changed static path logic in model files

models/Autoformer.py

@@ -26,6 +26,8 @@ def __init__(self, configs):
         self.label_len = configs.label_len
         self.pred_len = configs.pred_len
         self.output_attention = configs.output_attention
+        self.data = configs.data 
+
         self.use_static = True 
 
         self.static1    = configs.static=="static1"
@@ -66,9 +68,10 @@ def __init__(self, configs):
             # static_raw = torch.tensor([1, 1, 2, 1, 2, 2, 1])   ## synthetic data for ETTh1 
 
             ### this is for Divvy bikes 
-            #self.static_raw = torch.tensor(np.load('auxutils/divvy_static.npy').tolist() )  ## static real data for Divvy Bikes
-
-            self.static_raw = torch.tensor(np.load('auxutils/M5_static.npy')[1].tolist() )  ## static real data for Divvy Bikes
+            if self.data == "Divvy":
+                self.static_raw = torch.tensor(np.load('auxutils/divvy_static.npy').tolist() )  ## static real data for Divvy Bikes
+            if self.data == "M5":
+                self.static_raw = torch.tensor(np.load('auxutils/M5_static.npy')[1].tolist() )  ## static real data for Divvy Bikes
 
             #static_raw = static_raw.repeat((32,72,1))   ## for input it should 96, for output it should be 144
             self.static_raw = self.static_raw.repeat((32,self.repeat_freq,1))   ## for input it should 96, for output it should be 144 

models/DLinear.py

@@ -33,7 +33,8 @@ def __init__(self, configs, individual=False):
         self.static4    = configs.static=="static4"
         self.static6    = configs.static=="static6"
         self.static7    = configs.static=="static7"
-
+        self.data       = configs.data 
+
         print ("self.static1, self.static2, self.static4, self.static6, self.static7", self.static1, self.static2, self.static4, self.static6, self.static7)
 
         ## Raman code starts
@@ -43,8 +44,10 @@ def __init__(self, configs, individual=False):
         if (self.use_static):
 
             # static_raw = torch.tensor([1, 1, 2, 1, 2, 2, 1])   ## synthetic data for ETTh1 
-            #self.static_raw = torch.tensor(np.load('auxutils/divvy_static.npy').tolist() )  ## static real data for Divvy Bikes
-            self.static_raw = torch.tensor(np.load('auxutils/M5_static.npy')[1].tolist() )  ## static real data for Divvy Bikes
+            if self.data == "Divvy":
+                self.static_raw = torch.tensor(np.load('auxutils/divvy_static.npy').tolist() )  ## static real data for Divvy Bikes
+            if self.data == "M5":  
+                    self.static_raw = torch.tensor(np.load('auxutils/M5_static.npy')[1].tolist() )  ## static real data for Divvy Bikes
 
             #static_raw = static_raw.repeat((32,72,1))   ## for input it should 96, for output it should be 144
             #static_raw = static_raw.repeat((32,144,1))  # for Auto and FED former  ## for input it should 96, for output it should be 144 

models/FEDformer.py

@@ -40,7 +40,7 @@ def __init__(self, configs, version='fourier', mode_select='random', modes=32):
         self.static6    = configs.static=="static6"
         self.static7    = configs.static=="static7"
         self.repeat_freq = self.pred_len + self.label_len
-
+        self.data       = configs.data
         # Decomp
         self.decomp = series_decomp(configs.moving_avg)
 
@@ -54,8 +54,10 @@ def __init__(self, configs, version='fourier', mode_select='random', modes=32):
             print ("pred_len, label_len", self.pred_len, self.label_len, self.pred_len + self.label_len)
 
             # static_raw = torch.tensor([1, 1, 2, 1, 2, 2, 1])   ## synthetic data for ETTh1 
-            #self.static_raw = torch.tensor(np.load('auxutils/divvy_static.npy').tolist() )  ## static real data for Divvy Bikes
-            self.static_raw = torch.tensor(np.load('auxutils/M5_static.npy')[1].tolist() )  ## static real data for Divvy Bikes
+            if self.data == "Divvy":
+                self.static_raw = torch.tensor(np.load('auxutils/divvy_static.npy').tolist() )  ## static real data for Divvy Bikes
+            if self.data == "M5":
+                self.static_raw = torch.tensor(np.load('auxutils/M5_static.npy')[1].tolist() )  ## static real data for Divvy Bikes
 
             #static_raw = static_raw.repeat((32,72,1))   ## for input it should 96, for output it should be 144