Add matrixmarket parser.
This commit is contained in:
sebcrozet
parent
383a18f083
commit
ed07b78b97
|
|
@ -26,6 +26,7 @@ abomonation-serialize = [ "abomonation" ]
|
|||
sparse = [ ]
|
||||
debug = [ ]
|
||||
alloc = [ ]
|
||||
io = [ "pest", "pest_derive" ]
|
||||
|
||||
[dependencies]
|
||||
typenum = "1.10"
|
||||
|
|
@ -41,6 +42,8 @@ serde_derive = { version = "1.0", optional = true }
|
|||
abomonation = { version = "0.5", optional = true }
|
||||
mint = { version = "0.5", optional = true }
|
||||
quickcheck = { version = "0.6", optional = true }
|
||||
pest = { version = "2.0", optional = true }
|
||||
pest_derive = { version = "2.0", optional = true }
|
||||
|
||||
[dev-dependencies]
|
||||
serde_json = "1.0"
|
||||
|
|
|
|||
|
|
@ -0,0 +1,16 @@
|
|||
WHITESPACE = _{ " " }
|
||||
|
||||
Comments = _{ "%" ~ (!NEWLINE ~ ANY)* }
|
||||
Header = { "%%" ~ (!NEWLINE ~ ANY)* }
|
||||
Shape = { Dimension ~ Dimension ~ Dimension }
|
||||
Document = {
|
||||
SOI ~
|
||||
NEWLINE ~
|
||||
Header ~
|
||||
(NEWLINE ~ Comments)* ~
|
||||
(NEWLINE ~ Shape) ~
|
||||
(NEWLINE ~ Entry?)*
|
||||
}
|
||||
Dimension = @{ ASCII_DIGIT+ }
|
||||
Value = @{ ("+" | "-")? ~ NUMBER+ ~ ("." ~ NUMBER+)? ~ ("e" ~ ("+" | "-")? ~ NUMBER+)? }
|
||||
Entry = { Dimension ~ Dimension ~ Value }
|
||||
|
|
@ -0,0 +1,51 @@
|
|||
use std::fs;
|
||||
use std::path::Path;
|
||||
|
||||
use pest::Parser;
|
||||
use sparse::CsMatrix;
|
||||
use Real;
|
||||
|
||||
#[derive(Parser)]
|
||||
#[grammar = "io/matrix_market.pest"]
|
||||
struct MatrixMarketParser;
|
||||
|
||||
// FIXME: return an Error instead of an Option.
|
||||
pub fn cs_matrix_from_matrix_market<N: Real, P: AsRef<Path>>(path: P) -> Option<CsMatrix<N>> {
|
||||
let file = fs::read_to_string(path).ok()?;
|
||||
cs_matrix_from_matrix_market_str(&file)
|
||||
}
|
||||
|
||||
// FIXME: return an Error instead of an Option.
|
||||
pub fn cs_matrix_from_matrix_market_str<N: Real>(data: &str) -> Option<CsMatrix<N>> {
|
||||
let file = MatrixMarketParser::parse(Rule::Document, data)
|
||||
.unwrap()
|
||||
.next()?;
|
||||
let mut shape = (0, 0, 0);
|
||||
let mut rows: Vec<usize> = Vec::new();
|
||||
let mut cols: Vec<usize> = Vec::new();
|
||||
let mut data: Vec<N> = Vec::new();
|
||||
|
||||
for line in file.into_inner() {
|
||||
match line.as_rule() {
|
||||
Rule::Header => {}
|
||||
Rule::Shape => {
|
||||
let mut inner = line.into_inner();
|
||||
shape.0 = inner.next()?.as_str().parse::<usize>().ok()?;
|
||||
shape.1 = inner.next()?.as_str().parse::<usize>().ok()?;
|
||||
shape.2 = inner.next()?.as_str().parse::<usize>().ok()?;
|
||||
}
|
||||
Rule::Entry => {
|
||||
let mut inner = line.into_inner();
|
||||
// NOTE: indices are 1-based.
|
||||
rows.push(inner.next()?.as_str().parse::<usize>().ok()? - 1);
|
||||
cols.push(inner.next()?.as_str().parse::<usize>().ok()? - 1);
|
||||
data.push(::convert(inner.next()?.as_str().parse::<f64>().ok()?));
|
||||
}
|
||||
_ => return None, // FIXME: return an Err instead.
|
||||
}
|
||||
}
|
||||
|
||||
Some(CsMatrix::from_triplet(
|
||||
shape.0, shape.1, &rows, &cols, &data,
|
||||
))
|
||||
}
|
||||
|
|
@ -0,0 +1,3 @@
|
|||
pub use self::matrix_market::*;
|
||||
|
||||
mod matrix_market;
|
||||
|
|
@ -7,8 +7,43 @@ use std::slice;
|
|||
|
||||
use allocator::Allocator;
|
||||
use constraint::{AreMultipliable, DimEq, SameNumberOfRows, ShapeConstraint};
|
||||
use sparse::cs_utils;
|
||||
use storage::{Storage, StorageMut};
|
||||
use {DefaultAllocator, Dim, Matrix, MatrixMN, Real, Scalar, Vector, VectorN, U1};
|
||||
use {
|
||||
DVector, DefaultAllocator, Dim, Dynamic, Matrix, MatrixMN, MatrixVec, Real, Scalar, Vector,
|
||||
VectorN, U1,
|
||||
};
|
||||
|
||||
pub struct ColumnEntries<'a, N> {
|
||||
curr: usize,
|
||||
i: &'a [usize],
|
||||
v: &'a [N],
|
||||
}
|
||||
|
||||
impl<'a, N> ColumnEntries<'a, N> {
|
||||
#[inline]
|
||||
pub fn new(i: &'a [usize], v: &'a [N]) -> Self {
|
||||
assert_eq!(i.len(), v.len());
|
||||
ColumnEntries { curr: 0, i, v }
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a, N: Copy> Iterator for ColumnEntries<'a, N> {
|
||||
type Item = (usize, N);
|
||||
|
||||
#[inline]
|
||||
fn next(&mut self) -> Option<(usize, N)> {
|
||||
if self.curr >= self.i.len() {
|
||||
None
|
||||
} else {
|
||||
let res = Some((unsafe { *self.i.get_unchecked(self.curr) }, unsafe {
|
||||
*self.v.get_unchecked(self.curr)
|
||||
}));
|
||||
self.curr += 1;
|
||||
res
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// FIXME: this structure exists for now only because impl trait
|
||||
// cannot be used for trait method return types.
|
||||
|
|
@ -17,12 +52,15 @@ pub trait CsStorageIter<'a, N, R, C = U1> {
|
|||
type ColumnRowIndices: Iterator<Item = usize>;
|
||||
|
||||
fn column_row_indices(&'a self, j: usize) -> Self::ColumnRowIndices;
|
||||
#[inline(always)]
|
||||
fn column_entries(&'a self, j: usize) -> Self::ColumnEntries;
|
||||
}
|
||||
|
||||
pub trait CsStorageIterMut<'a, N: 'a, R, C = U1> {
|
||||
type ValuesMut: Iterator<Item = &'a mut N>;
|
||||
type ColumnEntriesMut: Iterator<Item = (usize, &'a mut N)>;
|
||||
|
||||
fn values_mut(&'a mut self) -> Self::ValuesMut;
|
||||
fn column_entries_mut(&'a mut self, j: usize) -> Self::ColumnEntriesMut;
|
||||
}
|
||||
|
||||
|
|
@ -41,7 +79,7 @@ pub trait CsStorageMut<N, R, C = U1>:
|
|||
{
|
||||
}
|
||||
|
||||
#[derive(Clone, Debug)]
|
||||
#[derive(Clone, Debug, PartialEq)]
|
||||
pub struct CsVecStorage<N: Scalar, R: Dim, C: Dim>
|
||||
where
|
||||
DefaultAllocator: Allocator<usize, C>,
|
||||
|
|
@ -59,6 +97,12 @@ where
|
|||
pub fn values(&self) -> &[N] {
|
||||
&self.vals
|
||||
}
|
||||
pub fn p(&self) -> &[usize] {
|
||||
self.p.as_slice()
|
||||
}
|
||||
pub fn i(&self) -> &[usize] {
|
||||
&self.i
|
||||
}
|
||||
}
|
||||
|
||||
impl<N: Scalar, R: Dim, C: Dim> CsVecStorage<N, R, C> where DefaultAllocator: Allocator<usize, C> {}
|
||||
|
|
@ -67,17 +111,13 @@ impl<'a, N: Scalar, R: Dim, C: Dim> CsStorageIter<'a, N, R, C> for CsVecStorage<
|
|||
where
|
||||
DefaultAllocator: Allocator<usize, C>,
|
||||
{
|
||||
type ColumnEntries =
|
||||
iter::Zip<iter::Cloned<slice::Iter<'a, usize>>, iter::Cloned<slice::Iter<'a, N>>>;
|
||||
type ColumnEntries = ColumnEntries<'a, N>;
|
||||
type ColumnRowIndices = iter::Cloned<slice::Iter<'a, usize>>;
|
||||
|
||||
#[inline]
|
||||
fn column_entries(&'a self, j: usize) -> Self::ColumnEntries {
|
||||
let rng = self.column_range(j);
|
||||
self.i[rng.clone()]
|
||||
.iter()
|
||||
.cloned()
|
||||
.zip(self.vals[rng].iter().cloned())
|
||||
ColumnEntries::new(&self.i[rng.clone()], &self.vals[rng])
|
||||
}
|
||||
|
||||
#[inline]
|
||||
|
|
@ -137,8 +177,14 @@ impl<'a, N: Scalar, R: Dim, C: Dim> CsStorageIterMut<'a, N, R, C> for CsVecStora
|
|||
where
|
||||
DefaultAllocator: Allocator<usize, C>,
|
||||
{
|
||||
type ValuesMut = slice::IterMut<'a, N>;
|
||||
type ColumnEntriesMut = iter::Zip<iter::Cloned<slice::Iter<'a, usize>>, slice::IterMut<'a, N>>;
|
||||
|
||||
#[inline]
|
||||
fn values_mut(&'a mut self) -> Self::ValuesMut {
|
||||
self.vals.iter_mut()
|
||||
}
|
||||
|
||||
#[inline]
|
||||
fn column_entries_mut(&'a mut self, j: usize) -> Self::ColumnEntriesMut {
|
||||
let rng = self.column_range(j);
|
||||
|
|
@ -163,13 +209,18 @@ pub struct CsSliceStorage<'a, N: Scalar, R: Dim, C: DimAdd<U1>> {
|
|||
}*/
|
||||
|
||||
/// A compressed sparse column matrix.
|
||||
#[derive(Clone, Debug)]
|
||||
pub struct CsMatrix<N: Scalar, R: Dim, C: Dim, S: CsStorage<N, R, C> = CsVecStorage<N, R, C>> {
|
||||
#[derive(Clone, Debug, PartialEq)]
|
||||
pub struct CsMatrix<
|
||||
N: Scalar,
|
||||
R: Dim = Dynamic,
|
||||
C: Dim = Dynamic,
|
||||
S: CsStorage<N, R, C> = CsVecStorage<N, R, C>,
|
||||
> {
|
||||
pub data: S,
|
||||
_phantoms: PhantomData<(N, R, C)>,
|
||||
}
|
||||
|
||||
pub type CsVector<N, R, S = CsVecStorage<N, R, U1>> = CsMatrix<N, R, U1, S>;
|
||||
pub type CsVector<N, R = Dynamic, S = CsVecStorage<N, R, U1>> = CsMatrix<N, R, U1, S>;
|
||||
|
||||
impl<N: Scalar, R: Dim, C: Dim> CsMatrix<N, R, C>
|
||||
where
|
||||
|
|
@ -198,22 +249,66 @@ where
|
|||
_phantoms: PhantomData,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
fn cumsum<D: Dim>(a: &mut VectorN<usize, D>, b: &mut VectorN<usize, D>) -> usize
|
||||
pub fn from_parts_generic(
|
||||
nrows: R,
|
||||
ncols: C,
|
||||
p: VectorN<usize, C>,
|
||||
i: Vec<usize>,
|
||||
vals: Vec<N>,
|
||||
) -> Self
|
||||
where
|
||||
DefaultAllocator: Allocator<usize, D>,
|
||||
N: Zero + ClosedAdd,
|
||||
DefaultAllocator: Allocator<N, R>,
|
||||
{
|
||||
assert!(a.len() == b.len());
|
||||
let mut sum = 0;
|
||||
assert_eq!(ncols.value(), p.len(), "Invalid inptr size.");
|
||||
assert_eq!(i.len(), vals.len(), "Invalid value size.");
|
||||
|
||||
for i in 0..a.len() {
|
||||
b[i] = sum;
|
||||
sum += a[i];
|
||||
a[i] = b[i];
|
||||
// Check p.
|
||||
for ptr in &p {
|
||||
assert!(*ptr < i.len(), "Invalid inptr value.");
|
||||
}
|
||||
|
||||
sum
|
||||
for ptr in p.as_slice().windows(2) {
|
||||
assert!(ptr[0] <= ptr[1], "Invalid inptr ordering.");
|
||||
}
|
||||
|
||||
// Check i.
|
||||
for i in &i {
|
||||
assert!(*i < nrows.value(), "Invalid row ptr value.")
|
||||
}
|
||||
|
||||
let mut res = CsMatrix {
|
||||
data: CsVecStorage {
|
||||
shape: (nrows, ncols),
|
||||
p,
|
||||
i,
|
||||
vals,
|
||||
},
|
||||
_phantoms: PhantomData,
|
||||
};
|
||||
|
||||
// Sort and remove duplicates.
|
||||
res.sort();
|
||||
res.dedup();
|
||||
|
||||
res
|
||||
}
|
||||
}
|
||||
|
||||
impl<N: Scalar + Zero + ClosedAdd> CsMatrix<N> {
|
||||
pub fn from_parts(
|
||||
nrows: usize,
|
||||
ncols: usize,
|
||||
p: Vec<usize>,
|
||||
i: Vec<usize>,
|
||||
vals: Vec<N>,
|
||||
) -> Self {
|
||||
let nrows = Dynamic::new(nrows);
|
||||
let ncols = Dynamic::new(ncols);
|
||||
let p = DVector::from_data(MatrixVec::new(ncols, U1, p));
|
||||
Self::from_parts_generic(nrows, ncols, p, i, vals)
|
||||
}
|
||||
}
|
||||
|
||||
impl<N: Scalar, R: Dim, C: Dim, S: CsStorage<N, R, C>> CsMatrix<N, R, C, S> {
|
||||
|
|
@ -288,7 +383,7 @@ impl<N: Scalar, R: Dim, C: Dim, S: CsStorage<N, R, C>> CsMatrix<N, R, C, S> {
|
|||
workspace[row_id] += 1;
|
||||
}
|
||||
|
||||
let _ = cumsum(&mut workspace, &mut res.data.p);
|
||||
let _ = cs_utils::cumsum(&mut workspace, &mut res.data.p);
|
||||
|
||||
// Fill the result.
|
||||
for j in 0..ncols.value() {
|
||||
|
|
@ -305,6 +400,13 @@ impl<N: Scalar, R: Dim, C: Dim, S: CsStorage<N, R, C>> CsMatrix<N, R, C, S> {
|
|||
}
|
||||
}
|
||||
|
||||
impl<N: Scalar, R: Dim, C: Dim, S: CsStorageMut<N, R, C>> CsMatrix<N, R, C, S> {
|
||||
#[inline]
|
||||
pub fn values_mut(&mut self) -> impl Iterator<Item = &mut N> {
|
||||
self.data.values_mut()
|
||||
}
|
||||
}
|
||||
|
||||
impl<N: Scalar, R: Dim, C: Dim> CsMatrix<N, R, C>
|
||||
where
|
||||
DefaultAllocator: Allocator<usize, C>,
|
||||
|
|
@ -341,4 +443,46 @@ where
|
|||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Remove dupliate entries on a sorted CsMatrix.
|
||||
pub(crate) fn dedup(&mut self)
|
||||
where
|
||||
N: Zero + ClosedAdd,
|
||||
{
|
||||
let mut curr_i = 0;
|
||||
|
||||
for j in 0..self.ncols() {
|
||||
let range = self.data.column_range(j);
|
||||
self.data.p[j] = curr_i;
|
||||
|
||||
if range.start != range.end {
|
||||
let mut value = N::zero();
|
||||
let mut irow = self.data.i[range.start];
|
||||
|
||||
for idx in range {
|
||||
let curr_irow = self.data.i[idx];
|
||||
|
||||
if curr_irow == irow {
|
||||
value += self.data.vals[idx];
|
||||
} else {
|
||||
self.data.i[curr_i] = irow;
|
||||
self.data.vals[curr_i] = value;
|
||||
value = self.data.vals[idx];
|
||||
irow = curr_irow;
|
||||
curr_i += 1;
|
||||
}
|
||||
}
|
||||
|
||||
// Handle the last entry.
|
||||
self.data.i[curr_i] = irow;
|
||||
self.data.vals[curr_i] = value;
|
||||
curr_i += 1;
|
||||
}
|
||||
}
|
||||
|
||||
self.data.i.truncate(curr_i);
|
||||
self.data.i.shrink_to_fit();
|
||||
self.data.vals.truncate(curr_i);
|
||||
self.data.vals.shrink_to_fit();
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -7,9 +7,67 @@ use std::slice;
|
|||
|
||||
use allocator::Allocator;
|
||||
use constraint::{AreMultipliable, DimEq, SameNumberOfRows, ShapeConstraint};
|
||||
use sparse::cs_utils;
|
||||
use sparse::{CsMatrix, CsStorage, CsVector};
|
||||
use storage::{Storage, StorageMut};
|
||||
use {DefaultAllocator, Dim, Matrix, MatrixMN, Real, Scalar, Vector, VectorN, U1};
|
||||
use {DefaultAllocator, Dim, Dynamic, Matrix, MatrixMN, Real, Scalar, Vector, VectorN, U1};
|
||||
|
||||
impl<'a, N: Scalar + Zero + ClosedAdd> CsMatrix<N> {
|
||||
// FIXME: implement for dimensions other than Dynamic too.
|
||||
pub fn from_triplet(
|
||||
nrows: usize,
|
||||
ncols: usize,
|
||||
irows: &[usize],
|
||||
icols: &[usize],
|
||||
vals: &[N],
|
||||
) -> Self {
|
||||
Self::from_triplet_generic(Dynamic::new(nrows), Dynamic::new(ncols), irows, icols, vals)
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a, N: Scalar + Zero + ClosedAdd, R: Dim, C: Dim> CsMatrix<N, R, C>
|
||||
where
|
||||
DefaultAllocator: Allocator<usize, C> + Allocator<N, R>,
|
||||
{
|
||||
pub fn from_triplet_generic(
|
||||
nrows: R,
|
||||
ncols: C,
|
||||
irows: &[usize],
|
||||
icols: &[usize],
|
||||
vals: &[N],
|
||||
) -> Self {
|
||||
assert!(vals.len() == irows.len());
|
||||
assert!(vals.len() == icols.len());
|
||||
|
||||
let mut res = CsMatrix::new_uninitialized_generic(nrows, ncols, vals.len());
|
||||
let mut workspace = res.data.p.clone();
|
||||
|
||||
// Column count.
|
||||
for j in icols.iter().cloned() {
|
||||
workspace[j] += 1;
|
||||
}
|
||||
|
||||
let _ = cs_utils::cumsum(&mut workspace, &mut res.data.p);
|
||||
|
||||
// Fill i and vals.
|
||||
for ((i, j), val) in irows
|
||||
.iter()
|
||||
.cloned()
|
||||
.zip(icols.iter().cloned())
|
||||
.zip(vals.iter().cloned())
|
||||
{
|
||||
let offset = workspace[j];
|
||||
res.data.i[offset] = i;
|
||||
res.data.vals[offset] = val;
|
||||
workspace[j] = offset + 1;
|
||||
}
|
||||
|
||||
// Sort the result.
|
||||
res.sort();
|
||||
res.dedup();
|
||||
res
|
||||
}
|
||||
}
|
||||
|
||||
impl<'a, N: Scalar + Zero, R: Dim, C: Dim, S> From<CsMatrix<N, R, C, S>> for MatrixMN<N, R, C>
|
||||
where
|
||||
|
|
|
|||
|
|
@ -0,0 +1,18 @@
|
|||
use allocator::Allocator;
|
||||
use {DefaultAllocator, Dim, VectorN};
|
||||
|
||||
pub fn cumsum<D: Dim>(a: &mut VectorN<usize, D>, b: &mut VectorN<usize, D>) -> usize
|
||||
where
|
||||
DefaultAllocator: Allocator<usize, D>,
|
||||
{
|
||||
assert!(a.len() == b.len());
|
||||
let mut sum = 0;
|
||||
|
||||
for i in 0..a.len() {
|
||||
b[i] = sum;
|
||||
sum += a[i];
|
||||
a[i] = b[i];
|
||||
}
|
||||
|
||||
sum
|
||||
}
|
||||
|
|
@ -8,3 +8,4 @@ mod cs_matrix_cholesky;
|
|||
mod cs_matrix_conversion;
|
||||
mod cs_matrix_ops;
|
||||
mod cs_matrix_solve;
|
||||
pub mod cs_utils;
|
||||
|
|
|
|||
|
|
@ -1,9 +1,8 @@
|
|||
#![cfg_attr(rustfmt, rustfmt_skip)]
|
||||
|
||||
use na::{Matrix4x5, CsMatrix};
|
||||
use na::{CsMatrix, DMatrix, Matrix4x5};
|
||||
|
||||
#[test]
|
||||
fn cs_from_to_matrix() {
|
||||
#[cfg_attr(rustfmt, rustfmt_skip)]
|
||||
let m = Matrix4x5::new(
|
||||
5.0, 6.0, 0.0, 8.0, 15.0,
|
||||
9.0, 10.0, 11.0, 12.0, 0.0,
|
||||
|
|
@ -17,3 +16,74 @@ fn cs_from_to_matrix() {
|
|||
let m2: Matrix4x5<_> = cs.into();
|
||||
assert_eq!(m2, m);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn cs_matrix_from_triplet() {
|
||||
let mut irows = vec![0, 0, 0, 0, 1, 1, 1, 1, 2, 3, 3, 3];
|
||||
let mut icols = vec![0, 1, 3, 4, 0, 1, 2, 3, 2, 1, 2, 4];
|
||||
let mut vals = vec![
|
||||
5.0, 6.0, 8.0, 15.0, 9.0, 10.0, 11.0, 12.0, 13.0, 1.0, 4.0, 14.0,
|
||||
];
|
||||
|
||||
#[cfg_attr(rustfmt, rustfmt_skip)]
|
||||
let expected = DMatrix::from_row_slice(4, 5, &[
|
||||
5.0, 6.0, 0.0, 8.0, 15.0,
|
||||
9.0, 10.0, 11.0, 12.0, 0.0,
|
||||
0.0, 0.0, 13.0, 0.0, 0.0,
|
||||
0.0, 1.0, 4.0, 0.0, 14.0,
|
||||
]);
|
||||
let cs_expected = CsMatrix::from_parts(
|
||||
4,
|
||||
5,
|
||||
vec![0, 2, 5, 8, 10],
|
||||
vec![0, 1, 0, 1, 3, 1, 2, 3, 0, 1, 0, 3],
|
||||
vec![
|
||||
5.0, 9.0, 6.0, 10.0, 1.0, 11.0, 13.0, 4.0, 8.0, 12.0, 15.0, 14.0,
|
||||
],
|
||||
);
|
||||
|
||||
let cs_mat = CsMatrix::from_triplet(4, 5, &irows, &icols, &vals);
|
||||
println!("Mat from triplet: {:?}", cs_mat);
|
||||
assert!(cs_mat.is_sorted());
|
||||
assert_eq!(cs_mat, cs_expected);
|
||||
|
||||
let m: DMatrix<_> = cs_mat.into();
|
||||
assert_eq!(m, expected);
|
||||
|
||||
/*
|
||||
* Try again with some permutations.
|
||||
*/
|
||||
let permutations = [(2, 5), (0, 4), (8, 10), (1, 11)];
|
||||
|
||||
for (i, j) in &permutations {
|
||||
irows.swap(*i, *j);
|
||||
icols.swap(*i, *j);
|
||||
vals.swap(*i, *j);
|
||||
}
|
||||
|
||||
let cs_mat = CsMatrix::from_triplet(4, 5, &irows, &icols, &vals);
|
||||
println!("Mat from triplet: {:?}", cs_mat);
|
||||
assert!(cs_mat.is_sorted());
|
||||
assert_eq!(cs_mat, cs_expected);
|
||||
|
||||
let m: DMatrix<_> = cs_mat.into();
|
||||
assert_eq!(m, expected);
|
||||
|
||||
/*
|
||||
* Try again, duplicating all entries.
|
||||
*/
|
||||
let mut ir = irows.clone();
|
||||
let mut ic = icols.clone();
|
||||
let mut va = vals.clone();
|
||||
irows.append(&mut ir);
|
||||
icols.append(&mut ic);
|
||||
vals.append(&mut va);
|
||||
|
||||
let cs_mat = CsMatrix::from_triplet(4, 5, &irows, &icols, &vals);
|
||||
println!("Mat from triplet: {:?}", cs_mat);
|
||||
assert!(cs_mat.is_sorted());
|
||||
assert_eq!(cs_mat, cs_expected * 2.0);
|
||||
|
||||
let m: DMatrix<_> = cs_mat.into();
|
||||
assert_eq!(m, expected * 2.0);
|
||||
}
|
||||
|
|
|
|||
|
|
@ -0,0 +1,55 @@
|
|||
#![cfg_attr(rustfmt, rustfmt_skip)]
|
||||
|
||||
|
||||
use na::io;
|
||||
use na::DMatrix;
|
||||
|
||||
#[test]
|
||||
fn cs_matrix_market() {
|
||||
let file_str = r#"
|
||||
%%MatrixMarket matrix coordinate real general
|
||||
%=================================================================================
|
||||
%
|
||||
% This ASCII file represents a sparse MxN matrix with L
|
||||
% nonzeros in the following Matrix Market format:
|
||||
%
|
||||
% +----------------------------------------------+
|
||||
% |%%MatrixMarket matrix coordinate real general | <--- header line
|
||||
% |% | <--+
|
||||
% |% comments | |-- 0 or more comment lines
|
||||
% |% | <--+
|
||||
% | M N L | <--- rows, columns, entries
|
||||
% | I1 J1 A(I1, J1) | <--+
|
||||
% | I2 J2 A(I2, J2) | |
|
||||
% | I3 J3 A(I3, J3) | |-- L lines
|
||||
% | . . . | |
|
||||
% | IL JL A(IL, JL) | <--+
|
||||
% +----------------------------------------------+
|
||||
%
|
||||
% Indices are 1-based, i.e. A(1,1) is the first element.
|
||||
%
|
||||
%=================================================================================
|
||||
5 5 8
|
||||
1 1 1.000e+00
|
||||
2 2 1.050e+01
|
||||
3 3 1.500e-02
|
||||
1 4 6.000e+00
|
||||
4 2 2.505e+02
|
||||
4 4 -2.800e+02
|
||||
4 5 3.332e+01
|
||||
5 5 1.200e+01
|
||||
"#;
|
||||
|
||||
let cs_mat = io::cs_matrix_from_matrix_market_str(file_str).unwrap();
|
||||
println!("CS mat: {:?}", cs_mat);
|
||||
let mat: DMatrix<_> = cs_mat.into();
|
||||
let expected = DMatrix::from_row_slice(5, 5, &[
|
||||
1.0, 0.0, 0.0, 6.0, 0.0,
|
||||
0.0, 10.5, 0.0, 0.0, 0.0,
|
||||
0.0, 0.0, 0.015, 0.0, 0.0,
|
||||
0.0, 250.5, 0.0, -280.0, 33.32,
|
||||
0.0, 0.0, 0.0, 0.0, 12.0,
|
||||
]);
|
||||
|
||||
assert_eq!(mat, expected);
|
||||
}
|
||||
|
|
@ -2,5 +2,7 @@ mod cs_cholesky;
|
|||
mod cs_construction;
|
||||
mod cs_conversion;
|
||||
mod cs_matrix;
|
||||
#[cfg(feature = "io")]
|
||||
mod cs_matrix_market;
|
||||
mod cs_ops;
|
||||
mod cs_solve;
|
||||
|
|
|
|||
Loading…
Reference in New Issue