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-rw-r--r--src/Python/test_reconstructor-os.py379
1 files changed, 379 insertions, 0 deletions
diff --git a/src/Python/test_reconstructor-os.py b/src/Python/test_reconstructor-os.py
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+# -*- coding: utf-8 -*-
+"""
+Created on Wed Aug 23 16:34:49 2017
+
+@author: ofn77899
+Based on DemoRD2.m
+"""
+
+import h5py
+import numpy
+
+from ccpi.fista.FISTAReconstructor import FISTAReconstructor
+import astra
+import matplotlib.pyplot as plt
+
+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)
+
+## First pass the arguments to the FISTAReconstructor and test the
+## Lipschitz constant
+
+fistaRecon = FISTAReconstructor(proj_geom,
+ vol_geom,
+ Sino3D ,
+ weights=Weights3D)
+
+print ("Lipschitz Constant {0}".format(fistaRecon.pars['Lipschitz_constant']))
+fistaRecon.setParameter(number_of_iterations = 12)
+fistaRecon.setParameter(Lipschitz_constant = 767893952.0)
+fistaRecon.setParameter(ring_alpha = 21)
+fistaRecon.setParameter(ring_lambda_R_L1 = 0.002)
+
+## Ordered subset
+if True:
+ subsets = 16
+ angles = fistaRecon.getParameter('projector_geometry')['ProjectionAngles']
+ #binEdges = numpy.linspace(angles.min(),
+ # angles.max(),
+ # subsets + 1)
+ binsDiscr, binEdges = numpy.histogram(angles, bins=subsets)
+ # get rearranged subset indices
+ IndicesReorg = numpy.zeros((numpy.shape(angles)))
+ counterM = 0
+ for ii in range(binsDiscr.max()):
+ counter = 0
+ for jj in range(subsets):
+ curr_index = ii + jj + counter
+ #print ("{0} {1} {2}".format(binsDiscr[jj] , ii, counterM))
+ if binsDiscr[jj] > ii:
+ if (counterM < numpy.size(IndicesReorg)):
+ IndicesReorg[counterM] = curr_index
+ counterM = counterM + 1
+
+ counter = counter + binsDiscr[jj] - 1
+
+
+if True:
+ print ("Lipschitz Constant {0}".format(fistaRecon.pars['Lipschitz_constant']))
+ print ("prepare for iteration")
+ fistaRecon.prepareForIteration()
+
+
+
+ print("initializing ...")
+ if False:
+ # if X doesn't exist
+ #N = params.vol_geom.GridColCount
+ N = vol_geom['GridColCount']
+ print ("N " + str(N))
+ X = numpy.zeros((N,N,SlicesZ), dtype=numpy.float)
+ else:
+ #X = fistaRecon.initialize()
+ X = numpy.load("X.npy")
+
+ print (numpy.shape(X))
+ X_t = X.copy()
+ print ("initialized")
+ proj_geom , vol_geom, sino , \
+ SlicesZ = fistaRecon.getParameter(['projector_geometry' ,
+ 'output_geometry',
+ 'input_sinogram',
+ 'SlicesZ'])
+
+ #fistaRecon.setParameter(number_of_iterations = 3)
+ iterFISTA = fistaRecon.getParameter('number_of_iterations')
+ # errors vector (if the ground truth is given)
+ Resid_error = numpy.zeros((iterFISTA));
+ # objective function values vector
+ objective = numpy.zeros((iterFISTA));
+
+
+ t = 1
+
+ ## additional for
+ proj_geomSUB = proj_geom.copy()
+ fistaRecon.residual2 = numpy.zeros(numpy.shape(self.pars['input_sinogram']))
+ print ("starting iterations")
+## % Outer FISTA iterations loop
+ for i in range(fistaRecon.getParameter('number_of_iterations')):
+## % With OS approach it becomes trickier to correlate independent subsets, hence additional work is required
+## % one solution is to work with a full sinogram at times
+## if ((i >= 3) && (lambdaR_L1 > 0))
+## [sino_id2, sino_updt2] = astra_create_sino3d_cuda(X, proj_geom, vol_geom);
+## astra_mex_data3d('delete', sino_id2);
+## end
+ # With OS approach it becomes trickier to correlate independent subsets,
+ # hence additional work is required one solution is to work with a full
+ # sinogram at times
+
+ ## https://github.com/vais-ral/CCPi-FISTA_Reconstruction/issues/4
+ if (lambdaR_L1 > 0) :
+ sino_id2, sino_updt2 = astra.creators.create_sino3d_gpu(
+ X, proj_geom, vol_geom)
+ astra.matlab.data3d('delete', sino_id2)
+
+ # subset loop
+ counterInd = 1
+ for ss in range(fistaRecon.getParameter('subsets')):
+ print ("Subset {0}".format(ss))
+ X_old = X.copy()
+ t_old = t
+ r_old = fistaRecon.r.copy()
+
+ # the number of projections per subset
+ numProjSub = fistaRecon.getParameter('os_bins')[ss]
+ CurrSubIndices = fistaRecon.getParameter('os_indices')\
+ [counterInd:counterInd+numProjSub-1]
+ proj_geomSUB['ProjectionAngles'] = angles[CurrSubIndeces]
+
+## if fistaRecon.getParameter('projector_geometry')['type'] == 'parallel' or \
+## fistaRecon.getParameter('projector_geometry')['type'] == 'fanflat' or \
+## fistaRecon.getParameter('projector_geometry')['type'] == 'fanflat_vec' :
+## # if the geometry is parallel use slice-by-slice
+## # projection-backprojection routine
+## #sino_updt = zeros(size(sino),'single');
+## proj_geomT = proj_geom.copy()
+## proj_geomT['DetectorRowCount'] = 1
+## vol_geomT = vol_geom.copy()
+## vol_geomT['GridSliceCount'] = 1;
+## sino_updt = numpy.zeros(numpy.shape(sino), dtype=numpy.float)
+## for kkk in range(SlicesZ):
+## sino_id, sino_updt[kkk] = \
+## astra.creators.create_sino3d_gpu(
+## X_t[kkk:kkk+1], proj_geom, vol_geom)
+## astra.matlab.data3d('delete', sino_id)
+## else:
+## # for divergent 3D geometry (watch the GPU memory overflow in
+## # ASTRA versions < 1.8)
+## #[sino_id, sino_updt] = astra_create_sino3d_cuda(X_t, proj_geom, vol_geom);
+## sino_id, sino_updt = astra.creators.create_sino3d_gpu(
+## X_t, proj_geom, vol_geom)
+
+ ## RING REMOVAL
+ residual = fistaRecon.residual
+ residual2 = fistaRecon.residual2
+
+ lambdaR_L1 , alpha_ring , weights , L_const= \
+ fistaRecon.getParameter(['ring_lambda_R_L1',
+ 'ring_alpha' , 'weights',
+ 'Lipschitz_constant'])
+ r_x = fistaRecon.r_x
+ SlicesZ, anglesNumb, Detectors = \
+ numpy.shape(fistaRecon.getParameter('input_sinogram'))
+ if lambdaR_L1 > 0 :
+ print ("ring removal")
+## % the ring removal part (Group-Huber fidelity)
+## % first 2 iterations do additional work reconstructing whole dataset to ensure
+## % the stablility
+## if (i < 3)
+## [sino_id2, sino_updt2] = astra_create_sino3d_cuda(X_t, proj_geom, vol_geom);
+## astra_mex_data3d('delete', sino_id2);
+## else
+## [sino_id, sino_updt] = astra_create_sino3d_cuda(X_t, proj_geomSUB, vol_geom);
+## end
+
+## https://github.com/vais-ral/CCPi-FISTA_Reconstruction/issues/4
+ if i < 3:
+ pass
+ else:
+ sino_id, sino_updt = astra.creators.create_sino3d_gpu(
+ X_t, proj_geomSUB, vol_geom)
+## sino_id, sino_updt = astra.creators.create_sino3d_gpu(
+## X, proj_geom, vol_geom)
+## astra.matlab.data3d('delete', sino_id)
+
+ for kkk in range(anglesNumb):
+
+ residual2[:,kkk,:] = (weights[:,kkk,:]).squeeze() * \
+ ((sino_updt2[:,kkk,:]).squeeze() - \
+ (sino[:,kkk,:]).squeeze() -\
+ (alpha_ring * r_x)
+ )
+ shape = list(numpy.shape(fistaRecon.getParameter('input_sinogram')))
+ shape[1] = numProjSub
+ fistaRecon.residual = numpy.zeros(shape)
+ if fistaRecon.residual.__hash__() != residual.__hash__():
+ residual = fistaRecon.residual
+## for kkk = 1:numProjSub
+## indC = CurrSubIndeces(kkk);
+## if (i < 3)
+## residual(:,kkk,:) = squeeze(residual2(:,indC,:));
+## else
+## residual(:,kkk,:) = squeeze(weights(:,indC,:)).*(squeeze(sino_updt(:,kkk,:)) - (squeeze(sino(:,indC,:)) - alpha_ring.*r_x));
+## end
+## end
+ for kk in range(numProjSub):
+ indC = fistaRecon.getParameter('os_indices')[kkk]
+ if i < 3:
+ residual[:,kkk,:] = residual2[:,indC,:].squeeze()
+ else:
+ residual(:,kkk,:) = \
+ weights[:,indC,:].squeeze() * sino_updt[:,kkk,:].squeeze() - \
+ sino[:,indC,:].squeeze() - alpha_ring * fistaRecon.r_x
+ #squeeze(weights(:,indC,:)).* \
+ # (squeeze(sino_updt(:,kkk,:)) - \
+ #(squeeze(sino(:,indC,:)) - alpha_ring.*r_x));
+
+
+
+ vec = residual.sum(axis = 1)
+ #if SlicesZ > 1:
+ # vec = vec[:,1,:].squeeze()
+ fistaRecon.r = (r_x - (1./L_const) * vec).copy()
+ objective[i] = (0.5 * (residual ** 2).sum())
+## % the ring removal part (Group-Huber fidelity)
+## for kkk = 1:anglesNumb
+## residual(:,kkk,:) = squeeze(weights(:,kkk,:)).*
+## (squeeze(sino_updt(:,kkk,:)) -
+## (squeeze(sino(:,kkk,:)) - alpha_ring.*r_x));
+## end
+## vec = sum(residual,2);
+## if (SlicesZ > 1)
+## vec = squeeze(vec(:,1,:));
+## end
+## r = r_x - (1./L_const).*vec;
+## objective(i) = (0.5*sum(residual(:).^2)); % for the objective function output
+
+
+
+ # Projection/Backprojection Routine
+ if fistaRecon.getParameter('projector_geometry')['type'] == 'parallel' or \
+ fistaRecon.getParameter('projector_geometry')['type'] == 'fanflat' or\
+ fistaRecon.getParameter('projector_geometry')['type'] == 'fanflat_vec':
+ x_temp = numpy.zeros(numpy.shape(X),dtype=numpy.float32)
+ print ("Projection/Backprojection Routine")
+ for kkk in range(SlicesZ):
+
+ x_id, x_temp[kkk] = \
+ astra.creators.create_backprojection3d_gpu(
+ residual[kkk:kkk+1],
+ proj_geomT, vol_geomT)
+ astra.matlab.data3d('delete', x_id)
+ else:
+ x_id, x_temp = \
+ astra.creators.create_backprojection3d_gpu(
+ residual, proj_geom, vol_geom)
+
+ X = X_t - (1/L_const) * x_temp
+ astra.matlab.data3d('delete', sino_id)
+ astra.matlab.data3d('delete', x_id)
+
+
+ ## REGULARIZATION
+ ## SKIPPING FOR NOW
+ ## Should be simpli
+ # regularizer = fistaRecon.getParameter('regularizer')
+ # for slices:
+ # out = regularizer(input=X)
+ print ("skipping regularizer")
+
+
+ ## FINAL
+ print ("final")
+ lambdaR_L1 = fistaRecon.getParameter('ring_lambda_R_L1')
+ if lambdaR_L1 > 0:
+ fistaRecon.r = numpy.max(
+ numpy.abs(fistaRecon.r) - lambdaR_L1 , 0) * \
+ numpy.sign(fistaRecon.r)
+ t = (1 + numpy.sqrt(1 + 4 * t**2))/2
+ X_t = X + (((t_old -1)/t) * (X - X_old))
+
+ if lambdaR_L1 > 0:
+ fistaRecon.r_x = fistaRecon.r + \
+ (((t_old-1)/t) * (fistaRecon.r - r_old))
+
+ if fistaRecon.getParameter('region_of_interest') is None:
+ string = 'Iteration Number {0} | Objective {1} \n'
+ print (string.format( i, objective[i]))
+ else:
+ ROI , X_ideal = fistaRecon.getParameter('region_of_interest',
+ 'ideal_image')
+
+ Resid_error[i] = RMSE(X*ROI, X_ideal*ROI)
+ string = 'Iteration Number {0} | RMS Error {1} | Objective {2} \n'
+ print (string.format(i,Resid_error[i], objective[i]))
+
+## if (lambdaR_L1 > 0)
+## r = max(abs(r)-lambdaR_L1, 0).*sign(r); % soft-thresholding operator for ring vector
+## end
+##
+## t = (1 + sqrt(1 + 4*t^2))/2; % updating t
+## X_t = X + ((t_old-1)/t).*(X - X_old); % updating X
+##
+## if (lambdaR_L1 > 0)
+## r_x = r + ((t_old-1)/t).*(r - r_old); % updating r
+## end
+##
+## if (show == 1)
+## figure(10); imshow(X(:,:,slice), [0 maxvalplot]);
+## if (lambdaR_L1 > 0)
+## figure(11); plot(r); title('Rings offset vector')
+## end
+## pause(0.01);
+## end
+## if (strcmp(X_ideal, 'none' ) == 0)
+## Resid_error(i) = RMSE(X(ROI), X_ideal(ROI));
+## fprintf('%s %i %s %s %.4f %s %s %f \n', 'Iteration Number:', i, '|', 'Error RMSE:', Resid_error(i), '|', 'Objective:', objective(i));
+## else
+## fprintf('%s %i %s %s %f \n', 'Iteration Number:', i, '|', 'Objective:', objective(i));
+## end
+else:
+ fistaRecon = FISTAReconstructor(proj_geom,
+ vol_geom,
+ Sino3D ,
+ weights=Weights3D)
+
+ print ("Lipschitz Constant {0}".format(fistaRecon.pars['Lipschitz_constant']))
+ fistaRecon.setParameter(number_of_iterations = 12)
+ fistaRecon.setParameter(Lipschitz_constant = 767893952.0)
+ fistaRecon.setParameter(ring_alpha = 21)
+ fistaRecon.setParameter(ring_lambda_R_L1 = 0.002)
+ fistaRecon.prepareForIteration()
+ X = fistaRecon.iterate(numpy.load("X.npy"))