plotfair 0.1.0

Features

• PaintKit Color System - Curated color swatches with filtering by saturation (bright, dark, muted) and color family. Includes the Flexoki color scheme.

• Perceptual Colormaps - Create colormaps that are perceptually uniform using CIECAM02 color space, ensuring smooth gradients for data visualization.

• Matplotlib Presets - Publication-ready defaults with enhanced DPI, clean styling, and automatic figure saving to organized folders.

• Plotly Wrapper - Matplotlib-like interface for Plotly via the Plty class.

• Interplot Integration - Pre-configured settings for interplot with matplotlib-style plotting via the Iplt class.

Installation

pip install plotfair

Quick Start

import plotfair as pf
import matplotlib as mpl

# Set a color scheme
scheme = pf.paintkit.filter(tags={'dark'}).ordered_swatches(pf.full_rainbow)
mpl.rcParams['axes.prop_cycle'] = scheme.to_cycler()

# Create a perceptual colormap
colors = [s.hex for s in pf.paintkit.ordered_swatches(['blue', 'pink', 'orange']).colors]
cmap = pf.colormaps.perceptual_colormap_nonuniform(colors, [0.0, 0.5, 1.0])
pf.show_colormap(cmap, name='Custom Colormap')

bright = pf.paintkit.filter(tags={'bright'})
blues = pf.paintkit.filter(tags={'blue'})
flexoki = pf.paintkit.filter(tags={'flexoki'})

# Available: pf.rainbow, pf.full_rainbow, pf.tab10, pf.flexoki
scheme = pf.paintkit.filter(tags={'bright'}).ordered_swatches(pf.tab10)

from plotfair import Plty
import numpy as np

plty = Plty()
x = np.linspace(0, 10, 100)

plty.plot(x, np.sin(x), label='sin(x)')
plty.xlabel('x')
plty.ylabel('y')
plty.show()

Documentation

Full documentation is available at plotfair.readthedocs.io.

Requirements

• Python 3.9+

• matplotlib

• numpy

• colorspacious

• plotly >= 6.5.2

• interplot >= 1.1.1

License

MIT License. See LICENSE for details.

Flexoki color scheme © Stephen Ango, licensed under the MIT License.

Links

• Documentation

• Source Code

• Issue Tracker