pyhctsa.operations.scaling.mma¶

pyhctsa.operations.scaling.mma(y, do_overlap=False, scale_range=None, q_range=None)¶

Scale-dependent estimates of multifractal scaling in a time series.

Physionet implementation of multiscale multifractal analysis (MMA). Method was first proposed in [1]. Original author is Jan Gieraltowski (Warsaw University of Technology, Faculty of Physics).

References

Parameters:¶

y : array_like¶

Input time series (a 1-D vector).

do_overlap : bool, optional¶

False (default): partition into non-overlapping windows of analysis. True: overlapping windows with a step of 1 (much longer calculations).

scale_range : sequence of 2 numbers, optional¶

[min_scale, max_scale]. Defaults to [10, round(N/40)]. max_scale must be a multiple of 5 and is rounded to one if it is not.

q_range : sequence of 2 numbers, optional¶

[q_min, q_max] multifractal parameter range. Defaults to [-5, 5].

Returns:¶

Summary statistics.

Return type:¶

dict