add thread

Code/ldpc/Cargo.lock

@@ -40,6 +40,37 @@ dependencies = [
  "libc",
 ]
 
+[[package]]
+name = "crossbeam-deque"
+version = "0.8.6"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "9dd111b7b7f7d55b72c0a6ae361660ee5853c9af73f70c3c2ef6858b950e2e51"
+dependencies = [
+ "crossbeam-epoch",
+ "crossbeam-utils",
+]
+
+[[package]]
+name = "crossbeam-epoch"
+version = "0.9.18"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "5b82ac4a3c2ca9c3460964f020e1402edd5753411d7737aa39c3714ad1b5420e"
+dependencies = [
+ "crossbeam-utils",
+]
+
+[[package]]
+name = "crossbeam-utils"
+version = "0.8.21"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "d0a5c400df2834b80a4c3327b3aad3a4c4cd4de0629063962b03235697506a28"
+
+[[package]]
+name = "either"
+version = "1.15.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "48c757948c5ede0e46177b7add2e67155f70e33c07fea8284df6576da70b3719"
+
 [[package]]
 name = "equivalent"
 version = "1.0.2"
@@ -116,6 +147,7 @@ name = "ldpc"
 version = "0.1.0"
 dependencies = [
  "rand",
+ "rayon",
 ]
 
 [[package]]
@@ -193,6 +225,26 @@ version = "0.10.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "0c8d0fd677905edcbeedbf2edb6494d676f0e98d54d5cf9bda0b061cb8fb8aba"
 
+[[package]]
+name = "rayon"
+version = "1.11.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "368f01d005bf8fd9b1206fb6fa653e6c4a81ceb1466406b81792d87c5677a58f"
+dependencies = [
+ "either",
+ "rayon-core",
+]
+
+[[package]]
+name = "rayon-core"
+version = "1.13.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "22e18b0f0062d30d4230b2e85ff77fdfe4326feb054b9783a3460d8435c8ab91"
+dependencies = [
+ "crossbeam-deque",
+ "crossbeam-utils",
+]
+
 [[package]]
 name = "semver"
 version = "1.0.27"

Code/ldpc/Cargo.toml

@@ -5,3 +5,4 @@ edition = "2024"
 
 [dependencies]
 rand = "0.10.0"
+rayon = "1.11.0"

Code/ldpc/src/analyse/ldpc_analysis_results.csv

@@ -0,0 +1,91 @@
+k,n,wc,wr,rate,p,ber,fer,avg_iter
+50,100,3,6,0.5000,0.000000,0.00000000,0.00000000,0.00
+50,100,3,6,0.5000,0.008571,0.09586000,0.21200000,0.00
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+50,75,3,9,0.6667,0.025714,0.27240000,0.54800000,0.00
+50,75,3,9,0.6667,0.034286,0.34341333,0.69300000,0.00
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+200,400,3,6,0.5000,0.000000,0.00000000,0.00000000,0.00
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+200,400,3,6,0.5000,0.077143,0.50014500,1.00000000,50.00
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+400,600,3,9,0.6667,0.120000,0.50078833,1.00000000,50.00

Code/ldpc/src/analyse/trace.py

@@ -0,0 +1,138 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+import seaborn as sns
+import numpy as np
+import sys
+from matplotlib.colors import LogNorm
+import matplotlib.ticker as ticker
+
+sns.set_theme(style="whitegrid", context="talk")
+plt.rcParams['font.family'] = 'sans-serif'
+plt.rcParams['figure.dpi'] = 300
+
+def load_data(filename):
+    try:
+        df = pd.read_csv(filename)
+        
+        df['Label'] = (
+            "k=" + df['k'].astype(str) + 
+            " | Wc=" + df['wc'].astype(str) + 
+            " | Wr=" + df['wr'].astype(str)
+        )
+        
+        df = df.sort_values(by=['k', 'wc', 'wr'])
+        
+        return df
+    except FileNotFoundError:
+        print(f"Erreur : Le fichier '{filename}' est introuvable.")
+        sys.exit(1)
+
+def plot_1_waterfall_zoomed(df):
+    print("   -> Génération du Waterfall...")
+    plt.figure(figsize=(14, 9))
+    
+    df_zoom = df[df['ber'] > 0].copy()
+    
+    if df_zoom.empty:
+        print("    Pas d'erreurs trouvées, impossible de tracer.")
+        return
+
+    sns.lineplot(
+        data=df_zoom, 
+        x='p', 
+        y='ber', 
+        hue='Label', 
+        style='Label',
+        markers=True, 
+        dashes=False, 
+        linewidth=2.5, 
+        palette="turbo",
+        markersize=9
+    )
+
+    plt.yscale('log')
+    ax = plt.gca()
+    ax.yaxis.set_major_locator(ticker.LogLocator(base=10.0, numticks=12))
+    
+    plt.title("Vue Globale : Performance des configurations", fontweight='bold', pad=20)
+    plt.ylabel("BER [Log Scale]", labelpad=15)
+    plt.xlabel("Bruit du Canal (p)", labelpad=15)
+    plt.grid(True, which="both", ls="-", alpha=0.3)
+    
+    plt.legend(bbox_to_anchor=(1.02, 1), loc='upper left', borderaxespad=0, title="Configuration", fontsize='x-small')
+    
+    plt.tight_layout()
+    plt.savefig("Final_1_Waterfall.png")
+
+def plot_2_ranking_bars(df):
+    print("   -> Génération du Classement...")
+    
+    means = df.groupby('p')['ber'].mean()
+    target_p = means[means > 0.0001].first_valid_index()
+    
+    if target_p is None:
+        target_p = df['p'].max()
+
+    subset = df[df['p'] == target_p].sort_values('ber', ascending=True)
+
+    plt.figure(figsize=(12, max(6, len(subset)*0.4))) 
+    
+    barplot = sns.barplot(
+        data=subset, 
+        y='Label', 
+        x='ber', 
+        palette="viridis", 
+        edgecolor=".2"
+    )
+    
+    plt.xscale('log')
+    plt.title(f"Robustesse p={target_p:.3f} (Gauche = Meilleur)", fontweight='bold', pad=20)
+    plt.xlabel("BER", labelpad=10)
+    plt.ylabel("") 
+    
+    for i, container in enumerate(barplot.containers):
+        barplot.bar_label(container, fmt='%.1e', padding=5, fontsize=11)
+        
+    plt.grid(True, axis='x', which="both", ls="--", alpha=0.5)
+    plt.tight_layout()
+    plt.savefig("Final_2_Classement.png")
+
+def plot_3_heatmap_gradient(df):
+    print("   -> Génération de la Heatmap...")
+    
+    pivot = df.pivot(index="Label", columns="p", values="ber")
+    
+    pivot_log = pivot.replace(0, 1e-9) 
+    
+    plt.figure(figsize=(16, max(6, len(pivot)*0.5))) 
+    
+    ax = sns.heatmap(
+        pivot_log, 
+        cmap="Spectral_r", 
+        norm=LogNorm(vmin=1e-5, vmax=1),
+        cbar_kws={'label': 'BER (Log Scale)'},
+        linewidths=0.5,
+        linecolor='white'
+    )
+    
+    plt.title("Résistance (Bleu=Zone de Confort, Rouge=Zone d'Échec)", fontweight='bold', pad=20)
+    plt.xlabel("Bruit du Canal (p)", labelpad=10)
+    plt.ylabel("")
+    
+    plt.xticks(rotation=45)
+    plt.tight_layout()
+    plt.savefig("Final_3_Heatmap.png")
+
+if __name__ == "__main__":
+    print("Démarrage de l'analyse graphique finale...")
+    
+    df = load_data("ldpc_analysis_results.csv")
+    
+    plot_1_waterfall_zoomed(df)
+    plot_2_ranking_bars(df)
+    plot_3_heatmap_gradient(df)
+    
+    print("\nTerminé ! Trois images générées :")
+    print("   1. Final_1_Waterfall.png (Courbes détaillées)")
+    print("   2. Final_2_Classement.png (Comparatif barres)")
+    print("   3. Final_3_Heatmap.png (Vision globale couleur)")

Code/ldpc/src/analysis.rs

@@ -0,0 +1,208 @@
+use crate::channel::Channel;
+use crate::code::LdpcCode;
+use crate::construction::random::generate_random_h_for_k;
+use crate::decoder::bit_flip::BitFlipDecoder;
+use crate::encoder::dense::DenseEncoder;
+use rand::{Rng, RngExt};
+use rayon::prelude::*;
+use std::fs::File;
+use std::io::Write;
+
+#[derive(Debug, Clone, Copy)]
+pub enum DecoderAlgorithm {
+    BitFlipping,
+}
+
+#[derive(Clone)]
+pub struct AnalysisConfig {
+    pub k_values: Vec<usize>,
+    pub wc_values: Vec<usize>,
+    pub wr_values: Vec<usize>,
+    pub min_error_prob: f64,
+    pub max_error_prob: f64,
+    pub steps: usize,
+    pub frames_per_step: usize,
+    pub max_iter: usize,
+    pub algorithm: DecoderAlgorithm,
+}
+
+#[derive(Debug, Clone)]
+pub struct SimulationPoint {
+    pub k_config: usize,
+    pub n_real: usize,
+    pub wc: usize,
+    pub wr: usize,
+    pub rate: f64,
+    pub error_rate: f64,
+    pub ber: f64,
+    pub fer: f64,
+    pub avg_iter: f64,
+}
+
+pub struct Analyzer;
+
+impl Analyzer {
+    pub fn run_batch(config: AnalysisConfig) -> Vec<SimulationPoint> {
+        let mut tasks = Vec::new();
+
+        for &k in &config.k_values {
+            for &wc in &config.wc_values {
+                for &wr in &config.wr_values {
+                    if wr <= wc {
+                        continue;
+                    }
+                    if (k * wr) % (wr - wc) != 0 {
+                        continue;
+                    }
+                    tasks.push((k, wc, wr));
+                }
+            }
+        }
+
+        println!("Configurations valides : {}", tasks.len());
+        println!("Execution sur {} coeurs...", rayon::current_num_threads());
+
+        let results: Vec<SimulationPoint> = tasks
+            .par_iter()
+            .flat_map(|&(k_target, wc, wr)| {
+                let h_matrix = generate_random_h_for_k(k_target, wc, wr);
+                let ldpc = LdpcCode::new(h_matrix);
+                let encoder = DenseEncoder::new(&ldpc);
+
+                let k_real = encoder.k;
+                let n_real = encoder.n;
+                let rate_theoretical = k_real as f64 / n_real as f64;
+
+                let step_size = if config.steps > 1 {
+                    (config.max_error_prob - config.min_error_prob) / (config.steps as f64 - 1.0)
+                } else {
+                    0.0
+                };
+
+                (0..config.steps)
+                    .into_par_iter()
+                    .map(|i| {
+                        let p = config.min_error_prob + (i as f64 * step_size);
+
+                        let point = Self::simulate_point(
+                            &encoder,
+                            &ldpc,
+                            p,
+                            &config,
+                            k_real,
+                            k_target,
+                            n_real,
+                            wc,
+                            wr,
+                            rate_theoretical,
+                        );
+
+                        println!(
+                            "Termine : k={} wc={} wr={} p={:.3} -> BER={:.5}",
+                            point.k_config, point.wc, point.wr, point.error_rate, point.ber
+                        );
+
+                        point
+                    })
+                    .collect::<Vec<SimulationPoint>>()
+            })
+            .collect();
+
+        println!("Simulation terminee. {} points generes.", results.len());
+        results
+    }
+
+    fn simulate_point(
+        encoder: &DenseEncoder,
+        ldpc: &LdpcCode,
+        p: f64,
+        config: &AnalysisConfig,
+        k_real: usize,
+        k_orig: usize,
+        n: usize,
+        wc: usize,
+        wr: usize,
+        rate: f64,
+    ) -> SimulationPoint {
+        let channel = Channel::new(p);
+        let mut rng = rand::rng();
+
+        let mut total_bit_errors = 0;
+        let mut total_frame_errors = 0;
+        let mut total_iterations = 0;
+        let mut converged_count = 0;
+
+        for _ in 0..config.frames_per_step {
+            let message: Vec<u8> = (0..k_real).map(|_| rng.random_range(0..2)).collect();
+            let codeword = encoder.encode(&message);
+            let received = channel.add_noise(&codeword);
+
+            let (decoded, iters) = match config.algorithm {
+                DecoderAlgorithm::BitFlipping => {
+                    let decoder = BitFlipDecoder::new(ldpc);
+                    let res = decoder.decode(&received, config.max_iter);
+                    (res, 0)
+                }
+            };
+
+            match decoded {
+                Some(res_code) => {
+                    if res_code != codeword {
+                        total_frame_errors += 1;
+                        total_bit_errors += Channel::count_errors(&codeword, &res_code);
+                    } else {
+                        converged_count += 1;
+                        total_iterations += iters;
+                    }
+                }
+                None => {
+                    total_frame_errors += 1;
+                    total_bit_errors += Channel::count_errors(&codeword, &received);
+                }
+            }
+        }
+
+        let total_bits = (config.frames_per_step * n) as f64;
+        let avg_iter = if converged_count > 0 {
+            total_iterations as f64 / converged_count as f64
+        } else {
+            config.max_iter as f64
+        };
+
+        SimulationPoint {
+            k_config: k_orig,
+            n_real: n,
+            wc,
+            wr,
+            rate,
+            error_rate: p,
+            ber: total_bit_errors as f64 / total_bits,
+            fer: total_frame_errors as f64 / config.frames_per_step as f64,
+            avg_iter,
+        }
+    }
+
+    pub fn save_csv(results: &[SimulationPoint], filename: &str) {
+        let mut sorted_results = results.to_vec();
+        sorted_results.sort_by(|a, b| {
+            a.k_config
+                .cmp(&b.k_config)
+                .then(a.wc.cmp(&b.wc))
+                .then(a.wr.cmp(&b.wr))
+                .then(a.error_rate.partial_cmp(&b.error_rate).unwrap())
+        });
+
+        let mut file = File::create(filename).expect("Erreur fichier");
+        writeln!(file, "k,n,wc,wr,rate,p,ber,fer,avg_iter").unwrap();
+
+        for r in sorted_results {
+            writeln!(
+                file,
+                "{},{},{},{},{:.4},{:.6},{:.8},{:.8},{:.2}",
+                r.k_config, r.n_real, r.wc, r.wr, r.rate, r.error_rate, r.ber, r.fer, r.avg_iter
+            )
+            .unwrap();
+        }
+        println!("Resultats sauvegardes dans '{}'", filename);
+    }
+}

Code/ldpc/src/main.rs

@@ -8,6 +8,24 @@ mod matrix;
 mod simulation;
 mod tanner;
 
+use analysis::{AnalysisConfig, Analyzer, DecoderAlgorithm};
+
 fn main() {
-    simulation::run_simulation(8, 2, 4, 0.1);
+    println!("Analyse des performences");
+
+    let config = AnalysisConfig {
+        k_values: vec![50, 200, 400, 800, 1000],
+        wc_values: vec![3, 4, 5],
+        wr_values: vec![6, 8, 9, 12, 15, 16],
+        min_error_prob: 0.00,
+        max_error_prob: 0.12,
+        steps: 15,
+        frames_per_step: 1000,
+        max_iter: 50,
+        algorithm: DecoderAlgorithm::BitFlipping,
+    };
+
+    let res = Analyzer::run_batch(config);
+    Analyzer::save_csv(&res, "ldpc_analysis_results.csv");
+    // simulation::run_simulation(1000, 3, 6, 0.005);
 }

Code/ldpc/src/simulation.rs

@@ -40,8 +40,8 @@ pub fn run_simulation(k: usize, wc: usize, wr: usize, error_prob: f64) {
 
     let codeword = encoder.encode(&message);
 
-    println!("  -> Message  u ({:02} bits) : {:?}", k, message);
+    // println!("  -> Message  u ({:02} bits) : {:?}", k, message);
-    println!("  -> Codeword s ({:02} bits) : {:?}", encoder.n, codeword);
+    // println!("  -> Codeword s ({:02} bits) : {:?}", encoder.n, codeword);
 
     println!("\nCanal bruité (p = {})", error_prob);
 
@@ -53,7 +53,7 @@ pub fn run_simulation(k: usize, wc: usize, wr: usize, error_prob: f64) {
         println!("   -> Aucune erreur.")
     } else {
         println!("  -> {} erreurs !", nb_errors);
-        println!("  -> Recu r ({:02} bits) : {:?}", received.len(), received);
+        // println!("  -> Recu r ({:02} bits) : {:?}", received.len(), received);
     }
 
     println!("\n Décodage (bit-flipping)");