Added chk input demo code

demo/chk_horz_inp.py

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+import numpy as np
+from PIL import Image #To read images in TIFF format
+from pysaber import get_trans_masks #To compute transmission function and masks
+import matplotlib.pyplot as plt #To display images
+
+pix_wid = 0.675 #Width of each pixel in micrometers
+
+#Read a horizontal edge radiograph for which the transmission function must be computed
+rad = Image.open('data/horz_edge_25mm.tif') #Read radiograph
+rad = np.asarray(rad) #Convert to numpy array
+bright = Image.open('data/horz_bright.tif') #Read bright field
+bright = np.asarray(bright) #Convert to numpy array
+dark = Image.open('data/horz_dark.tif') #Read dark field
+dark = np.asarray(dark) #Convert to numpy array
+nrad = (rad-dark)/(bright-dark) #Normalize radiograph
+
+#Get the transmission function and masks 
+trans,trans_mask,rad_mask = get_trans_masks(nrad,edge='straight',pad=[3,3])
+#Use pad = [1,1] if you do not want padding
+
+#Display the array trans
+#Visually check for inaccurate localization of the sharp-edge
+plt.imshow(trans,cmap='gray')
+plt.colorbar()
+plt.show()
+
+#Display and inspect the mask for transmission function
+plt.imshow(trans_mask,cmap='gray')
+plt.show()
+
+#Display and inspect the mask for radiograph
+plt.imshow(rad_mask,cmap='gray')
+plt.show()
+
+#Show a line plot comparing the measured radiograph and transmission function
+sz = nrad.shape
+coords = np.arange(-(sz[0]//2),sz[0]//2,1)*pix_wid
+mid = (trans.shape[0]//2,trans.shape[1]//2)
+
+plt.plot(coords,nrad[:,sz[1]//2])
+#Due to padding, trans is three times the size of nrad in each dimension
+#For proper alignment in the presence of padding, both nrad and trans are center aligned
+#Center alignment is used since an equal amount of padding is applied at both ends of each axis
+plt.plot(coords,trans[mid[0]-(sz[0]//2):mid[0]+(sz[0]//2),mid[1]])
+plt.xlabel('micrometers')
+plt.legend(['Measured','Transmission'])
+plt.show()

demo/chk_vert_inp.py

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+import numpy as np
+from PIL import Image #To read images in TIFF format
+from pysaber import get_trans_masks #To compute transmission function and masks
+import matplotlib.pyplot as plt #To display images
+
+pix_wid = 0.675 #Width of each pixel in micrometers
+
+#Read a vertical edge radiograph for which the transmission function must be computed
+rad = Image.open('data/vert_edge_25mm.tif') #Read radiograph
+rad = np.asarray(rad) #Convert to numpy array 
+bright = Image.open('data/vert_bright.tif') #Read bright field
+bright = np.asarray(bright) #Convert to numpy array
+dark = Image.open('data/vert_dark.tif') #Read dark field
+dark = np.asarray(dark) #Convert to numpy array
+nrad = (rad-dark)/(bright-dark) #Normalize radiograph
+
+#Get the transmission function and masks 
+trans,trans_mask,rad_mask = get_trans_masks(nrad,edge='straight',pad=[3,3])
+#Use pad = [1,1] if you do not want padding
+
+#Display the array trans
+#Visually check for inaccurate localization of the sharp-edge
+plt.imshow(trans,cmap='gray')
+plt.colorbar()
+plt.show()
+
+#Display and inspect the mask for transmission function
+plt.imshow(trans_mask,cmap='gray')
+plt.show()
+
+#Display and inspect the mask for radiograph
+plt.imshow(rad_mask,cmap='gray')
+plt.show()
+
+#Show a line plot comparing the measured radiograph and transmission function
+sz = nrad.shape
+coords = np.arange(-(sz[1]//2),sz[1]//2,1)*pix_wid
+mid = (trans.shape[0]//2,trans.shape[1]//2)
+
+plt.plot(coords,nrad[sz[0]//2,:])
+#Due to padding, trans is three times the size of nrad in each dimension
+#For proper alignment in the presence of padding, both nrad and trans are center aligned
+#Center alignment is used since an equal amount of padding is applied at both ends of each axis
+plt.plot(coords,trans[mid[0],mid[1]-(sz[1]//2):mid[1]+(sz[1]//2)])
+plt.xlabel('micrometers')
+plt.legend(['Measured','Transmission'])
+plt.show()