# gnuplot-style
[](https://badge.fury.io/py/gnuplot-style)
[](https://pypi.org/project/gnuplot-style/)
[](https://opensource.org/licenses/MIT)
[](https://github.com/psf/black)
A Python package that provides gnuplot-style aesthetics for matplotlib plots.
## Features
- Easy-to-use API for applying gnuplot styles to matplotlib
- Support for gnuplot's default colors, line styles, markers, and patterns
- Modular design allowing selective application of styles
- Compatible with matplotlib's style system
- Includes pattern fills for histograms and bar charts
## Installation
```bash
pip install gnuplot-style
```
## Quick Start
```python
import matplotlib.pyplot as plt
import numpy as np
import gnuplot_style as gp
# Apply gnuplot aesthetics BEFORE creating figures
gp.use() # Default: colors only
# Create your plots as usual
x = np.linspace(0, 2*np.pi, 100)
for i in range(4):
plt.plot(x, np.sin(x + i*0.5), label=f'Series {i+1}')
plt.legend()
plt.show()
```
### Note on Axes Created Before Style Application
If you create axes before calling `gp.use()`, you need to explicitly apply the style:
```python
# If axes already exist
fig, ax = plt.subplots()
# Apply style
gp.use('cl')
# Apply the prop_cycle to existing axes
ax.set_prop_cycle(plt.rcParams['axes.prop_cycle'])
# Now plot with the new style
ax.plot(x, y)
```
## Style Options
The package provides several style combinations:
```python
# Individual components
gp.use('color') # or 'c' - Just colors (default)
gp.use('line') # or 'l' - Just line styles
gp.use('marker') # or 'm' - Just markers
# Combinations
gp.use('color+line') # or 'cl' - Colors + line styles
gp.use('color+marker') # or 'cm' - Colors + markers
gp.use('all') # or 'clm' - Everything combined
```
### Convenience Functions
```python
gp.colors() # Apply colors only
gp.lines() # Apply line styles only
gp.markers() # Apply markers only
gp.colors_lines() # Apply colors + lines
gp.colors_markers() # Apply colors + markers
gp.all() # Apply all styles
```
## Pattern Fills
Apply gnuplot-style patterns to bar charts:
```python
# Create a bar chart
bars = plt.bar(['A', 'B', 'C'], [1, 2, 3])
# Apply pattern (0-7)
gp.apply_pattern(bars, pattern=1) # Cross-hatch pattern
```
Available patterns:
- 0: Empty (no fill)
- 1: Cross-hatch
- 2: Dense cross-hatch
- 3: Solid fill
- 4: Diagonal lines (45°)
- 5: Diagonal lines (-45°)
- 6: Wide diagonal lines (45°)
- 7: Wide diagonal lines (-45°)
## Development
### Setup
```bash
# Clone the repository
git clone https://github.com/vectorsss/gnuplot-style.git
cd gnuplot-style
# Install in development mode with all dependencies
pip install -e ".[dev]"
# Install pre-commit hooks
pre-commit install
```
### Running Tests
```bash
# Run all tests
pytest
# Run with coverage
pytest --cov=gnuplot_style
# Generate reference figures
python tests/test_reference_gnuplot_style.py
```
### Code Formatting
The project uses pre-commit hooks to ensure code quality:
```bash
# Run all pre-commit hooks
pre-commit run --all-files
# Or let them run automatically on commit
git commit -m "Your message"
```
## Contributing
1. Fork the repository
2. Create a feature branch (`git checkout -b feature/amazing-feature`)
3. Make your changes
4. Run tests and ensure code quality (`pytest && pre-commit run --all-files`)
5. Commit your changes (`git commit -m 'Add amazing feature'`)
6. Push to the branch (`git push origin feature/amazing-feature`)
7. Open a Pull Request
## Releasing (For Maintainers)
The package is automatically published to PyPI when a GitHub release is created.
### Setup (one-time)
1. Create PyPI API tokens:
- Go to https://pypi.org/manage/account/token/
- Create a token for this project
- Add it as `PYPI_API_TOKEN` in GitHub repository secrets
2. Create TestPyPI API token (optional):
- Go to https://test.pypi.org/manage/account/token/
- Create a token for this project
- Add it as `TEST_PYPI_API_TOKEN` in GitHub repository secrets
### Release Process
1. Update version in `src/gnuplot_style/__init__.py`
2. Create a GitHub release:
- For pre-releases: Check "Set as pre-release" (publishes to TestPyPI)
- For production releases: Leave unchecked (publishes to PyPI)
## Acknowledgments
- Inspired by the aesthetic of gnuplot's default terminal
- Built on top of matplotlib's excellent style system
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"description": "# gnuplot-style\n\n[](https://badge.fury.io/py/gnuplot-style)\n[](https://pypi.org/project/gnuplot-style/)\n[](https://opensource.org/licenses/MIT)\n[](https://github.com/psf/black)\n\nA Python package that provides gnuplot-style aesthetics for matplotlib plots.\n\n## Features\n\n- Easy-to-use API for applying gnuplot styles to matplotlib\n- Support for gnuplot's default colors, line styles, markers, and patterns\n- Modular design allowing selective application of styles\n- Compatible with matplotlib's style system\n- Includes pattern fills for histograms and bar charts\n\n## Installation\n\n```bash\npip install gnuplot-style\n```\n\n## Quick Start\n\n```python\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport gnuplot_style as gp\n\n# Apply gnuplot aesthetics BEFORE creating figures\ngp.use() # Default: colors only\n\n# Create your plots as usual\nx = np.linspace(0, 2*np.pi, 100)\nfor i in range(4):\n plt.plot(x, np.sin(x + i*0.5), label=f'Series {i+1}')\n\nplt.legend()\nplt.show()\n```\n\n### Note on Axes Created Before Style Application\n\nIf you create axes before calling `gp.use()`, you need to explicitly apply the style:\n\n```python\n# If axes already exist\nfig, ax = plt.subplots()\n\n# Apply style\ngp.use('cl')\n\n# Apply the prop_cycle to existing axes\nax.set_prop_cycle(plt.rcParams['axes.prop_cycle'])\n\n# Now plot with the new style\nax.plot(x, y)\n```\n\n## Style Options\n\nThe package provides several style combinations:\n\n```python\n# Individual components\ngp.use('color') # or 'c' - Just colors (default)\ngp.use('line') # or 'l' - Just line styles\ngp.use('marker') # or 'm' - Just markers\n\n# Combinations\ngp.use('color+line') # or 'cl' - Colors + line styles\ngp.use('color+marker') # or 'cm' - Colors + markers\ngp.use('all') # or 'clm' - Everything combined\n```\n\n### Convenience Functions\n\n```python\ngp.colors() # Apply colors only\ngp.lines() # Apply line styles only\ngp.markers() # Apply markers only\ngp.colors_lines() # Apply colors + lines\ngp.colors_markers() # Apply colors + markers\ngp.all() # Apply all styles\n```\n\n## Pattern Fills\n\nApply gnuplot-style patterns to bar charts:\n\n```python\n# Create a bar chart\nbars = plt.bar(['A', 'B', 'C'], [1, 2, 3])\n\n# Apply pattern (0-7)\ngp.apply_pattern(bars, pattern=1) # Cross-hatch pattern\n```\n\nAvailable patterns:\n- 0: Empty (no fill)\n- 1: Cross-hatch\n- 2: Dense cross-hatch\n- 3: Solid fill\n- 4: Diagonal lines (45\u00b0)\n- 5: Diagonal lines (-45\u00b0)\n- 6: Wide diagonal lines (45\u00b0)\n- 7: Wide diagonal lines (-45\u00b0)\n\n## Development\n\n### Setup\n\n```bash\n# Clone the repository\ngit clone https://github.com/vectorsss/gnuplot-style.git\ncd gnuplot-style\n\n# Install in development mode with all dependencies\npip install -e \".[dev]\"\n\n# Install pre-commit hooks\npre-commit install\n```\n\n### Running Tests\n\n```bash\n# Run all tests\npytest\n\n# Run with coverage\npytest --cov=gnuplot_style\n\n# Generate reference figures\npython tests/test_reference_gnuplot_style.py\n```\n\n### Code Formatting\n\nThe project uses pre-commit hooks to ensure code quality:\n\n```bash\n# Run all pre-commit hooks\npre-commit run --all-files\n\n# Or let them run automatically on commit\ngit commit -m \"Your message\"\n```\n\n## Contributing\n\n1. Fork the repository\n2. Create a feature branch (`git checkout -b feature/amazing-feature`)\n3. Make your changes\n4. Run tests and ensure code quality (`pytest && pre-commit run --all-files`)\n5. Commit your changes (`git commit -m 'Add amazing feature'`)\n6. Push to the branch (`git push origin feature/amazing-feature`)\n7. Open a Pull Request\n\n## Releasing (For Maintainers)\n\nThe package is automatically published to PyPI when a GitHub release is created.\n\n### Setup (one-time)\n\n1. Create PyPI API tokens:\n - Go to https://pypi.org/manage/account/token/\n - Create a token for this project\n - Add it as `PYPI_API_TOKEN` in GitHub repository secrets\n\n2. Create TestPyPI API token (optional):\n - Go to https://test.pypi.org/manage/account/token/\n - Create a token for this project\n - Add it as `TEST_PYPI_API_TOKEN` in GitHub repository secrets\n\n### Release Process\n\n1. Update version in `src/gnuplot_style/__init__.py`\n2. Create a GitHub release:\n - For pre-releases: Check \"Set as pre-release\" (publishes to TestPyPI)\n - For production releases: Leave unchecked (publishes to PyPI)\n\n## Acknowledgments\n\n- Inspired by the aesthetic of gnuplot's default terminal\n- Built on top of matplotlib's excellent style system\n",
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