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ArmavicaArmavica
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Cargo fmt
1 parent 62ba446 commit 878abc3

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5 files changed

+59
-78
lines changed

5 files changed

+59
-78
lines changed

‎benches/deviation.rs‎

Lines changed: 8 additions & 13 deletions
Original file line numberDiff line numberDiff line change
@@ -1,27 +1,22 @@
11
use criterion::{
2-
black_box, criterion_group, criterion_main, AxisScale, Criterion,
3-
PlotConfiguration,
2+
black_box, criterion_group, criterion_main, AxisScale, Criterion, PlotConfiguration,
43
};
54
use ndarray::prelude::*;
5+
use ndarray_rand::rand_distr::Uniform;
66
use ndarray_rand::RandomExt;
77
use ndarray_stats::DeviationExt;
8-
use ndarray_rand::rand_distr::Uniform;
98

109
fn sq_l2_dist(c: &mut Criterion) {
1110
let lens = vec![10, 100, 1000, 10000];
1211
let mut group = c.benchmark_group("sq_l2_dist");
13-
group.plot_config(
14-
PlotConfiguration::default().summary_scale(AxisScale::Logarithmic));
12+
group.plot_config(PlotConfiguration::default().summary_scale(AxisScale::Logarithmic));
1513
for len in &lens {
16-
group.bench_with_input(
17-
format!("{}", len),
18-
len,
19-
|b, &len| {
20-
let data = Array::random(len, Uniform::new(0.0, 1.0));
21-
let data2 = Array::random(len, Uniform::new(0.0, 1.0));
14+
group.bench_with_input(format!("{}", len), len, |b, &len| {
15+
let data = Array::random(len, Uniform::new(0.0, 1.0));
16+
let data2 = Array::random(len, Uniform::new(0.0, 1.0));
2217

23-
b.iter(|| black_box(data.sq_l2_dist(&data2).unwrap()))
24-
});
18+
b.iter(|| black_box(data.sq_l2_dist(&data2).unwrap()))
19+
});
2520
}
2621
group.finish();
2722
}

‎benches/sort.rs‎

Lines changed: 31 additions & 40 deletions
Original file line numberDiff line numberDiff line change
@@ -1,6 +1,5 @@
11
use criterion::{
2-
black_box, criterion_group, criterion_main, AxisScale, BatchSize, Criterion,
3-
PlotConfiguration,
2+
black_box, criterion_group, criterion_main, AxisScale, BatchSize, Criterion, PlotConfiguration,
43
};
54
use ndarray::prelude::*;
65
use ndarray_stats::Sort1dExt;
@@ -9,53 +8,45 @@ use rand::prelude::*;
98
fn get_from_sorted_mut(c: &mut Criterion) {
109
let lens = vec![10, 100, 1000, 10000];
1110
let mut group = c.benchmark_group("get_from_sorted_mut");
12-
group.plot_config(
13-
PlotConfiguration::default().summary_scale(AxisScale::Logarithmic));
11+
group.plot_config(PlotConfiguration::default().summary_scale(AxisScale::Logarithmic));
1412
for len in &lens {
15-
group.bench_with_input(
16-
format!("{}", len),
17-
len,
18-
|b, &len| {
19-
let mut rng = StdRng::seed_from_u64(42);
20-
let mut data: Vec<_> = (0..len).collect();
21-
data.shuffle(&mut rng);
22-
let indices: Vec<_> = (0..len).step_by(len / 10).collect();
23-
b.iter_batched(
24-
|| Array1::from(data.clone()),
25-
|mut arr| {
26-
for &i in &indices {
27-
black_box(arr.get_from_sorted_mut(i));
28-
}
29-
},
30-
BatchSize::SmallInput,
31-
)
32-
});
13+
group.bench_with_input(format!("{}", len), len, |b, &len| {
14+
let mut rng = StdRng::seed_from_u64(42);
15+
let mut data: Vec<_> = (0..len).collect();
16+
data.shuffle(&mut rng);
17+
let indices: Vec<_> = (0..len).step_by(len / 10).collect();
18+
b.iter_batched(
19+
|| Array1::from(data.clone()),
20+
|mut arr| {
21+
for &i in &indices {
22+
black_box(arr.get_from_sorted_mut(i));
23+
}
24+
},
25+
BatchSize::SmallInput,
26+
)
27+
});
3328
}
3429
group.finish();
3530
}
3631

3732
fn get_many_from_sorted_mut(c: &mut Criterion) {
3833
let lens = vec![10, 100, 1000, 10000];
3934
let mut group = c.benchmark_group("get_many_from_sorted_mut");
40-
group.plot_config(
41-
PlotConfiguration::default().summary_scale(AxisScale::Logarithmic));
35+
group.plot_config(PlotConfiguration::default().summary_scale(AxisScale::Logarithmic));
4236
for len in &lens {
43-
group.bench_with_input(
44-
format!("{}", len),
45-
len,
46-
|b, &len| {
47-
let mut rng = StdRng::seed_from_u64(42);
48-
let mut data: Vec<_> = (0..len).collect();
49-
data.shuffle(&mut rng);
50-
let indices: Array1<_> = (0..len).step_by(len / 10).collect();
51-
b.iter_batched(
52-
|| Array1::from(data.clone()),
53-
|mut arr| {
54-
black_box(arr.get_many_from_sorted_mut(&indices));
55-
},
56-
BatchSize::SmallInput,
57-
)
58-
});
37+
group.bench_with_input(format!("{}", len), len, |b, &len| {
38+
let mut rng = StdRng::seed_from_u64(42);
39+
let mut data: Vec<_> = (0..len).collect();
40+
data.shuffle(&mut rng);
41+
let indices: Array1<_> = (0..len).step_by(len / 10).collect();
42+
b.iter_batched(
43+
|| Array1::from(data.clone()),
44+
|mut arr| {
45+
black_box(arr.get_many_from_sorted_mut(&indices));
46+
},
47+
BatchSize::SmallInput,
48+
)
49+
});
5950
}
6051
group.finish();
6152
}

‎benches/summary_statistics.rs‎

Lines changed: 15 additions & 20 deletions
Original file line numberDiff line numberDiff line change
@@ -1,33 +1,28 @@
11
use criterion::{
2-
black_box, criterion_group, criterion_main, AxisScale, BatchSize, Criterion,
3-
PlotConfiguration,
2+
black_box, criterion_group, criterion_main, AxisScale, BatchSize, Criterion, PlotConfiguration,
43
};
54
use ndarray::prelude::*;
5+
use ndarray_rand::rand_distr::Uniform;
66
use ndarray_rand::RandomExt;
77
use ndarray_stats::SummaryStatisticsExt;
8-
use ndarray_rand::rand_distr::Uniform;
98

109
fn weighted_std(c: &mut Criterion) {
1110
let lens = vec![10, 100, 1000, 10000];
1211
let mut group = c.benchmark_group("weighted_std");
13-
group.plot_config(
14-
PlotConfiguration::default().summary_scale(AxisScale::Logarithmic));
12+
group.plot_config(PlotConfiguration::default().summary_scale(AxisScale::Logarithmic));
1513
for len in &lens {
16-
group.bench_with_input(
17-
format!("{}", len),
18-
len,
19-
|b, &len| {
20-
let data = Array::random(len, Uniform::new(0.0, 1.0));
21-
let mut weights = Array::random(len, Uniform::new(0.0, 1.0));
22-
weights /= weights.sum();
23-
b.iter_batched(
24-
|| data.clone(),
25-
|arr| {
26-
black_box(arr.weighted_std(&weights, 0.0).unwrap());
27-
},
28-
BatchSize::SmallInput,
29-
)
30-
});
14+
group.bench_with_input(format!("{}", len), len, |b, &len| {
15+
let data = Array::random(len, Uniform::new(0.0, 1.0));
16+
let mut weights = Array::random(len, Uniform::new(0.0, 1.0));
17+
weights /= weights.sum();
18+
b.iter_batched(
19+
|| data.clone(),
20+
|arr| {
21+
black_box(arr.weighted_std(&weights, 0.0).unwrap());
22+
},
23+
BatchSize::SmallInput,
24+
)
25+
});
3126
}
3227
group.finish();
3328
}

‎src/correlation.rs‎

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -185,10 +185,10 @@ where
185185
mod cov_tests {
186186
use super::*;
187187
use ndarray::array;
188-
use ndarray_rand::RandomExt;
189-
use quickcheck_macros::quickcheck;
190188
use ndarray_rand::rand;
191189
use ndarray_rand::rand_distr::Uniform;
190+
use ndarray_rand::RandomExt;
191+
use quickcheck_macros::quickcheck;
192192

193193
#[quickcheck]
194194
fn constant_random_variables_have_zero_covariance_matrix(value: f64) -> bool {
@@ -289,9 +289,9 @@ mod pearson_correlation_tests {
289289
use super::*;
290290
use ndarray::array;
291291
use ndarray::Array;
292-
use quickcheck_macros::quickcheck;
293-
use ndarray_rand::RandomExt;
294292
use ndarray_rand::rand_distr::Uniform;
293+
use ndarray_rand::RandomExt;
294+
use quickcheck_macros::quickcheck;
295295

296296
#[quickcheck]
297297
fn output_matrix_is_symmetric(bound: f64) -> bool {

‎tests/summary_statistics.rs‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -1,13 +1,13 @@
11
use approx::{abs_diff_eq, assert_abs_diff_eq};
22
use ndarray::{arr0, array, Array, Array1, Array2, Axis};
3+
use ndarray_rand::rand_distr::Uniform;
34
use ndarray_rand::RandomExt;
45
use ndarray_stats::{
56
errors::{EmptyInput, MultiInputError, ShapeMismatch},
67
SummaryStatisticsExt,
78
};
89
use noisy_float::types::N64;
910
use quickcheck::{quickcheck, TestResult};
10-
use ndarray_rand::rand_distr::Uniform;
1111
use std::f64;
1212

1313
#[test]

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