refactoring to allow different models
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2d3572e63b
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c3cc7f690e
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@ -1,8 +1,11 @@
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mod graph;
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mod graph;
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mod model;
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mod runner;
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mod runner;
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mod spring_model;
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mod spring_model;
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mod utils;
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mod utils;
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use std::sync::{Arc, RwLock};
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use pyo3::prelude::*;
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use pyo3::prelude::*;
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/// Formats the sum of two numbers as string.
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/// Formats the sum of two numbers as string.
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@ -13,8 +16,9 @@ fn layout_from_edge_list(
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iter: usize,
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iter: usize,
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threads: usize,
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threads: usize,
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) -> PyResult<Vec<(f32, f32)>> {
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) -> PyResult<Vec<(f32, f32)>> {
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let model = Arc::new(RwLock::new(spring_model::SimpleSpringModel::new(1.0)));
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let r = runner::Runner::new(iter, threads);
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let r = runner::Runner::new(iter, threads);
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Ok(r.layout(number_of_nodes, edges))
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Ok(r.layout(number_of_nodes, edges, model))
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}
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}
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/// A Python module implemented in Rust.
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/// A Python module implemented in Rust.
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@ -0,0 +1,7 @@
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use crate::graph::{EdgeMatrix, Node, NodeVector};
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pub trait ForceModel {
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fn init(&mut self, edges: EdgeMatrix, size: usize, iterations: usize);
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fn prepare(&mut self, _nodes: &NodeVector);
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fn step(&self, nodes: &NodeVector, i_node: usize) -> Node;
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}
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@ -1,5 +1,5 @@
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use crate::graph::{new_edge_matrix, new_node_vector, EdgeMatrix};
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use crate::graph::{new_edge_matrix, new_node_vector, EdgeMatrix};
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use crate::spring_model;
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use crate::model::ForceModel;
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use crate::utils;
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use crate::utils;
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use std::sync::{Arc, RwLock};
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use std::sync::{Arc, RwLock};
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use std::thread;
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use std::thread;
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@ -30,22 +30,21 @@ impl Runner {
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}
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}
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}
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}
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pub fn layout(
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pub fn layout<T: 'static + ForceModel + Sync + Send>(
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self: &Self,
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self: &Self,
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number_of_nodes: usize,
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number_of_nodes: usize,
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edge_list: Vec<(u32, u32)>,
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edge_list: Vec<(u32, u32)>,
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model: Arc<RwLock<T>>,
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) -> Vec<(f32, f32)> {
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) -> Vec<(f32, f32)> {
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// let edges = connection_matrix(size);
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// let edges = connection_matrix(size);
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let edges = edge_matrix_from_edge_list(number_of_nodes, edge_list);
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let edges = edge_matrix_from_edge_list(number_of_nodes, edge_list);
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let mut nodes = new_node_vector(number_of_nodes);
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let mut nodes = new_node_vector(number_of_nodes);
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let mut nodes_next = new_node_vector(number_of_nodes);
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let mut nodes_next = new_node_vector(number_of_nodes);
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// let model = Arc::new(RwLock::new(spring_model::InitialModel::new(edges, number_of_nodes)));
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model
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let model = Arc::new(RwLock::new(spring_model::MyModel::new(
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.write()
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edges,
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.unwrap()
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number_of_nodes,
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.init(edges, number_of_nodes, self.iterations);
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self.iterations,
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)));
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let chunks = utils::gen_chunks(number_of_nodes, self.threads);
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let chunks = utils::gen_chunks(number_of_nodes, self.threads);
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for _epoch in 0..self.iterations {
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for _epoch in 0..self.iterations {
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@ -1,32 +1,37 @@
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use crate::graph::{EdgeMatrix, Node, NodeVector};
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use crate::graph::{new_edge_matrix, EdgeMatrix, Node, NodeVector};
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use crate::model::ForceModel;
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pub struct MyModel {
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pub struct SimpleSpringModel {
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edges: EdgeMatrix,
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edges: EdgeMatrix,
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size: usize,
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size: usize,
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opt_dist: f32,
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c: f32,
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c: f32,
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dc: f32,
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dc: f32,
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}
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}
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impl MyModel {
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impl SimpleSpringModel {
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pub fn new(edges: EdgeMatrix, size: usize, iterations: usize) -> MyModel {
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pub fn new(c: f32) -> Self {
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let opt_dist = 1.0;
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SimpleSpringModel {
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let c = 0.1;
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edges: new_edge_matrix(0),
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size: 0,
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MyModel {
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c,
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edges,
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dc: 0.0,
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size,
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opt_dist,
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c: c,
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dc: c / ((iterations + 1) as f32),
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}
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}
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}
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}
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}
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pub fn prepare(&mut self, _nodes: &NodeVector) {
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impl ForceModel for SimpleSpringModel {
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fn init(&mut self, edges: EdgeMatrix, size: usize, iterations: usize) {
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let dc = self.c / ((iterations + 1) as f32);
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self.edges = edges;
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self.size = size;
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self.dc = dc;
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}
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fn prepare(&mut self, _nodes: &NodeVector) {
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self.c -= self.dc;
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self.c -= self.dc;
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}
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}
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pub fn step(&self, nodes: &NodeVector, i_node: usize) -> Node {
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fn step(&self, nodes: &NodeVector, i_node: usize) -> Node {
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let node = nodes[i_node].read().unwrap();
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let node = nodes[i_node].read().unwrap();
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let edges = self.edges.read().unwrap();
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let edges = self.edges.read().unwrap();
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@ -57,14 +62,14 @@ impl MyModel {
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let edge = edges[i_node][o].weight;
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let edge = edges[i_node][o].weight;
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if edge == 0.0 {
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if edge == 0.0 {
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let f_rep = dist.powi(2).recip().min(self.opt_dist);
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let f_rep = dist.powi(2).recip().min(1.0);
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let f_rep_x = f_rep * unit_x;
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let f_rep_x = f_rep * unit_x;
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let f_rep_y = f_rep * unit_y;
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let f_rep_y = f_rep * unit_y;
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sum_x -= f_rep_x;
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sum_x -= f_rep_x;
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sum_y -= f_rep_y;
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sum_y -= f_rep_y;
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} else {
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} else {
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let f_spring = 0.5 * (dist - self.opt_dist);
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let f_spring = 0.5 * (dist - 1.0);
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let f_spring_x = f_spring * unit_x;
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let f_spring_x = f_spring * unit_x;
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let f_spring_y = f_spring * unit_y;
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let f_spring_y = f_spring * unit_y;
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sum_x += f_spring_x;
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sum_x += f_spring_x;
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