Usage from Python

Install the pluot Python package from PyPI.

pip install pluot

Not yet published to PyPI

For now, the package is only available from GitHub; we have only reserved the package name on PyPI.

Static plotting

Use the render_to_array and render_to_image functions to render static plots in raster format. The former returns a Numpy array, while the latter returns a PIL.Image object.

When used in a Jupyter notebook, the returned PIL.Image object will be displayed as an image output of the notebook cell.

from pluot import render_to_image
import numpy as np

camera_view = [
    0.15, 0.0, 0.0, 0.0,
    0.0, 0.15, 0.0, 0.0,
    0.0, 0.0, 1.0, 0.0,
    0.0, 0.0, 0.0, 1.0,
]

x_arr = ((np.random.rand(500) - 0.5) * 10.0).astype('<f8')
y_arr = ((np.random.rand(500) - 0.5) * 10.0).astype('<f8')
color_arr = np.array(
  [0, 1, 2, 3, 4] * 100
).astype('<i8')

await render_to_image(
    camera_view=camera_view,
    width=700,
    height=800,
    plot_id="test",
    plot_type="Scatterplot",
    plot_params=dict(
        x_arr=x_arr,
        y_arr=y_arr,
        color_arr=color_arr,
        point_radius=10.0
    ),
    margin_left=100,
    margin_bottom=100
)

Async runtime

Since the plotting function is async, it must be called from a Python async runtime. Code executed in Jupyter notebooks is already running in an async runtime, so await render_to_image will "just work".

However, in other contexts, be careful to ensure render_to_image is await-ed within an async runtime. For instance, to use within a REPL, run python -m asyncio.

Interactive notebook widget

TODO