rustml 0.0.7

A library for doing maching learning in Rust.
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140

extern crate num;

use matrix::Matrix;
use ops_inplace::VectorVectorOpsInPlace;
use math::Dimension;
use math::SumVec;

// ----------------------------------------------------------------------------

pub trait MeanVec<T> {
    fn mean(&self) -> T;
}

macro_rules! mean_vec_impl {
    ($($t:ty)*) => ($(
        impl MeanVec<$t> for Vec<$t> {

            fn mean(&self) -> $t {
                (&self[..]).mean()
            }
        }

        impl MeanVec<$t> for [$t] {

            fn mean(&self) -> $t {
                let n = if self.len() == 0 { 1 as $t } else { self.len() as $t };
                self.sum() / n
            }
        }
    )*)
}

mean_vec_impl!{ usize u8 u16 u32 u64 isize i8 i16 i32 i64 f32 f64 }

// ----------------------------------------------------------------------------

/// Trait to compute the mean of values.
pub trait Mean<T> {
    /// Computes the mean over all elements for the specified dimension.
    ///
    /// When computing the mean of a vector or a slice both
    /// are interpreted as a row vector. Thus,
    /// the only valid dimension for vectors or slices
    /// is `Dimension::Row`. For other dimensions or if the vector or
    /// slice is empty the function will always return zero. 
    ///
    /// # Examples
    ///
    /// ```
    /// use rustml::*;
    ///
    /// let v = vec![1.0, 5.0, 9.0];
    /// assert_eq!(v.mean(), 5.0);
    /// ```
    ///
    /// # Implementation details
    ///
    /// Uses the [Sum](trait.Sum.html) trait to compute the sum which is then
    /// divided by the number of values.
    fn mean(&self, dim: Dimension) -> T;
    // TODO document matrix
}

macro_rules! mean_impl {
    ($($t:ty)*) => ($(
        impl Mean<Vec<$t>> for Matrix<$t> {

            fn mean(&self, dim: Dimension) -> Vec<$t> {

                if self.rows() == 0 || self.cols() == 0 {
                    return vec![];
                }

                match dim {
                    Dimension::Column => {
                        // TODO reimplement when Sum for Matrix is implemented
                        let mut r: Vec<$t> = self.iter().take(self.cols()).cloned().collect();
                        for row in self.row_iter_at(1) {
                            r.iadd(row);
                        }
                        let n = self.rows() as $t;
                        for i in r.iter_mut() {
                            *i = *i / n;
                        }
                        r
                    }
                    Dimension::Row => {
                        // TODO reimplement when Sum for Matrix is implemented
                        let n = self.cols() as $t;
                        self.row_iter().map(|row| row.sum() / n).collect()
                    }
                }
            }
        }
    )*)
}

mean_impl!{ f32 f64 }

// ----------------------------------------------------------------------------

#[cfg(test)]
mod tests {
    use super::*;
    use matrix::*;
    use math::Dimension;

    #[test]
    fn test_mean_vec_f32() {

        let x: Vec<f32> = vec![1.0, 2.0, 3.0, 4.0];
        assert_eq!(x.mean(), 2.5);

        let a: Vec<f32> = Vec::new();
        assert_eq!(a.mean(), 0.0);

        let b = [1.0f32, 2.0, 3.0, 4.0];
        assert_eq!(b.mean(), 2.5);
    }

    #[test]
    fn test_mean_mat_f32() {

        let a = Matrix::<f32>::new();
        assert_eq!(a.mean(Dimension::Column), vec![]);
        assert_eq!(a.mean(Dimension::Row), vec![]);

        let b = mat![5.0, 6.0];
        assert_eq!(b.mean(Dimension::Column), vec![5.0, 6.0]);
        assert_eq!(b.mean(Dimension::Row), vec![5.5]);

        let x = mat![
            1.0, 2.0;
            3.0, 4.0
        ];
        assert_eq!(x.mean(Dimension::Column), vec![2.0, 3.0]);
        assert_eq!(x.mean(Dimension::Row), vec![1.5, 3.5]);
    }
}