Source code for pysparse.evaluation.error

#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Date    : 2019-06-13 10:34:43
# @Author  : Yan Liu & Zhi Liu (zhiliu.mind@gmail.com)
# @Link    : http://iridescent.ink
# @Version : $1.0$
import numpy as np


[docs]def mse(o, r): r"""Mean Squared Error The Mean Squared Error (MSE) is expressed as .. math:: {\rm MSE} = \frac{1}{MN}\sum_{i=1}^{M}\sum_{j=0}^{N}[{\bm I}(i,j), \hat{\bm I}(i, j)]^2 Arguments --------------- o : ndarray Orignal signal matrix. r : ndarray Reconstructed signal matrix Returns --------------- MSE : float Mean Squared Error """ return np.mean((o.astype(float) - r.astype(float)) ** 2)
[docs]def rmse(o, r): r"""Root Mean Squared Error The Root Mean Squared Error (MSE) is expressed as .. math:: {\rm RMSE} = \sqrt{\frac{1}{MN}\sum_{i=1}^{M}\sum_{j=0}^{N}[{\bm I}(i,j), \hat{\bm I}(i, j)]^2} Arguments --------------- o : ndarray Orignal signal matrix. r : ndarray Reconstructed signal matrix Returns --------------- RMSE : float Root Mean Squared Error """ return np.sqrt(np.mean((o.astype(float) - r.astype(float)) ** 2))
if __name__ == '__main__': o = np.array([[1, 2, 3], [4, 5, 6]]) r = np.array([[0, 2, 3], [4, 5, 6]]) print(mse(o, r)) print(rmse(o, r))