Drop bad trials from covariates and images



In [1]:

    
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
sns.set_context('paper')
sns.set_style('ticks')









    



/usr/local/python-2.7.6/lib/python2.7/site-packages/matplotlib-1.5.1-py2.7-linux-x86_64.egg/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.
  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')
/usr/local/python-2.7.6/lib/python2.7/site-packages/matplotlib-1.5.1-py2.7-linux-x86_64.egg/matplotlib/__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.
  warnings.warn(self.msg_depr % (key, alt_key))



In [2]:

    
import numpy as np
import pandas as pd
from glob import glob
from os.path import join, exists
from os import remove
import json

Set directory and session information



In [3]:

    
directory = '/tier2/freeman/Nick/lfov.calibration'



In [4]:

    
key = '2016-04-23'
name = 'anm-0330549-5'

List trials to exlude from analysis



In [12]:

    
drop = {'trials': range(323, 500)} #range(0,31)

Load covariates



In [5]:

    
path = join(directory, 'reprocessed', name, key, 'covariates')
print exists(path)









    



True



In [6]:

    
covariates = pd.read_csv(join(path, 'covariates.csv'))

Save list of dropped trials



In [13]:

    
with open(join(path, 'drop.json'), 'w') as outfile:
    json.dump(drop, outfile, indent=2)

Process covariates



In [14]:

    
keep = np.ones(len(covariates), dtype='bool')
for trial in drop['trials']:
    keep[(covariates.number == trial).values] = False



In [15]:

    
delete = covariates.index[~keep]
covariates = covariates[keep]

Overwrite covariates



In [16]:

    
covariates.to_csv(join(path, 'covariates.csv'))

Delete volumes



In [17]:

    
imagepath = join(directory, 'reprocessed', name, key, 'images')
print exists(imagepath)









    



True



In [18]:

    
for index in delete:
    remove(join(imagepath, 'image-%05d.bin' % index))

Update meta



In [19]:

    
summarypath = join(directory, 'reprocessed', name, key, 'summary')
with open(join(summarypath, 'meta.json')) as infile:
    meta = json.load(infile)
meta['shape'] = [len(covariates)] + meta['shape'][1:]



In [20]:

    
with open(join(summarypath, 'meta.json'), 'w') as outfile:
    json.dump(meta, outfile, indent=2)



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