training

.gitignore

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+utils/__pycache__/plot_metrics.cpython-310.pyc

utils/plot_metrics.py

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+from typing import List, Tuple
+import matplotlib.pyplot as plt
+from matplotlib.axes import Axes
+import pandas as pd
+
+def plot_metrics(
+        metrics: List[Tuple[pd.Series, pd.Series, str]] | List[List[Tuple[pd.Series, pd.Series, str]]],
+        remove_na: bool = False,
+        subAxes: Axes = None,
+        title: str = None,
+        xlabel: str = None,
+        ylabel: str = None,
+        figsize=(8, 6)):
+    _, axes = plt.subplots(len(metrics), 1, figsize=(
+        figsize[0], figsize[1] * len(metrics))) if subAxes is None else (None, subAxes)
+    for index, metric in enumerate(metrics):
+        ax = (axes[index] if len(metrics) >
+              1 else axes) if subAxes is None else subAxes
+        if type(metric) is tuple:
+            (x, y, legend) = metric[0:3]
+            color = metric[3] if len(metric) > 3 else 'blue'
+            [x, y] = [x, y] if not remove_na else zip(
+                *[[x_1, y_1] for x_1, y_1 in zip(x, y) if pd.notna(y_1)])
+            ax.plot(x, y, color=color, label=legend)
+            ax.legend()
+        else:
+            plot_metrics(metric, remove_na, ax)
+    plt.title(title)
+    plt.xlabel(xlabel)
+    plt.ylabel(ylabel)