smartcorelib · dependabot · Apr 17, 2025 · May 1, 2025
@@ -25,7 +25,7 @@ cfg-if = "1.0.0"
 ndarray = { version = "0.15", optional = true }
 num-traits = "0.2.12"
 num = "0.4"
-rand = { version = "0.8.5", default-features = false, features = ["small_rng"] }
+rand = { version = "0.9.1", default-features = false, features = ["small_rng"] }
 rand_distr = { version = "0.4", optional = true }
 serde = { version = "1", features = ["derive"], optional = true }
 

diff --git a/src/ensemble/random_forest_regressor.rs b/src/ensemble/random_forest_regressor.rs
    fn sample_with_replacement(nrows: usize, rng: &mut impl Rng) -> Vec<usize> {
        let mut samples = vec![0; nrows];
        for _ in 0..nrows {
            let xi = rng.gen_range(0..nrows);
            samples[xi] += 1;
        }
        samples
diff --git a/src/ensemble/random_forest_classifier.rs b/src/ensemble/random_forest_classifier.rs

            let size = ((n_samples as f64) / *class_weight_l) as usize;
            for _ in 0..size {
                let xi: usize = rng.gen_range(0..n_samples);
                samples[index[xi]] += 1;
            }
        }
diff --git a/src/cluster/kmeans.rs b/src/cluster/kmeans.rs
        let (n, _) = data.shape();
        let mut y = vec![0; n];
        let mut centroid: Vec<TX> = data
            .get_row(rng.gen_range(0..n))
            .iterator(0)
            .cloned()
            .collect();
            for i in d.iter() {
                sum += *i;
            }
            let cutoff = rng.gen::<f64>() * sum;
            let mut cost = 0f64;
            let mut index = 0;
            while index < n {
diff --git a/src/numbers/floatnum.rs b/src/numbers/floatnum.rs
    fn rand() -> f64 {
        use rand::Rng;
        let mut rng = get_rng_impl(None);
        rng.gen()
    }

    fn two() -> Self {
    fn rand() -> f32 {
        use rand::Rng;
        let mut rng = get_rng_impl(None);
        rng.gen()
    }

    fn two() -> Self {
diff --git a/src/numbers/realnum.rs b/src/numbers/realnum.rs
        let mut small_rng = get_rng_impl(None);

        let mut rngs: Vec<SmallRng> = (0..3)
            .map(|_| SmallRng::from_rng(&mut small_rng).unwrap())
            .collect();
        rngs[0].gen::<f64>()
    }
        let mut small_rng = get_rng_impl(None);

        let mut rngs: Vec<SmallRng> = (0..3)
            .map(|_| SmallRng::from_rng(&mut small_rng).unwrap())
            .collect();
        rngs[0].gen::<f32>()
    }
diff --git a/src/rand_custom.rs b/src/rand_custom.rs
            cfg_if::cfg_if! {
                if #[cfg(feature = "std_rand")] {
                    use rand::RngCore;
                    RngImpl::seed_from_u64(rand::thread_rng().next_u64())
                } else {
                    // no std_random feature build, use getrandom
                    #[cfg(feature = "js")]
diff --git a/src/dataset/generator.rs b/src/dataset/generator.rs
 //! # Dataset Generators
 //!
 use rand::distributions::Uniform;
 use rand::prelude::*;
 use rand_distr::Normal;

    let cluster_std = 1.0;
    let mut centers: Vec<Vec<Normal<f32>>> = Vec::with_capacity(num_centers);

    let mut rng = rand::thread_rng();
    for _ in 0..num_centers {
        centers.push(
            (0..num_features)
        let label = i % num_centers;
        y.push(label as f32);
        for j in 0..num_features {
            x.push(centers[label][j].sample(&mut rng));
        }
    }

    let linspace_in = linspace(0.0, 2.0 * std::f32::consts::PI, num_samples_in);

    let noise = Normal::new(0.0, noise).unwrap();
    let mut rng = rand::thread_rng();

    let mut x: Vec<f32> = Vec::with_capacity(num_samples * 2);
    let mut y: Vec<f32> = Vec::with_capacity(num_samples);

    for v in linspace_out {
        x.push(v.cos() + noise.sample(&mut rng));
        x.push(v.sin() + noise.sample(&mut rng));
        y.push(0.0);
    }

    let linspace_in = linspace(0.0, std::f32::consts::PI, num_samples_in);

    let noise = Normal::new(0.0, noise).unwrap();
    let mut rng = rand::thread_rng();

    let mut x: Vec<f32> = Vec::with_capacity(num_samples * 2);
    let mut y: Vec<f32> = Vec::with_capacity(num_samples);
	fn sample_with_replacement(nrows: usize, rng: &mut impl Rng) -> Vec<usize> {
	let mut samples = vec![0; nrows];
	for _ in 0..nrows {
	let xi = rng.gen_range(0..nrows);
Check warning on line 518 in src/ensemble/random_forest_regressor.rs GitHub Actions / check_features (ubuntu) use of deprecated method `rand::Rng::gen_range`: Renamed to `random_range` Check warning on line 518 in src/ensemble/random_forest_regressor.rs GitHub Actions / tests (macos, aarch64-apple-darwin) use of deprecated method `rand::Rng::gen_range`: Renamed to `random_range`
	samples[xi] += 1;
	}
	samples

	let size = ((n_samples as f64) / *class_weight_l) as usize;
	for _ in 0..size {
	let xi: usize = rng.gen_range(0..n_samples);
Check warning on line 599 in src/ensemble/random_forest_classifier.rs GitHub Actions / check_features (ubuntu) use of deprecated method `rand::Rng::gen_range`: Renamed to `random_range` Check warning on line 599 in src/ensemble/random_forest_classifier.rs GitHub Actions / tests (macos, aarch64-apple-darwin) use of deprecated method `rand::Rng::gen_range`: Renamed to `random_range`
	samples[index[xi]] += 1;
	}
	}
	let (n, _) = data.shape();
	let mut y = vec![0; n];
	let mut centroid: Vec<TX> = data
	.get_row(rng.gen_range(0..n))
Check warning on line 359 in src/cluster/kmeans.rs GitHub Actions / check_features (ubuntu) use of deprecated method `rand::Rng::gen_range`: Renamed to `random_range` Check failure on line 359 in src/cluster/kmeans.rs GitHub Actions / lint use of deprecated method `rand::Rng::gen_range`: Renamed to `random_range` Check warning on line 359 in src/cluster/kmeans.rs GitHub Actions / tests (macos, aarch64-apple-darwin) use of deprecated method `rand::Rng::gen_range`: Renamed to `random_range`
	.iterator(0)
	.cloned()
	.collect();
	for i in d.iter() {
	sum += *i;
	}
	let cutoff = rng.gen::<f64>() * sum;
Check warning on line 385 in src/cluster/kmeans.rs GitHub Actions / check_features (ubuntu) use of deprecated method `rand::Rng::gen`: Renamed to `random` to avoid conflict with the new `gen` keyword in Rust 2024. Check warning on line 385 in src/cluster/kmeans.rs GitHub Actions / tests (macos, aarch64-apple-darwin) use of deprecated method `rand::Rng::gen`: Renamed to `random` to avoid conflict with the new `gen` keyword in Rust 2024.
	let mut cost = 0f64;
	let mut index = 0;
	while index < n {
	fn rand() -> f64 {
	use rand::Rng;
	let mut rng = get_rng_impl(None);
	rng.gen()
Check warning on line 61 in src/numbers/floatnum.rs GitHub Actions / check_features (ubuntu) use of deprecated method `rand::Rng::gen`: Renamed to `random` to avoid conflict with the new `gen` keyword in Rust 2024. Check failure on line 61 in src/numbers/floatnum.rs GitHub Actions / lint use of deprecated method `rand::Rng::gen`: Renamed to `random` to avoid conflict with the new `gen` keyword in Rust 2024. Check warning on line 61 in src/numbers/floatnum.rs GitHub Actions / tests (macos, aarch64-apple-darwin) use of deprecated method `rand::Rng::gen`: Renamed to `random` to avoid conflict with the new `gen` keyword in Rust 2024.
	}

	fn two() -> Self {
	fn rand() -> f32 {
	use rand::Rng;
	let mut rng = get_rng_impl(None);
	rng.gen()
Check warning on line 103 in src/numbers/floatnum.rs GitHub Actions / check_features (ubuntu) use of deprecated method `rand::Rng::gen`: Renamed to `random` to avoid conflict with the new `gen` keyword in Rust 2024. Check failure on line 103 in src/numbers/floatnum.rs GitHub Actions / lint use of deprecated method `rand::Rng::gen`: Renamed to `random` to avoid conflict with the new `gen` keyword in Rust 2024. Check warning on line 103 in src/numbers/floatnum.rs GitHub Actions / tests (macos, aarch64-apple-darwin) use of deprecated method `rand::Rng::gen`: Renamed to `random` to avoid conflict with the new `gen` keyword in Rust 2024.
	}

	fn two() -> Self {
	let mut small_rng = get_rng_impl(None);

	let mut rngs: Vec<SmallRng> = (0..3)
	.map(\|_\| SmallRng::from_rng(&mut small_rng).unwrap())
Check failure on line 73 in src/numbers/realnum.rs GitHub Actions / check_features (ubuntu) no method named `unwrap` found for struct `SmallRng` in the current scope Check failure on line 73 in src/numbers/realnum.rs GitHub Actions / lint no method named `unwrap` found for struct `rand::prelude::SmallRng` in the current scope Check failure on line 73 in src/numbers/realnum.rs GitHub Actions / tests (macos, aarch64-apple-darwin) no method named `unwrap` found for struct `SmallRng` in the current scope
	.collect();
	rngs[0].gen::<f64>()
	}
	let mut small_rng = get_rng_impl(None);

	let mut rngs: Vec<SmallRng> = (0..3)
	.map(\|_\| SmallRng::from_rng(&mut small_rng).unwrap())
Check failure on line 122 in src/numbers/realnum.rs GitHub Actions / check_features (ubuntu) no method named `unwrap` found for struct `SmallRng` in the current scope Check failure on line 122 in src/numbers/realnum.rs GitHub Actions / lint no method named `unwrap` found for struct `rand::prelude::SmallRng` in the current scope Check failure on line 122 in src/numbers/realnum.rs GitHub Actions / tests (macos, aarch64-apple-darwin) no method named `unwrap` found for struct `SmallRng` in the current scope
	.collect();
	rngs[0].gen::<f32>()
	}
	cfg_if::cfg_if! {
	if #[cfg(feature = "std_rand")] {
	use rand::RngCore;
	RngImpl::seed_from_u64(rand::thread_rng().next_u64())
Check failure on line 15 in src/rand_custom.rs GitHub Actions / lint cannot find function `thread_rng` in crate `rand` Check failure on line 15 in src/rand_custom.rs GitHub Actions / tests (macos, aarch64-apple-darwin) cannot find function `thread_rng` in crate `rand`
	} else {
	// no std_random feature build, use getrandom
	#[cfg(feature = "js")]
	//! # Dataset Generators
	//!
	use rand::distributions::Uniform;
Check failure on line 3 in src/dataset/generator.rs GitHub Actions / lint unresolved import `rand::distributions` Check failure on line 3 in src/dataset/generator.rs GitHub Actions / tests (macos, aarch64-apple-darwin) unresolved import `rand::distributions` Check failure on line 3 in src/dataset/generator.rs GitHub Actions / coverage unresolved import `rand::distributions`
	use rand::prelude::*;
	use rand_distr::Normal;

	let cluster_std = 1.0;
	let mut centers: Vec<Vec<Normal<f32>>> = Vec::with_capacity(num_centers);

	let mut rng = rand::thread_rng();
Check failure on line 19 in src/dataset/generator.rs GitHub Actions / lint cannot find function `thread_rng` in crate `rand` Check failure on line 19 in src/dataset/generator.rs GitHub Actions / tests (macos, aarch64-apple-darwin) cannot find function `thread_rng` in crate `rand`
	for _ in 0..num_centers {
	centers.push(
	(0..num_features)
	let label = i % num_centers;
	y.push(label as f32);
	for j in 0..num_features {
	x.push(centers[label][j].sample(&mut rng));
Check failure on line 35 in src/dataset/generator.rs GitHub Actions / tests (macos, aarch64-apple-darwin) the method `sample` exists for struct `Normal<f32>`, but its trait bounds were not satisfied
	}
	}

	let linspace_in = linspace(0.0, 2.0 * std::f32::consts::PI, num_samples_in);

	let noise = Normal::new(0.0, noise).unwrap();
	let mut rng = rand::thread_rng();
Check failure on line 63 in src/dataset/generator.rs GitHub Actions / lint cannot find function `thread_rng` in crate `rand` Check failure on line 63 in src/dataset/generator.rs GitHub Actions / tests (macos, aarch64-apple-darwin) cannot find function `thread_rng` in crate `rand`

	let mut x: Vec<f32> = Vec::with_capacity(num_samples * 2);
	let mut y: Vec<f32> = Vec::with_capacity(num_samples);

	for v in linspace_out {
	x.push(v.cos() + noise.sample(&mut rng));
Check failure on line 69 in src/dataset/generator.rs GitHub Actions / tests (macos, aarch64-apple-darwin) the method `sample` exists for struct `Normal<f32>`, but its trait bounds were not satisfied
	x.push(v.sin() + noise.sample(&mut rng));
Check failure on line 70 in src/dataset/generator.rs GitHub Actions / tests (macos, aarch64-apple-darwin) the method `sample` exists for struct `Normal<f32>`, but its trait bounds were not satisfied
	y.push(0.0);
	}

	let linspace_in = linspace(0.0, std::f32::consts::PI, num_samples_in);

	let noise = Normal::new(0.0, noise).unwrap();
	let mut rng = rand::thread_rng();
Check failure on line 100 in src/dataset/generator.rs GitHub Actions / lint cannot find function `thread_rng` in crate `rand` Check failure on line 100 in src/dataset/generator.rs GitHub Actions / tests (macos, aarch64-apple-darwin) cannot find function `thread_rng` in crate `rand`

	let mut x: Vec<f32> = Vec::with_capacity(num_samples * 2);
	let mut y: Vec<f32> = Vec::with_capacity(num_samples);