def buildVitessceConfig(adata, area_name):
vc = VitessceConfig("Developing human neocortex: gestational week 20")
dataset = vc.add_dataset(area_name).add_object(
# The`add_object()` function converts the AnnData data structure into a [Zarr]
# (https://zarr.readthedocs.io/en/stable/) store that is compatible with Vitessce.
AnnDataWrapper(adata,
mappings_obsm=["X_tsne"],
mappings_obsm_names=["t-SNE"],
expression_matrix="X",
spatial_centroid_obsm="X_spatial"))
spatial_plot = vc.add_view(dataset, cm.SPATIAL)
tsne_plot = vc.add_view(dataset, cm.SCATTERPLOT, mapping="t-SNE")
heatmap = vc.add_view(dataset, cm.HEATMAP)
genes_list = vc.add_view(dataset, cm.GENES)
vc.layout((spatial_plot | tsne_plot) / (heatmap | genes_list))
return vc
def test_config_add_scatterplot_view_with_mapping(self):
vc = VitessceConfig()
my_dataset = vc.add_dataset(name='My Dataset')
my_view = vc.add_view(cm.SCATTERPLOT,
dataset=my_dataset,
mapping="X_umap")
vc_dict = vc.to_dict()
vc_json = json.dumps(vc_dict)
self.assertEqual(
vc_dict, {
"version":
"1.0.4",
"name":
"",
"description":
"",
"datasets": [{
'uid': 'A',
'name': 'My Dataset',
'files': []
}],
'coordinationSpace': {
'dataset': {
'A': 'A'
},
'embeddingType': {
'A': 'X_umap'
}
},
"layout": [{
'component': 'scatterplot',
'coordinationScopes': {
'dataset': 'A',
'embeddingType': 'A'
},
'h': 1,
'w': 1,
'x': 0,
'y': 0
}],
"initStrategy":
"auto"
})
def test_config_set_layout_single_view(self):
vc = VitessceConfig()
my_dataset = vc.add_dataset(name='My Dataset')
my_view = vc.add_view(cm.SPATIAL, dataset=my_dataset)
vc.layout(my_view)
vc_dict = vc.to_dict()
vc_json = json.dumps(vc_dict)
self.assertEqual(
vc_dict, {
"version":
"1.0.4",
"name":
"",
"description":
"",
"datasets": [{
'uid': 'A',
'name': 'My Dataset',
'files': []
}],
'coordinationSpace': {
'dataset': {
'A': 'A'
},
},
"layout": [{
'component': 'spatial',
'coordinationScopes': {
'dataset': 'A',
},
'x': 0,
'y': 0,
'h': 12,
'w': 12,
}],
"initStrategy":
"auto"
})
def test_config_to_python_with_data_objects(self):
vc = VitessceConfig()
class MockWrapperA(AbstractWrapper):
def __init__(self, name, **kwargs):
super().__init__(**kwargs)
self._repr = make_repr(locals())
self.name = name
def convert_and_save(self, dataset_uid, obj_i):
def get_molecules(base_url):
return {
"url": f"{base_url}/molecules",
"type": "molecules",
"fileType": "molecules.json"
}
def get_cells(base_url):
return {
"url": f"{base_url}/cells",
"type": "cells",
"fileType": "cells.json"
}
self.file_def_creators += [get_molecules, get_cells]
class MockWrapperB(AbstractWrapper):
def __init__(self, name, **kwargs):
super().__init__(**kwargs)
self._repr = make_repr(locals())
self.name = name
def convert_and_save(self, dataset_uid, obj_i):
def get_cell_sets(base_url):
return {
"url": f"{base_url}/cell-sets",
"type": "cell-sets",
"fileType": "cell-sets.json"
}
self.file_def_creators += [get_cell_sets]
dataset_a = vc.add_dataset(name='My First Dataset').add_object(
obj=MockWrapperA("Experiment A")).add_file(
url="http://example.com/my_cells.json",
file_type=ft.CELLS_JSON,
data_type=dt.CELLS)
dataset_b = vc.add_dataset(name='My Second Dataset').add_object(
obj=MockWrapperB("Experiment B"))
vc.add_view(cm.SPATIAL, dataset=dataset_a, x=0, y=0, w=3,
h=3).set_props(title="My spatial plot")
vc.add_view(cm.SCATTERPLOT,
dataset=dataset_b,
x=3,
y=0,
w=3,
h=3,
mapping="PCA").set_props(title="My scatterplot")
base_url = "http://localhost:8000"
classes_to_import, code_block = vc.to_python()
self.assertEqual(
classes_to_import,
['VitessceChainableConfig', 'VitessceConfigDatasetFile'])
# Evaluate the code string directly
reconstructed_vc = eval(code_block)
self.assertEqual(vc.to_dict(base_url=base_url),
reconstructed_vc.to_dict(base_url=base_url))
# Convert code string to an AST and back before evaluation
if hasattr(ast, 'unparse'):
# Unparse added in Python 3.9
ast_reconstructed_vc = eval(ast.unparse(ast.parse(code_block)))
self.assertEqual(vc.to_dict(base_url=base_url),
ast_reconstructed_vc.to_dict(base_url=base_url))
else:
ast.parse(code_block)
def test_config_add_scatterplot_view_with_embedding_coordinations(self):
vc = VitessceConfig()
my_dataset = vc.add_dataset(name='My Dataset')
my_view = vc.add_view(cm.SCATTERPLOT, dataset=my_dataset)
et_scope, ez_scope, ex_scope, ey_scope = vc.add_coordination(
ct.EMBEDDING_TYPE, ct.EMBEDDING_ZOOM, ct.EMBEDDING_TARGET_X,
ct.EMBEDDING_TARGET_Y)
my_view.use_coordination(et_scope, ez_scope, ex_scope, ey_scope)
et_scope.set_value("X_pca")
ez_scope.set_value(2)
ex_scope.set_value(10)
ey_scope.set_value(11)
vc_dict = vc.to_dict()
vc_json = json.dumps(vc_dict)
self.assertEqual(
vc_dict, {
"version":
"1.0.4",
"name":
"",
"description":
"",
"datasets": [{
'uid': 'A',
'name': 'My Dataset',
'files': []
}],
'coordinationSpace': {
'dataset': {
'A': 'A'
},
'embeddingType': {
'A': 'X_pca'
},
'embeddingZoom': {
'A': 2
},
'embeddingTargetX': {
'A': 10
},
'embeddingTargetY': {
'A': 11
},
},
"layout": [{
'component': 'scatterplot',
'coordinationScopes': {
'dataset': 'A',
'embeddingType': 'A',
'embeddingZoom': 'A',
'embeddingTargetX': 'A',
'embeddingTargetY': 'A',
},
'h': 1,
'w': 1,
'x': 0,
'y': 0
}],
"initStrategy":
"auto"
})