From 962d94aa758f28897017006c484235bbc05394dc Mon Sep 17 00:00:00 2001
From: James Fulton <41546094+dfulu@users.noreply.github.com>
Date: Wed, 17 Apr 2024 10:20:29 +0100
Subject: [PATCH 1/2] Loosen requirements

---
 requirements.txt | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/requirements.txt b/requirements.txt
index f394115..4101254 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,5 +1,5 @@
-ocf_datapipes==3.2.*
-pvnet==3.0.*
+ocf_datapipes>=3.2
+pvnet>=3.0
 numpy
 pandas
 matplotlib

From 956a9832d8af389444f6b9d2d8153e65b7a13817 Mon Sep 17 00:00:00 2001
From: James Fulton <djamesfulton@yahoo.co.uk>
Date: Wed, 17 Apr 2024 09:42:30 +0000
Subject: [PATCH 2/2] partial update to new pvnet

---
 pvnet_summation/models/base_model.py | 9 +++++----
 pvnet_summation/models/model.py      | 2 +-
 requirements.txt                     | 4 ++--
 3 files changed, 8 insertions(+), 7 deletions(-)

diff --git a/pvnet_summation/models/base_model.py b/pvnet_summation/models/base_model.py
index 6e7d541..50e23a1 100644
--- a/pvnet_summation/models/base_model.py
+++ b/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 = (
diff --git a/pvnet_summation/models/model.py b/pvnet_summation/models/model.py
index fb0ad79..18ae98e 100644
--- a/pvnet_summation/models/model.py
+++ b/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)
diff --git a/requirements.txt b/requirements.txt
index 4101254..c31f661 100644
--- a/requirements.txt
+++ b/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