| Name | daaf-plot JSON |
| Version |
1.0.1
JSON |
| download |
| home_page | None |
| Summary | Personal python toolbox to make interactive plot in python notebooks |
| upload_time | 2025-10-22 11:33:40 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.11 |
| license | None |
| keywords |
interactive plots
notebooks
visualization
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# daaf-plot
[](https://badge.fury.io/py/daaf-plot)
[](https://opensource.org/licenses/MIT)
`daaf-plot` is a python toolbox to make interactive plot in python notebooks.
## Installation
Install using `pip`:
$ pip install daaf-plot
## Usage
The primary goal of the present toolbox is to help the creation of interactive plots.
Nevertheless, it also provides a function to open a `matplotlib` figure from a given list
of settings (number of rows and columns, padding, etc.) as well as some stylistic options
which can be used outside python notebooks.
### Interactive plots
To make an interactive plot, you need:
1. to enable the `%matplotlib widget` magic in a notebook;
2. an `xarray.DataArray` containing the data to plot.
Import `InteractiveLinePlot` or `InteractivePColorMesh` from `daaf_plot.figure`, instantiate with:
>>> fig = InteractiveLinePlot(
... data_array,
... x_dim='the_x_dim',
... line_dim='the_line_dim',
... facet_dim=...,
... open_figure_kwargs=dict(...),
... )
for a line plot and with:
>>> fig = InteractivePColorMesh(
... data_array,
... x_dim='the_x_dim',
... y_dim='the_y_dim',
... facet_dim=...
... open_figure_kwargs=dict(...),
... )
for a pcolormesh. This creates an abstract figure object, which you can then open using:
>>> fig.interactive_show()
Have at look at the examples in the `examples/` repository!
### Open a matplotlib figure
The `daaf_plot.geometry.open_figure()` function can be used to open a `matplotlib` figure,
even outside python notebooks.
### Stylistic options
Some `matplotlib` stylistic options are provided when importing `daaf_plot.style`:
- scale `linlogp`;
- color map `deep` (from `seaborn`) and its reversed counterpart;
- a unified function `daaf_plot.style.set_font_size()` to set font size in figures;
- ...
In addition, my custom style sheet is stored in `src/daaf_plot/style/laptop.mplstyle`
and can be used as follows:
>>> import matplotlib.pyplot as plt
>>> plt.style.use('daaf_plot.style.laptop')
## Todo-list
- write docstrings
- write documentation
- add type hints
Raw data
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"description": "# daaf-plot\n\n[](https://badge.fury.io/py/daaf-plot)\n[](https://opensource.org/licenses/MIT)\n\n`daaf-plot` is a python toolbox to make interactive plot in python notebooks.\n\n## Installation\n\nInstall using `pip`:\n\n $ pip install daaf-plot\n\n## Usage\n\nThe primary goal of the present toolbox is to help the creation of interactive plots.\nNevertheless, it also provides a function to open a `matplotlib` figure from a given list\nof settings (number of rows and columns, padding, etc.) as well as some stylistic options\nwhich can be used outside python notebooks.\n\n### Interactive plots\n\nTo make an interactive plot, you need:\n1. to enable the `%matplotlib widget` magic in a notebook;\n2. an `xarray.DataArray` containing the data to plot.\n\nImport `InteractiveLinePlot` or `InteractivePColorMesh` from `daaf_plot.figure`, instantiate with:\n\n >>> fig = InteractiveLinePlot(\n ... data_array,\n ... x_dim='the_x_dim',\n ... line_dim='the_line_dim',\n ... facet_dim=...,\n ... open_figure_kwargs=dict(...),\n ... )\n\nfor a line plot and with:\n\n >>> fig = InteractivePColorMesh(\n ... data_array,\n ... x_dim='the_x_dim',\n ... y_dim='the_y_dim',\n ... facet_dim=...\n ... open_figure_kwargs=dict(...),\n ... )\n\nfor a pcolormesh. This creates an abstract figure object, which you can then open using:\n\n >>> fig.interactive_show()\n\nHave at look at the examples in the `examples/` repository!\n\n### Open a matplotlib figure\n\nThe `daaf_plot.geometry.open_figure()` function can be used to open a `matplotlib` figure,\neven outside python notebooks.\n\n### Stylistic options\n\nSome `matplotlib` stylistic options are provided when importing `daaf_plot.style`:\n- scale `linlogp`;\n- color map `deep` (from `seaborn`) and its reversed counterpart;\n- a unified function `daaf_plot.style.set_font_size()` to set font size in figures;\n- ...\n\nIn addition, my custom style sheet is stored in `src/daaf_plot/style/laptop.mplstyle`\nand can be used as follows:\n\n >>> import matplotlib.pyplot as plt\n >>> plt.style.use('daaf_plot.style.laptop')\n\n## Todo-list\n\n- write docstrings\n- write documentation\n- add type hints\n",
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