Merge branch 'master' of gitlab.inf.unibz.it:REMSEN/climax

Scripts/downscale.sh

@@ -5,7 +5,7 @@ conda activate climax
 cd ~/git/climax
 
 # wet day thresholds to test
-WET_DAY_THRESHOLDS=(0, 0.5, 1, 2, 3, 5)
+WET_DAY_THRESHOLDS=(0 0.5 1 2 3 5)
 
 for w in ${WET_DAY_THRESHOLDS[@]}; do
     # change wet day threshold in configuration

climax/core/loss.py

@@ -48,7 +48,7 @@ class L1Loss(NaNLoss):
         return F.l1_loss(y_pred[mask], y_true[mask], reduction=self.reduction)
 
 
-class BernoulliLoss(NaNLoss):
+class BernoulliGammaLoss(NaNLoss):
 
     def __init__(self, size_average=None, reduce=None, reduction='mean',
                  min_amount=0):
@@ -57,13 +57,6 @@ class BernoulliLoss(NaNLoss):
         # minimum amount of precipitation to be classified as precipitation
         self.min_amount = min_amount
 
-
-class BernoulliGammaLoss(BernoulliLoss):
-
-    def __init__(self, size_average=None, reduce=None, reduction='mean',
-                 min_amount=0):
-        super().__init__(size_average, reduce, reduction)
-
     def forward(self, y_pred, y_true):
 
         # convert to float32
@@ -111,12 +104,15 @@ class BernoulliGammaLoss(BernoulliLoss):
         return p * np.exp(shape) * np.exp(scale)
 
 
-class BernoulliGenParetoLoss(BernoulliLoss):
+class BernoulliGenParetoLoss(NaNLoss):
 
     def __init__(self, size_average=None, reduce=None, reduction='mean',
                  min_amount=0):
         super().__init__(size_average, reduce, reduction)
 
+        # minimum amount of precipitation to be classified as precipitation
+        self.min_amount = min_amount
+
     def forward(self, y_pred, y_true):
 
         # convert to float32
@@ -157,12 +153,15 @@ class BernoulliGenParetoLoss(BernoulliLoss):
         return self.reduce(loss)
 
 
-class BernoulliWeibullLoss(BernoulliLoss):
+class BernoulliWeibullLoss(NaNLoss):
 
     def __init__(self, size_average=None, reduce=None, reduction='mean',
                  min_amount=0):
         super().__init__(size_average, reduce, reduction)
 
+        # minimum amount of precipitation to be classified as precipitation
+        self.min_amount = min_amount
+
     def forward(self, y_pred, y_true):
 
         # convert to float32