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https://github.com/janjoch/interplot-minimal
Minimal install version: Create matplotlib and plotly charts with the same few lines of code.
https://github.com/janjoch/interplot-minimal
Last synced: 11 days ago
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Minimal install version: Create matplotlib and plotly charts with the same few lines of code.
- Host: GitHub
- URL: https://github.com/janjoch/interplot-minimal
- Owner: janjoch
- Created: 2024-06-10T17:38:06.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2024-06-20T20:16:40.000Z (5 months ago)
- Last Synced: 2024-10-11T19:12:09.820Z (about 1 month ago)
- Language: Jupyter Notebook
- Size: 2.24 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# interplot
[](https://www.gnu.org/licenses/gpl-3.0) [](https://mybinder.org/v2/gh/janjoch/interplot/HEAD) [](https://nbviewer.org/github/janjoch/interplot/tree/main/)
Create `matplotlib` and `plotly` charts with the same few lines of code.
It combines the best of the `matplotlib` and the `plotly` worlds through a unified, flat API.
Switch between `matplotlib` and `plotly` with the single keyword `interactive`. All the necessary boilerplate code to translate between the packages is contained in this module.
Currently supported building blocks:
- scatter plots
- `line`
- `scatter`
- `linescatter`
- bar charts `bar`
- histogram `hist`
- boxplot `boxplot`
- heatmap `heatmap`
- linear regression `regression`
- line fill `fill`
- annotations `text`
Supported
- 2D subplots
- automatic color cycling
- 3 different API modes
- One line of code
```python
>>> interplot.line([0,4,6,7], [1,2,4,8])
[plotly line figure]
>>> interplot.hist(np.random.normal(40, 8, 1000), interactive=False)
[matplotlib hist figure]
>>> interplot.boxplot(
>>> [
>>> np.random.normal(20, 5, 1000),
>>> np.random.normal(40, 8, 1000),
>>> np.random.normal(60, 5, 1000),
>>> ],
>>> )
[plotly boxplots]
```
- Decorator to auto-initialize plots to use in your methods
```python
>>> @interplot.magic_plot
>>> def plot_my_data(fig=None):
>>> # import and process your data...
>>> data = np.random.normal(2, 3, 1000)
>>> # draw with the fig instance obtained from the decorator function
>>> fig.add_line(data, label="my data")
>>> fig.add_fill((0, 999), (-1, -1), (5, 5), label="sigma")
>>> plot_my_data(title="My Recording")
[plotly figure "My Recording"]
>>> @interplot.magic_plot_preset(interactive=False, title="Preset Title")
>>> def plot_my_data_preconfigured(fig=None):
>>> # import and process your data...
>>> data = np.random.normal(2, 3, 1000)
>>> # draw with the fig instance obtained from the decorator function
>>> fig.add_line(data, label="my data")
>>> fig.add_fill((0, 999), (-1, -1), (5, 5), label="sigma")
>>> plot_my_data_preconfigured()
[matplotlib figure "Preset Title"]
```
- The ```interplot.Plot``` class for full control
```python
>>> fig = interplot.Plot(
>>> interactive=True,
>>> title="Everything Under Control",
>>> fig_size=(800, 500),
>>> rows=1,
>>> cols=2,
>>> shared_yaxes=True,
>>> # ...
>>> )
>>> fig.add_hist(np.random.normal(1, 0.5, 1000), row=0, col=0)
>>> fig.add_boxplot(
>>> [
>>> np.random.normal(20, 5, 1000),
>>> np.random.normal(40, 8, 1000),
>>> np.random.normal(60, 5, 1000),
>>> ],
>>> row=0,
>>> col=1,
>>> )
>>> # ...
>>> fig.post_process()
>>> fig.show()
[plotly figure "Everything Under Control"]
>>> fig.save("export/path/file.html")
saved figure at export/path/file.html
```
## Resources
- **Documentation:** https://interplot.janjo.ch
- **Demo Notebooks:** https://nbviewer.org/github/janjoch/interplot/tree/main/demo/
- **Source Code:** https://github.com/janjoch/interplot
- **PyPI:** https://pypi.org/project/interplot/
## Licence
[](https://www.gnu.org/licenses/gpl-3.0)
## Demo
View on `NBViewer`:
[](https://nbviewer.org/github/janjoch/interplot/tree/main/)
Try on `Binder`:
[](https://mybinder.org/v2/gh/janjoch/interplot/HEAD)
## Install
```pip install interplot```
### dev installation
1. ```git clone https://github.com/janjoch/interplot```
2. ```cd interplot```
2. ```pip install -e .```
## Contribute
Ideas, bug reports/fixes, feature requests and code submissions are very welcome! Please write to [[email protected]](mailto:[email protected]) or directly into a pull request.