sparsemat 0.2.0

A simple sparse matrix library
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

use crate::vector::*;
use crate::types::ValueType;

#[derive(Clone, Debug)]
pub struct DenseVec<T> {
    values: Vec<T>,
}

impl<'a, T> DenseVec<T> {
    pub fn iter_ref(&'a self) -> std::slice::Iter<'a, T> {
        self.values.iter()
    }
}

impl<'a, T> Vector<'a> for DenseVec<T>
where T: 'a + ValueType {
    type Value = T;
    type IterVal = std::iter::Cloned<std::slice::Iter<'a, T>>;

    fn iter(&'a self) -> Self::IterVal {
        self.values.iter().cloned()
    }

    fn with_capacity(cap: usize) -> Self {
        Self {
            values: Vec::<T>::with_capacity(cap),
        }
    }

    fn from_vec(vec: Vec<T>) -> Self {
        Self {
            values: vec,
        }
    }

    fn dim(&self) -> usize {
        self.values.len()
    }

    fn get(&self, i: usize) -> Self::Value {
        self.values[i]
    }

    fn get_mut(&mut self, i: usize) -> &mut Self::Value {
        if i >= self.values.len() {
            self.values.resize(i + 1, Self::Value::zero());
        }
        &mut self.values[i]
    }

    fn add(&'a mut self, rhs: &Self) {
        if self.dim() < rhs.dim() {
            panic!("Dimension mismatch");
        }
        for (x, y) in self.values.iter_mut().zip(rhs.iter()) {
            *x += y;
        }
    }

    fn sub(&'a mut self, rhs: &Self) {
        if self.dim() < rhs.dim() {
            panic!("Dimension mismatch");
        }
        for (x, y) in self.values.iter_mut().zip(rhs.iter()) {
            *x -= y;
        }
    }

    fn scale(&'a mut self, rhs: Self::Value) {
        for x in self.values.iter_mut() {
            *x *= rhs;
        }
    }
}

impl<T> std::ops::AddAssign for DenseVec<T>
where T: ValueType {
    fn add_assign(&mut self, rhs: Self) {
        self.add(&rhs);
    }
}

impl<T> std::ops::SubAssign for DenseVec<T>
where T: ValueType {
    fn sub_assign(&mut self, rhs: Self) {
        self.sub(&rhs);
    }
}

// Vector scaling
impl<T> std::ops::MulAssign<T> for DenseVec<T>
where T: ValueType {
    fn mul_assign(&mut self, rhs: T) {
        self.scale(rhs);
    }
}

impl<T> std::ops::Add<DenseVec<T>> for DenseVec<T>
where T: ValueType {
    type Output = Self;

    fn add(self, rhs: Self) -> Self::Output {
        let mut ret = self.clone();
        ret += rhs;
        ret
    }
}

impl<T> std::ops::Sub<DenseVec<T>> for DenseVec<T>
where T: ValueType {
    type Output = Self;

    fn sub(self, rhs: Self) -> Self::Output {
        let mut ret = self.clone();
        ret -= rhs;
        ret
    }
}

// Vector scaling
impl<T> std::ops::Mul<T> for DenseVec<T>
where T: ValueType {
    type Output = Self;

    fn mul(self, rhs: T) -> Self::Output {
       let mut ret = self.clone();
       ret *= rhs;
       ret 
    }
}

// Inner product
impl<T> std::ops::Mul<DenseVec<T>> for DenseVec<T>
where T: ValueType {
    type Output = T;

    fn mul(self, rhs: Self) -> Self::Output {
        self.inner_prod(&rhs)
    }
}