pyhctsa.operations.stationarity.moment_corr

pyhctsa.operations.stationarity.moment_corr(x, window_length=None, w_overlap=None, mom_1='mean', mom_2='std', what_transform='none')

Correlations between simple statistics in local windows of a time series. The idea to implement this was that of Prof. Nick S. Jones (Imperial College London).

Parameters:
x : array-like

the input time series

window_length : float, optional

the sliding window length (can be a fraction to specify or a proportion of the time-series length)

w_overlap : None | float

the overlap between consecutive windows as a fraction of the window length

mom_1 : str, optional

the statistics to investigate correlations between (in each window):

  1. ’iqr’: interquartile range

  2. ’median’: median

  3. ’std’: standard deviation (about the local mean)

  4. ’mean’: mean

mom_2 : str, optional

the statistics to investigate correlations between (in each window):

  1. ’iqr’: interquartile range

  2. ’median’: median

  3. ’std’: standard deviation (about the local mean)

  4. ’mean’: mean

what_transform : str, optional

the pre-processing what_transform to apply to the time series before analyzing it:

  1. ’abs’: takes absolute values of all data points

  2. ’sqrt’: takes the square root of absolute values of all data points

  3. ’sq’: takes the square of every data point

  4. ’none’: does no what_transform

Returns:

Dictionary of statistics related to the correlation between simple statistics in local windows of the input time series.

Return type:

out