Other utility functions API
CePNEMAnalysis.gaussian_kernel — Functiongaussian_kernel(x::Real; sigma::Float64=1.0)Evaluates a Gaussian kernel at position xwith standard deviationsigma`.
CePNEMAnalysis.convolve — Functionconvolve(x::Vector{Float64}, k::Vector{Float64})Convolves a vector x with a kernel vector k.
CePNEMAnalysis.correct_name — Functioncorrect_name(neuron_name)Corrects the name of a neuron by removing the "0" substring from the name if it contains "DB0" or "VB0". This causes the neuron name to be compatible with the connectome files.
Arguments:
neuron_name::String: The name of the neuron to be corrected.
Returns:
neuron_name::String: The corrected name of the neuron.
CePNEMAnalysis.find_peaks — Functionfind_peaks(neural_activity::Vector{Float64}, threshold::Float64)Find the peaks in a vector of neural activity above a given threshold. This method is most useful for finding spikes in the activity of spiking neurons.
Arguments:
neural_activity::Vector{Float64}: A vector of neural activity.threshold::Float64: The threshold above which to consider a value a peak.
Returns:
peaks::Vector{Int}: A vector of indices of the peaks in the neural activity.peak_heights::Vector{Float64}: A vector of the heights of the peaks in the neural activity.