def RegisterData(RegularData, TargetData, FibreData, current_study_name):
## current directory should be: Geometric_Models/DS_FE_Models
## NB: the input file names should not include the extension name.
print ''
print '==================================================='
print '== Step 1 : Align Surface Data with the LV Model =='
print '==================================================='
print ''
##### Step 1: Read in surface data files #####
### Step 1.1: Read in regular surface data
filename = RegularData+'LVRegular_Epi.ipdata'
print filename
regularEpi = readIpdata(filename)
numData_regularEpi = len(regularEpi)
regularEndo = readIpdata(RegularData+'LVRegular_Endo.ipdata')
numData_regularEndo = len(regularEndo)
"""
writeComFile(RegularData+'LVRegular_Endo','LVRegular_Endo')
os.system('cm ExportData.com')
writeComFile(RegularData+'LVRegular_Epi','LVRegular_Epi')
os.system('cm ExportData.com')
"""
regularTotal = concatenate((regularEndo, regularEpi),0)
numData = len(regularTotal)
print '== Step 1.1 : Read in regular model Data =='
print 'The total number data in the regular model is ', numData
################################ DS #############################################
### Step 1.2: Read in target surface data
filenameEpi = TargetData + 'DS_Epi.ipdata'
print filename
targetEpi = readIpdata(filenameEpi)
filenameEndo = TargetData + 'DS_Endo.ipdata'
targetEndo = readIpdata(filenameEndo)
targetTotal = concatenate((targetEndo, targetEpi),0)
numData = len(targetTotal)
print '== Step 1.2 : Read in target model Data =='
print 'The total number data in the target model is ', numData
##### Step 2: Transformation #####
### Step 2.1: Perform initial transformation of target data to match regular
print '== Step 2.1: Translate, rotate and scale the regular data to match regular data =='
[transVector, regularEpi_transformed, regularEndo_transformed] = fitDataAnisotropicScaleRigidNoCorr_ModelTree_TwoSurfaces(regularEpi, regularEndo, targetEpi, targetEndo, 'transMatrixScaling.TRN', xtol=1e-5, maxfev=0, t0=None)
def TransformingData (current_study_name,current_file):
print ''
print '==================================================='
print '== Step 1 : Align Surface Data with the LV Model =='
print '==================================================='
print ''
#####################################################################################
##############============ Step 1.1(a): Read in the UPF data ==============############
## Select files associated with DS
for j in current_file:
if re.search('_epi_DS',str(j)):
filename_tmp=j
filename='../Data/'+ filename_tmp
UPFEpi=readSurfaceData(filename)
noData_UPFEpi=len(UPFEpi)
## Select files associated with DS
for j in current_file:
if re.search('_endo_DS',str(j)):
filename_tmp=j
filename='../Data/'+ filename_tmp
UPFEndo=readSurfaceData(filename)
noData_UPFEndo=len(UPFEndo)
UPFTotal = concatenate((UPFEndo,UPFEpi),0)
noData=len(UPFTotal)
filename='../'+current_study_name +'/TransformedData/' + current_study_name + '_ds_lvepi.ipdata'
groupname=current_study_name.replace("-","")
writeIpdata(UPFEpi, filename, header=groupname+'_ds_lvepi')
filename='../'+current_study_name +'/TransformedData/' + current_study_name + '_ds_lvendo.ipdata'
writeIpdata(UPFEndo, filename, header=groupname+'_ds_lvendo')
print '== Step 1.1 : Read in UPF Data =='
print 'The total number data in UPF is ', noData
print ' '
## Calculate the max x
x_coor=UPFEpi[:,0]
y_coor=UPFEpi[:,1]
z_coor=UPFEpi[:,2]
x_coor_mean=scipy.mean(x_coor)
y_coor_mean=scipy.mean(y_coor)
z_coor_mean=scipy.mean(z_coor)
#####################################################################################
##############======== Step 1.1(b): Remove Extra RV Endo points =========############
print '== Step 1.1(b) : Remove extra RV Endo points at DS =='
index=[38,39,40,42,43,44,48,49,50,77,78,98,99,100,101,133,135,138,151,153,154,155,158,167,168,174,180,191,204,205,215,220,221,224,225,238,240,245,248,252,255,259,270,275,285,290,293,298,302,312,319,327,330,331,334,337,353,354,358,363,365,373,379,380,382,385,387,388,390,400,401,406,415,416,418,423,428,442,452,457,462,472,484,486,513,526,527,540,543,544,559,566,574,575,578,583,593,597,610,612,613,644,645,654,664,666,682,683,695,696,698,702,707,709,712,735,742,748,750,751,766,770,771,787,790,807,808,810,818,819,828,846,857,861,864,866,867,871,875,883,885,887,893,894,896,906,918,919,920,923,932,937,941,942,944,949,960,961,964,973,977,983,988,989,994,999,1002,1014,1018,1020,1024,1025,1027,1030,1039,1041,1048,1052,1054,1063,1067,1070,1079,1080,1087,1093,1101,1110,1116,1118]
no_data_delete=len(index)
print 'The total number of Endo points to be deleted is '
print no_data_delete
UPFEndo_trunc=[]
j=0
for i in range(0,noData_UPFEndo):
if j<no_data_delete :
if i!=(index[j]-1):
UPFEndo_trunc.append(UPFEndo[i,:])
else :
j=j+1
else :
UPFEndo_trunc.append(UPFEndo[i,:])
UPFEndo=array(UPFEndo_trunc)
noData_UPFEndo_trunc=len(UPFEndo)
print 'After deleting the extra RV points, the total number of Endo points is '
print noData_UPFEndo_trunc
filename='../'+current_study_name +'/TransformedData/' + current_study_name + '_ds_lvendo_trunc.ipdata'
writeIpdata(UPFEndo, filename, header=groupname+'_ds_lvendo_trunc')
#####################################################################################
##############======== Step 1.2: Read in the Canine Surface data ==========############
CanineEpi = readIpdata('../../../LVModel/VickyCanineModel/LVModelEpi.ipdata')
CanineEndo = readIpdata('../../../LVModel/VickyCanineModel/LVModelEndo.ipdata')
CanineTotal = concatenate((CanineEndo,CanineEpi),0)
noData=len(CanineTotal)
print '== Step 1.2 : Read in Canine Data =='
print 'The total number data in Canine is ', noData
print ' '
## Firstly translate the data
UPFEpi_Trans=transformRigid3D( UPFEpi, scipy.hstack(([-x_coor_mean,-y_coor_mean,-z_coor_mean,0.0,0,0,0.0])) )
UPFEndo_Trans=transformRigid3D(UPFEndo, scipy.hstack(([-x_coor_mean,-y_coor_mean,-z_coor_mean,0.0,0,0,0.0])) )
filename='../'+current_study_name +'/TransformedData/' + current_study_name + '_ds_lvepi_Trans.ipdata'
writeIpdata(UPFEpi_Trans, filename, header=groupname+'_ds_lvepi_Trans')
filename='../'+current_study_name +'/TransformedData/' + current_study_name + '_ds_lvendo_Trans.ipdata'
writeIpdata(UPFEndo_Trans, filename, header=groupname+'_ds_lvendo_Trans')
UPFEpi=UPFEpi_Trans
UPFEndo=UPFEndo_Trans
#####################################################################################
##########============= Step 1.3: Perform initial transformation ==============########
##########========== to match canine surface data with UPF surface data =====########
print '== Step 1.3 : Translate,Rotate and Scale the canine data to match UPF data =='
## Write out the final scaling vector
filename='../'+ current_study_name + '/GeometricModel_DS_' + current_study_name +'/TransformationMatrix_Scaling.TRN'
[TransformationVector,CanineEpi_Transformed,CanineEndo_Transformed]= fitDataAnisotropicScaleRigidNoCorr_ModelTree_TwoSurfaces(CanineEpi,CanineEndo,UPFEpi,UPFEndo, filename,xtol=1e-5, maxfev=0, t0=None)
print 'Transformation Vector from Canine to UPF with Anisotropic Scaling is '
print TransformationVector
print ' '
## Import the transformation vector and compute the full transformation matrix
TransformationMatrix_Full=constructTransformationMatrix(TransformationVector)
#####################################################################################
########========= Step 1.4: Inverse rigid transform the UPF data ==============########
########======== Back transform UPF data to cardiac cooridinate system ======########
print '== Step 1.4 : Back transform UPF to align with cardiac coordinate system =='
UPFEpi_BackTransformed = inverseTransformRigid3D( UPFEpi, scipy.hstack(TransformationVector))
UPFEndo_BackTransformed = inverseTransformRigid3D( UPFEndo, scipy.hstack(TransformationVector))
CanineEpi_BackTransformed = inverseTransformRigid3D( CanineEpi_Transformed, scipy.hstack(TransformationVector))
CanineEndo_BackTransformed = inverseTransformRigid3D( CanineEndo_Transformed, scipy.hstack(TransformationVector))
#####################################################################################
#########========= Step 1.5(a): Rotate the UPF data along the y and z axes ==========########
print '== Step 1.5(a) : Rotate UPF data =='
x_apex = UPFEpi_BackTransformed[6,0]
y_apex = UPFEpi_BackTransformed[6,1] ## Most Apical Epi data point
z_apex = UPFEpi_BackTransformed[6,2] ## Most Apical Epi data point
print 'The Y and Z coordinates of the most apical data points are ',y_apex,z_apex
print ' '
## Further rotate the UPF data
apex_vector_length=scipy.sqrt(x_apex*x_apex+y_apex*y_apex+z_apex*z_apex)
x_apex=x_apex/apex_vector_length
y_apex=y_apex/apex_vector_length
z_apex=z_apex/apex_vector_length
theta_z=-scipy.arctan2(y_apex,x_apex)
theta_y=scipy.arctan2(z_apex,x_apex)
print theta_z
print theta_y
UPFEpi_BackTransformed_Rotated = transformRigid3D( UPFEpi_BackTransformed, scipy.hstack(([0.0,0.0,0.0,0.0,theta_y,theta_z])) )
UPFEndo_BackTransformed_Rotated = transformRigid3D( UPFEndo_BackTransformed, scipy.hstack(([0.0,0.0,0.0,0.0,theta_y,theta_z])) )
#####################################################################################
#########========= Step 1.5(b): Rotate the UPF data along the long-axis ==========########
####### to ensure y-axis goes through data point 1199 (center points in RV) #########
## Print closest RV point
print '== Step 1.5(b) : Rotate UPF data to align y-axis with RV =='
print 'Cloest RV points'
print UPFEpi_BackTransformed_Rotated[1270]
print ' '
## Define the theta angle for rigid rotation about long-axis to align y with RV
theta=scipy.arctan2(UPFEpi_BackTransformed_Rotated[1270,2],UPFEpi_BackTransformed_Rotated[1270,1])
print 'UPF data should be rotated along the x-axis by ', theta
print ' '
## Write the rotational angle to a file
filename='../'+ current_study_name + '/GeometricModel_DS_' + current_study_name + '/TransformationMatrix_Scaling.TRN'
writeTransformation_Rotation(theta/scipy.constants.pi*180,filename)
## Perform rigid rotation about long-axis to align y-axis with RV for the UPF data
UPFEpi_BackTransformed_FinalRotated = transformRigid3D( UPFEpi_BackTransformed_Rotated,scipy.hstack(([0.0,0.0,0.0,-theta,0.0,0.0])) )
UPFEndo_BackTransformed_FinalRotated = transformRigid3D( UPFEndo_BackTransformed_Rotated, scipy.hstack(([0.0,0.0,0.0,-theta,0.0,0.0])) )
## Perform rigid rotation about long-axis to align y-axis with RV for the canine data
CanineEpi_BackTransformed_Rotated = transformRigid3D( CanineEpi_BackTransformed, scipy.hstack(([0.0,0.0,0.0,-theta,0.0,0.0])) )
CanineEndo_BackTransformed_Rotated = transformRigid3D( CanineEndo_BackTransformed, scipy.hstack(([0.0,0.0,0.0,-theta,0.0,0.0])) )
#####################################################################################
#####################################################################################
#############============= Step 1.6: WriteOut Transformed Data ===================#####
## Create a folder to store output data
print '== Step 1.6(a) : Write out transformed canine model data =='
filename='../'+current_study_name +'/TransformedData/TransformedCanine_Epi.ipdata'
writeIpdata(CanineEpi_Transformed, filename, header='TransformedCanine_Epi')
filename='../'+current_study_name +'/TransformedData/TransformedCanine_Endo.ipdata'
writeIpdata(CanineEndo_Transformed, filename, header='TransformedCanine_Endo')
print '== Step 1.6(b) : Write out backtransformed UPF data =='
filename='../'+current_study_name +'/TransformedData/BackTransformedUPF_Epi.ipdata'
writeIpdata(UPFEpi_BackTransformed, filename, header='BackTransformedUPF_Epi')
filename='../'+current_study_name +'/TransformedData/BackTransformedUPF_Endo.ipdata'
writeIpdata(UPFEndo_BackTransformed, filename, header='BackTransformedUPF_Endo')
print '== Step 1.6(c) : Write out backtransformed canine model data =='
filename='../'+current_study_name +'/TransformedData/BackTransformedCanine_Epi.ipdata'
writeIpdata(CanineEpi_BackTransformed, filename, header='BackTransformedCanine_Epi')
filename='../'+current_study_name +'/TransformedData/BackTransformedCanine_Endo.ipdata'
writeIpdata(CanineEndo_BackTransformed, filename, header='BackTransformedCanine_Endo')
print '== Step 1.6(d) : Write out backtransformed canine model data after rotating along long-axis =='
filename='../'+current_study_name +'/TransformedData/BackTransformedCanineRotated_Epi.ipdata'
writeIpdata(CanineEpi_BackTransformed_Rotated, filename, header='BackTransformedCanineRotated_Epi')
filename='../'+current_study_name +'/TransformedData/BackTransformedCanineRotated_Endo.ipdata'
writeIpdata(CanineEndo_BackTransformed_Rotated, filename, header='BackTransformedCanineRotated_Endo')
print '== Step 1.6(e) : Write out backtransformed UPF data after rotating along y and z axes =='
filename='../'+current_study_name +'/TransformedData/BackTransformedUPFRotated_Epi.ipdata'
writeIpdata(UPFEpi_BackTransformed_Rotated, filename, header='BackTransformedUPFRotated_Epi')
filename='../'+current_study_name +'/TransformedData/BackTransformedUPFRotated_Endo.ipdata'
writeIpdata(UPFEndo_BackTransformed_Rotated, filename, header='BackTransformedUPFRotated_Endo')
print '== Step 1.6(f) : Write out backtransformed UPF data after rotating along long-axis =='
filename='../'+current_study_name +'/TransformedData/BackTransformedUPFFinalRotated_Epi.ipdata'
writeIpdata(UPFEpi_BackTransformed_FinalRotated, filename, header='BackTransformedUPFFinalRotated_Epi')
filename='../'+current_study_name +'/TransformedData/BackTransformedUPFFinalRotated_Endo.ipdata'
writeIpdata(UPFEndo_BackTransformed_FinalRotated, filename, header='BackTransformedUPFFinalRotated_Endo')
#####################################################################################
########### Step 1.7: Apply transformation to the ED surface data #####################
## Select files associated with ED
for j in current_file:
if re.search('_epi_ED',str(j)):
filename_tmp=j
filename='../Data/'+ filename_tmp
UPFEpi_ED=readSurfaceData(filename)
noData_UPFEpi_ED=len(UPFEpi_ED)
for j in current_file:
if re.search('_endo_ED',str(j)):
filename_tmp=j
filename='../Data/'+ filename_tmp
UPFEndo_ED=readSurfaceData(filename)
noData_UPFEndo_ED=len(UPFEndo_ED)
UPFTotal_ED = concatenate((UPFEndo_ED,UPFEpi_ED),0)
noData=len(UPFTotal_ED)
filename='../'+current_study_name +'/TransformedData/' + current_study_name + '_ed_lvepi.ipdata'
writeIpdata(UPFEpi_ED, filename, header=groupname+'_ed_lvepi')
filename='../'+current_study_name +'/TransformedData/' + current_study_name + '_ed_lvendo.ipdata'
writeIpdata(UPFEndo_ED, filename, header=groupname+'_ed_lvendo')
print '================ Step 1.7(a) : Read in UPF Data at ED ===================='
print 'The total number data in UPF is ', noData
print ' '
##############======== Step 1.7(b): Remove Extra RV Endo points =========############
print '== Step 1.7(b) : Remove extra RV Endo points at ED =='
index=[38,39,40,42,43,44,48,49,50,77,78,98,99,100,101,133,135,138,151,153,154,155,158,167,168,174,180,191,204,205,215,220,221,224,225,238,240,245,248,252,255,259,270,275,285,290,293,298,302,312,319,327,330,331,334,337,353,354,358,363,365,373,379,380,382,385,387,388,390,400,401,406,415,416,418,423,428,442,452,457,462,472,484,486,513,526,527,540,543,544,559,566,574,575,578,583,593,597,610,612,613,644,645,654,664,666,682,683,695,696,698,702,707,709,712,735,742,748,750,751,766,770,771,787,790,807,808,810,818,819,828,846,857,861,864,866,867,871,875,883,885,887,893,894,896,906,918,919,920,923,932,937,941,942,944,949,960,961,964,973,977,983,988,989,994,999,1002,1014,1018,1020,1024,1025,1027,1030,1039,1041,1048,1052,1054,1063,1067,1070,1079,1080,1087,1093,1101,1110,1116,1118]
no_data_delete=len(index)
print 'The total number of Endo points to be deleted is '
print no_data_delete
UPFEndo_ED_trunc=[]
j=0
for i in range(0,noData_UPFEndo_ED):
if j<no_data_delete :
if i!=(index[j]-1):
UPFEndo_ED_trunc.append(UPFEndo_ED[i,:])
else :
j=j+1
else :
UPFEndo_ED_trunc.append(UPFEndo_ED[i,:])
UPFEndo_ED=array(UPFEndo_ED_trunc)
noData_UPFEndo_trunc=len(UPFEndo_ED)
print 'After deleting the extra RV points, the total number of Endo points is '
print noData_UPFEndo_trunc
filename='../'+current_study_name +'/TransformedData/' + current_study_name + '_ed_lvendo_trunc.ipdata'
writeIpdata(UPFEndo_ED, filename, header=groupname+'_ed_lvendo_trunc')
## Firstly translate the data
UPFEpi_ED_Trans=transformRigid3D( UPFEpi_ED, scipy.hstack(([-x_coor_mean,-y_coor_mean,-z_coor_mean,0.0,0,0,0.0])) )
UPFEndo_ED_Trans=transformRigid3D(UPFEndo_ED, scipy.hstack(([-x_coor_mean,-y_coor_mean,-z_coor_mean,0.0,0,0,0.0])) )
filename='../'+current_study_name +'/TransformedData/' + current_study_name + '_ed_lvepi_Trans.ipdata'
writeIpdata(UPFEpi_ED_Trans, filename, header=groupname+'_ed_lvepi_Trans')
filename='../'+current_study_name +'/TransformedData/' + current_study_name + '_ed_lvendo_Trans.ipdata'
writeIpdata(UPFEndo_ED_Trans, filename, header=groupname+'_ed_lvendo_Trans')
UPFEpi_ED=UPFEpi_ED_Trans
UPFEndo_ED=UPFEndo_ED_Trans
print '== Step 1.7(c) : Back-transform the UPF data at ED =='
UPFEpi_ED_BackTransformed = inverseTransformRigid3D( UPFEpi_ED, scipy.hstack(TransformationVector))
UPFEndo_ED_BackTransformed = inverseTransformRigid3D( UPFEndo_ED, scipy.hstack(TransformationVector))
print '== Step 1.7(d) : Rotate UPF data at ED along y and z axes =='
UPFEpi_ED_BackTransformed_Rotated = transformRigid3D( UPFEpi_ED_BackTransformed, scipy.hstack(([0.0,0.0,0.0,0.0,theta_y,theta_z])) )
UPFEndo_ED_BackTransformed_Rotated = transformRigid3D( UPFEndo_ED_BackTransformed, scipy.hstack(([0.0,0.0,0.0,0.0,theta_y,theta_z])) )
print '== Step 1.7(e) : Rotate UPF data at ED to align y-axis with RV =='
UPFEpi_ED_BackTransformed_FinalRotated = transformRigid3D( UPFEpi_ED_BackTransformed_Rotated, scipy.hstack(([0.0,0.0,0.0,-theta,0.0,0.0])) )
UPFEndo_ED_BackTransformed_FinalRotated = transformRigid3D( UPFEndo_ED_BackTransformed_Rotated, scipy.hstack(([0.0,0.0,0.0,-theta,0.0,0.0])) )
print '== Step 1.7(f) : Write out the transformed data at ED =='
filename='../'+current_study_name +'/TransformedData/BackTransformedUPFFinalRotated_Epi_ED.ipdata'
writeIpdata(UPFEpi_ED_BackTransformed_FinalRotated, filename, header='BackTransformedUPFFinalRotated_Epi_ED')
filename='../'+current_study_name +'/TransformedData/BackTransformedUPFFinalRotated_Endo_ED.ipdata'
writeIpdata(UPFEndo_ED_BackTransformed_FinalRotated, filename, header='BackTransformedUPFFinalRotated_Endo_ED')
#####################################################################################
########### Step 1.8: Apply transformation to the ES surface data #####################
## Select files associated with ED
for j in current_file:
if re.search('_epi_ES',str(j)):
filename_tmp=j
filename='../Data/'+ filename_tmp
UPFEpi_ES=readSurfaceData(filename)
noData_UPFEpi_ES=len(UPFEpi_ES)
for j in current_file:
if re.search('_endo_ES',str(j)):
filename_tmp=j
filename='../Data/'+ filename_tmp
UPFEndo_ES=readSurfaceData(filename)
noData_UPFEndo_ES=len(UPFEndo_ES)
UPFTotal_ES = concatenate((UPFEndo_ES,UPFEpi_ES),0)
noData=len(UPFTotal_ES)
filename='../'+current_study_name +'/TransformedData/' + current_study_name + '_es_lvepi.ipdata'
writeIpdata(UPFEpi_ES, filename, header=groupname+'_es_lvepi')
filename='../'+current_study_name +'/TransformedData/' + current_study_name + '_es_lvendo.ipdata'
writeIpdata(UPFEndo_ES, filename, header=groupname+'_es_lvendo')
print '== Step 1.8(a) : Read in UPF Data at ES =='
print 'The total number data in UPF is ', noData
print ' '
##############======== Step 1.8(b): Remove Extra RV Endo points =========############
print '== Step 1.8(b) : Remove extra RV Endo points at ES =='
index=[38,39,40,42,43,44,48,49,50,77,78,98,99,100,101,133,135,138,151,153,154,155,158,167,168,174,180,191,204,205,215,220,221,224,225,238,240,245,248,252,255,259,270,275,285,290,293,298,302,312,319,327,330,331,334,337,353,354,358,363,365,373,379,380,382,385,387,388,390,400,401,406,415,416,418,423,428,442,452,457,462,472,484,486,513,526,527,540,543,544,559,566,574,575,578,583,593,597,610,612,613,644,645,654,664,666,682,683,695,696,698,702,707,709,712,735,742,748,750,751,766,770,771,787,790,807,808,810,818,819,828,846,857,861,864,866,867,871,875,883,885,887,893,894,896,906,918,919,920,923,932,937,941,942,944,949,960,961,964,973,977,983,988,989,994,999,1002,1014,1018,1020,1024,1025,1027,1030,1039,1041,1048,1052,1054,1063,1067,1070,1079,1080,1087,1093,1101,1110,1116,1118]
no_data_delete=len(index)
print 'The total number of Endo points to be deleted is '
print no_data_delete
UPFEndo_ES_trunc=[]
j=0
for i in range(0,noData_UPFEndo_ES):
if j<no_data_delete :
if i!=(index[j]-1):
UPFEndo_ES_trunc.append(UPFEndo_ES[i,:])
else :
j=j+1
else :
UPFEndo_ES_trunc.append(UPFEndo_ES[i,:])
UPFEndo_ES=array(UPFEndo_ES_trunc)
noData_UPFEndo_trunc=len(UPFEndo_ES)
print 'After deleting the extra RV points, the total number of Endo points is '
print noData_UPFEndo_trunc
filename='../'+current_study_name +'/TransformedData/' + current_study_name + '_es_lvendo_trunc.ipdata'
writeIpdata(UPFEndo_ES, filename, header=groupname+'_ES_lvendo_trunc')
## Firstly translate the data
UPFEpi_ES_Trans=transformRigid3D( UPFEpi_ES, scipy.hstack(([-x_coor_mean,-y_coor_mean,-z_coor_mean,0.0,0,0,0.0])) )
UPFEndo_ES_Trans=transformRigid3D(UPFEndo_ES, scipy.hstack(([-x_coor_mean,-y_coor_mean,-z_coor_mean,0.0,0,0,0.0])) )
filename='../'+current_study_name +'/TransformedData/' + current_study_name + '_es_lvepi_Trans.ipdata'
writeIpdata(UPFEpi_ES_Trans, filename, header=groupname+'_es_lvepi_Trans')
filename='../'+current_study_name +'/TransformedData/' + current_study_name + '_es_lvendo_Trans.ipdata'
writeIpdata(UPFEndo_ES_Trans, filename, header=groupname+'_es_lvendo_Trans')
UPFEpi_ES=UPFEpi_ES_Trans
UPFEndo_ES=UPFEndo_ES_Trans
print '== Step 1.8(c) : Back-transform the UPF data at ES =='
UPFEpi_ES_BackTransformed = inverseTransformRigid3D( UPFEpi_ES, scipy.hstack(TransformationVector))
UPFEndo_ES_BackTransformed = inverseTransformRigid3D( UPFEndo_ES, scipy.hstack(TransformationVector))
print '== Step 1.8(d) : Rotate UPF data at ES along y and z axes =='
UPFEpi_ES_BackTransformed_Rotated = transformRigid3D( UPFEpi_ES_BackTransformed, scipy.hstack(([0.0,0.0,0.0,0.0,theta_y,theta_z])) )
UPFEndo_ES_BackTransformed_Rotated = transformRigid3D( UPFEndo_ES_BackTransformed, scipy.hstack(([0.0,0.0,0.0,0.0,theta_y,theta_z])) )
print '== Step 1.8(e) : Rotate UPF data at ES to align y-axis with RV =='
UPFEpi_ES_BackTransformed_FinalRotated = transformRigid3D( UPFEpi_ES_BackTransformed_Rotated, scipy.hstack(([0.0,0.0,0.0,-theta,0.0,0.0])) )
UPFEndo_ES_BackTransformed_FinalRotated = transformRigid3D( UPFEndo_ES_BackTransformed_Rotated, scipy.hstack(([0.0,0.0,0.0,-theta,0.0,0.0])) )
print '== Step 1.8(f) : Write out the transformed data at ES =='
filename='../'+current_study_name +'/TransformedData/BackTransformedUPFFinalRotated_Epi_ES.ipdata'
writeIpdata(UPFEpi_ES_BackTransformed_FinalRotated, filename, header='BackTransformedUPFFinalRotated_Epi_ES')
filename='../'+current_study_name +'/TransformedData/BackTransformedUPFFinalRotated_Endo_ES.ipdata'
writeIpdata(UPFEndo_ES_BackTransformed_FinalRotated, filename, header='BackTransformedUPFFinalRotated_Endo_ES')
return
from scipy import array,concatenate
from scipy import spatial
from scipy import delete
from fitting_SurfaceData import readSurfaceData, readIpdata, constructTransformationMatrix, inverseTransformRigid3D, transformScale3D
from fitting_SurfaceData import transformRigid3DFinal, fitDataRigidScaleNoCorr, fitDataRigidScaleNoCorr_TwoSurfaces, fitDataRigidAnisotropicScaleNoCorr
from fitting_SurfaceData import fitDataRigidScaleNoCorr_ModelTree, fitDataRigidAnisotropicScaleNoCorr_ModelTree, fitDataRigidAnisotropicScaleNoCorr_ModelTree_TwoSurfaces
from fitting_SurfaceData import fitDataAnisotropicScaleRigidNoCorr_ModelTree_TwoSurfaces
from fitting_SurfaceData import writeIpdata, writeTransformation, writeTransformation_Scaling, writeTransformation_Rotation
# Read in current ED model surface data
filename_Epi = 'output_debug/ES_model_surface_epi.ipdata'
filename_Endo = 'output_debug/ES_model_surface_endo.ipdata'
modelEpi = readIpdata(filename_Epi)
nd_modelEpi = len(modelEpi)
modelEndo = readIpdata(filename_Endo)
nd_modelEndo = len(modelEndo)
model = concatenate((modelEpi, modelEndo),0)
nd_model = len(model)
print 'Total number of data from the model is ', nd_model
## Read in ED experimental surface data
SDEpi = readIpdata('Surface_Points_Epi_ES.ipdata')
SDEndo = readIpdata('Surface_Points_Endo_ES.ipdata')
SD = concatenate((SDEpi, SDEndo),0)
nd_SD = len(SD)
print 'Total number of experimental data is ', nd_SD
import os
import scipy
from scipy import array
from fitting_SurfaceData import readIpdata, writeIpdata
from writeComFile import writeComFile
studies = ['0912', '0917', '1017', '1024']
### Step 1: Convert text files to .ipdata files
for study in studies:
print 'Current study is '+study
all_files = os.listdir(study)
os.chdir(study)
for filename in all_files:
print filename
name,ext = os.path.splitext(filename)
if ext == '.txt':
coords = readIpdata(filename) # This function can take either txt or ipdata file.
print coords
writeIpdata(coords,name+'.ipdata', header='Data File')
### Step 2: Export ipdata file in cm.
print 'about to write com file'
os.chdir('../')
writeComFile(study,name)
os.system('cm ExportData.com')
os.chdir(study)
os.chdir('../')