Trait basic_dsp_vector::FrequencyToTimeDomainOperations [−] [src]

pub trait FrequencyToTimeDomainOperations<S, T>: ToTimeResult where S: ToSliceMut<T>, T: RealNumber {
    fn plain_ifft<B>(self, buffer: &mut B) -> Self::TimeResult where B: Buffer<S, T>;
    fn ifft<B>(self, buffer: &mut B) -> Self::TimeResult where B: Buffer<S, T>;
    fn windowed_ifft<B>(self,
                    buffer: &mut B,
                    window: &WindowFunction<T>)
                    -> Self::TimeResult where B: Buffer<S, T>;
}

Defines all operations which are valid on DataVecs containing frequency domain data.

Failures

All operations in this trait set self.len() to 0 if the vector isn't in frequency domain and complex number space.

Required Methods

Performs an Inverse Fast Fourier Transformation transforming a frequency domain vector into a time domain vector.

This version of the IFFT neither applies a window nor does it scale the vector.

Example

use std::f32;
use basic_dsp_vector::*;
let vector = vec!(0.0, 0.0, 1.0, 0.0, 0.0, 0.0).to_complex_freq_vec();
let mut buffer = SingleBuffer::new();
let result = vector.plain_ifft(&mut buffer);
let actual = &result[..];
let expected = &[1.0, 0.0, -0.5, 0.8660254, -0.5, -0.8660254];
assert_eq!(actual.len(), expected.len());
for i in 0..actual.len() {
       assert!(f32::abs(actual[i] - expected[i]) < 1e-4);
}

Performs an Inverse Fast Fourier Transformation transforming a frequency domain vector into a time domain vector.

Example

use std::f32;
use basic_dsp_vector::*;
let vector = vec!(0.0, 0.0, 0.0, 0.0, 3.0, 0.0).to_complex_freq_vec();
let mut buffer = SingleBuffer::new();
let result = vector.ifft(&mut buffer);
let actual = &result[..];
let expected = &[1.0, 0.0, -0.5, 0.8660254, -0.5, -0.8660254];
assert_eq!(actual.len(), expected.len());
for i in 0..actual.len() {
       assert!(f32::abs(actual[i] - expected[i]) < 1e-4);
}

Performs an Inverse Fast Fourier Transformation transforming a frequency domain vector into a time domain vector and removes the FFT window.

Implementors