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utils/metrics.py

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+import numpy as np
+
+def RSE(pred, true):
+    return np.sqrt(np.sum((true-pred)**2)) / np.sqrt(np.sum((true-true.mean())**2))
+
+def CORR(pred, true):
+    u = ((true-true.mean(0))*(pred-pred.mean(0))).sum(0) 
+    d = np.sqrt(((true-true.mean(0))**2*(pred-pred.mean(0))**2).sum(0))
+    return (u/d).mean(-1)
+
+def MAE(pred, true):
+    return np.mean(np.abs(pred-true))
+
+def MSE(pred, true):
+    return np.mean((pred-true)**2)
+
+def RMSE(pred, true):
+    return np.sqrt(MSE(pred, true))
+
+def MAPE(pred, true):
+    return np.mean(np.abs((pred - true) / true))
+
+def MSPE(pred, true):
+    return np.mean(np.square((pred - true) / true))
+
+def metric(pred, true):
+    mae = MAE(pred, true)
+    mse = MSE(pred, true)
+    rmse = RMSE(pred, true)
+    mape = MAPE(pred, true)
+    mspe = MSPE(pred, true)
+    
+    return mae,mse,rmse,mape,mspe