some development

3 files changed, 530 insertions, 1 deletions

diff --git a/src/Python/ccpi/reconstruction/FISTAReconstructor.py b/src/Python/ccpi/reconstruction/FISTAReconstructor.py
index af6275f..e40ad24 100644
--- a/src/Python/ccpi/reconstruction/FISTAReconstructor.py
+++ b/src/Python/ccpi/reconstruction/FISTAReconstructor.py
@@ -233,7 +233,7 @@ class FISTAReconstructor():
             #x1 = rand(N,N,1);
             x1 = numpy.random.rand(1,N,N)
             #sqweight = sqrt(weights(:,:,1));
-            sqweight = numpy.sqrt(weights[0])
+            sqweight = numpy.sqrt(weights[0:1,:,:])
             proj_geomT = proj_geom.copy();
             proj_geomT['DetectorRowCount'] = 1;
             vol_geomT = vol_geom.copy();
diff --git a/src/Python/test/create_phantom_projections.py b/src/Python/test/create_phantom_projections.py
new file mode 100644
index 0000000..20a9278
--- /dev/null
+++ b/src/Python/test/create_phantom_projections.py
@@ -0,0 +1,49 @@
+from ccpi.reconstruction.AstraDevice import AstraDevice
+from ccpi.reconstruction.DeviceModel import DeviceModel
+import h5py
+import numpy
+import matplotlib.pyplot as plt
+
+nx = h5py.File('phant3D_256.h5', "r")
+phantom = numpy.asarray(nx.get('/dataset1'))
+pX,pY,pZ = numpy.shape(phantom)
+
+filename = r'/home/ofn77899/Reconstruction/CCPi-FISTA_Reconstruction/demos/DendrData.h5'
+nxa = h5py.File(filename, "r")
+#getEntry(nx, '/')
+# I have exported the entries as children of /
+entries = [entry for entry in nxa['/'].keys()]
+print (entries)
+
+angles_rad = numpy.asarray(nxa.get('/angles_rad'), dtype="float32")
+
+
+device = AstraDevice(
+    DeviceModel.DeviceType.PARALLEL3D.value,
+    [ pX , pY , 1., 1., angles_rad],
+    [ pX, pY, pZ ] )
+
+
+proj = device.doForwardProject(phantom)
+stack = [proj[:,i,:] for i in range(len(angles_rad))]
+stack = numpy.asarray(stack)
+
+
+fig = plt.figure()
+a=fig.add_subplot(1,2,1)
+a.set_title('proj')
+imgplot = plt.imshow(proj[:,100,:])
+a=fig.add_subplot(1,2,2)
+a.set_title('stack')
+imgplot = plt.imshow(stack[100])
+plt.show()
+
+pf = h5py.File("phantom3D256_projections.h5" , "w")
+pf.create_dataset("/projections", data=stack)
+pf.create_dataset("/sinogram", data=proj)
+pf.create_dataset("/angles", data=angles_rad)
+pf.create_dataset("/reconstruction_volume" , data=numpy.asarray([pX, pY, pZ]))
+pf.create_dataset("/camera/size" , data=numpy.asarray([pX , pY ]))
+pf.create_dataset("/camera/spacing" , data=numpy.asarray([1.,1.]))
+pf.flush()
+pf.close()
diff --git a/src/Python/test/test_reconstructor-os_phantom.py b/src/Python/test/test_reconstructor-os_phantom.py
new file mode 100644
index 0000000..01f1354
--- /dev/null
+++ b/src/Python/test/test_reconstructor-os_phantom.py
@@ -0,0 +1,480 @@
+# -*- 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
+
+#from ccpi.viewer.CILViewer2D import *
+
+
+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/src/Python/test/phantom3D256_projections.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)
+
+projections = numpy.asarray(nx.get('/projections'), 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'), dtype="float32")
+angSize = numpy.size(angles_rad)
+image_size_x, image_size_y, image_size_z = \
+              numpy.asarray(nx.get('/reconstruction_volume'), dtype=int)
+det_col_count, det_row_count = \
+              numpy.asarray(nx.get('/camera/size'))
+#slices_tot = numpy.asarray(nx.get('/slices_tot'), dtype=int)[0]
+detectorSpacingX, detectorSpacingY = numpy.asarray(nx.get('/camera/spacing'), dtype=int)
+
+Z_slices = 20
+#det_row_count = image_size_y
+# next definition is just for consistency of naming
+#det_col_count = image_size_x
+
+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
+astradevice = AstraDevice(DeviceModel.DeviceType.PARALLEL3D.value,
+                [proj_geom['DetectorRowCount'] ,
+                 proj_geom['DetectorColCount'] ,
+                 proj_geom['DetectorSpacingX'] ,
+                 proj_geom['DetectorSpacingY'] ,
+                 proj_geom['ProjectionAngles']
+                 ],
+                [
+                    vol_geom['GridColCount'],
+                    vol_geom['GridRowCount'], 
+                    vol_geom['GridSliceCount'] ] )
+## create the sinogram 
+Sino3D = numpy.transpose(projections, axes=[1,0,2])
+
+fistaRecon = FISTAReconstructor(proj_geom,
+                                vol_geom,
+                                Sino3D ,
+                                #weights=Weights3D,
+                                device=astradevice)
+
+print ("Lipschitz Constant {0}".format(fistaRecon.pars['Lipschitz_constant']))
+fistaRecon.setParameter(number_of_iterations = 4)
+#fistaRecon.setParameter(Lipschitz_constant = 767893952.0)
+fistaRecon.setParameter(ring_alpha = 21)
+fistaRecon.setParameter(ring_lambda_R_L1 = 0.002)
+#fistaRecon.setParameter(ring_lambda_R_L1 = 0)
+subsets = 8
+fistaRecon.setParameter(subsets=subsets)
+
+
+#reg = Regularizer(Regularizer.Algorithm.FGP_TV)
+#reg.setParameter(regularization_parameter=0.005,
+#                          number_of_iterations=50)
+reg = Regularizer(Regularizer.Algorithm.FGP_TV)
+reg.setParameter(regularization_parameter=5e6,
+                          tolerance_constant=0.0001,
+                          number_of_iterations=50)
+
+#fistaRecon.setParameter(regularizer=reg)
+#lc = fistaRecon.getParameter('Lipschitz_constant')
+#reg.setParameter(regularization_parameter=5e6/lc)
+
+## Ordered subset
+if True:
+    #subsets = 8
+    fistaRecon.setParameter(subsets=subsets)
+    fistaRecon.createOrderedSubsets()
+else:
+    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 True:
+        # if X doesn't exist
+        #N = params.vol_geom.GridColCount
+        N = vol_geom['GridColCount']
+        print ("N " + str(N))
+        X = numpy.asarray(numpy.ones((image_size_x,image_size_y,image_size_z)),
+                        dtype=numpy.float) * 0.001
+        X = numpy.asarray(numpy.zeros((image_size_x,image_size_y,image_size_z)),
+                        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, weights , alpha_ring = fistaRecon.getParameter(
+            ['projector_geometry' , 'output_geometry',
+             'input_sinogram', 'SlicesZ' ,  'weights', 'ring_alpha'])
+    lambdaR_L1 , alpha_ring , weights , L_const= \
+                       fistaRecon.getParameter(['ring_lambda_R_L1',
+                                               'ring_alpha' , 'weights',
+                                               'Lipschitz_constant'])
+
+    #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(fistaRecon.pars['input_sinogram']))
+    residual2 = fistaRecon.residual2
+    sino_updt_FULL = fistaRecon.residual.copy()
+    r_x = fistaRecon.r.copy()
+
+    results = []
+    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
+
+        
+        #t_old = t
+        SlicesZ, anglesNumb, Detectors = \
+                    numpy.shape(fistaRecon.getParameter('input_sinogram'))
+        ## https://github.com/vais-ral/CCPi-FISTA_Reconstruction/issues/4
+        r_old = fistaRecon.r.copy()
+            
+        if (i > 1 and lambdaR_L1 > 0) :
+            for kkk in range(anglesNumb):
+                 
+                 residual2[:,kkk,:] = (weights[:,kkk,:]).squeeze() * \
+                                       ((sino_updt_FULL[:,kkk,:]).squeeze() - \
+                                        (sino[:,kkk,:]).squeeze() -\
+                                        (alpha_ring * r_x)
+                                        )
+            #r_old = fistaRecon.r.copy()
+            vec = fistaRecon.residual.sum(axis = 1)
+            #if SlicesZ > 1:
+            #    vec = vec[:,1,:] # 1 or 0?
+            r_x = fistaRecon.r_x
+            # update ring variable
+            fistaRecon.r = (r_x - (1./L_const) * vec)
+
+        # subset loop
+        counterInd = 1
+        geometry_type = fistaRecon.getParameter('projector_geometry')['type']
+        angles = fistaRecon.getParameter('projector_geometry')['ProjectionAngles']
+    
+##        if geometry_type == 'parallel' or \
+##           geometry_type == 'fanflat' or \
+##           geometry_type == 'fanflat_vec' :
+##            
+##            for kkk in range(SlicesZ):
+##                sino_id, sinoT[kkk] = \
+##                         astra.creators.create_sino3d_gpu(
+##                             X_t[kkk:kkk+1], proj_geomSUB, vol_geom)
+##                sino_updt_Sub[kkk] = sinoT.T.copy()
+##                
+##        else:
+##            sino_id, sino_updt_Sub = \
+##                astra.creators.create_sino3d_gpu(X_t, proj_geomSUB, vol_geom)
+##        
+##        astra.matlab.data3d('delete', sino_id)
+  
+        for ss in range(fistaRecon.getParameter('subsets')):
+            print ("Subset {0}".format(ss))
+            X_old = X.copy()
+            t_old = t
+            print ("X[0][0][0] {0} t {1}".format(X[0][0][0], t))
+            
+            # the number of projections per subset
+            numProjSub = fistaRecon.getParameter('os_bins')[ss]
+            CurrSubIndices = fistaRecon.getParameter('os_indices')\
+                             [counterInd:counterInd+numProjSub]
+            shape = list(numpy.shape(fistaRecon.getParameter('input_sinogram')))
+            shape[1] = numProjSub
+            sino_updt_Sub = numpy.zeros(shape)
+            
+            #print ("Len CurrSubIndices {0}".format(numProjSub))
+            mask = numpy.zeros(numpy.shape(angles), dtype=bool)
+            cc = 0
+            for j in range(len(CurrSubIndices)):
+                mask[int(CurrSubIndices[j])] = True
+
+            ## this is a reduced device
+            rdev = fistaRecon.getParameter('device_model')\
+                   .createReducedDevice(proj_par={'angles' : angles[mask]},
+                                        vol_par={})
+            proj_geomSUB['ProjectionAngles'] = angles[mask]
+
+            
+
+            if geometry_type == 'parallel' or \
+               geometry_type == 'fanflat' or \
+               geometry_type == 'fanflat_vec' :
+
+                for kkk in range(SlicesZ):
+                    sino_id, sinoT = astra.creators.create_sino3d_gpu (
+                        X_t[kkk:kkk+1] , proj_geomSUB, vol_geom)
+                    sino_updt_Sub[kkk] = sinoT.T.copy()
+                    astra.matlab.data3d('delete', sino_id)
+            else:
+                # for 3D geometry (watch the GPU memory overflow in ASTRA < 1.8)
+                sino_id, sino_updt_Sub = \
+                     astra.creators.create_sino3d_gpu (X_t,
+                                                       proj_geomSUB,
+                                                       vol_geom)
+                
+                astra.matlab.data3d('delete', sino_id)
+                
+            
+
+
+            ## RING REMOVAL
+            residual = fistaRecon.residual
+            
+            
+            if lambdaR_L1 > 0 :
+                 print ("ring removal")
+                 residualSub = numpy.zeros(shape)
+    ##             for a chosen subset
+    ##                for kkk = 1:numProjSub
+    ##                    indC = CurrSubIndeces(kkk);
+    ##                    residualSub(:,kkk,:) =  squeeze(weights(:,indC,:)).*(squeeze(sino_updt_Sub(:,kkk,:)) - (squeeze(sino(:,indC,:)) - alpha_ring.*r_x));
+    ##                    sino_updt_FULL(:,indC,:) = squeeze(sino_updt_Sub(:,kkk,:)); % filling the full sinogram
+    ##                end
+                 for kkk in range(numProjSub):
+                     #print ("ring removal indC ... {0}".format(kkk))
+                     indC = int(CurrSubIndices[kkk])
+                     residualSub[:,kkk,:] = weights[:,indC,:].squeeze() * \
+                            (sino_updt_Sub[:,kkk,:].squeeze() - \
+                             sino[:,indC,:].squeeze() - alpha_ring * r_x)
+                     # filling the full sinogram
+                     sino_updt_FULL[:,indC,:] = sino_updt_Sub[:,kkk,:].squeeze()
+
+            else:
+                #PWLS model
+                # I guess we need to use mask here instead
+                residualSub = weights[:,CurrSubIndices,:] * \
+                              ( sino_updt_Sub - \
+                                sino[:,CurrSubIndices,:].squeeze() )
+            # it seems that in the original code the following like is not
+            # calculated in the case of ring removal
+            objective[i] = 0.5 * numpy.linalg.norm(residualSub)
+
+            #backprojection
+            if geometry_type == 'parallel' or \
+               geometry_type == 'fanflat' or \
+               geometry_type == 'fanflat_vec' :
+                # if geometry is 2D use slice-by-slice projection-backprojection
+                # routine
+                x_temp = numpy.zeros(numpy.shape(X), dtype=numpy.float32)
+                for kkk in range(SlicesZ):
+                    
+                    x_id, x_temp[kkk] = \
+                             astra.creators.create_backprojection3d_gpu(
+                                 residualSub[kkk:kkk+1],
+                                 proj_geomSUB, vol_geom)
+                    astra.matlab.data3d('delete', x_id)
+                    
+            else:
+                x_id, x_temp = \
+                      astra.creators.create_backprojection3d_gpu(
+                          residualSub, proj_geomSUB, vol_geom)
+
+                astra.matlab.data3d('delete', x_id)
+                
+            X = X_t - (1/L_const) * x_temp
+
+        
+
+            ## REGULARIZATION
+            ## SKIPPING FOR NOW
+            ## Should be simpli
+            # regularizer = fistaRecon.getParameter('regularizer')
+            # for slices:
+            # out = regularizer(input=X)
+            print ("regularizer")
+            reg = fistaRecon.getParameter('regularizer')
+
+            if reg is not None:
+                X = reg(input=X,
+                        output_all=False)
+
+            t = (1 + numpy.sqrt(1 + 4 * t **2))/2
+            X_t = X + (((t_old -1)/t) * (X-X_old))
+            counterInd = counterInd + numProjSub - 1
+        if i == 1:
+            r_old = fistaRecon.r.copy()
+            
+        ## 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)
+            # updating r
+            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]))
+
+        results.append(X[10])
+    numpy.save("X_out_os.npy", X)
+
+else:
+    
+    
+    
+    astradevice = AstraDevice(DeviceModel.DeviceType.PARALLEL3D.value,
+                [proj_geom['DetectorRowCount'] ,
+                 proj_geom['DetectorColCount'] ,
+                 proj_geom['DetectorSpacingX'] ,
+                 proj_geom['DetectorSpacingY'] ,
+                 proj_geom['ProjectionAngles']
+                 ],
+                [
+                    vol_geom['GridColCount'],
+                    vol_geom['GridRowCount'], 
+                    vol_geom['GridSliceCount'] ] )
+    regul = Regularizer(Regularizer.Algorithm.FGP_TV)
+    regul.setParameter(regularization_parameter=5e6,
+                       number_of_iterations=50,
+                       tolerance_constant=1e-4,
+                       TV_penalty=Regularizer.TotalVariationPenalty.isotropic)
+
+    fistaRecon = FISTAReconstructor(proj_geom,
+                                vol_geom,
+                                Sino3D ,
+                                weights=Weights3D,
+                                device=astradevice,
+                                #regularizer = regul,
+                                subsets=8)
+
+    print ("Lipschitz Constant {0}".format(fistaRecon.pars['Lipschitz_constant']))
+    fistaRecon.setParameter(number_of_iterations = 1)
+    fistaRecon.setParameter(Lipschitz_constant = 767893952.0)
+    fistaRecon.setParameter(ring_alpha = 21)
+    fistaRecon.setParameter(ring_lambda_R_L1 = 0.002)
+    #fistaRecon.setParameter(subsets=8)
+    
+    #lc = fistaRecon.getParameter('Lipschitz_constant')
+    #fistaRecon.getParameter('regularizer').setParameter(regularization_parameter=5e6/lc)
+    
+    fistaRecon.prepareForIteration()
+    X = fistaRecon.iterate(numpy.load("X.npy"))
+    
+
+# plot
+fig = plt.figure()
+cols = 3
+
+## add the difference
+rd = []
+for i in range(1,len(results)):
+    rd.append(results[i-1])
+    rd.append(results[i])
+    rd.append(results[i] - results[i-1])
+
+rows = (lambda x: int(numpy.floor(x/cols) + 1) if x%cols != 0  else int(x/cols)) \
+       (len (rd))
+for i in range(len (results)):
+    a=fig.add_subplot(rows,cols,i+1)
+    imgplot = plt.imshow(results[i], vmin=0, vmax=1)
+    a.text(0.05, 0.95, "iteration {0}".format(i),
+               verticalalignment='top')
+##    i = i + 1
+##    a=fig.add_subplot(rows,cols,i+1)
+##    imgplot = plt.imshow(results[i], vmin=0, vmax=10)
+##    a.text(0.05, 0.95, "iteration {0}".format(i),
+##               verticalalignment='top')
+    
+##    a=fig.add_subplot(rows,cols,i+2)
+##    imgplot = plt.imshow(results[i]-results[i-1], vmin=0, vmax=10)
+##    a.text(0.05, 0.95, "difference {0}-{1}".format(i, i-1),
+##               verticalalignment='top')
+        
+        
+
+plt.show()