def run_fit_grains(self, config):
self.fit_grains_results = None
min_samples, mean_rpg = create_clustering_parameters(
config, self.ome_maps)
# Add fit_grains config
dialog_config = HexrdConfig().indexing_config['fit_grains']
config.set('fitgrains:npdiv', dialog_config['npdiv'])
config.set('fitgrains:refit', dialog_config['refit'])
config.set('fitgrains:threshold', dialog_config['threshold'])
config.set('fitgrains:tth_max', dialog_config['tth_max'])
config.set('fitgrains:tolerance:tth', dialog_config['tth_tolerances'])
config.set('fitgrains:tolerance:eta', dialog_config['eta_tolerances'])
config.set('fitgrains:tolerance:omega',
dialog_config['omega_tolerances'])
kwargs = {
'compl': self.completeness,
'qfib': self.qfib,
'qsym': config.material.plane_data.getQSym(),
'cfg': config,
'min_samples': min_samples,
'compl_thresh': config.find_orientations.clustering.completeness,
'radius': config.find_orientations.clustering.radius
}
self.update_progress_text('Running clustering')
qbar, cl = run_cluster(**kwargs)
# Generate grains table
num_grains = qbar.shape[1]
if num_grains == 0:
print('Fit Grains Complete - no grains were found')
return
shape = (num_grains, 21)
grains_table = np.empty(shape)
gw = instrument.GrainDataWriter(array=grains_table)
for gid, q in enumerate(qbar.T):
phi = 2 * np.arccos(q[0])
n = xfcapi.unitRowVector(q[1:])
grain_params = np.hstack(
[phi * n, const.zeros_3, const.identity_6x1])
gw.dump_grain(gid, 1., 0., grain_params)
gw.close()
self.update_progress_text(
f'Found {num_grains} grains. Running fit optimization.')
self.fit_grains_results = fit_grains(config,
grains_table,
write_spots_files=False)
print('Fit Grains Complete')
def run_fit_grains(self):
cfg = create_indexing_config()
write_spots = HexrdConfig().indexing_config.get('_write_spots', False)
num_grains = self.grains_table.shape[0]
self.update_progress_text(f'Running fit grains on {num_grains} grains')
kwargs = {
'cfg': cfg,
'grains_table': self.grains_table,
'write_spots_files': write_spots,
}
self.fit_grains_results = fit_grains(**kwargs)
print('Fit Grains Complete')
# If we wrote out the spots, let's write out the grains.out file too
if write_spots:
write_fit_grains_results(self.fit_grains_results, cfg)
def test_fit_grains(single_ge_include_path, test_config, grains_file_path,
grains_reference_file_path):
os.chdir(str(single_ge_include_path))
grains_table = np.loadtxt(grains_reference_file_path, ndmin=2)
ref_grain_params = grains_table[:, 3:15]
gresults = fit_grains(test_config,
grains_table,
show_progress=False,
ids_to_refine=None,
write_spots_files=False)
cresult = compare_grain_fits(np.vstack([i[-1] for i in gresults]),
ref_grain_params,
mtol=1.e-4,
ctol=1.e-3,
vtol=1.e-4)
assert cresult
def run_fit_grains(self, config):
min_samples, mean_rpg = create_clustering_parameters(
config, self.ome_maps)
kwargs = {
'compl': self.completeness,
'qfib': self.qfib,
'qsym': config.material.plane_data.getQSym(),
'cfg': config,
'min_samples': min_samples,
'compl_thresh': config.find_orientations.clustering.completeness,
'radius': config.find_orientations.clustering.radius
}
self.update_progress_text('Running clustering')
qbar, cl = run_cluster(**kwargs)
# Generate grains table
num_grains = qbar.shape[1]
if num_grains == 0:
QMessageBox.warning(self.parent, 'No Grains',
'Clustering found no grains')
return
shape = (num_grains, 21)
grains_table = np.empty(shape)
gw = instrument.GrainDataWriter(array=grains_table)
for gid, q in enumerate(qbar.T):
phi = 2 * np.arccos(q[0])
n = xfcapi.unitRowVector(q[1:])
grain_params = np.hstack(
[phi * n, const.zeros_3, const.identity_6x1])
gw.dump_grain(gid, 1., 0., grain_params)
gw.close()
self.update_progress_text(
f'Found {num_grains} grains. Running fit optimization.')
self.fit_grains_results = fit_grains(config,
grains_table,
write_spots_files=False)
print('Fit Grains Complete')
def execute(args, parser):
import logging
import os
import sys
import yaml
from hexrd import config
from hexrd.fitgrains import fit_grains
# load the configuration settings
cfgs = config.open(args.yml)
# configure logging to the console:
log_level = logging.DEBUG if args.debug else logging.INFO
if args.quiet:
log_level = logging.ERROR
logger = logging.getLogger('hexrd')
logger.setLevel(log_level)
ch = logging.StreamHandler()
ch.setLevel(logging.CRITICAL if args.quiet else log_level)
cf = logging.Formatter('%(asctime)s - %(message)s', '%y-%m-%d %H:%M:%S')
ch.setFormatter(cf)
logger.addHandler(ch)
# ...make this an attribute in cfg?
analysis_id = '%s_%s' % (
cfgs[0].analysis_name.strip().replace(' ', '-'),
cfgs[0].material.active.strip().replace(' ', '-'),
)
# if find-orientations has not already been run, do so:
quats_f = os.path.join(cfgs[0].working_dir,
'accepted_orientations_%s.dat' % analysis_id)
if not os.path.exists(quats_f):
logger.info("Missing %s, running find-orientations", quats_f)
logger.removeHandler(ch)
from . import findorientations
findorientations.execute(args, parser)
logger.addHandler(ch)
logger.info('=== begin fit-grains ===')
clobber = args.force or args.clean
for cfg in cfgs:
# prepare the analysis directory
if os.path.exists(cfg.analysis_dir) and not clobber:
logger.error(
'Analysis "%s" at %s already exists.'
' Change yml file or specify "force"', cfg.analysis_name,
cfg.analysis_dir)
sys.exit()
if not os.path.exists(cfg.analysis_dir):
os.makedirs(cfg.analysis_dir)
logger.info('*** begin analysis "%s" ***', cfg.analysis_name)
# configure logging to file for this particular analysis
logfile = os.path.join(cfg.working_dir, cfg.analysis_name,
'fit-grains.log')
fh = logging.FileHandler(logfile, mode='w')
fh.setLevel(log_level)
ff = logging.Formatter('%(asctime)s - %(name)s - %(message)s',
'%m-%d %H:%M:%S')
fh.setFormatter(ff)
logger.info("logging to %s", logfile)
logger.addHandler(fh)
if args.profile:
import cProfile as profile, pstats, StringIO
pr = profile.Profile()
pr.enable()
# process the data
gid_list = None
if args.grains is not None:
gid_list = [int(i) for i in args.grains.split(',')]
fit_grains(
cfg,
force=args.force,
clean=args.clean,
show_progress=not args.quiet,
ids_to_refine=gid_list,
)
if args.profile:
pr.disable()
s = StringIO.StringIO()
ps = pstats.Stats(pr, stream=s).sort_stats('cumulative')
ps.print_stats(50)
logger.info('%s', s.getvalue())
# stop logging for this particular analysis
fh.flush()
fh.close()
logger.removeHandler(fh)
logger.info('*** end analysis "%s" ***', cfg.analysis_name)
logger.info('=== end fit-grains ===')
# stop logging to the console
ch.flush()
ch.close()
logger.removeHandler(ch)
def execute(args, parser):
import logging
import os
import sys
import yaml
from hexrd import config
from hexrd.fitgrains import fit_grains
# load the configuration settings
cfgs = config.open(args.yml)
# configure logging to the console:
log_level = logging.DEBUG if args.debug else logging.INFO
if args.quiet:
log_level = logging.ERROR
logger = logging.getLogger('hexrd')
logger.setLevel(log_level)
ch = logging.StreamHandler()
ch.setLevel(logging.CRITICAL if args.quiet else log_level)
cf = logging.Formatter('%(asctime)s - %(message)s', '%y-%m-%d %H:%M:%S')
ch.setFormatter(cf)
logger.addHandler(ch)
# ...make this an attribute in cfg?
analysis_id = '%s_%s' %(
cfgs[0].analysis_name.strip().replace(' ', '-'),
cfgs[0].material.active.strip().replace(' ', '-'),
)
# if find-orientations has not already been run, do so:
quats_f = os.path.join(
cfgs[0].working_dir,
'accepted_orientations_%s.dat' %analysis_id
)
if not os.path.exists(quats_f):
logger.info("Missing %s, running find-orientations", quats_f)
logger.removeHandler(ch)
from . import findorientations
findorientations.execute(args, parser)
logger.addHandler(ch)
logger.info('=== begin fit-grains ===')
clobber = args.force or args.clean
for cfg in cfgs:
# prepare the analysis directory
if os.path.exists(cfg.analysis_dir) and not clobber:
logger.error(
'Analysis "%s" at %s already exists.'
' Change yml file or specify "force"',
cfg.analysis_name, cfg.analysis_dir
)
sys.exit()
if not os.path.exists(cfg.analysis_dir):
os.makedirs(cfg.analysis_dir)
logger.info('*** begin analysis "%s" ***', cfg.analysis_name)
# configure logging to file for this particular analysis
logfile = os.path.join(
cfg.working_dir,
cfg.analysis_name,
'fit-grains.log'
)
fh = logging.FileHandler(logfile, mode='w')
fh.setLevel(log_level)
ff = logging.Formatter(
'%(asctime)s - %(name)s - %(message)s',
'%m-%d %H:%M:%S'
)
fh.setFormatter(ff)
logger.info("logging to %s", logfile)
logger.addHandler(fh)
if args.profile:
import cProfile as profile, pstats, StringIO
pr = profile.Profile()
pr.enable()
# process the data
if args.grains is not None:
args.grains = [int(i) for i in args.grains.split(',')]
fit_grains(
cfg,
force=args.force,
clean=args.clean,
show_progress=not args.quiet,
ids_to_refine=args.grains,
)
if args.profile:
pr.disable()
s = StringIO.StringIO()
ps = pstats.Stats(pr, stream=s).sort_stats('cumulative')
ps.print_stats(50)
logger.info('%s', s.getvalue())
# stop logging for this particular analysis
fh.flush()
fh.close()
logger.removeHandler(fh)
logger.info('*** end analysis "%s" ***', cfg.analysis_name)
logger.info('=== end fit-grains ===')
# stop logging to the console
ch.flush()
ch.close()
logger.removeHandler(ch)
def execute(args, parser):
import logging
import os
import sys
import yaml
from hexrd import config
from hexrd.fitgrains import fit_grains
# load the configuration settings
cfgs = config.open(args.yml)
# if find-orientations has not already been run, do so:
quats_f = os.path.join(cfgs[0].working_dir, 'accepted_orientations.dat')
if not os.path.exists(quats_f):
from . import findorientations
findorientations.execute(args, parser)
# configure logging to the console:
log_level = logging.DEBUG if args.debug else logging.INFO
if args.quiet:
log_level = logging.ERROR
logger = logging.getLogger('hexrd')
logger.setLevel(log_level)
ch = logging.StreamHandler()
ch.setLevel(logging.CRITICAL if args.quiet else log_level)
cf = logging.Formatter('%(asctime)s - %(message)s', '%y-%m-%d %H:%M:%S')
ch.setFormatter(cf)
logger.addHandler(ch)
logger.info('=== begin fit-grains ===')
for cfg in config.open(args.yml):
# prepare the analysis directory
if os.path.exists(cfg.analysis_dir) and not args.force:
logger.error(
'Analysis "%s" at %s already exists.'
' Change yml file or specify "force"',
cfg.analysis_name, cfg.analysis_dir
)
sys.exit()
if not os.path.exists(cfg.analysis_dir):
os.makedirs(cfg.analysis_dir)
logger.info('*** begin analysis "%s" ***', cfg.analysis_name)
# configure logging to file for this particular analysis
logfile = os.path.join(
cfg.working_dir,
cfg.analysis_name,
'fit-grains.log'
)
fh = logging.FileHandler(logfile, mode='w')
fh.setLevel(log_level)
ff = logging.Formatter(
'%(asctime)s - %(name)s - %(message)s',
'%m-%d %H:%M:%S'
)
fh.setFormatter(ff)
logger.info("logging to %s", logfile)
logger.addHandler(fh)
# process the data
fit_grains(cfg, force=args.force, show_progress=not args.quiet)
# stop logging for this particular analysis
fh.flush()
fh.close()
logger.removeHandler(fh)
logger.info('*** end analysis "%s" ***', cfg.analysis_name)
logger.info('=== end fit-grains ===')
# stop logging to the console
ch.flush()
ch.close()
logger.removeHandler(ch)
for o, val in opts:
if o == "-p":
prof_dict["profile"] = True
elif o == "-n":
prof_dict["use_nvtx"] = True
elif o=="-c":
try:
max_grains = int(val)
except ValueError:
print "invalid grain count"
usage()
sys.exit(2)
else:
assert False, "unhandled option '{0}'".format(o)
if len(args) < 1:
usage()
sys.exit(2)
cfg_filename = args[0]
with profiling(**prof_dict):
start = time.time()
print "Using cfg file '%s'" % (cfg_filename)
config = config.open(cfg_filename)[0]
config._cfg['multiproc'] = 1 # force sequential run
target.fit_grains(config, force=True, grains=range(max_grains))
elapsed = time.time() - start
print "\nTotal processing time %.2f seconds" % elapsed
def execute(args, parser):
# load the configuration settings
cfgs = config.open(args.yml)
# configure logging to the console:
log_level = logging.DEBUG if args.debug else logging.INFO
if args.quiet:
log_level = logging.ERROR
logger = logging.getLogger('hexrd')
logger.setLevel(log_level)
ch = logging.StreamHandler()
ch.setLevel(logging.CRITICAL if args.quiet else log_level)
cf = logging.Formatter('%(asctime)s - %(message)s', '%y-%m-%d %H:%M:%S')
ch.setFormatter(cf)
logger.addHandler(ch)
# if find-orientations has not already been run, do so:
quats_f = os.path.join(
cfgs[0].working_dir,
'accepted_orientations_%s.dat' % cfgs[0].analysis_id)
if os.path.exists(quats_f):
try:
qbar = np.loadtxt(quats_f).T
except (IOError):
raise (RuntimeError,
"error loading indexing results '%s'" % quats_f)
else:
logger.info("Missing %s, running find-orientations", quats_f)
logger.removeHandler(ch)
from hexrd.findorientations import find_orientations
results = find_orientations(cfgs[0])
qbar = results['qbar']
logger.addHandler(ch)
logger.info('=== begin fit-grains ===')
clobber = args.force or args.clean
for cfg in cfgs:
# prepare the analysis directory
if os.path.exists(cfg.analysis_dir) and not clobber:
logger.error(
'Analysis "%s" at %s already exists.'
' Change yml file or specify "force"', cfg.analysis_name,
cfg.analysis_dir)
sys.exit()
# make output directories
instr = cfg.instrument.hedm
if not os.path.exists(cfg.analysis_dir):
os.makedirs(cfg.analysis_dir)
for det_key in instr.detectors:
os.mkdir(os.path.join(cfg.analysis_dir, det_key))
else:
# make sure panel dirs exist under analysis dir
for det_key in instr.detectors:
if not os.path.exists(os.path.join(cfg.analysis_dir, det_key)):
os.mkdir(os.path.join(cfg.analysis_dir, det_key))
logger.info('*** begin analysis "%s" ***', cfg.analysis_name)
# configure logging to file for this particular analysis
logfile = os.path.join(cfg.working_dir, cfg.analysis_name,
'fit-grains.log')
fh = logging.FileHandler(logfile, mode='w')
fh.setLevel(log_level)
ff = logging.Formatter('%(asctime)s - %(name)s - %(message)s',
'%m-%d %H:%M:%S')
fh.setFormatter(ff)
logger.info("logging to %s", logfile)
logger.addHandler(fh)
if args.profile:
import cProfile as profile
import pstats
from io import StringIO
pr = profile.Profile()
pr.enable()
grains_filename = os.path.join(cfg.analysis_dir, 'grains.out')
# some conditions for arg handling
existing_analysis = os.path.exists(grains_filename)
new_with_estimate = not existing_analysis \
and cfg.fit_grains.estimate is not None
new_without_estimate = not existing_analysis \
and cfg.fit_grains.estimate is None
force_with_estimate = args.force \
and cfg.fit_grains.estimate is not None
force_without_estimate = args.force and cfg.fit_grains.estimate is None
# handle args
if args.clean or force_without_estimate or new_without_estimate:
# need accepted orientations from indexing in this case
if args.clean:
logger.info(
"'clean' specified; ignoring estimate and using default")
elif force_without_estimate:
logger.info(
"'force' option specified, but no initial estimate; " +
"using default")
try:
gw = instrument.GrainDataWriter(grains_filename)
for i_g, q in enumerate(qbar.T):
phi = 2 * np.arccos(q[0])
n = xfcapi.unitRowVector(q[1:])
grain_params = np.hstack(
[phi * n, cnst.zeros_3, cnst.identity_6x1])
gw.dump_grain(int(i_g), 1., 0., grain_params)
gw.close()
except (IOError):
raise (RuntimeError, "indexing results '%s' not found!" %
'accepted_orientations_' + cfg.analysis_id + '.dat')
elif force_with_estimate or new_with_estimate:
grains_filename = cfg.fit_grains.estimate
elif existing_analysis and not (clean or force):
raise (RuntimeError, "fit results '%s' exist, " % grains_filename +
"but --clean or --force options not specified")
grains_table = np.loadtxt(grains_filename, ndmin=2)
# process the data
gid_list = None
if args.grains is not None:
gid_list = [int(i) for i in args.grains.split(',')]
pass
cfg.fit_grains.qbar = qbar
fit_results = fit_grains(
cfg,
grains_table,
show_progress=not args.quiet,
ids_to_refine=gid_list,
)
if args.profile:
pr.disable()
s = StringIO.StringIO()
ps = pstats.Stats(pr, stream=s).sort_stats('cumulative')
ps.print_stats(50)
logger.info('%s', s.getvalue())
# stop logging for this particular analysis
fh.flush()
fh.close()
logger.removeHandler(fh)
logger.info('*** end analysis "%s" ***', cfg.analysis_name)
write_results(fit_results, cfg, grains_filename)
logger.info('=== end fit-grains ===')
# stop logging to the console
ch.flush()
ch.close()
logger.removeHandler(ch)
help="stretch threshold",
type=float,
default=1.e-4)
args = parser.parse_args()
cfg_file = args.cfg_file
gt_ref = args.gt_ref
mtol = args.misorientation
ctol = args.centroid
vtol = args.stretch
# load the config object
cfg = config.open(cfg_file)[0]
grains_table = np.loadtxt(gt_ref, ndmin=2)
ref_grain_params = grains_table[:, 3:15]
gresults = fit_grains(cfg,
grains_table,
show_progress=False,
ids_to_refine=None,
write_spots_files=False)
cresult = compare_grain_fits(np.vstack([i[-1] for i in gresults]),
ref_grain_params,
mtol=mtol,
ctol=ctol,
vtol=vtol)
if cresult:
print("test passed")
else:
print("test failed")
