utils-box-mathematics 1.0.1

#[derive(Debug, PartialEq)]
pub enum MedianMissingMode {
    IncludeNaN,
    OmitNaN,
}

#[derive(Debug, PartialEq)]
pub enum MedianPaddingMode {
    ZeroPad,
    Truncate,
}

/// Wrapper to call median_filter() with the most useful configuration
/// ZeroPad and IncludeNaN are active
pub fn medianfilter_default(x: &[f64], n: usize) -> Vec<f64> {
    moving_median_filter(
        x,
        n,
        MedianPaddingMode::ZeroPad,
        MedianMissingMode::IncludeNaN,
    )
}

/// An implementation of Moving Median Filtering
/// Returns the filtered data after using medians of a moving n-point window over the data
/// It is the equivelant of MATLAB's movmedian() function for 1D arrays
pub fn moving_median_filter(
    x: &[f64],
    n: usize,
    padding: MedianPaddingMode,
    missing: MedianMissingMode,
) -> Vec<f64> {
    let len = x.len();
    let mut y = vec![0.0; len];
    for (i, y_value) in y.iter_mut().enumerate() {
        let mut segment: Vec<f64> = vec![];
        let mut segment_start: i64 = i as i64 - (n as i64 - 1) / 2;
        if n.is_multiple_of(2) {
            segment_start = i as i64 - n as i64 / 2;
        }
        for j in 0..n {
            let index = segment_start + j as i64;
            if index < 0 || index >= len as i64 {
                match padding {
                    MedianPaddingMode::ZeroPad => segment.push(0.0),
                    MedianPaddingMode::Truncate => continue,
                }
            } else {
                segment.push(x[index as usize]);
            }
        }

        if missing == MedianMissingMode::OmitNaN {
            segment = remove_nan(&segment);
        }

        if segment.iter().any(|x| x.is_nan()) {
            *y_value = f64::NAN;
            continue;
        }

        segment.sort_by(|a, b| a.partial_cmp(b).unwrap());

        if segment.len() % 2 == 1 {
            *y_value = segment[segment.len() / 2];
        } else {
            let middle = segment.len() / 2;
            *y_value = (segment[middle - 1] + segment[middle]) / 2.0;
        }
    }

    y
}

fn remove_nan(segment: &[f64]) -> Vec<f64> {
    segment.iter().filter(|x| !x.is_nan()).copied().collect()
}

#[cfg(test)]
mod tests {
    use crate::median_filter::*;

    #[test]
    fn remove_nan_test_nan_array() {
        let nan_array = vec![f64::NAN; 50];
        assert_eq!(50, nan_array.len());
        let result = remove_nan(&nan_array);
        assert_eq!(0, result.len());
    }

    #[test]
    fn remove_nan_test_non_nan_array() {
        let nan_array = vec![2.0_f64; 50];
        assert_eq!(50, nan_array.len());
        let result = remove_nan(&nan_array);
        assert_eq!(50, result.len());
    }

    #[test]
    fn omit_nan_test_odd_window() {
        let nan_array = vec![
            4.0,
            8.0,
            f64::NAN,
            -1.0,
            -2.0,
            -3.0,
            f64::NAN,
            3.0,
            4.0,
            5.0,
        ];
        let expected = vec![
            6.0000, 6.0000, 3.5000, -1.5000, -2.0000, -2.5000, 0.0, 3.5000, 4.0000, 4.5000,
        ];

        let result = moving_median_filter(
            &nan_array,
            3,
            MedianPaddingMode::Truncate,
            MedianMissingMode::OmitNaN,
        );
        assert_eq!(expected, result);
    }

    #[test]
    fn omit_nan_test_even_window() {
        let nan_array = vec![
            4.0,
            8.0,
            f64::NAN,
            -1.0,
            -2.0,
            -3.0,
            f64::NAN,
            3.0,
            4.0,
            5.0,
        ];
        let expected = vec![
            6.0000, 6.0000, 4.0000, -1.0, -2.0000, -2.0000, -2.0, 3.000, 4.0000, 4.0000,
        ];

        let result = moving_median_filter(
            &nan_array,
            4,
            MedianPaddingMode::Truncate,
            MedianMissingMode::OmitNaN,
        );
        assert_eq!(expected, result);
    }

    #[test]
    fn include_nan_test_odd_window() {
        let nan_array = vec![
            4.0,
            8.0,
            f64::NAN,
            -1.0,
            -2.0,
            -3.0,
            f64::NAN,
            3.0,
            4.0,
            5.0,
        ];
        let expected = vec![
            6.0000,
            f64::NAN,
            f64::NAN,
            f64::NAN,
            -2.0000,
            f64::NAN,
            f64::NAN,
            f64::NAN,
            4.0000,
            4.5000,
        ];

        let result = moving_median_filter(
            &nan_array,
            3,
            MedianPaddingMode::Truncate,
            MedianMissingMode::IncludeNaN,
        );

        for (idx, &value) in expected.iter().enumerate() {
            if value.is_nan() {
                assert!(result[idx].is_nan());
                continue;
            }
            assert_eq!(
                (value * 100.0_f64).round() / 100.0,
                (result[idx] * 100.0).round() / 100.0
            );
        }
    }

    #[test]
    fn include_nan_test_even_window() {
        let nan_array = vec![
            4.0,
            8.0,
            f64::NAN,
            -1.0,
            -2.0,
            -3.0,
            f64::NAN,
            3.0,
            4.0,
            5.0,
        ];
        let expected = vec![
            6.0000,
            f64::NAN,
            f64::NAN,
            f64::NAN,
            f64::NAN,
            f64::NAN,
            f64::NAN,
            f64::NAN,
            f64::NAN,
            4.0000,
        ];

        let result = moving_median_filter(
            &nan_array,
            4,
            MedianPaddingMode::Truncate,
            MedianMissingMode::IncludeNaN,
        );

        for (idx, &value) in expected.iter().enumerate() {
            if value.is_nan() {
                assert!(result[idx].is_nan());
                continue;
            }
            assert_eq!(
                (value * 100.0_f64).round() / 100.0,
                (result[idx] * 100.0).round() / 100.0
            );
        }
    }

    #[test]
    fn median_test() {
        /*
         * fs = 100;
         * t = 0:1/fs:1;
         * x = sin(2*pi*t*3)+0.25*sin(2*pi*t*40);
         * y = medfilt1(x,10);
         * %plot(t,x,t,y)
         * y
         */

        let data = vec![
            0.0, 0.3343, 0.1304, 0.7736, 0.5376, 0.8090, 1.0518, 0.7308, 1.2358, 0.8452, 0.9511,
            1.0233, 0.5327, 0.8752, 0.3348, 0.3090, 0.2723, -0.3006, -0.0109, -0.5727, -0.5878,
            -0.5820, -1.0821, -0.6920, -1.1292, -1.0000, -0.8353, -1.1675, -0.6066, -0.8759,
            -0.5878, -0.2788, -0.4865, 0.1750, -0.0216, 0.3090, 0.6287, 0.3997, 1.0083, 0.7294,
            0.9511, 1.1391, 0.7603, 1.2063, 0.7579, 0.8090, 0.8315, 0.2981, 0.6059, 0.0404,
            -0.0000, -0.0404, -0.6059, -0.2981, -0.8315, -0.8090, -0.7579, -1.2063, -0.7603,
            -1.1391, -0.9511, -0.7294, -1.0083, -0.3997, -0.6287, -0.3090, 0.0216, -0.1750, 0.4865,
            0.2788, 0.5878, 0.8759, 0.6066, 1.1675, 0.8353, 1.0000, 1.1292, 0.6920, 1.0821, 0.5820,
            0.5878, 0.5727, 0.0109, 0.3006, -0.2723, -0.3090, -0.3348, -0.8752, -0.5327, -1.0233,
            -0.9511, -0.8452, -1.2358, -0.7308, -1.0518, -0.8090, -0.5376, -0.7736, -0.1304,
            -0.3343, -0.0000,
        ];

        let expected_outcome = vec![
            0.0, 0.0652, 0.2324, 0.4359, 0.6342, 0.7522, 0.7913, 0.8271, 0.8271, 0.8602, 0.8602,
            0.8602, 0.788, 0.6889, 0.4338, 0.3219, 0.2906, 0.1307, -0.1557, -0.4366, -0.5773,
            -0.5849, -0.6399, -0.7636, -0.7636, -0.8556, -0.8556, -0.8556, -0.7636, -0.7209,
            -0.5972, -0.5371, -0.3826, -0.1502, 0.0767, 0.242, 0.3544, 0.5142, 0.6791, 0.7449,
            0.7591, 0.7847, 0.8203, 0.8203, 0.7847, 0.7847, 0.7591, 0.6819, 0.452, 0.1692, 0.0202,
            -0.0202, -0.1692, -0.452, -0.6819, -0.7591, -0.7847, -0.7847, -0.8202, -0.8202,
            -0.7847, -0.7591, -0.7448, -0.679, -0.5142, -0.3543, -0.242, -0.0767, 0.1502, 0.3827,
            0.5372, 0.5972, 0.721, 0.7636, 0.8556, 0.8556, 0.8556, 0.7636, 0.7636, 0.6399, 0.5849,
            0.5774, 0.4367, 0.1558, -0.1307, -0.2906, -0.3219, -0.4337, -0.6889, -0.788, -0.8602,
            -0.8602, -0.8602, -0.8271, -0.8271, -0.7913, -0.7522, -0.6342, -0.4359, -0.2323,
            -0.0652,
        ];

        let filtered_data = medianfilter_default(&data, 10);

        assert_eq!(expected_outcome.len(), filtered_data.len());

        for (idx, &value) in expected_outcome.iter().enumerate() {
            assert_eq!(
                (value * 100.0_f64).round() / 100.0,
                (filtered_data[idx] * 100.0).round() / 100.0
            );
        }
    }

    #[test]
    fn median_test2() {
        /*
         * fs = 100;
         * t = 0:1/fs:1;
         * x = cos(2*pi*t*3)+0.25*cos(2*pi*t*40);
         * y = medfilt1(x,10);
         * %plot(t,x,t,y)
         * y
         */

        let data = vec![
            1.25000000000000,
            0.780033002134952,
            1.00703073448199,
            0.921582174095752,
            0.526714378827675,
            0.837785252292473,
            0.223525042971336,
            0.325944135758592,
            0.140044768123050,
            -0.327587482158041,
            -0.0590169943749473,
            -0.684007922695452,
            -0.560169741154953,
            -0.693258994182052,
            -1.07856092863760,
            -0.701056516295154,
            -1.19436894990821,
            -0.920772479834533,
            -0.891328912534894,
            -1.10708130105976,
            -0.559016994374948,
            -0.886801354522425,
            -0.458572546385261,
            -0.290870304090940,
            -0.389635563179463,
            0.250000000000000,
            -0.0148729340080113,
            0.445378801278418,
            0.613081043572731,
            0.482292857334951,
            1.05901699437495,
            0.702572803872283,
            1.04583740972237,
            1.07528097702201,
            0.789860452720743,
            1.20105651629515,
            0.674052431450127,
            0.847767491369528,
            0.714678238342428,
            0.279499425507979,
            0.559016994374948,
            -0.0769210150294324,
            0.0144637290644198,
            -0.171435638571114,
            -0.628033540158809,
            -0.337785252292473,
            -0.931222876015148,
            -0.767073676908276,
            -0.852522237294513,
            -1.18454149932243,
            -0.750000000000000,
            -1.18454149932243,
            -0.852522237294515,
            -0.767073676908280,
            -0.931222876015144,
            -0.337785252292472,
            -0.628033540158813,
            -0.171435638571117,
            0.0144637290644248,
            -0.0769210150294367,
            0.559016994374947,
            0.279499425507977,
            0.714678238342426,
            0.847767491369531,
            0.674052431450126,
            1.20105651629515,
            0.789860452720746,
            1.07528097702200,
            1.04583740972237,
            0.702572803872281,
            1.05901699437495,
            0.482292857334956,
            0.613081043572731,
            0.445378801278420,
            -0.0148729340080096,
            0.250000000000001,
            -0.389635563179459,
            -0.290870304090939,
            -0.458572546385256,
            -0.886801354522425,
            -0.559016994374947,
            -1.10708130105976,
            -0.891328912534896,
            -0.920772479834529,
            -1.19436894990822,
            -0.701056516295154,
            -1.07856092863760,
            -0.693258994182052,
            -0.560169741154952,
            -0.684007922695451,
            -0.0590169943749481,
            -0.327587482158040,
            0.140044768123049,
            0.325944135758597,
            0.223525042971329,
            0.837785252292474,
            0.526714378827674,
            0.921582174095753,
            1.00703073448199,
            0.780033002134953,
            1.25000000000000,
        ];

        let expected_outcome = vec![
            0.263357189413837,
            0.653373690481313,
            0.653373690481313,
            0.653373690481313,
            0.653373690481313,
            0.653373690481313,
            0.426329257293134,
            0.274734589364964,
            0.181784905547193,
            0.0405138868740515,
            -0.193302238266494,
            -0.443878611656497,
            -0.622088831925202,
            -0.688633458438752,
            -0.697157755238603,
            -0.796192714415024,
            -0.796192714415024,
            -0.889065133528659,
            -0.889065133528659,
            -0.889065133528659,
            -0.793928935408789,
            -0.722909174448686,
            -0.508794770380104,
            -0.424104054782362,
            -0.340252933635202,
            -0.152871619049476,
            0.117563532995994,
            0.347689400639209,
            0.463835829306684,
            0.547686950453841,
            0.657826923722507,
            0.746216628296513,
            0.746216628296513,
            0.818813972045136,
            0.818813972045136,
            0.818813972045136,
            0.752269345531585,
            0.752269345531585,
            0.694365334896278,
            0.616534712912537,
            0.419258209941463,
            0.146981577286199,
            -0.0312286429825063,
            -0.124178326800273,
            -0.254610445431793,
            -0.482909396225641,
            -0.689016770079405,
            -0.758536838454138,
            -0.809797957101394,
            -0.809797957101397,
            -0.852522237294514,
            -0.852522237294514,
            -0.809797957101397,
            -0.809797957101397,
            -0.758536838454140,
            -0.689016770079406,
            -0.482909396225642,
            -0.254610445431794,
            -0.124178326800277,
            -0.0312286429825060,
            0.146981577286201,
            0.419258209941462,
            0.616534712912537,
            0.694365334896276,
            0.752269345531586,
            0.752269345531586,
            0.818813972045138,
            0.818813972045138,
            0.818813972045138,
            0.746216628296513,
            0.746216628296513,
            0.657826923722506,
            0.547686950453844,
            0.463835829306688,
            0.347689400639210,
            0.117563532995995,
            -0.152871619049474,
            -0.340252933635199,
            -0.424104054782358,
            -0.508794770380102,
            -0.722909174448686,
            -0.793928935408790,
            -0.889065133528661,
            -0.889065133528661,
            -0.889065133528661,
            -0.796192714415025,
            -0.796192714415025,
            -0.697157755238603,
            -0.688633458438751,
            -0.622088831925202,
            -0.443878611656496,
            -0.193302238266494,
            0.0405138868740504,
            0.181784905547189,
            0.274734589364963,
            0.426329257293135,
            0.653373690481313,
            0.653373690481313,
            0.653373690481313,
            0.653373690481313,
            0.653373690481313,
        ];

        let filtered_data = medianfilter_default(&data, 10);

        assert_eq!(expected_outcome.len(), filtered_data.len());

        for (idx, &value) in expected_outcome.iter().enumerate() {
            assert_eq!(
                (value * 10000.0_f64).round() / 10000.0,
                (filtered_data[idx] * 10000.0).round() / 10000.0
            );
        }
    }

    #[test]
    fn median_test3() {
        /*
         * fs = 99;
         * t = 0:1/fs:1;
         * x = cos(2*pi*t*3)+0.25*cos(2*pi*t*40);
         * y = medfilt1(x,10);
         * %plot(t,x,t,y)
         * y
         */
        let data = vec![
            1.25000000000000,
            0.776009551905249,
            1.01758948841404,
            0.900193266708538,
            0.537417925686131,
            0.828045612778897,
            0.193206150838156,
            0.353826704202598,
            0.0752914657989951,
            -0.306030021759606,
            -0.0850807879683331,
            -0.734923155196478,
            -0.509846506552486,
            -0.790019585701491,
            -1.02731546462145,
            -0.727400990360479,
            -1.23932936929444,
            -0.825844569683800,
            -0.995071683182819,
            -0.999852101806367,
            -0.567590750475342,
            -0.903728714588556,
            -0.308488889220254,
            -0.393686416739931,
            -0.224081829102642,
            0.248899480206506,
            -0.0141152000863687,
            0.625728396209682,
            0.483470628147915,
            0.672532371088771,
            1.02218704235745,
            0.681508210846974,
            1.20766033183436,
            0.874999999999997,
            0.962116208048515,
            1.08600609978720,
            0.601380289427557,
            0.961251817540307,
            0.428654487786782,
            0.427310491957822,
            0.367565302412047,
            -0.181445198534276,
            0.103167336042392,
            -0.502436685244003,
            -0.456587955583265,
            -0.551006980694814,
            -1.00054894805153,
            -0.639338779536952,
            -1.15600624730019,
            -0.921241828741014,
            -0.921241828741009,
            -1.15600624730020,
            -0.639338779536952,
            -1.00054894805153,
            -0.551006980694820,
            -0.456587955583269,
            -0.502436685244005,
            0.103167336042391,
            -0.181445198534276,
            0.367565302412046,
            0.427310491957825,
            0.428654487786777,
            0.961251817540306,
            0.601380289427558,
            1.08600609978720,
            0.962116208048510,
            0.874999999999994,
            1.20766033183436,
            0.681508210846975,
            1.02218704235745,
            0.672532371088775,
            0.483470628147911,
            0.625728396209682,
            -0.0141152000863688,
            0.248899480206507,
            -0.224081829102638,
            -0.393686416739931,
            -0.308488889220254,
            -0.903728714588555,
            -0.567590750475340,
            -0.999852101806364,
            -0.995071683182821,
            -0.825844569683801,
            -1.23932936929444,
            -0.727400990360479,
            -1.02731546462145,
            -0.790019585701486,
            -0.509846506552483,
            -0.734923155196479,
            -0.0850807879683352,
            -0.306030021759605,
            0.0752914657989951,
            0.353826704202600,
            0.193206150838158,
            0.828045612778898,
            0.537417925686131,
            0.900193266708532,
            1.01758948841404,
            0.776009551905250,
            1.25000000000000,
        ];

        let expected_outcome = vec![
            0.268708962843066,
            0.656713738795690,
            0.656713738795690,
            0.656713738795690,
            0.656713738795690,
            0.656713738795690,
            0.445622314944365,
            0.273516427520377,
            0.134248808318575,
            -0.00489466108466900,
            -0.195555404863970,
            -0.407938264156046,
            -0.618623748456483,
            -0.731162072778478,
            -0.762471370448984,
            -0.807932077692645,
            -0.807932077692645,
            -0.864786642136178,
            -0.864786642136178,
            -0.864786642136178,
            -0.776622780022140,
            -0.696717660079571,
            -0.480638583607636,
            -0.351087652980092,
            -0.266285359161448,
            -0.119098514594505,
            0.117392140060069,
            0.366185054177211,
            0.554599512178799,
            0.649130383649227,
            0.677020290967873,
            0.778254105423486,
            0.778254105423486,
            0.918125908770152,
            0.918125908770152,
            0.918125908770152,
            0.778254105423486,
            0.738190144713777,
            0.515017388607170,
            0.427982489872302,
            0.397437897184935,
            0.235366319227220,
            -0.0391389312459419,
            -0.319016577058771,
            -0.479512320413634,
            -0.526721832969409,
            -0.595172880115883,
            -0.780290304138980,
            -0.780290304138981,
            -0.921241828741011,
            -0.921241828741011,
            -0.921241828741011,
            -0.780290304138981,
            -0.780290304138981,
            -0.595172880115886,
            -0.526721832969413,
            -0.479512320413637,
            -0.319016577058773,
            -0.0391389312459427,
            0.235366319227218,
            0.397437897184936,
            0.427982489872301,
            0.515017388607167,
            0.738190144713776,
            0.778254105423485,
            0.918125908770150,
            0.918125908770150,
            0.918125908770150,
            0.778254105423485,
            0.778254105423485,
            0.677020290967875,
            0.649130383649229,
            0.554599512178797,
            0.366185054177209,
            0.117392140060069,
            -0.119098514594504,
            -0.266285359161446,
            -0.351087652980093,
            -0.480638583607636,
            -0.696717660079570,
            -0.776622780022140,
            -0.864786642136178,
            -0.864786642136178,
            -0.864786642136178,
            -0.807932077692644,
            -0.807932077692644,
            -0.762471370448983,
            -0.731162072778479,
            -0.618623748456481,
            -0.407938264156044,
            -0.195555404863970,
            -0.00489466108467005,
            0.134248808318576,
            0.273516427520379,
            0.445622314944365,
            0.656713738795690,
            0.656713738795690,
            0.656713738795690,
            0.656713738795690,
            0.656713738795690,
        ];

        let filtered_data = medianfilter_default(&data, 10);

        assert_eq!(expected_outcome.len(), filtered_data.len());

        for (idx, &value) in expected_outcome.iter().enumerate() {
            assert_eq!(
                (value * 10000.0_f64).round() / 10000.0,
                (filtered_data[idx] * 10000.0).round() / 10000.0
            );
        }
    }

    #[test]
    fn median_test4() {
        /*
         * fs = 99;
         * t = 0:1/fs:1;
         * x = sin(2*pi*t*3)+0.25*sin(2*pi*t*40);
         * y = medfilt1(x,10);
         * %plot(t,x,t,y)
         * y
         */
        let data = vec![
            0.0,
            0.331016210326103,
            0.138125490594051,
            0.783593709536483,
            0.523386761353039,
            0.846224065443774,
            1.02418862578637,
            0.751448227461646,
            1.24732695529832,
            0.800884048292368,
            1.00778781550994,
            0.951530439615855,
            0.552105586341674,
            0.868127518139074,
            0.250084058068717,
            0.374648170756512,
            0.150133676500818,
            -0.278703970468565,
            -0.0342771963711963,
            -0.682224965300244,
            -0.496609802195486,
            -0.731985563528213,
            -1.02672230620607,
            -0.704040279074683,
            -1.22607164655960,
            -0.850640356919347,
            -0.979743551698061,
            -1.04479219971842,
            -0.583987378524191,
            -0.934779623035807,
            -0.368121064585069,
            -0.411162804653666,
            -0.296699972382703,
            0.216506350946108,
            -0.0599624496275750,
            0.565699071733269,
            0.470207678245239,
            0.612070650057492,
            1.01351641218304,
            0.659915160558767,
            1.18424292581092,
            0.898634705331355,
            0.942508630790831,
            1.12317436155938,
            0.619823465531387,
            0.983157573192888,
            0.489739638327251,
            0.442370541813275,
            0.436272303396584,
            -0.143669517056834,
            0.143669517056835,
            -0.436272303396578,
            -0.442370541813277,
            -0.489739638327244,
            -0.983157573192890,
            -0.619823465531386,
            -1.12317436155938,
            -0.942508630790833,
            -0.898634705331353,
            -1.18424292581092,
            -0.659915160558768,
            -1.01351641218304,
            -0.612070650057487,
            -0.470207678245238,
            -0.565699071733275,
            0.0599624496275739,
            -0.216506350946107,
            0.296699972382696,
            0.411162804653669,
            0.368121064585067,
            0.934779623035806,
            0.583987378524192,
            1.04479219971842,
            0.979743551698064,
            0.850640356919345,
            1.22607164655960,
            0.704040279074684,
            1.02672230620607,
            0.731985563528220,
            0.496609802195490,
            0.682224965300246,
            0.0342771963711990,
            0.278703970468564,
            -0.150133676500818,
            -0.374648170756510,
            -0.250084058068714,
            -0.868127518139074,
            -0.552105586341676,
            -0.951530439615854,
            -1.00778781550995,
            -0.800884048292364,
            -1.24732695529832,
            -0.751448227461648,
            -1.02418862578638,
            -0.846224065443774,
            -0.523386761353040,
            -0.783593709536485,
            -0.138125490594055,
            -0.331016210326108,
            -3.18408167778312e-15,
        ];

        let expected_outcome = vec![
            0.0,
            0.0690627452970254,
            0.234570850460077,
            0.427201485839571,
            0.637417494407343,
            0.767520968499065,
            0.792238878914426,
            0.823554056868071,
            0.823554056868071,
            0.857175791791424,
            0.857175791791424,
            0.834505783215721,
            0.776166137877007,
            0.676494817317021,
            0.463376878549093,
            0.312366114412614,
            0.200108867284767,
            0.0579282400648109,
            -0.156490583419880,
            -0.387656886332025,
            -0.589417383747865,
            -0.693132622187464,
            -0.718012921301448,
            -0.791312960223780,
            -0.791312960223780,
            -0.892709989977577,
            -0.892709989977577,
            -0.892709989977577,
            -0.777340317997015,
            -0.717313867721769,
            -0.497575091588928,
            -0.389641934619368,
            -0.332410518483886,
            -0.178331211005139,
            0.0782719506592667,
            0.343357014595674,
            0.517953374989254,
            0.588884860895380,
            0.635992905308130,
            0.779274932945061,
            0.779274932945061,
            0.920571668061093,
            0.920571668061093,
            0.920571668061093,
            0.779274932945061,
            0.759229085431371,
            0.554781551929319,
            0.466055090070263,
            0.439321422604929,
            0.289970910226709,
            3.60822483003176e-16,
            -0.289970910226706,
            -0.439321422604928,
            -0.466055090070261,
            -0.554781551929315,
            -0.759229085431370,
            -0.779274932945061,
            -0.920571668061093,
            -0.920571668061093,
            -0.920571668061093,
            -0.779274932945061,
            -0.779274932945061,
            -0.635992905308128,
            -0.588884860895381,
            -0.517953374989256,
            -0.343357014595672,
            -0.0782719506592666,
            0.178331211005135,
            0.332410518483881,
            0.389641934619368,
            0.497575091588930,
            0.717313867721768,
            0.777340317997014,
            0.892709989977575,
            0.892709989977575,
            0.892709989977575,
            0.791312960223782,
            0.791312960223782,
            0.718012921301452,
            0.693132622187465,
            0.589417383747868,
            0.387656886332027,
            0.156490583419882,
            -0.0579282400648092,
            -0.200108867284765,
            -0.312366114412612,
            -0.463376878549093,
            -0.676494817317020,
            -0.776166137877006,
            -0.834505783215719,
            -0.857175791791424,
            -0.857175791791424,
            -0.823554056868069,
            -0.823554056868069,
            -0.792238878914424,
            -0.767520968499067,
            -0.637417494407344,
            -0.427201485839574,
            -0.234570850460081,
            -0.0690627452970292,
        ];

        let filtered_data = medianfilter_default(&data, 10);

        assert_eq!(expected_outcome.len(), filtered_data.len());

        for (idx, &value) in expected_outcome.iter().enumerate() {
            assert_eq!(
                (value * 10000.0_f64).round() / 10000.0,
                (filtered_data[idx] * 10000.0).round() / 10000.0
            );
        }
    }

    #[test]
    fn median_test5() {
        /*
         * fs = 100;
         * t = 0:1/fs:1;
         * x = sin(2*pi*t*3)+0.25*sin(2*pi*t*40);
         * y = medfilt1(x,9);
         * %plot(t,x,t,y)
         * y
         */
        let data = vec![
            0.0,
            0.334327627658843,
            0.130360423610890,
            0.773590924052785,
            0.537600792855571,
            0.809016994374947,
            1.05177336553914,
            0.730819032054843,
            1.23579085750206,
            0.845168388241360,
            0.951056516295153,
            1.02325299311698,
            0.532749113702001,
            0.875188118822478,
            0.334807361028596,
            0.309016994374947,
            0.272279546637423,
            -0.300554648603102,
            -0.0109257580910668,
            -0.572725604638190,
            -0.587785252292474,
            -0.582022314348291,
            -1.08209205457580,
            -0.692012356814463,
            -1.12923356380181,
            -1.00000000000000,
            -0.835340937655570,
            -1.16754061496204,
            -0.606563796428226,
            -0.875914940494530,
            -0.587785252292474,
            -0.278832978491953,
            -0.486454016238643,
            0.174973609544476,
            -0.0216130795088154,
            0.309016994374946,
            0.628699987174835,
            0.399659860674902,
            1.00827737184958,
            0.729360366970746,
            0.951056516295153,
            1.13906101438760,
            0.760262599354482,
            1.20634729020242,
            0.757880739392903,
            0.809016994374947,
            0.831493419001808,
            0.298062665905210,
            0.605888681758468,
            0.0404350015126084,
            -8.57252759403147e-16,
            -0.0404350015126085,
            -0.605888681758468,
            -0.298062665905207,
            -0.831493419001812,
            -0.809016994374946,
            -0.757880739392906,
            -1.20634729020242,
            -0.760262599354484,
            -1.13906101438759,
            -0.951056516295155,
            -0.729360366970747,
            -1.00827737184958,
            -0.399659860674903,
            -0.628699987174832,
            -0.309016994374962,
            0.0216130795088196,
            -0.174973609544479,
            0.486454016238641,
            0.278832978491956,
            0.587785252292471,
            0.875914940494533,
            0.606563796428227,
            1.16754061496204,
            0.835340937655566,
            0.999999999999995,
            1.12923356380181,
            0.692012356814464,
            1.08209205457580,
            0.582022314348292,
            0.587785252292472,
            0.572725604638188,
            0.0109257580910650,
            0.300554648603100,
            -0.272279546637414,
            -0.309016994374944,
            -0.334807361028590,
            -0.875188118822477,
            -0.532749113702000,
            -1.02325299311698,
            -0.951056516295156,
            -0.845168388241361,
            -1.23579085750206,
            -0.730819032054845,
            -1.05177336553913,
            -0.809016994374953,
            -0.537600792855571,
            -0.773590924052786,
            -0.130360423610892,
            -0.334327627658844,
            -3.18408167778312e-15,
        ];

        let expected_outcome = vec![
            0.0, 0.1304, 0.3343, 0.5376, 0.7308, 0.7736, 0.809, 0.8452, 0.8452, 0.8752, 0.8752,
            0.8452, 0.8452, 0.5327, 0.3348, 0.309, 0.2723, -0.0109, -0.3006, -0.5727, -0.582,
            -0.5878, -0.692, -0.8353, -0.8353, -0.8759, -0.8759, -0.8353, -0.8353, -0.6066,
            -0.5878, -0.4865, -0.2788, -0.0216, 0.175, 0.309, 0.3997, 0.6287, 0.7294, 0.7603,
            0.7603, 0.809, 0.8315, 0.809, 0.809, 0.7603, 0.7579, 0.6059, 0.2981, 0.0404, 0.0,
            -0.0404, -0.2981, -0.6059, -0.7579, -0.7603, -0.809, -0.809, -0.8315, -0.809, -0.7603,
            -0.7603, -0.7294, -0.6287, -0.3997, -0.309, -0.175, 0.0216, 0.2788, 0.4865, 0.5878,
            0.6066, 0.8353, 0.8353, 0.8759, 0.8759, 0.8353, 0.8353, 0.692, 0.5878, 0.582, 0.5727,
            0.3006, 0.0109, -0.2723, -0.309, -0.3348, -0.5327, -0.8452, -0.8452, -0.8752, -0.8752,
            -0.8452, -0.8452, -0.809, -0.7736, -0.7308, -0.5376, -0.3343, -0.1304, 0.0,
        ];

        let filtered_data = medianfilter_default(&data, 9);

        assert_eq!(expected_outcome.len(), filtered_data.len());

        for (idx, &value) in expected_outcome.iter().enumerate() {
            assert_eq!(
                (value * 10000.0_f64).round() / 10000.0,
                (filtered_data[idx] * 10000.0).round() / 10000.0
            );
        }
    }

    #[test]
    fn median_test6() {
        /*
         * fs = 99;
         * t = 0:1/fs:1;
         * x = cos(2*pi*t*3)+0.25*cos(2*pi*t*40);
         * y = medfilt1(x,10);
         * %plot(t,x,t,y)
         * y
         */
        let data = vec![
            1.25000000000000,
            0.776009551905249,
            1.01758948841404,
            0.900193266708538,
            0.537417925686131,
            0.828045612778897,
            0.193206150838156,
            0.353826704202598,
            0.0752914657989951,
            -0.306030021759606,
            -0.0850807879683331,
            -0.734923155196478,
            -0.509846506552486,
            -0.790019585701491,
            -1.02731546462145,
            -0.727400990360479,
            -1.23932936929444,
            -0.825844569683800,
            -0.995071683182819,
            -0.999852101806367,
            -0.567590750475342,
            -0.903728714588556,
            -0.308488889220254,
            -0.393686416739931,
            -0.224081829102642,
            0.248899480206506,
            -0.0141152000863687,
            0.625728396209682,
            0.483470628147915,
            0.672532371088771,
            1.02218704235745,
            0.681508210846974,
            1.20766033183436,
            0.874999999999997,
            0.962116208048515,
            1.08600609978720,
            0.601380289427557,
            0.961251817540307,
            0.428654487786782,
            0.427310491957822,
            0.367565302412047,
            -0.181445198534276,
            0.103167336042392,
            -0.502436685244003,
            -0.456587955583265,
            -0.551006980694814,
            -1.00054894805153,
            -0.639338779536952,
            -1.15600624730019,
            -0.921241828741014,
            -0.921241828741009,
            -1.15600624730020,
            -0.639338779536952,
            -1.00054894805153,
            -0.551006980694820,
            -0.456587955583269,
            -0.502436685244005,
            0.103167336042391,
            -0.181445198534276,
            0.367565302412046,
            0.427310491957825,
            0.428654487786777,
            0.961251817540306,
            0.601380289427558,
            1.08600609978720,
            0.962116208048510,
            0.874999999999994,
            1.20766033183436,
            0.681508210846975,
            1.02218704235745,
            0.672532371088775,
            0.483470628147911,
            0.625728396209682,
            -0.0141152000863688,
            0.248899480206507,
            -0.224081829102638,
            -0.393686416739931,
            -0.308488889220254,
            -0.903728714588555,
            -0.567590750475340,
            -0.999852101806364,
            -0.995071683182821,
            -0.825844569683801,
            -1.23932936929444,
            -0.727400990360479,
            -1.02731546462145,
            -0.790019585701486,
            -0.509846506552483,
            -0.734923155196479,
            -0.0850807879683352,
            -0.306030021759605,
            0.0752914657989951,
            0.353826704202600,
            0.193206150838158,
            0.828045612778898,
            0.537417925686131,
            0.900193266708532,
            1.01758948841404,
            0.776009551905250,
            1.25000000000000,
        ];

        let expected_outcome = vec![
            0.5374, 0.776, 0.776, 0.776, 0.776, 0.5374, 0.3538, 0.1932, 0.0753, -0.0851, -0.306,
            -0.5098, -0.7274, -0.7349, -0.79, -0.8258, -0.8258, -0.9037, -0.9037, -0.8258, -0.8258,
            -0.5676, -0.3937, -0.3085, -0.2241, -0.0141, 0.2489, 0.4835, 0.6257, 0.6725, 0.6815,
            0.875, 0.875, 0.9613, 0.9613, 0.875, 0.875, 0.6014, 0.4287, 0.4273, 0.3676, 0.1032,
            -0.1814, -0.4566, -0.5024, -0.551, -0.6393, -0.9212, -0.9212, -0.9212, -0.9212,
            -0.9212, -0.9212, -0.6393, -0.551, -0.5024, -0.4566, -0.1814, 0.1032, 0.3676, 0.4273,
            0.4287, 0.6014, 0.875, 0.875, 0.9613, 0.9613, 0.875, 0.875, 0.6815, 0.6725, 0.6257,
            0.4835, 0.2489, -0.0141, -0.2241, -0.3085, -0.3937, -0.5676, -0.8258, -0.8258, -0.9037,
            -0.9037, -0.8258, -0.8258, -0.79, -0.7349, -0.7274, -0.5098, -0.306, -0.0851, 0.0753,
            0.1932, 0.3538, 0.5374, 0.776, 0.776, 0.776, 0.776, 0.5374,
        ];

        let filtered_data = medianfilter_default(&data, 9);

        assert_eq!(expected_outcome.len(), filtered_data.len());

        for (idx, &value) in expected_outcome.iter().enumerate() {
            assert_eq!(
                (value * 10000.0_f64).round() / 10000.0,
                (filtered_data[idx] * 10000.0).round() / 10000.0
            );
        }
    }

    #[test]
    fn median_test7() {
        /*
         * fs = 100;
         * t = 0:1/fs:1;
         * x = cos(2*pi*t*3)+0.25*cos(2*pi*t*40);
         * y = medfilt1(x, 10, "omitnan", "truncate");
         * %plot(t,x,t,y)
         * y
         */
        let data = vec![
            1.25000000000000,
            0.780033002134952,
            1.00703073448199,
            0.921582174095752,
            0.526714378827675,
            0.837785252292473,
            0.223525042971336,
            0.325944135758592,
            0.140044768123050,
            -0.327587482158041,
            -0.0590169943749473,
            -0.684007922695452,
            -0.560169741154953,
            -0.693258994182052,
            -1.07856092863760,
            -0.701056516295154,
            -1.19436894990821,
            -0.920772479834533,
            -0.891328912534894,
            -1.10708130105976,
            -0.559016994374948,
            -0.886801354522425,
            -0.458572546385261,
            -0.290870304090940,
            -0.389635563179463,
            0.250000000000000,
            -0.0148729340080113,
            0.445378801278418,
            0.613081043572731,
            0.482292857334951,
            1.05901699437495,
            0.702572803872283,
            1.04583740972237,
            1.07528097702201,
            0.789860452720743,
            1.20105651629515,
            0.674052431450127,
            0.847767491369528,
            0.714678238342428,
            0.279499425507979,
            0.559016994374948,
            -0.0769210150294324,
            0.0144637290644198,
            -0.171435638571114,
            -0.628033540158809,
            -0.337785252292473,
            -0.931222876015148,
            -0.767073676908276,
            -0.852522237294513,
            -1.18454149932243,
            -0.750000000000000,
            -1.18454149932243,
            -0.852522237294515,
            -0.767073676908280,
            -0.931222876015144,
            -0.337785252292472,
            -0.628033540158813,
            -0.171435638571117,
            0.0144637290644248,
            -0.0769210150294367,
            0.559016994374947,
            0.279499425507977,
            0.714678238342426,
            0.847767491369531,
            0.674052431450126,
            1.20105651629515,
            0.789860452720746,
            1.07528097702200,
            1.04583740972237,
            0.702572803872281,
            1.05901699437495,
            0.482292857334956,
            0.613081043572731,
            0.445378801278420,
            -0.0148729340080096,
            0.250000000000001,
            -0.389635563179459,
            -0.290870304090939,
            -0.458572546385256,
            -0.886801354522425,
            -0.559016994374947,
            -1.10708130105976,
            -0.891328912534896,
            -0.920772479834529,
            -1.19436894990822,
            -0.701056516295154,
            -1.07856092863760,
            -0.693258994182052,
            -0.560169741154952,
            -0.684007922695451,
            -0.0590169943749481,
            -0.327587482158040,
            0.140044768123049,
            0.325944135758597,
            0.223525042971329,
            0.837785252292474,
            0.526714378827674,
            0.921582174095753,
            1.00703073448199,
            0.780033002134953,
            1.25000000000000,
        ];

        let expected_outcome = vec![
            0.921582174095752,
            0.879683713194113,
            0.837785252292473,
            0.808909127213713,
            0.780033002134952,
            0.653373690481313,
            0.426329257293134,
            0.274734589364964,
            0.181784905547193,
            0.0405138868740515,
            -0.193302238266494,
            -0.443878611656497,
            -0.622088831925202,
            -0.688633458438752,
            -0.697157755238603,
            -0.796192714415024,
            -0.796192714415024,
            -0.889065133528659,
            -0.889065133528659,
            -0.889065133528659,
            -0.793928935408789,
            -0.722909174448686,
            -0.508794770380104,
            -0.424104054782362,
            -0.340252933635202,
            -0.152871619049476,
            0.117563532995994,
            0.347689400639209,
            0.463835829306684,
            0.547686950453841,
            0.657826923722507,
            0.746216628296513,
            0.746216628296513,
            0.818813972045136,
            0.818813972045136,
            0.818813972045136,
            0.752269345531585,
            0.752269345531585,
            0.694365334896278,
            0.616534712912537,
            0.419258209941463,
            0.146981577286199,
            -0.0312286429825063,
            -0.124178326800273,
            -0.254610445431793,
            -0.482909396225641,
            -0.689016770079405,
            -0.758536838454138,
            -0.809797957101394,
            -0.809797957101397,
            -0.852522237294514,
            -0.852522237294514,
            -0.809797957101397,
            -0.809797957101397,
            -0.758536838454140,
            -0.689016770079406,
            -0.482909396225642,
            -0.254610445431794,
            -0.124178326800277,
            -0.0312286429825060,
            0.146981577286201,
            0.419258209941462,
            0.616534712912537,
            0.694365334896276,
            0.752269345531586,
            0.752269345531586,
            0.818813972045138,
            0.818813972045138,
            0.818813972045138,
            0.746216628296513,
            0.746216628296513,
            0.657826923722506,
            0.547686950453844,
            0.463835829306688,
            0.347689400639210,
            0.117563532995995,
            -0.152871619049474,
            -0.340252933635199,
            -0.424104054782358,
            -0.508794770380102,
            -0.722909174448686,
            -0.793928935408790,
            -0.889065133528661,
            -0.889065133528661,
            -0.889065133528661,
            -0.796192714415025,
            -0.796192714415025,
            -0.697157755238603,
            -0.688633458438751,
            -0.622088831925202,
            -0.443878611656496,
            -0.193302238266494,
            0.0405138868740504,
            0.181784905547189,
            0.274734589364963,
            0.426329257293135,
            0.653373690481313,
            0.780033002134953,
            0.808909127213713,
            0.837785252292474,
            0.879683713194113,
        ];

        let filtered_data = moving_median_filter(
            &data,
            10,
            MedianPaddingMode::Truncate,
            MedianMissingMode::IncludeNaN,
        );

        assert_eq!(expected_outcome.len(), filtered_data.len());

        for (idx, &value) in expected_outcome.iter().enumerate() {
            assert_eq!(
                (value * 10000.0_f64).round() / 10000.0,
                (filtered_data[idx] * 10000.0).round() / 10000.0
            );
        }
    }
}