removed src dir

1 files changed, 0 insertions, 168 deletions

diff --git a/src/Python/demo/demo_dendrites.py b/src/Python/demo/demo_dendrites.py
deleted file mode 100644
index f5dc845..0000000
--- a/src/Python/demo/demo_dendrites.py
+++ /dev/null
@@ -1,168 +0,0 @@
-
-# -*- coding: utf-8 -*-
-"""
-Created on Wed Aug 23 16:34:49 2017
-
-@author: ofn77899
-Based on DemoRD2.m
-"""
-
-import h5py
-import numpy
-
-from ccpi.reconstruction.FISTAReconstructor import FISTAReconstructor
-import astra
-import matplotlib.pyplot as plt
-from ccpi.imaging.Regularizer import Regularizer
-from ccpi.reconstruction.AstraDevice import AstraDevice
-from ccpi.reconstruction.DeviceModel import DeviceModel
-
-def RMSE(signal1, signal2):
-    '''RMSE Root Mean Squared Error'''
-    if numpy.shape(signal1) == numpy.shape(signal2):
-        err = (signal1 - signal2)
-        err = numpy.sum( err * err )/numpy.size(signal1);  # MSE
-        err = sqrt(err);                                   # RMSE
-        return err
-    else:
-        raise Exception('Input signals must have the same shape')
-  
-filename = r'/home/ofn77899/Reconstruction/CCPi-FISTA_Reconstruction/demos/DendrData.h5'
-nx = h5py.File(filename, "r")
-#getEntry(nx, '/')
-# I have exported the entries as children of /
-entries = [entry for entry in nx['/'].keys()]
-print (entries)
-
-Sino3D = numpy.asarray(nx.get('/Sino3D'), dtype="float32")
-Weights3D = numpy.asarray(nx.get('/Weights3D'), dtype="float32")
-angSize = numpy.asarray(nx.get('/angSize'), dtype=int)[0]
-angles_rad = numpy.asarray(nx.get('/angles_rad'), dtype="float32")
-recon_size = numpy.asarray(nx.get('/recon_size'), dtype=int)[0]
-size_det = numpy.asarray(nx.get('/size_det'), dtype=int)[0]
-slices_tot = numpy.asarray(nx.get('/slices_tot'), dtype=int)[0]
-
-Z_slices = 20
-det_row_count = Z_slices
-# next definition is just for consistency of naming
-det_col_count = size_det
-
-detectorSpacingX = 1.0
-detectorSpacingY = detectorSpacingX
-
-
-proj_geom = astra.creators.create_proj_geom('parallel3d',
-                                            detectorSpacingX,
-                                            detectorSpacingY,
-                                            det_row_count,
-                                            det_col_count,
-                                            angles_rad)
-
-#vol_geom = astra_create_vol_geom(recon_size,recon_size,Z_slices);
-image_size_x = recon_size
-image_size_y = recon_size
-image_size_z = Z_slices
-vol_geom = astra.creators.create_vol_geom( image_size_x,
-                                           image_size_y,
-                                           image_size_z)
-
-
-## Create a Acquisition Device Model
-## Must specify some parameters of the acquisition:
-
-astradevice = AstraDevice(
-                DeviceModel.DeviceType.PARALLEL3D.value,
-                [det_row_count , det_col_count ,
-                 detectorSpacingX, detectorSpacingY ,
-                 angles_rad
-                 ],
-                [ image_size_x, image_size_y, image_size_z ] )
-
-fistaRecon = FISTAReconstructor(proj_geom,
-                            vol_geom,
-                            Sino3D ,
-                            weights=Weights3D,
-                            device=astradevice,
-                            Lipschitz_constant = 767893952.0,
-                            subsets = 8)
-
-print("Reconstruction using FISTA-OS-PWLS without regularization...")
-fistaRecon.setParameter(number_of_iterations = 5)
-
-### adjust the regularization parameter
-##lc = fistaRecon.getParameter('Lipschitz_constant')
-##fistaRecon.getParameter('regularizer')\
-##             .setParameter(regularization_parameter=5e6/lc)
-fistaRecon.use_device = True
-if True:
-    fistaRecon.prepareForIteration()
-    X = fistaRecon.iterate(numpy.load("../test/X.npy"))
-    numpy.save("FISTA-OS-PWLS.npy",X)
-
-## setup a regularizer algorithm
-regul = Regularizer(Regularizer.Algorithm.FGP_TV)
-regul.setParameter(regularization_parameter=5e6,
-                   number_of_iterations=50,
-                   tolerance_constant=1e-4,
-                   TV_penalty=Regularizer.TotalVariationPenalty.isotropic)
-if False:
-    # adjust the regularization parameter
-    lc = fistaRecon.getParameter('Lipschitz_constant')
-    regul.setParameter(regularization_parameter=5e6/lc)
-    fistaRecon.setParameter(regularizer=regul)
-    fistaRecon.prepareForIteration()
-    X = fistaRecon.iterate(numpy.load("../test/X.npy"))
-    numpy.save("FISTA-OS-PWLS-TV.npy",X)
-
-if False:
-    # adjust the regularization parameter
-    lc = fistaRecon.getParameter('Lipschitz_constant')
-    regul.setParameter(regularization_parameter=5e6/lc)
-    fistaRecon.setParameter(regularizer=regul)
-    fistaRecon.setParameter(ring_lambda_R_L1=0.002, ring_alpha=21)
-    fistaRecon.prepareForIteration()
-    X = fistaRecon.iterate(numpy.load("../test/X.npy"))
-    numpy.save("FISTA-OS-GH-TV.npy",X)
-
-if False:
-    # adjust the regularization parameter
-    lc = fistaRecon.getParameter('Lipschitz_constant')
-    regul.setParameter(
-        algorithm=Regularizer.Algorithm.TGV_PD,
-        regularization_parameter=0.5/lc,
-        number_of_iterations=5)
-    fistaRecon.setParameter(regularizer=regul)
-    fistaRecon.setParameter(ring_lambda_R_L1=0.002, ring_alpha=21)
-    fistaRecon.prepareForIteration()
-    X = fistaRecon.iterate(numpy.load("../test/X.npy"))
-    numpy.save("FISTA-OS-GH-TGV.npy",X)
-    
-if False:
-    # adjust the regularization parameter
-    lc = fistaRecon.getParameter('Lipschitz_constant')
-    regul.setParameter(
-        algorithm=Regularizer.Algorithm.PatchBased_Regul,
-        regularization_parameter=3/lc,
-        searching_window_ratio=3,
-        similarity_window_ratio=1,
-        PB_filtering_parameter=0.04
-        
-        )
-    fistaRecon.setParameter(regularizer=regul)
-    fistaRecon.setParameter(ring_lambda_R_L1=0.002, ring_alpha=21)
-    fistaRecon.prepareForIteration()
-    X = fistaRecon.iterate(numpy.load("../test/X.npy"))
-    numpy.save("FISTA-OS-CPU_PB.npy",X)
-
-if False:
-    fistaRecon = FISTAReconstructor(proj_geom,
-                            vol_geom,
-                            Sino3D ,
-                            weights=Weights3D,
-                            device=astradevice,
-                            Lipschitz_constant = 7.6792e8,
-                            number_of_iterations=50)
-
-    fistaRecon.prepareForIteration()
-    X = fistaRecon.iterate(numpy.load("../test/X.npy"))
-    numpy.save("FISTA.npy",X)