In [2]:

    

import matplotlib.pyplot as plt
import numpy as np


    

In [3]:

    

%matplotlib inline


    

In [7]:

    

full_data = np.load("../data/combined_runs.npy")


    

In [10]:

    

full_data.shape


    

    
Out[10]:





(132, 175, 48, 3543)

In [5]:

    

mask50k = np.load("../brain_mask/sm_mask55468.npy")


    

In [7]:

    

mask50k.shape


    

    
Out[7]:





(1108800,)

In [8]:

    

mask50k


    

    
Out[8]:





array([False, False, False, ..., False, False, False], dtype=bool)

In [10]:

    

~mask50k


    

    
Out[10]:





array([ True,  True,  True, ...,  True,  True,  True], dtype=bool)

In [ ]:

    

mask50k_3d = mask50k.reshape((full_data.shape[0],full_data.shape[1],full_data.shape[2]))


    

In [19]:

    

mask50k_3d.shape


    

    
Out[19]:





(1108800,)

In [22]:

    

mask17k = np.load("../brain_mask/sm_mask17887.npy")
mask17k_3d = mask17k.reshape((full_data.shape[0],full_data.shape[1],full_data.shape[2]))


    

In [23]:

    

mask9k = np.load("../brain_mask/sm_mask9051.npy")
mask9k_3d = mask9k.reshape((full_data.shape[0],full_data.shape[1],full_data.shape[2]))


    

In [24]:

    

masked_data_50k = full_data[mask50k_3d,:]
np.save("../data/masked_data_50k.npy",masked_data_50k)


    

In [25]:

    

masked_data_50k.shape


    

    
Out[25]:





(55468, 3543)

In [28]:

    

masked_data_17k = full_data[mask17k_3d,:]
np.save("../data/masked_data_17k.npy",masked_data_17k)


    

In [29]:

    

masked_data_9k = full_data[mask9k_3d,:]
np.save("../data/masked_data_9k.npy",masked_data_9k)


    

In [ ]: