use R for Random and make default nondeterministic

argmin-rs · Jan 6, 2024 · 63f01cf · 63f01cf
1 parent 50ec33f
commit 63f01cf
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Showing 6 changed files with 17 additions and 17 deletions.
diff --git a/argmin-math/src/lib.rs b/argmin-math/src/lib.rs
@@ -337,7 +337,7 @@ pub trait ArgminInv<T> {
 /// Create a random number
 pub trait ArgminRandom {
     /// Get a random element between min and max,
-    fn rand_from_range<G: Rng>(min: &Self, max: &Self, rng: &mut G) -> Self;
+    fn rand_from_range<R: Rng>(min: &Self, max: &Self, rng: &mut R) -> Self;
 }
 
 /// Minimum and Maximum of type `T`

diff --git a/argmin-math/src/nalgebra_m/random.rs b/argmin-math/src/nalgebra_m/random.rs
@@ -22,7 +22,7 @@ where
     DefaultAllocator: Allocator<N, R, C>,
 {
     #[inline]
-    fn rand_from_range<G: Rng>(min: &Self, max: &Self, rng: &mut G) -> OMatrix<N, R, C> {
+    fn rand_from_range<R: Rng>(min: &Self, max: &Self, rng: &mut R) -> OMatrix<N, R, C> {
         assert!(!min.is_empty());
         assert_eq!(min.shape(), max.shape());
 

diff --git a/argmin-math/src/ndarray_m/random.rs b/argmin-math/src/ndarray_m/random.rs
@@ -12,7 +12,7 @@ use crate::ArgminRandom;
 macro_rules! make_random {
     ($t:ty) => {
         impl ArgminRandom for ndarray::Array1<$t> {
-            fn rand_from_range<G: Rng>(min: &Self, max: &Self, rng: &mut G) -> ndarray::Array1<$t> {
+            fn rand_from_range<R: Rng>(min: &Self, max: &Self, rng: &mut R) -> ndarray::Array1<$t> {
                 assert!(!min.is_empty());
                 assert_eq!(min.len(), max.len());
 
@@ -33,7 +33,7 @@ macro_rules! make_random {
         }
 
         impl ArgminRandom for ndarray::Array2<$t> {
-            fn rand_from_range<G: Rng>(min: &Self, max: &Self, rng: &mut G) -> ndarray::Array2<$t> {
+            fn rand_from_range<R: Rng>(min: &Self, max: &Self, rng: &mut R) -> ndarray::Array2<$t> {
                 assert!(!min.is_empty());
                 assert_eq!(min.raw_dim(), max.raw_dim());
 

diff --git a/argmin-math/src/primitives/random.rs b/argmin-math/src/primitives/random.rs
@@ -12,7 +12,7 @@ macro_rules! make_random {
     ($t:ty) => {
         impl ArgminRandom for $t {
             #[inline]
-            fn rand_from_range<G: Rng>(min: &Self, max: &Self, rng: &mut G) -> $t {
+            fn rand_from_range<R: Rng>(min: &Self, max: &Self, rng: &mut R) -> $t {
                 rng.gen_range(*min..*max)
             }
         }

diff --git a/argmin-math/src/vec/random.rs b/argmin-math/src/vec/random.rs
@@ -11,7 +11,7 @@ use rand::Rng;
 macro_rules! make_random {
     ($t:ty) => {
         impl ArgminRandom for Vec<$t> {
-            fn rand_from_range<G: Rng>(min: &Self, max: &Self, rng: &mut G) -> Vec<$t> {
+            fn rand_from_range<R: Rng>(min: &Self, max: &Self, rng: &mut R) -> Vec<$t> {
                 assert!(!min.is_empty());
                 assert_eq!(min.len(), max.len());
 
@@ -35,7 +35,7 @@ macro_rules! make_random {
         }
 
         impl ArgminRandom for Vec<Vec<$t>> {
-            fn rand_from_range<G: Rng>(min: &Self, max: &Self, rng: &mut G) -> Vec<Vec<$t>> {
+            fn rand_from_range<R: Rng>(min: &Self, max: &Self, rng: &mut R) -> Vec<Vec<$t>> {
                 assert!(!min.is_empty());
                 assert_eq!(min.len(), max.len());
                 min.iter()

diff --git a/argmin/src/solver/particleswarm/mod.rs b/argmin/src/solver/particleswarm/mod.rs
@@ -51,7 +51,7 @@ use serde::{Deserialize, Serialize};
 /// \[1\] <https://en.wikipedia.org/wiki/Particle_swarm_optimization>
 #[derive(Clone)]
 #[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))]
-pub struct ParticleSwarm<P, F, G> {
+pub struct ParticleSwarm<P, F, R> {
     /// Inertia weight
     weight_inertia: F,
     /// Cognitive acceleration coefficient
@@ -63,7 +63,7 @@ pub struct ParticleSwarm<P, F, G> {
     /// Number of particles
     num_particles: usize,
     /// Random number generator
-    rng_generator: G,
+    rng_generator: R,
 }
 
 impl<P, F> ParticleSwarm<P, F, rand::rngs::StdRng>
@@ -103,15 +103,15 @@ where
             weight_social: float!(0.5 + 2.0f64.ln()),
             bounds,
             num_particles,
-            rng_generator: rand::rngs::StdRng::seed_from_u64(42),
+            rng_generator: rand::rngs::StdRng::from_entropy(),
         }
     }
 }
-impl<P, F, G0> ParticleSwarm<P, F, G0>
+impl<P, F, R0> ParticleSwarm<P, F, R0>
 where
     P: Clone + SyncAlias + ArgminSub<P, P> + ArgminMul<F, P> + ArgminRandom + ArgminZeroLike,
     F: ArgminFloat,
-    G0: Rng,
+    R0: Rng,
 {
     /// Set the random number generator
     ///
@@ -131,7 +131,7 @@ where
     /// # Ok(())
     /// # }
     /// ```
-    pub fn with_rng_generator<G1: Rng>(self, generator: G1) -> ParticleSwarm<P, F, G1> {
+    pub fn with_rng_generator<R1: Rng>(self, generator: R1) -> ParticleSwarm<P, F, R1> {
         ParticleSwarm {
             weight_inertia: self.weight_inertia,
             weight_cognitive: self.weight_cognitive,
@@ -143,11 +143,11 @@ where
     }
 }
 
-impl<P, F, G> ParticleSwarm<P, F, G>
+impl<P, F, R> ParticleSwarm<P, F, R>
 where
     P: Clone + SyncAlias + ArgminSub<P, P> + ArgminMul<F, P> + ArgminRandom + ArgminZeroLike,
     F: ArgminFloat,
-    G: Rng,
+    R: Rng,
 {
     /// Set inertia factor on particle velocity
     ///
@@ -276,7 +276,7 @@ where
     }
 }
 
-impl<O, P, F, G> Solver<O, PopulationState<Particle<P, F>, F>> for ParticleSwarm<P, F, G>
+impl<O, P, F, R> Solver<O, PopulationState<Particle<P, F>, F>> for ParticleSwarm<P, F, R>
 where
     O: CostFunction<Param = P, Output = F> + SyncAlias,
     P: SerializeAlias
@@ -289,7 +289,7 @@ where
         + ArgminRandom
         + ArgminMinMax,
     F: ArgminFloat,
-    G: Rng,
+    R: Rng,
 {
     const NAME: &'static str = "Particle Swarm Optimization";