support for enphase and no inverter

Author: aryanbhosale

tests/data/test_make_pv_data.py

@@ -1,4 +1,5 @@
 import pandas as pd
+import numpy as np
 import xarray as xr
 import pytest
 from unittest.mock import patch
@@ -19,7 +20,7 @@ def mock_enphase_data(*args, **kwargs):
     (PVSite(latitude=40.7128, longitude=-74.0059, capacity_kwp=8.5, inverter_type='enphase'), mock_enphase_data()),
 ])
 @patch('quartz_solar_forecast.inverters.enphase.get_enphase_data', side_effect=mock_enphase_data)
-def test_make_pv_data(mock_get_enphase, site, expected_data, ts=pd.Timestamp('2023-06-14 12:15:00')):
+def test_make_pv_data_enphase(mock_get_enphase, site, expected_data, ts=pd.Timestamp('2023-06-14 12:15:00')):
     from quartz_solar_forecast.data import make_pv_data
     result = make_pv_data(site, ts)
     expected = expected_data[expected_data['timestamp'] <= ts]
@@ -38,30 +39,25 @@ def test_make_pv_data(mock_get_enphase, site, expected_data, ts=pd.Timestamp('20
     ).to_dataset(name='generation_kw')
 
     assert result.equals(expected_xr)
-
+    
 @pytest.mark.parametrize("site, expected_data", [
-    (PVSite(latitude=40.7128, longitude=-74.0059, capacity_kwp=8.5, inverter_type='enphase'), pd.DataFrame({'timestamp': [], 'power_kw': []})),
+    (PVSite(latitude=40.7128, longitude=-74.0059, capacity_kwp=8.5, inverter_type='unknown'), np.array([[np.nan]])),
 ])
-@patch('quartz_solar_forecast.inverters.enphase.get_enphase_data', return_value=pd.DataFrame({'timestamp': [], 'power_kw': []}))
-def test_make_pv_data_empty_data(mock_get_enphase, site, expected_data, ts=pd.Timestamp('2023-06-14 12:15:00')):
+def test_make_pv_data_no_live(site, expected_data, ts=pd.Timestamp('2023-06-14 12:15:00')):
     from quartz_solar_forecast.data import make_pv_data
     result = make_pv_data(site, ts)
-    if not expected_data.empty:
-        expected = expected_data[expected_data['timestamp'] <= ts]
-    else:
-        expected = expected_data
     expected_xr = xr.DataArray(
-        data=expected['power_kw'].values.reshape(1, -1),
+        data=expected_data,
         dims=['pv_id', 'timestamp'],
         coords={
             'longitude': (['pv_id'], [site.longitude]),
             'latitude': (['pv_id'], [site.latitude]),
-            'timestamp': (['timestamp'], expected['timestamp'].values.astype('datetime64[ns]')),
+            'timestamp': (['timestamp'], [ts]),
             'pv_id': [1],
             'kwp': (['pv_id'], [site.capacity_kwp]),
             'tilt': (["pv_id"], [site.tilt]),
             'orientation': (["pv_id"], [site.orientation]),
         }
     ).to_dataset(name='generation_kw')
 
-    assert result.equals(expected_xr)
+    assert result.equals(expected_xr)