tools_extractdataΒΆ
This section contains the tools_extractdata script.
Download file: tools_extractdata.py
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# (C) 2016 Elettra - Sincrotrone Trieste S.C.p.A.. All rights reserved. #
# #
# #
# This file is part of STP-Core, the Python core of SYRMEP Tomo Project, #
# a software tool for the reconstruction of experimental CT datasets. #
# #
# STP-Core is free software: you can redistribute it and/or modify it #
# under the terms of the GNU General Public License as published by the #
# Free Software Foundation, either version 3 of the License, or (at your #
# option) any later version. #
# #
# STP-Core is distributed in the hope that it will be useful, but WITHOUT #
# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or #
# FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License #
# for more details. #
# #
# You should have received a copy of the GNU General Public License #
# along with STP-Core. If not, see <http://www.gnu.org/licenses/>. #
# #
###########################################################################
#
# Author: Francesco Brun
# Last modified: July, 8th 2016
#
import os
import os.path
import numpy
import time
from sys import argv, exit
from h5py import File as getHDF5
from numpy import float32
# pystp-specific:
import stp_core.io.tdf as tdf
def main(argv):
"""Extract a 2D image (projection or sinogram) from the input TDF file (DataExchange HDF5) and
creates a 32-bit RAW file to disk.
Parameters
----------
argv[0] : string
The absolute path of the input TDF.
argv[1] : int
The relative position of the image within the dataset.
argv[2] : string
One of the following options: 'tomo', 'sino', 'flat', 'dark'.
argv[3] : string
The absolute path of the output 32-bit RAW image file. Filename will be modified by adding
image width, image height, minimum and maximum value of the input TDF dataset.
Example
-------
tools_extractdata "S:\\dataset.tdf" 128 tomo "R:\\proj"
"""
try:
#
# Get input parameters:
#
infile = argv[0]
index = int(argv[1])
imtype = argv[2]
outfile = argv[3]
#
# Body
#
# Check if file exists:
if not os.path.exists(infile):
#log = open(logfilename,"a")
#log.write(os.linesep + "\tError: input TDF file not found. Process will end.")
#log.close()
exit()
# Open the HDF5 file:
f = getHDF5( infile, 'r' )
if (imtype == 'sino'):
if "/tomo" in f:
dset = f['tomo']
else:
dset = f['exchange/data']
im = tdf.read_sino( dset, index )
elif (imtype == 'dark'):
if "/dark" in f:
dset = f['dark']
else:
dset = f['exchange/data_dark']
im = tdf.read_tomo( dset, index )
elif (imtype == 'flat'):
if "/flat" in f:
dset = f['flat']
else:
dset = f['exchange/data_white']
im = tdf.read_tomo( dset, index )
else:
if "/tomo" in f:
dset = f['tomo']
else:
dset = f['exchange/data']
im = tdf.read_tomo( dset, index )
min = float(numpy.nanmin(im[:]))
max = float(numpy.nanmax(im[:]))
# Get global attributes (if any):
try:
if ('version' in f.attrs):
if (f.attrs['version'] == '1.0'):
min = float(dset_tomo.attrs['min'])
max = float(dset_tomo.attrs['max'])
except:
pass
f.close()
# Cast type:
im = im.astype(float32)
# Modify file name:
outfile = outfile + '_' + str(im.shape[1]) + 'x' + str(im.shape[0]) + '_' + str(min) + '$' + str(max)
# Write RAW data to disk:
im.tofile(outfile)
except:
exit()
if __name__ == "__main__":
main(argv[1:])
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