Crates.io | ndrustfft |
lib.rs | ndrustfft |
version | 0.5.0 |
source | src |
created_at | 2021-07-04 10:58:39.666881 |
updated_at | 2024-08-18 14:06:09.827321 |
description | N-dimensional FFT, real-to-complex FFT and real-to-real DCT |
homepage | |
repository | https://github.com/preiter93/ndrustfft |
max_upload_size | |
id | 418534 |
size | 83,136 |
This library is a wrapper for RustFFT
, RustDCT
and RealFft
that enables performing FFTs and DCTs of complex- and real-valued
data on n-dimensional arrays (ndarray).
ndrustfft provides Handler structs for FFT's and DCTs, which must be provided alongside with the arrays to the respective functions (see below) . The Handlers implement a process function, which is a wrapper around Rustfft's process. Transforms along the outermost axis are in general the fastest, while transforms along other axis' will temporarily create copies of the input array.
The library ships all functions with a parallel version which leverages the parallel iterators of the ndarray crate.
fft
: [ndfft
], [ndfft_par
]ifft
: [ndifft
],[ndifft_par
]fft_r2c
: [ndfft_r2c
], [ndfft_r2c_par
],ifft_r2c
: [ndifft_r2c
],[ndifft_r2c_par
]dct1
: [nddct1
],[nddct1_par
]dct2
: [nddct2
],[nddct2_par
]dct3
: [nddct3
],[nddct3_par
]dct4
: [nddct4
],[nddct4_par
]2-Dimensional real-to-complex fft along first axis
use ndarray::{Array2, Dim, Ix};
use ndrustfft::{ndfft_r2c, Complex, R2cFftHandler};
let (nx, ny) = (6, 4);
let mut data = Array2::<f64>::zeros((nx, ny));
let mut vhat = Array2::<Complex<f64>>::zeros((nx / 2 + 1, ny));
for (i, v) in data.iter_mut().enumerate() {
*v = i as f64;
}
let mut fft_handler = R2cFftHandler::<f64>::new(nx);
ndfft_r2c(
&data.view(),
&mut vhat.view_mut(),
&mut fft_handler,
0,
);
RustFFT
, RustDCT
and RealFft
do not normalise,
while this library applies normalization as scipy by default.
This means, inverse ffts are divided by a factor of data.len()
,
and dcts are multiplied by two. It is possible to switch from the
default normalization to no normalization, or to apply a custom
normalization by using the normalization builder.
See: examples/fft_norm
ndarrays
+ rayon
(enabled by default)rustfft
's avx feature (enabled by default)rustfft
's sse feature (enabled by default)rustfft
's neon feature (enabled by default)License: MIT