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use super::super::{
Buffer, ComplexNumberSpace, DataDomain, DspVec, ErrorReason, FloatIndex, FrequencyDomain,
FrequencyDomainOperations, InsertZerosOpsBuffered, MetaData, RededicateForceOps, ScaleOps,
TimeDomainOperations, ToRealTimeResult, ToSliceMut, ToTimeResult, TransRes, Vector,
};
use super::fft;
use crate::multicore_support::*;
use crate::numbers::*;
use crate::window_functions::*;
use rustfft::FftDirection;
/// 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.
pub trait FrequencyToTimeDomainOperations<S, T>: ToTimeResult
where
S: ToSliceMut<T>,
T: RealNumber,
{
/// 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::*;
/// # use num_complex::Complex;
/// let vector = vec!(Complex::new(0.0, 0.0), Complex::new(1.0, 0.0), Complex::new(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 = &[Complex::new(1.0, 0.0), Complex::new(-0.5, 0.8660254), Complex::new(-0.5, -0.8660254)];
/// assert_eq!(actual.len(), expected.len());
/// for i in 0..actual.len() {
/// assert!((actual[i] - expected[i]).norm() < 1e-4);
/// }
/// ```
fn plain_ifft<B>(self, buffer: &mut B) -> Self::TimeResult
where
B: for<'a> Buffer<'a, S, T>;
/// Performs an Inverse Fast Fourier Transformation transforming a frequency domain vector
/// into a time domain vector.
/// # Example
///
/// ```
/// use std::f32;
/// use basic_dsp_vector::*;
/// # use num_complex::Complex;
/// let vector = vec!(Complex::new(0.0, 0.0), Complex::new(0.0, 0.0), Complex::new(3.0, 0.0)).to_complex_freq_vec();
/// let mut buffer = SingleBuffer::new();
/// let result = vector.ifft(&mut buffer);
/// let actual = &result[..];
/// let expected = &[Complex::new(1.0, 0.0), Complex::new(-0.5, 0.8660254), Complex::new(-0.5, -0.8660254)];
/// assert_eq!(actual.len(), expected.len());
/// for i in 0..actual.len() {
/// assert!((actual[i] - expected[i]).norm() < 1e-4);
/// }
/// ```
fn ifft<B>(self, buffer: &mut B) -> Self::TimeResult
where
B: for<'a> Buffer<'a, S, T>;
/// Performs an Inverse Fast Fourier Transformation transforming a frequency domain vector
/// into a time domain vector and removes the FFT window.
fn windowed_ifft<B>(self, buffer: &mut B, window: &dyn WindowFunction<T>) -> Self::TimeResult
where
B: for<'a> Buffer<'a, S, T>;
}
/// Defines all operations which are valid on `DataVecs` containing frequency domain data and
/// the data is assumed to half of complex conjugate symmetric spectrum round 0 Hz where
/// the 0 Hz element itself is real.
/// # Failures
/// All operations in this trait set `self.len()` to `0` if the first element (0Hz)
/// isn't real.
pub trait SymmetricFrequencyToTimeDomainOperations<S, T>: ToRealTimeResult
where
S: ToSliceMut<T>,
T: RealNumber,
{
/// Performs a Symmetric Inverse Fast Fourier Transformation under the assumption that `self`
/// contains half of a symmetric spectrum starting from 0 Hz. This assumption
/// isn't verified and no error is raised if the spectrum isn't symmetric. The reason
/// for this is that there is no robust verification possible.
///
/// The argument indicates whether the resulting real vector should have `2*N`
/// or `2*N-1` points.
///
/// This version of the IFFT neither applies a window nor does it scale the
/// vector.
fn plain_sifft<B>(self, buffer: &mut B) -> TransRes<Self::RealTimeResult>
where
B: for<'a> Buffer<'a, S, T>;
/// Performs a Symmetric Inverse Fast Fourier Transformation under the assumption that `self`
/// contains half of a symmetric spectrum starting from 0 Hz. This assumption
/// isn't verified and no error is raised if the spectrum isn't symmetric. The reason
/// for this is that there is no robust verification possible.
///
/// The argument indicates whether the resulting real vector should have `2*N` or
/// `2*N-1` points.
fn sifft<B>(self, buffer: &mut B) -> TransRes<Self::RealTimeResult>
where
B: for<'a> Buffer<'a, S, T>;
/// Performs a Symmetric Inverse Fast Fourier Transformation (SIFFT) and removes the FFT
/// window. The SIFFT is performed under the assumption that `self`
/// contains half of a symmetric spectrum starting from 0 Hz. This assumption
/// isn't verified and no error is raised if the spectrum isn't symmetric. The reason
/// for this is that there is no robust verification possible.
///
/// The argument indicates whether the resulting real vector should have `2*N` or `2*N-1`
/// points.
fn windowed_sifft<B>(
self,
buffer: &mut B,
window: &dyn WindowFunction<T>,
) -> TransRes<Self::RealTimeResult>
where
B: for<'a> Buffer<'a, S, T>;
}
impl<S, T, N, D> FrequencyToTimeDomainOperations<S, T> for DspVec<S, T, N, D>
where
DspVec<S, T, N, D>: ToTimeResult,
<DspVec<S, T, N, D> as ToTimeResult>::TimeResult:
RededicateForceOps<DspVec<S, T, N, D>> + TimeDomainOperations<S, T>,
S: ToSliceMut<T>,
T: RealNumber,
N: ComplexNumberSpace,
D: FrequencyDomain,
{
fn plain_ifft<B>(mut self, buffer: &mut B) -> Self::TimeResult
where
B: for<'a> Buffer<'a, S, T>,
{
if self.domain() != DataDomain::Frequency {
self.mark_vector_as_invalid();
self.number_space.to_complex();
self.domain.to_freq();
return Self::TimeResult::rededicate_from_force(self);
}
if !self.is_complex() {
self.zero_interleave_b(buffer, 2);
self.number_space.to_complex();
}
fft(&mut self, buffer, FftDirection::Inverse);
self.domain.to_freq();
Self::TimeResult::rededicate_from_force(self)
}
fn ifft<B>(mut self, buffer: &mut B) -> Self::TimeResult
where
B: for<'a> Buffer<'a, S, T>,
{
let points = self.points();
self.scale(T::one() / T::from(points).unwrap());
self.ifft_shift();
self.plain_ifft(buffer)
}
fn windowed_ifft<B>(self, buffer: &mut B, window: &dyn WindowFunction<T>) -> Self::TimeResult
where
B: for<'a> Buffer<'a, S, T>,
{
let mut result = self.ifft(buffer);
result.unapply_window(window);
result
}
}
impl<S, T, N, D> SymmetricFrequencyToTimeDomainOperations<S, T> for DspVec<S, T, N, D>
where
DspVec<S, T, N, D>: ToRealTimeResult + ToTimeResult + FrequencyDomainOperations<S, T>,
<DspVec<S, T, N, D> as ToRealTimeResult>::RealTimeResult:
RededicateForceOps<DspVec<S, T, N, D>> + TimeDomainOperations<S, T>,
S: ToSliceMut<T>,
T: RealNumber,
N: ComplexNumberSpace,
D: FrequencyDomain,
{
fn plain_sifft<B>(mut self, buffer: &mut B) -> TransRes<Self::RealTimeResult>
where
B: for<'a> Buffer<'a, S, T>,
{
if self.domain() != DataDomain::Frequency || !self.is_complex() {
self.mark_vector_as_invalid();
self.number_space.to_complex();
self.domain.to_freq();
return Err((
ErrorReason::InputMustBeInFrequencyDomain,
Self::RealTimeResult::rededicate_from_force(self),
));
}
if self.points() > 0 && self.data(1).abs() > T::from(1e-10).unwrap() {
self.mark_vector_as_invalid();
self.number_space.to_complex();
self.domain.to_freq();
return Err((
ErrorReason::InputMustBeConjSymmetric,
Self::RealTimeResult::rededicate_from_force(self),
));
}
self.mirror(buffer);
fft(&mut self, buffer, FftDirection::Inverse);
self.domain.to_freq();
self.pure_complex_to_real_operation(buffer, |x, _arg| x.re, (), Complexity::Small);
Ok(Self::RealTimeResult::rededicate_from_force(self))
}
fn sifft<B>(mut self, buffer: &mut B) -> TransRes<Self::RealTimeResult>
where
B: for<'a> Buffer<'a, S, T>,
{
let points = self.points();
self.scale(Complex::<T>::new(
T::one() / T::from(points).unwrap(),
T::zero(),
));
self.ifft_shift();
self.plain_sifft(buffer)
}
fn windowed_sifft<B>(
self,
buffer: &mut B,
window: &dyn WindowFunction<T>,
) -> TransRes<Self::RealTimeResult>
where
B: for<'a> Buffer<'a, S, T>,
{
let mut result = self.sifft(buffer)?;
result.unapply_window(window);
Ok(result)
}
}