806 lines
27 KiB
Rust
806 lines
27 KiB
Rust
//! An implementation of the CSR sparse matrix format.
|
|
//!
|
|
//! This is the module-level documentation. See [`CsrMatrix`] for the main documentation of the
|
|
//! CSC implementation.
|
|
use crate::cs::{CsLane, CsLaneIter, CsLaneIterMut, CsLaneMut, CsMatrix};
|
|
use crate::csc::CscMatrix;
|
|
use crate::pattern::{SparsityPattern, SparsityPatternFormatError, SparsityPatternIter};
|
|
use crate::utils::apply_permutation;
|
|
use crate::{SparseEntry, SparseEntryMut, SparseFormatError, SparseFormatErrorKind};
|
|
|
|
use nalgebra::Scalar;
|
|
use num_traits::One;
|
|
use num_traits::Zero;
|
|
|
|
use std::slice::{Iter, IterMut};
|
|
|
|
/// A CSR representation of a sparse matrix.
|
|
///
|
|
/// The Compressed Sparse Row (CSR) format is well-suited as a general-purpose storage format
|
|
/// for many sparse matrix applications.
|
|
///
|
|
/// # Usage
|
|
///
|
|
/// ```
|
|
/// use nalgebra_sparse::csr::CsrMatrix;
|
|
/// use nalgebra::{DMatrix, Matrix3x4};
|
|
/// use matrixcompare::assert_matrix_eq;
|
|
///
|
|
/// // The sparsity patterns of CSR matrices are immutable. This means that you cannot dynamically
|
|
/// // change the sparsity pattern of the matrix after it has been constructed. The easiest
|
|
/// // way to construct a CSR matrix is to first incrementally construct a COO matrix,
|
|
/// // and then convert it to CSR.
|
|
/// # use nalgebra_sparse::coo::CooMatrix;
|
|
/// # let coo = CooMatrix::<f64>::new(3, 3);
|
|
/// let csr = CsrMatrix::from(&coo);
|
|
///
|
|
/// // Alternatively, a CSR matrix can be constructed directly from raw CSR data.
|
|
/// // Here, we construct a 3x4 matrix
|
|
/// let row_offsets = vec![0, 3, 3, 5];
|
|
/// let col_indices = vec![0, 1, 3, 1, 2];
|
|
/// let values = vec![1.0, 2.0, 3.0, 4.0, 5.0];
|
|
///
|
|
/// // The dense representation of the CSR data, for comparison
|
|
/// let dense = Matrix3x4::new(1.0, 2.0, 0.0, 3.0,
|
|
/// 0.0, 0.0, 0.0, 0.0,
|
|
/// 0.0, 4.0, 5.0, 0.0);
|
|
///
|
|
/// // The constructor validates the raw CSR data and returns an error if it is invalid.
|
|
/// let csr = CsrMatrix::try_from_csr_data(3, 4, row_offsets, col_indices, values)
|
|
/// .expect("CSR data must conform to format specifications");
|
|
/// assert_matrix_eq!(csr, dense);
|
|
///
|
|
/// // A third approach is to construct a CSR matrix from a pattern and values. Sometimes this is
|
|
/// // useful if the sparsity pattern is constructed separately from the values of the matrix.
|
|
/// let (pattern, values) = csr.into_pattern_and_values();
|
|
/// let csr = CsrMatrix::try_from_pattern_and_values(pattern, values)
|
|
/// .expect("The pattern and values must be compatible");
|
|
///
|
|
/// // Once we have constructed our matrix, we can use it for arithmetic operations together with
|
|
/// // other CSR matrices and dense matrices/vectors.
|
|
/// let x = csr;
|
|
/// # #[allow(non_snake_case)]
|
|
/// let xTx = x.transpose() * &x;
|
|
/// let z = DMatrix::from_fn(4, 8, |i, j| (i as f64) * (j as f64));
|
|
/// let w = 3.0 * xTx * z;
|
|
///
|
|
/// // Although the sparsity pattern of a CSR matrix cannot be changed, its values can.
|
|
/// // Here are two different ways to scale all values by a constant:
|
|
/// let mut x = x;
|
|
/// x *= 5.0;
|
|
/// x.values_mut().iter_mut().for_each(|x_i| *x_i *= 5.0);
|
|
/// ```
|
|
///
|
|
/// # Format
|
|
///
|
|
/// An `m x n` sparse matrix with `nnz` non-zeros in CSR format is represented by the
|
|
/// following three arrays:
|
|
///
|
|
/// - `row_offsets`, an array of integers with length `m + 1`.
|
|
/// - `col_indices`, an array of integers with length `nnz`.
|
|
/// - `values`, an array of values with length `nnz`.
|
|
///
|
|
/// The relationship between the arrays is described below.
|
|
///
|
|
/// - Each consecutive pair of entries `row_offsets[i] .. row_offsets[i + 1]` corresponds to an
|
|
/// offset range in `col_indices` that holds the column indices in row `i`.
|
|
/// - For an entry represented by the index `idx`, `col_indices[idx]` stores its column index and
|
|
/// `values[idx]` stores its value.
|
|
///
|
|
/// The following invariants must be upheld and are enforced by the data structure:
|
|
///
|
|
/// - `row_offsets[0] == 0`
|
|
/// - `row_offsets[m] == nnz`
|
|
/// - `row_offsets` is monotonically increasing.
|
|
/// - `0 <= col_indices[idx] < n` for all `idx < nnz`.
|
|
/// - The column indices associated with each row are monotonically increasing (see below).
|
|
///
|
|
/// The CSR format is a standard sparse matrix format (see [Wikipedia article]). The format
|
|
/// represents the matrix in a row-by-row fashion. The entries associated with row `i` are
|
|
/// determined as follows:
|
|
///
|
|
/// ```
|
|
/// # let row_offsets: Vec<usize> = vec![0, 0];
|
|
/// # let col_indices: Vec<usize> = vec![];
|
|
/// # let values: Vec<i32> = vec![];
|
|
/// # let i = 0;
|
|
/// let range = row_offsets[i] .. row_offsets[i + 1];
|
|
/// let row_i_cols = &col_indices[range.clone()];
|
|
/// let row_i_vals = &values[range];
|
|
///
|
|
/// // For each pair (j, v) in (row_i_cols, row_i_vals), we obtain a corresponding entry
|
|
/// // (i, j, v) in the matrix.
|
|
/// assert_eq!(row_i_cols.len(), row_i_vals.len());
|
|
/// ```
|
|
///
|
|
/// In the above example, for each row `i`, the column indices `row_i_cols` must appear in
|
|
/// monotonically increasing order. In other words, they must be *sorted*. This criterion is not
|
|
/// standard among all sparse matrix libraries, but we enforce this property as it is a crucial
|
|
/// assumption for both correctness and performance for many algorithms.
|
|
///
|
|
/// Note that the CSR and CSC formats are essentially identical, except that CSC stores the matrix
|
|
/// column-by-column instead of row-by-row like CSR.
|
|
///
|
|
/// [Wikipedia article]: https://en.wikipedia.org/wiki/Sparse_matrix#Compressed_sparse_row_(CSR,_CRS_or_Yale_format)
|
|
#[derive(Debug, Clone, PartialEq, Eq)]
|
|
pub struct CsrMatrix<T> {
|
|
// Rows are major, cols are minor in the sparsity pattern
|
|
pub(crate) cs: CsMatrix<T>,
|
|
}
|
|
|
|
impl<T> CsrMatrix<T> {
|
|
/// Constructs a CSR representation of the (square) `n x n` identity matrix.
|
|
#[inline]
|
|
pub fn identity(n: usize) -> Self
|
|
where
|
|
T: Scalar + One,
|
|
{
|
|
Self {
|
|
cs: CsMatrix::identity(n),
|
|
}
|
|
}
|
|
|
|
/// Create a zero CSR matrix with no explicitly stored entries.
|
|
pub fn zeros(nrows: usize, ncols: usize) -> Self {
|
|
Self {
|
|
cs: CsMatrix::new(nrows, ncols),
|
|
}
|
|
}
|
|
|
|
/// Try to construct a CSR matrix from raw CSR data.
|
|
///
|
|
/// It is assumed that each row contains unique and sorted column indices that are in
|
|
/// bounds with respect to the number of columns in the matrix. If this is not the case,
|
|
/// an error is returned to indicate the failure.
|
|
///
|
|
/// An error is returned if the data given does not conform to the CSR storage format.
|
|
/// See the documentation for [CsrMatrix](struct.CsrMatrix.html) for more information.
|
|
pub fn try_from_csr_data(
|
|
num_rows: usize,
|
|
num_cols: usize,
|
|
row_offsets: Vec<usize>,
|
|
col_indices: Vec<usize>,
|
|
values: Vec<T>,
|
|
) -> Result<Self, SparseFormatError> {
|
|
let pattern = SparsityPattern::try_from_offsets_and_indices(
|
|
num_rows,
|
|
num_cols,
|
|
row_offsets,
|
|
col_indices,
|
|
)
|
|
.map_err(pattern_format_error_to_csr_error)?;
|
|
Self::try_from_pattern_and_values(pattern, values)
|
|
}
|
|
|
|
/// Try to construct a CSR matrix from raw CSR data with unsorted column indices.
|
|
///
|
|
/// It is assumed that each row contains unique column indices that are in
|
|
/// bounds with respect to the number of columns in the matrix. If this is not the case,
|
|
/// an error is returned to indicate the failure.
|
|
///
|
|
/// An error is returned if the data given does not conform to the CSR storage format
|
|
/// with the exception of having unsorted column indices and values.
|
|
/// See the documentation for [CsrMatrix](struct.CsrMatrix.html) for more information.
|
|
pub fn try_from_unsorted_csr_data(
|
|
num_rows: usize,
|
|
num_cols: usize,
|
|
row_offsets: Vec<usize>,
|
|
col_indices: Vec<usize>,
|
|
values: Vec<T>,
|
|
) -> Result<Self, SparseFormatError>
|
|
where
|
|
T: Scalar + Zero,
|
|
{
|
|
use SparsityPatternFormatError::*;
|
|
let count = col_indices.len();
|
|
let mut p: Vec<usize> = (0..count).collect();
|
|
|
|
if col_indices.len() != values.len() {
|
|
return Err(SparseFormatError::from_kind_and_msg(
|
|
SparseFormatErrorKind::InvalidStructure,
|
|
"Number of values and column indices must be the same",
|
|
));
|
|
}
|
|
|
|
if row_offsets.len() == 0 {
|
|
return Err(SparseFormatError::from_kind_and_msg(
|
|
SparseFormatErrorKind::InvalidStructure,
|
|
"Number of offsets should be greater than 0",
|
|
));
|
|
}
|
|
|
|
for (index, &offset) in row_offsets[0..row_offsets.len() - 1].iter().enumerate() {
|
|
let next_offset = row_offsets[index + 1];
|
|
if next_offset > count {
|
|
return Err(SparseFormatError::from_kind_and_msg(
|
|
SparseFormatErrorKind::InvalidStructure,
|
|
"No row offset should be greater than the number of column indices",
|
|
));
|
|
}
|
|
if offset > next_offset {
|
|
return Err(NonmonotonicOffsets).map_err(pattern_format_error_to_csr_error);
|
|
}
|
|
p[offset..next_offset].sort_by(|a, b| {
|
|
let x = &col_indices[*a];
|
|
let y = &col_indices[*b];
|
|
x.partial_cmp(y).unwrap()
|
|
});
|
|
}
|
|
|
|
// permute indices
|
|
let sorted_col_indices: Vec<usize> = p.iter().map(|i| col_indices[*i]).collect();
|
|
|
|
// permute values
|
|
let mut sorted_values: Vec<T> = vec![T::zero(); count];
|
|
apply_permutation(&mut sorted_values, &values, &p);
|
|
|
|
return Self::try_from_csr_data(
|
|
num_rows,
|
|
num_cols,
|
|
row_offsets,
|
|
sorted_col_indices,
|
|
sorted_values,
|
|
);
|
|
}
|
|
|
|
/// Try to construct a CSR matrix from a sparsity pattern and associated non-zero values.
|
|
///
|
|
/// Returns an error if the number of values does not match the number of minor indices
|
|
/// in the pattern.
|
|
pub fn try_from_pattern_and_values(
|
|
pattern: SparsityPattern,
|
|
values: Vec<T>,
|
|
) -> Result<Self, SparseFormatError> {
|
|
if pattern.nnz() == values.len() {
|
|
Ok(Self {
|
|
cs: CsMatrix::from_pattern_and_values(pattern, values),
|
|
})
|
|
} else {
|
|
Err(SparseFormatError::from_kind_and_msg(
|
|
SparseFormatErrorKind::InvalidStructure,
|
|
"Number of values and column indices must be the same",
|
|
))
|
|
}
|
|
}
|
|
|
|
/// The number of rows in the matrix.
|
|
#[inline]
|
|
#[must_use]
|
|
pub fn nrows(&self) -> usize {
|
|
self.cs.pattern().major_dim()
|
|
}
|
|
|
|
/// The number of columns in the matrix.
|
|
#[inline]
|
|
#[must_use]
|
|
pub fn ncols(&self) -> usize {
|
|
self.cs.pattern().minor_dim()
|
|
}
|
|
|
|
/// The number of non-zeros in the matrix.
|
|
///
|
|
/// Note that this corresponds to the number of explicitly stored entries, *not* the actual
|
|
/// number of algebraically zero entries in the matrix. Explicitly stored entries can still
|
|
/// be zero. Corresponds to the number of entries in the sparsity pattern.
|
|
#[inline]
|
|
#[must_use]
|
|
pub fn nnz(&self) -> usize {
|
|
self.cs.pattern().nnz()
|
|
}
|
|
|
|
/// The row offsets defining part of the CSR format.
|
|
#[inline]
|
|
#[must_use]
|
|
pub fn row_offsets(&self) -> &[usize] {
|
|
let (offsets, _, _) = self.cs.cs_data();
|
|
offsets
|
|
}
|
|
|
|
/// The column indices defining part of the CSR format.
|
|
#[inline]
|
|
#[must_use]
|
|
pub fn col_indices(&self) -> &[usize] {
|
|
let (_, indices, _) = self.cs.cs_data();
|
|
indices
|
|
}
|
|
|
|
/// The non-zero values defining part of the CSR format.
|
|
#[inline]
|
|
#[must_use]
|
|
pub fn values(&self) -> &[T] {
|
|
self.cs.values()
|
|
}
|
|
|
|
/// Mutable access to the non-zero values.
|
|
#[inline]
|
|
pub fn values_mut(&mut self) -> &mut [T] {
|
|
self.cs.values_mut()
|
|
}
|
|
|
|
/// An iterator over non-zero triplets (i, j, v).
|
|
///
|
|
/// The iteration happens in row-major fashion, meaning that i increases monotonically,
|
|
/// and j increases monotonically within each row.
|
|
///
|
|
/// Examples
|
|
/// --------
|
|
/// ```
|
|
/// # use nalgebra_sparse::csr::CsrMatrix;
|
|
/// let row_offsets = vec![0, 2, 3, 4];
|
|
/// let col_indices = vec![0, 2, 1, 0];
|
|
/// let values = vec![1, 2, 3, 4];
|
|
/// let mut csr = CsrMatrix::try_from_csr_data(3, 4, row_offsets, col_indices, values)
|
|
/// .unwrap();
|
|
///
|
|
/// let triplets: Vec<_> = csr.triplet_iter().map(|(i, j, v)| (i, j, *v)).collect();
|
|
/// assert_eq!(triplets, vec![(0, 0, 1), (0, 2, 2), (1, 1, 3), (2, 0, 4)]);
|
|
/// ```
|
|
pub fn triplet_iter(&self) -> CsrTripletIter<'_, T> {
|
|
CsrTripletIter {
|
|
pattern_iter: self.pattern().entries(),
|
|
values_iter: self.values().iter(),
|
|
}
|
|
}
|
|
|
|
/// A mutable iterator over non-zero triplets (i, j, v).
|
|
///
|
|
/// Iteration happens in the same order as for [triplet_iter](#method.triplet_iter).
|
|
///
|
|
/// Examples
|
|
/// --------
|
|
/// ```
|
|
/// # use nalgebra_sparse::csr::CsrMatrix;
|
|
/// # let row_offsets = vec![0, 2, 3, 4];
|
|
/// # let col_indices = vec![0, 2, 1, 0];
|
|
/// # let values = vec![1, 2, 3, 4];
|
|
/// // Using the same data as in the `triplet_iter` example
|
|
/// let mut csr = CsrMatrix::try_from_csr_data(3, 4, row_offsets, col_indices, values)
|
|
/// .unwrap();
|
|
///
|
|
/// // Zero out lower-triangular terms
|
|
/// csr.triplet_iter_mut()
|
|
/// .filter(|(i, j, _)| j < i)
|
|
/// .for_each(|(_, _, v)| *v = 0);
|
|
///
|
|
/// let triplets: Vec<_> = csr.triplet_iter().map(|(i, j, v)| (i, j, *v)).collect();
|
|
/// assert_eq!(triplets, vec![(0, 0, 1), (0, 2, 2), (1, 1, 3), (2, 0, 0)]);
|
|
/// ```
|
|
pub fn triplet_iter_mut(&mut self) -> CsrTripletIterMut<'_, T> {
|
|
let (pattern, values) = self.cs.pattern_and_values_mut();
|
|
CsrTripletIterMut {
|
|
pattern_iter: pattern.entries(),
|
|
values_mut_iter: values.iter_mut(),
|
|
}
|
|
}
|
|
|
|
/// Return the row at the given row index.
|
|
///
|
|
/// Panics
|
|
/// ------
|
|
/// Panics if row index is out of bounds.
|
|
#[inline]
|
|
#[must_use]
|
|
pub fn row(&self, index: usize) -> CsrRow<'_, T> {
|
|
self.get_row(index).expect("Row index must be in bounds")
|
|
}
|
|
|
|
/// Mutable row access for the given row index.
|
|
///
|
|
/// Panics
|
|
/// ------
|
|
/// Panics if row index is out of bounds.
|
|
#[inline]
|
|
pub fn row_mut(&mut self, index: usize) -> CsrRowMut<'_, T> {
|
|
self.get_row_mut(index)
|
|
.expect("Row index must be in bounds")
|
|
}
|
|
|
|
/// Return the row at the given row index, or `None` if out of bounds.
|
|
#[inline]
|
|
#[must_use]
|
|
pub fn get_row(&self, index: usize) -> Option<CsrRow<'_, T>> {
|
|
self.cs.get_lane(index).map(|lane| CsrRow { lane })
|
|
}
|
|
|
|
/// Mutable row access for the given row index, or `None` if out of bounds.
|
|
#[inline]
|
|
#[must_use]
|
|
pub fn get_row_mut(&mut self, index: usize) -> Option<CsrRowMut<'_, T>> {
|
|
self.cs.get_lane_mut(index).map(|lane| CsrRowMut { lane })
|
|
}
|
|
|
|
/// An iterator over rows in the matrix.
|
|
pub fn row_iter(&self) -> CsrRowIter<'_, T> {
|
|
CsrRowIter {
|
|
lane_iter: CsLaneIter::new(self.pattern(), self.values()),
|
|
}
|
|
}
|
|
|
|
/// A mutable iterator over rows in the matrix.
|
|
pub fn row_iter_mut(&mut self) -> CsrRowIterMut<'_, T> {
|
|
let (pattern, values) = self.cs.pattern_and_values_mut();
|
|
CsrRowIterMut {
|
|
lane_iter: CsLaneIterMut::new(pattern, values),
|
|
}
|
|
}
|
|
|
|
/// Disassembles the CSR matrix into its underlying offset, index and value arrays.
|
|
///
|
|
/// If the matrix contains the sole reference to the sparsity pattern,
|
|
/// then the data is returned as-is. Otherwise, the sparsity pattern is cloned.
|
|
///
|
|
/// Examples
|
|
/// --------
|
|
///
|
|
/// ```
|
|
/// # use nalgebra_sparse::csr::CsrMatrix;
|
|
/// let row_offsets = vec![0, 2, 3, 4];
|
|
/// let col_indices = vec![0, 2, 1, 0];
|
|
/// let values = vec![1, 2, 3, 4];
|
|
/// let mut csr = CsrMatrix::try_from_csr_data(
|
|
/// 3,
|
|
/// 4,
|
|
/// row_offsets.clone(),
|
|
/// col_indices.clone(),
|
|
/// values.clone())
|
|
/// .unwrap();
|
|
/// let (row_offsets2, col_indices2, values2) = csr.disassemble();
|
|
/// assert_eq!(row_offsets2, row_offsets);
|
|
/// assert_eq!(col_indices2, col_indices);
|
|
/// assert_eq!(values2, values);
|
|
/// ```
|
|
pub fn disassemble(self) -> (Vec<usize>, Vec<usize>, Vec<T>) {
|
|
self.cs.disassemble()
|
|
}
|
|
|
|
/// Returns the sparsity pattern and values associated with this matrix.
|
|
pub fn into_pattern_and_values(self) -> (SparsityPattern, Vec<T>) {
|
|
self.cs.into_pattern_and_values()
|
|
}
|
|
|
|
/// Returns a reference to the sparsity pattern and a mutable reference to the values.
|
|
#[inline]
|
|
pub fn pattern_and_values_mut(&mut self) -> (&SparsityPattern, &mut [T]) {
|
|
self.cs.pattern_and_values_mut()
|
|
}
|
|
|
|
/// Returns a reference to the underlying sparsity pattern.
|
|
#[must_use]
|
|
pub fn pattern(&self) -> &SparsityPattern {
|
|
self.cs.pattern()
|
|
}
|
|
|
|
/// Reinterprets the CSR matrix as its transpose represented by a CSC matrix.
|
|
///
|
|
/// This operation does not touch the CSR data, and is effectively a no-op.
|
|
pub fn transpose_as_csc(self) -> CscMatrix<T> {
|
|
let (pattern, values) = self.cs.take_pattern_and_values();
|
|
CscMatrix::try_from_pattern_and_values(pattern, values).unwrap()
|
|
}
|
|
|
|
/// Returns an entry for the given row/col indices, or `None` if the indices are out of bounds.
|
|
///
|
|
/// Each call to this function incurs the cost of a binary search among the explicitly
|
|
/// stored column entries for the given row.
|
|
#[must_use]
|
|
pub fn get_entry(&self, row_index: usize, col_index: usize) -> Option<SparseEntry<'_, T>> {
|
|
self.cs.get_entry(row_index, col_index)
|
|
}
|
|
|
|
/// Returns a mutable entry for the given row/col indices, or `None` if the indices are out
|
|
/// of bounds.
|
|
///
|
|
/// Each call to this function incurs the cost of a binary search among the explicitly
|
|
/// stored column entries for the given row.
|
|
pub fn get_entry_mut(
|
|
&mut self,
|
|
row_index: usize,
|
|
col_index: usize,
|
|
) -> Option<SparseEntryMut<'_, T>> {
|
|
self.cs.get_entry_mut(row_index, col_index)
|
|
}
|
|
|
|
/// Returns an entry for the given row/col indices.
|
|
///
|
|
/// Same as `get_entry`, except that it directly panics upon encountering row/col indices
|
|
/// out of bounds.
|
|
///
|
|
/// Panics
|
|
/// ------
|
|
/// Panics if `row_index` or `col_index` is out of bounds.
|
|
#[must_use]
|
|
pub fn index_entry(&self, row_index: usize, col_index: usize) -> SparseEntry<'_, T> {
|
|
self.get_entry(row_index, col_index)
|
|
.expect("Out of bounds matrix indices encountered")
|
|
}
|
|
|
|
/// Returns a mutable entry for the given row/col indices.
|
|
///
|
|
/// Same as `get_entry_mut`, except that it directly panics upon encountering row/col indices
|
|
/// out of bounds.
|
|
///
|
|
/// Panics
|
|
/// ------
|
|
/// Panics if `row_index` or `col_index` is out of bounds.
|
|
pub fn index_entry_mut(&mut self, row_index: usize, col_index: usize) -> SparseEntryMut<'_, T> {
|
|
self.get_entry_mut(row_index, col_index)
|
|
.expect("Out of bounds matrix indices encountered")
|
|
}
|
|
|
|
/// Returns a triplet of slices `(row_offsets, col_indices, values)` that make up the CSR data.
|
|
#[must_use]
|
|
pub fn csr_data(&self) -> (&[usize], &[usize], &[T]) {
|
|
self.cs.cs_data()
|
|
}
|
|
|
|
/// Returns a triplet of slices `(row_offsets, col_indices, values)` that make up the CSR data,
|
|
/// where the `values` array is mutable.
|
|
pub fn csr_data_mut(&mut self) -> (&[usize], &[usize], &mut [T]) {
|
|
self.cs.cs_data_mut()
|
|
}
|
|
|
|
/// Creates a sparse matrix that contains only the explicit entries decided by the
|
|
/// given predicate.
|
|
#[must_use]
|
|
pub fn filter<P>(&self, predicate: P) -> Self
|
|
where
|
|
T: Clone,
|
|
P: Fn(usize, usize, &T) -> bool,
|
|
{
|
|
Self {
|
|
cs: self
|
|
.cs
|
|
.filter(|row_idx, col_idx, v| predicate(row_idx, col_idx, v)),
|
|
}
|
|
}
|
|
|
|
/// Returns a new matrix representing the upper triangular part of this matrix.
|
|
///
|
|
/// The result includes the diagonal of the matrix.
|
|
#[must_use]
|
|
pub fn upper_triangle(&self) -> Self
|
|
where
|
|
T: Clone,
|
|
{
|
|
self.filter(|i, j, _| i <= j)
|
|
}
|
|
|
|
/// Returns a new matrix representing the lower triangular part of this matrix.
|
|
///
|
|
/// The result includes the diagonal of the matrix.
|
|
#[must_use]
|
|
pub fn lower_triangle(&self) -> Self
|
|
where
|
|
T: Clone,
|
|
{
|
|
self.filter(|i, j, _| i >= j)
|
|
}
|
|
|
|
/// Returns the diagonal of the matrix as a sparse matrix.
|
|
#[must_use]
|
|
pub fn diagonal_as_csr(&self) -> Self
|
|
where
|
|
T: Clone,
|
|
{
|
|
Self {
|
|
cs: self.cs.diagonal_as_matrix(),
|
|
}
|
|
}
|
|
|
|
/// Compute the transpose of the matrix.
|
|
#[must_use]
|
|
pub fn transpose(&self) -> CsrMatrix<T>
|
|
where
|
|
T: Scalar,
|
|
{
|
|
CscMatrix::from(self).transpose_as_csr()
|
|
}
|
|
}
|
|
|
|
/// Convert pattern format errors into more meaningful CSR-specific errors.
|
|
///
|
|
/// This ensures that the terminology is consistent: we are talking about rows and columns,
|
|
/// not lanes, major and minor dimensions.
|
|
fn pattern_format_error_to_csr_error(err: SparsityPatternFormatError) -> SparseFormatError {
|
|
use SparseFormatError as E;
|
|
use SparseFormatErrorKind as K;
|
|
use SparsityPatternFormatError::DuplicateEntry as PatternDuplicateEntry;
|
|
use SparsityPatternFormatError::*;
|
|
|
|
match err {
|
|
InvalidOffsetArrayLength => E::from_kind_and_msg(
|
|
K::InvalidStructure,
|
|
"Length of row offset array is not equal to nrows + 1.",
|
|
),
|
|
InvalidOffsetFirstLast => E::from_kind_and_msg(
|
|
K::InvalidStructure,
|
|
"First or last row offset is inconsistent with format specification.",
|
|
),
|
|
NonmonotonicOffsets => E::from_kind_and_msg(
|
|
K::InvalidStructure,
|
|
"Row offsets are not monotonically increasing.",
|
|
),
|
|
NonmonotonicMinorIndices => E::from_kind_and_msg(
|
|
K::InvalidStructure,
|
|
"Column indices are not monotonically increasing (sorted) within each row.",
|
|
),
|
|
MinorIndexOutOfBounds => {
|
|
E::from_kind_and_msg(K::IndexOutOfBounds, "Column indices are out of bounds.")
|
|
}
|
|
PatternDuplicateEntry => {
|
|
E::from_kind_and_msg(K::DuplicateEntry, "Matrix data contains duplicate entries.")
|
|
}
|
|
}
|
|
}
|
|
|
|
/// Iterator type for iterating over triplets in a CSR matrix.
|
|
#[derive(Debug)]
|
|
pub struct CsrTripletIter<'a, T> {
|
|
pattern_iter: SparsityPatternIter<'a>,
|
|
values_iter: Iter<'a, T>,
|
|
}
|
|
|
|
impl<'a, T: Clone> CsrTripletIter<'a, T> {
|
|
/// Adapts the triplet iterator to return owned values.
|
|
///
|
|
/// The triplet iterator returns references to the values. This method adapts the iterator
|
|
/// so that the values are cloned.
|
|
#[inline]
|
|
pub fn cloned_values(self) -> impl 'a + Iterator<Item = (usize, usize, T)> {
|
|
self.map(|(i, j, v)| (i, j, v.clone()))
|
|
}
|
|
}
|
|
|
|
impl<'a, T> Iterator for CsrTripletIter<'a, T> {
|
|
type Item = (usize, usize, &'a T);
|
|
|
|
fn next(&mut self) -> Option<Self::Item> {
|
|
let next_entry = self.pattern_iter.next();
|
|
let next_value = self.values_iter.next();
|
|
|
|
match (next_entry, next_value) {
|
|
(Some((i, j)), Some(v)) => Some((i, j, v)),
|
|
_ => None,
|
|
}
|
|
}
|
|
}
|
|
|
|
/// Iterator type for mutably iterating over triplets in a CSR matrix.
|
|
#[derive(Debug)]
|
|
pub struct CsrTripletIterMut<'a, T> {
|
|
pattern_iter: SparsityPatternIter<'a>,
|
|
values_mut_iter: IterMut<'a, T>,
|
|
}
|
|
|
|
impl<'a, T> Iterator for CsrTripletIterMut<'a, T> {
|
|
type Item = (usize, usize, &'a mut T);
|
|
|
|
#[inline]
|
|
fn next(&mut self) -> Option<Self::Item> {
|
|
let next_entry = self.pattern_iter.next();
|
|
let next_value = self.values_mut_iter.next();
|
|
|
|
match (next_entry, next_value) {
|
|
(Some((i, j)), Some(v)) => Some((i, j, v)),
|
|
_ => None,
|
|
}
|
|
}
|
|
}
|
|
|
|
/// An immutable representation of a row in a CSR matrix.
|
|
#[derive(Debug, Clone, PartialEq, Eq)]
|
|
pub struct CsrRow<'a, T> {
|
|
lane: CsLane<'a, T>,
|
|
}
|
|
|
|
/// A mutable representation of a row in a CSR matrix.
|
|
///
|
|
/// Note that only explicitly stored entries can be mutated. The sparsity pattern belonging
|
|
/// to the row cannot be modified.
|
|
#[derive(Debug, PartialEq, Eq)]
|
|
pub struct CsrRowMut<'a, T> {
|
|
lane: CsLaneMut<'a, T>,
|
|
}
|
|
|
|
/// Implement the methods common to both CsrRow and CsrRowMut
|
|
macro_rules! impl_csr_row_common_methods {
|
|
($name:ty) => {
|
|
impl<'a, T> $name {
|
|
/// The number of global columns in the row.
|
|
#[inline]
|
|
#[must_use]
|
|
pub fn ncols(&self) -> usize {
|
|
self.lane.minor_dim()
|
|
}
|
|
|
|
/// The number of non-zeros in this row.
|
|
#[inline]
|
|
#[must_use]
|
|
pub fn nnz(&self) -> usize {
|
|
self.lane.nnz()
|
|
}
|
|
|
|
/// The column indices corresponding to explicitly stored entries in this row.
|
|
#[inline]
|
|
#[must_use]
|
|
pub fn col_indices(&self) -> &[usize] {
|
|
self.lane.minor_indices()
|
|
}
|
|
|
|
/// The values corresponding to explicitly stored entries in this row.
|
|
#[inline]
|
|
#[must_use]
|
|
pub fn values(&self) -> &[T] {
|
|
self.lane.values()
|
|
}
|
|
|
|
/// Returns an entry for the given global column index.
|
|
///
|
|
/// Each call to this function incurs the cost of a binary search among the explicitly
|
|
/// stored column entries.
|
|
#[inline]
|
|
#[must_use]
|
|
pub fn get_entry(&self, global_col_index: usize) -> Option<SparseEntry<'_, T>> {
|
|
self.lane.get_entry(global_col_index)
|
|
}
|
|
}
|
|
};
|
|
}
|
|
|
|
impl_csr_row_common_methods!(CsrRow<'a, T>);
|
|
impl_csr_row_common_methods!(CsrRowMut<'a, T>);
|
|
|
|
impl<'a, T> CsrRowMut<'a, T> {
|
|
/// Mutable access to the values corresponding to explicitly stored entries in this row.
|
|
#[inline]
|
|
pub fn values_mut(&mut self) -> &mut [T] {
|
|
self.lane.values_mut()
|
|
}
|
|
|
|
/// Provides simultaneous access to column indices and mutable values corresponding to the
|
|
/// explicitly stored entries in this row.
|
|
///
|
|
/// This method primarily facilitates low-level access for methods that process data stored
|
|
/// in CSR format directly.
|
|
#[inline]
|
|
pub fn cols_and_values_mut(&mut self) -> (&[usize], &mut [T]) {
|
|
self.lane.indices_and_values_mut()
|
|
}
|
|
|
|
/// Returns a mutable entry for the given global column index.
|
|
#[inline]
|
|
#[must_use]
|
|
pub fn get_entry_mut(&mut self, global_col_index: usize) -> Option<SparseEntryMut<'_, T>> {
|
|
self.lane.get_entry_mut(global_col_index)
|
|
}
|
|
}
|
|
|
|
/// Row iterator for [CsrMatrix](struct.CsrMatrix.html).
|
|
pub struct CsrRowIter<'a, T> {
|
|
lane_iter: CsLaneIter<'a, T>,
|
|
}
|
|
|
|
impl<'a, T> Iterator for CsrRowIter<'a, T> {
|
|
type Item = CsrRow<'a, T>;
|
|
|
|
fn next(&mut self) -> Option<Self::Item> {
|
|
self.lane_iter.next().map(|lane| CsrRow { lane })
|
|
}
|
|
}
|
|
|
|
/// Mutable row iterator for [CsrMatrix](struct.CsrMatrix.html).
|
|
pub struct CsrRowIterMut<'a, T> {
|
|
lane_iter: CsLaneIterMut<'a, T>,
|
|
}
|
|
|
|
impl<'a, T> Iterator for CsrRowIterMut<'a, T>
|
|
where
|
|
T: 'a,
|
|
{
|
|
type Item = CsrRowMut<'a, T>;
|
|
|
|
fn next(&mut self) -> Option<Self::Item> {
|
|
self.lane_iter.next().map(|lane| CsrRowMut { lane })
|
|
}
|
|
}
|