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import matplotlib | |
matplotlib.use("agg") | |
import numpy as np | |
import pandas as pd | |
from matplotlib import pyplot as plt | |
plt.ioff() | |
plt.rcParams["font.family"] = "monospace" | |
# 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 plot_predictions(y, ypred): | |
fig, ax = plt.subplots(figsize=(6, 6), dpi=100) | |
ax.scatter(y, ypred, alpha=0.7, edgecolors="w", s=50) | |
stylize_axis(ax) | |
ax.set_xlabel("true") | |
ax.set_ylabel("prediction") | |
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) | |