#!/usr/bin/env python
import numpy as np
import argparse
import sys
import os
import logging
from py_src import read_config
from py_src import py_utils
if __name__ == "__main__":
logging.basicConfig(filename="recon.log", level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
parser = py_utils.my_argparser(description="make detector")
args = parser.special_parse_args()
det_file = os.path.join(args.main_dir, read_config.get_filename(args.config_file, 'make_detector', "out_detector_file"))
to_write = py_utils.check_to_overwrite(det_file)
logging.info("\n\nStarting make_detector....")
logging.info(' '.join(sys.argv))
if to_write:
timer = py_utils.my_timer()
pm = read_config.get_detector_config(args.config_file, show=args.vb)
q_pm = read_config.compute_q_params(pm['detd'], pm['dets_x'], pm['dets_y'], pm['pixsize'], pm['wavelength'], pm['ewald_rad'], show=args.vb)
timer.reset_and_report("Reading experiment parameters") if args.vb else timer.reset()
fov_len = 2 * int(np.ceil(q_pm['fov_in_A']/q_pm['half_p_res']/2.)) + 3
det_cen_x = pm['detc_x']
det_cen_y = pm['detc_y']
qscaling = 1. / pm['wavelength'] / q_pm['q_sep']
(x, y) = np.mgrid[0:pm['dets_x'], 0:pm['dets_y']]
(x, y) = (x.flatten()-det_cen_x, y.flatten()-det_cen_y)
'''
import os
import numpy as np
import h5py
import sys
import logging
#Add utils directory to pythonpath
sys.path.append(os.path.dirname(os.path.dirname(os.path.realpath(__file__))))
from py_src import py_utils
from py_src import writeemc
from py_src import read_config
if __name__ == '__main__':
logging.basicConfig(filename='recon.log', level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
parser = py_utils.my_argparser(description='cheetahtodet')
parser.add_argument('h5_name', help='HDF5 file to convert to detector format')
parser.add_argument('-M', '--mask', help='Path to detector style mask (0:good, 1:no_orient, 2:bad) in h5 file')
parser.add_argument('--mask_dset', help='Data set in mask file. Default: /data/data', default='data/data')
args = parser.special_parse_args()
logging.info('Starting cheetahtodet...')
logging.info(' '.join(sys.argv))
pm = read_config.get_detector_config(args.config_file, show=args.vb)
q_pm = read_config.compute_q_params(pm['detd'], pm['dets_x'], pm['dets_y'], pm['pixsize'], pm['wavelength'], pm['ewald_rad'], show=args.vb)
output_folder = read_config.get_filename(args.config_file, 'emc', 'output_folder')
# Cheetah geometry files have coordinates in m
with h5py.File(args.h5_name, 'r') as f:
x = f['x'][:].flatten() * 1.e3
y = f['y'][:].flatten() * 1.e3
import logging
#Add utils directory to pythonpath
sys.path.append(os.path.dirname(os.path.dirname(os.path.realpath(__file__))))
from py_src import py_utils
from py_src import writeemc
from py_src import read_config
try:
import psana
except ImportError:
sys.stderr.write('This utility needs PSANA to run. Unable to import psana module\n')
sys.exit(1)
if __name__ == '__main__':
logging.basicConfig(filename='recon.log', level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
parser = py_utils.my_argparser(description='PSANA to det')
parser.add_argument('exp_string', help='PSANA experiment string')
parser.add_argument('det_name', help='Detector name (either source string or alias)')
args = parser.special_parse_args()
logging.info('Starting psanatodet...')
logging.info(' '.join(sys.argv))
pm = read_config.get_detector_config(args.config_file, show=args.vb)
q_pm = read_config.compute_q_params(pm['detd'], pm['dets_x'], pm['dets_y'], pm['pixsize'], pm['wavelength'], pm['ewald_rad'], show=args.vb)
output_folder = read_config.get_filename(args.config_file, 'emc', 'output_folder')
ds = psana.DataSource(args.exp_string + ':idx')
run = ds.runs().next()
times = run.times()
evt = run.event(times[0])
det = psana.Detector(args.det_name)
#!/usr/bin/env python
import numpy as np
import argparse
import sys
import os
import logging
from py_src import read_config
from py_src import process_pdb
from py_src import py_utils
if __name__ == "__main__":
# logging config must occur before my_argparser, because latter already starts logging
logging.basicConfig(filename="recon.log", level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
parser = py_utils.my_argparser(description="make electron density")
args = parser.special_parse_args()
logging.info("\n\nStarting.... make_densities")
logging.info(' '.join(sys.argv))
try:
pdb_file = os.path.join(args.main_dir, read_config.get_filename(args.config_file, 'make_densities', "in_pdb_file"))
pdb_code = None
except read_config.ConfigParser.NoOptionError:
pdb_code = read_config.get_filename(args.config_file, 'make_densities', 'pdb_code')
pdb_file = 'aux/%s.pdb' % pdb_code.upper()
aux_dir = os.path.join(args.main_dir, read_config.get_filename(args.config_file, 'make_densities', "scatt_dir"))
den_file = os.path.join(args.main_dir, read_config.get_filename(args.config_file, 'make_densities', "out_density_file"))
to_write = py_utils.check_to_overwrite(den_file)
if to_write:
timer = py_utils.my_timer()
pm = read_config.get_detector_config(args.config_file, show=args.vb)
#!/usr/bin/env python
import numpy as np
import argparse
import sys
import os
import logging
from py_src import read_config
from py_src import py_utils
if __name__ == "__main__":
logging.basicConfig(filename="recon.log",
level=logging.INFO,
format='%(asctime)s - %(levelname)s -%(message)s')
parser = py_utils.my_argparser(description="make intensities")
args = parser.special_parse_args()
den_file = os.path.join(
args.main_dir,
read_config.get_filename(args.config_file, 'make_intensities',
"in_density_file"))
intens_file = os.path.join(
args.main_dir,
read_config.get_filename(args.config_file, 'make_intensities',
"out_intensity_file"))
to_write = py_utils.check_to_overwrite(intens_file)
logging.info("Starting.... make_intensities")
logging.info(' '.join(sys.argv))
if to_write:
timer = py_utils.my_timer()
pm = read_config.get_detector_config(args.config_file, show=args.vb)
num = int(self.numstr.get()) - 1
if num > -1:
self.numstr.set(str(num))
self.plot_frame()
def rand_frame(self, event=None):
num = np.random.randint(0, self.num_frames)
self.numstr.set(str(num))
self.plot_frame()
def quit(self, event=None):
self.master.quit()
if __name__ == '__main__':
parser = py_utils.my_argparser(
description='Utility for viewing frames of the emc file (list)')
parser.add_argument('--cmap', help='Matplotlib color map (default: jet)')
parser.add_argument('--mask',
help='Name of mask file of type uint8 (default: None)')
args = parser.special_parse_args()
try:
pfile = read_config.get_filename(args.config_file, 'emc',
'in_photons_file')
print 'Using in_photons_file: %s' % pfile
photons_list = [pfile]
except ConfigParser.NoOptionError:
plist = read_config.get_filename(args.config_file, 'emc',
'in_photons_list')
print 'Using in_photons_list: %s' % plist
with open(plist, 'r') as f:
'''
import os
import numpy as np
import h5py
import sys
import logging
#Add utils directory to pythonpath
sys.path.append(os.path.dirname(os.path.dirname(os.path.realpath(__file__))))
from py_src import py_utils
from py_src import writeemc
from py_src import read_config
if __name__ == '__main__':
logging.basicConfig(filename='recon.log', level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
parser = py_utils.my_argparser(description='condortoemc')
parser.add_argument('condor_fname', help='Condor CXI file to convert to emc format')
parser.add_argument('-o', '--output', help='Output folder, read from config file by default', type=str, default=None)
parser.add_argument('-l', '--list', help='condor_fname is list of condor CXI files rather than a single one', action='store_true', default=False)
args = parser.special_parse_args()
logging.info('Starting condortoemc...')
logging.info(' '.join(sys.argv))
print args.config_file
pm = read_config.get_detector_config(args.config_file, show=args.vb)
if args.output is None:
output_folder = read_config.get_filename(args.config_file, 'emc', 'output_folder')
else:
output_folder = args.output
if not os.path.isfile(args.condor_fname):
from py_src import py_utils
from py_src import writeemc
from py_src import read_config
try:
import psana
except ImportError:
sys.stderr.write(
'This utility needs PSANA to run. Unable to import psana module\n')
sys.exit(1)
if __name__ == '__main__':
logging.basicConfig(filename='recon.log',
level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s')
parser = py_utils.my_argparser(description='PSANA to det')
parser.add_argument('exp_string', help='PSANA experiment string')
parser.add_argument('det_name',
help='Detector name (either source string or alias)')
args = parser.special_parse_args()
logging.info('Starting psanatodet...')
logging.info(' '.join(sys.argv))
pm = read_config.get_detector_config(args.config_file, show=args.vb)
q_pm = read_config.compute_q_params(pm['detd'],
pm['dets_x'],
pm['dets_y'],
pm['pixsize'],
pm['wavelength'],
pm['ewald_rad'],
show=args.vb)
import logging
#Add utils directory to pythonpath
sys.path.append(os.path.dirname(os.path.dirname(os.path.realpath(__file__))))
from py_src import py_utils
from py_src import writeemc
from py_src import read_config
try:
import condor
except ImportError:
sys.stderr.write('This utility needs CONDOR to run. Unable to import condor module\n')
sys.exit(1)
if __name__ == '__main__':
logging.basicConfig(filename='recon.log', level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
parser = py_utils.my_argparser(description='CONDOR to det')
parser.add_argument('filename', help='CONDOR file', type=str)
args = parser.special_parse_args()
logging.info('Starting condortodet...')
logging.info(' '.join(sys.argv))
pm = read_config.get_detector_config(args.config_file, show=args.vb)
output_folder = read_config.get_filename(args.config_file, 'emc', 'output_folder')
with h5py.File(args.filename,'r') as f:
condor_dets_x = f['detector']['nx'][0]
condor_dets_y = f['detector']['ny'][0]
condor_detc_x = f['detector']['cx'][0]
condor_detc_y = f['detector']['cy'][0]
condor_detd = f['detector']['distance'][0] # in units of m
condor_pixsize = f['detector']['pixel_size'][0] # in units of m
def bin_image(array, binning):
'''
Convenience function to bin 2D array by some bin factor
The binning must divide the array shape
'''
s = array.shape
out = array.reshape(s[0] / binning, binning, s[1] / binning,
binning).sum(axis=(1, 3))
return out
if __name__ == '__main__':
logging.basicConfig(filename='recon.log',
level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s')
parser = py_utils.my_argparser(description='h5toemc')
parser.add_argument('h5_name', help='HDF5 file to convert to emc format')
parser.add_argument('-d',
'--dset_name',
help='Name of HDF5 dataset containing photon data',
default=None)
parser.add_argument(
'-s',
'--sel_file',
help=
'Path to text file containing indices of frames\nor a set of 0 or 1 values. Default: Do all',
default=None)
parser.add_argument(
'-S',
'--sel_dset',
help='Same as --sel_file, but pointing to the name of an HDF5 dataset',
from py_src import py_utils
from py_src import writeemc
from py_src import read_config
try:
import condor
except ImportError:
sys.stderr.write(
'This utility needs CONDOR to run. Unable to import condor module\n')
sys.exit(1)
if __name__ == '__main__':
logging.basicConfig(filename='recon.log',
level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s')
parser = py_utils.my_argparser(description='CONDOR to det')
parser.add_argument('filename', help='CONDOR file', type=str)
args = parser.special_parse_args()
logging.info('Starting condortodet...')
logging.info(' '.join(sys.argv))
pm = read_config.get_detector_config(args.config_file, show=args.vb)
output_folder = read_config.get_filename(args.config_file, 'emc',
'output_folder')
with h5py.File(args.filename, 'r') as f:
condor_dets_x = f['detector']['nx'][0]
condor_dets_y = f['detector']['ny'][0]
condor_detc_x = f['detector']['cx'][0]
condor_detc_y = f['detector']['cy'][0]
condor_detd = f['detector']['distance'][0] # in units of m
'''
import os
import numpy as np
import h5py
import sys
import logging
#Add utils directory to pythonpath
sys.path.append(os.path.dirname(os.path.dirname(os.path.realpath(__file__))))
from py_src import py_utils
from py_src import writeemc
from py_src import read_config
if __name__ == '__main__':
logging.basicConfig(filename='recon.log', level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
parser = py_utils.my_argparser(description='cheetahtodet')
parser.add_argument('h5_name', help='HDF5 file to convert to detector format')
parser.add_argument('-M', '--mask', help='Path to detector style mask (0:good, 1:no_orient, 2:bad) in h5 file')
parser.add_argument('--mask_dset', help='Data set in mask file. Default: /data/data', default='data/data')
parser.add_argument('--dragonfly_mask', help='Whether mask has Dragonfly style values or not. (Default: false)', default=False, action='store_true')
args = parser.special_parse_args()
logging.info('Starting cheetahtodet...')
logging.info(' '.join(sys.argv))
pm = read_config.get_detector_config(args.config_file, show=args.vb)
q_pm = read_config.compute_q_params(pm['detd'], pm['dets_x'], pm['dets_y'], pm['pixsize'], pm['wavelength'], pm['ewald_rad'], show=args.vb)
output_folder = read_config.get_filename(args.config_file, 'emc', 'output_folder')
# Cheetah geometry files have coordinates in m
with h5py.File(args.h5_name, 'r') as f:
x = f['x'][:].flatten() * 1.e3
if self.classes.unsaved:
result = QtWidgets.QMessageBox.question(
self, 'Warning', 'Unsaved changes to class list. Save?',
QtWidgets.QMessageBox.Yes | QtWidgets.QMessageBox.No
| QtWidgets.QMessageBox.Cancel, QtWidgets.QMessageBox.Cancel)
if result == QtWidgets.QMessageBox.Yes:
self.classes.save()
event.accept()
elif result == QtWidgets.QMessageBox.No:
event.accept()
else:
event.ignore()
if __name__ == '__main__':
parser = py_utils.my_argparser(description='Data classifier')
parser.add_argument('--cmap',
help='Matplotlib color map (default: CMRmap)')
parser.add_argument(
'-M',
'--mask',
help='Whether to zero out masked pixels (default False)',
action='store_true',
default=False)
parser.add_argument('-C',
'--class_fname',
help='File containing classes for each frame',
default='my_classes.dat')
args = parser.special_parse_args()
app = QtWidgets.QApplication(sys.argv)
num_frames = 1
return ind, num_frames
def bin_image(array, binning):
'''
Convenience function to bin 2D array by some bin factor
The binning must divide the array shape
'''
s = array.shape
out = array.reshape(s[0]/binning, binning, s[1]/binning, binning).sum(axis=(1,3))
return out
if __name__ == '__main__':
logging.basicConfig(filename='recon.log', level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
parser = py_utils.my_argparser(description='h5toemc')
parser.add_argument('h5_name', help='HDF5 file to convert to emc format')
parser.add_argument('-d', '--dset_name', help='Name of HDF5 dataset containing photon data', default=None)
parser.add_argument('-s', '--sel_file', help='Path to text file containing indices of frames\nor a set of 0 or 1 values. Default: Do all', default=None)
parser.add_argument('-S', '--sel_dset', help='Same as --sel_file, but pointing to the name of an HDF5 dataset', default=None)
parser.add_argument('-l', '--list', help='h5_name is list of h5 files rather than a single one', action='store_true', default=False)
parser.add_argument('-o', '--out_fname', help='Output filename if different from calculated name', default=None)
args = parser.special_parse_args()
logging.info('Starting h5toemc....')
logging.info(' '.join(sys.argv))
pm = read_config.get_detector_config(args.config_file, show=args.vb)
output_folder = read_config.get_filename(args.config_file, 'emc', 'output_folder')
curr_num_data = 0
if not os.path.isfile(args.h5_name):
#!/usr/bin/env python
import numpy as np
import sys
import os
import ConfigParser
from py_src import py_utils
from py_src import read_config
if __name__ == "__main__":
# Read detector and photons file from config
parser = py_utils.my_argparser(description="Generate virtual powder pattern")
args = parser.special_parse_args()
try:
photons_list = [read_config.get_filename(args.config_file, 'emc', "in_photons_file")]
except ConfigParser.NoOptionError:
with open(read_config.get_param(args.config_file, 'emc', "in_photons_list"), 'r') as f:
photons_list = map(lambda x: x.rstrip(), f.readlines())
pm = read_config.get_detector_config(args.config_file, show=args.vb)
x, y = np.indices((pm['dets_x'], pm['dets_y']))
x = x.flatten()
y = y.flatten()
powder = np.zeros((x.max()+1,y.max()+1))
# For each emc file, read data and add to powder
for photons_file in photons_list:
# Read photon data
with open(photons_file, 'rb') as f:
