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! 🎨