Stft
torch_stft(
input,
n_fft,
hop_length = NULL,
win_length = NULL,
window = NULL,
center = TRUE,
pad_mode = "reflect",
normalized = FALSE,
onesided = TRUE,
return_complex = NULL
)(Tensor) the input tensor
(int) size of Fourier transform
(int, optional) the distance between neighboring sliding window
frames. Default: NULL (treated as equal to floor(n_fft / 4))
(int, optional) the size of window frame and STFT filter.
Default: NULL (treated as equal to n_fft)
(Tensor, optional) the optional window function.
Default: NULL (treated as window of all \(1\) s)
(bool, optional) whether to pad input on both sides so
that the \(t\)-th frame is centered at time \(t \times \mbox{hop\_length}\).
Default: TRUE
(string, optional) controls the padding method used when
center is TRUE. Default: "reflect"
(bool, optional) controls whether to return the normalized
STFT results Default: FALSE
(bool, optional) controls whether to return half of results to
avoid redundancy Default: TRUE
(bool, optional) controls whether to return complex tensors or not.
Short-time Fourier transform (STFT).
Ignoring the optional batch dimension, this method computes the following
expression:
$$
X[m, \omega] = \sum_{k = 0}^{\mbox{win\_length-1}}%
\mbox{window}[k]\ \mbox{input}[m \times \mbox{hop\_length} + k]\ %
\exp\left(- j \frac{2 \pi \cdot \omega k}{\mbox{win\_length}}\right),
$$
where \(m\) is the index of the sliding window, and \(\omega\) is
the frequency that \(0 \leq \omega < \mbox{n\_fft}\). When
onesided is the default value TRUE,
* `input` must be either a 1-D time sequence or a 2-D batch of time
sequences.* If `hop_length` is `NULL` (default), it is treated as equal to
`floor(n_fft / 4)`.
* If `win_length` is `NULL` (default), it is treated as equal to
`n_fft`.
* `window` can be a 1-D tensor of size `win_length`, e.g., from
`torch_hann_window`. If `window` is `NULL` (default), it is
treated as if having \eqn{1} everywhere in the window. If
\eqn{\mbox{win\_length} < \mbox{n\_fft}}, `window` will be padded on
both sides to length `n_fft` before being applied.
* If `center` is `TRUE` (default), `input` will be padded on
both sides so that the \eqn{t}-th frame is centered at time
\eqn{t \times \mbox{hop\_length}}. Otherwise, the \eqn{t}-th frame
begins at time \eqn{t \times \mbox{hop\_length}}.
* `pad_mode` determines the padding method used on `input` when
`center` is `TRUE`. See `torch_nn.functional.pad` for
all available options. Default is `"reflect"`.
* If `onesided` is `TRUE` (default), only values for \eqn{\omega}
in \eqn{\left[0, 1, 2, \dots, \left\lfloor \frac{\mbox{n\_fft}}{2} \right\rfloor + 1\right]}
are returned because the real-to-complex Fourier transform satisfies the
conjugate symmetry, i.e., \eqn{X[m, \omega] = X[m, \mbox{n\_fft} - \omega]^*}.
* If `normalized` is `TRUE` (default is `FALSE`), the function
returns the normalized STFT results, i.e., multiplied by \eqn{(\mbox{frame\_length})^{-0.5}}.
Returns the real and the imaginary parts together as one tensor of size
\eqn{(* \times N \times T \times 2)}, where \eqn{*} is the optional
batch size of `input`, \eqn{N} is the number of frequencies where
STFT is applied, \eqn{T} is the total number of frames used, and each pair
in the last dimension represents a complex number as the real part and the
imaginary part.
This function changed signature at version 0.4.1. Calling with the previous signature may cause error or return incorrect result.