diff options
| -rwxr-xr-x | Wrappers/Python/wip/test_reader_reconstr.py | 198 |
1 files changed, 198 insertions, 0 deletions
diff --git a/Wrappers/Python/wip/test_reader_reconstr.py b/Wrappers/Python/wip/test_reader_reconstr.py new file mode 100755 index 0000000..33ab461 --- /dev/null +++ b/Wrappers/Python/wip/test_reader_reconstr.py @@ -0,0 +1,198 @@ +# -*- coding: utf-8 -*-
+"""
+Created on Wed Mar 21 14:26:21 2018
+
+@author: ofn77899
+"""
+
+from ccpi.framework import ImageData , AcquisitionData, ImageGeometry, AcquisitionGeometry
+from ccpi.reconstruction.algs import FISTA, FBPD, CGLS
+from ccpi.reconstruction.funcs import Norm2sq, Norm1
+from ccpi.reconstruction.ops import CCPiProjectorSimple
+from ccpi.reconstruction.parallelbeam import alg as pbalg
+from ccpi.processors import CCPiForwardProjector, CCPiBackwardProjector , \
+Normalizer , CenterOfRotationFinder , AcquisitionDataPadder
+
+from ccpi.io.reader import NexusReader
+
+import numpy
+import matplotlib.pyplot as plt
+
+import os
+
+def add_dimension(data, fill_with, axis, start=True):
+ delta = data.shape[data.get_dimension_axis(axis)] - fill_with.shape[fill_with.get_dimension_axis(axis)]
+ command = 'data.array['
+ i = 0
+ for k,v in data.dimension_labels.items():
+ if axis == v:
+ if start:
+ command = command + str(delta) + ":"
+ else:
+ l = data.get_dimension_size(axis) - delta
+ command = command + "0:" + str(l)
+ else:
+ command = command + ":"
+
+ if i < data.number_of_dimensions -1:
+ command = command + ','
+ i += 1
+ command = command + "] = fill_with.array[:]"
+ #print (command)
+ exec(command)
+ #return command
+
+
+def avg_img(image):
+ shape = list(numpy.shape(image))
+ l = shape.pop(0)
+ avg = numpy.zeros(shape)
+ for i in range(l):
+ avg += image[i] / l
+ return avg
+
+def setupCCPiGeometries(voxel_num_x, voxel_num_y, voxel_num_z, angles, counter):
+ vg = ImageGeometry(voxel_num_x=voxel_num_x,voxel_num_y=voxel_num_y, voxel_num_z=voxel_num_z)
+ Phantom_ccpi = ImageData(geometry=vg,
+ dimension_labels=['horizontal_x','horizontal_y','vertical'])
+ #.subset(['horizontal_x','horizontal_y','vertical'])
+ # ask the ccpi code what dimensions it would like
+
+ voxel_per_pixel = 1
+ geoms = pbalg.pb_setup_geometry_from_image(Phantom_ccpi.as_array(),
+ angles,
+ voxel_per_pixel )
+
+ pg = AcquisitionGeometry('parallel',
+ '3D',
+ angles,
+ geoms['n_h'], 1,
+ geoms['n_v'], 1 #2D in 3D is a slice 1 pixel thick
+ )
+
+ center_of_rotation = Phantom_ccpi.get_dimension_size('horizontal_x') / 2
+ ad = AcquisitionData(geometry=pg,dimension_labels=['angle','vertical','horizontal'])
+ geoms_i = pbalg.pb_setup_geometry_from_acquisition(ad.as_array(),
+ angles,
+ center_of_rotation,
+ voxel_per_pixel )
+
+ #print (counter)
+ counter+=1
+ #print (geoms , geoms_i)
+ if counter < 4:
+ if (not ( geoms_i == geoms )):
+ print ("not equal and {0}".format(counter))
+ X = max(geoms['output_volume_x'], geoms_i['output_volume_x'])
+ Y = max(geoms['output_volume_y'], geoms_i['output_volume_y'])
+ Z = max(geoms['output_volume_z'], geoms_i['output_volume_z'])
+ return setupCCPiGeometries(X,Y,Z,angles, counter)
+ else:
+ print ("return geoms {0}".format(geoms))
+ return geoms
+ else:
+ print ("return geoms_i {0}".format(geoms_i))
+ return geoms_i
+
+reader = NexusReader(os.path.join(".." ,".." ,".." , "data" , "24737_fd.nxs" ))
+
+dims = reader.get_projection_dimensions()
+print (dims)
+
+flat = avg_img(reader.load_flat())
+dark = avg_img(reader.load_dark())
+
+data = reader.getAcquisitionData()
+norm = Normalizer(flat_field=flat, dark_field=dark)
+
+norm.set_input(reader.getAcquisitionData())
+
+cor = CenterOfRotationFinder()
+cor.set_input(norm.get_output())
+center_of_rotation = cor.get_output()
+voxel_per_pixel = 1
+
+padder = AcquisitionDataPadder(center_of_rotation=center_of_rotation)
+padder.set_input(norm.get_output())
+padded_data = padder.get_output()
+
+pg = padded_data.geometry
+geoms = pbalg.pb_setup_geometry_from_acquisition(padded_data.as_array(),
+ pg.angles,
+ center_of_rotation,
+ voxel_per_pixel )
+vg = ImageGeometry(voxel_num_x=geoms['output_volume_x'],
+ voxel_num_y=geoms['output_volume_y'],
+ voxel_num_z=geoms['output_volume_z'])
+#data = numpy.reshape(reader.getAcquisitionData())
+print ("define projector")
+Cop = CCPiProjectorSimple(vg, pg)
+# Create least squares object instance with projector and data.
+print ("Create least squares object instance with projector and data.")
+f = Norm2sq(Cop,padded_data,c=0.5)
+print ("Initial guess")
+# Initial guess
+x_init = ImageData(geometry=vg, dimension_labels=['horizontal_x','horizontal_y','vertical'])
+#invL = 0.5
+#g = f.grad(x_init)
+#print (g)
+#u = x_init - invL*f.grad(x_init)
+
+#%%
+print ("run FISTA")
+# Run FISTA for least squares without regularization
+opt = {'tol': 1e-4, 'iter': 10}
+x_fista0, it0, timing0, criter0 = FISTA(x_init, f, None, opt=opt)
+
+plt.imshow(x_fista0.subset(horizontal_x=80).array)
+plt.title('FISTA0')
+plt.show()
+
+# Now least squares plus 1-norm regularization
+lam = 0.1
+g0 = Norm1(lam)
+
+# Run FISTA for least squares plus 1-norm function.
+x_fista1, it1, timing1, criter1 = FISTA(x_init, f, g0,opt=opt)
+
+plt.imshow(x_fista0.subset(horizontal_x=80).array)
+plt.title('FISTA1')
+plt.show()
+
+plt.semilogy(criter1)
+plt.show()
+
+# Run FBPD=Forward Backward Primal Dual method on least squares plus 1-norm
+x_fbpd1, it_fbpd1, timing_fbpd1, criter_fbpd1 = FBPD(x_init,None,f,g0,opt=opt)
+
+plt.imshow(x_fbpd1.subset(horizontal_x=80).array)
+plt.title('FBPD1')
+plt.show()
+
+plt.semilogy(criter_fbpd1)
+plt.show()
+
+# Now FBPD for least squares plus TV
+#lamtv = 1
+#gtv = TV2D(lamtv)
+
+#x_fbpdtv, it_fbpdtv, timing_fbpdtv, criter_fbpdtv = FBPD(x_init,None,f,gtv,opt=opt)
+
+#plt.imshow(x_fbpdtv.subset(vertical=0).array)
+#plt.show()
+
+#plt.semilogy(criter_fbpdtv)
+#plt.show()
+
+
+# Run CGLS, which should agree with the FISTA0
+x_CGLS, it_CGLS, timing_CGLS, criter_CGLS = CGLS(x_init, Cop, padded_data, opt=opt)
+
+plt.imshow(x_CGLS.subset(horizontal_x=80).array)
+plt.title('CGLS')
+plt.title('CGLS recon, compare FISTA0')
+plt.show()
+
+plt.semilogy(criter_CGLS)
+plt.title('CGLS criterion')
+plt.show()
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