update

ModelPerformance.py

@@ -1,6 +1,15 @@
 import numpy as np
 import  matplotlib.pyplot as plt
 from sklearn.metrics import mean_squared_error
+def std_inverse(std,data):
+    original_shape = data.shape
+    try:
+        data = data.copy()
+    except Exception:
+        pass
+    inversed_data = std.inverse_transform(np.reshape(data,(-1,data.shape[-2]*data.shape[-1])))
+    inversed_data = inversed_data.reshape(original_shape)
+    return inversed_data
 def compare_result(predict,real):
     assert(predict.shape == real.shape)
     original_shape = predict.shape
@@ -27,12 +36,3 @@ def plot_result(predict,real,batch =0,in_out = 0):
     axs[2].imshow(np.abs(predict[batch,in_out,:,:] - real[batch,in_out,:,:]), cmap = cmap,vmin = vmin,vmax = vmax)
 
     plt.show()
-def std_inverse(std,data):
-    original_shape = data.shape
-    try:
-        data = data.copy()
-    except Exception:
-        pass
-    inversed_data = std.inverse_transform(np.reshape(data,(-1,data.shape[-2]*data.shape[-1])))
-    inversed_data = inversed_data.reshape(original_shape)
-    return inversed_data