def write_example(filename):
# --- prepare data ---
# Generate fake data
rawdata = np.ones(180 * 256 * 256, np.uint16).reshape(180, 256, 256)
rawdata_white = np.ones(2 * 256 * 256, np.uint16).reshape(2, 256, 256)
rawdata_dark = np.zeros(10 * 256 * 256, np.uint16).reshape(10, 256, 256)
# x, y and z ranges
x = np.arange(256)
y = np.arange(256)
z = np.arange(180);
# --- create file ---
# Open DataExchangeFile file
f = DataExchangeFile(filename, mode='w')
# Create core HDF5 dataset in exchange group for 180 deep stack
# of x,y images /exchange/data
f.add_entry([
DataExchangeEntry.data(data={'value':rawdata, 'units':'counts'}),
DataExchangeEntry.data(data_dark={'value':rawdata_dark, 'units':'counts'}),
DataExchangeEntry.data(data_white={'value':rawdata_white, 'units':'counts'})
]
)
# --- All done ---
f.close()
def write_example(filename):
# --- prepare data ---
# Generate fake raw data
rawdata = np.ones(180 * 256 * 256, np.uint16).reshape(180, 256, 256)
# x, y and z ranges
x = np.arange(128)
y = np.arange(128)
z = np.arange(180);
# --- create file ---
# Open DataExchange file
f = DataExchangeFile(filename, mode='w')
# Create core HDF5 dataset in exchange group for 180 deep stack of x,y
# images /exchange/data
data_en = DataExchangeEntry.data(data={'value': rawdata, 'units':'counts', 'description': 'Projection Data',
'dataset_opts': {'compression': 'gzip', 'compression_opts': 4} })
f.add_entry(data_en)
# The default location for sample in DataExchangeEntry is /measurement/sample
# To override the default set e.g 'root'='/measurement_4/sample'
sample_en = DataExchangeEntry.sample(name={'value': 'Minivirus'}, temperature={'value': 200.0, 'units':'celsius',
'dataset_opts': {'dtype': 'd'}})
f.add_entry(sample_en)
# --- All done ---
f.close()
def write_example(filename):
# --- prepare data ---
# Generate fake data
rawdata = np.ones(180 * 256 * 256, np.uint16).reshape(180, 256, 256)
rawdata_white = np.ones(2 * 256 * 256, np.uint16).reshape(2, 256, 256)
rawdata_dark = np.zeros(10 * 256 * 256, np.uint16).reshape(10, 256, 256)
# x, y and z ranges
x = np.arange(256)
y = np.arange(256)
z = np.arange(180)
# Fabricated theta values
theta = (z / float(180)) * 180.0
theta_white = (0.0, 180.0)
theta_dark = (0.0, 0.0, 0.0, 0.0, 0.0, 180.0, 180.0, 180.0, 180.0, 180.0)
# --- create file ---
# Open HDF5 file
f = DataExchangeFile(filename, mode='w')
#Create HDF5 dataset in exchange group for data, data_dark & data_white, theta, theta_dark, theta_white under /exchange
f.add_entry([
DataExchangeEntry.data(data={
'value': rawdata,
'units': 'counts',
'axes': 'theta:y:x'
}),
DataExchangeEntry.data(data_dark={
'value': rawdata_dark,
'units': 'counts',
'axes': 'theta:y:x'
}),
DataExchangeEntry.data(data_white={
'value': rawdata_white,
'units': 'counts',
'axes': 'theta:y:x'
}),
DataExchangeEntry.data(theta={
'value': theta,
'units': 'degrees'
}),
DataExchangeEntry.data(theta_dark={
'value': theta_dark,
'units': 'degrees'
}),
DataExchangeEntry.data(theta_white={
'value': theta_white,
'units': 'degrees'
})
])
# --- All done ---
f.close()
def main():
file_name = '/local/data/databank/Diamond/projections_13429.hdf'
hdf5_file_name = '/local/data/databank/dataExchange/microCT/Diamond_2bin.h5'
mydata = Convert()
# Create minimal hdf5 file
if verbose: print "Reading data ... "
mydata.nexus(file_name,
hdf5_file_name = hdf5_file_name,
projections_start=20,
projections_end=1820,
projections_step=2,
white_start=11,
white_end=20,
dark_start=1,
dark_end=3,
sample_name = 'unknown'
)
# Add extra metadata if available / desired
# Open DataExchange file
f = DataExchangeFile(hdf5_file_name, mode='a')
# Create HDF5 subgroup
# /measurement/instrument
f.add_entry( DataExchangeEntry.instrument(name={'value': 'Diamond I12'}) )
### Create HDF5 subgroup
### /measurement/instrument/source
f.add_entry( DataExchangeEntry.source(name={'value': "Diamond Light Source"},
date_time={'value': "2013-11-30T19:17:04+0100"},
beamline={'value': "JEEP I12"},
)
)
# Create HDF5 subgroup
# /measurement/experimenter
f.add_entry( DataExchangeEntry.experimenter(name={'value':"Michael Drakopoulos"},
role={'value':"Project PI"},
)
)
f.close()
print "Done creating data exchange file: ", hdf5_file_name
def write_example(filename):
# --- prepare data ---
# Generate fake raw data
rawdata = np.ones(180 * 256 * 256, np.uint16).reshape(180, 256, 256)
# x, y and z ranges
x = np.arange(128)
y = np.arange(128)
z = np.arange(180)
# --- create file ---
# Open HDF5 file
f = DataExchangeFile(filename, mode='w')
# Create core HDF5 dataset in exchange group for 180 deep stack of x,y
# images /exchange/data
f.add_entry(
DataExchangeEntry.data(
data={
'value': rawdata,
'units': 'counts',
'description': 'Projection Data',
'dataset_opts': {
'compression': 'gzip',
'compression_opts': 4
}
}))
# Create HDF5 subgroup
# /measurement/sample
f.add_entry(
DataExchangeEntry.sample(name={'value': 'Minivirus'},
temperature={
'value': 200.0,
'units': 'celsius',
'dataset_opts': {
'dtype': 'd'
}
}))
# Create HDF5 subgroup
# /measurement/instrument
f.add_entry(DataExchangeEntry.instrument(name={'value': 'APS 2-BM'}))
# Create HDF5 subgroup
# /measurement/instrument/monochromator
f.add_entry(
DataExchangeEntry.monochromator(name={'value': 'DMM'},
energy={
'value': 10.00,
'units': 'keV',
'dataset_opts': {
'dtype': 'd'
}
}))
# --- All done ---
f.close()
def pack_data_exchange():
f = DataExchangeFile(CXP.io.data_exchange_filename, mode='w')
sim = DataExchangeEntry.simulation(
name={'value': 'Simulated Ptycho Data.'},
energy={
'value': CXP.experiment.energy,
'units': 'keV'
},
focusing_optic={'value': CXP.experiment.optic},
probe_modes={'value': CXP.reconstruction.probe_modes},
noise_model={'value': CXP.simulation.noise_model},
gaussian_noise_level={'value': CXP.simulation.gaussian_noise_level},
total_photons={'value': CXP.simulation.total_photons},
beam_stop={'value': CXP.simulation.beam_stop},
beam_stop_size={'value': CXP.simulation.beam_stop_size},
beam_stop_attenuation={'value': CXP.simulation.beam_stop_attenuation},
defocus={'value': CXP.simulation.defocus},
position_jitter={
'value': CXP.reconstruction.initial_position_jitter_radius,
'units': 'pixels'
})
f.add_entry(sim)
sample = DataExchangeEntry.sample(
root='/simulation',
name={'value': 'ground truth sample complex amplitude'},
data={
'value': cxph.sample.data[0],
'units': 'sqrt(counts)'
},
)
f.add_entry(sample)
probe = DataExchangeEntry.sample(
root='/simulation',
entry_name='probe',
)
for mode in range(CXP.reconstruction.probe_modes):
setattr(probe, 'mode_{:d}'.format(mode), {
'value': cxph.input_probe.modes[mode].data[0],
'units': 'counts'
})
f.add_entry(probe)
detector = DataExchangeEntry.detector(
root='/simulation',
x_pixel_size={'value': CXP.experiment.dx_d},
y_pixel_size={'value': CXP.experiment.dx_d},
x_dimension={'value': CXP.experiment.px},
y_dimension={'value': CXP.experiment.py},
distance={'value': CXP.experiment.z},
basis_vectors={
'value': [[0, -CXP.experiment.dx_d, 0],
[-CXP.experiment.dx_d, 0, 0]]
},
corner_position={'value': [0, 0, 0]})
f.add_entry(detector)
data = DataExchangeEntry.data(
name={'value': 'simulated_data'},
data={
'value': sp.array(cxph.det_mod.data),
'axes': 'translation:y:x',
'units': 'counts',
'dataset_opts': {
'compression': 'gzip',
'compression_opts': 4
}
},
translation={'value': '/exchange/sample/geometry/translation'})
f.add_entry(data)
# Get scan positions into dex format
pos = sp.zeros((cxph.positions.total, 3))
y, x = cxph.positions.correct
for i in range(cxph.positions.total):
pos[i, 0], pos[i, 1] = x[i] * CXP.dx_s, y[i] * CXP.dx_s
positions = DataExchangeEntry.translation(
root='/exchange/sample/geometry',
name={'value': 'ptychography scan positions'},
scan_type={'value': CXP.measurement.ptycho_scan_type},
data={
'value': pos,
'units': 'm'
})
f.add_entry(positions)
f.close()
def main():
file_name = '/local/data/databank/TXM_26ID/20130731_004_Stripe_Solder_Sample_Tip1_TomoScript_181imgs_p1s_b1.txrm'
white_file_name = '/local/data/databank/TXM_26ID/20130731_001_Background_Reference_20imgs_p5s_b1.xrm'
hdf5_file_name = '/local/data/databank/dataExchange/TXM/20130731_004_Stripe_Solder_Sample_Tip1_nx.h5'
log_file = '/local/data/databank/dataExchange/TXM/20130731_004_Stripe_Solder_Sample_Tip1.log'
mydata = Convert()
# Create minimal hdf5 file
if verbose: print "Reading data ... "
mydata.stack(file_name,
hdf5_file_name=hdf5_file_name,
white_file_name=white_file_name,
sample_name='Stripe_Solder_Sample_Tip1')
# Add extra metadata if available / desired
reader = xradia.xrm()
array = dstruct
reader.read_txrm(file_name, array)
# Read angles
n_angles = np.shape(array.exchange.angles)
if verbose: print "Done reading ", n_angles, " angles"
theta = np.zeros(n_angles)
theta = array.exchange.angles[:]
# Save any other available metadata in a log file
f = open(log_file, 'w')
f.write('Data creation date: \n')
f.write(str(array.information.file_creation_datetime))
f.write('\n')
f.write('=======================================\n')
f.write('Sample name: \n')
f.write(str(array.information.sample.name))
f.write('\n')
f.write('=======================================\n')
f.write('Experimenter name: \n')
f.write(str(array.information.experimenter.name))
f.write('\n')
f.write('=======================================\n')
f.write('X-ray energy: \n')
f.write(str(array.exchange.energy))
f.write(str(array.exchange.energy_units))
f.write('\n')
f.write('=======================================\n')
f.write('Angles: \n')
f.write(str(array.exchange.angles))
f.write('\n')
f.write('=======================================\n')
f.write('Data axes: \n')
f.write(str(array.exchange.data_axes))
f.write('\n')
f.write('=======================================\n')
f.write('x distance: \n')
f.write(str(array.exchange.x))
f.write('\n')
f.write('=======================================\n')
f.write('x units: \n')
f.write(str(array.exchange.x_units))
f.write('\n')
f.write('=======================================\n')
f.write('y distance: \n')
f.write(str(array.exchange.y))
f.write('\n')
f.write('=======================================\n')
f.write('y units: \n')
f.write(str(array.exchange.y_units))
f.write('\n')
f.close()
# Open DataExchange file
f = DataExchangeFile(hdf5_file_name, mode='a')
# Create HDF5 subgroup
# /measurement/instrument
f.add_entry(DataExchangeEntry.instrument(name={'value': 'APS-CNM 26-ID'}))
### Create HDF5 subgroup
### /measurement/instrument/source
f.add_entry(
DataExchangeEntry.source(
name={'value': "Advanced Photon Source"},
date_time={'value': "2013-07-31T19:42:13+0100"},
beamline={'value': "26-ID"},
))
# Create HDF5 subgroup
# /measurement/instrument/monochromator
f.add_entry(
DataExchangeEntry.monochromator(
type={'value': 'Unknown'},
energy={
'value': float(array.exchange.energy[0]),
'units': 'keV',
'dataset_opts': {
'dtype': 'd'
}
},
mono_stripe={'value': 'Unknown'},
))
# Create HDF5 subgroup
# /measurement/experimenter
f.add_entry(
DataExchangeEntry.experimenter(
name={'value': "Robert Winarski"},
role={'value': "Project PI"},
))
# Create HDF5 subgroup
# /measurement/sample
f.add_entry(
DataExchangeEntry.data(theta={
'value': theta,
'units': 'degrees'
}))
f.close()
print "Done creating data exchange file: ", hdf5_file_name
def xtomo_exchange(self,
data,
data_white=None,
data_dark=None,
theta=None,
sample_name=None,
data_exchange_type=None,
hdf5_file_name=None,
log='INFO'):
"""
Write 3-D data to a data-exchange file.
Parameters
----------
data : ndarray
3-D X-ray absorption tomography raw data.
Size of the dimensions should be:
[projections, slices, pixels].
data_white, data_dark : ndarray, optional
3-D white-field/dark_field data. Multiple
projections are stacked together to obtain
a 3-D matrix. 2nd and 3rd dimensions should
be the same as data: [shots, slices, pixels].
theta : ndarray, optional
Data acquisition angles corresponding
to each projection.
data_excahnge_type : str
label defyining the type of data contained in data exchange file
for raw data tomography data use 'tomography_raw_projections'
hd5_file_name : str
Output file.
Notes
-----
If file exists, does nothing
Examples
--------
- Convert tomographic projection series (raw, dark, white) of tiff in data exchange:
>>> from dataexchange import xtomo_importer as dx
>>> from dataexchange import xtomo_exporter as ex
>>> 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/tmp/Anka.h5'
>>> projections_start = 0
>>> projections_end = 3167
>>> white_start = 0
>>> white_end = 100
>>> dark_start = 0
>>> dark_end = 100
>>> sample_name = 'Anka'
>>>
>>> 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,
>>> dark_file_name = dark_file_name,
>>> dark_start = dark_start,
>>> dark_end = dark_end,
>>> 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',
>>> sample_name = sample_name
>>> )
"""
if (hdf5_file_name != None):
if os.path.isfile(hdf5_file_name):
self.logger.error("Data Exchange file: [%s] already exists",
hdf5_file_name)
else:
# Create new folder.
dirPath = os.path.dirname(hdf5_file_name)
if not os.path.exists(dirPath):
os.makedirs(dirPath)
# Get the file_name in lower case.
lFn = hdf5_file_name.lower()
# Split the string with the delimeter '.'
end = lFn.split('.')
# Write the Data Exchange HDF5 file.
# Open DataExchange file
f = DataExchangeFile(hdf5_file_name, mode='w')
self.logger.info("Creating Data Exchange File [%s]",
hdf5_file_name)
# Create core HDF5 dataset in exchange group for projections_theta_range
# deep stack of x,y images /exchange/data
self.logger.info(
"Adding projections to Data Exchange File [%s]",
hdf5_file_name)
f.add_entry(
DataExchangeEntry.data(
data={
'value': data,
'units': 'counts',
'description': 'transmission',
'axes': 'theta:y:x'
}))
# f.add_entry( DataExchangeEntry.data(data={'value': data, 'units':'counts', 'description': 'transmission', 'axes':'theta:y:x', 'dataset_opts': {'compression': 'gzip', 'compression_opts': 4} }))
if (theta != None):
f.add_entry(
DataExchangeEntry.data(theta={
'value': theta,
'units': 'degrees'
}))
self.logger.info("Adding theta to Data Exchange File [%s]",
hdf5_file_name)
else:
self.logger.warning("theta is not defined")
if (data_dark != None):
self.logger.info(
"Adding dark fields to Data Exchange File [%s]",
hdf5_file_name)
f.add_entry(
DataExchangeEntry.data(
data_dark={
'value': data_dark,
'units': 'counts',
'axes': 'theta_dark:y:x'
}))
# f.add_entry( DataExchangeEntry.data(data_dark={'value': data_dark, 'units':'counts', 'axes':'theta_dark:y:x', 'dataset_opts': {'compression': 'gzip', 'compression_opts': 4} }))
else:
self.logger.warning("data dark is not defined")
if (data_white != None):
self.logger.info(
"Adding white fields to Data Exchange File [%s]",
hdf5_file_name)
f.add_entry(
DataExchangeEntry.data(
data_white={
'value': data_white,
'units': 'counts',
'axes': 'theta_white:y:x'
}))
# f.add_entry( DataExchangeEntry.data(data_white={'value': data_white, 'units':'counts', 'axes':'theta_white:y:x', 'dataset_opts': {'compression': 'gzip', 'compression_opts': 4} }))
else:
self.logger.warning("data white is not defined")
if (data_exchange_type != None):
self.logger.info(
"Adding data type to Data Exchange File [%s]",
hdf5_file_name)
f.add_entry(
DataExchangeEntry.data(
title={'value': data_exchange_type}))
if (sample_name == None):
sample_name = end[0]
f.add_entry(
DataExchangeEntry.sample(
name={'value': sample_name},
description={
'value':
'Sample name was assigned by the HDF5 converter and based on the HDF5 file name'
}))
else:
f.add_entry(
DataExchangeEntry.sample(
name={'value': sample_name},
description={
'value':
'Sample name was read from the user log file'
}))
f.close()
self.logger.info("DONE!!!!. Created Data Exchange File [%s]",
hdf5_file_name)
else:
self.logger.warning("Nothing to do ...")
def main():
file_name = '/local/data/databank/TXM_26ID/Miller1/ABR_1SP_.tif'
#dark_file_name = '/local/data/databank/AS/Mayo_tooth_AS/BG__AFTER_.tif'
#white_file_name = '/local/data/databank/AS/Mayo_tooth_AS/BG__BEFORE_.tif'
hdf5_file_name = '/local/data/databank/dataExchange/TXM/TXM_APS26IDMiller1.h5'
sample_name = 'Teeth'
projections_start = 0
projections_end = 361
white_start = 0
white_end = 0
white_step = 1
dark_start = 0
dark_end = 0
dark_step = 1
verbose = True
if verbose: print "Input projection base name: ", file_name
#if verbose: print "Input white base name: ", white_file_name
#if verbose: print "Input dark base name: ", dark_file_name
if verbose: print "Output data exchange file name: ", hdf5_file_name
mydata = Convert()
# Create minimal hdf5 file
mydata.series_of_images(
file_name,
hdf5_file_name,
projections_start,
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,
#sample_name = sample_name,
projections_digits=4,
#white_digits = 2,
#dark_digits = 2,
projections_zeros=True,
verbose=False)
if verbose: print "Done reading data ... "
# Add extra metadata if available
# Open DataExchange file
f = DataExchangeFile(hdf5_file_name, mode='a')
# Create HDF5 subgroup
# /measurement/instrument
f.add_entry(
DataExchangeEntry.instrument(
name={'value': 'Australian Synchrotron Facility'}))
# Create HDF5 subgroup
# /measurement/instrument/source
f.add_entry(
DataExchangeEntry.source(
name={'value': 'Australian Synchrotron FacilityI'},
date_time={'value': "2013-10-19T22:22:13+0100"},
beamline={'value': "Tomography"},
))
# /measurement/experimenter
f.add_entry(
DataExchangeEntry.experimenter(
name={'value': "Sherry Mayo"},
role={'value': "Project PI"},
))
f.close()
if verbose: print "Done creating data exchange file: ", hdf5_file_name
def xtomo_exchange(self,
data,
data_white=None,
data_dark=None,
theta=None,
data_exchange_type=None,
source_name=None,
source_mode=None,
source_datetime=None,
beamline=None,
energy=None,
current=None,
actual_pixel_size=None,
experimenter_name=None,
experimenter_affiliation=None,
experimenter_email=None,
instrument_comment=None,
sample_name=None,
sample_comment=None,
acquisition_mode=None,
acquisition_comment=None,
sample_position_x=None,
sample_position_y=None,
sample_position_z=None,
sample_image_shift_x=None,
sample_image_shift_y=None,
hdf5_file_name=None,
axes='theta:y:x',
log='INFO'):
"""
Write 3-D data to a data-exchange file.
Parameters
data : ndarray
3-D X-ray absorption tomography raw data.
Size of the dimensions should be:
[projections, slices, pixels].
data_white, data_dark : ndarray, optional
3-D white-field/dark_field data. Multiple
projections are stacked together to obtain
a 3-D matrix. 2nd and 3rd dimensions should
be the same as data: [shots, slices, pixels].
theta : ndarray, optional
Data acquisition angles corresponding
to each projection.
data_excahnge_type : str, optional
label defyining the type of data contained in data exchange file
for raw data tomography data use 'tomography_raw_projections'
source_name, source_mode, source_datetime : str, optional
label defining the source name, operation mode and date/time when these values were taken
beamline : str, optional
label defining the beamline name
energy, current : float, optional
X-ray energy and bean current
actual_pixel_size : float, optional
pixel size on the sample plane
experimenter_name, experimenter_affiliation, experimenter_email : str, optional
user name, affiliation and e-mail address
instrument_comment : str, optional
instrument comment
sample_name, sample_comment : str, optional
sample name and comment
acquisition_mode, acquisition_comment : str, optional
acquisition mode and comment
hd5_file_name : str
Output file.
Notes
-----
If file exists, does nothing
Examples
- Convert tomographic projection series (raw, dark, white) of tiff in data exchange:
>>> import dataexchange
>>> 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/tmp/Anka.h5'
>>> projections_start = 0
>>> projections_end = 3167
>>> white_start = 0
>>> white_end = 100
>>> dark_start = 0
>>> dark_end = 100
>>> sample_name = 'Anka'
>>>
>>> # Read raw data
>>> read = dataexchange.Import()
>>> data, white, dark, theta = read.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,
>>> dark_file_name = dark_file_name,
>>> dark_start = dark_start,
>>> dark_end = dark_end,
>>> projections_digits = 5,
>>> log='INFO'
>>> )
>>>
>>> # Save data
>>> write = dataexchange.Export()
>>> write.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
>>> )
"""
if (hdf5_file_name != None):
if os.path.isfile(hdf5_file_name):
self.logger.error("Data Exchange file: [%s] already exists",
hdf5_file_name)
else:
# Create new folder.
dirPath = os.path.dirname(hdf5_file_name)
if not os.path.exists(dirPath):
os.makedirs(dirPath)
# Get the file_name in lower case.
lFn = hdf5_file_name.lower()
# Split the string with the delimeter '.'
end = lFn.split('.')
# Write the Data Exchange HDF5 file.
# Open DataExchange file
f = DataExchangeFile(hdf5_file_name, mode='w')
self.logger.info("Creating Data Exchange File [%s]",
hdf5_file_name)
# Create core HDF5 dataset in exchange group for projections_theta_range
# deep stack of x,y images /exchange/data
self.logger.info(
"Adding projections to Data Exchange File [%s]",
hdf5_file_name)
f.add_entry(
DataExchangeEntry.data(
data={
'value': data,
'units': 'counts',
'description': 'transmission',
'axes': axes
}))
# f.add_entry( DataExchangeEntry.data(data={'value': data, 'units':'counts', 'description': 'transmission', 'axes':'theta:y:x', 'dataset_opts': {'compression': 'gzip', 'compression_opts': 4} }))
if (theta != None):
f.add_entry(
DataExchangeEntry.data(theta={
'value': theta,
'units': 'degrees'
}))
self.logger.info("Adding theta to Data Exchange File [%s]",
hdf5_file_name)
else:
self.logger.warning("theta is not defined")
if (data_dark != None):
self.logger.info(
"Adding dark fields to Data Exchange File [%s]",
hdf5_file_name)
f.add_entry(
DataExchangeEntry.data(
data_dark={
'value': data_dark,
'units': 'counts',
'axes': 'theta_dark:y:x'
}))
# f.add_entry( DataExchangeEntry.data(data_dark={'value': data_dark, 'units':'counts', 'axes':'theta_dark:y:x', 'dataset_opts': {'compression': 'gzip', 'compression_opts': 4} }))
else:
self.logger.warning("data dark is not defined")
if (data_white != None):
self.logger.info(
"Adding white fields to Data Exchange File [%s]",
hdf5_file_name)
f.add_entry(
DataExchangeEntry.data(
data_white={
'value': data_white,
'units': 'counts',
'axes': 'theta_white:y:x'
}))
# f.add_entry( DataExchangeEntry.data(data_white={'value': data_white, 'units':'counts', 'axes':'theta_white:y:x', 'dataset_opts': {'compression': 'gzip', 'compression_opts': 4} }))
else:
self.logger.warning("data white is not defined")
if (data_exchange_type != None):
self.logger.info(
"Adding data type to Data Exchange File [%s]",
hdf5_file_name)
f.add_entry(
DataExchangeEntry.data(
title={'value': data_exchange_type}))
if (source_name != None):
f.add_entry(
DataExchangeEntry.source(name={'value': source_name}))
if (source_mode != None):
f.add_entry(
DataExchangeEntry.source(mode={'value': source_mode}))
if (source_datetime != None):
f.add_entry(
DataExchangeEntry.source(
datetime={'value': source_datetime}))
if (beamline != None):
f.add_entry(
DataExchangeEntry.source(beamline={'value': beamline}))
if (energy != None):
f.add_entry(
DataExchangeEntry.monochromator(
energy={
'value': energy,
'units': 'keV',
'dataset_opts': {
'dtype': 'd'
}
}))
if (current != None):
f.add_entry(
DataExchangeEntry.source(
current={
'value': current,
'units': 'mA',
'dataset_opts': {
'dtype': 'd'
}
}))
if (actual_pixel_size != None):
f.add_entry(
DataExchangeEntry.detector(actual_pixel_size_x={
'value': actual_pixel_size,
'units': 'microns',
'dataset_opts': {
'dtype': 'd'
}
},
actual_pixel_size_y={
'value':
actual_pixel_size,
'units': 'microns',
'dataset_opts': {
'dtype': 'd'
}
}))
if (experimenter_name != None):
f.add_entry(
DataExchangeEntry.experimenter(
name={'value': experimenter_name}))
if (experimenter_affiliation != None):
f.add_entry(
DataExchangeEntry.experimenter(
affiliation={'value': experimenter_affiliation}))
if (experimenter_email != None):
f.add_entry(
DataExchangeEntry.experimenter(
email={'value': experimenter_email}))
if (instrument_comment != None):
f.add_entry(
DataExchangeEntry.instrument(
comment={'value': instrument_comment}))
if (sample_name == None):
sample_name = end[0]
f.add_entry(
DataExchangeEntry.sample(
name={'value': sample_name},
description={
'value':
'Sample name assigned by the HDF5 converter and based on the HDF5 file name'
}))
else:
f.add_entry(
DataExchangeEntry.sample(name={'value': sample_name}))
if (sample_comment != None):
f.add_entry(
DataExchangeEntry.sample(
comment={'value': sample_comment}))
if (acquisition_mode != None):
f.add_entry(
DataExchangeEntry.acquisition(
mode={'value': acquisition_mode}))
if (acquisition_comment != None):
f.add_entry(
DataExchangeEntry.acquisition(
comment={'value': acquisition_comment}))
if (sample_position_x != None):
f.add_entry(
DataExchangeEntry.acquisition(
sample_position_x={
'value': sample_position_x,
'units': 'microns',
'dataset_opts': {
'dtype': 'd'
}
}))
if (sample_position_y != None):
f.add_entry(
DataExchangeEntry.acquisition(
sample_position_y={
'value': sample_position_y,
'units': 'microns',
'dataset_opts': {
'dtype': 'd'
}
}))
if (sample_position_z != None):
f.add_entry(
DataExchangeEntry.acquisition(
sample_position_z={
'value': sample_position_z,
'units': 'microns',
'dataset_opts': {
'dtype': 'd'
}
}))
if (sample_image_shift_x != None):
f.add_entry(
DataExchangeEntry.acquisition(
sample_image_shift_x={
'value': sample_image_shift_x,
'units': 'microns',
'dataset_opts': {
'dtype': 'd'
}
}))
if (sample_image_shift_y != None):
f.add_entry(
DataExchangeEntry.acquisition(
sample_image_shift_y={
'value': sample_image_shift_y,
'units': 'microns',
'dataset_opts': {
'dtype': 'd'
}
}))
f.close()
self.logger.info("DONE!!!!. Created Data Exchange File [%s]",
hdf5_file_name)
else:
self.logger.warning("Nothing to do ...")
