forked from M-Labs/nalgebra
Make use of rand more idiomatic
This should improve performance and accuracy.
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@ -284,7 +284,8 @@ where
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where
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Standard: Distribution<N>,
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{
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Self::from_fn_generic(nrows, ncols, |_, _| rand::random())
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let mut rng = rand::thread_rng();
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Self::from_fn_generic(nrows, ncols, |_, _| rng.gen())
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}
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/// Creates a matrix filled with random values from the given distribution.
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@ -7,7 +7,7 @@ use quickcheck::{Arbitrary, Gen};
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#[cfg(feature = "rand-no-std")]
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use rand::{
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distributions::{Distribution, OpenClosed01, Standard},
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distributions::{Distribution, OpenClosed01, Standard, Uniform, uniform::SampleUniform},
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Rng,
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};
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@ -855,6 +855,7 @@ impl<N: SimdRealField> Distribution<UnitQuaternion<N>> for Standard
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where
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N::Element: SimdRealField,
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OpenClosed01: Distribution<N>,
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N: SampleUniform,
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{
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/// Generate a uniformly distributed random rotation quaternion.
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#[inline]
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@ -863,10 +864,9 @@ where
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// Uniform random rotations.
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// In D. Kirk, editor, Graphics Gems III, pages 124-132. Academic, New York, 1992.
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let x0 = rng.sample(OpenClosed01);
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let x1 = rng.sample(OpenClosed01);
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let x2 = rng.sample(OpenClosed01);
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let theta1 = N::simd_two_pi() * x1;
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let theta2 = N::simd_two_pi() * x2;
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let twopi = Uniform::new(N::zero(), N::simd_two_pi());
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let theta1 = rng.sample(&twopi);
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let theta2 = rng.sample(&twopi);
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let s1 = theta1.simd_sin();
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let c1 = theta1.simd_cos();
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let s2 = theta2.simd_sin();
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@ -7,7 +7,7 @@ use num::Zero;
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#[cfg(feature = "rand-no-std")]
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use rand::{
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distributions::{Distribution, OpenClosed01, Standard},
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distributions::{Distribution, OpenClosed01, Standard, Uniform, uniform::SampleUniform},
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Rng,
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};
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@ -265,12 +265,13 @@ impl<N: SimdRealField> Rotation2<N> {
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impl<N: SimdRealField> Distribution<Rotation2<N>> for Standard
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where
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N::Element: SimdRealField,
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OpenClosed01: Distribution<N>,
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N: SampleUniform,
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{
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/// Generate a uniformly distributed random rotation.
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#[inline]
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fn sample<'a, R: Rng + ?Sized>(&self, rng: &'a mut R) -> Rotation2<N> {
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Rotation2::new(rng.sample(OpenClosed01) * N::simd_two_pi())
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let twopi = Uniform::new(N::zero(), N::simd_two_pi());
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Rotation2::new(rng.sample(twopi))
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}
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}
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@ -923,6 +924,7 @@ impl<N: SimdRealField> Distribution<Rotation3<N>> for Standard
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where
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N::Element: SimdRealField,
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OpenClosed01: Distribution<N>,
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N: SampleUniform,
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{
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/// Generate a uniformly distributed random rotation.
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#[inline]
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@ -932,7 +934,8 @@ where
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// In D. Kirk, editor, Graphics Gems III, pages 117-120. Academic, New York, 1992.
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// Compute a random rotation around Z
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let theta = N::simd_two_pi() * rng.sample(OpenClosed01);
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let twopi = Uniform::new(N::zero(), N::simd_two_pi());
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let theta = rng.sample(&twopi);
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let (ts, tc) = theta.simd_sin_cos();
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let a = MatrixN::<N, U3>::new(
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tc,
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@ -947,7 +950,7 @@ where
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);
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// Compute a random rotation *of* Z
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let phi = N::simd_two_pi() * rng.sample(OpenClosed01);
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let phi = rng.sample(&twopi);
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let z = rng.sample(OpenClosed01);
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let (ps, pc) = phi.simd_sin_cos();
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let sqrt_z = z.simd_sqrt();
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@ -3,7 +3,7 @@ use quickcheck::{Arbitrary, Gen};
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#[cfg(feature = "rand-no-std")]
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use rand::{
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distributions::{Distribution, OpenClosed01, Standard},
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distributions::{Distribution, Uniform, uniform::SampleUniform, Standard},
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Rng,
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};
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@ -401,12 +401,13 @@ where
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impl<N: SimdRealField> Distribution<UnitComplex<N>> for Standard
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where
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N::Element: SimdRealField,
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OpenClosed01: Distribution<N>,
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N: SampleUniform,
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{
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/// Generate a uniformly distributed random `UnitComplex`.
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#[inline]
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fn sample<'a, R: Rng + ?Sized>(&self, rng: &mut R) -> UnitComplex<N> {
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UnitComplex::from_angle(rng.sample(OpenClosed01) * N::simd_two_pi())
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let twopi = Uniform::new(N::zero(), N::simd_two_pi());
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UnitComplex::from_angle(rng.sample(twopi))
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}
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}
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