refactor(api-download): correct implementation of `get_matrix_with_in…

…dex_and_header`

antarest/study/service.py

@@ -1,10 +1,10 @@
 import base64
 import contextlib
+import fnmatch
 import io
 import json
 import logging
 import os
-import re
 import time
 import typing as t
 from datetime import datetime, timedelta
@@ -116,7 +116,7 @@
 from antarest.study.storage.utils import (
     MatrixProfile,
     assert_permission,
-    get_specific_matrices_according_to_version,
+    get_matrix_profile_by_version,
     get_start_date,
     is_managed,
     remove_from_cache,
@@ -2426,41 +2426,41 @@ def get_matrix_with_index_and_header(
     ) -> pd.DataFrame:
         matrix_path = Path(path)
         study = self.get_study(study_id)
-        for aggregate in ["allocation", "correlation"]:
-            if matrix_path == Path("input") / "hydro" / aggregate:
-                all_areas = t.cast(
-                    t.List[AreaInfoDTO],
-                    self.get_all_areas(study_id, area_type=AreaType.AREA, ui=False, params=parameters),
-                )
-                if aggregate == "allocation":
-                    hydro_matrix = self.allocation_manager.get_allocation_matrix(study, all_areas)
-                else:
-                    hydro_matrix = self.correlation_manager.get_correlation_matrix(all_areas, study, [])  # type: ignore
-                return pd.DataFrame(data=hydro_matrix.data, columns=hydro_matrix.columns, index=hydro_matrix.index)
-
-        json_matrix = self.get(study_id, path, depth=3, formatted=True, params=parameters)
-        for key in ["data", "index", "columns"]:
-            if key not in json_matrix:
-                raise IncorrectPathError(f"The path filled does not correspond to a matrix : {path}")
-        if not json_matrix["data"]:
+
+        if matrix_path.parts in [("input", "hydro", "allocation"), ("input", "hydro", "correlation")]:
+            all_areas = t.cast(
+                t.List[AreaInfoDTO],
+                self.get_all_areas(study_id, area_type=AreaType.AREA, ui=False, params=parameters),
+            )
+            if matrix_path.parts[-1] == "allocation":
+                hydro_matrix = self.allocation_manager.get_allocation_matrix(study, all_areas)
+            else:
+                hydro_matrix = self.correlation_manager.get_correlation_matrix(all_areas, study, [])  # type: ignore
+            return pd.DataFrame(data=hydro_matrix.data, columns=hydro_matrix.columns, index=hydro_matrix.index)
+
+        matrix_obj = self.get(study_id, path, depth=3, formatted=True, params=parameters)
+        if set(matrix_obj) != {"data", "index", "columns"}:
+            raise IncorrectPathError(f"The provided path does not point to a valid matrix: '{path}'")
+        if not matrix_obj["data"]:
             return pd.DataFrame()
-        df_matrix = pd.DataFrame(data=json_matrix["data"], columns=json_matrix["columns"], index=json_matrix["index"])
 
+        df_matrix = pd.DataFrame(**matrix_obj)
         if with_index:
             matrix_index = self.get_input_matrix_startdate(study_id, path, parameters)
             time_column = pd.date_range(
                 start=matrix_index.start_date, periods=len(df_matrix), freq=matrix_index.level.value[0]
             )
             df_matrix.index = time_column
 
-        specific_matrices = get_specific_matrices_according_to_version(int(study.version))
-        for specific_matrix in specific_matrices:
-            if re.match(specific_matrix, path):
+        matrix_profiles = get_matrix_profile_by_version(int(study.version))
+        for pattern, matrix_profile in matrix_profiles.items():
+            if fnmatch.fnmatch(path, pattern):
                 return _handle_specific_matrices(
                     df_matrix,
-                    specific_matrices[specific_matrix],
+                    matrix_profile,
                     path,
                     with_index=with_index,
                     with_header=with_header,
                 )
+
         return df_matrix

antarest/study/storage/utils.py

@@ -239,30 +239,9 @@ def assert_permission(
 
 MATRIX_INPUT_DAYS_COUNT = 365
 
-MONTHS = (
-    "January",
-    "February",
-    "March",
-    "April",
-    "May",
-    "June",
-    "July",
-    "August",
-    "September",
-    "October",
-    "November",
-    "December",
-)
+MONTHS = calendar.month_name[1:]
 
-DAY_NAMES = (
-    "Monday",
-    "Tuesday",
-    "Wednesday",
-    "Thursday",
-    "Friday",
-    "Saturday",
-    "Sunday",
-)
+DAY_NAMES = calendar.day_name[:]
 
 
 def _generate_columns(column_suffix: str) -> t.List[str]:
@@ -378,12 +357,13 @@ class MatrixProfile(t.NamedTuple):
 SPECIFIC_MATRICES_870["input/bindingconstraints/*"] = MatrixProfile(cols=[], rows=[], stats=False)
 
 
-def get_specific_matrices_according_to_version(study_version: int) -> t.Dict[str, MatrixProfile]:
+def get_matrix_profile_by_version(study_version: int) -> t.Dict[str, MatrixProfile]:
     if study_version < 820:
         return SPECIFIC_MATRICES
     elif study_version < 870:
         return SPECIFIC_MATRICES_820
-    return SPECIFIC_MATRICES_870
+    else:
+        return SPECIFIC_MATRICES_870
 
 
 def get_start_date(

antarest/study/web/raw_studies_blueprint.py

@@ -317,7 +317,11 @@ def get_matrix(
     ) -> FileResponse:
         parameters = RequestParameters(user=current_user)
         df_matrix = study_service.get_matrix_with_index_and_header(
-            study_id=uuid, path=matrix_path, with_index=with_index, with_header=with_header, parameters=parameters
+            study_id=uuid,
+            path=matrix_path,
+            with_index=with_index,
+            with_header=with_header,
+            parameters=parameters,
         )
 
         matrix_name = Path(matrix_path).stem

tests/integration/raw_studies_blueprint/test_download_matrices.py

@@ -209,7 +209,11 @@ def test_download_matrices(self, client: TestClient, admin_access_token: str, st
         assert dataframe.index[0] == "2018-01-01 00:00:00"
         dataframe.index = range(len(dataframe))
         transposed_matrix = list(zip(*[8760 * [1.0], 8760 * [1.0], 8760 * [1.0], 8760 * [0.0]]))
-        expected_df = pd.DataFrame(columns=["0", "1", "2", "3"], index=range(8760), data=transposed_matrix)
+        expected_df = pd.DataFrame(
+            columns=["Marginal cost modulation", "Market bid modulation", "Capacity modulation", "Min gen modulation"],
+            index=range(8760),
+            data=transposed_matrix,
+        )
         assert dataframe.equals(expected_df)
 
         # asserts endpoint returns the right columns for output matrix
@@ -281,7 +285,7 @@ def test_download_matrices(self, client: TestClient, admin_access_token: str, st
         )
         assert res.status_code == 404
         assert res.json()["exception"] == "IncorrectPathError"
-        assert res.json()["description"] == "The path filled does not correspond to a matrix : settings/generaldata"
+        assert res.json()["description"] == "The provided path does not point to a valid matrix: 'settings/generaldata'"
 
         # wrong format
         res = client.get(