def core_helper(plate, settings_dict, imagecontainer, position, version,
redirect=True, debug=False):
"""Embeds analysis of a positon in a single function"""
# see http://stackoverflow.com/questions/3288595/
# multiprocessing-using-pool-map-on-a-function-defined-in-a-class
logger = logging.getLogger(str(os.getpid()))
import numpy
reload(numpy.core._dotblas)
try:
settings = ConfigSettings()
settings.from_dict(settings_dict)
settings.set('General', 'constrain_positions', True)
settings.set('General', 'positions', position)
environ = CecogEnvironment(version, redirect=redirect, debug=debug)
if debug:
environ.pprint()
analyzer = AnalyzerCore(plate, settings, imagecontainer)
post_hdf5_link_list = analyzer.processPositions()
return plate, position, copy.deepcopy(post_hdf5_link_list)
except Exception as e:
errortxt = "plate: %s, position: %s\n" %(plate, position)
errortxt = "".join([errortxt] + \
traceback.format_exception(*sys.exc_info()))
logger.error(errortxt)
raise e.__class__(errortxt)
def _run(self):
for plate_id in self._imagecontainer.plates:
analyzer = AnalyzerCore(plate_id, self._settings,
copy.deepcopy(self._imagecontainer))
h5_links = analyzer.processPositions(self)
if h5_links:
link_hdf5_files(h5_links)
def core_helper(plate,
settings_dict,
imagecontainer,
position,
version,
redirect=True,
debug=False):
"""Embeds analysis of a positon in a single function"""
# see http://stackoverflow.com/questions/3288595/
# multiprocessing-using-pool-map-on-a-function-defined-in-a-class
logger = logging.getLogger(str(os.getpid()))
import numpy
reload(numpy.core._dotblas)
try:
settings = ConfigSettings()
settings.from_dict(settings_dict)
settings.set('General', 'constrain_positions', True)
settings.set('General', 'positions', position)
environ = CecogEnvironment(version, redirect=redirect, debug=debug)
if debug:
environ.pprint()
analyzer = AnalyzerCore(plate, settings, imagecontainer)
post_hdf5_link_list = analyzer.processPositions()
return plate, position, copy.deepcopy(post_hdf5_link_list)
except Exception as e:
errortxt = "plate: %s, position: %s\n" % (plate, position)
errortxt = "".join([errortxt] + \
traceback.format_exception(*sys.exc_info()))
logger.error(errortxt)
raise e.__class__(errortxt)
def core_helper(plate_id, settings_str, imagecontainer, position):
settings = ConfigSettings(SECTION_REGISTRY)
settings.from_string(settings_str)
settings.set(SECTION_NAME_GENERAL, 'constrain_positions', True)
settings.set(SECTION_NAME_GENERAL, 'positions', position)
try:
analyzer = AnalyzerCore(plate_id, settings, imagecontainer)
result = analyzer.processPositions()
except Exception:
traceback.print_exc()
raise
return plate_id, position, copy.deepcopy(result['post_hdf5_link_list'])
def core_helper(plate_id, settings_str, imagecontainer, position):
settings = ConfigSettings(SECTION_REGISTRY)
settings.from_string(settings_str)
settings.set(SECTION_NAME_GENERAL, 'constrain_positions', True)
settings.set(SECTION_NAME_GENERAL, 'positions', position)
try:
analyzer = AnalyzerCore(plate_id, settings, imagecontainer)
result = analyzer.processPositions()
except Exception:
traceback.print_exc()
raise
return plate_id, position, copy.deepcopy(result['post_hdf5_link_list'])
def _process_image(self):
print 'process image'
self._stopwatch.reset()
s = StopWatch()
settings = _ProcessorMixin.get_special_settings(self._settings)
settings.set_section('General')
settings.set2('constrain_positions', True)
settings.set2('positions', self.coordinate.position)
settings.set2('redofailedonly', False)
settings.set2('framerange', True)
settings.set2('framerange_begin', self.coordinate.time)
settings.set2('framerange_end', self.coordinate.time)
settings.set_section('ObjectDetection')
prim_id = PrimaryChannel.NAME
#sec_id = SecondaryChannel.NAME
#sec_regions = settings.get2('secondary_regions')
settings.set_section('Processing')
settings.set2('primary_classification', False)
settings.set2('secondary_classification', False)
settings.set2('primary_featureextraction', False)
settings.set2('secondary_featureextraction', False)
settings.set2('objectdetection', self._show_objects)
settings.set2('tracking', False)
settings.set_section('Output')
settings.set2('rendering_contours_discwrite', False)
settings.set2('rendering_class_discwrite', False)
settings.set2('export_object_counts', False)
settings.set2('export_object_details', False)
settings.set2('export_track_data', False)
settings.set_section('Classification')
settings.set2('collectsamples', False)
settings.set('General', 'rendering', {})
settings.set('General', 'rendering_class', {})
if len(self._imagecontainer.channels) > 1:
settings.set('Processing', 'secondary_processChannel', True)
settings.set('General', 'rendering', {})
print settings
analyzer = AnalyzerCore(self.coordinate.plate, settings,
self._imagecontainer)
analyzer.processPositions(myhack=self)
print('PROCESS IMAGE: %s' % s)
elif len(compound) == 1:
if not multiple_plates:
plate_id = os.path.split(path_input)[1]
pos = compound[0]
else:
parser.error("Position must be of the form 'plateid___position'. Found '%s' instead." % item)
else:
parser.error("Position must be of the form 'position' or 'plateid___position'. Found '%s' instead." % item)
if not plate_id in plates:
plates[plate_id] = []
plates[plate_id].append(pos)
# start one analyzer per plate with the corresponding positions
post_hdf5_link_list = []
for plate_id in plates:
# redefine the positions
settings.set(SECTION_NAME_GENERAL, 'constrain_positions', True)
settings.set(SECTION_NAME_GENERAL, 'positions', ','.join(plates[plate_id]))
logger.info("Launching analyzer for plate '%s' with positions %s" % (plate_id, plates[plate_id]))
# initialize and run the analyzer
analyzer = AnalyzerCore(plate_id, settings, imagecontainer)
hdf_links = analyzer.processPositions()
post_hdf5_link_list.append(hdf_links)
if settings.get('Output', 'hdf5_create_file') and settings.get('Output', 'hdf5_merge_positions'):
if len(post_hdf5_link_list) > 0:
post_hdf5_link_list = reduce(lambda x,y: x + y, post_hdf5_link_list)
link_hdf5_files(sorted(post_hdf5_link_list))
print 'BATCHPROCESSING DONE!'
elif len(compound) == 1:
if not multiple_plates:
plate_id = os.path.split(path_input)[1]
pos = compound[0]
else:
parser.error("Position must be of the form 'plateid___position'. Found '%s' instead." % item)
else:
parser.error("Position must be of the form 'position' or 'plateid___position'. Found '%s' instead." % item)
if not plate_id in plates:
plates[plate_id] = []
plates[plate_id].append(pos)
# start one analyzer per plate with the corresponding positions
post_hdf5_link_list = []
for plate_id in plates:
# redefine the positions
settings.set(SECTION_NAME_GENERAL, 'constrain_positions', True)
settings.set(SECTION_NAME_GENERAL, 'positions', ','.join(plates[plate_id]))
logger.info("Launching analyzer for plate '%s' with positions %s" % (plate_id, plates[plate_id]))
# initialize and run the analyzer
analyzer = AnalyzerCore(plate_id, settings, imagecontainer)
hdf_links = analyzer.processPositions()
post_hdf5_link_list.append(hdf_links)
if settings.get('Output', 'hdf5_create_file') and settings.get('Output', 'hdf5_merge_positions'):
if len(post_hdf5_link_list) > 0:
post_hdf5_link_list = reduce(lambda x,y: x + y, post_hdf5_link_list)
link_hdf5_files(sorted(post_hdf5_link_list))
print 'BATCHPROCESSING DONE!'
def _process_image(self):
settings = _ProcessorMixin.get_special_settings(self._settings)
settings.set_section('General')
settings.set2('constrain_positions', True)
settings.set2('positions', self.coordinate.position)
settings.set2('redofailedonly', False)
settings.set2('framerange', True)
settings.set2('framerange_begin', self.coordinate.time)
settings.set2('framerange_end', self.coordinate.time)
settings.set_section('ObjectDetection')
prim_id = PrimaryChannel.NAME
#sec_id = SecondaryChannel.NAME
#sec_regions = settings.get2('secondary_regions')
settings.set_section('Processing')
settings.set2('primary_classification', False)
settings.set2('secondary_classification', False)
settings.set2('tertiary_classification', False)
settings.set2('merged_classification', False)
settings.set2('primary_featureextraction', False)
settings.set2('secondary_featureextraction', False)
settings.set2('objectdetection', self._show_objects)
settings.set2('tracking', False)
settings.set_section('Output')
settings.set2('rendering_contours_discwrite', False)
settings.set2('rendering_class_discwrite', False)
settings.set2('export_object_counts', False)
settings.set2('export_object_details', False)
settings.set2('export_track_data', False)
settings.set2('hdf5_create_file', False)
settings.set_section('Classification')
settings.set2('collectsamples', False)
settings.set('General', 'rendering', {})
settings.set('General', 'rendering_class', {})
settings.set('Output', 'events_export_gallery_images', False)
# turn of output:
settings.set('Output', 'export_object_counts', False)
settings.set('Output', 'export_object_details', False)
settings.set('Output', 'export_file_names', False)
settings.set('Output', 'events_export_gallery_images', False)
settings.set('Output', 'export_track_data', False)
settings.set('Output', 'export_tracking_as_dot', False)
nchannels = len(self._imagecontainer.channels)
# XXX channel mapping unclear
# processing channel <--> color channel
# i.e problems if 2 processing channels have the
# same color
if nchannels == 2:
settings.set('Processing', 'secondary_processChannel', True)
elif nchannels == 3:
settings.set('Processing', 'secondary_processChannel', True)
settings.set('Processing', 'tertiary_processChannel', True)
# need turn of virtual channels
settings.set('Processing', 'merged_processChannel', False)
settings.set('General', 'rendering', {})
analyzer = AnalyzerCore(self.coordinate.plate, settings,
self._imagecontainer)
# as long the GIL is not released, if GIL is released
# just use self.setCursor
try:
QApplication.setOverrideCursor(QCursor(Qt.WaitCursor))
analyzer.processPositions(myhack=self)
except Exception, e:
import traceback
traceback.print_exc()
raise(e)
def _process_image(self):
settings = _ProcessorMixin.get_special_settings(self._settings)
settings.set_section('General')
settings.set2('constrain_positions', True)
settings.set2('positions', self.coordinate.position)
settings.set2('redofailedonly', False)
settings.set2('framerange', True)
settings.set2('framerange_begin', self.coordinate.time)
settings.set2('framerange_end', self.coordinate.time)
settings.set_section('ObjectDetection')
prim_id = PrimaryChannel.NAME
#sec_id = SecondaryChannel.NAME
#sec_regions = settings.get2('secondary_regions')
settings.set_section('Processing')
settings.set2('primary_classification', False)
settings.set2('secondary_classification', False)
settings.set2('tertiary_classification', False)
settings.set2('merged_classification', False)
settings.set2('primary_featureextraction', False)
settings.set2('secondary_featureextraction', False)
settings.set2('objectdetection', self._show_objects)
settings.set2('tracking', False)
settings.set_section('Output')
settings.set2('rendering_contours_discwrite', False)
settings.set2('rendering_class_discwrite', False)
settings.set2('export_object_counts', False)
settings.set2('export_object_details', False)
settings.set2('export_track_data', False)
settings.set2('hdf5_create_file', False)
settings.set_section('Classification')
settings.set2('collectsamples', False)
settings.set('General', 'rendering', {})
settings.set('General', 'rendering_class', {})
settings.set('Output', 'events_export_gallery_images', False)
# turn of output:
settings.set('Output', 'export_object_counts', False)
settings.set('Output', 'export_object_details', False)
settings.set('Output', 'export_file_names', False)
settings.set('Output', 'events_export_gallery_images', False)
settings.set('Output', 'export_track_data', False)
settings.set('Output', 'export_tracking_as_dot', False)
nchannels = len(self._imagecontainer.channels)
# XXX channel mapping unclear
# processing channel <--> color channel
# i.e problems if 2 processing channels have the
# same color
if nchannels == 2:
settings.set('Processing', 'secondary_processChannel', True)
elif nchannels == 3:
settings.set('Processing', 'secondary_processChannel', True)
settings.set('Processing', 'tertiary_processChannel', True)
# need turn of virtual channels
settings.set('Processing', 'merged_processChannel', False)
settings.set('General', 'rendering', {})
analyzer = AnalyzerCore(self.coordinate.plate, settings,
self._imagecontainer)
# as long the GIL is not released, if GIL is released
# just use self.setCursor
try:
QApplication.setOverrideCursor(QCursor(Qt.WaitCursor))
analyzer.processPositions(myhack=self)
except Exception, e:
import traceback
traceback.print_exc()
raise (e)
for item in positions:
compound = item.split('___')
if len(compound) == 2:
plate_id, pos = compound
elif len(compound) == 1:
if not multiple_plates:
plate_id = os.path.split(path_input)[1]
pos = compound[0]
else:
parser.error("Position must be of the form 'plateid___position'. Found '%s' instead." % item)
else:
parser.error("Position must be of the form 'position' or 'plateid___position'. Found '%s' instead." % item)
if not plate_id in plates:
plates[plate_id] = []
plates[plate_id].append(pos)
# start one analyzer per plate with the corresponding positions
for plate_id in plates:
# redefine the positions
settings.set(SECTION_NAME_GENERAL, 'constrain_positions', True)
settings.set(SECTION_NAME_GENERAL, 'positions', ','.join(plates[plate_id]))
logger.info("Launching analyzer for plate '%s' with positions %s" % (plate_id, plates[plate_id]))
# initialize and run the analyzer
analyzer = AnalyzerCore(plate_id, settings, imagecontainer)
analyzer.processPositions()
print 'BATCHPROCESSING DONE!'
