def get_measurement_columns(self, pipeline):
columns = get_object_measurement_columns(self.output_objects_name.value)
columns += [
(self.output_objects_name.value, FF_PARENT % self.objects_name.value, cpmeas.COLTYPE_INTEGER),
(self.objects_name.value, FF_CHILDREN_COUNT % self.output_objects_name.value, cpmeas.COLTYPE_INTEGER),
]
return columns
def get_measurement_columns(self, pipeline):
columns = get_object_measurement_columns(self.output_objects_name.value)
columns += [(self.output_objects_name.value,
FF_PARENT % self.objects_name.value,
cpmeas.COLTYPE_INTEGER),
(self.objects_name.value,
FF_CHILDREN_COUNT % self.output_objects_name.value,
cpmeas.COLTYPE_INTEGER)]
return columns
def get_measurement_columns(self, pipeline):
'''Return database info on measurements made in module
pipeline - pipeline being run
Return a list of tuples of object name, measurement name and data type
'''
result = I.get_object_measurement_columns(self.objects_name.value)
return result
def get_measurement_columns(self, pipeline):
"""Return database info on measurements made in module
pipeline - pipeline being run
Return a list of tuples of object name, measurement name and data type
"""
result = I.get_object_measurement_columns(self.objects_name.value)
return result
def get_measurement_columns(self, pipeline):
'''Return column definitions for measurements made by this module'''
object_name = self.object_name.value
remaining_object_name = self.remaining_objects.value
columns = I.get_object_measurement_columns(self.remaining_objects.value)
columns += [(object_name, cellprofiler.measurement.FF_CHILDREN_COUNT % remaining_object_name,
cpmeas.COLTYPE_INTEGER),
(remaining_object_name, cellprofiler.measurement.FF_PARENT % object_name,
cpmeas.COLTYPE_INTEGER)]
return columns
def get_measurement_columns(self, pipeline):
'''Return information to use when creating database columns'''
orig_image_name = self.object_name.value
filtered_image_name = self.filtered_objects.value
columns = I.get_object_measurement_columns(filtered_image_name)
columns += [(orig_image_name,
cellprofiler.measurement.FF_CHILDREN_COUNT % filtered_image_name,
cpmeas.COLTYPE_INTEGER),
(filtered_image_name,
cellprofiler.measurement.FF_PARENT % orig_image_name,
cpmeas.COLTYPE_INTEGER)]
return columns
def get_measurement_columns(self, pipeline):
'''Return measurement column defs for the parent/child measurement'''
object_list = ([(self.object_name.value, self.target_name.value)] +
[(x.object_name.value, x.target_name.value)
for x in self.additional_objects])
columns = []
for src_name, target_name in object_list:
columns += [(target_name, FF_PARENT % src_name,
cpmeas.COLTYPE_INTEGER),
(src_name, FF_CHILDREN_COUNT % target_name,
cpmeas.COLTYPE_INTEGER)]
columns += get_object_measurement_columns(target_name)
return columns
def get_measurement_columns(self, pipeline):
'''Return column definitions for measurements made by this module'''
object_name = self.object_name.value
remaining_object_name = self.remaining_objects.value
columns = I.get_object_measurement_columns(
self.remaining_objects.value)
columns += [(object_name, cellprofiler.measurement.FF_CHILDREN_COUNT %
remaining_object_name, cpmeas.COLTYPE_INTEGER),
(remaining_object_name,
cellprofiler.measurement.FF_PARENT % object_name,
cpmeas.COLTYPE_INTEGER)]
return columns
def get_measurement_columns(self, pipeline):
'''Return column definitions for measurements made by this module'''
subregion_name = self.subregion_objects_name.value
columns = cpmi.get_object_measurement_columns(subregion_name)
for parent in (self.primary_objects_name.value,
self.secondary_objects_name.value):
columns += [(parent,
cellprofiler.measurement.FF_CHILDREN_COUNT % subregion_name,
cpmeas.COLTYPE_INTEGER),
(subregion_name,
cellprofiler.measurement.FF_PARENT % parent,
cpmeas.COLTYPE_INTEGER)]
return columns
def get_measurement_columns(self, pipeline):
'''Return information to use when creating database columns'''
orig_image_name = self.object_name.value
filtered_image_name = self.filtered_objects.value
columns = I.get_object_measurement_columns(filtered_image_name)
columns += [
(orig_image_name,
cellprofiler.measurement.FF_CHILDREN_COUNT % filtered_image_name,
cpmeas.COLTYPE_INTEGER),
(filtered_image_name,
cellprofiler.measurement.FF_PARENT % orig_image_name,
cpmeas.COLTYPE_INTEGER)
]
return columns
def get_measurement_columns(self, pipeline):
'''Return column definitions for measurements made by this module'''
subregion_name = self.subregion_objects_name.value
columns = cpmi.get_object_measurement_columns(subregion_name)
for parent in (self.primary_objects_name.value,
self.secondary_objects_name.value):
columns += [
(parent,
cellprofiler.measurement.FF_CHILDREN_COUNT % subregion_name,
cpmeas.COLTYPE_INTEGER),
(subregion_name, cellprofiler.measurement.FF_PARENT % parent,
cpmeas.COLTYPE_INTEGER)
]
return columns
def get_measurement_columns(self, pipeline):
'''Return measurement column defs for the parent/child measurement'''
object_list = ([(self.object_name.value, self.target_name.value)] +
[(x.object_name.value, x.target_name.value)
for x in self.additional_objects])
columns = []
for src_name, target_name in object_list:
columns += [(target_name,
FF_PARENT % src_name,
cpmeas.COLTYPE_INTEGER),
(src_name,
FF_CHILDREN_COUNT % target_name,
cpmeas.COLTYPE_INTEGER)]
columns += get_object_measurement_columns(target_name)
return columns
def get_measurement_columns(self, pipeline):
columns = []
for file_setting in self.file_settings:
if file_setting.image_objects_choice == IO_IMAGES:
image_name = file_setting.image_name.value
path_name_category = C_PATH_NAME
file_name_category = C_FILE_NAME
columns += [
(
cpmeas.IMAGE,
"_".join((C_MD5_DIGEST, image_name)),
cpmeas.COLTYPE_VARCHAR_FORMAT % 32,
),
(
cpmeas.IMAGE,
"_".join((C_SCALING, image_name)),
cpmeas.COLTYPE_FLOAT,
),
(
cpmeas.IMAGE,
"_".join((C_HEIGHT, image_name)),
cpmeas.COLTYPE_INTEGER,
),
(
cpmeas.IMAGE,
"_".join((C_WIDTH, image_name)),
cpmeas.COLTYPE_INTEGER,
),
]
else:
image_name = file_setting.objects_name.value
path_name_category = C_OBJECTS_PATH_NAME
file_name_category = C_OBJECTS_FILE_NAME
columns += get_object_measurement_columns(image_name)
columns += [(cpmeas.IMAGE, "_".join(
(feature, image_name)), coltype) for feature, coltype in (
(file_name_category, cpmeas.COLTYPE_VARCHAR_FILE_NAME),
(path_name_category, cpmeas.COLTYPE_VARCHAR_PATH_NAME),
)]
return columns
def get_measurement_columns(self, pipeline):
columns = []
for file_setting in self.file_settings:
if file_setting.image_objects_choice == IO_IMAGES:
image_name = file_setting.image_name.value
path_name_category = C_PATH_NAME
file_name_category = C_FILE_NAME
columns += [
(cpmeas.IMAGE, "_".join((C_MD5_DIGEST, image_name)), cpmeas.COLTYPE_VARCHAR_FORMAT % 32),
(cpmeas.IMAGE, "_".join((C_SCALING, image_name)), cpmeas.COLTYPE_FLOAT),
(cpmeas.IMAGE, "_".join((C_HEIGHT, image_name)), cpmeas.COLTYPE_INTEGER),
(cpmeas.IMAGE, "_".join((C_WIDTH, image_name)), cpmeas.COLTYPE_INTEGER)]
else:
image_name = file_setting.objects_name.value
path_name_category = C_OBJECTS_PATH_NAME
file_name_category = C_OBJECTS_FILE_NAME
columns += get_object_measurement_columns(image_name)
columns += [(cpmeas.IMAGE, '_'.join((feature, image_name)), coltype)
for feature, coltype in (
(file_name_category, cpmeas.COLTYPE_VARCHAR_FILE_NAME),
(path_name_category, cpmeas.COLTYPE_VARCHAR_PATH_NAME),
)]
return columns
def get_measurement_columns(self, pipeline):
'''Column definitions for measurements made by IdentifyPrimaryObjects'''
return get_object_measurement_columns(self.output_objects_name.value)
def get_measurement_columns(self, pipeline):
'''Return column definitions for measurements made by this module'''
columns = get_object_measurement_columns(self.output_object_name.value)
return columns
def get_measurement_columns(self, pipeline):
"""Return column definitions for measurements made by this module"""
columns = get_object_measurement_columns(self.output_object_name.value)
return columns
def get_measurement_columns(self, pipeline):
import cellprofiler.modules.identify as I
return I.get_object_measurement_columns(self.output_objects.value)
def get_measurement_columns(self, pipeline):
'''Column definitions for measurements made by IdentifyPrimaryObjects'''
return get_object_measurement_columns(self.output_objects_name.value)
def get_measurement_columns(self, pipeline):
"""Column definitions for measurements made by DetectSpots"""
columns = cpmi.get_object_measurement_columns(self.object_name.value)
return columns
