This is a library that performs MF-DFA analysis on solar weather data, as described in https://academic.oup.com/mnras/article/519/3/3623/6881729?login=false.

Prerequisites Python 3 or higher must be installed. The following Python libraries must be installed: numpy, and pyspedas

How to run with MMS1 FGM data:

This library currently contains a function to run an MF-DFA analysis on MMS1 FGM data. This is the main function used to perform the entire analysis. This can be run as such:

python3 main.py

List of functions:

Here is a list of functions that perform the MF-DFA analysis. These are contained in the file called mfdfa_lib.py in the source folder.

mfdfa_lib.int_series() This function returns the integrated time series of an input time series.

mfdfa_lib.poly_fit() This function returns the polynomial fit of an integrated time series segment. The function returns the coefficients of the polynomial fit.

mfdfa_lib.polyFunc() This function evaluates the value of the polynomial from a set of fit coefficients.

mfdfa_lib.variance() This function evaluates the variance of a given segment.