Tutorials#
Entry-point material for learning the API on synthetic data.
The fluent .pl API, layering, and styling on the in-memory blobs
dataset. Ideal first read.
How color= resolves, the v0.3.0 groups behaviour, and building
perceptually well-spaced or colourblind-safe palettes with
make_palette and make_palette_from_data.
Render several colourings at once by passing a list to color=,
scanpy-style, with per-panel legends/colourbars, shared palette/cmap,
and ncols grid control.
Keep rendering fast on large data: automatic rasterization and scale
selection for images, and the datashader backend for large collections
of shapes and points.
Draw shapes and label masks as one dot per centroid with as_points=True
— a fast overview that trades geometry for speed, including the matplotlib
→ datashader switch above ~50k elements.
Add a physical scalebar with scalebar_dx, choose units, and style
placement, colour, length and fonts through scalebar_params.
Draw circle elements as circles, hexagons, or squares with shape=, and
render Visium spots as a hex grid with shape="visium_hex".
Render multiplexed and fluorescence images: select channels by name,
composite them with per-channel palette LUTs, fix heavy-tailed contrast
per channel, and label the composite with channels_as_legend.
Zoom into a bounding box with crop_coord — every layer windowed at draw
time, images rasterized for the window only, and how it differs from
bounding_box_query.