lazymatrix 0.6.0

Lazy normalized design matrices: apply column centering/scaling without materializing (X - 1cᵀ)S⁻¹, preserving sparsity.
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

use super::{SprsCsc, SprsCsr};
use crate::{MatrixWrite, Scalar, VectorView, WeightedGramInto, WeightedGramKernel};
use crate::{VectorViewMut, WeightedColumnSumsInto, WeightedColumnSumsKernel};
use sprs::{CsMatBase, SpIndex};
use std::ops::Deref;

impl<F, IP, IS, DS, Iptr> WeightedGramInto<F> for SprsCsr<CsMatBase<F, usize, IP, IS, DS, Iptr>>
where
    F: Scalar,
    Iptr: SpIndex,
    IP: Deref<Target = [Iptr]>,
    IS: Deref<Target = [usize]>,
    DS: Deref<Target = [F]>,
{
    fn weighted_gram_into<W, O>(&self, weights: &W, out: &mut O) -> Result<(), Self::Error>
    where
        W: VectorView<F> + ?Sized,
        O: MatrixWrite<F> + ?Sized,
    {
        self.weighted_gram_normalized_into(weights, None, None, out)
    }
}

impl<F, IP, IS, DS, Iptr> WeightedGramKernel<F> for SprsCsr<CsMatBase<F, usize, IP, IS, DS, Iptr>>
where
    F: Scalar,
    Iptr: SpIndex,
    IP: Deref<Target = [Iptr]>,
    IS: Deref<Target = [usize]>,
    DS: Deref<Target = [F]>,
{
    fn weighted_gram_normalized_into<W, O>(
        &self,
        weights: &W,
        centers: Option<&[F]>,
        scales: Option<&[F]>,
        out: &mut O,
    ) -> Result<(), Self::Error>
    where
        W: VectorView<F> + ?Sized,
        O: MatrixWrite<F> + ?Sized,
    {
        crate::gram::sparse_row_gram(self, weights, centers, scales, out);
        Ok(())
    }
}

impl<F, IP, IS, DS, Iptr> WeightedGramInto<F> for SprsCsc<CsMatBase<F, usize, IP, IS, DS, Iptr>>
where
    F: Scalar,
    Iptr: SpIndex,
    IP: Deref<Target = [Iptr]>,
    IS: Deref<Target = [usize]>,
    DS: Deref<Target = [F]>,
{
    fn weighted_gram_into<W, O>(&self, weights: &W, out: &mut O) -> Result<(), Self::Error>
    where
        W: VectorView<F> + ?Sized,
        O: MatrixWrite<F> + ?Sized,
    {
        self.weighted_gram_normalized_into(weights, None, None, out)
    }
}

impl<F, IP, IS, DS, Iptr> WeightedGramKernel<F> for SprsCsc<CsMatBase<F, usize, IP, IS, DS, Iptr>>
where
    F: Scalar,
    Iptr: SpIndex,
    IP: Deref<Target = [Iptr]>,
    IS: Deref<Target = [usize]>,
    DS: Deref<Target = [F]>,
{
    fn weighted_gram_normalized_into<W, O>(
        &self,
        weights: &W,
        centers: Option<&[F]>,
        scales: Option<&[F]>,
        out: &mut O,
    ) -> Result<(), Self::Error>
    where
        W: VectorView<F> + ?Sized,
        O: MatrixWrite<F> + ?Sized,
    {
        crate::gram::sparse_gram(self, weights, centers, scales, out);
        Ok(())
    }
}

impl<F, IP, IS, DS, Iptr> WeightedColumnSumsInto<F>
    for SprsCsc<CsMatBase<F, usize, IP, IS, DS, Iptr>>
where
    F: Scalar,
    Iptr: SpIndex,
    IP: Deref<Target = [Iptr]>,
    IS: Deref<Target = [usize]>,
    DS: Deref<Target = [F]>,
{
    fn weighted_column_sums_into<W, O>(&self, weights: &W, out: &mut O) -> Result<(), Self::Error>
    where
        W: VectorView<F> + ?Sized,
        O: VectorViewMut<F> + ?Sized,
    {
        self.weighted_column_sums_normalized_into(weights, None, None, out)
    }
}

impl<F, IP, IS, DS, Iptr> WeightedColumnSumsKernel<F>
    for SprsCsc<CsMatBase<F, usize, IP, IS, DS, Iptr>>
where
    F: Scalar,
    Iptr: SpIndex,
    IP: Deref<Target = [Iptr]>,
    IS: Deref<Target = [usize]>,
    DS: Deref<Target = [F]>,
{
    fn weighted_column_sums_normalized_into<W, O>(
        &self,
        weights: &W,
        centers: Option<&[F]>,
        scales: Option<&[F]>,
        out: &mut O,
    ) -> Result<(), Self::Error>
    where
        W: VectorView<F> + ?Sized,
        O: VectorViewMut<F> + ?Sized,
    {
        crate::weighted_sums::sparse_sums(self, weights, centers, scales, out);
        Ok(())
    }
}