pyhctsa.operations.information.automutual_info¶

pyhctsa.operations.information.automutual_info(y, time_delay=1, est_method='kernel', extra_param=None)¶

Compute time-delayed automutual information of a time series.

Calculates the mutual information between a time series and its time-delayed version using various estimation methods from the JIDT (Java Information Dynamics Toolkit).

References

Parameters:¶

y : array-like¶

Input time series (1D).

time_delay : int, str, or list of int, optional¶

Time lag(s) for automutual information calculation. Can be:

• int: a fixed lag

• list of int: multiple lags

• ’ac’: first zero-crossing of autocorrelation

• ’tau’: same as ‘ac’

Default is 1.

est_method : {'gaussian', 'kernel', 'kraskov1', 'kraskov2'}, optional¶

Method for estimating mutual information:

• ’gaussian’: Assumes Gaussian variables

• ’kernel’: Kernel density estimation (default)

• ’kraskov1’: Kraskov estimator 1 (KSG1)

• ’kraskov2’: Kraskov estimator 2 (KSG2)

extra_param : int or str, optional¶

Extra parameter for the estimator. For Kraskov estimators, this sets the number of nearest neighbors ‘k’ (default is 3).

Returns:¶

If single time_delay:

float: The automutual information value

If multiple time_delay:

dict: Keys are f”ami{delay}”, values are corresponding AMI values

Return type:¶

float or dict