adding gridrec.py

.gitignore

+_data/
\ No newline at end of file

README.md

@@ -2,6 +2,8 @@
 
 ## Tomopy
 
+![coil_tomopy_recon](images/coil_tomopy_recon.gif)
+
 ### Gridrec
 * parallel beam
 

gridrec.py

+
+# coding: utf-8
+
+# ## Gridrec
+# 
+# Here is an example on how to use [TomoPy](http://tomopy.readthedocs.io/en/latest/) with the gridrec algorithm.
+# 
+# [user manual](https://media.readthedocs.org/pdf/tomopy/latest/tomopy.pdf)
+
+# In[3]:
+
+
+# get_ipython().run_line_magic('pylab', 'inline')
+
+
+# In[4]:
+
+
+import tomopy
+import dxchange
+import numpy as np
+import matplotlib.pyplot as plt
+import ipyvolume as ipv
+
+
+if __name__ == '__main__':
+
+	haveLoaded = False
+
+	if (haveLoaded):
+		print("loading projection data...")
+		proj = np.load("projection_data.npy")
+	else:
+		print("loading angle data...")
+		ctdata = np.loadtxt("test_scan_250/_ctdata.txt",skiprows=3)
+		theta = np.deg2rad(ctdata[:,1])
+
+		fname = '_data/test_scan_250/test scan 250_0001.tif'
+
+		print("loading tiff stack...")
+		indices = [i for i in range(1,752)]
+		data = dxchange.read_tiff_stack(fname, indices)
+		print(np.shape(data))
+
+		# downsample and minus log
+		print("downsampling and taking minus log...")
+		proj = tomopy.minus_log(data[::1,::8,::8])
+		print(np.shape(proj))
+
+		print("saving projection data...")
+		np.save('projection_data',proj)
+
+	rot_center = proj.shape[2]/2
+
+	# gridrec
+	print("running reconstruction...")
+	rec = tomopy.recon(proj,theta,sinogram_order=False,
+	                   center=rot_center,algorithm='art')
+
+	# LPrec (not working)
+	# rec = tomopy.recon(proj, theta, center=rot_center, 
+	#                    algorithm=tomopy.lprec, lpmethod='lpfbp', 
+	#                    filter_name='parzen')
+
+	# ASTRA (not working)
+	options = {'proj_type':'linear', 'method':'FBP'}
+	rec = tomopy.recon(proj, theta, center=rot_center, 
+	                     algorithm=tomopy.astra, options=options)
+
+	print("applying circular mask...")
+	rec = tomopy.circ_mask(rec, axis=0, ratio=0.75)
+
+	print("saving data to reconstruction_data.npy...")
+	np.save('reconstruction_data',rec)
+
+	# use jupyter notebook to visualize results
+
+	# print("visualizing...")
+	# ipv.figure()
+	# vol = ipv.volshow(rec)
+	# ipv.show()
+