malachite-nz 0.9.2

The bignum types Natural and Integer, with efficient algorithms partially derived from GMP and FLINT.
Documentation 
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// Copyright © 2026 Mikhail Hogrefe
//
// This file is part of Malachite.
//
// Malachite is free software: you can redistribute it and/or modify it under the terms of the GNU
// Lesser General Public License (LGPL) as published by the Free Software Foundation; either version
// 3 of the License, or (at your option) any later version. See <https://www.gnu.org/licenses/>.

use malachite_base::num::float::NiceFloat;
use malachite_base::random::EXAMPLE_SEED;
use malachite_base::test_util::stats::moments::MomentStats;
use malachite_nz::integer::Integer;
use malachite_nz::integer::random::uniform_random_integer_range;
use malachite_nz::test_util::integer::random::random_integers_helper_helper;
use std::str::FromStr;

fn uniform_random_integer_range_helper(
    a: &str,
    b: &str,
    expected_values: &[&str],
    expected_common_values: &[(&str, usize)],
    expected_sample_median: (&str, Option<&str>),
    expected_sample_moment_stats: MomentStats,
) {
    random_integers_helper_helper(
        uniform_random_integer_range(
            EXAMPLE_SEED,
            Integer::from_str(a).unwrap(),
            Integer::from_str(b).unwrap(),
        ),
        expected_values,
        expected_common_values,
        expected_sample_median,
        expected_sample_moment_stats,
    );
}

#[test]
fn test_uniform_random_integer_range() {
    let values = &["0"; 20];
    let common_values = &[("0", 1000000)];
    let sample_median = ("0", None);
    let sample_moment_stats = MomentStats {
        mean: NiceFloat(0.0),
        standard_deviation: NiceFloat(0.0),
        skewness: NiceFloat(f64::NAN),
        excess_kurtosis: NiceFloat(f64::NAN),
    };
    uniform_random_integer_range_helper(
        "0",
        "1",
        values,
        common_values,
        sample_median,
        sample_moment_stats,
    );
    let values = &[
        "-3", "3", "1", "1", "3", "-3", "-2", "-4", "-2", "-1", "0", "-1", "2", "1", "2", "2",
        "-1", "-3", "-1", "3",
    ];
    let common_values = &[
        ("-2", 125739),
        ("-1", 125293),
        ("2", 125220),
        ("3", 125016),
        ("-4", 124976),
        ("1", 124665),
        ("-3", 124627),
        ("0", 124464),
    ];
    let sample_median = ("-1", None);
    let sample_moment_stats = MomentStats {
        mean: NiceFloat(-0.5004029999999962),
        standard_deviation: NiceFloat(2.291244004332587),
        skewness: NiceFloat(0.0011305808123400524),
        excess_kurtosis: NiceFloat(-1.2381429974564255),
    };
    uniform_random_integer_range_helper(
        "-4",
        "4",
        values,
        common_values,
        sample_median,
        sample_moment_stats,
    );
    let values = &[
        "1023", "1025", "1023", "1023", "1025", "1023", "1024", "1022", "1024", "1025", "1022",
        "1025", "1024", "1023", "1024", "1024", "1025", "1023", "1025", "1025",
    ];
    let common_values = &[("1024", 250959), ("1025", 250309), ("1022", 249440), ("1023", 249292)];
    let sample_median = ("1024", None);
    let sample_moment_stats = MomentStats {
        mean: NiceFloat(1023.5021369999873),
        standard_deviation: NiceFloat(1.1178079811513417),
        skewness: NiceFloat(-0.003486279405775989),
        excess_kurtosis: NiceFloat(-1.3594690811608392),
    };
    uniform_random_integer_range_helper(
        "1022",
        "1026",
        values,
        common_values,
        sample_median,
        sample_moment_stats,
    );
    let values = &[
        "-1025", "-1023", "-1025", "-1025", "-1023", "-1025", "-1024", "-1026", "-1024", "-1023",
        "-1026", "-1023", "-1024", "-1025", "-1024", "-1024", "-1023", "-1025", "-1023", "-1023",
    ];
    let common_values =
        &[("-1024", 250959), ("-1023", 250309), ("-1026", 249440), ("-1025", 249292)];
    let sample_median = ("-1024", None);
    let sample_moment_stats = MomentStats {
        mean: NiceFloat(-1024.4978629999973),
        standard_deviation: NiceFloat(1.1178079811512938),
        skewness: NiceFloat(-0.0034862794057047334),
        excess_kurtosis: NiceFloat(-1.3594690811609873),
    };
    uniform_random_integer_range_helper(
        "-1026",
        "-1022",
        values,
        common_values,
        sample_median,
        sample_moment_stats,
    );
    let values = &[
        "7279", "1141", "3725", "8735", "8576", "4611", "-916", "5299", "2421", "2094", "8430",
        "-253", "5785", "1183", "9525", "1201", "3280", "3065", "6206", "8542",
    ];
    let common_values = &[
        ("3214", 127),
        ("7954", 126),
        ("2592", 125),
        ("6885", 125),
        ("7656", 125),
        ("2344", 124),
        ("6392", 124),
        ("4426", 123),
        ("-312", 122),
        ("1519", 122),
    ];
    let sample_median = ("4509", None);
    let sample_moment_stats = MomentStats {
        mean: NiceFloat(4503.707855999995),
        standard_deviation: NiceFloat(3172.2131846202396),
        skewness: NiceFloat(-0.0021819995553274013),
        excess_kurtosis: NiceFloat(-1.196969134950911),
    };
    uniform_random_integer_range_helper(
        "-1000",
        "10000",
        values,
        common_values,
        sample_median,
        sample_moment_stats,
    );
}

#[test]
#[should_panic]
fn uniform_random_integer_range_fail_1() {
    uniform_random_integer_range(EXAMPLE_SEED, Integer::from(-9), Integer::from(-10));
}

#[test]
#[should_panic]
fn uniform_random_integer_range_fail_2() {
    uniform_random_integer_range(EXAMPLE_SEED, Integer::from(-10), Integer::from(-10));
}