Add part of an FIR crossover
This includes an algorithm that efficiently converts biquad coefficients to a linear-phase FIR filter kernel.
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// You should have received a copy of the GNU General Public License
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// along with this program. If not, see <https://www.gnu.org/licenses/>.
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pub mod fir;
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pub mod iir;
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317
plugins/crossover/src/crossover/fir.rs
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317
plugins/crossover/src/crossover/fir.rs
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// Crossover: clean crossovers as a multi-out plugin
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// Copyright (C) 2022 Robbert van der Helm
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//
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// This program is free software: you can redistribute it and/or modify
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// it under the terms of the GNU General Public License as published by
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// the Free Software Foundation, either version 3 of the License, or
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// (at your option) any later version.
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//
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// This program is distributed in the hope that it will be useful,
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// but WITHOUT ANY WARRANTY; without even the implied warranty of
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU General Public License
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// along with this program. If not, see <https://www.gnu.org/licenses/>.
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use nih_plug::buffer::ChannelSamples;
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use nih_plug::debug::*;
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use std::f32;
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use std::simd::{f32x2, StdFloat};
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use crate::biquad::{Biquad, BiquadCoefficients};
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use crate::NUM_BANDS;
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// TODO: These filters would be more efficient when processing four samples at a time instead of
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// processing two channels at a time. But this keeps the interface nicer.
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/// The size of the FIR filter window, or the number of taps.
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const FILTER_SIZE: usize = 121;
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/// The size of the FIR filter's ring buffer. This is `FILTER_SIZE` rounded up to the next power of
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/// two.
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const RING_BUFFER_SIZE: usize = FILTER_SIZE.next_power_of_two();
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#[derive(Debug)]
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pub struct FirCrossover {
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/// The kind of crossover to use. `.update_filters()` must be called after changing this.
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mode: FirCrossoverType,
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/// Filters for each of the bands. Depending on the number of bands argument passed to
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/// `.process()` two to five of these may be used. The first one always contains a low-pass
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/// filter, the last one always contains a high-pass filter, while the other bands will contain
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/// band-pass filters.
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band_filters: [FirFilter; NUM_BANDS],
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}
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/// The type of FIR crossover to use.
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#[derive(Debug, Clone, Copy)]
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pub enum FirCrossoverType {
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/// Emulates the filter slope of [`super::iir::IirCrossoverType`], but with linear-phase FIR
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/// filters instead of minimum-phase IIR filters. The exact same filters are used to design the
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/// FIR filters.
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LinkwitzRiley24LinearPhase,
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}
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/// A single FIR filter that may be configured in any way. In this plugin this will be a
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/// linear-phase low-pass, band-pass, or high-pass filter.
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#[derive(Debug, Clone)]
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struct FirFilter {
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/// The coefficients for this filter. The filters for both channels should be equivalent, this
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/// just avoids broadcasts in the filter process.
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///
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/// TODO: Profile to see if storing this as f32x2 rather than f32s plus splatting makes any
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/// difference in performance at all
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coefficients: FirCoefficients,
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/// A ring buffer storing the last `FILTER_SIZE - 1` samples. The capacity is `FILTER_SIZE`
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/// rounded up to the next power of two.
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delay_buffer: [f32x2; RING_BUFFER_SIZE],
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/// The index in `delay_buffer` to write the next sample to. Wrapping negative indices back to
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/// the end, the previous sample can be found at `delay_buffer[delay_buffer_next_idx - 1]`, the
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/// one before that at `delay_buffer[delay_buffer_next_idx - 2]`, and so on.
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delay_buffer_next_idx: usize,
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}
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/// Coefficients for an FIR filter. This struct includes ways to design the filter. Parameterized
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/// over `f32x2` only for the time being since that's what we need here.
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#[repr(transparent)]
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#[derive(Debug, Clone)]
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struct FirCoefficients([f32x2; FILTER_SIZE]);
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impl Default for FirFilter {
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fn default() -> Self {
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Self {
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coefficients: FirCoefficients::default(),
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delay_buffer: [f32x2::default(); RING_BUFFER_SIZE],
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delay_buffer_next_idx: 0,
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}
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}
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}
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impl Default for FirCoefficients {
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fn default() -> Self {
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// Initialize this to a delay with the same amount of latency as we'd introduce with our
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// linear-phase filters
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let mut coefficients = [f32x2::default(); FILTER_SIZE];
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coefficients[FILTER_SIZE / 2] = f32x2::splat(1.0);
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Self(coefficients)
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}
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}
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impl FirCrossover {
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/// Create a new multiband crossover processor. All filters will be configured to pass audio
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/// through as is, albeit with a delay. `.update()` needs to be called first to set up the
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/// filters, and `.reset()` can be called whenever the filter state must be cleared.
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///
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/// Make sure to add the latency reported by [`latency()`][Self::latency()] to the plugin's
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/// reported latency.
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pub fn new(mode: FirCrossoverType) -> Self {
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Self {
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mode,
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band_filters: Default::default(),
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}
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}
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/// Get the current latency in samples. This depends on the selected mode.
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pub fn latency(&self) -> usize {
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// Actually, that's a lie, since we currently only do linear-phase filters with a constant
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// size
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match self.mode {
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FirCrossoverType::LinkwitzRiley24LinearPhase => FILTER_SIZE / 2,
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}
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}
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/// Split the signal into bands using the crossovers previously configured through `.update()`.
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/// The split bands will be written to `band_outputs`. `main_io` is not written to, and should
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/// be cleared separately.
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pub fn process(
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&mut self,
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num_bands: usize,
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main_io: &ChannelSamples,
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mut band_outputs: [ChannelSamples; NUM_BANDS],
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) {
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nih_debug_assert!(num_bands >= 2);
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nih_debug_assert!(num_bands <= NUM_BANDS);
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// Required for the SIMD, so we'll just do a hard assert or the unchecked conversions will
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// be unsound
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assert!(main_io.len() == 2);
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let mut samples: f32x2 = unsafe { main_io.to_simd_unchecked() };
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match self.mode {
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FirCrossoverType::LinkwitzRiley24LinearPhase => {
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todo!();
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}
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}
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}
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/// Update the crossover frequencies for all filters.
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pub fn update(
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&mut self,
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sample_rate: f32,
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num_bands: usize,
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frequencies: [f32; NUM_BANDS - 1],
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) {
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match self.mode {
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FirCrossoverType::LinkwitzRiley24LinearPhase => todo!(),
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}
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}
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/// Reset the internal filter state for all crossovers.
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pub fn reset(&mut self) {
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for filter in &mut self.band_filters {
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filter.reset();
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}
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}
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}
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impl FirFilter {
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/// Process left and right audio samples through the filter.
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pub fn process(&mut self, samples: f32x2) -> f32x2 {
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// TODO: Replace direct convolution with FFT convolution, would make the implementation much
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// more complex though because of the multi output part
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let coefficients = &self.coefficients.0;
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let mut result = coefficients[0] * samples;
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// Now multiply `self.coefficients[1..]` with the delay buffer starting at
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// `self.delay_buffer_next_idx - 1`, wrapping around to the end when that is reached
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// The end index is exclusive, and we already did the multiply+add for the first coefficient.
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let before_wraparound_start_idx = self
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.delay_buffer_next_idx
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.saturating_sub(coefficients.len() - 1);
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let before_wraparound_end_idx = self.delay_buffer_next_idx;
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let num_before_wraparound = before_wraparound_end_idx - before_wraparound_start_idx;
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for (coefficient, delayed_sample) in coefficients[1..1 + num_before_wraparound].iter().zip(
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self.delay_buffer[before_wraparound_start_idx..before_wraparound_end_idx]
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.iter()
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.rev(),
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) {
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// `result += coefficient * sample`, but with explicit FMA
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result = coefficient.mul_add(*delayed_sample, result);
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}
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let after_wraparound_begin_idx =
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self.delay_buffer.len() - (coefficients.len() - num_before_wraparound);
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let after_wraparound_end_idx = self.delay_buffer.len();
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for (coefficient, delayed_sample) in coefficients[1 + num_before_wraparound..].iter().zip(
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self.delay_buffer[after_wraparound_begin_idx..after_wraparound_end_idx]
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.iter()
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.rev(),
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) {
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result = coefficient.mul_add(*delayed_sample, result);
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}
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// And finally write the samples to the delay buffer for the enxt sample
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self.delay_buffer[self.delay_buffer_next_idx] = samples;
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self.delay_buffer_next_idx = (self.delay_buffer_next_idx + 1) % self.delay_buffer.len();
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result
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}
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/// Update the coefficients for all filters in the crossover.
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pub fn update_coefficients(&mut self, coefs: FirCoefficients) {
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self.coefficients = coefs;
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}
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/// Reset the internal filter state.
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pub fn reset(&mut self) {
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self.delay_buffer.fill(f32x2::default());
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self.delay_buffer_next_idx = 0;
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}
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}
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impl FirCoefficients {
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/// A somewhat crude but very functional and relatively fast way create a linear phase FIR
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/// **low-pass** filter that matches the frequency response of a biquad filter. This normalizes
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/// the result, so biquad coefficients for high- and band-pass filters will not work correctly.
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/// The algorithm works as follows:
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///
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/// - An impulse function (so all zeroes except for the first element) of length `FILTER_LEN / 2
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/// + 1` is filtered with the biquad.
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/// - The biquad's state is reset, and the impulse response is filtered in the opposite
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/// direction.
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/// - At this point the bidirectionally filtered impulse response contains the **right** half of
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/// a truncated linear phase FIR kernel.
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///
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/// Since the FIR filter will be a symmetrical version of this impulse response, we can optimize
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/// the post-processing work slightly by windowing and normalizing this bidirectionally filtered
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/// impulse response instead.
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///
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/// - A half Blackman window is applied to the impulse response. Since this is the right half,
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/// this starts at unity gain for the first sample and then tapers off towards the right.
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/// - The impulse response is then normalized such that the final linear-phase FIR kernel has a
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/// sum of 1.0. Since it will be symmetrical around the IRs first sample, the would-be final
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/// sum can be computed as `ir.sum() * 2 - ir[0]`>
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///
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/// Lastly the linear phase FIR filter simply needs to be constructed from this right half:
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///
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/// - This bidirectionally filtered impulse response is then reversed, and placed at the start
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/// of the `FILTER_LEN` size FIR coefficient array.
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/// - The non-reversed bidirectionally filtered impulse response is copied to the second half of
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/// the coefficients. (one of the copies doesn't need to include the centermost coefficient)
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///
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/// The corresponding high-pass filter can be computed through spectral inversion.
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pub fn design_linear_phase_low_pass_from_biquad(
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biquad_coefs: BiquadCoefficients<f32x2>,
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) -> Self {
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// We'll start with an impulse...
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let mut impulse_response = [f32x2::default(); FILTER_SIZE / 2 + 1];
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impulse_response[0] = f32x2::splat(1.0);
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// ...and filter that in both directions
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let mut biquad = Biquad::default();
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biquad.coefficients = biquad_coefs;
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for sample in impulse_response.iter_mut() {
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*sample = biquad.process(*sample);
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}
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biquad.reset();
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for sample in impulse_response.iter_mut().rev() {
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*sample = biquad.process(*sample);
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}
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// Now `impulse_response` contains a truncated right half of the linear-phase FIR filter. We
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// can apply the window function here, and then normalize it so that the the final FIR
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// filter kernel sums to 1.
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// Adopted from `nih_plug::util::window`
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let blackman_scale_1 = (2.0 * f32::consts::PI) / (impulse_response.len() - 1) as f32;
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let blackman_scale_2 = blackman_scale_1 * 2.0;
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// We only apply the right half of the window, starting at the top of the window
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let blackman_offset = impulse_response.len() / 2;
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for (sample_idx, sample) in impulse_response.iter_mut().enumerate() {
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let i = sample_idx + blackman_offset;
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let cos_1 = (blackman_scale_1 * i as f32).cos();
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let cos_2 = (blackman_scale_2 * i as f32).cos();
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*sample *= f32x2::splat(0.42 - (0.5 * cos_1) + (0.08 * cos_2));
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}
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// Since this final filter will be symmetrical around
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// `impulse_response[0]`, we can simply normalized based on that fact:
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let would_be_coefficients_sum =
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impulse_response.iter().sum::<f32x2>() * f32x2::splat(2.0) - impulse_response[0];
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let would_be_coefficients_recip = would_be_coefficients_sum.recip();
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for sample in &mut impulse_response {
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*sample *= would_be_coefficients_recip;
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}
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// And finally we can simply build the filter from the processed impulse response (which,
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// again, corresponds to the right half of the final linear-phase filter kernel with the
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// first sample in the IR being the middlemost element in the kernel)
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let mut coefficients = [f32x2::default(); FILTER_SIZE];
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for (coefficient, ir_sample) in coefficients
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.iter_mut()
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.take(impulse_response.len() / 2 - 1)
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// We won't copy the very first sample of the IR here, that will be part of the second
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// (non-reversed) half
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.zip(impulse_response.iter().skip(1).rev())
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{
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*coefficient = *ir_sample;
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}
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// And the second half can be a simple memcpy
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coefficients[impulse_response.len() / 2..].copy_from_slice(&impulse_response);
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Self(coefficients)
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}
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}
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@ -75,7 +75,7 @@ struct AllPassCascade {
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impl IirCrossover {
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/// Create a new multiband crossover processor. All filters will be configured to pass audio
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/// through as it. `.update()` needs to be called first to set up the filters, and `.reset()`
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/// through as is. `.update()` needs to be called first to set up the filters, and `.reset()`
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/// can be called whenever the filter state must be cleared.
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pub fn new(mode: IirCrossoverType) -> Self {
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Self {
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@ -126,9 +126,7 @@ impl IirCrossover {
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}
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}
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/// Update the crossover frequencies for all filters. If the frequencies are not monotonic then
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/// this function will ensure that they are. The active number of bands is used to make sure
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/// unused bands are not part of the normalization.
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/// Update the crossover frequencies for all filters.
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pub fn update(
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&mut self,
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sample_rate: f32,
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