A Matplotlib wrapper with more convenience and pretty plots with a style common in physics papers.
Project description
pyescher 🎨✨
A Python plotting library for elegant and physics-inspired visualizations
📌 Overview
pyescher is a convenient wrapper for Matplotlib, designed to create beautiful, publication-ready plots with minimal effort. It includes built-in styling, marker cycling, and support for mathematical functions.
🚀 Installation
Install pyescher using pip:
pip install pyescher
📜 Quick Example: Bessel and Hankel Functions
The following example demonstrates how to plot Bessel and Hankel functions using pyescher:
import pyescher as pe
from scipy.special import jn, hankel1
import numpy as np
# Define x-values
x = np.linspace(0, 20, 1000)
# Compute function values
y1 = jn(1, x) # Bessel function J1
y2 = hankel1(2, x) # Hankel function H2
# Create Line objects
l1 = pe.Line(x, y1, label='Bessel function of the first kind of order 1')
l2 = pe.Line(x, y2, label='Hankel function of the first kind of order 2')
# Plot using pyescher
pe.plot_lines(l1, l2,
xlabel='x',
ylabel='y',
title='Bessel and Hankel functions',
show_marker=True,
nmarkers=21,
cycle_markers=True,
cycle_linestyle=True,
marker_size=5)
📊 Example Output
🎯 Features
✅ Publication-Ready Styling – Easily generate beautiful plots.
✅ Auto-Cycling Markers & Linestyles – Ensures unique styles per plot.
✅ Convenient Plot Handling – Simplifies function-based plotting.
✅ Customizable Annotations & Legends – Clean, well-labeled visuals.
🔧 API Overview
📈 pe.plot_lines(*lines, **kwargs)
Plot multiple Line objects with various styling options.
Common Parameters:
xlabel,ylabel,title– Axis labels and title.show_marker=True– Adds markers automatically.nmarkers=21– Controls marker placement frequency.cycle_markers=True– Cycles through different marker styles.cycle_linestyle=True– Cycles through different line styles.marker_size=5– Adjusts marker size.
🎨 Why Use pyescher?
📌 Optimized for Scientific & Technical Plots
📌 Saves Time on Styling & Formatting
📌 Produces Aesthetic, Readable Visuals for Papers & Presentations
🛠️ Installation & Development
Clone the repository and install dependencies:
git clone https://github.com/fennisrobert/pyescher.git
cd pyescher
pip install -e .
🤝 Contributing
Contributions are welcome! Feel free to submit an issue or pull request.
🏆 Acknowledgments
Inspired by physics-style plots commonly found in academic papers.
📧 Contact: fennisrobert@gmail.com
📜 License: MIT
🚀 Get started with pyescher and create stunning plots effortlessly! 🎨
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