Merge pull request #18 from openclimatefix/Loosen-requirements

Loosen requirements

pvnet_summation/models/base_model.py

@@ -65,22 +65,23 @@ def __init__(
         self.output_quantiles = output_quantiles
 
         # Number of timestemps for 30 minutely data
-        self.forecast_len_30 = self.forecast_minutes // 30
+        self.forecast_len = self.forecast_minutes // 30
 
-        self.weighted_losses = WeightedLosses(forecast_length=self.forecast_len_30)
+        self.weighted_losses = WeightedLosses(forecast_length=self.forecast_len)
 
         self._accumulated_metrics = MetricAccumulator()
         self._accumulated_y = PredAccumulator()
         self._accumulated_y_hat = PredAccumulator()
         self._accumulated_y_sum = PredAccumulator()
         self._accumulated_times = PredAccumulator()
+        self._horizon_maes = MetricAccumulator()
 
         self.use_quantile_regression = self.output_quantiles is not None
 
         if self.use_quantile_regression:
-            self.num_output_features = self.forecast_len_30 * len(self.output_quantiles)
+            self.num_output_features = self.forecast_len * len(self.output_quantiles)
         else:
-            self.num_output_features = self.forecast_len_30
+            self.num_output_features = self.forecast_len
 
         if self.pvnet_model.use_quantile_regression:
             self.pvnet_output_shape = (

pvnet_summation/models/model.py

@@ -96,7 +96,7 @@ def forward(self, x):
 
         if self.use_quantile_regression:
             # Shape: batch_size, seq_length * num_quantiles
-            out = out.reshape(out.shape[0], self.forecast_len_30, len(self.output_quantiles))
+            out = out.reshape(out.shape[0], self.forecast_len, len(self.output_quantiles))
 
         if self.predict_difference_from_sum:
             gsp_sum = self.sum_of_gsps(x)

requirements.txt

@@ -1,5 +1,5 @@
-ocf_datapipes==3.2.*
-pvnet==3.0.*
+ocf_datapipes>=3.3.19
+pvnet>=3.0.25
 numpy
 pandas
 matplotlib