- tensorstore.Schema.__getitem__(self, indices: NumpyIndexingSpec) Schema
Transforms the schema using NumPy-style indexing with default index array semantics.
Example
>>> schema = ts.Schema( ... domain=ts.IndexDomain(labels=['x', 'y', 'z'], ... shape=[1000, 2000, 3000]), ... chunk_layout=ts.ChunkLayout(grid_origin=[100, 200, 300], ... inner_order=[0, 1, 2]), ... ) >>> schema[[5, 10, 20], 6:10] Schema({ 'chunk_layout': {'grid_origin': [None, 200, 300], 'inner_order': [1, 2, 0]}, 'domain': { 'exclusive_max': [3, 10, 3000], 'inclusive_min': [0, 6, 0], 'labels': ['', 'y', 'z'], }, 'rank': 3, })
- Returns:¶
New schema with the indexing operation applied.
- Raises:¶
ValueError – If
self.rank
isNone
.