4.2.1.4. PSPAttenuationTest

class PSPAttenuationTest(config={}, observation={}, name='PSP attenuation test', force_run=False, base_directory=None, show_plot=True, num_of_dend_locations=15, random_seed=1, save_all=True, trunk_origin=None)[source]

Bases: sciunit.tests.Test

Tests how much synaptic potential attenuates from the dendrite (different distances) to the soma.

Parameters

  • config (dict) – dictionary loaded from a JSON file, containing the parameters of the simulation

  • observation (dict) – dictionary loaded from a JSON file, containing the experimental mean and std values for the features to be tested

  • force_run (boolean) – If True and the pickle files containing the model’s response to the simulation exists, the simulation won’t be run again, traces are loaded from the pickle file

  • base_directory (str) – Results will be saved here

  • show_plot (boolean) – If False, plots are not displayed but still saved

  • save_all (boolean) – If False, only the JSON files containing the absolute feature values, the feature error scores and the final scores, and a log file are saved, but the figures and pickle files are not.

  • num_of_dend_locations (int) – Number of randomly selected dendritic locations to be tested

  • random_seed (int) – random seed for random dendritic location selection

  • trunk_origin (list) – first element : name of the section from which the trunk originates, second element : position on section (E.g. [‘soma[5]’, 1]). If not set by the user, the end of the default soma section is used.

Methods Summary

analyse_traces(model, traces_dict_no_input, …)

bind_score(score, model, observation, prediction)

For the user to bind additional features to the score.

calcs_and_plots(model, attenuation_values, …)

calculate_weights(traces_no_input, EPSC_amp)

compute_score(observation, prediction[, verbose])

Implementation of sciunit.Test.score_prediction.

format_data(observation)

generate_prediction(model[, verbose])

Implementation of sciunit.Test.generate_prediction.

run_stimulus(model, locations_weights, tau1, …)

Methods Documentation

analyse_traces(model, traces_dict_no_input, traces_dict, locations_distances)[source]
bind_score(score, model, observation, prediction)[source]

For the user to bind additional features to the score.

calcs_and_plots(model, attenuation_values, locations_distances, EPSP_amp_values)[source]
calculate_weights(traces_no_input, EPSC_amp)[source]
compute_score(observation, prediction, verbose=False)[source]

Implementation of sciunit.Test.score_prediction.

format_data(observation)[source]
generate_prediction(model, verbose=False)[source]

Implementation of sciunit.Test.generate_prediction.

run_stimulus(model, locations_weights, tau1, tau2)[source]