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Fix nalgebra-sparse.

This commit is contained in:
Sébastien Crozet 2021-08-04 18:20:55 +02:00
parent 148b164aaa
commit 0b9a1acea5
2 changed files with 17 additions and 16 deletions
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17
nalgebra-sparse/src/factorization/cholesky.rs
View File

@ -3,7 +3,7 @@ use crate::ops::serial::spsolve_csc_lower_triangular;
use crate::ops::Op; use crate::ops::Op;
use crate::pattern::SparsityPattern; use crate::pattern::SparsityPattern;
use core::{iter, mem}; use core::{iter, mem};
use nalgebra::{DMatrix, DMatrixSlice, DMatrixSliceMut, RealField, Scalar}; use nalgebra::{DMatrix, DMatrixSlice, DMatrixSliceMut, RealField};
use std::fmt::{Display, Formatter}; use std::fmt::{Display, Formatter};
/// A symbolic sparse Cholesky factorization of a CSC matrix. /// A symbolic sparse Cholesky factorization of a CSC matrix.
@ -209,15 +209,16 @@ impl<T: RealField> CscCholesky<T> {
let irow = *self.m_pattern.minor_indices().get_unchecked(p); let irow = *self.m_pattern.minor_indices().get_unchecked(p);
if irow >= k { if irow >= k {
*self.work_x.get_unchecked_mut(irow) = *values.get_unchecked(p); *self.work_x.get_unchecked_mut(irow) = values.get_unchecked(p).clone();
} }
} }
for &j in self.u_pattern.lane(k) { for &j in self.u_pattern.lane(k) {
let factor = -*self let factor = -self
.l_factor .l_factor
.values() .values()
.get_unchecked(*self.work_c.get_unchecked(j)); .get_unchecked(*self.work_c.get_unchecked(j))
.clone();
*self.work_c.get_unchecked_mut(j) += 1; *self.work_c.get_unchecked_mut(j) += 1;
if j < k { if j < k {
@ -225,27 +226,27 @@ impl<T: RealField> CscCholesky<T> {
let col_j_entries = col_j.row_indices().iter().zip(col_j.values()); let col_j_entries = col_j.row_indices().iter().zip(col_j.values());
for (&z, val) in col_j_entries { for (&z, val) in col_j_entries {
if z >= k { if z >= k {
*self.work_x.get_unchecked_mut(z) += val.clone() * factor; *self.work_x.get_unchecked_mut(z) += val.clone() * factor.clone();
} }
} }
} }
} }
let diag = *self.work_x.get_unchecked(k); let diag = self.work_x.get_unchecked(k).clone();
if diag > T::zero() { if diag > T::zero() {
let denom = diag.sqrt(); let denom = diag.sqrt();
{ {
let (offsets, _, values) = self.l_factor.csc_data_mut(); let (offsets, _, values) = self.l_factor.csc_data_mut();
*values.get_unchecked_mut(*offsets.get_unchecked(k)) = denom; *values.get_unchecked_mut(*offsets.get_unchecked(k)) = denom.clone();
} }
let mut col_k = self.l_factor.col_mut(k); let mut col_k = self.l_factor.col_mut(k);
let (col_k_rows, col_k_values) = col_k.rows_and_values_mut(); let (col_k_rows, col_k_values) = col_k.rows_and_values_mut();
let col_k_entries = col_k_rows.iter().zip(col_k_values); let col_k_entries = col_k_rows.iter().zip(col_k_values);
for (&p, val) in col_k_entries { for (&p, val) in col_k_entries {
*val = *self.work_x.get_unchecked(p) / denom; *val = self.work_x.get_unchecked(p).clone() / denom.clone();
*self.work_x.get_unchecked_mut(p) = T::zero(); *self.work_x.get_unchecked_mut(p) = T::zero();
} }
} else { } else {

16
nalgebra-sparse/src/ops/serial/csc.rs
View File

@ -165,13 +165,13 @@ fn spsolve_csc_lower_triangular_no_transpose<T: RealField>(
// a severe penalty) // a severe penalty)
let diag_csc_index = l_col_k.row_indices().iter().position(|&i| i == k); let diag_csc_index = l_col_k.row_indices().iter().position(|&i| i == k);
if let Some(diag_csc_index) = diag_csc_index { if let Some(diag_csc_index) = diag_csc_index {
let l_kk = l_col_k.values()[diag_csc_index]; let l_kk = l_col_k.values()[diag_csc_index].clone();
if l_kk != T::zero() { if l_kk != T::zero() {
// Update entry associated with diagonal // Update entry associated with diagonal
x_col_j[k] /= l_kk; x_col_j[k] /= l_kk;
// Copy value after updating (so we don't run into the borrow checker) // Copy value after updating (so we don't run into the borrow checker)
let x_kj = x_col_j[k]; let x_kj = x_col_j[k].clone();
let row_indices = &l_col_k.row_indices()[(diag_csc_index + 1)..]; let row_indices = &l_col_k.row_indices()[(diag_csc_index + 1)..];
let l_values = &l_col_k.values()[(diag_csc_index + 1)..]; let l_values = &l_col_k.values()[(diag_csc_index + 1)..];
@ -179,7 +179,7 @@ fn spsolve_csc_lower_triangular_no_transpose<T: RealField>(
// Note: The remaining entries are below the diagonal // Note: The remaining entries are below the diagonal
for (&i, l_ik) in row_indices.iter().zip(l_values) { for (&i, l_ik) in row_indices.iter().zip(l_values) {
let x_ij = &mut x_col_j[i]; let x_ij = &mut x_col_j[i];
*x_ij -= l_ik.clone() * x_kj; *x_ij -= l_ik.clone() * x_kj.clone();
} }
x_col_j[k] = x_kj; x_col_j[k] = x_kj;
@ -223,22 +223,22 @@ fn spsolve_csc_lower_triangular_transpose<T: RealField>(
// TODO: Can use exponential search here to quickly skip entries // TODO: Can use exponential search here to quickly skip entries
let diag_csc_index = l_col_i.row_indices().iter().position(|&k| i == k); let diag_csc_index = l_col_i.row_indices().iter().position(|&k| i == k);
if let Some(diag_csc_index) = diag_csc_index { if let Some(diag_csc_index) = diag_csc_index {
let l_ii = l_col_i.values()[diag_csc_index]; let l_ii = l_col_i.values()[diag_csc_index].clone();
if l_ii != T::zero() { if l_ii != T::zero() {
// // Update entry associated with diagonal // // Update entry associated with diagonal
// x_col_j[k] /= a_kk; // x_col_j[k] /= a_kk;
// Copy value after updating (so we don't run into the borrow checker) // Copy value after updating (so we don't run into the borrow checker)
let mut x_ii = x_col_j[i]; let mut x_ii = x_col_j[i].clone();
let row_indices = &l_col_i.row_indices()[(diag_csc_index + 1)..]; let row_indices = &l_col_i.row_indices()[(diag_csc_index + 1)..];
let a_values = &l_col_i.values()[(diag_csc_index + 1)..]; let a_values = &l_col_i.values()[(diag_csc_index + 1)..];
// Note: The remaining entries are below the diagonal // Note: The remaining entries are below the diagonal
for (&k, &l_ki) in row_indices.iter().zip(a_values) { for (k, l_ki) in row_indices.iter().zip(a_values) {
let x_kj = x_col_j[k]; let x_kj = x_col_j[*k].clone();
x_ii -= l_ki * x_kj; x_ii -= l_ki.clone() * x_kj;
} }
x_col_j[i] = x_ii / l_ii; x_col_j[i] = x_ii / l_ii;