postprocessor.core.multisignal.crosscorr.crosscorr

class postprocessor.core.multisignal.crosscorr.crosscorr(parameters: crosscorrParameters)

Bases: PostProcessABC

Attributes

parameters

Methods

run(trace_dfA[, trace_dfB])

Calculates normalised cross-correlations as a function of time.

as_function
default_parameters

__init__(parameters: crosscorrParameters)

Methods

__init__(parameters)
as_function(data, *args, **kwargs)
default_parameters(*args, **kwargs)
run(trace_dfA[, trace_dfB])	Calculates normalised cross-correlations as a function of time.

Attributes

parameters

run(trace_dfA: DataFrame, trace_dfB: Optional[DataFrame] = None)

Calculates normalised cross-correlations as a function of time.

Calculates normalised auto- or cross-correlations as a function of time. Normalisation is by the product of the standard deviation for each variable calculated across replicates at each time point. With zero lag, the normalised correlation should be one.

Parameters

trace_dfA: dataframe

An array of signal values, with each row a replicate measurement and each column a time point.

trace_dfB: dataframe (required for cross-correlation only)

An array of signal values, with each row a replicate measurement and each column a time point.

Returns

norm_corr: array or aliby dataframe

An array of the correlations with each row the result for the corresponding replicate and each column a time point