Create waking_state_plots.py

wind_up/plots/waking_state_plots.py

@@ -0,0 +1,48 @@
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+import pandas as pd
+
+from wind_up.constants import RAW_POWER_COL, RAW_WINDSPEED_COL, SCATTER_ALPHA, SCATTER_S
+from wind_up.models import PlotConfig
+
+mpl.use("Agg")
+
+
+def plot_waking_state_one_ttype_or_wtg(wf_df: pd.DataFrame, ttype_or_wtg: str, plot_cfg: PlotConfig) -> None:
+    waking_df = wf_df[wf_df["waking"]]
+    not_waking_df = wf_df[wf_df["not_waking"]]
+    unknown_df = wf_df[wf_df["unknown_waking"]]
+    plt.figure()
+    plt.scatter(
+        waking_df[RAW_WINDSPEED_COL],
+        waking_df[RAW_POWER_COL],
+        label="waking",
+        s=SCATTER_S,
+        alpha=SCATTER_ALPHA,
+    )
+    plt.scatter(
+        not_waking_df[RAW_WINDSPEED_COL],
+        not_waking_df[RAW_POWER_COL],
+        label="not waking",
+        s=SCATTER_S,
+        alpha=SCATTER_ALPHA,
+    )
+    plt.scatter(
+        unknown_df[RAW_WINDSPEED_COL],
+        unknown_df[RAW_POWER_COL],
+        label="unknown or partial waking",
+        s=SCATTER_S,
+        alpha=SCATTER_ALPHA,
+    )
+    plt.xlabel(f"{RAW_WINDSPEED_COL} [m/s]")
+    plt.ylabel(f"{RAW_POWER_COL} [kW]")
+    plot_title = f"{ttype_or_wtg} power curve by waking state"
+    plt.title(plot_title)
+    plt.grid()
+    plt.legend(loc="lower right")
+    plt.tight_layout()
+    if plot_cfg.show_plots:
+        plt.show()
+    if plot_cfg.save_plots:
+        plt.savefig(plot_cfg.plots_dir / ttype_or_wtg / f"{plot_title}.png")
+    plt.close()