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import sys
sys.path.insert(0, '../functions/')


    

In [51]:

    

from skimage.filters import threshold_otsu
import tiffIO as tIO
import mouseVis as mv
import plosLib as pLib
import connectLib as cLib
import matplotlib.pyplot as plt
import numpy as np
import cv2


    

In [52]:

    

#load the data
data0 = tIO.unzipChannels(tIO.loadTiff('../../data/SEP-GluA1-KI_tp1.tif'))[0][0:5]


    

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#generate a foreground probability map for the data
probVox = pLib.pipeline(data0)


    

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#generate a histogram to show bimodlity of the foreground probs
mv.generateVoxHist(probVox, figName='Distribution of Probabilities')
plt.show()


    

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#get the otsu binarization of the probability voxel
bianVox = cLib.otsuVox(probVox)


    

In [49]:

    

#get the connected components of the binary supervoxel
connectedComponents = cLib.connectedComponents(bianVox)


    

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plt.imshow(connectedComponents[2])
plt.show()


    

In [33]:

    

sizeHistCounts = np.bincount(np.ndarray.flatten(connectedComponents[2]))


    

In [44]:

    

plt.hist(sizeHistCounts, bins=len(sizeHistCounts), range=[0, 100])
plt.show()


    

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