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use crate::{Buffer, Input, Node, BoxedNodeSend, NodeData, Message, impl_to_boxed_nodedata};
use hashbrown::HashMap;
#[derive(Debug, Clone)]
pub struct ResonantLowPassFilter {
pattern: Vec<(f32, f32)>,
span: f32,
bpm: f32,
sr: usize,
cutoff: f32,
q: f32,
x0: f32,
x1: f32,
x2: f32,
y1: f32,
y2: f32,
step: usize,
input_order: Vec<usize>,
}
impl ResonantLowPassFilter {
pub fn new() -> Self {
Self {
pattern: vec![],
span: 1.,
bpm: 120.,
sr: 44100,
step: 0,
cutoff: 20.,
q: 1.0,
x0: 0.,
x1: 0.,
x2: 0.,
y1: 0.,
y2: 0.,
input_order: vec![]
}
}
pub fn pattern(self, pattern: Vec<(f32, f32)>) -> Self {
Self {pattern, ..self}
}
pub fn span(self, span: f32) -> Self {
Self {span, ..self}
}
pub fn bpm(self, bpm: f32) -> Self {
Self {bpm, ..self}
}
pub fn sr(self, sr: usize) -> Self {
Self {sr, ..self}
}
pub fn cutoff(self, cutoff: f32) -> Self {
Self {cutoff, ..self}
}
pub fn q(self, q: f32) -> Self {
Self {q, ..self}
}
impl_to_boxed_nodedata!();
}
impl<const N: usize> Node<N> for ResonantLowPassFilter {
fn process(&mut self, inputs: &mut HashMap<usize, Input<N>>, output: &mut [Buffer<N>]) {
match inputs.len() {
1 => {
let cycle_dur = 60. / self.bpm * 4.;
let bar_dur = cycle_dur * self.span * self.sr as f32;
for i in 0..N {
for event in &self.pattern {
if (self.step % (bar_dur as usize)) == ((event.1 * cycle_dur * self.sr as f32) as usize) {
self.cutoff = event.0
}
}
let main_input = inputs.values_mut().next().unwrap();
let theta_c = 2.0 * std::f32::consts::PI * self.cutoff / self.sr as f32;
let d = 1.0 / self.q;
let beta = 0.5 * (1.0-d*theta_c.sin()/2.0) / (1.0+d*theta_c.sin()/2.0);
let gama = (0.5 + beta) * theta_c.cos();
let a0 = (0.5 + beta - gama) / 2.0;
let a1 = 0.5 + beta - gama;
let a2 = (0.5 + beta - gama) / 2.0;
let b1 = -2.0 * gama;
let b2 = 2.0 * beta;
let x0 = main_input.buffers()[0][i];
let y = a0 * self.x0 + a1 * self.x1 + a2 * self.x2
- b1 * self.y1 - b2 * self.y2;
output[0][i] = y;
self.x2 = self.x1;
self.x1 = x0;
self.y2 = self.y1;
self.y1 = y;
self.step += 1;
}
},
2 => {
let main_input = &inputs[&self.input_order[0]]; let ref_input = &inputs[&self.input_order[1]]; let theta_c = 2.0 * std::f32::consts::PI * ref_input.buffers()[0][0] / self.sr as f32;
let d = 1.0 / self.q;
let beta = 0.5 * (1.0-d*theta_c.sin()/2.0) / (1.0+d*theta_c.sin()/2.0);
let gama = (0.5 + beta) * theta_c.cos();
let a0 = (0.5 + beta - gama) / 2.0;
let a1 = 0.5 + beta - gama;
let a2 = (0.5 + beta - gama) / 2.0;
let b1 = -2.0 * gama;
let b2 = 2.0 * beta;
for i in 0..N {
let x0 = main_input.buffers()[0][i];
let y = a0 * self.x0 + a1 * self.x1 + a2 * self.x2 - b1 * self.y1 - b2 * self.y2;
output[0][i] = y;
self.x2 = self.x1;
self.x1 = x0;
self.y2 = self.y1;
self.y1 = y;
self.step += 1;
}
},
_ => {return ()}
}
}
fn send_msg(&mut self, info: Message) {
match info {
Message::SetPattern(p, span) => {
self.pattern = p;
self.span = span;
},
Message::SetToNumber(pos, value) => {
match pos {
0 => {self.cutoff = value},
1 => {self.q = value},
_ => {}
}
},
Message::Index(i) => {
self.input_order.push(i)
},
Message::IndexOrder(pos, index) => {
self.input_order.insert(pos, index)
},
Message::ResetOrder => {
self.input_order.clear();
},
_ => {}
}
}
}