Remove Zero bound for transpose and impl SparsityPattern::transpose
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3b1303d1e0
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@ -107,7 +107,7 @@ impl<'a, T> From<&'a CscMatrix<T>> for DMatrix<T>
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impl<'a, T> From<&'a CscMatrix<T>> for CsrMatrix<T>
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where
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T: Scalar + Zero
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T: Scalar
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{
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fn from(matrix: &'a CscMatrix<T>) -> Self {
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convert_csc_csr(matrix)
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@ -116,7 +116,7 @@ impl<'a, T> From<&'a CscMatrix<T>> for CsrMatrix<T>
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impl<'a, T> From<&'a CsrMatrix<T>> for CscMatrix<T>
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where
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T: Scalar + Zero
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T: Scalar
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{
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fn from(matrix: &'a CsrMatrix<T>) -> Self {
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convert_csr_csc(matrix)
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@ -1,12 +1,15 @@
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//! TODO
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use crate::coo::CooMatrix;
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use crate::csr::CsrMatrix;
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use nalgebra::{DMatrix, Scalar, Matrix, Dim, ClosedAdd};
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use nalgebra::storage::Storage;
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use std::ops::Add;
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use num_traits::Zero;
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use std::ops::{Add};
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use nalgebra::{ClosedAdd, Dim, DMatrix, Matrix, Scalar};
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use nalgebra::storage::Storage;
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use crate::coo::CooMatrix;
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use crate::cs;
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use crate::csc::CscMatrix;
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use crate::csr::CsrMatrix;
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/// TODO
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pub fn convert_dense_coo<T, R, C, S>(dense: &Matrix<T, R, C, S>) -> CooMatrix<T>
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@ -192,13 +195,13 @@ pub fn convert_dense_csc<T, R, C, S>(dense: &Matrix<T, R, C, S>) -> CscMatrix<T>
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/// TODO
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pub fn convert_csr_csc<T>(csr: &CsrMatrix<T>) -> CscMatrix<T>
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where
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T: Scalar + Zero
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T: Scalar
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{
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let (offsets, indices, values) = transpose_cs(csr.nrows(),
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csr.ncols(),
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csr.row_offsets(),
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csr.col_indices(),
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csr.values());
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let (offsets, indices, values) = cs::transpose_cs(csr.nrows(),
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csr.ncols(),
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csr.row_offsets(),
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csr.col_indices(),
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csr.values());
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// TODO: Avoid data validity check?
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CscMatrix::try_from_csc_data(csr.nrows(), csr.ncols(), offsets, indices, values)
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@ -208,13 +211,13 @@ where
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/// TODO
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pub fn convert_csc_csr<T>(csc: &CscMatrix<T>) -> CsrMatrix<T>
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where
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T: Scalar + Zero
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T: Scalar
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{
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let (offsets, indices, values) = transpose_cs(csc.ncols(),
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csc.nrows(),
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csc.col_offsets(),
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csc.row_indices(),
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csc.values());
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let (offsets, indices, values) = cs::transpose_cs(csc.ncols(),
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csc.nrows(),
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csc.col_offsets(),
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csc.row_indices(),
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csc.values());
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// TODO: Avoid data validity check?
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CsrMatrix::try_from_csr_data(csc.nrows(), csc.ncols(), offsets, indices, values)
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@ -326,7 +329,7 @@ fn coo_to_unsorted_cs<T: Clone>(
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major_offsets[*major_idx] += 1;
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}
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convert_counts_to_offsets(major_offsets);
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cs::convert_counts_to_offsets(major_offsets);
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{
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// TODO: Instead of allocating a whole new vector storing the current counts,
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@ -377,66 +380,6 @@ fn sort_lane<T: Clone>(
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apply_permutation(values_result, values, permutation);
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}
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/// Transposes the compressed format.
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///
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/// This means that major and minor roles are switched. This is used for converting between CSR
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/// and CSC formats.
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fn transpose_cs<T>(major_dim: usize,
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minor_dim: usize,
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source_major_offsets: &[usize],
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source_minor_indices: &[usize],
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values: &[T])
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-> (Vec<usize>, Vec<usize>, Vec<T>)
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where
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T: Scalar + Zero
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{
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assert_eq!(source_major_offsets.len(), major_dim + 1);
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assert_eq!(source_minor_indices.len(), values.len());
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let nnz = values.len();
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// Count the number of occurences of each minor index
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let mut minor_counts = vec![0; minor_dim];
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for minor_idx in source_minor_indices {
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minor_counts[*minor_idx] += 1;
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}
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convert_counts_to_offsets(&mut minor_counts);
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let mut target_offsets = minor_counts;
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target_offsets.push(nnz);
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let mut target_indices = vec![usize::MAX; nnz];
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let mut target_values = vec![T::zero(); nnz];
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// Keep track of how many entries we have placed in each target major lane
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let mut current_target_major_counts = vec![0; minor_dim];
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for source_major_idx in 0 .. major_dim {
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let source_lane_begin = source_major_offsets[source_major_idx];
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let source_lane_end = source_major_offsets[source_major_idx + 1];
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let source_lane_indices = &source_minor_indices[source_lane_begin .. source_lane_end];
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let source_lane_values = &values[source_lane_begin .. source_lane_end];
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for (&source_minor_idx, val) in source_lane_indices.iter().zip(source_lane_values) {
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// Compute the offset in the target data for this particular source entry
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let target_lane_count = &mut current_target_major_counts[source_minor_idx];
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let entry_offset = target_offsets[source_minor_idx] + *target_lane_count;
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target_indices[entry_offset] = source_major_idx;
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target_values[entry_offset] = val.inlined_clone();
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*target_lane_count += 1;
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}
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}
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(target_offsets, target_indices, target_values)
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}
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fn convert_counts_to_offsets(counts: &mut [usize]) {
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// Convert the counts to an offset
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let mut offset = 0;
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for i_offset in counts.iter_mut() {
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let count = *i_offset;
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*i_offset = offset;
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offset += count;
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}
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}
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// TODO: Move this into `utils` or something?
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fn apply_permutation<T: Clone>(out_slice: &mut [T], in_slice: &[T], permutation: &[usize]) {
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assert_eq!(out_slice.len(), in_slice.len());
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@ -1,12 +1,14 @@
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use crate::pattern::SparsityPattern;
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use crate::{SparseEntry, SparseEntryMut};
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use std::sync::Arc;
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use std::ops::Range;
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use std::mem::replace;
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use std::ops::Range;
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use std::sync::Arc;
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use num_traits::One;
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use nalgebra::Scalar;
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use crate::{SparseEntry, SparseEntryMut};
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use crate::pattern::SparsityPattern;
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/// An abstract compressed matrix.
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///
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/// For the time being, this is only used internally to share implementation between
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@ -396,4 +398,101 @@ impl<'a, T> CsLaneMut<'a, T> {
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self.values,
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global_minor_index)
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}
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}
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}
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/// Helper struct for working with uninitialized data in vectors.
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/// TODO: This doesn't belong here.
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struct UninitVec<T> {
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vec: Vec<T>
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}
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impl<T> UninitVec<T> {
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pub fn from_len(len: usize) -> Self {
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Self {
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vec: Vec::with_capacity(len)
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}
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}
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/// Sets the element associated with the given index to the provided value.
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///
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/// Must be called exactly once per index, otherwise results in undefined behavior.
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pub unsafe fn set(&mut self, index: usize, value: T) {
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self.vec.as_mut_ptr().add(index).write(value)
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}
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/// Marks the vector data as initialized by returning a full vector.
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///
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/// It is undefined behavior to call this function unless *all* elements have been written to
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/// exactly once.
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pub unsafe fn assume_init(mut self) -> Vec<T> {
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self.vec.set_len(self.vec.capacity());
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self.vec
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}
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}
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/// Transposes the compressed format.
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///
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/// This means that major and minor roles are switched. This is used for converting between CSR
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/// and CSC formats.
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pub fn transpose_cs<T>(
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major_dim: usize,
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minor_dim: usize,
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source_major_offsets: &[usize],
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source_minor_indices: &[usize],
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values: &[T])
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-> (Vec<usize>, Vec<usize>, Vec<T>)
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where
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T: Scalar
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{
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assert_eq!(source_major_offsets.len(), major_dim + 1);
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assert_eq!(source_minor_indices.len(), values.len());
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let nnz = values.len();
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// Count the number of occurences of each minor index
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let mut minor_counts = vec![0; minor_dim];
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for minor_idx in source_minor_indices {
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minor_counts[*minor_idx] += 1;
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}
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convert_counts_to_offsets(&mut minor_counts);
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let mut target_offsets = minor_counts;
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target_offsets.push(nnz);
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let mut target_indices = vec![usize::MAX; nnz];
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// We have to use uninitialized storage, because we don't have any kind of "default" value
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// available for `T`. Unfortunately this necessitates some small amount of unsafe code
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let mut target_values = UninitVec::from_len(nnz);
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// Keep track of how many entries we have placed in each target major lane
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let mut current_target_major_counts = vec![0; minor_dim];
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for source_major_idx in 0 .. major_dim {
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let source_lane_begin = source_major_offsets[source_major_idx];
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let source_lane_end = source_major_offsets[source_major_idx + 1];
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let source_lane_indices = &source_minor_indices[source_lane_begin .. source_lane_end];
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let source_lane_values = &values[source_lane_begin .. source_lane_end];
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for (&source_minor_idx, val) in source_lane_indices.iter().zip(source_lane_values) {
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// Compute the offset in the target data for this particular source entry
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let target_lane_count = &mut current_target_major_counts[source_minor_idx];
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let entry_offset = target_offsets[source_minor_idx] + *target_lane_count;
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target_indices[entry_offset] = source_major_idx;
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unsafe { target_values.set(entry_offset, val.inlined_clone()); }
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*target_lane_count += 1;
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}
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}
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// At this point, we should have written to each element in target_values exactly once,
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// so initialization should be sound
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let target_values = unsafe { target_values.assume_init() };
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(target_offsets, target_indices, target_values)
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}
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pub fn convert_counts_to_offsets(counts: &mut [usize]) {
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// Convert the counts to an offset
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let mut offset = 0;
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for i_offset in counts.iter_mut() {
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let count = *i_offset;
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*i_offset = offset;
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offset += count;
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}
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}
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@ -7,7 +7,7 @@ use crate::cs::{CsMatrix, CsLane, CsLaneMut, CsLaneIter, CsLaneIterMut};
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use std::sync::Arc;
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use std::slice::{IterMut, Iter};
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use num_traits::{Zero, One};
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use num_traits::{One};
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use nalgebra::Scalar;
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/// A CSC representation of a sparse matrix.
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@ -368,7 +368,7 @@ impl<T> CscMatrix<T> {
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impl<T> CscMatrix<T>
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where
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T: Scalar + Zero
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T: Scalar
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{
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/// Compute the transpose of the matrix.
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pub fn transpose(&self) -> CscMatrix<T> {
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@ -5,7 +5,7 @@ use crate::csc::CscMatrix;
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use crate::cs::{CsMatrix, CsLaneIterMut, CsLaneIter, CsLane, CsLaneMut};
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use nalgebra::Scalar;
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use num_traits::{Zero, One};
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use num_traits::{One};
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use std::sync::Arc;
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use std::slice::{IterMut, Iter};
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@ -368,7 +368,7 @@ impl<T> CsrMatrix<T> {
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impl<T> CsrMatrix<T>
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where
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T: Scalar + Zero
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T: Scalar
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{
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/// Compute the transpose of the matrix.
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pub fn transpose(&self) -> CsrMatrix<T> {
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@ -2,6 +2,7 @@
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use crate::SparseFormatError;
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use std::fmt;
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use std::error::Error;
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use crate::cs::transpose_cs;
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/// A representation of the sparsity pattern of a CSR or CSC matrix.
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///
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@ -204,6 +205,24 @@ impl SparsityPattern {
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pub fn disassemble(self) -> (Vec<usize>, Vec<usize>) {
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(self.major_offsets, self.minor_indices)
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}
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/// TODO
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pub fn transpose(&self) -> Self {
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// By using unit () values, we can use the same routines as for CSR/CSC matrices
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let values = vec![(); self.nnz()];
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let (new_offsets, new_indices, _) = transpose_cs(
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self.major_dim(),
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self.minor_dim(),
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self.major_offsets(),
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self.minor_indices(),
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&values);
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// TODO: Skip checks
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Self::try_from_offsets_and_indices(self.minor_dim(),
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self.major_dim(),
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new_offsets,
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new_indices)
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.expect("Internal error: Transpose should never fail.")
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}
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}
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/// Error type for `SparsityPattern` format errors.
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