Source code for mars.tensor.datasource.indices

#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright 1999-2021 Alibaba Group Holding Ltd.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.

from import Iterable

import numpy as np

from ... import opcodes as OperandDef
from ...serialization.serializables import FieldTypes, ListField
from .core import TensorNoInput
from .arange import arange
from .empty import empty
from .meshgrid import meshgrid

class TensorIndices(TensorNoInput):
    _op_type_ = OperandDef.TENSOR_INDICES

    _dimensions = ListField("dimensions", FieldTypes.uint64)

    def __init__(self, dimensions=None, **kw):
        super().__init__(_dimensions=dimensions, **kw)

    def dimensions(self):
        return self._dimensions

[docs]def indices(dimensions, dtype=int, chunk_size=None): """ Return a tensor representing the indices of a grid. Compute a tensor where the subtensors contain index values 0,1,... varying only along the corresponding axis. Parameters ---------- dimensions : sequence of ints The shape of the grid. dtype : dtype, optional Data type of the result. chunk_size : int or tuple of int or tuple of ints, optional Desired chunk size on each dimension Returns ------- grid : Tensor The tensor of grid indices, ``grid.shape = (len(dimensions),) + tuple(dimensions)``. See Also -------- mgrid, meshgrid Notes ----- The output shape is obtained by prepending the number of dimensions in front of the tuple of dimensions, i.e. if `dimensions` is a tuple ``(r0, ..., rN-1)`` of length ``N``, the output shape is ``(N,r0,...,rN-1)``. The subtensors ``grid[k]`` contains the N-D array of indices along the ``k-th`` axis. Explicitly:: grid[k,i0,i1,...,iN-1] = ik Examples -------- >>> import mars.tensor as mt >>> grid = mt.indices((2, 3)) >>> grid.shape (2, 2, 3) >>> grid[0].execute() # row indices array([[0, 0, 0], [1, 1, 1]]) >>> grid[1].execute() # column indices array([[0, 1, 2], [0, 1, 2]]) The indices can be used as an index into a tensor. >>> x = mt.arange(20).reshape(5, 4) >>> row, col = mt.indices((2, 3)) >>> # x[row, col] # TODO(jisheng): accomplish this if multiple fancy indexing is supported Note that it would be more straightforward in the above example to extract the required elements directly with ``x[:2, :3]``. """ from ..merge import stack dimensions = tuple(dimensions) dtype = np.dtype(dtype) raw_chunk_size = chunk_size if chunk_size is not None and isinstance(chunk_size, Iterable): chunk_size = tuple(chunk_size) else: chunk_size = (chunk_size,) * len(dimensions) xi = [] for ch, dim in zip(chunk_size, dimensions): xi.append(arange(dim, dtype=dtype, chunk_size=ch)) grid = None if grid = meshgrid(*xi, indexing="ij") if grid: grid = stack(grid) else: if raw_chunk_size is None: empty_chunk_size = None else: empty_chunk_size = (1,) + chunk_size grid = empty( (len(dimensions),) + dimensions, dtype=dtype, chunk_size=empty_chunk_size ) return grid