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.. image:: https://github.com/Kitware/trame-plotly/actions/workflows/test_and_release.yml/badge.svg :target: https://github.com/Kitware/trame-plotly/actions/workflows/test_and_release.yml :alt: Test and Release
trame-plotly extend trame widgets with components that can interface with Plotly to display their charts.
Plotly integration in trame allow you to create rich visualization by leveraging their Python <https://plotly.com/python/>
_ or JavaScript <https://plotly.com/javascript/>
_ interface.
The JavaScript version is exposed via Vue.plotly <https://david-desmaisons.github.io/vue-plotly/>
_ within trame.widgets.plotly.Plotly class definition.
This package is not supposed to be used by itself but rather should come as a dependency of trame.
For any specificity, please refer to the trame documentation <https://kitware.github.io/trame/>
_.
trame-plotly can be installed with pip <https://pypi.org/project/trame-plotly/>
_:
.. code-block:: bash
pip install --upgrade trame-plotly
The Trame Tutorial <https://kitware.github.io/trame/docs/tutorial.html>
_ is the place to go to learn how to use the library and start building your own application.
The API Reference <https://trame.readthedocs.io/en/latest/index.html>
_ documentation provides API-level documentation.
The Plotly component relies on the server for generating the chart definition. This can be achieved by hand or by simply using the Python version of Plotly.
How to use it?
Using the Python library
.. code-block:: python
import plotly.graph_objects as go
from trame.widgets import plotly
fig = go.Figure(
data=go.Contour(
z=[
[10, 10.625, 12.5, 15.625, 20],
[5.625, 6.25, 8.125, 11.25, 15.625],
[2.5, 3.125, 5.0, 8.125, 12.5],
[0.625, 1.25, 3.125, 6.25, 10.625],
[0, 0.625, 2.5, 5.625, 10],
]
)
)
fig2 = go.Figure(
data=go.Contour(
z=[
[5.625, 6.25, 8.125, 11.25, 15.625],
[2.5, 3.125, 5.0, 8.125, 12.5],
[10, 10.625, 12.5, 15.625, 20],
[0.625, 1.25, 3.125, 6.25, 10.625],
[0, 0.625, 2.5, 5.625, 10],
]
)
)
widget = plotly.Figure(fig)
widget.update(fig2)
But if you are feeling more adventurous you can use the component API directly by building the data yourself as well.
.. code-block:: python
from trame.widgets import plotly
# https://plotly.com/javascript/reference/
plotly_data = [
{
"x": [1,2,3,4],
"y": [10,15,13,17],
"type": "scatter",
}
]
# https://plotly.com/javascript/reference/layout/
plotly_layout = {
"title": "My graph",
}
# https://plotly.com/javascript/configuration-options/
plotly_options = {
"scroll_zoom": True,
"editable": True,
"static_plot": True,
"to_image_options": {
"format": "svg", # one of png, svg, jpeg, webp
"filename": "custom_image",
"height": 500,
"width": 700,
"scale": 1 # Multiply title/legend/axis/canvas sizes by this factor
},
"display_mode_bar": True,
"mode_bar_buttons_to_remove": [
"zoom2d", "pan2d", "select2d", "lasso2d", "zoomIn2d", "zoomOut2d", "autoScale2d", "resetScale2d", # 2D
"zoom3d", "pan3d", "orbitRotation", "tableRotation", "handleDrag3d", "resetCameraDefault3d", "resetCameraLastSave3d", "hoverClosest3d", # 3D
"hoverClosestCartesian", "hoverCompareCartesian", # Cartesian
"zoomInGeo", "zoomOutGeo", "resetGeo", "hoverClosestGeo", # Geo
"hoverClosestGl2d", "hoverClosestPie", "toggleHover", "resetViews", "toImage", "sendDataToCloud", "toggleSpikelines", "resetViewMapbox", # Other
],
"mode_bar_buttons_to_add": [
{
"name": 'color toggler',
"icon": icon1, # https://plotly.com/javascript/configuration-options/#add-buttons-to-modebar
"click": "...",
},
],
"locale": "fr",
"display_logo": False,
"responsive": True,
"double_click_delay": 1000,
}
# Hand made chart
chart = plotly.Figure(
data=("chart_data", plotly_data),
layout=("chart_layout", plotly_layout),
**plotly_options,
)
.. list-table::
:widths: 20 80
:header-rows: 1
* - Type
- Values
* - properties
- data, layout, display_mode_bar, scroll_zoom, editable, static_plot, to_image_options, mode_bar_buttons_to_remove, mode_bar_buttons_to_add, locale, display_logo, responsive, double_click_delay
* - events
- after_export, after_plot, animated, animating_frame, animation_interrupted, auto_size, before_export, button_clicked, click, click_annotation, deselect, double_click, framework, hover, legend_click, legend_double_click, relayout, restyle, redraw, selected, selecting, slider_change, slider_end, slider_start, transitioning, transition_interrupted, unhover
License
-----------------------------------------------------------
trame-plotly is made available under the MIT License. For more details, see `LICENSE <https://github.com/Kitware/trame-plotly/blob/master/LICENSE>`_
This license has been chosen to match the one use by `Plotly <https://github.com/plotly/plotly.py/blob/master/LICENSE.txt>`_ and `vue-plotly <https://github.com/David-Desmaisons/vue-plotly/blob/master/LICENSE>`_ which are instrumental for making that library possible.
Community
-----------------------------------------------------------
`Trame <https://kitware.github.io/trame/>`_ | `Discussions <https://github.com/Kitware/trame/discussions>`_ | `Issues <https://github.com/Kitware/trame/issues>`_ | `RoadMap <https://github.com/Kitware/trame/projects/1>`_ | `Contact Us <https://www.kitware.com/contact-us/>`_
.. image:: https://zenodo.org/badge/410108340.svg
:target: https://zenodo.org/badge/latestdoi/410108340
Enjoying trame?
-----------------------------------------------------------
Share your experience `with a testimonial <https://github.com/Kitware/trame/issues/18>`_ or `with a brand approval <https://github.com/Kitware/trame/issues/19>`_.
FAQs
Plotly figure widget for trame
We found that trame-plotly demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
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