def test_metric_decoding_without_spots():
codebook, image_stack, max_intensity = two_spot_sparse_coded_data_factory()
bd = starfish.spots.DetectSpots.BlobDetector(min_sigma=1,
max_sigma=1,
num_sigma=1,
threshold=max_intensity + 0.1)
no_spots = bd.run(image_stack)
decode = starfish.spots.Decode.MetricDistance(codebook,
max_distance=0,
min_intensity=max_intensity +
0.1)
decoded_no_spots: starfish.IntensityTable = decode.run(no_spots)
decoded_spot_table = decoded_no_spots.to_decoded_spots()
with TemporaryDirectory() as dir_:
filename = os.path.join(dir_, 'test.csv')
decoded_spot_table.save_csv(os.path.join(dir_, 'test.csv'))
# verify we can concatenate two empty tables
table1 = pd.read_csv(filename, index_col=0)
table2 = pd.read_csv(filename, index_col=0)
pd.concat([table1, table2], axis=0)
def test_per_round_max_spot_decoding_without_spots(tmpdir):
codebook, image_stack, max_intensity = two_spot_sparse_coded_data_factory()
bd = starfish.spots.FindSpots.BlobDetector(min_sigma=1,
max_sigma=1,
num_sigma=1,
threshold=max_intensity + 0.1)
no_spots = bd.run(image_stack)
decode = starfish.spots.DecodeSpots.PerRoundMaxChannel(codebook)
decoded_no_spots: starfish.DecodedIntensityTable = decode.run(
spots=no_spots)
decoded_spot_table = decoded_no_spots.to_decoded_dataframe()
filename = os.path.join(tmpdir, 'test.csv')
decoded_spot_table.save_csv(os.path.join(tmpdir, 'test.csv'))
# verify we can concatenate two empty tables
table1 = pd.read_csv(filename, index_col=0)
table2 = pd.read_csv(filename, index_col=0)
pd.concat([table1, table2], axis=0)
from starfish import ImageStack
from starfish.core.spots.DecodeSpots import trace_builders
from starfish.core.spots.FindSpots import BlobDetector
from starfish.core.spots.FindSpots import FindSpotsAlgorithm
from starfish.core.test.factories import (
two_spot_informative_blank_coded_data_factory,
two_spot_one_hot_coded_data_factory,
two_spot_sparse_coded_data_factory,
)
from starfish.types import Axes, Features, FunctionSource
# verify all spot finders handle different coding types
_, ONE_HOT_IMAGESTACK, ONE_HOT_MAX_INTENSITY = two_spot_one_hot_coded_data_factory()
_, SPARSE_IMAGESTACK, SPARSE_MAX_INTENSITY = two_spot_sparse_coded_data_factory()
_, BLANK_IMAGESTACK, BLANK_MAX_INTENSITY = two_spot_informative_blank_coded_data_factory()
# make sure that all spot finders handle empty arrays
EMPTY_IMAGESTACK = ImageStack.from_numpy(np.zeros((4, 2, 10, 100, 100), dtype=np.float32))
def simple_gaussian_spot_detector() -> BlobDetector:
"""create a basic gaussian spot detector"""
return BlobDetector(
min_sigma=1,
max_sigma=4,
num_sigma=5,
threshold=0,
measurement_type='max')