Default time series with zeroes are created if none is provided

src/antares/service/local_services/binding_constraint_local.py

@@ -12,6 +12,7 @@
 
 from typing import Optional, Any
 
+import numpy as np
 import pandas as pd
 
 from antares.config.local_configuration import LocalConfiguration
@@ -21,6 +22,7 @@
     BindingConstraint,
     ConstraintMatrixName,
     BindingConstraintOperator,
+    BindingConstraintFrequency,
 )
 from antares.service.base_services import BaseBindingConstraintService
 from antares.tools.ini_tool import IniFile, IniFileTypes
@@ -58,40 +60,49 @@ def create_binding_constraint(
         self._write_binding_constraint_ini()
 
         # Add constraint time series
-        if (
-            constraint.properties.operator in (BindingConstraintOperator.LESS, BindingConstraintOperator.BOTH)
-            and less_term_matrix is not None
-        ):
+        time_series_length = (
+            (365 * 24 + 24) if constraint.properties.time_step == BindingConstraintFrequency.HOURLY else 366
+        )
+
+        if constraint.properties.operator in (BindingConstraintOperator.LESS, BindingConstraintOperator.BOTH):
+            time_series = (
+                less_term_matrix if less_term_matrix is not None else pd.DataFrame(np.zeros([time_series_length, 1]))
+            )
             self._time_series[f"{name}_lt"] = TimeSeries(
-                less_term_matrix,
+                time_series,
                 TimeSeriesFile(
                     TimeSeriesFileType.BINDING_CONSTRAINT_LESS,
                     self.config.study_path,
                     constraint_id=constraint.id.lower(),
-                    time_series=less_term_matrix,
+                    time_series=time_series,
                 ),
             )
-        if constraint.properties.operator == BindingConstraintOperator.EQUAL and equal_term_matrix is not None:
+        if constraint.properties.operator == BindingConstraintOperator.EQUAL:
+            time_series = (
+                equal_term_matrix if equal_term_matrix is not None else pd.DataFrame(np.zeros([time_series_length, 1]))
+            )
             self._time_series[f"{name}_eq"] = TimeSeries(
-                equal_term_matrix,
+                time_series,
                 TimeSeriesFile(
                     TimeSeriesFileType.BINDING_CONSTRAINT_EQUAL,
                     self.config.study_path,
                     constraint_id=constraint.id.lower(),
-                    time_series=equal_term_matrix,
+                    time_series=time_series,
                 ),
             )
-        if (
-            constraint.properties.operator in (BindingConstraintOperator.GREATER, BindingConstraintOperator.BOTH)
-            and greater_term_matrix is not None
-        ):
+        if constraint.properties.operator in (BindingConstraintOperator.GREATER, BindingConstraintOperator.BOTH):
+            time_series = (
+                greater_term_matrix
+                if greater_term_matrix is not None
+                else pd.DataFrame(np.zeros([time_series_length, 1]))
+            )
             self._time_series[f"{name}_gt"] = TimeSeries(
-                greater_term_matrix,
+                time_series,
                 TimeSeriesFile(
                     TimeSeriesFileType.BINDING_CONSTRAINT_GREATER,
                     self.config.study_path,
                     constraint_id=constraint.id.lower(),
-                    time_series=greater_term_matrix,
+                    time_series=time_series,
                 ),
             )
 

tests/antares/services/local_services/test_study.py

@@ -49,6 +49,7 @@
 from antares.service.local_services.st_storage_local import ShortTermStorageLocalService
 from antares.service.local_services.thermal_local import ThermalLocalService
 from antares.tools.ini_tool import IniFileTypes
+from antares.tools.time_series_tool import TimeSeriesFileType
 
 
 class TestCreateStudy:
@@ -1301,3 +1302,67 @@ def test_binding_constraint_with_timeseries_stores_ts_file(self, local_study_wit
         assert local_study_with_hydro._binding_constraints_service.time_series[
             f"{constraints['both'].id.lower()}_gt"
         ].local_file.file_path.is_file()
+
+    def test_binding_constraints_have_correct_default_time_series(self, test_constraint, local_study_with_constraint):
+        # Given
+        expected_time_series_hourly = pd.DataFrame(np.zeros([365 * 24 + 24, 1]))
+        expected_time_series_daily_weekly = pd.DataFrame(np.zeros([365 + 1, 1]))
+        local_study_with_constraint.create_binding_constraint(
+            name="test greater",
+            properties=BindingConstraintProperties(
+                operator=BindingConstraintOperator.GREATER, time_step=BindingConstraintFrequency.WEEKLY
+            ),
+        )
+        local_study_with_constraint.create_binding_constraint(
+            name="test equal",
+            properties=BindingConstraintProperties(
+                operator=BindingConstraintOperator.EQUAL, time_step=BindingConstraintFrequency.DAILY
+            ),
+        )
+        local_study_with_constraint.create_binding_constraint(
+            name="test both",
+            properties=BindingConstraintProperties(
+                operator=BindingConstraintOperator.BOTH, time_step=BindingConstraintFrequency.HOURLY
+            ),
+        )
+        expected_pre_created_ts_file = (
+            local_study_with_constraint.service.config.study_path
+            / TimeSeriesFileType.BINDING_CONSTRAINT_LESS.value.format(constraint_id=test_constraint.id)
+        )
+
+        # When
+        with local_study_with_constraint._binding_constraints_service.time_series[
+            f"{test_constraint.id}_lt"
+        ].local_file.file_path.open("r") as pre_created_file:
+            actual_time_series_pre_created = pd.read_csv(pre_created_file, header=None)
+        with local_study_with_constraint._binding_constraints_service.time_series[
+            "test greater_gt"
+        ].local_file.file_path.open("r") as greater_file:
+            actual_time_series_greater = pd.read_csv(greater_file, header=None)
+        with local_study_with_constraint._binding_constraints_service.time_series[
+            "test equal_eq"
+        ].local_file.file_path.open("r") as equal_file:
+            actual_time_series_equal = pd.read_csv(equal_file, header=None)
+        with local_study_with_constraint._binding_constraints_service.time_series[
+            "test both_gt"
+        ].local_file.file_path.open("r") as both_greater_file:
+            actual_time_series_both_greater = pd.read_csv(both_greater_file, header=None)
+        with local_study_with_constraint._binding_constraints_service.time_series[
+            "test both_lt"
+        ].local_file.file_path.open("r") as both_lesser_file:
+            actual_time_series_both_lesser = pd.read_csv(both_lesser_file, header=None)
+
+        # Then
+        # Verify that file names are created correctly
+        assert (
+            local_study_with_constraint._binding_constraints_service.time_series[
+                f"{test_constraint.id}_lt"
+            ].local_file.file_path
+            == expected_pre_created_ts_file
+        )
+        # Verify that default file contents are the correct and expected
+        assert actual_time_series_pre_created.equals(expected_time_series_hourly)
+        assert actual_time_series_greater.equals(expected_time_series_daily_weekly)
+        assert actual_time_series_equal.equals(expected_time_series_daily_weekly)
+        assert actual_time_series_both_greater.equals(expected_time_series_hourly)
+        assert actual_time_series_both_lesser.equals(expected_time_series_hourly)