stabilize geometric inverse cdf and clean lint warnings

src/distribution/geometric.rs

@@ -153,6 +153,23 @@ impl DiscreteCDF<u64, f64> for Geometric {
             ((-self.p).ln_1p() * (x as f64)).exp()
         }
     }
+
+    /// Calculates the inverse cumulative distribution function (quantile) for the
+    /// geometric distribution using its closed-form expression. Keeps behavior
+    /// consistent across platforms without relying on bisection.
+    fn inverse_cdf(&self, p: f64) -> u64 {
+        assert!((0.0..=1.0).contains(&p), "p must be on [0,1]");
+        if p <= 0.0 || prec::ulps_eq!(self.p, 1.0) {
+            return 1;
+        }
+        if p >= 1.0 {
+            return u64::MAX;
+        }
+
+        // k = ceil(log(1 - p) / log(1 - self.p)), clamped to domain ≥ 1.
+        let k = ((-p).ln_1p() / (-self.p).ln_1p()).ceil().max(1.0);
+        if k.is_finite() { k as u64 } else { u64::MAX }
+    }
 }
 
 impl Min<u64> for Geometric {

src/distribution/inverse_gamma.rs

@@ -344,7 +344,6 @@ impl Continuous<f64, f64> for InverseGamma {
 mod tests {
     use super::*;
     use crate::distribution::internal::density_util;
-    use crate::distribution::internal::testing_boiler;
 
     testing_boiler!(shape: f64, rate: f64; InverseGamma; InverseGammaError);
 

src/distribution/laplace.rs

@@ -323,7 +323,6 @@ mod tests {
     use super::*;
     use crate::prec;
 
-    use crate::distribution::internal::testing_boiler;
 
     testing_boiler!(location: f64, scale: f64; Laplace; LaplaceError);
 

src/distribution/log_normal.rs

@@ -364,7 +364,6 @@ impl Continuous<f64, f64> for LogNormal {
 mod tests {
     use super::*;
     use crate::distribution::internal::density_util;
-    use crate::distribution::internal::testing_boiler;
 
     testing_boiler!(location: f64, scale: f64; LogNormal; LogNormalError);
 

src/distribution/negative_binomial.rs

@@ -323,7 +323,6 @@ impl Discrete<u64, f64> for NegativeBinomial {
 mod tests {
     use super::*;
     use crate::distribution::internal::density_util;
-    use crate::distribution::internal::testing_boiler;
 
     testing_boiler!(r: f64, p: f64; NegativeBinomial; NegativeBinomialError);
 

src/distribution/poisson.rs

@@ -342,7 +342,6 @@ pub fn sample_unchecked<R: ::rand::Rng + ?Sized>(rng: &mut R, lambda: f64) -> f6
 mod tests {
     use super::*;
     use crate::distribution::internal::density_util;
-    use crate::distribution::internal::testing_boiler;
     testing_boiler!(lambda: f64; Poisson; PoissonError);
 
     #[test]

src/distribution/triangular.rs

@@ -438,7 +438,6 @@ fn sample_unchecked<R: ::rand::Rng + ?Sized>(rng: &mut R, min: f64, max: f64, mo
 mod tests {
     use super::*;
     use crate::distribution::internal::density_util;
-    use crate::distribution::internal::testing_boiler;
 
     testing_boiler!(min: f64, max: f64, mode: f64; Triangular; TriangularError);
 

src/distribution/uniform.rs

@@ -348,7 +348,6 @@ mod tests {
     use super::*;
     use crate::prec;
     use crate::distribution::internal::density_util;
-    use crate::distribution::internal::testing_boiler;
 
     testing_boiler!(min: f64, max: f64; Uniform; UniformError);
 

src/distribution/weibull.rs

@@ -381,7 +381,6 @@ impl Continuous<f64, f64> for Weibull {
 mod tests {
     use super::*;
     use crate::distribution::internal::density_util;
-    use crate::distribution::internal::testing_boiler;
 
     testing_boiler!(shape: f64, scale: f64; Weibull; WeibullError);