#!/usr/bin/env python # -*- coding: utf-8 -*- # Copyright 1999-2020 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 # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import numpy as np from ... import opcodes as OperandDef from ...serialize import AnyField, TupleField from .core import TensorReduction, TensorArgReductionMixin class TensorArgmin(TensorReduction, TensorArgReductionMixin): _op_type_ = OperandDef.ARGMIN _func_name = 'argmin' _agg_func_name = 'min' _offset = AnyField('offset') _total_shape = TupleField('total_shape') def __init__(self, axis=None, dtype=np.dtype(int), combine_size=None, offset=None, total_shape=None, stage=None, **kw): stage = self._rewrite_stage(stage) super().__init__(_axis=axis, _dtype=dtype, _combine_size=combine_size, _offset=offset, _total_shape=total_shape, _stage=stage, **kw) @property def offset(self): return getattr(self, '_offset', None) @property def total_shape(self): return getattr(self, '_total_shape', None) [docs]def argmin(a, axis=None, out=None, combine_size=None): """ Returns the indices of the minimum values along an axis. Parameters ---------- a : array_like Input tensor. axis : int, optional By default, the index is into the flattened tensor, otherwise along the specified axis. out : Tensor, optional If provided, the result will be inserted into this tensor. It should be of the appropriate shape and dtype. combine_size: int, optional The number of chunks to combine. Returns ------- index_array : Tensor of ints Tensor of indices into the tensor. It has the same shape as `a.shape` with the dimension along `axis` removed. See Also -------- Tensor.argmin, argmax amin : The minimum value along a given axis. unravel_index : Convert a flat index into an index tuple. Notes ----- In case of multiple occurrences of the minimum values, the indices corresponding to the first occurrence are returned. Examples -------- >>> import mars.tensor as mt >>> a = mt.arange(6).reshape(2,3) >>> a.execute() array([[0, 1, 2], [3, 4, 5]]) >>> mt.argmin(a).execute() 0 >>> mt.argmin(a, axis=0).execute() array([0, 0, 0]) >>> mt.argmin(a, axis=1).execute() array([0, 0]) Indices of the minimum elements of a N-dimensional tensor: >>> ind = mt.unravel_index(mt.argmin(a, axis=None), a.shape) >>> ind.execute() (0, 0) >>> a[ind] # TODO(jisheng): accomplish when fancy index on tensor is supported >>> b = mt.arange(6) >>> b[4] = 0 >>> b.execute() array([0, 1, 2, 3, 0, 5]) >>> mt.argmin(b).execute() # Only the first occurrence is returned. 0 """ op = TensorArgmin(axis=axis, dtype=np.dtype(int), combine_size=combine_size) return op(a, out=out)