The `siraph` crate is a node-based digital signal processing crate. # Features * **nodes:** Adds the `nodes` module that contains a couple of basic useful nodes as `Map` or `Const`. This feature is enabled by default. * **math:** Adds the `nodes::math` module that contains useful nodes related to mathematics as `Add` or `Oscillator`. This feature depends on the `num-traits` crate and the `nodes` feature. * **random:** Adds the `nodes::random` module that contains useful nodes related to random number generators as `SampleAndHold`. This feature depends on the `rand` crate and the `nodes` feature. # Example ```rust // Using the `nodes` feature use siraph::Graph; use siraph::nodes::{Hold, Pulse, FromIter, Map}; let mut graph = Graph::new(); // First, we can insert nodes into the graph. // This node just takes the values given by an iterator // and send them into its output. let from_iter = graph.insert(FromIter::new(std::iter::successors(Some(0u32), |&i| Some(i + 1)))); // This node infinitly outputs 4 `false` then 1 `true`. let pulse = graph.insert(Pulse::new(4)); // This one wait for a pulse and holds the value its has in its input // until a new pulse. let hold = graph.insert(Hold::::new()); // Simply uses the given function to maps its input to its output. let map = graph.insert(Map::new(|val: u32| val * val)); // Then, we can plug them together. graph.plug(from_iter, "output", hold, "input").unwrap(); graph.plug(pulse, "output", hold, "resample").unwrap(); graph.plug(hold, "output", map, "input").unwrap(); // Once our graph is done, we can retreive values from it using a sink. let mut sink = graph.sink(map, "output").unwrap(); // Here is a simple schem of what we have so far /* +------------------------+ | from_iter output i32 >----+ +------------------------------+ +------------------------+ +---> input | +----------------------+ | hold output i32 >--> input map output > sink +---> resample | +----------------------+ +---------------------+ | +------------------------------+ | pulse output bool >-------+ +---------------------+ */ // Values can be retreived with the `next` function on the sink // Once again, the `()` is the context provided to the nodes. assert_eq!(sink.next(), Some(0)); assert_eq!(sink.next(), Some(0)); assert_eq!(sink.next(), Some(0)); assert_eq!(sink.next(), Some(0)); assert_eq!(sink.next(), Some(0)); assert_eq!(sink.next(), Some(25)); assert_eq!(sink.next(), Some(25)); assert_eq!(sink.next(), Some(25)); assert_eq!(sink.next(), Some(25)); assert_eq!(sink.next(), Some(25)); // The sink is an iterator for (i, val) in sink.take(1000).enumerate() { let i = ((i/5)*5) as u32 + 10; assert_eq!(val, i*i) } ``` ## Create your own nodes You can create your own nodes using the `Node` trait. ```rust use siraph::{Node, Register, Input, Output}; // Our node will take an input and smooth it using a basic interpolation function. #[derive(Default)] pub struct Smooth { input: Input, output: Output, last_value: Option, } impl Node for Smooth { fn register(&self, r: &mut Register) { // This function will register the inputs and outputs of this node. r.input("input", &self.input); r.output("output", &self.output); } fn process(&mut self) { // It is in this function that all the processing will be done. const X: f64 = 1.0/3.0; // In our case, our computation is not very expensive but // in other cases, things can get complicated. // We can skip certain part of the processing by // checking if our outputs are used. if self.output.is_used() { if let Some(cur) = self.input.get() { if let Some(last) = self.last_value { self.last_value = Some(last * X + (1.0 - X) * cur); self.output.set(self.last_value); } else { self.output.set(cur); self.last_value = Some(cur); } } else { self.output.set(None); } } } fn reset(&mut self) { // In this function, the inputs of the node should not be used even // if they may return valid values. self.last_value = None; } } ``` # Todo List - [ ] Load VSTs as nodes