fix: clippy

Author: dancixx

examples/rl_vs_classical_fbm.rs

@@ -63,7 +63,7 @@ fn timing_table() -> Vec<TimingPoint> {
     for &n in &sizes {
       let classical = Fbm::<f64>::new(h, n, Some(1.0));
       let rl = RlFBm::<f64>::new(h, n, Some(1.0), None);
-      let iters = (5_000_000 / n).max(40).min(2_000);
+      let iters = (5_000_000 / n).clamp(40, 2_000);
       let t_classical = bench_time(|| classical.sample(), iters);
       let t_rl = bench_time(|| rl.sample(), iters);
       let ratio = t_rl / t_classical;

stochastic-rs-quant/src/calibration/rbergomi.rs

@@ -1056,7 +1056,7 @@ mod tests {
       xi0: RBergomiXi0::Constant(0.04),
     };
 
-    let maturities = vec![0.25, 0.5, 1.0];
+    let maturities = [0.25, 0.5, 1.0];
     let mut market_slices = Vec::with_capacity(maturities.len());
     for (i, &t) in maturities.iter().enumerate() {
       let market_samples = simulate_rbergomi_terminal_samples(

stochastic-rs-quant/src/curves/bootstrap.rs

@@ -256,6 +256,6 @@ mod tests {
       },
     ];
     let curve = bootstrap_iterative(&inst, InterpolationMethod::LinearOnZeroRates, 1e-10, 50);
-    assert!(curve.len() >= 1);
+    assert!(!curve.is_empty());
   }
 }

stochastic-rs-quant/src/pricing/rainbow.rs

@@ -297,8 +297,6 @@ impl McRainbowPricer {
 
 #[cfg(test)]
 mod tests {
-  use ndarray::array;
-
   use super::*;
 
   /// Stulz: $C_{\min} + C_{\max} = C_1 + C_2$ (vanilla call sum).

stochastic-rs-quant/src/pricing/regime_switching.rs

@@ -527,7 +527,7 @@ mod tests {
     q_mat[[0, 0]] = Complex64::new(-0.5 * t, 0.0);
     q_mat[[0, 1]] = Complex64::new(0.5 * t, 0.0);
     q_mat[[1, 0]] = Complex64::new(1.0 * t, 0.0);
-    q_mat[[1, 1]] = Complex64::new(-1.0 * t, 0.0);
+    q_mat[[1, 1]] = Complex64::new(-t, 0.0);
     let result = matrix_exp_complex(&q_mat);
 
     for i in 0..2 {

stochastic-rs-quant/src/pricing/sabr.rs

@@ -481,16 +481,7 @@ mod tests {
       // β=1 OTM put
       (90.0, 100.0, 1.0, 0.2, 1.0, -0.3, 0.5, 2.118933616456034e-01),
       // β=0.5 ATM
-      (
-        100.0,
-        100.0,
-        0.5,
-        0.15,
-        0.5,
-        -0.2,
-        0.8,
-        1.537376757812500e-02,
-      ),
+      (100.0, 100.0, 0.5, 0.15, 0.5, -0.2, 0.8, 1.5373767578125e-02),
       // β=0.5 OTM call
       (
         110.0,
@@ -582,7 +573,7 @@ mod tests {
         1.401312256794535e-01,
       ),
       // β=0.7 long-dated
-      (0.30, 50.0, 2.0, 0.7, 0.1, 0.4, 9.409442654142710e-01),
+      (0.30, 50.0, 2.0, 0.7, 0.1, 0.4, 9.40944265414271e-01),
       // β=0 (normal Sabr)
       (0.25, 100.0, 1.0, 0.0, 0.0, 0.3, 2.475118650781591e+01),
     ];

stochastic-rs-quant/src/pricing/snell_envelope.rs

@@ -411,7 +411,7 @@ mod tests {
     assert!(!result.exercise_boundary.is_empty());
 
     for &(t, s_star) in &result.exercise_boundary {
-      assert!(t >= 0.0 && t < 1.0);
+      assert!((0.0..1.0).contains(&t));
       assert!(s_star > 0.0 && s_star <= 100.0);
     }
 

stochastic-rs-stats/src/leverage.rs

@@ -98,6 +98,6 @@ mod tests {
     }
     let closes = Array1::from_vec(vals);
     let rho = estimate_leverage_rho(closes.view());
-    assert!(rho >= -0.99 && rho <= 0.99, "rho out of range: {rho}");
+    assert!((-0.99..=0.99).contains(&rho), "rho out of range: {rho}");
   }
 }

stochastic-rs-stats/src/mle/mod.rs

@@ -264,10 +264,10 @@ mod tests {
     let cir = Cir::seeded(3.0, 0.3, 0.2, 100, Some(0.4), Some(1.0), None, 0);
     let dt = 1.0 / 250.0;
     let d = DensityApprox::Euler.density(&cir, 0.4, 0.41, 0.0, dt);
-    // reference value: 18.715933204468332
+    // reference value: 18.71593320446833
     assert!(
-      (d - 18.715933204468332).abs() < 1e-8,
-      "Cir Euler: got {d}, expected 18.715933204468332"
+      (d - 18.71593320446833).abs() < 1e-8,
+      "Cir Euler: got {d}, expected 18.71593320446833"
     );
   }
 

stochastic-rs-stats/src/tail_index.rs

@@ -184,7 +184,7 @@ mod tests {
     let m = data.sum() / data.len() as f64;
     let v = data.iter().map(|x| (x - m).powi(2)).sum::<f64>() / (data.len() - 1) as f64;
     let alpha = estimate_cgmy_alpha(data.view(), m, v);
-    assert!(alpha >= 0.1 && alpha <= 1.9, "alpha out of range: {alpha}");
+    assert!((0.1..=1.9).contains(&alpha), "alpha out of range: {alpha}");
   }
 
   #[test]