In [1]:

    

%pylab inline


    

    




Populating the interactive namespace from numpy and matplotlib

In [5]:

    

%run ../common.ipynb


    

    




Populating the interactive namespace from numpy and matplotlib
Matlab usage:

    %%matlab
    a = 1

or
    results = mlab.run_code('a=1;')

or

    res = mlab.run_func('path/to/function.m', {'arg1': 3, 'arg2': 5})

See https://github.com/arokem/python-matlab-bridge#usage for more details.







    




WARNING: pylab import has clobbered these variables: ['mlab', 'imshow', 'imread', 'imsave']
`%matplotlib` prevents importing * from pylab and numpy

In [6]:

    

images = imread('sample.tif')


    

In [7]:

    

images.shape


    

    
Out[7]:





(3, 3846, 3875)

In [8]:

    

for img in images:
    imshow(img)


    

In [9]:

    

img1 = images[1];


    

In [10]:

    

img1[100:110,100:110]


    

    
Out[10]:





array([[ 6,  6,  0,  6,  0, 20,  6,  0,  6,  6],
       [ 0,  6, 13,  0,  6, 13,  0,  6,  6,  0],
       [ 0,  6,  6,  0,  6,  0,  0,  0,  6,  0],
       [ 6,  6, 13,  0,  0,  0, 13,  6, 13,  0],
       [ 6,  6, 13,  6,  6,  0,  0,  0,  0, 13],
       [ 0, 13,  6,  0,  0,  0,  6, 26,  6,  0],
       [ 0,  6,  6, 20,  6,  0,  0,  6, 20, 13],
       [ 6,  6,  0, 20,  6, 13,  0, 13,  0,  0],
       [ 0,  0,  0, 13,  0,  6, 13,  6,  0,  6],
       [ 6,  0, 13,  6,  0,  0,  6,  0,  6,  6]], dtype=uint8)

In [11]:

    

imshow(img1, cmap='gray')


    

    
Out[11]:





(<matplotlib.figure.Figure at 0x10ef35990>,
 <matplotlib.axes._subplots.AxesSubplot at 0x124eac490>,
 <matplotlib.image.AxesImage at 0x124eae2d0>)






    

In [12]:

    

img1.max()


    

    
Out[12]:





255

In [13]:

    

img1.var()


    

    
Out[13]:





1335.7627316724995

In [14]:

    

img1.mean()


    

    
Out[14]:





35.804770771476022

In [15]:

    

img1[img1 < 10] = 0


    

In [16]:

    

imshow(img)


    

    
Out[16]:





(<matplotlib.figure.Figure at 0x116af7d90>,
 <matplotlib.axes._subplots.AxesSubplot at 0x116ae5550>,
 <matplotlib.image.AxesImage at 0x116b18590>)






    

In [19]:

    

def f(n):
    temp = np.copy(img1)
    temp[temp < n] = 0
    imshow(temp)


    

In [20]:

    

interact(f, n=(0,255,1))


    

In [21]:

    

histshow(img1)


    

In [ ]: