bimfa#

pymultifracs.bivariate.bimfa(mrq1, mrq2, scaling_ranges, weighted=None, n_cumul=2, q1=None, q2=None, mode='all2all', min_j=1, bootstrap_weighted=None, R=1, estimates='auto', robust=False, robust_kwargs=None, idx_reject=None, check_regularity=True)#

Bivariate multifractal analysis.

Parameters:
mrq1MultiResolutionQuantityBase

Left-hand multi-resolution quantity to analyze.

mrq2MultiResolutionQuantityBase

Right-hand multi-resolution quantity to analyze.

scaling_rangeslist[tuple[int, int]]

List of pairs of (j1, j2) ranges of scales for the analysis.

weightedstr | None

Weighting mode for the linear regressions. Defaults to None, which is no weighting. Possible values are ‘Nj’ which weighs by number of coefficients, and ‘bootstrap’ which weights by bootstrap-derived estimates of variance.

n_cumulint

Number of cumulants computed.

q1ndarray of float, shape (n_exponents,)

List of q values used in the multifractal analysis of the mrq1.

q2ndarray of float, shape (n_exponents,)

List of q values used in the multifractal analysis of the mrq2.

modestr, optional
Mode of bivariate analysis. Either:
  • ‘all2all’: each possible pair of signals between mrq1 and

    mrq2 is analyzed, generating mrq1.n_channel x mrq2.n_channel pairs

  • ‘pairwise’: the signals in mrq1 and mrq2 are paired

    together based on their order of apparition, mrq1 and mrq2 need to have the same number of signals.

bootstrap_weightedstr | None

Whether the boostrapped mrqs will have weighted regressions.

Rint

Number of bootstrapped repetitions, R > 1 not currently tested!

estimatesstr
Quantities to estimate: string containing a character for each of:

  • “s”: structure function

  • “c”: cumulants

Defaults to “auto” which computes both.

robustbool

Use robust estimates of cumulants.

robust_kwargsdict | None

Arguments passed for robust estimation. Used for cumulant estimates of order >= 3.

idx_rejectdict[int, ndarray of bool]

Dictionary associating each scale to a boolean array indicating whether certain coefficients should be removed.

check_regularity: bool

Whether to check the minimum regularity requirements are met by the MRQs.

Returns:
MFractalBiVar

The output of the bivariate multifractal analysis.

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