def main():
file_name = '/local/dataraid/databank/dataExchange/microCT/Elettra.h5'
file_name_out = 'tmp/projection_'
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.xtomo_raw(file_name,
data_type='h5',
projections_start=0,
projections_end=16)
# Save data
mydata = ex.Export()
mydata.xtomo_tiff(data=data, output_file=file_name_out, axis=0)
file_name = '/local/dataraid/databank/dataExchange/microCT/Elettra.h5'
file_name_out = 'tmp/sinogram_'
# Load data
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.xtomo_raw(file_name,
data_type='h5',
slices_start=0,
slices_end=16)
# Save data
mydata = ex.Export()
mydata.xtomo_tiff(data=data, output_file=file_name_out, axis=1)
def main():
file_name = '/local/dataraid/databank/APS_13_BM/NC/Dorthe_F_.nc'
hdf5_file_name = '/local/dataraid/databank/dataExchange/tmp/APS_13_BM_netCDF.h5'
white_start = 1
white_end = 4
white_step = 2
projections_start = 2
projections_end = 3
projections_step = 1
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.xtomo_raw(
file_name,
projections_start=projections_start,
projections_end=projections_end,
projections_step=projections_step,
white_start=white_start,
white_end=white_end,
white_step=white_step,
projections_digits=3,
data_type='nc',
log='INFO')
mydata = ex.Export()
# Create minimal data exchange hdf5 file
mydata.xtomo_exchange(data=data,
data_white=white,
data_dark=dark,
theta=theta,
hdf5_file_name=hdf5_file_name,
data_exchange_type='tomography_raw_projections')
def main():
file_name = '/local/dataraid/databank/TXM_26_ID/20130731_004_Stripe_Solder_Sample_Tip1_TomoScript_181imgs_p1s_b1.txrm'
# white is saturated ....
white_file_name = '/local/dataraid/databank/TXM_26_ID/20130731_001_Background_Reference_20imgs_p5s_b1.xrm'
hdf5_file_name = '/local/dataraid/databank/dataExchange/tmp/APS_26_ID_xradia.h5'
sample_name = '20130731_004_Stripe_Solder_Sample_Tip1'
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.xtomo_raw(
file_name,
white_file_name=white_file_name,
data_type='xradia',
log='INFO')
mydata = ex.Export()
# Create minimal data exchange hdf5 file
mydata.xtomo_exchange(data=data,
data_white=white,
data_dark=dark,
theta=theta,
hdf5_file_name=hdf5_file_name,
data_exchange_type='tomography_raw_projections',
sample_name=sample_name)
def main():
file_name = '/local/dataraid/2013_11/Vincent_201311/GA_exp/92_2_01/rad_0400ms_.tiff'
white_file_name = '/local/dataraid/2013_11/Vincent_201311/GA_exp/92_2_01/ff_0350ms_.tiff'
hdf5_file_name = '/local/dataraid/databank/dataExchange/microCT/NSLS.h5'
white_start = 0
white_end = 2580
white_step = 30
projections_start = 0
projections_end = 2600
# set to convert slices between slices_start and slices_end
# if omitted all data set will be converted
slices_start = 800
slices_end = 804
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.series_of_images(file_name,
projections_start = projections_start,
projections_end = projections_end,
projections_digits=4,
slices_start = slices_start,
slices_end = slices_end,
white_file_name = white_file_name,
white_start = white_start,
white_end = white_end,
white_step = white_step,
log='INFO'
)
def main():
file_name = '/local/dataraid/databank/CHESS/Dummy001_.tif'
hdf5_file_name = '/local/dataraid/databank/dataExchange/microCT/CHESS_01.h5'
sample_name = 'Dummy'
projections_start = 1
projections_end = 181
white_start = 0
white_end = 10
white_step = 1
dark_start = 0
dark_end = 10
dark_step = 1
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.series_of_images(
file_name,
projections_start=projections_start,
projections_end=projections_end,
sample_name=sample_name,
projections_digits=4,
projections_zeros=True,
log='INFO')
mydata = ex.Export()
# Create minimal data exchange hdf5 file
mydata.xtomo_exchange(data=data,
data_white=white,
data_dark=dark,
theta=theta,
hdf5_file_name=hdf5_file_name,
data_exchange_type='tomography_raw_projections')
def main():
file_name = '/local/dataraid/databank/ESRF/scan.edf'
dark_file_name = '/local/dataraid/databank/ESRF/dark.edf'
white_file_name = '/local/dataraid/databank/ESRF/flat.edf'
hdf5_file_name = '/local/dataraid/databank/dataExchange/microCT/ESRF_test_06.h5'
sample_name = 'esrf'
# set to convert slices between slices_start and slices_end
# if omitted all data set will be converted
slices_start = 300
slices_end = 304
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.series_of_images(
file_name,
white_file_name=white_file_name,
dark_file_name=dark_file_name,
sample_name=sample_name,
slices_start=slices_start,
slices_end=slices_end,
data_type='edf',
log='INFO')
mydata = ex.Export()
# Create minimal data exchange hdf5 file
mydata.xtomo_exchange(data=data,
data_white=white,
data_dark=dark,
theta=theta,
hdf5_file_name=hdf5_file_name,
data_exchange_type='tomography_raw_projections')
def main():
file_name = '/local/dataraid/databank/CHESS/scan1/scan1_.tiff'
dark_file_name = '/local/dataraid/databank/CHESS/scan1/scan1_dark_.tiff'
white_file_name = '/local/dataraid/databank/CHESS/scan1/scan1_white_.tiff'
hdf5_file_name = '/local/dataraid/databank/dataExchange/microCT/CHESS_02.h5'
sample_name = 'Dummy'
projections_start = 1
projections_end = 361
white_start = 0
white_end = 1
white_step = 1
dark_start = 0
dark_end = 1
dark_step = 1
# set to convert slices between slices_start and slices_end
# if omitted all data set will be converted
slices_start = 400
slices_end = 405
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.series_of_images(
file_name,
projections_start=projections_start,
projections_end=projections_end,
slices_start=slices_start,
slices_end=slices_end,
sample_name=sample_name,
projections_digits=3,
projections_zeros=True,
log='INFO')
def main():
# read a series of tiff
# oster: pj: from 0 -> 1440; bf from 0 -> 19; df from 0 -> 19
file_name = '/local/dataraid/databank/PetraIII/2011_KW16_oster/oster02_0001/scan_0002/ccd/pco01/ccd_.tif'
dark_file_name = '/local/dataraid/databank/PetraIII/2011_KW16_oster/oster02_0001/scan_0000/ccd/pco01/ccd_.tif'
white_file_name = '/local/dataraid/databank/PetraIII/2011_KW16_oster/oster02_0001/scan_0001/ccd/pco01/ccd_.tif'
projections_start = 0
projections_end = 1441
white_start = 0
white_end = 20
white_step = 1
dark_start = 0
dark_end = 20
dark_step = 1
# to reconstruct slices from slices_start to slices_end
# if omitted all data set is recontructed
slices_start = 1000
slices_end = 1004
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.xtomo_raw(
file_name,
projections_start=projections_start,
projections_end=projections_end,
slices_start=slices_start,
slices_end=slices_end,
#projections_angle_range=360,
white_file_name=white_file_name,
white_start=white_start,
white_end=white_end,
white_step=white_step,
dark_file_name=dark_file_name,
dark_start=dark_start,
dark_end=dark_end,
dark_step=dark_step,
projections_digits=4,
projections_zeros=True,
log='INFO')
# TomoPy xtomo object creation and pipeline of methods.
d = tomopy.xtomo_dataset(log='debug')
d.dataset(data, white, dark, theta)
d.normalize()
d.correct_drift()
#d.optimize_center()
#d.phase_retrieval(pixel_size=0.9e-4, dist=6.9, energy=15.25)
#d.correct_drift()
d.center = 1872.87890625
d.gridrec()
# Write to stack of TIFFs.
mydata = ex.Export()
mydata.xtomo_tiff(data=d.data_recon,
output_file='tmp/PetraIII_tiff_2_tomoPy_',
axis=0)
def main():
file_name = '/local/dataraid/databank/SLS_2011/Ashley/3e_final_2_.tif'
log_file = '/local/dataraid/databank/SLS_2011/Ashley/3e_final_2_.log'
hdf5_file_name = '/local/dataraid/databank/dataExchange/microCT/Ashley_SLS.h5'
#Read SLS log file data
file = open(log_file, 'r')
for line in file:
if 'Number of darks' in line:
NumberOfDarks = re.findall(r'\d+', line)
if 'Number of flats' in line:
NumberOfFlats = re.findall(r'\d+', line)
if 'Number of projections' in line:
NumberOfProjections = re.findall(r'\d+', line)
if 'Number of inter-flats' in line:
NumberOfInterFlats = re.findall(r'\d+', line)
if 'Inner scan flag' in line:
InnerScanFlag = re.findall(r'\d+', line)
if 'Flat frequency' in line:
FlatFrequency = re.findall(r'\d+', line)
if 'Rot Y min' in line:
RotYmin = re.findall(r'\d+.\d+', line)
if 'Rot Y max' in line:
RotYmax = re.findall(r'\d+.\d+', line)
if 'Angular step' in line:
AngularStep = re.findall(r'\d+.\d+', line)
file.close()
dark_start = 1
dark_end = int(NumberOfDarks[0]) + 1
white_start = dark_end
white_end = white_start + int(NumberOfFlats[0])
projections_start = white_end
projections_end = projections_start + int(NumberOfProjections[0])
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.series_of_images(
file_name,
projections_start=projections_start,
projections_end=projections_end,
projections_digits=4,
white_start=white_start,
white_end=white_end,
dark_start=dark_start,
dark_end=dark_end,
log='INFO')
mydata = ex.Export()
# Create minimal data exchange hdf5 file
mydata.xtomo_exchange(data=data,
data_white=white,
data_dark=dark,
theta=theta,
hdf5_file_name=hdf5_file_name,
data_exchange_type='tomography_raw_projections')
def main():
# read a series of tiff
file_name = '/local/dataraid/databank/AS/Mayo_tooth_AS/SAMPLE_T_.tif'
dark_file_name = '/local/dataraid/databank/AS/Mayo_tooth_AS/DF__BEFORE_.tif'
white_file_name = '/local/dataraid/databank/AS/Mayo_tooth_AS/BG__BEFORE_.tif'
sample_name = 'Teeth'
projections_start = 0
projections_end = 1801
white_start = 0
white_end = 10
white_step = 1
dark_start = 0
dark_end = 10
dark_step = 1
# to reconstruct slices from slices_start to slices_end
# if omitted all data set is recontructed
slices_start = 290
slices_end = 294
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.xtomo_raw(file_name,
projections_start = projections_start,
projections_end = projections_end,
slices_start = slices_start,
slices_end = slices_end,
white_file_name = white_file_name,
white_start = white_start,
white_end = white_end,
white_step = white_step,
dark_file_name = dark_file_name,
dark_start = dark_start,
dark_end = dark_end,
dark_step = dark_step,
projections_digits = 4,
white_digits = 2,
dark_digits = 2,
projections_zeros = True,
log='INFO'
)
# TomoPy xtomo object creation and pipeline of methods.
d = tomopy.xtomo_dataset(log='debug')
d.dataset(data, white, dark, theta)
d.normalize()
d.correct_drift()
#d.optimize_center()
#d.phase_retrieval()
#d.correct_drift()
d.center=1184.0
d.gridrec()
# Write to stack of TIFFs.
mydata = ex.Export()
mydata.xtomo_tiff(data = d.data_recon, output_file = 'tmp/Australian_tiff_2_tomoPy_', axis=0)
def main():
# read a series of SPE
file_name = '/local/dataraid/databank/APS_13_BM/SPE/run2_soln1_2_.SPE'
hdf5_file_name = '/local/dataraid/databank/dataExchange/microCT/APS_13_BM_test_04.h5'
white_start = 1
white_end = 8
white_step = 2
projections_start = 2
projections_end = 7
projections_step = 2
# set to convert slices between slices_start and slices_end
# if omitted all data set will be converted
slices_start = 100
slices_end = 104
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.series_of_images(
file_name,
projections_start=projections_start,
projections_end=projections_end,
projections_step=projections_step,
slices_start=slices_start,
slices_end=slices_end,
white_start=white_start,
white_end=white_end,
white_step=white_step,
projections_zeros=False,
white_zeros=False,
dark_zeros=False,
data_type='spe',
sample_name='Stripe_Solder_Sample_Tip1',
log='INFO')
## # if you have already created a data exchange file using convert_SLS.py module,
## # comment the call above and read the data set as data exchange
## # Read HDF5 file.
## data, white, dark, theta = tomopy.xtomo_reader(hdf5_file_name,
## slices_start=0,
## slices_end=2)
# TomoPy xtomo object creation and pipeline of methods.
d = tomopy.xtomo_dataset(log='debug')
d.dataset(data, white, dark, theta)
d.normalize()
d.correct_drift()
#d.optimize_center()
#d.phase_retrieval()
#d.correct_drift()
d.center = 705
d.gridrec()
# Write to stack of TIFFs.
tomopy.xtomo_writer(d.data_recon, 'tmp/APS_13BM_', axis=0)
def main():
file_name = '/local/dataraid/databank/Elettra/Volcanic_rock/tomo_.tif'
dark_file_name = '/local/dataraid/databank/Elettra/Volcanic_rock/dark_.tif'
white_file_name = '/local/dataraid/databank/Elettra/Volcanic_rock/flat_.tif'
hdf5_file_name = '/local/dataraid/databank/dataExchange/microCT/Elettra_test.h5'
projections_start = 1
projections_end = 1441
white_start = 1
white_end = 11
white_step = 1
dark_start = 1
dark_end = 11
dark_step = 1
sample_name = 'Volcanic_rock'
# set to convert slices between slices_start and slices_end
# if omitted all data set will be converted
slices_start = 150
slices_end = 154
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.series_of_images(
file_name,
projections_start=projections_start,
projections_end=projections_end,
projections_digits=4,
slices_start=slices_start,
slices_end=slices_end,
white_file_name=white_file_name,
white_start=white_start,
white_end=white_end,
white_step=white_step,
dark_file_name=dark_file_name,
dark_start=dark_start,
dark_end=dark_end,
dark_step=dark_step,
data_type='compressed_tiff', # comment this line if regular tiff
projections_zeros=True,
white_zeros=False,
dark_zeros=False,
sample_name=sample_name,
log='INFO')
mydata = ex.Export()
# Create minimal data exchange hdf5 file
mydata.xtomo_exchange(data=data,
data_white=white,
data_dark=dark,
theta=theta,
hdf5_file_name=hdf5_file_name,
data_exchange_type='tomography_raw_projections')
def main():
file_name = '/local/dataraid/databank/CHESS/scan1/scan1_.tiff'
dark_file_name = '/local/dataraid/databank/CHESS/scan1/scan1_dark_.tiff'
white_file_name = '/local/dataraid/databank/CHESS/scan1/scan1_white_.tiff'
hdf5_file_name = '/local/dataraid/databank/dataExchange/microCT/CHESS_02.h5'
sample_name = 'Dummy'
projections_start = 1
projections_end = 361
white_start = 0
white_end = 1
white_step = 1
dark_start = 0
dark_end = 1
dark_step = 1
# set to convert slices between slices_start and slices_end
# if omitted all data set will be converted
slices_start = 400
slices_end = 405
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.series_of_images(
file_name,
projections_start=projections_start,
projections_end=projections_end,
slices_start=slices_start,
slices_end=slices_end,
sample_name=sample_name,
projections_digits=3,
projections_zeros=True,
log='INFO')
# and/or read as data exchange
# Read HDF5 file.
##data, white, dark, theta = tomopy.xtomo_reader('/local/dataraid/databank/dataExchange/microCT/CHESS_01.h5',
## slices_start=100,
## slices_end=101)
# Xtomo object creation and pipeline of methods.
d = tomopy.xtomo_dataset(log='debug')
d.dataset(data, white, dark, theta)
d.normalize()
d.correct_drift()
d.optimize_center()
#d.phase_retrieval()
#d.correct_drift()
#d.center=99.5
d.gridrec()
# Write to stack of TIFFs.
tomopy.xtomo_writer(d.data_recon, 'tmp/CHESS_scan1_', axis=0)
def main():
file_name = '/local/dataraid/databank/SLS_2011/Hornby_SLS/Hornby_b.tif'
log_file = '/local/dataraid/databank/SLS_2011/Hornby_SLS/Hornby.log'
hdf5_file_name = '/local/dataraid/databank/dataExchange/tmp/SLS.h5'
#Read SLS log file data
file = open(log_file, 'r')
for line in file:
linelist = line.split()
if len(linelist) > 1:
if (linelist[0] == "Number" and linelist[2] == "darks"):
number_of_darks = int(linelist[4])
elif (linelist[0] == "Number" and linelist[2] == "flats"):
number_of_flats = int(linelist[4])
elif (linelist[0] == "Number" and linelist[2] == "projections"):
number_of_projections = int(linelist[4])
elif (linelist[0] == "Rot" and linelist[2] == "min"):
rotation_min = float(linelist[6])
elif (linelist[0] == "Rot" and linelist[2] == "max"):
rotation_max = float(linelist[6])
elif (linelist[0] == "Angular" and linelist[1] == "step"):
angular_step = float(linelist[4])
file.close()
dark_start = 1
dark_end = number_of_darks + 1
white_start = dark_end
white_end = white_start + number_of_flats
projections_start = white_end
projections_end = projections_start + number_of_projections
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.xtomo_raw(
file_name,
projections_start=projections_start,
projections_end=projections_end,
projections_digits=4,
white_start=white_start,
white_end=white_end,
dark_start=dark_start,
dark_end=dark_end,
log='INFO')
mydata = ex.Export()
# Create minimal data exchange hdf5 file
mydata.xtomo_exchange(data=data,
data_white=white,
data_dark=dark,
theta=theta,
hdf5_file_name=hdf5_file_name,
data_exchange_type='tomography_raw_projections')
def main():
# read a series of netCDF
file_name = '/local/dataraid/databank/APS_13_BM/NC/Dorthe_F_.nc'
hdf5_file_name = '/local/dataraid/databank/dataExchange/microCT/APS_13_BM_NC_test_02.h5'
white_start = 1
white_end = 4
white_step = 2
projections_start = 2
projections_end = 3
projections_step = 1
# set to convert slices between slices_start and slices_end
# if omitted all data set will be converted
slices_start = 300
slices_end = 304
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.series_of_images(
file_name,
projections_start=projections_start,
projections_end=projections_end,
projections_step=projections_step,
slices_start=slices_start,
slices_end=slices_end,
white_start=white_start,
white_end=white_end,
white_step=white_step,
projections_digits=3,
data_type='nc',
log='INFO')
## # if you have already created a data exchange file using convert_SLS.py module,
## # comment the call above and read the data set as data exchange
## # Read HDF5 file.
## data, white, dark, theta = tomopy.xtomo_reader(hdf5_file_name,
## slices_start=0,
## slices_end=2)
# TomoPy xtomo object creation and pipeline of methods.
d = tomopy.xtomo_dataset(log='debug')
d.dataset(data, white, dark, theta)
d.normalize()
d.correct_drift()
#d.optimize_center()
#d.phase_retrieval()
#d.correct_drift()
d.center = 484.5
d.gridrec()
# Write to stack of TIFFs.
tomopy.xtomo_writer(d.data_recon, 'tmp/APS_13BM_', axis=0)
def main():
file_name = '/local/dataraid/2013_11/Vincent_201311/GA_exp/92_2_01/rad_0400ms_.tiff'
white_file_name = '/local/dataraid/2013_11/Vincent_201311/GA_exp/92_2_01/ff_0350ms_.tiff'
hdf5_file_name = '/local/dataraid/databank/dataExchange/microCT/NSLS.h5'
white_start = 0
white_end = 2580
white_step = 30
projections_start = 0
projections_end = 2600
# set to convert slices between slices_start and slices_end
# if omitted all data set will be converted
slices_start = 800
slices_end = 804
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.series_of_images(
file_name,
projections_start=projections_start,
projections_end=projections_end,
projections_digits=4,
slices_start=slices_start,
slices_end=slices_end,
white_file_name=white_file_name,
white_start=white_start,
white_end=white_end,
white_step=white_step,
log='INFO')
## # if you have already created a data exchange file using convert_SLS.py module,
## # comment the call above and read the data set as data exchange
## # Read HDF5 file.
## data, white, dark, theta = tomopy.xtomo_reader(hdf5_file_name,
## slices_start=0,
## slices_end=2)
# TomoPy xtomo object creation and pipeline of methods.
d = tomopy.xtomo_dataset(log='debug')
d.dataset(data, white, dark, theta)
d.normalize()
d.correct_drift()
#d.optimize_center()
#d.phase_retrieval()
#d.correct_drift()
d.center = 1010.0
d.gridrec()
# Write to stack of TIFFs.
tomopy.xtomo_writer(d.data_recon, 'tmp/SLS_', axis=0)
def main():
file_name = '/local/dataraid/databank/AS/Mayo_tooth_AS/SAMPLE_T_.tif'
dark_file_name = '/local/dataraid/databank/AS/Mayo_tooth_AS/DF__AFTER_.tif'
white_file_name = '/local/dataraid/databank/AS/Mayo_tooth_AS/BG__BEFORE_.tif'
hdf5_file_name = '/local/dataraid/databank/dataExchange/microCT/Australian_test.h5'
sample_name = 'Teeth'
projections_start = 0
projections_end = 1801
white_start = 0
white_end = 10
white_step = 1
dark_start = 0
dark_end = 10
dark_step = 1
# set to convert slices between slices_start and slices_end
# if omitted all data set will be converted
slices_start = 290
slices_end = 294
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.series_of_images(
file_name,
projections_start=projections_start,
projections_end=projections_end,
slices_start=slices_start,
slices_end=slices_end,
white_file_name=white_file_name,
white_start=white_start,
white_end=white_end,
white_step=white_step,
dark_file_name=dark_file_name,
dark_start=dark_start,
dark_end=dark_end,
dark_step=dark_step,
sample_name=sample_name,
projections_digits=4,
white_digits=2,
dark_digits=2,
projections_zeros=True,
log='INFO')
mydata = ex.Export()
# Create minimal data exchange hdf5 file
mydata.xtomo_exchange(data=data,
data_white=white,
data_dark=dark,
theta=theta,
hdf5_file_name=hdf5_file_name,
data_exchange_type='tomography_raw_projections')
def main():
# read a series of SPE
file_name = '/local/dataraid/databank/APS_13_BM/SPE/run2_soln1_2_.SPE'
white_start = 1
white_end = 8
white_step = 2
projections_start = 2
projections_end = 7
projections_step = 2
# set to convert slices between slices_start and slices_end
# if omitted all data set will be converted
slices_start = 100
slices_end = 104
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.xtomo_raw(
file_name,
projections_start=projections_start,
projections_end=projections_end,
projections_step=projections_step,
slices_start=slices_start,
slices_end=slices_end,
white_start=white_start,
white_end=white_end,
white_step=white_step,
projections_zeros=False,
white_zeros=False,
dark_zeros=False,
projections_digits=1,
data_type='spe',
log='INFO')
# TomoPy xtomo object creation and pipeline of methods.
d = tomopy.xtomo_dataset(log='debug')
d.dataset(data, white, dark, theta)
d.normalize()
d.correct_drift()
#d.optimize_center()
#d.phase_retrieval()
#d.correct_drift()
d.center = 705
d.gridrec()
# Write to stack of TIFFs.
mydata = ex.Export()
mydata.xtomo_tiff(data=d.data_recon,
output_file='tmp/APS_13_BM_spe_2_tomoPy_',
axis=0)
def main():
# read a series of tiff
file_name = '/local/dataraid/databank/Anka/radios/image_.tif'
dark_file_name = '/local/dataraid/databank/Anka/darks/image_.tif'
white_file_name = '/local/dataraid/databank/Anka/flats/image_.tif'
projections_start = 0
projections_end = 3167
white_start = 0
white_end = 100
dark_start = 0
dark_end = 100
sample_name = 'Anka'
# to reconstruct slices from slices_start to slices_end
# if omitted all data set is recontructed
slices_start = 800
slices_end = 804
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.xtomo_raw(file_name,
projections_start = projections_start,
projections_end = projections_end,
slices_start = slices_start,
slices_end = slices_end,
white_file_name = white_file_name,
white_start = white_start,
white_end = white_end,
dark_file_name = dark_file_name,
dark_start = dark_start,
dark_end = dark_end,
projections_digits = 5,
log='INFO'
)
# TomoPy xtomo object creation and pipeline of methods.
d = tomopy.xtomo_dataset(log='debug')
d.dataset(data, white, dark, theta)
d.normalize()
d.correct_drift()
#d.optimize_center()
#d.phase_retrieval()
#d.correct_drift()
d.center=993.825
d.gridrec()
# Write to stack of TIFFs.
mydata = ex.Export()
mydata.xtomo_tiff(data = d.data_recon, output_file = 'tmp/Anka_tiff_2_tomoPy_', axis=0)
def main():
file_name = '/local/dataraid/databank/ESRF/scan.edf'
dark_file_name = '/local/dataraid/databank/ESRF/dark.edf'
white_file_name = '/local/dataraid/databank/ESRF/flat.edf'
# only defined if used a converter
# omit when used as direct importer in tomoPy
hdf5_file_name = '/local/dataraid/databank/dataExchange/microCT/ESRF_test_02.h5'
sample_name = 'esrf'
# set to import/convert slices between slices_start and slices_end
# if omitted all data set will be converted
slices_start = 300
slices_end = 304
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.series_of_images(
file_name,
white_file_name=white_file_name,
dark_file_name=dark_file_name,
sample_name=sample_name,
slices_start=slices_start,
slices_end=slices_end,
data_type='edf',
log='INFO')
## # if you have already created a data exchange file using convert_SLS.py module,
## # comment the call above and read the data set as data exchange with:
## # Read HDF5 file.
## data, white, dark, theta = tomopy.xtomo_reader(hdf5_file_name,
## slices_start=0,
## slices_end=2)
# TomoPy xtomo object creation and pipeline of methods.
# for full set of options see http://tomopy.github.io/tomopy/
d = tomopy.xtomo_dataset(log='debug')
d.dataset(data, white, dark, theta)
d.normalize()
d.correct_drift()
#d.optimize_center()
#d.phase_retrieval()
#d.correct_drift()
d.center = 549.84
d.gridrec()
# Write to stack of TIFFs.
tomopy.xtomo_writer(d.data_recon, 'tmp/ESRF_OK', axis=0)
def main():
file_name = '/local/dataraid/databank/VirginiaTech/test_sample_Diplo_4/Diplodocus_1_200mm_4_.tif'
dark_file_name = '/local/dataraid/databank/VirginiaTech/test_sample_Diplo_4/Diplodocus_1_200mm_4postDark_.tif'
white_file_name = '/local/dataraid/databank/VirginiaTech/test_sample_Diplo_4/Diplodocus_1_200mm_4postFlat_.tif'
hdf5_file_name = '/local/dataraid/databank/dataExchange/microCT/VirginiaTech_test.h5'
sample_name = 'Diplodocus_1_200mm_'
projections_start = 1 # projection 0 is dark so we skip it
projections_end = 1500
white_start = 0
white_end = 10
white_step = 1
dark_start = 0
dark_end = 10
dark_step = 1
# set to convert slices between slices_start and slices_end
# if omitted all data set will be converted
slices_start = 600
slices_end = 604
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.series_of_images(
file_name,
projections_start=projections_start,
projections_end=projections_end,
slices_start=slices_start,
slices_end=slices_end,
white_file_name=white_file_name,
white_start=white_start,
white_end=white_end,
white_step=white_step,
dark_file_name=dark_file_name,
dark_start=dark_start,
dark_end=dark_end,
dark_step=dark_step,
sample_name=sample_name,
projections_digits=5,
projections_zeros=True,
log='INFO')
mydata = ex.Export()
# Create minimal data exchange hdf5 file
mydata.xtomo_exchange(data=data,
data_white=white,
data_dark=dark,
theta=theta,
hdf5_file_name=hdf5_file_name,
data_exchange_type='tomography_raw_projections')
def main():
file_name = '/local/dataraid/databank/Anka/radios/image_.tif'
dark_file_name = '/local/dataraid/databank/Anka/darks/image_.tif'
white_file_name = '/local/dataraid/databank/Anka/flats/image_.tif'
hdf5_file_name = '/local/dataraid/databank/dataExchange/microCT/Anka_test.h5'
projections_start = 0
projections_end = 3167
white_start = 0
white_end = 100
dark_start = 0
dark_end = 100
sample_name = 'Anka'
# set to convert slices between slices_start and slices_end
# if omitted all data set will be converted
slices_start = 800
slices_end = 804
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.series_of_images(
file_name,
projections_start=projections_start,
projections_end=projections_end,
slices_start=slices_start,
slices_end=slices_end,
white_file_name=white_file_name,
white_start=white_start,
white_end=white_end,
dark_file_name=dark_file_name,
dark_start=dark_start,
dark_end=dark_end,
sample_name=sample_name,
projections_digits=5,
log='INFO')
mydata = ex.Export()
# Create minimal data exchange hdf5 file
mydata.xtomo_exchange(data=data,
data_white=white,
data_dark=dark,
theta=theta,
hdf5_file_name=hdf5_file_name,
data_exchange_type='tomography_raw_projections')
def main():
# read a series of netCDF
file_name = '/local/dataraid/databank/APS_13_BM/NC/Dorthe_F_.nc'
white_start = 1
white_end = 4
white_step = 2
projections_start = 2
projections_end = 3
projections_step = 1
# set to convert slices between slices_start and slices_end
# if omitted all data set will be converted
slices_start = 300
slices_end = 304
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.xtomo_raw(
file_name,
projections_start=projections_start,
projections_end=projections_end,
projections_step=projections_step,
slices_start=slices_start,
slices_end=slices_end,
white_start=white_start,
white_end=white_end,
white_step=white_step,
projections_digits=3,
data_type='nc',
log='INFO')
# TomoPy xtomo object creation and pipeline of methods.
d = tomopy.xtomo_dataset(log='debug')
d.dataset(data, white, dark, theta)
d.normalize()
d.correct_drift()
#d.optimize_center()
#d.phase_retrieval()
#d.correct_drift()
d.center = 484.5
d.gridrec()
# Write to stack of TIFFs.
mydata = ex.Export()
mydata.xtomo_tiff(data=d.data_recon,
output_file='tmp/APS_13_BM_netCDF_2_tomoPy_',
axis=0)
def main():
file_name = '/local/dataraid/databank/CHESS/scan1/scan1_.tiff'
dark_file_name = '/local/dataraid/databank/CHESS/scan1/scan1_dark_.tiff'
white_file_name = '/local/dataraid/databank/CHESS/scan1/scan1_white_.tiff'
projections_start = 1
projections_end = 361
white_start = 0
white_end = 1
white_step = 1
dark_start = 0
dark_end = 1
dark_step = 1
# set to convert slices between slices_start and slices_end
# if omitted all data set will be converted
slices_start = 400
slices_end = 404
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.xtomo_raw(file_name,
projections_start = projections_start,
projections_end = projections_end,
slices_start = slices_start,
slices_end = slices_end,
projections_digits = 3,
projections_zeros = True,
log='INFO'
)
# Xtomo object creation and pipeline of methods.
d = tomopy.xtomo_dataset(log='debug')
d.dataset(data, white, dark, theta)
d.normalize()
d.correct_drift()
#d.optimize_center()
#d.phase_retrieval()
#d.correct_drift()
d.center=1160.5
d.gridrec()
# Write to stack of TIFFs.
mydata = ex.Export()
mydata.xtomo_tiff(data = d.data_recon, output_file = 'tmp/CHESS_tiff_2_tomoPy_', axis=0)
def main():
file_name = '/local/dataraid/databank/AS/Mayo_tooth_AS/SAMPLE_T_.tif'
dark_file_name = '/local/dataraid/databank/AS/Mayo_tooth_AS/DF__BEFORE_.tif'
white_file_name = '/local/dataraid/databank/AS/Mayo_tooth_AS/BG__BEFORE_.tif'
hdf5_file_name = '/local/dataraid/databank/dataExchange/tmp/Australian.h5'
sample_name = 'Teeth'
projections_start = 0
projections_end = 1801
white_start = 0
white_end = 10
white_step = 1
dark_start = 0
dark_end = 10
dark_step = 1
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.xtomo_raw(
file_name,
projections_start=projections_start,
projections_end=projections_end,
white_file_name=white_file_name,
white_start=white_start,
white_end=white_end,
white_step=white_step,
dark_file_name=dark_file_name,
dark_start=dark_start,
dark_end=dark_end,
dark_step=dark_step,
projections_digits=4,
white_digits=2,
dark_digits=2,
projections_zeros=True,
log='INFO')
mydata = ex.Export()
# Create minimal data exchange hdf5 file
mydata.xtomo_exchange(data=data,
data_white=white,
data_dark=dark,
theta=theta,
hdf5_file_name=hdf5_file_name,
data_exchange_type='tomography_raw_projections',
sample_name=sample_name)
def main():
file_name = '/local/dataraid/databank/APS_13_BM/SPE/run2_soln1_2_.SPE'
hdf5_file_name = '/local/dataraid/databank/dataExchange/microCT/APS_13_BM_test_07.h5'
white_start = 1
white_end = 8
white_step = 2
projections_start = 2
projections_end = 7
projections_step = 2
# set to convert slices between slices_start and slices_end
# if omitted all data set will be converted
slices_start = 100
slices_end = 104
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.series_of_images(file_name,
projections_start = projections_start,
projections_end = projections_end,
projections_step = projections_step,
slices_start = slices_start,
slices_end = slices_end,
white_start = white_start,
white_end = white_end,
white_step = white_step,
projections_zeros=False,
white_zeros=False,
dark_zeros=False,
projections_digits = 1,
data_type='spe',
log='INFO'
)
mydata = ex.Export()
# Create minimal data exchange hdf5 file
mydata.xtomo_exchange(data = data,
data_white = white,
data_dark = dark,
theta = theta,
hdf5_file_name = hdf5_file_name,
data_exchange_type = 'tomography_raw_projections'
)
def main():
file_name = '/local/dataraid/databank/dataExchange/microCT/Elettra.h5'
file_name_out = '/local/dataraid/databank/dataExchange/microCT/Elettra_out.h5'
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.xtomo_raw(file_name,
data_type='h5',
log='INFO')
mydata = ex.Export()
# Create minimal data exchange hdf5 file
mydata.xtomo_exchange(data=data,
data_white=white,
data_dark=dark,
theta=theta,
hdf5_file_name=file_name_out,
data_exchange_type='tomography_raw_projections')
def main():
raw_tiff_base_name = "/local/dataraid/databank/dataExchange/microCT/SRC/raw/FPA_16_18_18_TOMO_243_Fiber_2500_50_50_"
hdf5_base_name = "/local/dataraid/databank/dataExchange/tmp/SRC_"
log_file = raw_tiff_base_name + "wavelength.dpt"
angle_file = raw_tiff_base_name + "angle.dpt"
# Determine projection angle end
file = open(angle_file, 'r')
lines = file.readlines()
projections_angle_end = float(lines[0]) + float(lines[1])
file.close()
file = open(log_file, 'r')
for line in file:
linelist = line.split(",")
file_name = raw_tiff_base_name+linelist[0]+"cm-1.dpt"
sample_name = raw_tiff_base_name+linelist[0]+"cm-1"
hdf5_file_name = hdf5_base_name+linelist[0]+"cm-1.h5"
mydata = dx.Import()
# Read series of images from a single dpt file
data, white, dark, theta = mydata.xtomo_raw(file_name,
data_type='dpt',
projections_angle_end = projections_angle_end,
log='INFO'
)
mydata = ex.Export()
# Create minimal data exchange hdf5 file
mydata.xtomo_exchange(data = data,
data_white = white,
data_dark = dark,
theta = theta,
hdf5_file_name = hdf5_file_name,
sample_name = sample_name,
data_exchange_type = 'tomography_raw_projections'
)
file.close()
def main():
file_name = '/local/dataraid/databank/ESRF/scan.edf'
dark_file_name = '/local/dataraid/databank/ESRF/dark.edf'
white_file_name = '/local/dataraid/databank/ESRF/flat.edf'
hdf5_file_name = '/local/dataraid/databank/dataExchange/microCT/xx_ESRF.h5'
sample_name = 'esrf'
mydata = dx.Import()
# Create minimal hdf5 file
mydata.stack(file_name,
hdf5_file_name=hdf5_file_name,
white_file_name=white_file_name,
dark_file_name=dark_file_name,
projections_data_type='edf',
white_data_type='edf',
dark_data_type='edf',
sample_name=sample_name,
log='INFO')
def main():
file_name = '/local/dataraid/databank/APS_15_ID/AluminaStick_0A_fullRunRenamed/AluminaStick_.hdf'
projections_start = 1
projections_end = 361
# to reconstruct a subset of slices set slices_start and slices_end
# if omitted the full data set is recontructed
slices_start = 800
slices_end = 804
mydata = dx.Import()
# Read series of images
data, white, dark, theta = mydata.xtomo_raw(
file_name,
projections_start=projections_start,
projections_end=projections_end,
slices_start=slices_start,
slices_end=slices_end,
projections_digits=4,
data_type='hdf5',
log='INFO')
# TomoPy xtomo object creation and pipeline of methods.
d = tomopy.xtomo_dataset(log='debug')
d.dataset(data, white, dark, theta)
d.normalize()
d.correct_drift()
#d.optimize_center()
d.phase_retrieval(pixel_size=0.9e-4, dist=8.1, energy=17)
#d.correct_drift()
d.center = 772.2
d.gridrec()
# Write to stack of TIFFs.
mydata = ex.Export()
mydata.xtomo_tiff(data=d.data_recon,
output_file='tmp/AluminaStick_0A_',
axis=0)
