Add completed lec3 examples

plots.py

@@ -0,0 +1,54 @@
+from typing import Dict, List, Optional, Tuple
+
+import numpy as np
+import statsmodels.api as sm
+from matplotlib.axes import Axes
+from mlxtend.plotting import plot_decision_regions
+from pandas import DataFrame, Series
+from statsmodels.discrete.discrete_model import BinaryResultsWrapper
+
+
+def create_decision_plot(
+    X: DataFrame,
+    y: Series,
+    model: BinaryResultsWrapper,
+    feature_index: List[str],
+    feature_names: List[str],
+    highlight_index: int,
+    filter: Dict[str, Tuple[int, int]],
+    ax: Optional[Axes] = None,
+) -> Axes:
+    def _get_from_filter(is_value=True) -> Dict[int, int]:
+        filler = dict(
+            (columns.index(k) + 1, filter[k][0 if is_value else 1])
+            for k in filter.keys()
+            if k not in feature_index
+        )
+        constant = {0: 1}
+        return {**constant, **filler}
+
+    if feature_names is None:
+        feature_names = feature_index
+    columns = X.columns.to_list()
+    filler_values = _get_from_filter()
+    filler_ranges = _get_from_filter(False)
+    x_highlight = np.reshape(
+        np.concatenate(([1], X.iloc[highlight_index].to_numpy())),
+        (1, len(columns) + 1),
+    )
+    ax = plot_decision_regions(
+        sm.add_constant(X).to_numpy(),  # type: ignore
+        y.to_numpy(),
+        clf=model,
+        feature_index=[columns.index(k) + 1 for k in feature_index],
+        X_highlight=x_highlight,
+        filler_feature_values=filler_values,
+        filler_feature_ranges=filler_ranges,
+        scatter_kwargs={"s": 48, "edgecolor": None, "alpha": 0.7},
+        contourf_kwargs={"alpha": 0.2},
+        legend=2,
+        ax=ax,
+    )
+    ax.set_xlabel(feature_names[0])
+    ax.set_ylabel(feature_names[1])
+    return ax