_slice_1d(dim_shape, lengths, index)

This function figures out where each slice should start in each block for a single dimension. If the slice won't return any elements in the block, that block will not be in the output.

Parameters

dim_shape - the number of elements in this dimension. :

This should be a positive, non-zero integer

blocksize - the number of elements per block in this dimension :

This should be a positive, non-zero integer

index - a description of the elements in this dimension that we want :

This might be an integer, a slice(), or an Ellipsis

Returns

dictionary where the keys are the integer index of the blocks that

should be sliced and the values are the slices

Returns a dict of {blocknum: slice}

Examples

Trivial slicing

This example is valid syntax, but we were not able to check execution

>>> _slice_1d(100, [60, 40], slice(None, None, None))
{0: slice(None, None, None), 1: slice(None, None, None)}

100 length array cut into length 20 pieces, slice 0:35

This example is valid syntax, but we were not able to check execution

>>> _slice_1d(100, [20, 20, 20, 20, 20], slice(0, 35))
{0: slice(None, None, None), 1: slice(0, 15, 1)}

Support irregular blocks and various slices

This example is valid syntax, but we were not able to check execution

>>> _slice_1d(100, [20, 10, 10, 10, 25, 25], slice(10, 35))
{0: slice(10, 20, 1), 1: slice(None, None, None), 2: slice(0, 5, 1)}

Support step sizes

This example is valid syntax, but we were not able to check execution

>>> _slice_1d(100, [15, 14, 13], slice(10, 41, 3))
{0: slice(10, 15, 3), 1: slice(1, 14, 3), 2: slice(2, 12, 3)}

This example is valid syntax, but we were not able to check execution

>>> _slice_1d(100, [20, 20, 20, 20, 20], slice(0, 100, 40))  # step > blocksize
{0: slice(0, 20, 40), 2: slice(0, 20, 40), 4: slice(0, 20, 40)}

Also support indexing single elements

This example is valid syntax, but we were not able to check execution

>>> _slice_1d(100, [20, 20, 20, 20, 20], 25)
{1: 5}

And negative slicing

This example is valid syntax, but we were not able to check execution

>>> _slice_1d(100, [20, 20, 20, 20, 20], slice(100, 0, -3)) # doctest: +NORMALIZE_WHITESPACE
{4: slice(-1, -21, -3),
 3: slice(-2, -21, -3),
 2: slice(-3, -21, -3),
 1: slice(-1, -21, -3),
 0: slice(-2, -20, -3)}

This example is valid syntax, but we were not able to check execution

>>> _slice_1d(100, [20, 20, 20, 20, 20], slice(100, 12, -3)) # doctest: +NORMALIZE_WHITESPACE
{4: slice(-1, -21, -3),
 3: slice(-2, -21, -3),
 2: slice(-3, -21, -3),
 1: slice(-1, -21, -3),
 0: slice(-2, -8, -3)}

This example is valid syntax, but we were not able to check execution

>>> _slice_1d(100, [20, 20, 20, 20, 20], slice(100, -12, -3))
{4: slice(-1, -12, -3)}

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

dask.array.slicing.slice_slices_and_integers dask.array.slicing._slice_1d

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File: /dask/array/slicing.py#343
type: <class 'function'>
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