neuron_morphology.transforms.scale_correction.compute_scale_correction
¶
Module Contents¶
Functions¶
estimate_scale_correction (morphology: Morphology, soma_depth: float, soma_marker_z: float, cut_thickness: Optional[float] = 350) |
Estimate a scale factor to correct the reconstructed morphology | ||
get_soma_marker_from_marker_file (marker_path: str) |
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run_scale_correction (morphology: Morphology, soma_marker_z: float, soma_depth: float, cut_thickness: float) |
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collect_inputs (args: Dict[str, Any]) → Dict[str, Any] |
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main () |
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neuron_morphology.transforms.scale_correction.compute_scale_correction.
estimate_scale_correction
(morphology: Morphology, soma_depth: float, soma_marker_z: float, cut_thickness: Optional[float] = 350)¶ Estimate a scale factor to correct the reconstructed morphology for slice shrinkage
Prior to reconstruction, the slice shrinks due to evaporation. This is most notable in the z axis, which is the slice thickness.
To correct for shrinkage we compare soma depth within the slice obtained soon after cutting the slice to the fixed_soma_depth obtained during the reconstruction. Then the scale correction is estimated as: scale = soma_depth / fixed_soma_depth. This is sensible as long as the z span of the corrected reconstruction is contained within the slice thickness. Thus we also estimate the maximum scale correction as: scale_max = cut_thickness / z_span, and take the smaller of scale and scale_max
Parameters: - morphology: Morphology object
- soma_depth: recorded depth of the soma when it was sliced
- soma_marker_z: soma marker z value from revised marker file
(z is on the slice surface for the marker file)
- cut_thickness: thickness of the cut slice
Returns: - scale factor correction
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neuron_morphology.transforms.scale_correction.compute_scale_correction.
get_soma_marker_from_marker_file
(marker_path: str)¶
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neuron_morphology.transforms.scale_correction.compute_scale_correction.
run_scale_correction
(morphology: Morphology, soma_marker_z: float, soma_depth: float, cut_thickness: float)¶
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neuron_morphology.transforms.scale_correction.compute_scale_correction.
collect_inputs
(args: Dict[str, Any]) → Dict[str, Any]¶ Parameters: - args: dict of InputParameters
Returns: - dict with string keys:
morphology: Morphology object soma_marker_z: z value from the marker file soma_depth: soma depth cut_thickness: slice thickness
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neuron_morphology.transforms.scale_correction.compute_scale_correction.
main
()¶