neurots.extract_input.input_distributions¶
Input distributions.
Functions
|
Extracts the input distributions from an input population. |
- neurots.extract_input.input_distributions._append_dicts(*args)¶
Merge all dicts into the first one.
- neurots.extract_input.input_distributions.distributions(filepath, neurite_types=None, threshold_sec=2, diameter_input_morph=None, feature='path_distances', diameter_model=None)¶
Extracts the input distributions from an input population.
The population is defined by a directory of swc or h5 files.
- Parameters:
filepath (str) – the morphology file.
threshold_sec (int) – defines the minimum accepted number of terminations.
diameter_input_morph (str) – if input set of morphologies is provided it will be used for the generation of diameter model, if no input is provided no diameter model will be generated.
feature (str) – defines the TMD feature that will be used to extract the persistence barcode (can be
radial_distances
,path_distances
ortrunk_length
). It is also possible to define one different feature per neurite type using a dict like{<neurite type 1>: <feature 1>, ...}
.diameter_model (str) – model for diameters, internal models are
M1
,M2
,M3
,M4
andM5
. Can be set toexternal
for external model.
- Returns:
The input distributions.
- Return type: