Source code for mars.tensor.fft.rfft2

#!/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.

import numpy as np

from ... import opcodes as OperandDef
from ..datasource import tensor as astensor
from .core import TensorRealFFTNMixin, validate_fftn, TensorRealFFTN

class TensorRFFT2(TensorRealFFTN, TensorRealFFTNMixin):
    _op_type_ = OperandDef.RFFT2

    def __init__(self, shape=None, axes=None, norm=None, **kw):
        super().__init__(_shape=shape, _axes=axes, _norm=norm, **kw)

[docs]def rfft2(a, s=None, axes=(-2, -1), norm=None): """ Compute the 2-dimensional FFT of a real tensor. Parameters ---------- a : array_like Input tensor, taken to be real. s : sequence of ints, optional Shape of the FFT. axes : sequence of ints, optional Axes over which to compute the FFT. norm : {None, "ortho"}, optional Normalization mode (see `mt.fft`). Default is None. Returns ------- out : Tensor The result of the real 2-D FFT. See Also -------- rfftn : Compute the N-dimensional discrete Fourier Transform for real input. Notes ----- This is really just `rfftn` with different default behavior. For more details see `rfftn`. """ if len(axes) != 2: raise ValueError("axes length should be 2") a = astensor(a) axes = validate_fftn(a, s=s, axes=axes, norm=norm) op = TensorRFFT2(shape=s, axes=axes, norm=norm, dtype=np.dtype(np.complex_)) return op(a)