also add min_length parameter for train and val set

src/run_modules/experiment_setup.py

@@ -35,7 +35,7 @@ class ExperimentSetup(RunEnvironment):
                  test_end=None, use_all_stations_on_all_data_sets=True, trainable=None, fraction_of_train=None,
                  experiment_path=None, plot_path=None, forecast_path=None, overwrite_local_data=None, sampling="daily",
                  create_new_model=None, bootstrap_path=None, permute_data_on_training=None, transformation=None,
-                 test_min_length=None):
+                 train_min_length=None, val_min_length=None, test_min_length=None):
 
         # create run framework
         super().__init__()
@@ -100,19 +100,23 @@ class ExperimentSetup(RunEnvironment):
         # train set parameters
         self._set_param("start", train_start, default="1997-01-01", scope="general.train")
         self._set_param("end", train_end, default="2007-12-31", scope="general.train")
+        self._set_param("min_length", train_min_length, default=90, scope="general.train")
 
         # validation set parameters
         self._set_param("start", val_start, default="2008-01-01", scope="general.val")
         self._set_param("end", val_end, default="2009-12-31", scope="general.val")
+        self._set_param("min_length", val_min_length, default=90, scope="general.val")
 
         # test set parameters
         self._set_param("start", test_start, default="2010-01-01", scope="general.test")
         self._set_param("end", test_end, default="2017-12-31", scope="general.test")
-        self._set_param("min_length", test_min_length, default=30, scope="general.test")
+        self._set_param("min_length", test_min_length, default=90, scope="general.test")
 
         # train_val set parameters
         self._set_param("start", self.data_store.get("start", "general.train"), scope="general.train_val")
         self._set_param("end", self.data_store.get("end", "general.val"), scope="general.train_val")
+        train_val_min_length = sum([self.data_store.get("min_length", f"general.{s}") for s in ["train", "val"]])
+        self._set_param("min_length", train_val_min_length, default=180, scope="general.train_val")
 
         # use all stations on all data sets (train, val, test)
         self._set_param("use_all_stations_on_all_data_sets", use_all_stations_on_all_data_sets, default=True)

test/test_modules/test_experiment_setup.py

@@ -85,12 +85,19 @@ class TestExperimentSetup:
         # train parameters
         assert data_store.get("start", "general.train") == "1997-01-01"
         assert data_store.get("end", "general.train") == "2007-12-31"
+        assert data_store.get("min_length", "general.train") == 90
         # validation parameters
         assert data_store.get("start", "general.val") == "2008-01-01"
         assert data_store.get("end", "general.val") == "2009-12-31"
+        assert data_store.get("min_length", "general.val") == 90
         # test parameters
         assert data_store.get("start", "general.test") == "2010-01-01"
         assert data_store.get("end", "general.test") == "2017-12-31"
+        assert data_store.get("min_length", "general.test") == 90
+        # train_val parameters
+        assert data_store.get("start", "general.train_val") == "1997-01-01"
+        assert data_store.get("end", "general.train_val") == "2009-12-31"
+        assert data_store.get("min_length", "general.train_val") == 180
         # use all stations on all data sets (train, val, test)
         assert data_store.get("use_all_stations_on_all_data_sets", "general") is True
 
@@ -104,7 +111,7 @@ class TestExperimentSetup:
                       interpolate_dim="int_dim", interpolate_method="cubic", limit_nan_fill=5, train_start="2000-01-01",
                       train_end="2000-01-02", val_start="2000-01-03", val_end="2000-01-04", test_start="2000-01-05",
                       test_end="2000-01-06", use_all_stations_on_all_data_sets=False, trainable=False,
-                      fraction_of_train=0.5, experiment_path=experiment_path, create_new_model=True)
+                      fraction_of_train=0.5, experiment_path=experiment_path, create_new_model=True, val_min_length=20)
         exp_setup = ExperimentSetup(**kwargs)
         data_store = exp_setup.data_store
         # experiment setup
@@ -139,12 +146,19 @@ class TestExperimentSetup:
         # train parameters
         assert data_store.get("start", "general.train") == "2000-01-01"
         assert data_store.get("end", "general.train") == "2000-01-02"
+        assert data_store.get("min_length", "general.train") == 90
         # validation parameters
         assert data_store.get("start", "general.val") == "2000-01-03"
         assert data_store.get("end", "general.val") == "2000-01-04"
+        assert data_store.get("min_length", "general.val") == 20
         # test parameters
         assert data_store.get("start", "general.test") == "2000-01-05"
         assert data_store.get("end", "general.test") == "2000-01-06"
+        assert data_store.get("min_length", "general.test") == 90
+        # train_val parameters
+        assert data_store.get("start", "general.train_val") == "2000-01-01"
+        assert data_store.get("end", "general.train_val") == "2000-01-04"
+        assert data_store.get("min_length", "general.train_val") == 110
         # use all stations on all data sets (train, val, test)
         assert data_store.get("use_all_stations_on_all_data_sets", "general.test") is False