tf.keras.ops.rfft
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Real-valued Fast Fourier Transform along the last axis of the input.
tf.keras.ops.rfft(
x, fft_length=None
)
Computes the 1D Discrete Fourier Transform of a real-valued signal over the
inner-most dimension of input.
Since the Discrete Fourier Transform of a real-valued signal is
Hermitian-symmetric, RFFT only returns the fft_length / 2 + 1 unique
components of the FFT: the zero-frequency term, followed by the
fft_length / 2 positive-frequency terms.
Along the axis RFFT is computed on, if fft_length is smaller than the
corresponding dimension of the input, the dimension is cropped. If it is
larger, the dimension is padded with zeros.
Args |
|---|
x
|
Input tensor.
|
fft_length
|
An integer representing the number of the fft length. If not
specified, it is inferred from the length of the last axis of x.
Defaults to None.
|
Returns |
|---|
|
A tuple containing two tensors - the real and imaginary parts of the
output.
|
Examples:
x = keras.ops.convert_to_tensor([0.0, 1.0, 2.0, 3.0, 4.0])
rfft(x)
(array([10.0, -2.5, -2.5]), array([0.0, 3.4409548, 0.81229924]))
rfft(x, 3)
(array([3.0, -1.5]), array([0.0, 0.8660254]))
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Last updated 2024-06-07 UTC.
[null,null,["Last updated 2024-06-07 UTC."],[],[],null,["# tf.keras.ops.rfft\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/keras-team/keras/tree/v3.3.3/keras/src/ops/math.py#L488-L525) |\n\nReal-valued Fast Fourier Transform along the last axis of the input. \n\n tf.keras.ops.rfft(\n x, fft_length=None\n )\n\nComputes the 1D Discrete Fourier Transform of a real-valued signal over the\ninner-most dimension of input.\n\nSince the Discrete Fourier Transform of a real-valued signal is\nHermitian-symmetric, RFFT only returns the `fft_length / 2 + 1` unique\ncomponents of the FFT: the zero-frequency term, followed by the\n`fft_length / 2` positive-frequency terms.\n\nAlong the axis RFFT is computed on, if `fft_length` is smaller than the\ncorresponding dimension of the input, the dimension is cropped. If it is\nlarger, the dimension is padded with zeros.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|--------------|-----------------------------------------------------------------------------------------------------------------------------------------------------|\n| `x` | Input tensor. |\n| `fft_length` | An integer representing the number of the fft length. If not specified, it is inferred from the length of the last axis of `x`. Defaults to `None`. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A tuple containing two tensors - the real and imaginary parts of the output. ||\n\n\u003cbr /\u003e\n\n#### Examples:\n\n x = keras.ops.convert_to_tensor([0.0, 1.0, 2.0, 3.0, 4.0])\n rfft(x)\n (array([10.0, -2.5, -2.5]), array([0.0, 3.4409548, 0.81229924]))\n\n rfft(x, 3)\n (array([3.0, -1.5]), array([0.0, 0.8660254]))"]]
View source on GitHub