nnmt.lif.exp.sensitivity_measure

nnmt.lif.exp.sensitivity_measure(network, frequency, resorted_eigenvalues_mask='None', eigenvalue_index='None')

Calculates sensitivity measure as in Eq. 7 in Bos et al. [2016].

Requires the computation of nnmt.lif.exp.effective_connectivity() first.

See nnmt.lif.exp._sensitivity_measure() for full documentation.

Parameters:

networknnmt.models.Network or child class instance.

Network with the network parameters and previously calculated results.

frequencynp.float

Frequency at which the sensitivity is evaluated in Hz.

resorted_eigenvalues_masknp.ndarray

Mapping from old to new indices (e.g. for resorting the eigenmodes) as obtained from _match_eigenvalues_across_frequencies. Shape : (num populations, num analysis freqs)

eigenvalue_indexint

Index specifying the eigenvalue and corresponding eigenmode for which the sensitivity measure is evaluated.

Returns:

dict

Dictionary containing the results of the sensitivity analysis.

critical_frequencynp.float

Frequency at which the sensitivity is evaluated in Hz.

critical_frequency_indexint

Index of critical_frequency in all analysis frequencies.

critical_eigenvaluenp.complex

Critical eigenvalue.

left_eigenvectornp.ndarray

Left eigenvector corresponding to the critical eigenvalue.

right_eigenvectornp.ndarray

Right eigenvector corresponding to the critical eigenvalue.

knp.complex

Vector point from critical eigenvalue to complex(1,0).

k_pernp.complex

Vector perpendiculat to k.

sensitivitynp.ndarray

Sensitivity measure. Shape : (num analysis freqs, num populations, num populations)

sensitivity_ampnp.ndarray

Projection of sensitivity measure that alters amplitude of peak in power spectrum. Shape : (num analysis freqs, num populations, num populations)

sensitivity_freqnp.ndarray

Projection of Sensitivity measure that alters frequency of peak power spectrum. Shape : (num analysis freqs, num populations, num populations)