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| import numpy as np | |
| import pandas as pd | |
| from matplotlib import pyplot as plt | |
| plt.ioff() | |
| plt.rcParams["font.family"] = [ | |
| "IBM Plex Mono", | |
| # Fallback fonts: | |
| "DejaVu Sans Mono", | |
| "Courier New", | |
| "monospace", | |
| ] | |
| from data import generate_data | |
| def plot_pareto_curve(df: pd.DataFrame, maxsize: int): | |
| fig, ax = plt.subplots(figsize=(6, 6), dpi=100) | |
| if len(df) == 0 or "Equation" not in df.columns: | |
| return fig | |
| ax.loglog( | |
| df["Complexity"], | |
| df["Loss"], | |
| marker="o", | |
| linestyle="-", | |
| color="#333f48", | |
| linewidth=1.5, | |
| markersize=6, | |
| ) | |
| ax.set_xlim(0.5, maxsize + 1) | |
| ytop = 2 ** (np.ceil(np.log2(df["Loss"].max()))) | |
| ybottom = 2 ** (np.floor(np.log2(df["Loss"].min() + 1e-20))) | |
| ax.set_ylim(ybottom, ytop) | |
| stylize_axis(ax) | |
| ax.set_xlabel("Complexity") | |
| ax.set_ylabel("Loss") | |
| fig.tight_layout(pad=2) | |
| return fig | |
| def plot_example_data(test_equation, num_points, noise_level, data_seed): | |
| fig, ax = plt.subplots(figsize=(6, 6), dpi=100) | |
| X, y = generate_data(test_equation, num_points, noise_level, data_seed) | |
| x = X["x"] | |
| ax.scatter(x, y, alpha=0.7, edgecolors="w", s=50) | |
| stylize_axis(ax) | |
| ax.set_xlabel("x") | |
| ax.set_ylabel("y") | |
| fig.tight_layout(pad=2) | |
| return fig | |
| def stylize_axis(ax): | |
| ax.grid(True, which="both", ls="--", linewidth=0.5, color="gray", alpha=0.5) | |
| ax.spines["top"].set_visible(False) | |
| ax.spines["right"].set_visible(False) | |
| # Range-frame the plot | |
| for direction in ["bottom", "left"]: | |
| ax.spines[direction].set_position(("outward", 10)) | |
| # Delete far ticks | |
| ax.tick_params(axis="both", which="major", labelsize=10, direction="out", length=5) | |
| ax.tick_params(axis="both", which="minor", labelsize=8, direction="out", length=3) | |