This crate is part of Russell - Rust Scientific Library
This repository contains structures and functions to work with statistics and probability distributions. Internally, we wrap and use the rand_distr crate for generating samples.
Documentation:
Add this to your Cargo.toml (choose the right version):
toml
[dependencies]
russell_stat = "*"
```rust use russell_stat::{statistics, DistributionFrechet, Histogram, ProbabilityDistribution, StrError};
fn main() -> Result<(), StrError> { // generate samples let mut rng = rand::threadrng(); let dist = DistributionFrechet::new(0.0, 1.0, 1.0)?; let nsamples = 10000; let mut data = vec![0.0; nsamples]; for i in 0..nsamples { data[i] = dist.sample(&mut rng); } println!("{}", statistics(&data));
// text-plot
let stations = (0..20).map(|i| (i as f64) * 0.5).collect::<Vec<f64>>();
let mut hist = Histogram::new(&stations)?;
hist.count(&data);
println!("{}", hist);
Ok(())
} ```
Sample output:
```text min = 0.09073675834496424 max = 7694.599272007603 mean = 10.392955760859788 std_dev = 137.11729225249485
[ 0,0.5) | 1407 🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦 [0.5, 1) | 2335 🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦 [ 1,1.5) | 1468 🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦 [1.5, 2) | 913 🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦🟦 [ 2,2.5) | 640 🟦🟦🟦🟦🟦🟦🟦🟦 [2.5, 3) | 420 🟦🟦🟦🟦🟦 [ 3,3.5) | 358 🟦🟦🟦🟦 [3.5, 4) | 269 🟦🟦🟦 [ 4,4.5) | 207 🟦🟦 [4.5, 5) | 185 🟦🟦 [ 5,5.5) | 143 🟦 [5.5, 6) | 137 🟦 [ 6,6.5) | 99 🟦 [6.5, 7) | 76 [ 7,7.5) | 88 🟦 [7.5, 8) | 73 [ 8,8.5) | 51 [8.5, 9) | 63 [ 9,9.5) | 53 sum = 8985 ```
```rust use russell_stat::{statistics, DistributionGumbel, Histogram, ProbabilityDistribution, StrError};
fn main() -> Result<(), StrError> { // generate samples let mut rng = rand::threadrng(); let dist = DistributionGumbel::new(0.5, 2.0)?; let nsamples = 10000; let mut data = vec![0.0; nsamples]; for i in 0..nsamples { data[i] = dist.sample(&mut rng); } println!("{}", statistics(&data));
// text-plot
let stations = (0..20).map(|i| -5.0 + (i as f64)).collect::<Vec<f64>>();
let mut hist = Histogram::new(&stations)?;
hist.set_bar_char('#').set_bar_max_len(40);
hist.count(&data);
println!("{}", hist);
Ok(())
} ```
Sample output
```text min = -3.8702217016220706 max = 18.48991150178352 mean = 1.68369488450194 std_dev = 2.5805268053167527
[-5,-4) | 0 [-4,-3) | 38 [-3,-2) | 264 ##### [-2,-1) | 929 ################### [-1, 0) | 1457 ############################### [ 0, 1) | 1880 ######################################## [ 1, 2) | 1610 ################################## [ 2, 3) | 1283 ########################### [ 3, 4) | 910 ################### [ 4, 5) | 604 ############ [ 5, 6) | 398 ######## [ 6, 7) | 226 #### [ 7, 8) | 153 ### [ 8, 9) | 96 ## [ 9,10) | 57 # [10,11) | 42 [11,12) | 22 [12,13) | 9 [13,14) | 14 sum = 9992 ```
```rust use russell_stat::{statistics, DistributionNormal, Histogram, ProbabilityDistribution, StrError};
fn main() -> Result<(), StrError> { // generate samples let mut rng = rand::threadrng(); let dist = DistributionNormal::new(0.0, 1.0)?; let nsamples = 10000; let mut data = vec![0.0; nsamples]; for i in 0..nsamples { data[i] = dist.sample(&mut rng); } println!("{}", statistics(&data));
// text-plot
let stations = (0..20).map(|i| -4.0 + (i as f64) * 0.5).collect::<Vec<f64>>();
let mut hist = Histogram::new(&stations)?;
hist.set_bar_char('🍕').set_bar_max_len(30);
hist.count(&data);
println!("{:.2}", hist);
Ok(())
} ```
Sample output:
```text min = -3.466424128646902 max = 3.608012748101761 mean = 0.003299589990111208 std_dev = 0.9760553437435371
[-4.00,-3.50) | 0 [-3.50,-3.00) | 10 [-3.00,-2.50) | 41 [-2.50,-2.00) | 156 🍕🍕 [-2.00,-1.50) | 443 🍕🍕🍕🍕🍕🍕 [-1.50,-1.00) | 869 🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕 [-1.00,-0.50) | 1450 🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕 [-0.50, 0.00) | 1971 🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕 [ 0.00, 0.50) | 1996 🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕 [ 0.50, 1.00) | 1499 🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕 [ 1.00, 1.50) | 951 🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕🍕 [ 1.50, 2.00) | 419 🍕🍕🍕🍕🍕🍕 [ 2.00, 2.50) | 150 🍕🍕 [ 2.50, 3.00) | 34 [ 3.00, 3.50) | 10 [ 3.50, 4.00) | 1 [ 4.00, 4.50) | 0 [ 4.50, 5.00) | 0 [ 5.00, 5.50) | 0 sum = 10000 ```
```rust use russell_stat::{statistics, DistributionLognormal, Histogram, ProbabilityDistribution, StrError};
fn main() -> Result<(), StrError> { // generate samples let mut rng = rand::threadrng(); let dist = DistributionLognormal::new(0.0, 0.25)?; let nsamples = 10000; let mut data = vec![0.0; nsamples]; for i in 0..nsamples { data[i] = dist.sample(&mut rng); } println!("{}", statistics(&data));
// text-plot
let stations = (0..25).map(|i| (i as f64) * 0.1).collect::<Vec<f64>>();
let mut hist = Histogram::new(&stations)?;
hist.set_bar_char('✨').set_bar_max_len(30);
hist.count(&data);
println!("{:.2}", hist);
Ok(())
} ```
Sample output:
```text min = 0.42738183908592275 max = 2.5343346501352135 mean = 1.0330160154674082 std_dev = 0.2610005570820734
[0.00,0.10) | 0 [0.10,0.20) | 0 [0.20,0.30) | 0 [0.30,0.40) | 0 [0.40,0.50) | 33 [0.50,0.60) | 155 ✨✨ [0.60,0.70) | 558 ✨✨✨✨✨✨✨✨✨✨ [0.70,0.80) | 1092 ✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨ [0.80,0.90) | 1494 ✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨ [0.90,1.00) | 1622 ✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨ [1.00,1.10) | 1509 ✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨ [1.10,1.20) | 1275 ✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨ [1.20,1.30) | 817 ✨✨✨✨✨✨✨✨✨✨✨✨✨✨✨ [1.30,1.40) | 552 ✨✨✨✨✨✨✨✨✨✨ [1.40,1.50) | 364 ✨✨✨✨✨✨ [1.50,1.60) | 202 ✨✨✨ [1.60,1.70) | 151 ✨✨ [1.70,1.80) | 77 ✨ [1.80,1.90) | 49 [1.90,2.00) | 21 [2.00,2.10) | 14 [2.10,2.20) | 7 [2.20,2.30) | 5 [2.30,2.40) | 0 sum = 9997 ```
```rust use russell_stat::{statistics, DistributionUniform, Histogram, ProbabilityDistribution, StrError};
fn main() -> Result<(), StrError> { // generate samples let mut rng = rand::threadrng(); let dist = DistributionUniform::new(-10.0, 10.0)?; let nsamples = 10000; let mut data = vec![0.0; nsamples]; for i in 0..nsamples { data[i] = dist.sample(&mut rng); } println!("{}", statistics(&data));
// text-plot
let stations = (0..21).map(|i| -10.0 + (i as f64)).collect::<Vec<f64>>();
let mut hist = Histogram::new(&stations)?;
hist.set_bar_char('🟪').set_bar_max_len(30);
hist.count(&data);
println!("{:.2}", hist);
Ok(())
} ```
Sample output:
```text min = -9.995565022955866 max = 9.997897516369218 mean = 0.006907240624592568 std_dev = 5.761189943810604
[-10.00, -9.00) | 488 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ -9.00, -8.00) | 488 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ -8.00, -7.00) | 490 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ -7.00, -6.00) | 537 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ -6.00, -5.00) | 503 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ -5.00, -4.00) | 510 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ -4.00, -3.00) | 487 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ -3.00, -2.00) | 453 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ -2.00, -1.00) | 537 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ -1.00, 0.00) | 518 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ 0.00, 1.00) | 499 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ 1.00, 2.00) | 496 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ 2.00, 3.00) | 466 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ 3.00, 4.00) | 521 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ 4.00, 5.00) | 490 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ 5.00, 6.00) | 498 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ 6.00, 7.00) | 518 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ 7.00, 8.00) | 513 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ 8.00, 9.00) | 535 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 [ 9.00, 10.00) | 453 🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪🟪 sum = 10000 ```