def count_items(self, independent=True, seed=None, read=True):
"""Parse data to count items: cells, colonies, lineages, containers
Parameters
----------
independent : bool {True, False}
lineage decomposition parameter
seed : int, or None
lineage decomposition parameter
read : bool {True, False}
try to read it in analysis folder
"""
# 1. try to read
try:
if read:
# get analysis path
analysis_path = analysis.get_analysis_path(self, write=False)
i, filter_path = analysis.get_filter_path(analysis_path, self.fset,
write=False)
counts = analysis.read_count_file(filter_path)
self._counts = counts
else:
raise text.MissingFileError # mock it to go to exception
except (text.MissingFileError, text.MissingFolderError, text.CorruptedFileError):
self._count_items(independent=independent, seed=seed, write=True)
print(self._count_summary())
def import_from_text(self, analysis_folder=None):
try:
for key, val in self._items.items():
val.read_text(analysis_folder)
exp = self.exp
fset = self.exp.fset
analysis_path = analysis.get_analysis_path(
exp, user_abspath=analysis_folder, write=False)
res = analysis.get_filter_path(analysis_path, fset, write=False)
index_filter, filter_path = res
o1, o2 = [uni.obs for uni in self.univariates]
basename = 'data_{}_{}---{}'.format(self.label, o1.name, o2.name)
text_file = os.path.join(filter_path, basename + '.csv')
if not os.path.exists(text_file):
raise analysis.MissingFileError
df = pd.read_csv(text_file, index_col=False)
# convert column dtypes
for col_name in df.columns:
dtype = _dtype_converter(col_name)
if dtype is not None:
df[col_name] = df[col_name].astype(dtype)
self.dataframe = df
except (analysis.MissingFileError, analysis.MissingFolderError):
raise StationaryBivariateIOError
return
def _erase_count_file(self):
try:
analysis_path = analysis.get_analysis_path(self, write=False)
i, filter_path = analysis.get_filter_path(analysis_path, self.fset,
write=False)
filename = os.path.join(filter_path, '.counts.yml')
if os.path.exists(filename):
os.remove(filename)
except (text.MissingFileError, text.MissingFolderError):
pass
def _get_obs_path(self, user_root=None, write=False):
"""Get observable path"""
obs = self.obs
exp = self.exp
fset = self.exp.fset
analysis_path = analysis.get_analysis_path(exp,
user_abspath=user_root,
write=write)
res = analysis.get_filter_path(analysis_path, fset, write=write)
index_filter, filter_path = res
obs_path = analysis.get_observable_path(filter_path, obs, write=write)
return obs_path
def export_text(self, analysis_folder=None):
# write each condition
try:
for key, val in self._items.items():
val.write_text(analysis_folder)
# when not possible it means single object has not been exported yet
except analysis.MissingFolderError:
self.single.export_text(analysis_folder)
for key, val in self._items.items():
val.write_text(analysis_folder)
# export dataframe as csv file
if self.dataframe is not None:
exp = self.univariate.exp
fset = self.univariate.exp.fset
analysis_path = analysis.get_analysis_path(
exp, user_abspath=analysis_folder, write=True)
res = analysis.get_filter_path(analysis_path, fset, write=True)
index_filter, filter_path = res
basename = 'data_{}_{}'.format(self.label, self.obs.name)
text_file = os.path.join(filter_path, basename + '.csv')
self.dataframe.to_csv(text_file, index=False)
return
def analysis_path(self):
"""Get analysis path (with appropriate filterset path)"""
analysis_path = analysis.get_analysis_path(self, write=True)
index, filterset_path = analysis.get_filter_path(analysis_path, self.fset, write=True)
return filterset_path
def _path_to_file(self, write=False):
analysis_path = analysis.get_analysis_path(self.exp, write=write)
text_file = os.path.join(analysis_path, 'regions.tsv')
if not os.path.exists(text_file) and not write:
raise RegionsIOError
return text_file
