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allow skipping normalization when compute_cell_density #70

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allow skipping normalization when compute_cell_density #70

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17 changes: 16 additions & 1 deletion atlas_densities/app/cell_densities.py
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Original file line number Diff line number Diff line change
Expand Up @@ -183,8 +183,22 @@ def app(verbose):
help="Path to density groups ids config",
show_default=True,
)
@click.option(
"--skip-normalization",
is_flag=True,
default=False,
help="Whether to skip normalization of the Nissl path",
show_default=True,
)
@log_args(L)
def cell_density(annotation_path, hierarchy_path, nissl_path, output_path, group_ids_config_path):
def cell_density(
annotation_path,
hierarchy_path,
nissl_path,
output_path,
group_ids_config_path,
skip_normalization,
):
"""Compute and save the overall mouse brain cell density.

The input Nissl stain volume of AIBS is turned into an actual density field complying with
Expand Down Expand Up @@ -219,6 +233,7 @@ def cell_density(annotation_path, hierarchy_path, nissl_path, output_path, group
_get_voxel_volume_in_mm3(annotation),
nissl.raw,
group_ids_config=group_ids_config,
skip_normalization=skip_normalization,
)
nissl.with_data(overall_cell_density).save_nrrd(output_path)

Expand Down
6 changes: 5 additions & 1 deletion atlas_densities/densities/cell_density.py
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Original file line number Diff line number Diff line change
Expand Up @@ -60,6 +60,7 @@ def compute_cell_density(
voxel_volume: float,
nissl: FloatArray,
group_ids_config: dict,
skip_normalization: bool = False,
) -> FloatArray:
"""
Compute the overall cell density based on Nissl staining and cell counts from literature.
Expand Down Expand Up @@ -87,6 +88,8 @@ def compute_cell_density(
voxel_volume: the common volume of a voxel associated to any of the input arrays.
nissl: float array of shape (W, H, D) with non-negative entries. The input
Nissl stain intensity.
group_ids_config: Layout described in `atlas_densities/app/data/metadata/README.txt`
skip_normalization: whether the normalization should be skipped

Returns:
float array of shape (W, H, D) with non-negative entries. The returned array is a
Expand All @@ -97,7 +100,8 @@ def compute_cell_density(
"""

nissl = np.asarray(nissl, dtype=np.float64)
nissl = utils.normalize_intensity(nissl, annotation, threshold_scale_factor=1.0, copy=False)
if not skip_normalization:
nissl = utils.normalize_intensity(nissl, annotation, threshold_scale_factor=1.0, copy=False)
nissl = utils.compensate_cell_overlap(nissl, annotation, gaussian_filter_stdv=-1.0, copy=False)

group_ids = utils.get_group_ids(region_map, config=group_ids_config)
Expand Down
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