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Interactive Plot Generator

A Python project for generating high-quality scientific plots with custom data points and labels. This interactive tool allows users to input their own data and customize plot labels through a command-line interface.

Overview

This project creates matplotlib-based visualizations from user-provided data points. The program prompts users for x and y coordinates, axis labels, and a plot title, making it versatile for various data visualization needs.

Features

  • Interactive Input: User-friendly command-line interface for data entry
  • Flexible Plotting: Create plots with any numerical data series
  • Interactive Display: Uses Qt5Agg backend for interactive plot windows
  • High-Quality Output: Saves plots as high-resolution PNG images (300 DPI)
  • Grid Display: Enhanced readability with grid lines
  • Custom Labels: Full control over axis labels and plot title
  • Automatic Saving: Plots are automatically saved to the images/ directory

Prerequisites

  • Python 3.12 or higher
  • A GUI environment (for interactive plotting)
  • Git (for version control)

Dependencies

  • matplotlib >= 3.10.6
  • PyQt5 >= 5.15.11

Installation Guide

Choose one of the following installation methods:

1. Using uv (Recommended)

# Clone the repository
git clone https://github.com/Kneysh/plot-graph.git

# Navigate to project directory
cd plot-graph

# Install dependencies using uv
uv sync

2. Using pip

# Clone the repository
git clone https://github.com/Kneysh/plot-graph.git

# Navigate to project directory
cd plot-graph

# Create and activate virtual environment (recommended)
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install matplotlib>=3.10.6 pyqt5>=5.15.11

Usage Guide

Basic Usage

  1. Ensure you're in the project directory:

    cd plot-graph

  2. Run the script:

    python main.py

  3. The program will:

    • Display an interactive plot window
    • Save the plot as images/plot.png
    • Show a confirmation message

Using the Program

1. Input Format

When running the program, you'll be prompted to enter:

  1. X-axis values: Enter comma-separated numbers (e.g., 1,2,3,4,5)
  2. Y-axis values: Enter comma-separated numbers (e.g., 10,20,30,40,50)
  3. X-axis label: Enter a descriptive label for your x-axis
  4. Y-axis label: Enter a descriptive label for your y-axis
  5. Plot title: Enter the title for your plot

Example input:

Please Enter your data points:
x : 1,2,3,4,5
y : 10,20,30,40,50
Enter label for X axis: Time (seconds)
Enter label for Y axis: Temperature (°C)
Enter the Title of the graph: Temperature vs Time

2. Output

The program will:

  1. Generate an interactive plot window showing your data
  2. Save the plot as a high-resolution PNG file (300 DPI)
  3. Display a confirmation message

The generated plot includes:

  • Data points marked with circular markers
  • Lines connecting the data points
  • A grid for better readability
  • Your custom axis labels and title
  • Automatically scaled axes based on your data

3. Plot Customization

To modify the plot appearance, you can edit the plot function in main.py:

def plot(x:list, y:list, x_label:str, y_label:str, title:str):
    # Modify marker style, color, or size
    plt.plot(x, y, marker='o')  # Try 's' for squares, '^' for triangles

    # Adjust grid style
    plt.grid(True)  # Add alpha=0.5 for transparency

    # Change output settings
    plt.savefig('./images/plot.png', dpi=300, bbox_inches='tight')
```## Contribution Guidelines

We welcome contributions! Here's how you can help improve this project:

### 1. Setting Up Development Environment

```bash
# Fork the repository on GitHub

# Clone your fork
git clone https://github.com/YOUR-USERNAME/plot-graph.git

# Add upstream remote
git remote add upstream https://github.com/Kneysh/plot-graph.git

# Create a new branch
git checkout -b feature/your-feature-name

2. Development Workflow

  1. Code Style

    • Follow PEP 8 guidelines
    • Use meaningful variable names
    • Add comments for complex logic
    • Include docstrings for functions

  2. Testing

    • Test your changes with different data sets
    • Verify plot generation works
    • Check interactive features
    • Ensure proper error handling

  3. Committing Changes

    git add .
git commit -m "Brief description of changes"
git push origin feature/your-feature-name

3. Submitting Pull Requests

  1. Update your fork:

    git fetch upstream
git rebase upstream/main

  2. Create a pull request:

    • Go to GitHub and create a PR from your feature branch
    • Provide a clear description of changes
    • Include screenshots if UI changes were made
    • Reference any related issues

4. Code Review Process

  • All PRs will be reviewed
  • Address any requested changes
  • Maintain clear communication in PR comments
  • Be patient during the review process

Troubleshooting

Common Issues and Solutions

  1. Display Issues

    • Error: "No display name and no $DISPLAY environment variable"
    # Solution: Set matplotlib to use a non-interactive backend
export MPLBACKEND="Agg"

  2. Dependencies

    • Qt5 missing:
    # Ubuntu/Debian
sudo apt-get install python3-qt5

# macOS
brew install pyqt5

  3. Permission Issues

    # Fix images directory permissions
chmod 755 images/

Project Structure

plot-graph/
├── main.py           # Main plotting script with interactive input
├── pyproject.toml    # Project configuration and dependencies
├── README.md        # Documentation
└── images/          # Output directory for generated plots
    └── plot.png     # Your generated plot

License

This project is released under the MIT License. See LICENSE file for details.

Support

  • Create an issue for bug reports
  • Start a discussion for feature requests
  • Check existing issues before reporting

For more information, contact the maintainers or open an issue on GitHub.