166, 5)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)______________________________________________________smooth_img - 37.9s, 0.6min____________________________________________________resample_img - 70.3s, 1.2min____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub048/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub045/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9cfdb50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub046/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9451150>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.303929, ..., 16.055139],
...,
[ 10.364755, ..., 15.969678]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
Consonant strings vs. Objects: t_stat = [-0.16979054 -0.69797496 1.0374489 ..., 0.78644067 1.67759032
0.30757858], q-val = [ 0.86588846 0.48856044 0.30472489 ..., 0.43547494 0.09992802
0.75973367][NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)____________________________________________________resample_img - 83.1s, 1.4min
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.033784, ..., 14.926972],
...,
[ 9.097172, ..., 14.856032]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
____________________________________________________resample_img - 46.6s, 0.8min
(166, 5)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9521950>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images
___________________________________________________________clean - 26.0s, 0.4min(165, 5)
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub046/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
___________________________________________________________clean - 15.5s, 0.3min____________________________________________________resample_img - 43.4s, 0.7min________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9451e50>, fwhm=5)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b55e50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
______________________________________________________smooth_img - 12.5s, 0.2min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x946bc90>, fwhm=5)
____________________________________________________resample_img - 93.8s, 1.6min[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub048/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
______________________________________________________smooth_img - 11.9s, 0.2min
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub046/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9451850>, <nibabel.nifti1.Nifti1Image object at 0x9451590>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9451550>)[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa2c48d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub046/model/model001/BOLD/task001_run001/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x99d7950>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
_____________________________________________img_to_signals_maps - 14.1s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9b55550>, <nibabel.nifti1.Nifti1Image object at 0x9b55490>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9e0b9d0>)[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________resample_img - 83.8s, 1.4min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x946b050>, <nibabel.nifti1.Nifti1Image object at 0x946bd10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x946b210>)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x945f050>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
____________________________________________________resample_img - 43.9s, 0.7min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
_____________________________________________img_to_signals_maps - 13.2s, 0.2min
[NiftiMapsMasker.fit_transform] smoothing images
_____________________________________________img_to_signals_maps - 20.6s, 0.3min________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.303929, ..., 16.055139],
...,
[ 10.364755, ..., 15.969678]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
____________________________________________________resample_img - 71.1s, 1.2min[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x99d7090>, fwhm=5)[NiftiMapsMasker.fit_transform] cleaning extracted signals
(166, 5)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.884804, ..., 13.264801],
...,
[ 8.633775, ..., 13.030307]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] extracting region signals
______________________________________________________smooth_img - 12.0s, 0.2min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.32914 , ..., 16.214261],
...,
[ 10.364572, ..., 15.977494]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
(165, 5)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub047/model/model001/BOLD/task001_run002/bold.nii.gz
(165, 5)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.884804, ..., 13.264801],
...,
[ 8.633775, ..., 13.030307]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x99d7310>, <nibabel.nifti1.Nifti1Image object at 0x99d7a90>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x99d7fd0>)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub048/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b55450>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
(165, 5)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)_____________________________________________img_to_signals_maps - 12.8s, 0.2min[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c81290>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')____________________________________________________resample_img - 49.9s, 0.8min____________________________________________________________clean - 0.1s, 0.0min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub046/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
____________________________________________________resample_img - 43.2s, 0.7min[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub049/model/model001/BOLD/task001_run002/bold.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 8.945999, ..., 13.345351],
...,
[ 8.939278, ..., 13.230104]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9521e50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] smoothing images(166, 5)
____________________________________________________resample_img - 45.3s, 0.8min[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9523090>, <nibabel.nifti1.Nifti1Image object at 0x9b55510>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9b557d0>)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub047/model/model001/BOLD/task001_run001/bold.nii.gz
____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling images to fit maps________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0xa2c4c90>, fwhm=5)[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x94515d0>, <nibabel.nifti1.Nifti1Image object at 0x9451990>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9451b10>)_____________________________________________img_to_signals_maps - 14.1s, 0.2min
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x99fec10>, fwhm=5)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9433c50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')______________________________________________________smooth_img - 56.3s, 0.9min
_____________________________________________img_to_signals_maps - 13.3s, 0.2min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
______________________________________________________smooth_img - 49.0s, 0.8min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
____________________________________________________resample_img - 44.0s, 0.7min[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub047/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x945f050>, fwhm=5)
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub048/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] resampling images to fit maps______________________________________________________smooth_img - 11.8s, 0.2min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub049/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x99f2dd0>, <nibabel.nifti1.Nifti1Image object at 0x99d7d10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x99d74d0>)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b5d190>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9c6ec50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
Consonant strings vs. Scrambled objects: t_stat = [ 0.80289565 0.65336888 1.57567719 ..., -0.41322075 0.60899836
0.70345246], q-val = [ 0.4259929 0.5166362 0.12166895 ..., 0.68128514 0.54539722
0.48517221]
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x945fd50>, <nibabel.nifti1.Nifti1Image object at 0x945f9d0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x945fd10>)_____________________________________________img_to_signals_maps - 14.5s, 0.2min[NiftiMapsMasker.fit_transform] resampling mask
____________________________________________________resample_img - 43.7s, 0.7min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub047/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________resample_img - 74.6s, 1.2min
_____________________________________________img_to_signals_maps - 12.7s, 0.2min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9447ad0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] smoothing images________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9b5de50>, fwhm=5)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.907066, ..., 17.783904],
...,
[ 9.998616, ..., 17.697692]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
____________________________________________________resample_img - 57.0s, 1.0min________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9c6eed0>, fwhm=5)______________________________________________________smooth_img - 12.1s, 0.2min
[NiftiMapsMasker.fit_transform] resampling mask
(166, 5)
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub047/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
______________________________________________________smooth_img - 53.1s, 0.9min[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943e2d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] extracting region signals________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9b5d850>, <nibabel.nifti1.Nifti1Image object at 0x9b5dad0>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9b55990>)[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9447710>, <nibabel.nifti1.Nifti1Image object at 0x9447d10>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9447d90>)
____________________________________________________resample_img - 62.6s, 1.0min
[NiftiMapsMasker.fit_transform] cleaning extracted signals_____________________________________________img_to_signals_maps - 12.9s, 0.2min[NiftiMapsMasker.fit_transform] resampling mask
_____________________________________________img_to_signals_maps - 13.8s, 0.2min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub047/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling images to fit maps[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.32914 , ..., 16.214261],
...,
[ 10.364572, ..., 15.977494]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9433850>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)(165, 5)
____________________________________________________________clean - 0.0s, 0.0min
____________________________________________________resample_img - 45.4s, 0.8min________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.974209, ..., 17.826729],
...,
[ 9.852683, ..., 17.619916]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub048/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images
(165, 5)
[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9433350>, fwhm=5)____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub049/model/model001/BOLD/task001_run001/bold.nii.gz
______________________________________________________smooth_img - 12.0s, 0.2min[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9a0e7d0>, fwhm=5)[NiftiMapsMasker.fit_transform] resampling images to fit maps
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x9b5dd50>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] resampling mask
______________________________________________________smooth_img - 58.6s, 1.0min
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub048/model/model001/BOLD/task001_run002/bold.nii.gz
____________________________________________________resample_img - 75.6s, 1.3min________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9433650>, <nibabel.nifti1.Nifti1Image object at 0x9433110>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9433310>)[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] extracting region signals
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x943e990>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] smoothing images_____________________________________________img_to_signals_maps - 14.2s, 0.2min
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 62.4s, 1.0min
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9b5d410>, fwhm=5)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.974209, ..., 17.826729],
...,
[ 9.852683, ..., 17.619916]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)______________________________________________________smooth_img - 53.1s, 0.9min
[NiftiMapsMasker.fit_transform] extracting region signals
(165, 5)
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________________clean - 0.0s, 0.0min
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x943e8d0>, <nibabel.nifti1.Nifti1Image object at 0x943e210>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943e150>)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub049/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)_____________________________________________img_to_signals_maps - 13.1s, 0.2min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa6aa390>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] cleaning extracted signals
____________________________________________________resample_img - 82.6s, 1.4min[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub048/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] smoothing images
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9a0e0d0>, fwhm=5)
[NiftiMapsMasker.fit_transform] resampling mask
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9433910>, fwhm=5)[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub049/model/model001/BOLD/task001_run002/bold.nii.gz
______________________________________________________smooth_img - 62.0s, 1.0min
[NiftiMapsMasker.fit_transform] resampling images to fit maps
______________________________________________________smooth_img - 59.5s, 1.0min________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0x96385d0>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] extracting region signals____________________________________________________resample_img - 51.6s, 0.9min[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.871472, ..., 16.134119],
...,
[ 9.941695, ..., 16.117856]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9638850>, fwhm=5)
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
(165, 5)
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)______________________________________________________smooth_img - 14.1s, 0.2min____________________________________________________________clean - 0.0s, 0.0min
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub049/model/model001/BOLD/task001_run001/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9638390>, <nibabel.nifti1.Nifti1Image object at 0x9638150>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x943e910>)
________________________________________________________________________________
[Memory] Calling nilearn.image.resampling.resample_img...
resample_img(<nibabel.nifti1.Nifti1Image object at 0xa09cf10>, target_shape=(91, 109, 91), target_affine=array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), interpolation='continuous')_____________________________________________img_to_signals_maps - 13.7s, 0.2min
____________________________________________________resample_img - 82.7s, 1.4min[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.011377, ..., 15.894124],
...,
[ 10.147412, ..., 16.209967]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9433a10>, fwhm=5)(166, 5)
______________________________________________________smooth_img - 12.6s, 0.2min____________________________________________________________clean - 0.1s, 0.0min
[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)
________________________________________________________________________________
[Memory] Calling nilearn.region.img_to_signals_maps...
img_to_signals_maps(<nibabel.nifti1.Nifti1Image object at 0x9433f50>, <nibabel.nifti1.Nifti1Image object at 0x9ceaf50>, mask_img=<nibabel.nifti1.Nifti1Image object at 0x9ceaad0>)[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub049/model/model001/BOLD/task001_run002/bold.nii.gz
_____________________________________________img_to_signals_maps - 13.7s, 0.2min[NiftiMapsMasker.fit_transform] resampling images to fit maps
Objects vs. Words: t_stat = [-0.17105371 3.67952798 -0.38585408 ..., -2.0221359 0.8993616 1.5662046 ], q-val = [ 8.64900580e-01 5.90561060e-04 7.01309657e-01 ..., 4.87546337e-02
3.72949896e-01 1.23870339e-01][NiftiMapsMasker.fit_transform] smoothing images[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 9.871472, ..., 16.134119],
...,
[ 9.941695, ..., 16.117856]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0x9638ad0>, fwhm=5)
(165, 5)______________________________________________________smooth_img - 41.7s, 0.7min
____________________________________________________________clean - 0.1s, 0.0min
[NiftiMapsMasker.fit_transform] extracting region signals[NiftiMapsMasker.fit_transform] loading regions from /usr/share/fsl/data/atlases/HarvardOxford/HarvardOxford-cortl-prob-2mm.nii.gz
[NiftiMapsMasker.fit_transform] loading mask from Nifti1Image(
shape=(53, 63, 46),
affine=array([[ -3., 0., 0., 78.],
[ 0., 3., 0., -112.],
[ 0., 0., 3., -50.],
[ 0., 0., 0., 1.]])
)[NiftiMapsMasker.fit_transform] cleaning extracted signals
[NiftiMapsMasker.fit_transform] resampling mask
[NiftiMapsMasker.fit_transform] loading images from /volatile/storage/workspace/brainpedia/preproc/ds107/sub049/model/model001/BOLD/task001_run002/bold.nii.gz
[NiftiMapsMasker.fit_transform] resampling images to fit maps
[NiftiMapsMasker.fit_transform] smoothing images
________________________________________________________________________________
[Memory] Calling nilearn.image.image.smooth_img...
smooth_img(<nibabel.nifti1.Nifti1Image object at 0xa09c610>, fwhm=5)
______________________________________________________smooth_img - 11.9s, 0.2min
[NiftiMapsMasker.fit_transform] extracting region signals
[NiftiMapsMasker.fit_transform] cleaning extracted signals
________________________________________________________________________________
[Memory] Calling nilearn.signal.clean...
clean(array([[ 10.011377, ..., 15.894124],
...,
[ 10.147412, ..., 16.209967]]), standardize=True, n_hv_confounds=5, detrend=True, confounds=None, low_pass=None, t_r=None, high_pass=None)
(166, 5)
____________________________________________________________clean - 0.0s, 0.0min
Scrambled objects vs. Words: t_stat = [-1.38727369 0.61398214 0.44713908 ..., -0.92983481 0.6666574
2.19816896], q-val = [ 0.17176624 0.54212629 0.65678587 ..., 0.35710951 0.50818293
0.0327921 ]
Scrambled objects vs. Objects: t_stat = [-1.37601168 -3.60243083 0.84265009 ..., 1.47068162 -0.75526737
0.34501139], q-val = [ 0.1752045 0.00074642 0.4036035 ..., 0.14790271 0.4537788 0.7315931 ]
Consonant strings vs. Words: t_stat = [-0.17782169 0.92925989 -0.42497295 ..., -1.05799912 0.65798006
2.49703898], q-val = [ 0.85961134 0.35740426 0.67275549 ..., 0.29535137 0.51369438
0.01600723]
Consonant strings vs. Objects: t_stat = [ 0. -3.62866185 -0.08163832 ..., 0.79150807 -0.63809531
0.6450075 ], q-val = [ 1.00000000e+00 6.89420928e-04 9.35273800e-01 ..., 4.32541590e-01
5.26444312e-01 5.21993443e-01]
Consonant strings vs. Scrambled objects: t_stat = [ 1.33103476 0.41779775 -0.88152931 ..., -0.43009264 0.36539321
0.40474995], q-val = [ 0.18946552 0.67795812 0.38242445 ..., 0.6690531 0.71642318
0.68745943]
WARNING:root:[MemorizedFunc(func=<function resample_img at 0x92efe60>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x9414a50>,), kwargs={'target_shape': (91, 109, 91), 'target_affine': array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), 'interpolation': 'continuous'})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function resample_img at 0x92efe60>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x9412d50>,), kwargs={'target_shape': (91, 109, 91), 'target_affine': array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), 'interpolation': 'continuous'})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 411, in load
file_handle = open(filename, 'rb')
IOError: [Errno 2] Aucun fichier ou dossier de ce type: '/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib/nilearn/image/resampling/resample_img/2f36f60589ec40858fdaf35db7ff0961/output.pkl'
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x9e0b510>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function resample_img at 0x92efe60>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x946bc90>,), kwargs={'target_shape': (91, 109, 91), 'target_affine': array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), 'interpolation': 'continuous'})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x945f450>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x99d70d0>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0xa0f1c50>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function resample_img at 0x92efe60>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x9dffc90>,), kwargs={'target_shape': (91, 109, 91), 'target_affine': array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), 'interpolation': 'continuous'})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function resample_img at 0x92efe60>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x9b55ed0>,), kwargs={'target_shape': (91, 109, 91), 'target_affine': array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), 'interpolation': 'continuous'})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function resample_img at 0x92efe60>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x9447550>,), kwargs={'target_shape': (91, 109, 91), 'target_affine': array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), 'interpolation': 'continuous'})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x945dad0>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x941d790>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function resample_img at 0x92efe60>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0xa0f1b50>,), kwargs={'target_shape': (91, 109, 91), 'target_affine': array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), 'interpolation': 'continuous'})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function resample_img at 0x92efe60>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0xa2c4750>,), kwargs={'target_shape': (91, 109, 91), 'target_affine': array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), 'interpolation': 'continuous'})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function resample_img at 0x92efe60>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x9b55810>,), kwargs={'target_shape': (91, 109, 91), 'target_affine': array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), 'interpolation': 'continuous'})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function resample_img at 0x92efe60>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x9447dd0>,), kwargs={'target_shape': (91, 109, 91), 'target_affine': array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), 'interpolation': 'continuous'})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x7f80b0350810>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x99d7150>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x941d3d0>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function resample_img at 0x92efe60>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x7f80b0350050>,), kwargs={'target_shape': (91, 109, 91), 'target_affine': array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), 'interpolation': 'continuous'})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function img_to_signals_maps at 0x92f4e60>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x9b8be90>, <nibabel.nifti1.Nifti1Image object at 0x9b8b710>), kwargs={'mask_img': <nibabel.nifti1.Nifti1Image object at 0x9b8be50>})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x943cb10>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function resample_img at 0x92efe60>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x945de90>,), kwargs={'target_shape': (91, 109, 91), 'target_affine': array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), 'interpolation': 'continuous'})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x94664d0>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function resample_img at 0x92efe60>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x9c7f110>,), kwargs={'target_shape': (91, 109, 91), 'target_affine': array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), 'interpolation': 'continuous'})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function resample_img at 0x92efe60>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x946a650>,), kwargs={'target_shape': (91, 109, 91), 'target_affine': array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), 'interpolation': 'continuous'})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 411, in load
file_handle = open(filename, 'rb')
IOError: [Errno 2] Aucun fichier ou dossier de ce type: '/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib/nilearn/image/resampling/resample_img/9edcfc6b46330c2d50bc96ea04a2d79a/output.pkl'
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x9a0ee10>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x94330d0>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 293, in load_build
array = nd_array_wrapper.read(self)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 112, in read
mmap_mode=unpickler.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/numpy/lib/npyio.py", line 391, in load
return format.read_array(fid)
File "/home/rphlypo/.local/lib/python2.7/site-packages/numpy/lib/format.py", line 482, in read_array
array.shape = shape
ValueError: total size of new array must be unchanged
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x9466d10>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x94518d0>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x944f550>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 411, in load
file_handle = open(filename, 'rb')
IOError: [Errno 2] Aucun fichier ou dossier de ce type: '/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib/nilearn/image/image/smooth_img/9f4ac946d26956f3e902025e9c92ab6d/output.pkl'
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0xa09c610>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x9c6eed0>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function smooth_img at 0x92eff50>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0x9523310>,), kwargs={'fwhm': 5})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
WARNING:root:[MemorizedFunc(func=<function resample_img at 0x92efe60>, cachedir='/volatile/storage/workspace/parietal_retreat/covariance_learn/cache/ds107/joblib')]: Exception while loading results for (args=(<nibabel.nifti1.Nifti1Image object at 0xa2c48d0>,), kwargs={'target_shape': (91, 109, 91), 'target_affine': array([[ -2., 0., 0., 90.],
[ 0., 2., 0., -126.],
[ 0., 0., 2., -72.],
[ 0., 0., 0., 1.]]), 'interpolation': 'continuous'})
Traceback (most recent call last):
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 180, in __call__
out = self.load_output(output_dir)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/memory.py", line 436, in load_output
mmap_mode=self.mmap_mode)
File "/home/rphlypo/.local/lib/python2.7/site-packages/joblib-0.8.0a3-py2.7.egg/joblib/numpy_pickle.py", line 428, in load
obj = unpickler.load()
File "/usr/lib/python2.7/pickle.py", line 858, in load
dispatch[key](self)
File "/usr/lib/python2.7/pickle.py", line 880, in load_eof
raise EOFError
EOFError
In [ ]:
%debug
> /home/rphlypo/Projects/parietalretreat/classify_covs.py(121)_regress()
120 Q, _ = scipy.linalg.qr(y, mode="economic")
--> 121 return X - Q.dot(np.linalg.pinv(Q.T.dot(Q))).dot(Q.T.dot(X))
122
ipdb> u
> /home/rphlypo/Projects/parietalretreat/classify_covs.py(76)_get_region_signals()
75 confds = confound.compute_mvt_confounds(confd_file)[0]
---> 76 signals = _regress(region_signals[region_ix], confds)
77 data.append(_get_samples(signals, onset_file, TR))
ipdb> region_signals[region_ix].shape
(164, 96)
ipdb> confds.shape
(165, 18)
ipdb> df_
<pandas.core.groupby.DataFrameGroupBy object at 0x2e16d10>
ipdb> print df_
<pandas.core.groupby.DataFrameGroupBy object at 0x2e16d10>
ipdb> df
TR anat \
0 3.0 /volatile/storage/workspace/brainpedia/preproc...
1 3.0 /volatile/storage/workspace/brainpedia/preproc...
2 3.0 /volatile/storage/workspace/brainpedia/preproc...
3 3.0 /volatile/storage/workspace/brainpedia/preproc...
4 3.0 /volatile/storage/workspace/brainpedia/preproc...
5 3.0 /volatile/storage/workspace/brainpedia/preproc...
6 3.0 /volatile/storage/workspace/brainpedia/preproc...
7 3.0 /volatile/storage/workspace/brainpedia/preproc...
8 3.0 /volatile/storage/workspace/brainpedia/preproc...
9 3.0 /volatile/storage/workspace/brainpedia/preproc...
10 3.0 /volatile/storage/workspace/brainpedia/preproc...
11 3.0 /volatile/storage/workspace/brainpedia/preproc...
12 3.0 /volatile/storage/workspace/brainpedia/preproc...
13 3.0 /volatile/storage/workspace/brainpedia/preproc...
14 3.0 /volatile/storage/workspace/brainpedia/preproc...
15 3.0 /volatile/storage/workspace/brainpedia/preproc...
16 3.0 /volatile/storage/workspace/brainpedia/preproc...
17 3.0 /volatile/storage/workspace/brainpedia/preproc...
18 3.0 /volatile/storage/workspace/brainpedia/preproc...
19 3.0 /volatile/storage/workspace/brainpedia/preproc...
20 3.0 /volatile/storage/workspace/brainpedia/preproc...
21 3.0 /volatile/storage/workspace/brainpedia/preproc...
22 3.0 /volatile/storage/workspace/brainpedia/preproc...
23 3.0 /volatile/storage/workspace/brainpedia/preproc...
24 3.0 /volatile/storage/workspace/brainpedia/preproc...
25 3.0 /volatile/storage/workspace/brainpedia/preproc...
26 3.0 /volatile/storage/workspace/brainpedia/preproc...
27 3.0 /volatile/storage/workspace/brainpedia/preproc...
28 3.0 /volatile/storage/workspace/brainpedia/preproc...
29 3.0 /volatile/storage/workspace/brainpedia/preproc...
30 3.0 /volatile/storage/workspace/brainpedia/preproc...
31 3.0 /volatile/storage/workspace/brainpedia/preproc...
32 3.0 /volatile/storage/workspace/brainpedia/preproc...
33 3.0 /volatile/storage/workspace/brainpedia/preproc...
34 3.0 /volatile/storage/workspace/brainpedia/preproc...
35 3.0 /volatile/storage/workspace/brainpedia/preproc...
36 3.0 /volatile/storage/workspace/brainpedia/preproc...
37 3.0 /volatile/storage/workspace/brainpedia/preproc...
38 3.0 /volatile/storage/workspace/brainpedia/preproc...
39 3.0 /volatile/storage/workspace/brainpedia/preproc...
40 3.0 /volatile/storage/workspace/brainpedia/preproc...
41 3.0 /volatile/storage/workspace/brainpedia/preproc...
42 3.0 /volatile/storage/workspace/brainpedia/preproc...
43 3.0 /volatile/storage/workspace/brainpedia/preproc...
44 3.0 /volatile/storage/workspace/brainpedia/preproc...
45 3.0 /volatile/storage/workspace/brainpedia/preproc...
46 3.0 /volatile/storage/workspace/brainpedia/preproc...
47 3.0 /volatile/storage/workspace/brainpedia/preproc...
48 3.0 /volatile/storage/workspace/brainpedia/preproc...
49 3.0 /volatile/storage/workspace/brainpedia/preproc...
50 3.0 /volatile/storage/workspace/brainpedia/preproc...
51 3.0 /volatile/storage/workspace/brainpedia/preproc...
52 3.0 /volatile/storage/workspace/brainpedia/preproc...
53 3.0 /volatile/storage/workspace/brainpedia/preproc...
54 3.0 /volatile/storage/workspace/brainpedia/preproc...
55 3.0 /volatile/storage/workspace/brainpedia/preproc...
56 3.0 /volatile/storage/workspace/brainpedia/preproc...
57 3.0 /volatile/storage/workspace/brainpedia/preproc...
58 3.0 /volatile/storage/workspace/brainpedia/preproc...
59 3.0 /volatile/storage/workspace/brainpedia/preproc...
... ...
cond_onsets condition \
0 /volatile/storage/workspace/brainpedia/preproc... Scrambled objects
1 /volatile/storage/workspace/brainpedia/preproc... Consonant strings
2 /volatile/storage/workspace/brainpedia/preproc... Words
3 /volatile/storage/workspace/brainpedia/preproc... Objects
4 /volatile/storage/workspace/brainpedia/preproc... Scrambled objects
5 /volatile/storage/workspace/brainpedia/preproc... Consonant strings
6 /volatile/storage/workspace/brainpedia/preproc... Words
7 /volatile/storage/workspace/brainpedia/preproc... Objects
8 /volatile/storage/workspace/brainpedia/preproc... Scrambled objects
9 /volatile/storage/workspace/brainpedia/preproc... Consonant strings
10 /volatile/storage/workspace/brainpedia/preproc... Words
11 /volatile/storage/workspace/brainpedia/preproc... Objects
12 /volatile/storage/workspace/brainpedia/preproc... Scrambled objects
13 /volatile/storage/workspace/brainpedia/preproc... Consonant strings
14 /volatile/storage/workspace/brainpedia/preproc... Words
15 /volatile/storage/workspace/brainpedia/preproc... Objects
16 /volatile/storage/workspace/brainpedia/preproc... Scrambled objects
17 /volatile/storage/workspace/brainpedia/preproc... Consonant strings
18 /volatile/storage/workspace/brainpedia/preproc... Words
19 /volatile/storage/workspace/brainpedia/preproc... Objects
20 /volatile/storage/workspace/brainpedia/preproc... Scrambled objects
21 /volatile/storage/workspace/brainpedia/preproc... Consonant strings
22 /volatile/storage/workspace/brainpedia/preproc... Words
23 /volatile/storage/workspace/brainpedia/preproc... Objects
24 /volatile/storage/workspace/brainpedia/preproc... Scrambled objects
25 /volatile/storage/workspace/brainpedia/preproc... Consonant strings
26 /volatile/storage/workspace/brainpedia/preproc... Words
27 /volatile/storage/workspace/brainpedia/preproc... Objects
28 /volatile/storage/workspace/brainpedia/preproc... Scrambled objects
29 /volatile/storage/workspace/brainpedia/preproc... Consonant strings
30 /volatile/storage/workspace/brainpedia/preproc... Words
31 /volatile/storage/workspace/brainpedia/preproc... Objects
32 /volatile/storage/workspace/brainpedia/preproc... Scrambled objects
33 /volatile/storage/workspace/brainpedia/preproc... Consonant strings
34 /volatile/storage/workspace/brainpedia/preproc... Words
35 /volatile/storage/workspace/brainpedia/preproc... Objects
36 /volatile/storage/workspace/brainpedia/preproc... Scrambled objects
37 /volatile/storage/workspace/brainpedia/preproc... Consonant strings
38 /volatile/storage/workspace/brainpedia/preproc... Words
39 /volatile/storage/workspace/brainpedia/preproc... Objects
40 /volatile/storage/workspace/brainpedia/preproc... Scrambled objects
41 /volatile/storage/workspace/brainpedia/preproc... Consonant strings
42 /volatile/storage/workspace/brainpedia/preproc... Words
43 /volatile/storage/workspace/brainpedia/preproc... Objects
44 /volatile/storage/workspace/brainpedia/preproc... Scrambled objects
45 /volatile/storage/workspace/brainpedia/preproc... Consonant strings
46 /volatile/storage/workspace/brainpedia/preproc... Words
47 /volatile/storage/workspace/brainpedia/preproc... Objects
48 /volatile/storage/workspace/brainpedia/preproc... Scrambled objects
49 /volatile/storage/workspace/brainpedia/preproc... Consonant strings
50 /volatile/storage/workspace/brainpedia/preproc... Words
51 /volatile/storage/workspace/brainpedia/preproc... Objects
52 /volatile/storage/workspace/brainpedia/preproc... Scrambled objects
53 /volatile/storage/workspace/brainpedia/preproc... Consonant strings
54 /volatile/storage/workspace/brainpedia/preproc... Words
55 /volatile/storage/workspace/brainpedia/preproc... Objects
56 /volatile/storage/workspace/brainpedia/preproc... Scrambled objects
57 /volatile/storage/workspace/brainpedia/preproc... Consonant strings
58 /volatile/storage/workspace/brainpedia/preproc... Words
59 /volatile/storage/workspace/brainpedia/preproc... Objects
... ...
confds \
0 /volatile/storage/workspace/brainpedia/preproc...
1 /volatile/storage/workspace/brainpedia/preproc...
2 /volatile/storage/workspace/brainpedia/preproc...
3 /volatile/storage/workspace/brainpedia/preproc...
4 /volatile/storage/workspace/brainpedia/preproc...
5 /volatile/storage/workspace/brainpedia/preproc...
6 /volatile/storage/workspace/brainpedia/preproc...
7 /volatile/storage/workspace/brainpedia/preproc...
8 /volatile/storage/workspace/brainpedia/preproc...
9 /volatile/storage/workspace/brainpedia/preproc...
10 /volatile/storage/workspace/brainpedia/preproc...
11 /volatile/storage/workspace/brainpedia/preproc...
12 /volatile/storage/workspace/brainpedia/preproc...
13 /volatile/storage/workspace/brainpedia/preproc...
14 /volatile/storage/workspace/brainpedia/preproc...
15 /volatile/storage/workspace/brainpedia/preproc...
16 /volatile/storage/workspace/brainpedia/preproc...
17 /volatile/storage/workspace/brainpedia/preproc...
18 /volatile/storage/workspace/brainpedia/preproc...
19 /volatile/storage/workspace/brainpedia/preproc...
20 /volatile/storage/workspace/brainpedia/preproc...
21 /volatile/storage/workspace/brainpedia/preproc...
22 /volatile/storage/workspace/brainpedia/preproc...
23 /volatile/storage/workspace/brainpedia/preproc...
24 /volatile/storage/workspace/brainpedia/preproc...
25 /volatile/storage/workspace/brainpedia/preproc...
26 /volatile/storage/workspace/brainpedia/preproc...
27 /volatile/storage/workspace/brainpedia/preproc...
28 /volatile/storage/workspace/brainpedia/preproc...
29 /volatile/storage/workspace/brainpedia/preproc...
30 /volatile/storage/workspace/brainpedia/preproc...
31 /volatile/storage/workspace/brainpedia/preproc...
32 /volatile/storage/workspace/brainpedia/preproc...
33 /volatile/storage/workspace/brainpedia/preproc...
34 /volatile/storage/workspace/brainpedia/preproc...
35 /volatile/storage/workspace/brainpedia/preproc...
36 /volatile/storage/workspace/brainpedia/preproc...
37 /volatile/storage/workspace/brainpedia/preproc...
38 /volatile/storage/workspace/brainpedia/preproc...
39 /volatile/storage/workspace/brainpedia/preproc...
40 /volatile/storage/workspace/brainpedia/preproc...
41 /volatile/storage/workspace/brainpedia/preproc...
42 /volatile/storage/workspace/brainpedia/preproc...
43 /volatile/storage/workspace/brainpedia/preproc...
44 /volatile/storage/workspace/brainpedia/preproc...
45 /volatile/storage/workspace/brainpedia/preproc...
46 /volatile/storage/workspace/brainpedia/preproc...
47 /volatile/storage/workspace/brainpedia/preproc...
48 /volatile/storage/workspace/brainpedia/preproc...
49 /volatile/storage/workspace/brainpedia/preproc...
50 /volatile/storage/workspace/brainpedia/preproc...
51 /volatile/storage/workspace/brainpedia/preproc...
52 /volatile/storage/workspace/brainpedia/preproc...
53 /volatile/storage/workspace/brainpedia/preproc...
54 /volatile/storage/workspace/brainpedia/preproc...
55 /volatile/storage/workspace/brainpedia/preproc...
56 /volatile/storage/workspace/brainpedia/preproc...
57 /volatile/storage/workspace/brainpedia/preproc...
58 /volatile/storage/workspace/brainpedia/preproc...
59 /volatile/storage/workspace/brainpedia/preproc...
...
func model region_ix run \
0 /volatile/storage/workspace/brainpedia/preproc... 001 0 001
1 /volatile/storage/workspace/brainpedia/preproc... 001 0 001
2 /volatile/storage/workspace/brainpedia/preproc... 001 0 001
3 /volatile/storage/workspace/brainpedia/preproc... 001 0 001
4 /volatile/storage/workspace/brainpedia/preproc... 001 4 002
5 /volatile/storage/workspace/brainpedia/preproc... 001 4 002
6 /volatile/storage/workspace/brainpedia/preproc... 001 4 002
7 /volatile/storage/workspace/brainpedia/preproc... 001 4 002
8 /volatile/storage/workspace/brainpedia/preproc... 001 8 001
9 /volatile/storage/workspace/brainpedia/preproc... 001 8 001
10 /volatile/storage/workspace/brainpedia/preproc... 001 8 001
11 /volatile/storage/workspace/brainpedia/preproc... 001 8 001
12 /volatile/storage/workspace/brainpedia/preproc... 001 12 002
13 /volatile/storage/workspace/brainpedia/preproc... 001 12 002
14 /volatile/storage/workspace/brainpedia/preproc... 001 12 002
15 /volatile/storage/workspace/brainpedia/preproc... 001 12 002
16 /volatile/storage/workspace/brainpedia/preproc... 001 16 001
17 /volatile/storage/workspace/brainpedia/preproc... 001 16 001
18 /volatile/storage/workspace/brainpedia/preproc... 001 16 001
19 /volatile/storage/workspace/brainpedia/preproc... 001 16 001
20 /volatile/storage/workspace/brainpedia/preproc... 001 20 002
21 /volatile/storage/workspace/brainpedia/preproc... 001 20 002
22 /volatile/storage/workspace/brainpedia/preproc... 001 20 002
23 /volatile/storage/workspace/brainpedia/preproc... 001 20 002
24 /volatile/storage/workspace/brainpedia/preproc... 001 24 001
25 /volatile/storage/workspace/brainpedia/preproc... 001 24 001
26 /volatile/storage/workspace/brainpedia/preproc... 001 24 001
27 /volatile/storage/workspace/brainpedia/preproc... 001 24 001
28 /volatile/storage/workspace/brainpedia/preproc... 001 28 002
29 /volatile/storage/workspace/brainpedia/preproc... 001 28 002
30 /volatile/storage/workspace/brainpedia/preproc... 001 28 002
31 /volatile/storage/workspace/brainpedia/preproc... 001 28 002
32 /volatile/storage/workspace/brainpedia/preproc... 001 32 001
33 /volatile/storage/workspace/brainpedia/preproc... 001 32 001
34 /volatile/storage/workspace/brainpedia/preproc... 001 32 001
35 /volatile/storage/workspace/brainpedia/preproc... 001 32 001
36 /volatile/storage/workspace/brainpedia/preproc... 001 36 002
37 /volatile/storage/workspace/brainpedia/preproc... 001 36 002
38 /volatile/storage/workspace/brainpedia/preproc... 001 36 002
39 /volatile/storage/workspace/brainpedia/preproc... 001 36 002
40 /volatile/storage/workspace/brainpedia/preproc... 001 40 001
41 /volatile/storage/workspace/brainpedia/preproc... 001 40 001
42 /volatile/storage/workspace/brainpedia/preproc... 001 40 001
43 /volatile/storage/workspace/brainpedia/preproc... 001 40 001
44 /volatile/storage/workspace/brainpedia/preproc... 001 44 002
45 /volatile/storage/workspace/brainpedia/preproc... 001 44 002
46 /volatile/storage/workspace/brainpedia/preproc... 001 44 002
47 /volatile/storage/workspace/brainpedia/preproc... 001 44 002
48 /volatile/storage/workspace/brainpedia/preproc... 001 48 001
49 /volatile/storage/workspace/brainpedia/preproc... 001 48 001
50 /volatile/storage/workspace/brainpedia/preproc... 001 48 001
51 /volatile/storage/workspace/brainpedia/preproc... 001 48 001
52 /volatile/storage/workspace/brainpedia/preproc... 001 52 002
53 /volatile/storage/workspace/brainpedia/preproc... 001 52 002
54 /volatile/storage/workspace/brainpedia/preproc... 001 52 002
55 /volatile/storage/workspace/brainpedia/preproc... 001 52 002
56 /volatile/storage/workspace/brainpedia/preproc... 001 56 001
57 /volatile/storage/workspace/brainpedia/preproc... 001 56 001
58 /volatile/storage/workspace/brainpedia/preproc... 001 56 001
59 /volatile/storage/workspace/brainpedia/preproc... 001 56 001
... ... ... ...
subj_id task
0 001 001
1 001 001
2 001 001
3 001 001
4 001 001
5 001 001
6 001 001
7 001 001
8 002 001
9 002 001
10 002 001
11 002 001
12 002 001
13 002 001
14 002 001
15 002 001
16 003 001
17 003 001
18 003 001
19 003 001
20 003 001
21 003 001
22 003 001
23 003 001
24 004 001
25 004 001
26 004 001
27 004 001
28 004 001
29 004 001
30 004 001
31 004 001
32 005 001
33 005 001
34 005 001
35 005 001
36 005 001
37 005 001
38 005 001
39 005 001
40 006 001
41 006 001
42 006 001
43 006 001
44 006 001
45 006 001
46 006 001
47 006 001
48 007 001
49 007 001
50 007 001
51 007 001
52 007 001
53 007 001
54 007 001
55 007 001
56 008 001
57 008 001
58 008 001
59 008 001
... ...
[392 rows x 11 columns]
ipdb> np.loadtxt(df["confds"][0]).shape
(164, 6)
ipdb> import nibabel
ipdb> nibabel.load(df["func"][0]).shape
(53, 63, 46, 164)
ipdb> len(df)
392
ipdb> for k in range(len(df)):
*** SyntaxError: unexpected EOF while parsing (<stdin>, line 1)
ipdb> [np.loadtxt(df["confds"][k]).shape[0] == nibabel.load(df["func"][k]).shape[-1] for k in range(len(df))]]
*** SyntaxError: invalid syntax (<stdin>, line 1)
ipdb> [np.loadtxt(df["confds"][k]).shape[0] == nibabel.load(df["func"][k]).shape[-1] for k in range(len(df))]
[True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True, True]
In [71]:
p = t_test[2]["pval"][4]
In [75]:
import numpy as np
from connectivity import vec_to_sym
p_signif = p < 1e-8
p_signif
vec_to_sym(p_signif)[-5:-1,-5:-1]
Out[75]:
array([[ 1., 0., 0., 0.],
[ 0., 0., 0., 0.],
[ 0., 0., 1., 0.],
[ 0., 0., 0., 1.]])
In [ ]:
p = t_test[0]["pval"][4]
p_signif = p < 1e-4
p_signif
vec_to_sym(p_signif)[-5:-1,-5:-1]
In [70]:
t_test[2]["pval"][1]
Out[70]:
array([ 6.32032627e-04, 1.81022663e-01, 1.97745804e-04, ...,
9.22333264e-01, 3.20730115e-02, 6.78438410e-03])
In [33]:
t_test[1]
Out[33]:
comparison
tstat
pval
0
Objects vs. Words
[-8.16092629244, 3.69193845812, -5.62627615592...
[5.86355037478e-07, 2.64736050326, 0.004323208...
1
Scrambled objects vs. Words
[-3.34837337145, 1.39921202833, 0.081989738469...
[7.39447538235, 783.039691728, 4353.34052054, ...
2
Scrambled objects vs. Objects
[5.81969241626, -2.90826551666, 6.89636908598,...
[0.00219839585446, 25.560415086, 4.93607635003...
3
Consonant strings vs. Words
[-3.36888639509, 0.0716231112463, -1.009041123...
[6.96408316814, 4391.53663162, 1480.67597699, ...
4
Consonant strings vs. Objects
[3.6564040481, -4.27808322581, 5.64629998944, ...
[2.95045389405, 0.416188017241, 0.004031488381...
5
Consonant strings vs. Scrambled objects
[-1.409652764, -1.07296336341, -1.18974582934,...
[768.653757421, 1343.96535408, 1117.43076266, ...
6 rows × 3 columns
Content source: rphlypo/parietalretreat
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