feat(pygal): implement line-loss-training

plots/line-loss-training/implementations/pygal.py

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+""" pyplots.ai
+line-loss-training: Training Loss Curve
+Library: pygal 3.1.0 | Python 3.13.11
+Quality: 91/100 | Created: 2025-12-31
+"""
+
+import numpy as np
+import pygal
+from pygal.style import Style
+
+
+# Data: Simulated training loss curves showing typical overfitting behavior
+np.random.seed(42)
+epochs = np.arange(1, 51)
+
+# Training loss: Steadily decreasing with some noise
+train_loss = 2.5 * np.exp(-0.08 * epochs) + 0.1 + np.random.normal(0, 0.02, len(epochs))
+
+# Validation loss: Decreases then increases (overfitting after epoch ~30)
+val_loss = 2.3 * np.exp(-0.07 * epochs) + 0.15 + 0.003 * np.maximum(0, epochs - 25) ** 1.5
+val_loss += np.random.normal(0, 0.03, len(epochs))
+
+# Find minimum validation loss epoch for annotation
+min_val_epoch = int(epochs[np.argmin(val_loss)])
+min_val_loss = float(np.min(val_loss))
+
+# Custom style for large canvas
+custom_style = Style(
+    background="white",
+    plot_background="white",
+    foreground="#333333",
+    foreground_strong="#333333",
+    foreground_subtle="#666666",
+    colors=("#306998", "#FFD43B"),  # Python Blue, Python Yellow
+    title_font_size=48,
+    label_font_size=36,
+    major_label_font_size=32,
+    legend_font_size=32,
+    value_font_size=28,
+    stroke_width=4,
+    opacity=0.9,
+    opacity_hover=1.0,
+)
+
+# Create line chart
+chart = pygal.Line(
+    width=4800,
+    height=2700,
+    style=custom_style,
+    title="line-loss-training · pygal · pyplots.ai",
+    x_title="Epoch",
+    y_title="Cross-Entropy Loss",
+    show_x_guides=False,
+    show_y_guides=True,
+    dots_size=6,
+    stroke_style={"width": 4},
+    legend_at_bottom=False,
+    legend_box_size=24,
+    margin=50,
+    x_label_rotation=0,
+    truncate_label=-1,
+    show_dots=True,
+)
+
+# Set x-axis labels (show every 5th epoch for readability)
+chart.x_labels = [str(e) if e % 5 == 0 else "" for e in epochs]
+
+# Add training and validation loss data
+chart.add("Training Loss", list(train_loss))
+chart.add("Validation Loss", list(val_loss))
+
+# Save as PNG and HTML
+chart.render_to_png("plot.png")
+chart.render_to_file("plot.html")

plots/line-loss-training/metadata/pygal.yaml

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+library: pygal
+specification_id: line-loss-training
+created: '2025-12-31T00:13:54Z'
+updated: '2025-12-31T00:17:57Z'
+generated_by: claude-opus-4-5-20251101
+workflow_run: 20608711859
+issue: 2860
+python_version: 3.13.11
+library_version: 3.1.0
+preview_url: https://storage.googleapis.com/pyplots-images/plots/line-loss-training/pygal/plot.png
+preview_thumb: https://storage.googleapis.com/pyplots-images/plots/line-loss-training/pygal/plot_thumb.png
+preview_html: https://storage.googleapis.com/pyplots-images/plots/line-loss-training/pygal/plot.html
+quality_score: 91
+review:
+  strengths:
+  - Excellent demonstration of overfitting pattern with training loss continuing to
+    decrease while validation loss increases after epoch ~25
+  - Clean, readable code following KISS principles with proper random seed
+  - 'Appropriate use of Python brand colors (blue #306998, yellow #FFD43B) for visual
+    distinction'
+  - Good font sizing and spacing for 4800x2700 canvas with customized Style
+  - Y-axis label specifies Cross-Entropy Loss as recommended in specification
+  weaknesses:
+  - Legend positioned outside plot area in top-left corner appears slightly disconnected
+    from the chart
+  - 'Optional feature from spec not implemented: marking the epoch with minimum validation
+    loss (optimal stopping point)'
+  - Grid only shows horizontal lines; vertical guides disabled which reduces readability
+    for epoch identification