fix tests

antarest/study/storage/rawstudy/model/filesystem/common/prepro.py

@@ -61,11 +61,13 @@ class PreproArea(FolderNode):
     @override
     def build(self) -> TREE:
         children: TREE = {
-            "conversion": InputSeriesMatrix(self.context, self.config.next_file("conversion.txt"), default_conversion),
-            "data": InputSeriesMatrix(self.context, self.config.next_file("data.txt"), default_data),
-            "k": InputSeriesMatrix(self.context, self.config.next_file("k.txt"), default_k),
+            "conversion": InputSeriesMatrix(
+                self.context, self.config.next_file("conversion.txt"), default_empty=default_conversion
+            ),
+            "data": InputSeriesMatrix(self.context, self.config.next_file("data.txt"), default_empty=default_data),
+            "k": InputSeriesMatrix(self.context, self.config.next_file("k.txt"), default_empty=default_k),
             "translation": InputSeriesMatrix(
-                self.context, self.config.next_file("translation.txt"), default_scenario_hourly
+                self.context, self.config.next_file("translation.txt"), default_empty=default_scenario_hourly
             ),
             "settings": PreproAreaSettings(self.context, self.config.next_file("settings.ini")),
         }

antarest/study/storage/rawstudy/model/filesystem/matrix/input_series_matrix.py

@@ -42,14 +42,18 @@ def __init__(
         self,
         context: ContextServer,
         config: FileStudyTreeConfig,
-        default_empty: npt.NDArray[np.float64],
         freq: MatrixFrequency = MatrixFrequency.HOURLY,
         nb_columns: t.Optional[int] = None,
+        default_empty: t.Optional[npt.NDArray[np.float64]] = None,
     ):
         super().__init__(context=context, config=config, freq=freq)
         self.nb_columns = nb_columns
-        self.default_empty = np.copy(default_empty)
-        self.default_empty.flags.writeable = True
+        if default_empty is None:
+            self.default_empty = None
+        else:
+            # Clone the template value and make it writable
+            self.default_empty = np.copy(default_empty)
+            self.default_empty.flags.writeable = True
 
     def parse_as_dataframe(self, file_path: t.Optional[Path] = None) -> pd.DataFrame:
         file_path = file_path or self.config.path
@@ -81,7 +85,10 @@ def parse_as_dataframe(self, file_path: t.Optional[Path] = None) -> pd.DataFrame
             return final_matrix
         except EmptyDataError:
             logger.warning(f"Empty file found when parsing {file_path}")
-            return pd.DataFrame(self.default_empty)
+            final_matrix = pd.DataFrame()
+            if self.default_empty is not None:
+                final_matrix = pd.DataFrame(self.default_empty)
+            return final_matrix
 
     @override
     def parse_as_json(self, file_path: t.Optional[Path] = None) -> JSON:
@@ -145,5 +152,5 @@ def get_file_content(self) -> OriginalFile:
         return OriginalFile(content=content, suffix=suffix, filename=filename)
 
     @override
-    def get_default_empty_matrix(self) -> npt.NDArray[np.float64]:
+    def get_default_empty_matrix(self) -> t.Optional[npt.NDArray[np.float64]]:
         return self.default_empty

antarest/study/storage/rawstudy/model/filesystem/root/input/hydro/prepro/area/area.py

@@ -19,15 +19,17 @@
     InputHydroPreproAreaPrepro,
 )
 
-default_energy = np.zeros((5, 12), dtype=np.float64)
+default_energy = np.zeros((12, 5), dtype=np.float64)
 default_energy.flags.writeable = False
 
 
 class InputHydroPreproArea(FolderNode):
     @override
     def build(self) -> TREE:
         children: TREE = {
-            "energy": InputSeriesMatrix(self.context, self.config.next_file("energy.txt"), default_energy),
+            "energy": InputSeriesMatrix(
+                self.context, self.config.next_file("energy.txt"), default_empty=default_energy
+            ),
             "prepro": InputHydroPreproAreaPrepro(self.context, self.config.next_file("prepro.ini")),
         }
         return children

tests/integration/raw_studies_blueprint/test_download_matrices.py

@@ -275,15 +275,15 @@ def test_download_matrices(self, client: TestClient, user_access_token: str, int
             assert list(dataframe.index) == list(dataframe.columns) == ["de", "es", "fr", "it"]
             assert all(np.isclose(dataframe.iloc[i, i], 1.0) for i in range(len(dataframe)))
 
-        # test for empty matrix
+        # checks default value for an empty water_values matrix
         res = client.get(
             f"/v1/studies/{internal_study_id}/raw/download",
             params={"path": "input/hydro/common/capacity/waterValues_de", "format": "tsv"},
         )
         assert res.status_code == 200
         content = io.BytesIO(res.content)
         dataframe = pd.read_csv(content, index_col=0, sep="\t")
-        assert dataframe.empty
+        assert dataframe.to_numpy().tolist() == 365 * [101 * [0.0]]
 
         # modulation matrix
         res = client.get(
@@ -328,15 +328,15 @@ def test_download_matrices(self, client: TestClient, user_access_token: str, int
             "('HURDLE COST', 'Euro', '')",
         ]
 
-        # test energy matrix to test the regex
+        # checks default value for an empty energy matrix
         res = client.get(
             f"/v1/studies/{internal_study_id}/raw/download",
             params={"path": "input/hydro/prepro/de/energy", "format": "tsv"},
         )
         assert res.status_code == 200
         content = io.BytesIO(res.content)
         dataframe = pd.read_csv(content, index_col=0, sep="\t")
-        assert dataframe.empty
+        assert dataframe.to_numpy().tolist() == 12 * [5 * [0.0]]
 
         # test the Min Gen of the 8.6 study
         for export_format in ["tsv", "xlsx"]: