def test_write_csv(self, data: ImageSingleCellData, tmp_path: Path):
csv_file_path = tmp_path / '20210305_NE_mockData1_s0_a1_ac_fullFiltered.csv'
data.write_csv(csv_file_path,
cell_properties=True,
cell_channel_properties=True,
index=False)
df = pd.read_csv(csv_file_path)
assert df.shape == (47, 35)
def test_to_anndata(self, data: ImageSingleCellData):
ad = data.to_anndata(cell_properties=True,
cell_channel_properties=True,
x_cell_channel_property="mean_intensities")
assert ad.X.shape == (47, 5)
assert ad.shape == (47, 5)
assert len(ad.layers) == 6
def dist_graph(data: ImageSingleCellData):
dist_mat = data.compute_cell_centroid_distances(metric='euclidean')
return SpatialCellGraph.construct_dist_graph(data,
dist_mat,
15,
cell_properties=True,
cell_channel_properties=True)
def data(analysis_cpout_images_path: Path, analysis_cpout_masks_path: Path):
img_file_path = analysis_cpout_images_path / '20210305_NE_mockData1_s0_a1_ac_fullFiltered.tiff'
mask_file_path = analysis_cpout_masks_path / '20210305_NE_mockData1_s0_a1_ac_ilastik_s2_Probabilities_mask.tiff'
channel_names = ['Ag107', 'Pr141', 'Sm147', 'Eu153', 'Yb172']
return ImageSingleCellData(img_file_path,
mask_file_path,
channel_names=channel_names)
def test_compute_cell_intensities(self, data: ImageSingleCellData):
mean_cell_intensities = data.compute_cell_intensities(np.nanmean)
expected_mean_channel_intensities = [
0.12480281, 0.04633365, 0.03550479, 0.05638942, 0.53933499
]
assert all(
np.abs(
mean_cell_intensities.mean(axis=0) -
expected_mean_channel_intensities) < 10e-6)
def test_write_fcs(self, data: ImageSingleCellData, tmp_path: Path):
fcs_file_path = tmp_path / '20210305_NE_mockData1_s0_a1_ac_fullFiltered.fcs'
data.write_fcs(fcs_file_path,
cell_properties=True,
cell_channel_properties=True)
def test_to_dataframe(self, data: ImageSingleCellData):
df = data.to_dataframe(cell_properties=True,
cell_channel_properties=True)
assert df.shape == (47, 35)
def test_to_dataset(self, data: ImageSingleCellData):
data.to_dataset(cell_properties=True, cell_channel_properties=True)
def test_compute_cell_border_distances(self, data: ImageSingleCellData):
cell_border_distances = data.compute_cell_border_distances()
assert np.sum(cell_border_distances < 15) == 837
def test_compute_cell_centroid_distances(self, data: ImageSingleCellData):
cell_centroid_distances = data.compute_cell_centroid_distances(
metric='euclidean')
assert np.sum(cell_centroid_distances < 15) == 509