Source code for maxframe.tensor.fft.rfft2

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import numpy as np

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


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




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)
    cplx_type = np.complex_ if hasattr(np, "complex_") else np.complex128
    op = TensorRFFT2(shape=s, axes=axes, norm=norm, dtype=np.dtype(cplx_type))
    return op(a)