g_mean_diff

HydroErr.HydroErr.g_mean_diff(simulated_array: ndarray[tuple[Any, ...], dtype[floating | integer]] | Sequence[int | float], observed_array: ndarray[tuple[Any, ...], dtype[floating | integer]] | Sequence[int | float], replace_nan: float | None = None, replace_inf: float | None = None, remove_neg: bool = False, remove_zero: bool = False) → floating[Any]

Compute the geometric mean difference.

\[GM = e^{(S' - O')}\]

\[S' = \left( \prod^n_{i=1} \ln{(S_i)} \right)^{\frac{1}{n}}\]

\[O' = \left( \prod^n_{i=1} \ln{(O_i)} \right)^{\frac{1}{n}}\]

Range:

Notes: For the difference of geometric means, the geometric mean is computed for each of two samples then their difference is taken.

Parameters:

• simulated_array – An array of simulated data from the time series.

• observed_array – An array of observed data from the time series.

• replace_nan – If given, indicates which value to replace NaN values with in the two arrays. If None, when a NaN value is found at the i-th position in the observed OR simulated array, the i-th value of the observed and simulated array are removed before the computation.

• replace_inf – If given, indicates which value to replace Inf values with in the two arrays. If None, when an inf value is found at the i-th position in the observed OR simulated array, the i-th value of the observed and simulated array are removed before the computation.

• remove_neg – If True, when a negative value is found at the i-th position in the observed OR simulated array, the i-th value of the observed AND simulated array are removed before the computation.

• remove_zero – If true, when a zero value is found at the i-th position in the observed OR simulated array, the i-th value of the observed AND simulated array are removed before the computation.

Return type:

The geometric mean difference value.

Examples

>>> import HydroErr as he
>>> import numpy as np

>>> sim = np.array([5, 7, 9, 2, 4.5, 6.7])
>>> obs = np.array([4.7, 6, 10, 2.5, 4, 7])
>>> he.g_mean_diff(sim, obs)
0.988855412098022