def save(self, tile_indices, output_dir, data, compress=6):
region_index, tile_index, tx, ty = tile_indices
img_label, stats = data
# Save label volumes if present (use compression as these are often highly redundant)
label_tile_path = None
if img_label is not None:
label_tile_path = cytokit_io.get_cytometry_image_path(
region_index, tx, ty)
cytokit_io.save_tile(osp.join(output_dir, label_tile_path),
img_label,
config=self.config,
compress=compress)
# Save statistics if present
stats_path = None
if stats is not None:
# Append useful metadata to cytometry stats (align these names to those used in config.TileDims)
# and export as csv
stats.insert(0, 'tile_y', ty)
stats.insert(0, 'tile_x', tx)
stats.insert(0, 'tile_index', tile_index)
stats.insert(0, 'region_index', region_index)
stats_path = cytokit_io.get_cytometry_stats_path(
region_index, tx, ty)
cytokit_io.save_csv(osp.join(output_dir, stats_path),
stats,
index=False)
return label_tile_path, stats_path
def aggregate_cytometry_statistics(output_dir,
config,
mode='all',
export_csv=True,
export_fcs=True,
variant=None):
from cytokit.function import data as function_data
# Aggregate all cytometry csv data (across tiles)
res = function_data.get_cytometry_data(output_dir, config, mode=mode)
# Get file extension, possibly with user-defined "variant" name to be included in all
# resulting file names
def ext(file_ext):
return file_ext if variant is None else '{}.{}'.format(
variant, file_ext)
# Export result as csv
csv_path, fcs_path = None, None
if export_csv:
csv_path = osp.join(output_dir,
cytokit_io.get_cytometry_agg_path(ext('csv')))
cytokit_io.save_csv(csv_path, res, index=False)
logger.info(
'Saved cytometry aggregation results to csv at "{}"'.format(
csv_path))
if export_fcs:
import re
import fcswrite
nonalnum = '[^0-9a-zA-Z]+'
fcs_path = osp.join(output_dir,
cytokit_io.get_cytometry_agg_path(ext('fcs')))
if len(res) > 0:
# For FCS exports, save only integer and floating point values and replace any non-alphanumeric
# column name characters with underscores
res_fcs = res.select_dtypes(
['int',
'float']).rename(columns=lambda c: re.sub(nonalnum, '_', c))
if not osp.exists(osp.dirname(fcs_path)):
os.makedirs(osp.dirname(fcs_path), exist_ok=True)
fcswrite.write_fcs(filename=fcs_path,
chn_names=res_fcs.columns.tolist(),
data=res_fcs.values)
logger.info(
'Saved cytometry aggregation results to fcs at "{}"'.format(
fcs_path))
else:
# fcswrite fails on writing empty datasets so log a warning instead
logger.warning(
'Skipping FCS export because no objects were detected')
return csv_path, fcs_path