Ready to use test dataset

In [ ]:

    

%matplotlib inline


    

In [39]:

    

import matplotlib.pyplot as plt

import pandas as pd

from sktracker import data
from sktracker.trajectories import Trajectories
from sktracker.io import TiffFile


    

    




2014-09-04 11:37:23:INFO:sktracker.utils.mpl_loader: Matplotlib backend 'Qt4Agg' has been loaded.

In [3]:

    

trajs = Trajectories(data.brownian_trajectories_generator())
trajs.show(groupby_args={'by': 'true_label'})


    

    
Out[3]:





<matplotlib.axes._subplots.AxesSubplot at 0x2b946b1c1630>






    

In [4]:

    

trajs = Trajectories(data.directed_trajectories_generator())
trajs.show(groupby_args={'by': 'true_label'})


    

    
Out[4]:





<matplotlib.axes._subplots.AxesSubplot at 0x2b946b19bfd0>






    

In [5]:

    

tf = TiffFile(data.CZT_peaks())
arr = tf.asarray()
print("Shape is :", arr.shape)

a = arr[0, 0, 0]
plt.imshow(a, interpolation='none', cmap='gray')


    

    




Shape is : (1, 4, 4, 48, 56)






    
Out[5]:





<matplotlib.image.AxesImage at 0x2b946b360f60>






    

In [44]:

    

df = pd.HDFStore(data.sample_h5())
print(df.keys())
print(df['metadata'])


    

    




['/metadata', '/objects']
SizeT                             5
TimeIncrement                     3
DimensionOrder                 TZYX
Type                        unint16
PysicalSizeX                   0.43
PysicalSizeY                   0.43
PysicalSizeZ                    1.5
SizeX                           512
SizeY                           512
SizeZ                            23
FileName             sample.ome.tif
Shape             (512, 512, 23, 5)
dtype: object

In [ ]:

    

# Run this cell first.
%load_ext autoreload
%autoreload 2