Utility functions

The utils module provides utilities for handling the data.

Module Reference

encore.utils.data_converters.dict_to_matlab_struct(pars_dict)

Converts a Python dictionary to a MATLAB struct.

Parameters:

pars_dict (dict) – A dictionary where keys represent the names of fields in the MATLAB struct and the values represent the corresponding field values.

Returns:

A MATLAB struct where the keys are the field names and the values are converted to the appropriate MATLAB data type.

Return type:

dict

This function recursively converts a Python dictionary to a MATLAB struct. It handles nested dictionaries by recursively calling the conversion function. Numeric values (integers or floats) are converted into MATLAB double type, while other data types are kept unchanged.

encore.utils.metrics.calculate_neuron_overlap_ratio(m1_neus_in_ens, m2_neus_in_ens)

Compute pairwise neuron overlap ratio between two ensemble sets.

Parameters:

  • m1_neus_in_ens (numpy.ndarray) – Binary neuron membership for method 1.

  • m2_neus_in_ens (numpy.ndarray) – Binary neuron membership for method 2.

Returns:

Overlap ratio matrix.

Return type:

numpy.ndarray

encore.utils.metrics.calculate_neuron_overlap_shared(m1_neus_in_ens, m2_neus_in_ens)

Compute the number of shared neurons between ensembles from two methods.

Parameters:

  • m1_neus_in_ens (numpy.ndarray) – Binary neuron membership for method 1.

  • m2_neus_in_ens (numpy.ndarray) – Binary neuron membership for method 2.

Returns:

Matrix of shared neuron counts.

Return type:

numpy.ndarray

encore.utils.metrics.compute_auc_roc_ensemble_stimuli(ensemble_timecourse, stimuli)

Compute ROC curve and AUC between ensemble activity and stimuli.

Parameters:

  • ensemble_timecourse (numpy.ndarray) – Ensemble activity signal.

  • stimuli (numpy.ndarray) – Binary or continuous stimulus signal.

Returns:

False positive rate, true positive rate, thresholds, and AUC.

Return type:

tuple

encore.utils.metrics.compute_correlation_between_ensembles(ensembles_timecourse)

Compute correlation matrix between ensemble timecourses.

Parameters:

ensembles_timecourse (numpy.ndarray) – Ensemble activity timecourses.

Returns:

Ensemble-to-ensemble correlation matrix.

Return type:

numpy.ndarray

encore.utils.metrics.compute_correlation_inside_ensemble(activity_neus_in_ens)

Compute correlation matrix between neurons within an ensemble.

Parameters:

activity_neus_in_ens (numpy.ndarray) – Neuronal activity matrix.

Returns:

Neuron-to-neuron correlation matrix.

Return type:

numpy.ndarray

encore.utils.metrics.compute_correlation_with_stimuli(ensembles_timecourse, data_stims)

Compute Pearson correlations between ensemble timecourses and stimuli.

Parameters:

  • ensembles_timecourse (numpy.ndarray) – Ensemble activity array (ensembles, timepoints).

  • data_stims (numpy.ndarray) – Stimulus timecourses (stimuli, timepoints).

Returns:

Correlation matrix (ensembles, stimuli).

Return type:

numpy.ndarray

encore.utils.metrics.compute_cross_correlations(ensemble_timecourse, stimuli)

Compute cross-correlation between ensemble activity and stimuli.

Parameters:

  • ensemble_timecourse (numpy.ndarray) – Ensemble activity signal.

  • stimuli (numpy.ndarray) – Stimulus signal.

Returns:

Cross-correlation values and corresponding lags.

Return type:

tuple

encore.utils.parameters_validators.validate_binary_matrix(matrix: ndarray) → bool

Validates if a numpy matrix is a binary matrix

Parameters:

matrix (np.ndarray) – Numpy matrix to validate

Returns:

Bool value describing if it’s binary

Return type:

bool

encore.utils.parameters_validators.validate_params(params: dict, defaults: dict) → dict

Validate and coerce parameter values based on defaults.

  • Uses the type of each default value as the expected type

  • If a parameter is missing or invalid, the default is used

  • Extra keys in params are ignored

Parameters:

  • params – Parameters collected from the GUI

  • defaults – Default parameter values (type and fallback)

Returns:

Validated parameter dictionary

encore.utils.text_formatting.format_nums_to_string(numbers_list)

Format a list of numbers into a string, for display purposes.

Every element is separated with a comma, except for the last one.

Parameters:

numbers_list (list) – List with numbers.

Returns:

String with the list’s elements separated by a comma.

Return type:

string