Expand description
omni-wave
Easy to use DWT (Discrete Wavelet Transform) library, no need to worry about padding, and a variety of wavelets are available.
CAUTION: My knowledge can’t vouch for it being “correct”, but it does “concentrate energy” and “reconstruct perfectly”.
use approx::assert_abs_diff_eq;
use ndarray::{Array1, Array2, Axis};
use omni_wave::*;
let wavelet = wavelet::BIOR_3_1;
let love = Array2::from_shape_vec((8, 8),
vec![0., 0., 0., 0., 0., 0., 0., 0.,
0., 0.,99., 0., 0.,99., 0., 0.,
0.,99.,99.,99.,99.,99.,99., 0.,
0.,99.,99.,99.,99.,99.,99., 0.,
0.,99.,99.,99.,99.,99.,99., 0.,
0., 0.,99.,99.,99.,99., 0., 0.,
0., 0., 0.,99.,99., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0.,]).unwrap();
let mut signal = love.clone();
let mut buffer = Array1::zeros(signal.len_of(Axis(0)) + wavelet.window_size() - 2); // The minimum length of a buffer
completely_decompose_2d(signal.view_mut(), buffer.view_mut(), wavelet);
completely_reconstruct_2d(signal.view_mut(), buffer.view_mut(), wavelet);
love.into_iter()
.zip(signal)
.for_each(|(a, b)| assert_abs_diff_eq!(a, b, epsilon = 0.0001));
Features
f64
- The default primitive type used for calculations isf32
. Enable this feature to switch tof64
.
Knowledges
Signal
The data need to transform. The length should be even. Failure to meet the length requirement may not result a panic, but the behavior of functions will be undefined.
The left half of the input will be considered as Approx, while the right half will be considered as Detail.
Padding
The extension of a signal when processing. Our filling method named periodic
(in PyWavelets), ppd
(in Matlab) or wrap
(in numpy.pad).
[ A.B.C.D.E.F.G.H ] a.b.c.d ...
↑^^^^^^^^^^^^^^ ↑^^^^^^
Original signal Padding: automatically fill & detach.
Originally, I planned to provide more extension mode, but found that the first coefficient of wavelets such as bior2.2
is zero… Wouldn’t the information be lost in this way? ? So currently only periodic
mode is provided. Let me know if you have a better suggestion.
Buffer
Temporary buffer for calculations. For performance, it is strongly recommended that it be contiguous in memory.
window_size
The number of wavelet coefficients.
Modules
- Thanks to Wavelet Browser!
Structs
- Check
wavelet
to see all the wavelets provided.
Functions
- Forward wavelet transform, 1D, completely, inplace.
- Forward wavelet transform, 2D, completely, inplace.
- Inverse wavelet transform, 1D, completely, inplace.
- Inverse wavelet transform, 2D, completely, inplace.
- Forward wavelet transform, 1D, only once, inplace.
- Forward wavelet transform, 2D, only twice, inplace.
- Inverse wavelet transform, 1D, only once, inplace.
- Inverse wavelet transform, 2D, only twice, inplace.