hv_anndata.plotting.scanpy.tracksplot¶

hv_anndata.plotting.scanpy.tracksplot(adata, /, vdims, *, kdim=None, color=None)¶

Tracksplot.

Parameters:

adata AnnData: The AnnData object.
vdims Collection[AdDim]: The value dimensions (one per curve).
kdim AdDim | None, default: None: The key dimension (inferred if None).
color AdDim | None, default: None: The color dimension.

Return type:

NdLayout

Returns:

A NdLayout containing Curve objects.

Examples

bokeh

import hv_anndata.plotting.scanpy as hv_sc
from hv_anndata import data, register, A

register()

adata = data.pbmc68k_processed()
markers = ["C1QA", "PSAP", "CD79A", "CD79B", "CST3", "LYZ"]
hv_sc.tracksplot(
    adata, A.X[:, markers], color=A.obs["bulk_labels"]
).opts(hv.opts.Curve(aspect=20))

/home/docs/.local/share/hatch/env/virtual/hv-anndata/STk7F69l/docs/lib/python3.13/site-packages/numba/cpython/hashing.py:477: UserWarning: FNV hashing is not implemented in Numba. See PEP 456 https://www.python.org/dev/peps/pep-0456/ for rationale over not using FNV. Numba will continue to work, but hashes for built in types will be computed using siphash24. This will permit e.g. dictionaries to continue to behave as expected, however anything relying on the value of the hash opposed to hash as a derived property is likely to not work as expected.
  warnings.warn(msg)

matplotlib

import hv_anndata.plotting.scanpy as hv_sc
from hv_anndata import data, register, A

register()

adata = data.pbmc68k_processed()
markers = ["C1QA", "PSAP", "CD79A", "CD79B", "CST3", "LYZ"]
hv_sc.tracksplot(
    adata, A.X[:, markers], color=A.obs["bulk_labels"]
).opts(hv.opts.Curve(aspect=20))

plotly

import hv_anndata.plotting.scanpy as hv_sc
from hv_anndata import data, register, A

register()

adata = data.pbmc68k_processed()
markers = ["C1QA", "PSAP", "CD79A", "CD79B", "CST3", "LYZ"]
hv_sc.tracksplot(
    adata, A.X[:, markers], color=A.obs["bulk_labels"]
).opts(hv.opts.Curve(aspect=20))