break-axes 0.5.0

A Matplotlib-based utility module for creating broken axes.

中文版本

break_axes: Matplotlib Axis Break and Custom Scaling Tool

A Python-based Matplotlib extension module for implementing axis breaks (visual gaps) and multi-interval custom scaling functions, suitable for displaying data with large value ranges or irrelevant intermediate intervals.

Module Overview

Matplotlib natively does not support axis breaks (visual gaps) and flexible multi-interval scaling. This module fills this gap with a series of easy-to-use functions, including:

• Drawing break markers on axis edges to indicate data gaps
• Clipping axis spines, lines, and plot elements to hide unwanted intervals
• Supporting linear/logarithmic custom scaling for multiple data intervals

Installation

1. Install from PyPI

   pip install break_axes
   

2. Build the binary distribution package (wheel) locally
   First install the build tool: pip install build, then run:

   python -m build
   

   This generates a .whl binary package in the dist/ directory (faster installation).

3. Install the package locally (development mode)
   Use this for development and real-time debugging, allowing code changes without reinstalling:

   pip install -e .
   

Core Functions

The functions are usually used are below:

• scale_axes
• broken_and_clip_axes
• remove_minor_ticks

However, for more flexible break settings, you may need to read the source code (less than 900 lines, about half of which are docstrings).

Function Name	Description
create_scale	Used to generate a ScaleBase object for scaled axes
scale_axis	A wrapper function for create_scale, used to directly apply scaling
scale_axes	Used to apply axis scaling in batches, supporting simultaneous scaling of x-axis and y-axis
offset_data_point	Get the vertex coordinates of the break identifier corresponding to the specified break point
get_broken_points	Get the vertex coordinates of the marker end points
xy2points	Combine input x, y coordinates into data point coordinates
add_broken_line	Add break markers at specified positions
add_broken_line_in_axis	Add break markers on the axis
get_axis_clip_path	Get the clipping path of the specified axis for clipping axis spines
get_axes_clip_path	Get the clipping path of the axes for clipping artists within the axes
clip_axes	Clip spines and artists
broken_and_clip_axes	Wrapper for add_broken_line_in_axis and clip_axes
remove_minor_ticks	Remove minor ticks from the given axis
remove_xaxis_minor_ticks	Remove minor ticks from the x-axis
remove_yaxis_minor_ticks	Remove minor ticks from the y-axis

Dependencies

• Python 3.8 or higher
• Matplotlib 3.5.0 or higher
  Installation command: pip install matplotlib

Quick Start

1. Import the Module

import matplotlib.pyplot as plt

from break_axes import __version__, scale_axes, broken_and_clip_axes

plt.rcParams['figure.figsize'] = (3,3)
plt.rcParams['figure.dpi'] = 200
plt.rcParams['axes.linewidth'] = 1.5

print(f"break_axes version: {__version__}")

2. Multiple Axis Breaks

fig, ax = plt.subplots(figsize=(4.5,3))
ax.set(xlim=(-32,32), ylim=(0,180), xlabel="x (unit)", ylabel="y (unit)")
ax.set_facecolor("#DDFFAA")
ax.grid(ls=':', lw=0.5, color='dimgray')

# scale x-axis and y-axis to reduce the blank space
scale_axes(ax,
           x_interval=[(-28, -2, 0.01), (2, 28, 0.01)],
           y_interval=[(40,100, 0.1), (100, 180, 0.6)],
           mode="linear")


_ = ax.set_xticks([-31,-30,-29,-1,0,1,29,30,31])
_ = ax.set_yticks([0,20, 40, 100, 120, 140,160])

rects = ax.bar([-31,-30,-29,-1,0,1,31,30,29], [20,40,22,132,155,108,5,27,17] )
ax.bar_label(rects)

# Text and Annotation wont be clipped
ax.annotate("This is a very long long string.", xy=(-30, 80), xytext=(-30, 168),
    arrowprops=dict(
        arrowstyle='-|>',
        connectionstyle="arc3,rad=0.1",
        color='k',
        shrinkA=5, shrinkB=5
    )
)

# Add broken line in x-axis and y-axis, clip spines and artists in axes
broken_and_clip_axes(ax, x=[-15,15], y=[70], axes_clip=True, which='lower',
                     gap=5, dx=3, dy=3)

# plt.savefig("break_axes_bar.png", transparent=False)

3. Logarithmic Axes

import numpy as np

x = np.logspace(0, 16, 100, base=2)

fig, ax = plt.subplots(figsize=(4,3))
ax.set(xlim=(1, 2<<16), ylim=(1, 2<<16), facecolor="#DDFFAA")
ax.plot(x, x)
ax.set_xticks([ 2<<i for i in range(0,17,3)])
# ax.set_yticks([1, 10, 100, 500, 5000, 10000],
#               [1, 10, 100, 500, 5000, r'$10^4$'])  # type: ignore

ax.annotate("This is a very long long string.",
    xy=(5, 10), xytext=(10, 20000),
    arrowprops=dict(
        arrowstyle='-|>',
        connectionstyle="arc3,rad=0.1",
        color='k',
        shrinkA=5, shrinkB=5
    )
)

ax.grid(ls=':')
ax.set_xlabel("X Label")
ax.set_ylabel("Y Label")
ax.set_title("Broken Axis Example - Log Mode")

scale_axes(ax,
    x_interval=[(3, 6, 0.5)],
    y_interval=[(9, 12, 0.5)],
    mode='log', base_x=2, base_y=2)
broken_and_clip_axes(ax, x=[23], y=[1450],
    axes_clip=True, which='lower', gap=5, dx=3, dy=3)

plt.show()

4. Remove Minor Ticks

Minor Ticks in scaled interval maybe too dense because of the small scale factor, use remove_minor_ticks to remove minor ticks in the given axis.

import matplotlib.pyplot as plt
import numpy as np

from break_axes import broken_and_clip_axes, scale_axes
from break_axes.break_axes import remove_yaxis_minor_ticks

plt.rcParams["ytick.minor.visible"] = True
plt.rcParams["xtick.minor.visible"] = True
plt.rcParams["xtick.top"] = True
plt.rcParams["ytick.right"] = True


x = np.linspace(0, np.pi, 25)
y1 = 0.15 * np.sin(x) + 0.97
y2 = -0.06 * np.sin(x)

fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(6, 2.4), sharey=True)
for ax in (ax1, ax2):
    ax.set_xlim(-0.1, np.pi + 0.1)
    ax.plot(x, y1, marker="o", mew=1, mec="dimgray")
    ax.plot(x, y2, marker="s", mew=1, mec="dimgray")

    ax.set_yticks([-0.05, 0, 0.95, 1, 1.05, 1.1])
    scale_axes(ax, y_interval=[(0.02, 0.95, 0.05)])

    ax.set_yticks([-0.05, 0, 0.95, 1, 1.05, 1.1])

    broken_and_clip_axes(ax, y=[0.5])

# must be put below set_yticks or set_xticks
remove_yaxis_minor_ticks(ax2, intervals=[(0.02, 0.95)])

plt.show()

5. Set Broken Lines Property

import numpy as np

x = np.logspace(-2, 4, 150)

fig, ax = plt.subplots(figsize=(4,3))
ax.set(xlim=(1,10000), ylim=(1,10000), facecolor="#DDFFAA")
ax.plot(x, x)
ax.set_xticks([0.01, 0.1, 1, 10, 100, 500, 5000, 10000])
ax.set_yticks([0.01, 0.1, 1, 10, 100, 500, 5000, 10000])

ax.annotate("This is a very long long string.",
    xy=(5, 10), xytext=(10, 5000),
    arrowprops=dict(
        arrowstyle='-|>',
        connectionstyle="arc3,rad=0.1",
        color='k',
        shrinkA=5, shrinkB=5
    )
)

ax.grid(ls=':')
ax.set_xlabel("X Label")
ax.set_ylabel("Y Label")
ax.set_title("Set Broken Lines Propertye", pad=10)

scale_axes(ax,
    x_interval=[(2, 3, 0.5)],
    y_interval=[(-1, 0, 0.5)],
    mode='log')
broken_lines = broken_and_clip_axes(ax, x=[300], y=[0.3],
    axes_clip=True, which='both', gap=6, dx=4, dy=4)

bottom_left, bottom_right = broken_lines["bottom"][0]
bottom_left.set(color='r', linewidth=1)
bottom_right.set(color='g', linewidth=1)

left_bottom, left_top = broken_lines["left"][0]
left_bottom.set(color='r', linewidth=2.5)
left_top.set(color='g', linewidth=2.5)

plt.show()

6. Not Clip Line

Code to see the example: heat_capacity_of_ice_and_water.ipynb

Notes

1. Fix axis ranges first: Before calling the break/clip functions, you must fix the axis ranges using ax.set_xlim() or ax.set_ylim() — this is crucial to ensure accurate calculation of break positions.
2. Interval rules: When using scale_axes, intervals must be non-overlapping and in order (e.g., [(0,2,2), (5,10,1)] is valid, [(5,10,1), (0,2,2)] is invalid).
3. Clipping exclusions: Text elements (such as labels, tick values) and the axis background (ax.patch) will not be clipped to avoid affecting readability. Users can also use get_axes_clip_path to obtain the axis clipping path and manually add artists that need to be clipped with reference to the clip_axes function.

Version and Author

• Version: 0.5.0
• Author: Wu Yao [e-mail]