Allows generating dummy spatialdata objects, which can be useful for testing purposes.
pip install dummy-spatialdatadummy-spatialdata is compatible with both spatialdata == 0.5.0 (zarr v2) and 0.7.2 (zarr v3)
Thus please use
conda create --name dummy_sd_env python==3.12 spatialdata==0.7.2orconda create --name dummy_sd_env_05 python==3.12 spatialdata==0.5.0 setuptools==75.8.0
from dummy_spatialdata import generate_dataset
import dummy_anndata
import spatialdata_plot as sdp
import spatialdata as sd
import matplotlib.pyplot as plt
import anndata as ad
# generate dummy anndata
adata = dummy_anndata.generate_dataset(n_obs=12, n_vars=20)
sdata = generate_dataset(
images = [
{"type": "rgb", "n_layers": 4, "coordinate_system": "global"},
{"type": "grayscale", "n_layers": 1, "coordinate_system": "global"},
],
labels = [
{"n_labels": 12, "n_layers": 4, "coordinate_system": "global2"},
{"n_labels": 12, "n_layers": 0, "coordinate_system": "global2"},
],
shapes = [
{"n_shapes": 12, "coordinate_system": "global"},
{"n_shapes": 20},
],
points = [
{"n_points": 12}
],
tables = [
{"table": adata, "element": "shape", "element_index": 0}
],
coordinate_systems = {
"global": {"transformations": ["affine"], "shape": {"x": 2000, "y": 2000}},
"global2": {"transformations": ["scale", "translation"], "shape":{"x": 500, "y": 500}}},
SEED=13
)
sdata
SpatialData object
├── Images
│ ├── 'image_0': DataTree[cyx] (3, 2000, 2000), (3, 1000, 1000), (3, 500, 500), (3, 250, 250)
│ └── 'image_1': DataTree[cyx] (1, 2000, 2000)
├── Labels
│ ├── 'label_0': DataTree[yx] (500, 500), (250, 250), (125, 125), (62, 62)
│ └── 'label_1': DataTree[yx] (500, 500)
├── Points
│ └── 'point_0': DataFrame with shape: (<Delayed>, 2) (2D points)
├── Shapes
│ ├── 'shape_0': GeoDataFrame shape: (12, 1) (2D shapes)
│ └── 'shape_1': GeoDataFrame shape: (20, 1) (2D shapes)
└── Tables
└── 'table_0': AnnData (12, 20)
with coordinate systems:
▸ 'global', with elements:
image_0 (Images), image_1 (Images), shape_0 (Shapes)
▸ 'global2', with elements:
label_0 (Labels), label_1 (Labels)
▸ 'point_0', with elements:
point_0 (Points)
▸ 'shape_1', with elements:
shape_1 (Shapes)
You can plot the demo data now!
sdata.pl.render_images("image_0").pl.render_shapes("shape_0", color="Gene001", table_name = "table_0", table_layer = "float_matrix").pl.show(coordinate_systems = "global")