Visualization of a SpatialData object, blobs example

Import dependencies

[ ]:

import spatialdata
from os.path import join

[ ]:

sdata = spatialdata.datasets.blobs()

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spatialdata_filepath = join("data", "blobs.spatialdata.zarr")

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sdata.write(spatialdata_filepath, overwrite=True)

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# Change data type of x and y columns from int64 to int32
# Temporary workaround, will be resolved by https://github.com/vitessce/vitessce/issues/2292
ddf = sdata["blobs_points"]
ddf["x"] = ddf["x"].astype('int32')
ddf["y"] = ddf["y"].astype('int32')
sdata["blobs_points_2"] = ddf
sdata.write_element("blobs_points_2")

[ ]:

from vitessce import (
    VitessceConfig,
    ViewType as vt,
    CoordinationType as ct,
    CoordinationLevel as CL,
    SpatialDataWrapper,
    get_initial_coordination_scope_prefix
)

Configure Vitessce

Vitessce needs to know which pieces of data we are interested in visualizing, the visualization types we would like to use, and how we want to coordinate (or link) the views.

[ ]:

vc = VitessceConfig(
    schema_version="1.0.18",
    name='Visium SpatialData Demo (blobs)',
)
# Add data to the configuration:
wrapper = SpatialDataWrapper(
    sdata_store=spatialdata_filepath,
    # The following paths are relative to the root of the SpatialData zarr store on-disk.
    image_path="images/blobs_image",
    obs_segmentations_path="labels/blobs_labels",
    coordinate_system="global",
    coordination_values={
        "obsType": "blob",
        "fileUid": "my_unique_id"
    }
)
points_wrapper = SpatialDataWrapper(
    sdata_store=spatialdata_filepath,
    # The following paths are relative to the root of the SpatialData zarr store on-disk.
    obs_points_path="points/blobs_points_2",
    coordinate_system="global",
    coordination_values={
        "obsType": "point",
        "fileUid": "other_unique_id"
    }
)
dataset = vc.add_dataset(name='Blobs').add_object(wrapper).add_object(points_wrapper)

# Add views (visualizations) to the configuration:
spatial = vc.add_view("spatialBeta", dataset=dataset)
layer_controller = vc.add_view("layerControllerBeta", dataset=dataset)

vc.link_views_by_dict([spatial, layer_controller], {
    'imageLayer': CL([{
        "fileUid": "my_unique_id",
        'photometricInterpretation': 'BlackIsZero',
        'spatialLayerOpacity': 0.9,
        'imageChannel': CL([
            {
                "spatialTargetC": 0,
                "spatialChannelColor": [255, 0, 0],
                "spatialChannelOpacity": 1.0
            },
            {
                "spatialTargetC": 1,
                "spatialChannelColor": [0, 255, 0],
                "spatialChannelOpacity": 1.0
            },
            {
                "spatialTargetC": 2,
                "spatialChannelColor": [0, 0, 255],
                "spatialChannelOpacity": 1.0
            }
        ])
    }]),
}, scope_prefix=get_initial_coordination_scope_prefix("A", "image"))

vc.link_views_by_dict([spatial, layer_controller], {
    'segmentationLayer': CL([{
        "fileUid": "my_unique_id",
        'segmentationChannel': CL([{
            'spatialChannelVisible': True,
            'obsType': 'blob',
        }]),
    }]),
}, scope_prefix=get_initial_coordination_scope_prefix("A", "obsSegmentations"))

vc.link_views_by_dict([spatial, layer_controller], {
    'pointLayer': CL([{
        "fileUid": "other_unique_id",
        "obsType": "point",
        "obsHighlight": None,
    }]),
}, scope_prefix=get_initial_coordination_scope_prefix("A", "obsPoints"))

# Layout the views
vc.layout(spatial | layer_controller);