In [2]:

    

from photutils import Background2D, SigmaClip, MedianBackground

from skimage import color
from skimage import exposure

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline


    

In [4]:

    

afmdata = np.genfromtxt('../NaRWHAL/Data/UnbackgroundedTXT/500nmGood-0')
afmdata= afmdata*(10**9)
height, width = afmdata.shape


    

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plt.matshow(afmdata, origin='lower', cmap = 'viridis')


    

    
Out[5]:





<matplotlib.image.AxesImage at 0x113b47400>






    

In [6]:

    

sigma_clip = SigmaClip(sigma=3., iters=10)
bkg_estimator = MedianBackground()
bkg = Background2D(afmdata, (50, 50), filter_size=(3, 3), sigma_clip=sigma_clip, bkg_estimator=bkg_estimator)


    

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plt.matshow(bkg.background, origin='lower', cmap = 'viridis')


    

    
Out[7]:





<matplotlib.image.AxesImage at 0x113be6390>






    

In [8]:

    

plt.matshow(afmdata - bkg.background, origin='lower', cmap = 'viridis')


    

    
Out[8]:





<matplotlib.image.AxesImage at 0x113c599b0>






    

In [9]:

    

### This is the Backgrounded image shown two frames up. The frame below is super pale because I'm working
### on the histogram normalization

backgrounded = afmdata - bkg.background
plt.matshow(backgrounded, origin = 'lower', cmap = 'viridis')


    

    
Out[9]:





<matplotlib.image.AxesImage at 0x113a85710>






    

In [11]:

    

sigma_clip = SigmaClip(sigma=3., iters=10)
bkg_estimator = MedianBackground()
bkg1 = Background2D(backgrounded, (50, 50), filter_size=(3, 3), sigma_clip=sigma_clip, bkg_estimator=bkg_estimator)


    

In [12]:

    

plt.matshow(bkg1.background, origin='lower', cmap = 'viridis')


    

    
Out[12]:





<matplotlib.image.AxesImage at 0x11277a438>






    

In [13]:

    

plt.matshow(backgrounded - bkg1.background, origin='lower', cmap = 'viridis')


    

    
Out[13]:





<matplotlib.image.AxesImage at 0x110777160>






    

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fig = plt.figure(figsize = (8, 8))

fig.add_subplot(131)
plt.matshow(afmdata, origin = 'lower', cmap = 'viridis')
plt.title('Raw Data File')

fig.add_subplot(132)
plt.matshow(backgrounded, origin = 'lower', cmap = 'viridis')
plt.title('Backgounded')

plt.show()


    

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