dantinox.visualization

The visualization module uses a class-level registry. Charts are registered with @Visualizer.register and auto-discovered at import time. No configuration required to use built-in charts.

---

Visualizer

options:
  show_source: true
  members:
    - register
    - render

---

Base types

options:
  show_source: true

options:
  show_source: true
  members:
    - render
    - _render_mpl
    - _render_plotly

---

Built-in charts

options:
  show_source: true
  heading_level: 3

options:
  show_source: true
  heading_level: 3

options:
  show_source: true
  heading_level: 3

options:
  show_source: true
  heading_level: 3

options:
  show_source: true
  heading_level: 3

options:
  show_source: true
  heading_level: 3

---

Quick reference

import pandas as pd
from dantinox.visualization import Visualizer, RenderConfig

df = pd.read_csv("benchmark_results.csv")

# Render all registered default-constructible charts
Visualizer().render(df, out_dir="plots/")

# Specific charts with custom config
cfg = RenderConfig(backend="matplotlib", fmt="pdf", style="publication", dpi=300)
Visualizer().render(df, charts=["throughput", "pareto"], out_dir="paper_plots/", config=cfg)

# Radar chart (requires explicit instantiation — not auto-rendered)
from dantinox.visualization import RadarChart, Visualizer
radar = RadarChart(metrics=["peak_tps", "perplexity", "prefill_mean_ms"])
Visualizer(extra_charts=[radar]).render(df, charts=["radar"], out_dir="plots/")

Style presets

style	Use case
"publication"	LaTeX-compatible, high-DPI, serif fonts
"dark"	Presentations, dark-mode slides
"minimal"	Lightweight, no gridlines

Chart registry

from dantinox.visualization import Visualizer

# List all registered chart names
print(list(Visualizer._registry.keys()))
# ['training_curve', 'throughput', 'throughput_batch', 'latency', 'pareto', 'radar']