pub struct GoodThomasAlgorithm<T> { /* private fields */ }
Expand description

Implementation of the Good-Thomas Algorithm (AKA Prime Factor Algorithm)

This algorithm factors a size n FFT into n1 * n2, where GCD(n1, n2) == 1

Conceptually, this algorithm is very similar to the Mixed-Radix, except because GCD(n1, n2) == 1 we can do some number theory trickery to reduce the number of floating-point multiplications and additions. Additionally, It can be faster than Mixed-Radix at sizes below 10,000 or so.

// Computes a forward FFT of size 1200, using the Good-Thomas Algorithm
use rustfft::algorithm::GoodThomasAlgorithm;
use rustfft::{Fft, FftPlanner};
use rustfft::num_complex::Complex;
use rustfft::num_traits::Zero;

let mut buffer = vec![Complex{ re: 0.0f32, im: 0.0f32 }; 1200];

// we need to find an n1 and n2 such that n1 * n2 == 1200 and GCD(n1, n2) == 1
// n1 = 48 and n2 = 25 satisfies this
let mut planner = FftPlanner::new();
let inner_fft_n1 = planner.plan_fft_forward(48);
let inner_fft_n2 = planner.plan_fft_forward(25);

// the good-thomas FFT length will be inner_fft_n1.len() * inner_fft_n2.len() = 1200
let fft = GoodThomasAlgorithm::new(inner_fft_n1, inner_fft_n2);
fft.process(&mut buffer);

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impl<T: FftNum> GoodThomasAlgorithm<T>

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pub fn new(width_fft: Arc<dyn Fft<T>>, height_fft: Arc<dyn Fft<T>>) -> Self

Creates a FFT instance which will process inputs/outputs of size width_fft.len() * height_fft.len()

GCD(width_fft.len(), height_fft.len()) must be equal to 1

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impl<T: FftNum> Direction for GoodThomasAlgorithm<T>

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fn fft_direction(&self) -> FftDirection

Returns FftDirection::Forward if this instance computes forward FFTs, or FftDirection::Inverse for inverse FFTs
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impl<T: FftNum> Fft<T> for GoodThomasAlgorithm<T>

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fn process_outofplace_with_scratch( &self, input: &mut [Complex<T>], output: &mut [Complex<T>], scratch: &mut [Complex<T>] )

Divides input and output into chunks of size self.len(), and computes a FFT on each chunk. Read more
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fn process_with_scratch( &self, buffer: &mut [Complex<T>], scratch: &mut [Complex<T>] )

Divides buffer into chunks of size self.len(), and computes a FFT on each chunk. Read more
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fn get_inplace_scratch_len(&self) -> usize

Returns the size of the scratch buffer required by process_with_scratch Read more
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fn get_outofplace_scratch_len(&self) -> usize

Returns the size of the scratch buffer required by process_outofplace_with_scratch Read more
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fn process(&self, buffer: &mut [Complex<T>])

Computes a FFT in-place. Read more
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impl<T: FftNum> Length for GoodThomasAlgorithm<T>

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fn len(&self) -> usize

The FFT size that this algorithm can process

Auto Trait Implementations§

Blanket Implementations§

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impl<T> Any for T
where T: 'static + ?Sized,

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fn type_id(&self) -> TypeId

Gets the TypeId of self. Read more
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impl<T> Borrow<T> for T
where T: ?Sized,

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fn borrow(&self) -> &T

Immutably borrows from an owned value. Read more
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impl<T> BorrowMut<T> for T
where T: ?Sized,

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fn borrow_mut(&mut self) -> &mut T

Mutably borrows from an owned value. Read more
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impl<T> From<T> for T

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fn from(t: T) -> T

Returns the argument unchanged.

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impl<T, U> Into<U> for T
where U: From<T>,

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fn into(self) -> U

Calls U::from(self).

That is, this conversion is whatever the implementation of From<T> for U chooses to do.

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impl<T, U> TryFrom<U> for T
where U: Into<T>,

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type Error = Infallible

The type returned in the event of a conversion error.
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fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>

Performs the conversion.
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impl<T, U> TryInto<U> for T
where U: TryFrom<T>,

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type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.
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fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>

Performs the conversion.