pyhctsa.operations.symbolic.transition_p_alphabet¶

pyhctsa.operations.symbolic.transition_p_alphabet(y, num_groups=None, tau=1)¶

How transition probabilities change with alphabet size.

The time series is discretized by quantile separation into alphabets of a range of sizes, and the one-time transition matrix is computed for each. Statistics of those transition matrices are then tracked as a function of the alphabet size.

Parameters:¶

y : array-like¶

The input time series.

num_groups : array-like, optional¶

The range of alphabet sizes to compare across. Must contain more than one value, each at least 2. Default is range(2, 11).

tau : int or str, optional¶

The time-delay. The time series is downsampled at this lag before being discretized. Can also be set to 'ac' to use the first zero-crossing of the autocorrelation function. Default is 1.

Returns:¶

The decay rate of the sum, mean, and maximum of the diagonal elements of the transition matrices, changes in symmetry, and statistics of their eigenvalues.

Return type:¶

dict