Metadata-Version: 2.4
Name: iplotlib
Version: 1.3.2.post1
Summary: ITER plotting library
Author-email: ITER Organization <jscabanilla@minsait.com>
Maintainer-email: Jhon Steeven Cabanilla Alvarado <jscabanilla@minsait.com>, Pablo Martin Villares <pmartin@minsait.com>, Mario Gomez Ballesteros <mgomezb@minsait.com>
License: MIT
Project-URL: Homepage, https://github.com/iplot-viz/iplotlib
Project-URL: Repository, https://github.com/iplot-viz/iplotlib.git
Project-URL: Issues, https://github.com/iplot-viz/iplotlib/issues
Keywords: IDS,CBS,Matplotlib,PyQtGraph,Data Visualization
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Requires-Dist: iplotProcessing>=1.1.5
Requires-Dist: iplotDataAccess>=1.3.1
Requires-Dist: packaging>=20.0
Requires-Dist: matplotlib>=3.5.1
Requires-Dist: pandas>=1.2.0
Requires-Dist: PySide6>=6.2.3
Requires-Dist: vtk>=9.1.0
Requires-Dist: pyqtgraph>=0.13.7
Provides-Extra: test
Requires-Dist: pytest>=6.0; extra == "test"
Provides-Extra: docs
Requires-Dist: sphinx<7.0.0,>=6.0.0; extra == "docs"
Requires-Dist: sphinx-autosummary-accessors>=0.1.2; extra == "docs"
Requires-Dist: sphinx-immaterial<0.12,>=0.11.0; extra == "docs"
Requires-Dist: sphinx-click; extra == "docs"

# ITER plotting library

A high-level abstract plotting library.

| Graphics   |           GUI           |
|------------|:-----------------------:|
| matplotlib | PyQt5, PySide2, PySide6 |
| gnuplot    |          PyQt5          |
| vtk        |     PyQt5, PySide2      |

## Requirements

1. **python <= 3.11**
2. **Dependencies**: Managed
   via [pyproject.toml](https://github.com/iplot-viz/iplotlib/blob/develop/pyproject.toml).

## Installation

Install the package from PyPi:

  ```bash
  pip install iplotlib
  ```

## Usage Example

  ```bash
   from iplotlib.core import Canvas, PlotXY, SimpleSignal
   from iplotlib.qt.gui.iplotQtStandaloneCanvas import QStandaloneCanvas
   import numpy as np
   
   x = np.linspace(-1, 1, 1000)
   y = (1 - x ** 2) + 100 * (2 - x ** 2) ** 2
   
   s = SimpleSignal(label='signal_1', x_data=x, y_data=y)
   
   c = Canvas(rows=3, title='My Iplotlib Canvas')
   
   p = PlotXY()
   p.add_signal(s)
   c.add_plot(p)
   
   app = QStandaloneCanvas('matplotlib', use_toolbar=True)
   app.prepare()
   app.add_canvas(c)
   app.run()
  ```

## Run examples

```bash
iplotlib-qt-canvas -t
```

Click on canvas menu to switch between examples.


## Contributing

1. Fork it!
2. Create your feature branch: ```git checkout -b my-new-feature ```
3. Commit your changes: ```git commit -am 'Add some feature' ```
4. Push to the branch:```git push origin my-new-feature ```
5. Submit a pull request
