Add renewable reading + TU. Add timeserie services on AreaLocalService

src/antares/model/area.py

@@ -298,6 +298,9 @@ def get_reserves_matrix(self) -> pd.DataFrame:
 
     def get_misc_gen_matrix(self) -> pd.DataFrame:
         return self._area_service.get_misc_gen_matrix(self)
+
+    def get_renewable_matrix(self, renewable: RenewableCluster) -> pd.DataFrame:
+        return self._renewable_service.get_renewable_matrix(renewable)
 
     def delete_thermal_clusters(self, thermal_clusters: List[ThermalCluster]) -> None:
         self._area_service.delete_thermal_clusters(self, thermal_clusters)

src/antares/service/local_services/area_local.py

@@ -316,14 +316,13 @@ def delete_renewable_clusters(self, area: Area, renewable_clusters: List[Renewab
 
     def delete_st_storages(self, area: Area, storages: List[STStorage]) -> None:
         raise NotImplementedError
-    
+
     def _read_timeseries(self, ts_file_type: TimeSeriesFileType, study_path: Path, area_id: Optional[str] = None, constraint_id: Optional[str] = None) -> pd.DataFrame:
         file_path = study_path / (
             ts_file_type.value
             if not (area_id or constraint_id)
             else ts_file_type.value.format(area_id=area_id, constraint_id=constraint_id)
         )
-
         if os.path.getsize(file_path) != 0:
             _time_series = df_read(file_path)
         else:
@@ -335,17 +334,17 @@ def get_load_matrix(self, area: Area) -> pd.DataFrame:
         return self._read_timeseries(TimeSeriesFileType.LOAD, self.config.study_path, area_id=area.id)
 
     def get_solar_matrix(self, area: Area) -> pd.DataFrame:
-        raise NotImplementedError
+       return self._read_timeseries(TimeSeriesFileType.SOLAR, self.config.study_path, area_id=area.id)
 
     def get_wind_matrix(self, area: Area) -> pd.DataFrame:
-        raise NotImplementedError
+        return self._read_timeseries(TimeSeriesFileType.WIND, self.config.study_path, area_id=area.id)
 
     def get_reserves_matrix(self, area: Area) -> pd.DataFrame:
-        raise NotImplementedError
+        return self._read_timeseries(TimeSeriesFileType.RESERVES, self.config.study_path, area_id=area.id)
 
     def get_misc_gen_matrix(self, area: Area) -> pd.DataFrame:
-        raise NotImplementedError
-
+        return self._read_timeseries(TimeSeriesFileType.MISC_GEN, self.config.study_path, area_id=area.id)
+    
     def read_areas(self) -> List[Area]:
         local_path = self.config.local_path
         areas_path = local_path / self.study_name / "input" / "areas"
@@ -362,4 +361,3 @@ def read_areas(self) -> List[Area]:
                     )
                 )
         return areas
-

src/antares/service/local_services/renewable_local.py

@@ -10,13 +10,19 @@
 #
 # This file is part of the Antares project.
 
-from typing import Any, List
+import os
+
+from pathlib import Path
+from typing import Any, List, Optional
 
 import pandas as pd
 
 from antares.config.local_configuration import LocalConfiguration
-from antares.model.renewable import RenewableCluster, RenewableClusterProperties
+from antares.model.renewable import RenewableCluster, RenewableClusterProperties, RenewableClusterPropertiesLocal
 from antares.service.base_services import BaseRenewableService
+from antares.tools.ini_tool import IniFile, IniFileTypes
+from antares.tools.matrix_tool import df_read
+from antares.tools.time_series_tool import TimeSeriesFileType
 
 
 class RenewableLocalService(BaseRenewableService):
@@ -29,12 +35,40 @@ def update_renewable_properties(
         self, renewable_cluster: RenewableCluster, properties: RenewableClusterProperties
     ) -> RenewableClusterProperties:
         raise NotImplementedError
+
+    def _read_timeseries(self, ts_file_type: TimeSeriesFileType, study_path: Path, area_id: Optional[str] = None, renewable_id: Optional[str] = None) -> pd.DataFrame:
+        file_path = study_path / (
+            ts_file_type.value
+            if not (area_id or renewable_id)
+            else ts_file_type.value.format(area_id=area_id, renewable_id=renewable_id)
+        )
+        if os.path.getsize(file_path) != 0:
+            _time_series = df_read(file_path)
+        else:
+            _time_series = pd.DataFrame()
+
+        return _time_series
 
     def get_renewable_matrix(
         self,
         renewable: RenewableCluster,
     ) -> pd.DataFrame:
-        raise NotImplementedError
+        return self._read_timeseries(TimeSeriesFileType.RENEWABLE_DATA_SERIES, self.config.study_path, area_id=renewable.area_id, renewable_id=renewable.id)
+
 
     def read_renewables(self, area_id: str) -> List[RenewableCluster]:
-        raise NotImplementedError
+        renewable_dict = IniFile(self.config.study_path, IniFileTypes.RENEWABLES_LIST_INI, area_name=area_id).ini_dict
+        renewables_clusters = []
+        if renewable_dict:
+            for renewable_cluster in renewable_dict:
+                renewable_properties = RenewableClusterPropertiesLocal(
+                    group=renewable_dict[renewable_cluster]["group"],
+                    renewable_name=renewable_dict[renewable_cluster]["name"],
+                    enabled=renewable_dict[renewable_cluster]["enabled"],
+                    unit_count=renewable_dict[renewable_cluster]["unitcount"],
+                    nominal_capacity=renewable_dict[renewable_cluster]["nominalcapacity"],
+                    ts_interpretation=renewable_dict[renewable_cluster]["ts-interpretation"],
+                )
+                renewables_clusters.append(RenewableCluster(renewable_service=self, area_id=area_id, name=renewable_dict[renewable_cluster]["name"], properties=renewable_properties.yield_renewable_cluster_properties()))
+        return renewables_clusters
+

src/antares/tools/time_series_tool.py

@@ -48,6 +48,7 @@ class TimeSeriesFileType(Enum):
     WIND_DATA = "input/wind/prepro/{area_id}/data.txt"
     WIND_K = "input/wind/prepro/{area_id}/k.txt"
     WIND_TRANSLATION = "input/wind/prepro/{area_id}/translation.txt"
+    RENEWABLE_DATA_SERIES = "input/renewables/series/{area_id}/{renewable_id}/series.txt"
 
 
 class TimeSeries:

tests/antares/services/local_services/test_area.py

@@ -12,6 +12,7 @@
 
 import pytest
 
+import os
 import typing as t
 
 from configparser import ConfigParser
@@ -1116,15 +1117,16 @@ def test_read_areas_local(self, local_study_w_areas):
             assert area.id in expected_areas
 
 
+def _write_file(_file_path, _time_series) -> None:
+    _file_path.parent.mkdir(parents=True, exist_ok=True)
+    _time_series.to_csv(_file_path, sep="\t", header=False, index=False, encoding="utf-8")
+
 class TestReadLoad:
     def test_read_load_local(self, local_study_w_areas):
         study_path = local_study_w_areas.service.config.study_path
         local_study_object = read_study_local(study_path)
         areas = local_study_object.read_areas()
 
-        def _write_file(_file_path, _time_series) -> None:
-            _file_path.parent.mkdir(parents=True, exist_ok=True)
-            _time_series.to_csv(file_path, sep="\t", header=False, index=False, encoding="utf-8")
 
         for area in areas:
             expected_time_serie = pd.DataFrame(
@@ -1137,12 +1139,52 @@ def _write_file(_file_path, _time_series) -> None:
             file_path = study_path / "input" / "load" / "series" / f"load_{area.id}.txt"
             _write_file(file_path, expected_time_serie)
 
-            load_object = area.get_load_matrix()
-            pd.testing.assert_frame_equal(load_object.astype(str), expected_time_serie.astype(str), check_dtype=False)
+            matrix = area.get_load_matrix()
+            pd.testing.assert_frame_equal(matrix.astype(str), expected_time_serie.astype(str), check_dtype=False)
 
         expected_time_serie = pd.DataFrame([])
         for area in areas:
             file_path = study_path / "input" / "load" / "series" / f"load_{area.id}.txt"
             _write_file(file_path, expected_time_serie)
-            load_object = area.get_load_matrix()
-            pd.testing.assert_frame_equal(load_object, expected_time_serie)
+            matrix = area.get_load_matrix()
+            pd.testing.assert_frame_equal(matrix, expected_time_serie)
+
+
+class TestReadRenewable:
+    def test_read_renewable_local(self, local_study_with_renewable):
+        study_path = local_study_with_renewable.service.config.study_path
+        local_study_object = read_study_local(study_path)
+        areas = local_study_object.read_areas()
+
+        expected_time_serie = pd.DataFrame(
+                    [
+                        [-9999999980506447872, 0, 9999999980506447872],
+                        [0, area.id, 0],
+                    ]
+                , dtype="object")
+
+        for area in areas:
+            renewable_list = area.read_renewables(area.id)
+
+            if renewable_list:
+                assert area.id == "fr"
+                assert isinstance(renewable_list, list)
+                assert isinstance(renewable_list[0], RenewableCluster)
+
+            for renewable in renewable_list:
+                assert renewable.name == "renewable cluster"
+                assert renewable.properties.unit_count == 1
+                assert renewable.properties.ts_interpretation.value == "power-generation"
+                assert renewable.properties.nominal_capacity == 0.000000
+                assert renewable.properties.enabled
+                assert renewable.properties.group.value == "Other RES 1"
+
+                # Create folder and file for timeserie.
+                cluster_path = study_path / "input" / "renewables" / "series"/ Path(area.id) /  Path(renewable.id)
+                os.makedirs(cluster_path, exist_ok=True)
+                series_path = cluster_path / 'series.txt'
+                _write_file(series_path, expected_time_serie)
+
+                # Check matrix
+                matrix = area.get_renewable_matrix(renewable)
+                pd.testing.assert_frame_equal(matrix.astype(str), expected_time_serie.astype(str), check_dtype=False)