def test_run_pipline(self):
tempdir = exec.stages(self.stages, self.subdirs, keep_data=True)
intensities = IntensityTable.load(
os.path.join(tempdir, "results", self.spots_file))
self.verify_results(intensities)
if os.getenv("TEST_KEEP_DATA") is None:
shutil.rmtree(tempdir)
def _cli(cls, args, print_help=False):
"""Runs the decoder component based on parsed arguments."""
if args.decoder_algorithm_class is None or print_help:
cls.decoder_group.print_help()
cls.decoder_group.exit(status=2)
instance = args.decoder_algorithm_class(**vars(args))
# load intensities and codebook
intensities = IntensityTable.load(args.input)
codebook = Codebook.from_json(args.codebook)
# decode and save output
intensities = instance.decode(intensities, codebook)
intensities.save(args.output)
def test_run_pipeline(self):
tempdir = tempfile.mkdtemp()
coverage_enabled = "STARFISH_COVERAGE" in os.environ
def callback(interval):
print(" ".join(stage[:2]), " ==> {} seconds".format(interval))
try:
for subdir in TestWithIssData.SUBDIRS:
os.makedirs(
"{tempdir}".format(tempdir=os.path.join(tempdir, subdir)))
for stage in TestWithIssData.STAGES:
cmdline = [
element(tempdir=tempdir) if callable(element) else element
for element in stage
]
if cmdline[0] == "starfish" and coverage_enabled:
coverage_cmdline = [
"coverage",
"run",
"-p",
"--source",
"starfish",
"-m",
"starfish",
]
coverage_cmdline.extend(cmdline[1:])
cmdline = coverage_cmdline
with clock.timeit(callback):
subprocess.check_call(cmdline)
intensities = IntensityTable.load(
os.path.join(tempdir, "results", "spots.nc"))
genes, counts = np.unique(
intensities.coords[Codebook.Constants.GENE.value],
return_counts=True)
gene_counts = pd.Series(counts, genes)
assert gene_counts['ACTB_human'] > gene_counts['ACTB_mouse']
finally:
if os.getenv("TEST_ISS_KEEP_DATA") is None:
shutil.rmtree(tempdir)
def _cli(cls, args, print_help=False):
"""Runs the gene_assignment component based on parsed arguments."""
from starfish import munge
if args.gene_assignment_algorithm_class is None or print_help:
cls.gene_assignment_group.print_help()
cls.gene_assignment_group.exit(status=2)
with open(args.coordinates_geojson, "r") as fh:
coordinates = json.load(fh)
regions = munge.geojson_to_region(coordinates)
print('Assigning genes to cells...')
intensity_table = IntensityTable.load(args.intensities)
instance = args.gene_assignment_algorithm_class(**vars(args))
result = instance.assign_genes(intensity_table, regions)
print("Writing | cell_id | spot_id to: {}".format(args.output))
result.to_json(args.output, orient="records")