suboptimumg.log_analysis.utils#

suboptimumg.log_analysis.utils.estimate_fs(t_s)[source]#

Median-step sample-rate estimate (Hz) from a seconds time vector.

Parameters:

t_s (NDArray[float64])

Return type:

float

suboptimumg.log_analysis.utils.safe_gradient(signal, dt)[source]#

Compute a time derivative that is robust to zero-width time steps, so that duplicate timestamps do not produce inf or NaN values.

Parameters:

  • signal (NDArray[np.float64]) – The signal to differentiate.

  • dt (NDArray[np.float64]) – Time step array. Must be the same length as signal.

Returns:

d(signal)/dt with NaNs from zero-width steps filled by linear interpolation between the nearest valid neighbours.

Return type:

NDArray[np.float64]