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Common Chart Features Guide

hachimiku is designed with a "consistent-by-default" philosophy. Most parameters related to styling, layout, and formatting are shared across all chart types (Bar, Line, CDF, etc.). This guide explains these common features.

Table of Contents

Color Management

All charts support the color_preset parameter. The default is academic_vivid, which uses high-contrast colors suitable for academic publications.

Preset Description
academic_vivid (Default) Professional sequence (Green, Blue, Red, Orange, etc.) with high contrast.
opt_warm Optimized warm tones (Red, Orange, Yellow).
opt_cool Optimized cool tones (Blue, Cyan, Purple).

Example: academic_vivid vs opt_warm

Academic Vivid Opt Warm

Legend Placement

By default, hachimiku places legends outside the plot area (usually at the top) to maximize the data visualization space.

  • legend_outside: Set to True (default) or False.
  • legend_loc: Standard Matplotlib locations (e.g., 'upper left').
  • legend_ncol: Number of columns in the legend.

Example: Outside vs Inside

Legend Outside Legend Inside

Spine and Border Styles

You can control the visibility and style of the top and right "spines" (borders) using top_right_spine_style.

  • top_right_spine_style: 'solid' (default, gray) or 'none' (clean look).
  • spine_linewidth: Controls the thickness of all axes.

Example: Standard vs Clean Spines

Standard Spines Clean Spines

Padding and Positioning

Academic figures often require precise control over the placement of titles and labels.

  • title_y: Vertical position of the title (e.g., -0.2 for below the X-axis).
  • xlabel_pad, ylabel_pad: Space between labels and axes.
  • tick_pad: Space between tick labels and the axis line.

Example: Custom Padding and Title Position

Custom Padding

Grid and Ticks

  • grid, grid_x, grid_y: Toggle grid visibility.
  • grid_style: A dictionary of Matplotlib grid properties (e.g., {'linestyle': '--', 'alpha': 0.5}).
  • tick_direction: 'in' (default) or 'out'.

Example: Custom Grid Style

Custom Grid

Dynamic Font Scaling

One of hachimiku's most powerful features is automatic font scaling. It calculates the optimal font size based on:

  1. The figsize of the figure.
  2. The number of subplots (if using LayoutManager).

This ensures that your labels are always readable, whether you are generating a small single-column figure or a large full-page mosaic. You can still override these using label_fontsize, tick_fontsize, etc.

Examples

See examples/common_features_gallery.py for the code used to generate the demonstrations in this guide.