Create test_detrend.py

tests/test_detrend.py

@@ -0,0 +1,104 @@
+from pathlib import Path
+
+import pandas as pd
+import pytest
+from pandas.testing import assert_frame_equal
+
+from wind_up.detrend import apply_wsratio_v_wd_scen, calc_wsratio_v_wd_scen, check_applied_detrend
+from wind_up.models import WindUpConfig
+from wind_up.smart_data import add_smart_lat_long_to_cfg
+
+
+def test_apply_wsratio_v_wd_scen_pre() -> None:
+    expected_df = pd.read_parquet(Path(__file__).parents[0] / "test_data/LSA_T13_LSA_T12_pre_df.parquet")
+    pre_df = expected_df.drop(columns=["ws_rom", "ref_ws_detrended"])
+    wsratio_v_dir_scen = pd.read_parquet(
+        Path(__file__).parents[0] / "test_data/LSA_T13_LSA_T12_wsratio_v_dir_scen.parquet",
+    )
+    ref_ws_col = "ref_ws_est_blend"
+    ref_wd_col = "ref_YawAngleMean"
+    actual_df = apply_wsratio_v_wd_scen(pre_df, wsratio_v_dir_scen, ref_ws_col=ref_ws_col, ref_wd_col=ref_wd_col)
+    assert_frame_equal(actual_df, expected_df)
+
+
+def test_apply_wsratio_v_wd_scen_post() -> None:
+    expected_df = pd.read_parquet(Path(__file__).parents[0] / "test_data/LSA_T13_LSA_T12_post_df.parquet")
+    post_df = expected_df.drop(columns=["ws_rom", "ref_ws_detrended"])
+    wsratio_v_dir_scen = pd.read_parquet(
+        Path(__file__).parents[0] / "test_data/LSA_T13_LSA_T12_wsratio_v_dir_scen.parquet",
+    )
+    ref_ws_col = "ref_ws_est_blend"
+    ref_wd_col = "ref_YawAngleMean"
+    actual_df = apply_wsratio_v_wd_scen(post_df, wsratio_v_dir_scen, ref_ws_col=ref_ws_col, ref_wd_col=ref_wd_col)
+    assert_frame_equal(actual_df, expected_df)
+
+
+def test_check_applied_detrend(test_lsa_t13_config: WindUpConfig) -> None:
+    cfg = test_lsa_t13_config
+    pre_df = pd.read_parquet(Path(__file__).parents[0] / "test_data/LSA_T13_LSA_T12_pre_df.parquet")
+    post_df = pd.read_parquet(Path(__file__).parents[0] / "test_data/LSA_T13_LSA_T12_post_df.parquet")
+    test_name = "LSA_T13"
+    ref_name = "LSA_T12"
+    ref_wtg = next(x for x in cfg.asset.wtgs if x.name == ref_name)
+    ref_lat = ref_wtg.latitude
+    ref_long = ref_wtg.longitude
+    test_ws_col = "test_ws_est_blend"
+    ref_ws_col = "ref_ws_est_blend"
+    ref_wd_col = "ref_YawAngleMean"
+    detrend_ws_col = "ref_ws_detrended"
+
+    detrend_pre_r2_improvement, detrend_post_r2_improvement = check_applied_detrend(
+        test_name=test_name,
+        ref_name=ref_name,
+        ref_lat=ref_lat,
+        ref_long=ref_long,
+        pre_df=pre_df,
+        post_df=post_df,
+        test_ws_col=test_ws_col,
+        ref_ws_col=ref_ws_col,
+        detrend_ws_col=detrend_ws_col,
+        ref_wd_col=ref_wd_col,
+        cfg=cfg,
+        plot_cfg=None,
+    )
+
+    assert detrend_pre_r2_improvement == pytest.approx(0.03464757681986863)
+    assert detrend_post_r2_improvement == pytest.approx(0.03776561982402227)
+
+
+def test_calc_wsratio_v_wd_scen(test_lsa_t13_config: WindUpConfig) -> None:
+    # this test case borrows logic and results from check_applied_detrend where data which has already been detrended
+    # is used to calculate the wsratio_v_wd_scen again to check it is flat
+    cfg = test_lsa_t13_config
+    md_df = pd.read_csv(Path(__file__).parents[0] / "test_data/smart_data/Lisa Wind Farm/Lisa Wind Farm_md.csv")
+    cfg = add_smart_lat_long_to_cfg(md=md_df, cfg=cfg)
+    pre_df = pd.read_parquet(Path(__file__).parents[0] / "test_data/LSA_T13_LSA_T12_pre_df.parquet")
+    test_name = "LSA_T13"
+    ref_name = "LSA_T12"
+    ref_wtg = next(x for x in cfg.asset.wtgs if x.name == ref_name)
+    ref_lat = ref_wtg.latitude
+    ref_long = ref_wtg.longitude
+    test_ws_col = "test_ws_est_blend"
+    ref_wd_col = "ref_YawAngleMean"
+    detrend_ws_col = "ref_ws_detrended"
+
+    expected_pre_df = pd.read_parquet(
+        Path(__file__).parents[0] / "test_data/LSA_T13_LSA_T12_check_pre_wsratio_v_dir_scen.parquet",
+    )
+    actual_pre_df = calc_wsratio_v_wd_scen(
+        test_name=test_name,
+        ref_name=ref_name,
+        ref_lat=ref_lat,
+        ref_long=ref_long,
+        detrend_df=pre_df,
+        test_ws_col=test_ws_col,
+        ref_ws_col=detrend_ws_col,  # different intentionally
+        ref_wd_col=ref_wd_col,
+        cfg=cfg,
+        plot_cfg=None,
+    )
+
+    # on Github Actions get error DataFrame.iloc[:, 0] (column name="hours") values are different (0.13889 %)
+    # At positional index 50, first diff: 45.5 != 45.666666666666664
+    # therefore set rtol=5e-3 so the test passes on Github Actions
+    assert_frame_equal(actual_pre_df, expected_pre_df, rtol=5e-3)