Add support for POA column in TSV file

solarfarmer/weather.py

@@ -37,6 +37,8 @@
 ==============  ===========
 ``ghi``         ``GHI``
 ``dhi``         ``DHI``
+``poa``         ``POA``
+``gti``         ``POA``
 ``temp_air``    ``TAmb``
 ``wind_speed``  ``WS``
 ``pressure``    ``Pressure``
@@ -164,6 +166,8 @@ def check_sequential_year_timestamps(file_path: str | pathlib.Path) -> None:
 PVLIB_COLUMN_MAP: dict[str, str] = {
     "ghi": "GHI",
     "dhi": "DHI",
+    "poa": "POA",
+    "gti": "POA",
     "temp_air": "TAmb",
     "wind_speed": "WS",
     "pressure": "Pressure",
@@ -267,8 +271,8 @@ def from_pvlib(
     Parameters
     ----------
     df : pandas.DataFrame
-        pvlib-style DataFrame (columns ``ghi``, ``dhi``, ``temp_air``,
-        ``wind_speed``, ``pressure``) with a DatetimeIndex.  pvlib does not
+        pvlib-style DataFrame (columns ``ghi``, ``dhi``, ``poa``/``gti``,
+        ``temp_air``, ``wind_speed``, ``pressure``) with a DatetimeIndex.  pvlib does not
         standardise units across data sources, so check that the units from
         your source match what SolarFarmer expects (see :data:`TSV_COLUMNS`).
         This function applies ``pressure_pa_to_mbar=True``, dividing the
@@ -428,13 +432,6 @@ def shift_period_end_to_beginning(df: pd.DataFrame) -> pd.DataFrame:
             "note": "ISO 8601 with mandatory UTC offset; T separator required; no seconds. Must be the first column.",
             "aliases": ["Date", "DateTime", "Time"],
         },
-        {
-            "name": "GHI",
-            "unit": "W/m²",
-            "range": (0, 1300),
-            "note": "Required unless POA is provided instead.",
-            "aliases": ["GHI", "ghi", "Glob", "SolarTotal"],
-        },
         {
             "name": "TAmb",
             "unit": "°C",
@@ -443,6 +440,20 @@ def shift_period_end_to_beginning(df: pd.DataFrame) -> pd.DataFrame:
         },
     ],
     "optional": [
+        {
+            "name": "GHI",
+            "unit": "W/m²",
+            "range": (0, 1300),
+            "note": "Global horizontal irradiance. Either GHI or POA must be provided.",
+            "aliases": ["GHI", "ghi", "Glob", "SolarTotal"],
+        },
+        {
+            "name": "POA",
+            "unit": "W/m²",
+            "range": (0, 1300),
+            "note": "Plane of array irradiance. Either POA or GHI must be provided.",
+            "aliases": ["POA", "Gpoa", "Plane"],
+        },
         {
             "name": "DHI",
             "unit": "W/m²",

tests/test_weather.py

@@ -166,8 +166,27 @@ def pvlib_df(self):
     def test_columns_renamed(self, tmp_path, pvlib_df):
         out = from_pvlib(pvlib_df, tmp_path / "out.tsv")
         header = out.read_text().splitlines()[0]
-        for sf_col in PVLIB_COLUMN_MAP.values():
-            assert sf_col in header
+        # Only assert SF columns whose source column is actually present in the fixture.
+        for pvlib_col, sf_col in PVLIB_COLUMN_MAP.items():
+            if pvlib_col in pvlib_df.columns:
+                assert sf_col in header
+
+    @pytest.mark.parametrize("poa_col", ["poa", "gti"])
+    def test_poa_column_mapped(self, tmp_path, poa_col):
+        """pvlib 'poa' and 'gti' columns should both map to SolarFarmer 'POA'."""
+        pd = pytest.importorskip("pandas")
+        idx = pd.date_range("2020-01-01", periods=3, freq="h", tz="UTC")
+        df = pd.DataFrame(
+            {
+                poa_col: [0.0, 450.0, 750.0],
+                "temp_air": [5.0, 15.0, 25.0],
+            },
+            index=idx,
+        )
+        out = from_pvlib(df, tmp_path / "out.tsv")
+        header = out.read_text().splitlines()[0].split("\t")
+        assert "POA" in header
+        assert poa_col not in header  # raw pvlib name must be gone
 
     def test_pressure_converted(self, tmp_path, pvlib_df):
         out = from_pvlib(pvlib_df, tmp_path / "out.tsv")