pytc.vmc.blocking.detect_equilibration_cma¶

pytc.vmc.blocking.detect_equilibration_cma(data, threshold_sigma=0.5, print_results=True)[source]¶

Detects the equilibration point (burn-in length) using the reverse Cumulative Moving Average (CMA) deviation method.

It scans backward from the end of the simulation. For each step i, it calculates the mean of the data from i to the end. The burn-in period is considered over when this ‘tail mean’ is within a tight threshold of the final steady-state mean.

Parameters:

data (numpy.ndarray)
threshold_sigma (float)
print_results (bool)

Return type:

int