vennfan 0.0.6

VennFan

VennFan

Overview

We introduce VennFan, a method for generating n-set Venn diagrams based on the polar coordinate projection of trigonometric boundaries, resulting in Venn diagrams that resemble a set of fan blades.

This module provides a function for creating VennFan Matplotlib figures for up to nine classes.

Sine	Cosine

Installation

pip install vennfan

Usage

Basic Usage

import numpy as np
import matplotlib.pyplot as plt

from vennfan import vennfan

# Fill a 4D 2x2x2x2x2x2 array with random values
rand6 = np.random.randint(0, 1000, size=(2, 2, 2, 2, 2, 2))
    
# Set the value at A∩B∩C to 42
rand6[1,1,1,0,0,0] = 42

# Create the Venn-diagram
fig = vennfan(rand6, ["A", "B", "C", "D", "E", "F"])

# Save the figure
fig.savefig("rand6_demo.png", dpi=100, bbox_inches="tight")
plt.close(fig)

Optional Parameters

Core data

Parameter	Default	Description
title	None	Optional figure title (str). If None, no title is added.
outfile	None	Optional output path(s). If a str or a list of str-s, the figure is saved and the function returns None. If None, the function returns the Matplotlib Figure.

Geometry / boundary curves

Parameter	Default	Description
curve_mode	"cosine"	Boundary curve family: "cosine" or "sine".
decay	"linear"	Amplitude decay mode: "linear" or "exponential".
p	None	Curve parameter. If None, a per-N default is loaded from package defaults.
epsilon	None	Curve parameter. If None, a per-N default is loaded from package defaults.
delta	None	Curve parameter. If None, a per-N default is loaded from package defaults.
b	None	Curve parameter. If None, a per-N default is loaded from package defaults.

Colors

Parameter	Default	Description
colors	None	Per-class fill colors. If shorter than N, repeated cyclically. If None, uses the library default palette.
outline_colors	None	Per-class outline colors for boundary curves and class labels. If shorter than N, repeated cyclically. If None, uses the library default outline palette.
color_mixing	"average"	How to mix class colors into region colors. One of "average", "subtractive", "hue_average", "alpha_stack", or a callable f(colors_for_key, present) -> rgb.
text_color	None	If set, overrides region label text color everywhere. If None, text color is chosen automatically per region based on fill color.

Highlight

Parameter	Default	Description
highlight_factor	None	Enables a radial “halo” inside each region when set to a float in [0, 1]. None disables highlight. Higher values push colors more toward highlight_color.
highlight_color	"#FFFFFF"	Target color used for the highlight blend (only used when highlight_factor is not None).
highlight_gamma	0.5	Exponent controlling the gradient transition speed of the highlight (gamma on normalized interior-distance profile).

Font sizes / text fitting

Parameter	Default	Description
region_fontsize	None	Base font size for region labels. If None, uses a per-N default from package defaults.
class_label_fontsize	None	Font size for class labels around the outside. If None, uses a per-N default from package defaults.
complement_fontsize	None	Font size for the complement (all-zeros) label. If None, defaults to region_fontsize after defaults are resolved.
shrink_region_text	True	If True, region labels shrink-to-fit within their region masks. If False, base font sizes are used as-is.

Layout / resolution

Parameter	Default	Description
dpi	None	Figure DPI. If None, defaults to 100 * N.
linewidth	None	Boundary curve linewidth. If None, uses a per-N default. Also affects erosion radius used for shrink-to-fit.
disc_points_per_class	200	Grid resolution control for region masks. Higher values refine boundaries and can reduce over-aggressive shrink-to-fit in small regions, at the cost of runtime/memory.

Region label placement

Parameter	Default	Description
region_label_placement	"visual_text_center"	Label placement mode: "visual_text_center" (erosion-based interior anchor), "visual_center" (visual center), "radial" (along radial angle), or "hybrid" (per-region choice).

"visual_text_center"	"visual_center"	"radial"	"hybrid"

How to Cite

@misc{csanády2026newperspectivedrawingvenn,
      title={A New Perspective on Drawing Venn Diagrams for Data Visualization}, 
      author={Bálint Csanády},
      year={2026},
      eprint={2601.06980},
      archivePrefix={arXiv},
      primaryClass={cs.GR},
      url={https://arxiv.org/abs/2601.06980}, 
}

License

This project is licensed under the MIT License (c) 2025 Bálint Csanády, aielte-research. See the LICENSE file for details.