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
use std::cmp::min;
use ndarray::prelude::*;
use ndarray::LinalgScalar;
use error::LapackError;
use qr::ImplQR;
use svd::ImplSVD;
use norm::ImplNorm;
pub trait Matrix: Sized {
type Scalar;
type Vector;
fn size(&self) -> (usize, usize);
fn norm_1(&self) -> Self::Scalar;
fn norm_i(&self) -> Self::Scalar;
fn norm_f(&self) -> Self::Scalar;
fn svd(self) -> Result<(Self, Self::Vector, Self), LapackError>;
fn qr(self) -> Result<(Self, Self), LapackError>;
}
impl<A> Matrix for Array<A, (Ix, Ix)>
where A: ImplQR + ImplSVD + ImplNorm + LinalgScalar
{
type Scalar = A;
type Vector = Array<A, Ix>;
fn size(&self) -> (usize, usize) {
(self.rows(), self.cols())
}
fn norm_1(&self) -> Self::Scalar {
let (m, n) = self.size();
let strides = self.strides();
if strides[0] > strides[1] {
ImplNorm::norm_i(n, m, self.clone().into_raw_vec())
} else {
ImplNorm::norm_1(m, n, self.clone().into_raw_vec())
}
}
fn norm_i(&self) -> Self::Scalar {
let (m, n) = self.size();
let strides = self.strides();
if strides[0] > strides[1] {
ImplNorm::norm_1(n, m, self.clone().into_raw_vec())
} else {
ImplNorm::norm_i(m, n, self.clone().into_raw_vec())
}
}
fn norm_f(&self) -> Self::Scalar {
let (m, n) = self.size();
ImplNorm::norm_f(m, n, self.clone().into_raw_vec())
}
fn svd(self) -> Result<(Self, Self::Vector, Self), LapackError> {
let strides = self.strides();
let (m, n) = if strides[0] > strides[1] {
self.size()
} else {
let (n, m) = self.size();
(m, n)
};
let (u, s, vt) = try!(ImplSVD::svd(m, n, self.clone().into_raw_vec()));
let sv = Array::from_vec(s);
if strides[0] > strides[1] {
let ua = Array::from_vec(u).into_shape((n, n)).unwrap();
let va = Array::from_vec(vt).into_shape((m, m)).unwrap();
Ok((va, sv, ua))
} else {
let ua = Array::from_vec(u).into_shape((n, n)).unwrap().reversed_axes();
let va = Array::from_vec(vt).into_shape((m, m)).unwrap().reversed_axes();
Ok((ua, sv, va))
}
}
fn qr(self) -> Result<(Self, Self), LapackError> {
let (n, m) = self.size();
let strides = self.strides();
let k = min(n, m);
let (q, r) = if strides[0] < strides[1] {
try!(ImplQR::qr(m, n, self.clone().into_raw_vec()))
} else {
try!(ImplQR::lq(n, m, self.clone().into_raw_vec()))
};
let (qa, ra) = if strides[0] < strides[1] {
(Array::from_vec(q).into_shape((m, n)).unwrap().reversed_axes(),
Array::from_vec(r).into_shape((m, n)).unwrap().reversed_axes())
} else {
(Array::from_vec(q).into_shape((n, m)).unwrap(),
Array::from_vec(r).into_shape((n, m)).unwrap())
};
let qm = if m > k {
let (qsl, _) = qa.view().split_at(Axis(1), k);
qsl.to_owned()
} else {
qa
};
let mut rm = if n > k {
let (rsl, _) = ra.view().split_at(Axis(0), k);
rsl.to_owned()
} else {
ra
};
for ((i, j), val) in rm.indexed_iter_mut() {
if i > j {
*val = A::zero();
}
}
Ok((qm, rm))
}
}