def test_from_spot_attributes_must_have_aligned_dimensions_spot_attributes_and_data(
):
"""
Number of features must match number of SpotAttributes. Pass two attributes and 3 features and
verify a ValueError is raised.
"""
spot_attributes = spot_attribute_factory(2)
data = np.zeros(30).reshape(3, 5, 2)
with pytest.raises(ValueError):
IntensityTable.from_spot_data(data, spot_attributes)
def intensity_table_factory() -> IntensityTable:
"""IntensityTable with a single feature that was measured over 2 channels and 2 rounds."""
intensities = np.array([[[0, 3], [4, 0]]], dtype=float)
spot_attribute_data = pd.DataFrame(
data=[0, 0, 0, 1],
index=[Axes.ZPLANE, Axes.Y, Axes.X, Features.SPOT_RADIUS]).T
spot_attributes = SpotAttributes(spot_attribute_data)
intensity_table = IntensityTable.from_spot_data(intensities,
spot_attributes)
return intensity_table
def test_intensity_table_can_be_constructed_from_a_numpy_array_and_spot_attributes(
):
"""
Verify that the IntensityTable can be created and that the resulting data matches the array
it was constructed from.
"""
spot_attributes = spot_attribute_factory(3)
data = np.zeros(30).reshape(3, 5, 2)
intensities = IntensityTable.from_spot_data(data, spot_attributes)
assert intensities.shape == data.shape
assert np.array_equal(intensities.values, data)
def intensity_table_factory(data: np.ndarray=np.array([[[0, 3], [4, 0]]])) -> IntensityTable:
"""IntensityTable with a single feature that was measured over 2 channels and 2 rounds."""
# generates spot attributes equal in size to the number of passed features.
# each attribute has coordinates (z, y, x) equal to the feature index, and radius 1.
spot_attributes_data = pd.DataFrame(
data=np.array([[i, i, i, 1] for i in np.arange(data.shape[0])]),
columns=[Axes.ZPLANE, Axes.Y, Axes.X, Features.SPOT_RADIUS]
)
spot_attributes = SpotAttributes(spot_attributes_data)
intensity_table = IntensityTable.from_spot_data(data, spot_attributes)
return intensity_table
