Merge branch 'dev' of https://github.com/dimforge/nalgebra into dev

nalgebra-sparse/src/convert/serial.rs

@@ -14,6 +14,7 @@ use crate::coo::CooMatrix;
 use crate::cs;
 use crate::csc::CscMatrix;
 use crate::csr::CsrMatrix;
+use crate::utils::{apply_permutation, compute_sort_permutation};
 
 /// Converts a dense matrix to [`CooMatrix`].
 pub fn convert_dense_coo<T, R, C, S>(dense: &Matrix<T, R, C, S>) -> CooMatrix<T>
@@ -376,29 +377,12 @@ fn sort_lane<T: Clone>(
     assert_eq!(values.len(), workspace.len());
 
     let permutation = workspace;
-    // Set permutation to identity
+    compute_sort_permutation(permutation, minor_idx);
-    for (i, p) in permutation.iter_mut().enumerate() {
-        *p = i;
-    }
-
-    // Compute permutation needed to bring minor indices into sorted order
-    // Note: Using sort_unstable here avoids internal allocations, which is crucial since
-    // each lane might have a small number of elements
-    permutation.sort_unstable_by_key(|idx| minor_idx[*idx]);
 
     apply_permutation(minor_idx_result, minor_idx, permutation);
     apply_permutation(values_result, values, permutation);
 }
 
-// TODO: Move this into `utils` or something?
-fn apply_permutation<T: Clone>(out_slice: &mut [T], in_slice: &[T], permutation: &[usize]) {
-    assert_eq!(out_slice.len(), in_slice.len());
-    assert_eq!(out_slice.len(), permutation.len());
-    for (out_element, old_pos) in out_slice.iter_mut().zip(permutation) {
-        *out_element = in_slice[*old_pos].clone();
-    }
-}
-
 /// Given *sorted* indices and corresponding scalar values, combines duplicates with the given
 /// associative combiner and calls the provided produce methods with combined indices and values.
 fn combine_duplicates<T: Clone>(

nalgebra-sparse/src/cs.rs

@@ -6,7 +6,8 @@ use num_traits::One;
 use nalgebra::Scalar;
 
 use crate::pattern::SparsityPattern;
-use crate::{SparseEntry, SparseEntryMut};
+use crate::utils::{apply_permutation, compute_sort_permutation};
+use crate::{SparseEntry, SparseEntryMut, SparseFormatError, SparseFormatErrorKind};
 
 /// An abstract compressed matrix.
 ///
@@ -543,3 +544,151 @@ pub fn convert_counts_to_offsets(counts: &mut [usize]) {
         offset += count;
     }
 }
+
+/// Validates cs data, optionally sorts minor indices and values
+pub(crate) fn validate_and_optionally_sort_cs_data<T>(
+    major_dim: usize,
+    minor_dim: usize,
+    major_offsets: &[usize],
+    minor_indices: &mut [usize],
+    values: Option<&mut [T]>,
+    sort: bool,
+) -> Result<(), SparseFormatError>
+where
+    T: Scalar,
+{
+    let mut values_option = values;
+
+    if let Some(values) = values_option.as_mut() {
+        if minor_indices.len() != values.len() {
+            return Err(SparseFormatError::from_kind_and_msg(
+                SparseFormatErrorKind::InvalidStructure,
+                "Number of values and minor indices must be the same.",
+            ));
+        }
+    } else if sort {
+        unreachable!("Internal error: Sorting currently not supported if no values are present.");
+    }
+    if major_offsets.len() == 0 {
+        return Err(SparseFormatError::from_kind_and_msg(
+            SparseFormatErrorKind::InvalidStructure,
+            "Number of offsets should be greater than 0.",
+        ));
+    }
+    if major_offsets.len() != major_dim + 1 {
+        return Err(SparseFormatError::from_kind_and_msg(
+            SparseFormatErrorKind::InvalidStructure,
+            "Length of offset array is not equal to (major_dim + 1).",
+        ));
+    }
+
+    // Check that the first and last offsets conform to the specification
+    {
+        let first_offset_ok = *major_offsets.first().unwrap() == 0;
+        let last_offset_ok = *major_offsets.last().unwrap() == minor_indices.len();
+        if !first_offset_ok || !last_offset_ok {
+            return Err(SparseFormatError::from_kind_and_msg(
+                SparseFormatErrorKind::InvalidStructure,
+                "First or last offset is incompatible with format.",
+            ));
+        }
+    }
+
+    // Set up required buffers up front
+    let mut minor_idx_buffer: Vec<usize> = Vec::new();
+    let mut values_buffer: Vec<T> = Vec::new();
+    let mut minor_index_permutation: Vec<usize> = Vec::new();
+
+    // Test that each lane has strictly monotonically increasing minor indices, i.e.
+    // minor indices within a lane are sorted, unique. Sort minor indices within a lane if needed.
+    // In addition, each minor index must be in bounds with respect to the minor dimension.
+    {
+        for lane_idx in 0..major_dim {
+            let range_start = major_offsets[lane_idx];
+            let range_end = major_offsets[lane_idx + 1];
+
+            // Test that major offsets are monotonically increasing
+            if range_start > range_end {
+                return Err(SparseFormatError::from_kind_and_msg(
+                    SparseFormatErrorKind::InvalidStructure,
+                    "Offsets are not monotonically increasing.",
+                ));
+            }
+
+            let minor_idx_in_lane = minor_indices.get(range_start..range_end).ok_or(
+                SparseFormatError::from_kind_and_msg(
+                    SparseFormatErrorKind::IndexOutOfBounds,
+                    "A major offset is out of bounds.",
+                ),
+            )?;
+
+            // We test for in-bounds, uniqueness and monotonicity at the same time
+            // to ensure that we only visit each minor index once
+            let mut prev = None;
+            let mut monotonic = true;
+
+            for &minor_idx in minor_idx_in_lane {
+                if minor_idx >= minor_dim {
+                    return Err(SparseFormatError::from_kind_and_msg(
+                        SparseFormatErrorKind::IndexOutOfBounds,
+                        "A minor index is out of bounds.",
+                    ));
+                }
+
+                if let Some(prev) = prev {
+                    if prev >= minor_idx {
+                        if !sort {
+                            return Err(SparseFormatError::from_kind_and_msg(
+                                SparseFormatErrorKind::InvalidStructure,
+                                "Minor indices are not strictly monotonically increasing in each lane.",
+                            ));
+                        }
+                        monotonic = false;
+                    }
+                }
+                prev = Some(minor_idx);
+            }
+
+            // sort if indices are not monotonic and sorting is expected
+            if !monotonic && sort {
+                let range_size = range_end - range_start;
+                minor_index_permutation.resize(range_size, 0);
+                compute_sort_permutation(&mut minor_index_permutation, &minor_idx_in_lane);
+                minor_idx_buffer.clear();
+                minor_idx_buffer.extend_from_slice(&minor_idx_in_lane);
+                apply_permutation(
+                    &mut minor_indices[range_start..range_end],
+                    &minor_idx_buffer,
+                    &minor_index_permutation,
+                );
+
+                // check duplicates
+                prev = None;
+                for &minor_idx in &minor_indices[range_start..range_end] {
+                    if let Some(prev) = prev {
+                        if prev == minor_idx {
+                            return Err(SparseFormatError::from_kind_and_msg(
+                                SparseFormatErrorKind::DuplicateEntry,
+                                "Input data contains duplicate entries.",
+                            ));
+                        }
+                    }
+                    prev = Some(minor_idx);
+                }
+
+                // sort values if they exist
+                if let Some(values) = values_option.as_mut() {
+                    values_buffer.clear();
+                    values_buffer.extend_from_slice(&values[range_start..range_end]);
+                    apply_permutation(
+                        &mut values[range_start..range_end],
+                        &values_buffer,
+                        &minor_index_permutation,
+                    );
+                }
+            }
+        }
+    }
+
+    Ok(())
+}

nalgebra-sparse/src/csc.rs

@@ -6,6 +6,7 @@
 #[cfg(feature = "serde-serialize")]
 mod csc_serde;
 
+use crate::cs;
 use crate::cs::{CsLane, CsLaneIter, CsLaneIterMut, CsLaneMut, CsMatrix};
 use crate::csr::CsrMatrix;
 use crate::pattern::{SparsityPattern, SparsityPatternFormatError, SparsityPatternIter};
@@ -173,6 +174,50 @@ impl<T> CscMatrix<T> {
         Self::try_from_pattern_and_values(pattern, values)
     }
 
+    /// Try to construct a CSC matrix from raw CSC data with unsorted row indices.
+    ///
+    /// It is assumed that each column contains unique row indices that are in
+    /// bounds with respect to the number of rows 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 CSC storage format
+    /// with the exception of having unsorted row indices and values.
+    /// See the documentation for [CscMatrix](struct.CscMatrix.html) for more information.
+    pub fn try_from_unsorted_csc_data(
+        num_rows: usize,
+        num_cols: usize,
+        col_offsets: Vec<usize>,
+        mut row_indices: Vec<usize>,
+        mut values: Vec<T>,
+    ) -> Result<Self, SparseFormatError>
+    where
+        T: Scalar,
+    {
+        let result = cs::validate_and_optionally_sort_cs_data(
+            num_cols,
+            num_rows,
+            &col_offsets,
+            &mut row_indices,
+            Some(&mut values),
+            true,
+        );
+
+        match result {
+            Ok(()) => {
+                let pattern = unsafe {
+                    SparsityPattern::from_offset_and_indices_unchecked(
+                        num_cols,
+                        num_rows,
+                        col_offsets,
+                        row_indices,
+                    )
+                };
+                Self::try_from_pattern_and_values(pattern, values)
+            }
+            Err(err) => Err(err),
+        }
+    }
+
     /// Try to construct a CSC 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

nalgebra-sparse/src/csr.rs

@@ -6,6 +6,7 @@
 #[cfg(feature = "serde-serialize")]
 mod csr_serde;
 
+use crate::cs;
 use crate::cs::{CsLane, CsLaneIter, CsLaneIterMut, CsLaneMut, CsMatrix};
 use crate::csc::CscMatrix;
 use crate::pattern::{SparsityPattern, SparsityPatternFormatError, SparsityPatternIter};
@@ -13,7 +14,7 @@ use crate::{SparseEntry, SparseEntryMut, SparseFormatError, SparseFormatErrorKin
 
 use nalgebra::Scalar;
 use num_traits::One;
-use std::iter::FromIterator;
+
 use std::slice::{Iter, IterMut};
 
 /// A CSR representation of a sparse matrix.
@@ -187,62 +188,35 @@ impl<T> CsrMatrix<T> {
         num_rows: usize,
         num_cols: usize,
         row_offsets: Vec<usize>,
-        col_indices: Vec<usize>,
+        mut col_indices: Vec<usize>,
-        values: Vec<T>,
+        mut values: Vec<T>,
     ) -> Result<Self, SparseFormatError>
     where
         T: Scalar,
     {
-        use SparsityPatternFormatError::*;
+        let result = cs::validate_and_optionally_sort_cs_data(
-        let count = col_indices.len();
+            num_rows,
-        let mut p: Vec<usize> = (0..count).collect();
+            num_cols,
+            &row_offsets,
+            &mut col_indices,
+            Some(&mut values),
+            true,
+        );
 
-        if col_indices.len() != values.len() {
+        match result {
-            return Err(SparseFormatError::from_kind_and_msg(
+            Ok(()) => {
-                SparseFormatErrorKind::InvalidStructure,
+                let pattern = unsafe {
-                "Number of values and column indices must be the same",
+                    SparsityPattern::from_offset_and_indices_unchecked(
-            ));
-        }
-
-        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> =
-            Vec::from_iter((p.iter().map(|i| &col_indices[*i])).cloned());
-
-        // permute values
-        let sorted_values: Vec<T> = Vec::from_iter((p.iter().map(|i| &values[*i])).cloned());
-
-        return Self::try_from_csr_data(
                         num_rows,
                         num_cols,
                         row_offsets,
-            sorted_col_indices,
+                        col_indices,
-            sorted_values,
+                    )
-        );
+                };
+                Self::try_from_pattern_and_values(pattern, values)
+            }
+            Err(err) => Err(err),
+        }
     }
 
     /// Try to construct a CSR matrix from a sparsity pattern and associated non-zero values.

nalgebra-sparse/src/lib.rs

@@ -160,6 +160,7 @@ pub mod ops;
 pub mod pattern;
 
 pub(crate) mod cs;
+pub(crate) mod utils;
 
 #[cfg(feature = "proptest-support")]
 pub mod proptest;

nalgebra-sparse/src/pattern.rs

@@ -188,6 +188,35 @@ impl SparsityPattern {
         })
     }
 
+    /// Try to construct a sparsity pattern from the given dimensions, major offsets
+    /// and minor indices.
+    ///
+    /// # Panics
+    ///
+    /// Panics if the number of major offsets is not exactly one greater than the major dimension
+    /// or if major offsets do not start with 0 and end with the number of minor indices.
+    pub unsafe fn from_offset_and_indices_unchecked(
+        major_dim: usize,
+        minor_dim: usize,
+        major_offsets: Vec<usize>,
+        minor_indices: Vec<usize>,
+    ) -> Self {
+        assert_eq!(major_offsets.len(), major_dim + 1);
+
+        // Check that the first and last offsets conform to the specification
+        {
+            let first_offset_ok = *major_offsets.first().unwrap() == 0;
+            let last_offset_ok = *major_offsets.last().unwrap() == minor_indices.len();
+            assert!(first_offset_ok && last_offset_ok);
+        }
+
+        Self {
+            major_offsets,
+            minor_indices,
+            minor_dim,
+        }
+    }
+
     /// An iterator over the explicitly stored "non-zero" entries (i, j).
     ///
     /// The iteration happens in a lane-major fashion, meaning that the lane index i

nalgebra-sparse/src/utils.rs

@@ -0,0 +1,26 @@
+//! Helper functions for sparse matrix computations
+
+/// permutes entries of in_slice according to permutation slice and puts them to out_slice
+#[inline]
+pub fn apply_permutation<T: Clone>(out_slice: &mut [T], in_slice: &[T], permutation: &[usize]) {
+    assert_eq!(out_slice.len(), in_slice.len());
+    assert_eq!(out_slice.len(), permutation.len());
+    for (out_element, old_pos) in out_slice.iter_mut().zip(permutation) {
+        *out_element = in_slice[*old_pos].clone();
+    }
+}
+
+/// computes permutation by using provided indices as keys
+#[inline]
+pub fn compute_sort_permutation(permutation: &mut [usize], indices: &[usize]) {
+    assert_eq!(permutation.len(), indices.len());
+    // Set permutation to identity
+    for (i, p) in permutation.iter_mut().enumerate() {
+        *p = i;
+    }
+
+    // Compute permutation needed to bring minor indices into sorted order
+    // Note: Using sort_unstable here avoids internal allocations, which is crucial since
+    // each lane might have a small number of elements
+    permutation.sort_unstable_by_key(|idx| indices[*idx]);
+}

nalgebra-sparse/tests/unit_tests/csc.rs

@@ -5,6 +5,8 @@ use nalgebra_sparse::{SparseEntry, SparseEntryMut, SparseFormatErrorKind};
 use proptest::prelude::*;
 use proptest::sample::subsequence;
 
+use super::test_data_examples::{InvalidCsDataExamples, ValidCsDataExamples};
+
 use crate::assert_panics;
 use crate::common::csc_strategy;
 
@@ -171,11 +173,26 @@ fn csc_matrix_valid_data() {
     }
 }
 
+#[test]
+fn csc_matrix_valid_data_unsorted_column_indices() {
+    let valid_data: ValidCsDataExamples = ValidCsDataExamples::new();
+
+    let (offsets, indices, values) = valid_data.valid_unsorted_cs_data;
+    let csc = CscMatrix::try_from_unsorted_csc_data(5, 4, offsets, indices, values).unwrap();
+
+    let (offsets2, indices2, values2) = valid_data.valid_cs_data;
+    let expected_csc = CscMatrix::try_from_csc_data(5, 4, offsets2, indices2, values2).unwrap();
+
+    assert_eq!(csc, expected_csc);
+}
+
 #[test]
 fn csc_matrix_try_from_invalid_csc_data() {
+    let invalid_data: InvalidCsDataExamples = InvalidCsDataExamples::new();
     {
         // Empty offset array (invalid length)
-        let matrix = CscMatrix::try_from_csc_data(0, 0, Vec::new(), Vec::new(), Vec::<u32>::new());
+        let (offsets, indices, values) = invalid_data.empty_offset_array;
+        let matrix = CscMatrix::try_from_csc_data(0, 0, offsets, indices, values);
         assert_eq!(
             matrix.unwrap_err().kind(),
             &SparseFormatErrorKind::InvalidStructure
@@ -184,10 +201,8 @@ fn csc_matrix_try_from_invalid_csc_data() {
 
     {
         // Offset array invalid length for arbitrary data
-        let offsets = vec![0, 3, 5];
+        let (offsets, indices, values) =
-        let indices = vec![0, 1, 2, 3, 5];
+            invalid_data.offset_array_invalid_length_for_arbitrary_data;
-        let values = vec![0, 1, 2, 3, 4];
-
         let matrix = CscMatrix::try_from_csc_data(6, 3, offsets, indices, values);
         assert_eq!(
             matrix.unwrap_err().kind(),
@@ -197,9 +212,7 @@ fn csc_matrix_try_from_invalid_csc_data() {
 
     {
         // Invalid first entry in offsets array
-        let offsets = vec![1, 2, 2, 5];
+        let (offsets, indices, values) = invalid_data.invalid_first_entry_in_offsets_array;
-        let indices = vec![0, 5, 1, 2, 3];
-        let values = vec![0, 1, 2, 3, 4];
         let matrix = CscMatrix::try_from_csc_data(6, 3, offsets, indices, values);
         assert_eq!(
             matrix.unwrap_err().kind(),
@@ -209,9 +222,7 @@ fn csc_matrix_try_from_invalid_csc_data() {
 
     {
         // Invalid last entry in offsets array
-        let offsets = vec![0, 2, 2, 4];
+        let (offsets, indices, values) = invalid_data.invalid_last_entry_in_offsets_array;
-        let indices = vec![0, 5, 1, 2, 3];
-        let values = vec![0, 1, 2, 3, 4];
         let matrix = CscMatrix::try_from_csc_data(6, 3, offsets, indices, values);
         assert_eq!(
             matrix.unwrap_err().kind(),
@@ -221,9 +232,7 @@ fn csc_matrix_try_from_invalid_csc_data() {
 
     {
         // Invalid length of offsets array
-        let offsets = vec![0, 2, 2];
+        let (offsets, indices, values) = invalid_data.invalid_length_of_offsets_array;
-        let indices = vec![0, 5, 1, 2, 3];
-        let values = vec![0, 1, 2, 3, 4];
         let matrix = CscMatrix::try_from_csc_data(6, 3, offsets, indices, values);
         assert_eq!(
             matrix.unwrap_err().kind(),
@@ -233,9 +242,7 @@ fn csc_matrix_try_from_invalid_csc_data() {
 
     {
         // Nonmonotonic offsets
-        let offsets = vec![0, 3, 2, 5];
+        let (offsets, indices, values) = invalid_data.nonmonotonic_offsets;
-        let indices = vec![0, 1, 2, 3, 4];
-        let values = vec![0, 1, 2, 3, 4];
         let matrix = CscMatrix::try_from_csc_data(6, 3, offsets, indices, values);
         assert_eq!(
             matrix.unwrap_err().kind(),
@@ -257,9 +264,7 @@ fn csc_matrix_try_from_invalid_csc_data() {
 
     {
         // Minor index out of bounds
-        let offsets = vec![0, 2, 2, 5];
+        let (offsets, indices, values) = invalid_data.minor_index_out_of_bounds;
-        let indices = vec![0, 6, 1, 2, 3];
-        let values = vec![0, 1, 2, 3, 4];
         let matrix = CscMatrix::try_from_csc_data(6, 3, offsets, indices, values);
         assert_eq!(
             matrix.unwrap_err().kind(),
@@ -269,9 +274,7 @@ fn csc_matrix_try_from_invalid_csc_data() {
 
     {
         // Duplicate entry
-        let offsets = vec![0, 2, 2, 5];
+        let (offsets, indices, values) = invalid_data.duplicate_entry;
-        let indices = vec![0, 5, 2, 2, 3];
-        let values = vec![0, 1, 2, 3, 4];
         let matrix = CscMatrix::try_from_csc_data(6, 3, offsets, indices, values);
         assert_eq!(
             matrix.unwrap_err().kind(),
@@ -280,6 +283,121 @@ fn csc_matrix_try_from_invalid_csc_data() {
     }
 }
 
+#[test]
+fn csc_matrix_try_from_unsorted_invalid_csc_data() {
+    let invalid_data: InvalidCsDataExamples = InvalidCsDataExamples::new();
+    {
+        // Empty offset array (invalid length)
+        let (offsets, indices, values) = invalid_data.empty_offset_array;
+        let matrix = CscMatrix::try_from_unsorted_csc_data(0, 0, offsets, indices, values);
+        assert_eq!(
+            matrix.unwrap_err().kind(),
+            &SparseFormatErrorKind::InvalidStructure
+        );
+    }
+
+    {
+        // Offset array invalid length for arbitrary data
+        let (offsets, indices, values) =
+            invalid_data.offset_array_invalid_length_for_arbitrary_data;
+        let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
+        assert_eq!(
+            matrix.unwrap_err().kind(),
+            &SparseFormatErrorKind::InvalidStructure
+        );
+    }
+
+    {
+        // Invalid first entry in offsets array
+        let (offsets, indices, values) = invalid_data.invalid_first_entry_in_offsets_array;
+        let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
+        assert_eq!(
+            matrix.unwrap_err().kind(),
+            &SparseFormatErrorKind::InvalidStructure
+        );
+    }
+
+    {
+        // Invalid last entry in offsets array
+        let (offsets, indices, values) = invalid_data.invalid_last_entry_in_offsets_array;
+        let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
+        assert_eq!(
+            matrix.unwrap_err().kind(),
+            &SparseFormatErrorKind::InvalidStructure
+        );
+    }
+
+    {
+        // Invalid length of offsets array
+        let (offsets, indices, values) = invalid_data.invalid_length_of_offsets_array;
+        let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
+        assert_eq!(
+            matrix.unwrap_err().kind(),
+            &SparseFormatErrorKind::InvalidStructure
+        );
+    }
+
+    {
+        // Nonmonotonic offsets
+        let (offsets, indices, values) = invalid_data.nonmonotonic_offsets;
+        let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
+        assert_eq!(
+            matrix.unwrap_err().kind(),
+            &SparseFormatErrorKind::InvalidStructure
+        );
+    }
+
+    {
+        // Major offset out of bounds
+        let (offsets, indices, values) = invalid_data.major_offset_out_of_bounds;
+        let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
+        assert_eq!(
+            matrix.unwrap_err().kind(),
+            &SparseFormatErrorKind::IndexOutOfBounds
+        );
+    }
+
+    {
+        // Minor index out of bounds
+        let (offsets, indices, values) = invalid_data.minor_index_out_of_bounds;
+        let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
+        assert_eq!(
+            matrix.unwrap_err().kind(),
+            &SparseFormatErrorKind::IndexOutOfBounds
+        );
+    }
+
+    {
+        // Duplicate entry
+        let (offsets, indices, values) = invalid_data.duplicate_entry;
+        let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
+        assert_eq!(
+            matrix.unwrap_err().kind(),
+            &SparseFormatErrorKind::DuplicateEntry
+        );
+    }
+
+    {
+        // Duplicate entry in unsorted lane
+        let (offsets, indices, values) = invalid_data.duplicate_entry_unsorted;
+        let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
+        assert_eq!(
+            matrix.unwrap_err().kind(),
+            &SparseFormatErrorKind::DuplicateEntry
+        );
+    }
+
+    {
+        // Wrong values length
+        let (offsets, indices, values) = invalid_data.wrong_values_length;
+        let matrix = CscMatrix::try_from_unsorted_csc_data(6, 3, offsets, indices, values);
+        assert_eq!(
+            matrix.unwrap_err().kind(),
+            &SparseFormatErrorKind::InvalidStructure
+        );
+    }
+}
+
 #[test]
 fn csc_disassemble_avoids_clone_when_owned() {
     // Test that disassemble avoids cloning the sparsity pattern when it holds the sole reference

nalgebra-sparse/tests/unit_tests/csr.rs

@@ -5,7 +5,7 @@ use nalgebra_sparse::{SparseEntry, SparseEntryMut, SparseFormatErrorKind};
 use proptest::prelude::*;
 use proptest::sample::subsequence;
 
-use super::test_data_examples::InvalidCsrDataExamples;
+use super::test_data_examples::{InvalidCsDataExamples, ValidCsDataExamples};
 
 use crate::assert_panics;
 use crate::common::csr_strategy;
@@ -175,30 +175,20 @@ fn csr_matrix_valid_data() {
 
 #[test]
 fn csr_matrix_valid_data_unsorted_column_indices() {
-    let csr = CsrMatrix::try_from_unsorted_csr_data(
+    let valid_data: ValidCsDataExamples = ValidCsDataExamples::new();
-        4,
-        5,
-        vec![0, 3, 5, 8, 11],
-        vec![4, 1, 3, 3, 1, 2, 3, 0, 3, 4, 1],
-        vec![5, 1, 4, 7, 4, 2, 3, 1, 8, 9, 6],
-    )
-    .unwrap();
 
-    let expected_csr = CsrMatrix::try_from_csr_data(
+    let (offsets, indices, values) = valid_data.valid_unsorted_cs_data;
-        4,
+    let csr = CsrMatrix::try_from_unsorted_csr_data(4, 5, offsets, indices, values).unwrap();
-        5,
+
-        vec![0, 3, 5, 8, 11],
+    let (offsets2, indices2, values2) = valid_data.valid_cs_data;
-        vec![1, 3, 4, 1, 3, 0, 2, 3, 1, 3, 4],
+    let expected_csr = CsrMatrix::try_from_csr_data(4, 5, offsets2, indices2, values2).unwrap();
-        vec![1, 4, 5, 4, 7, 1, 2, 3, 6, 8, 9],
-    )
-    .unwrap();
 
     assert_eq!(csr, expected_csr);
 }
 
 #[test]
 fn csr_matrix_try_from_invalid_csr_data() {
-    let invalid_data: InvalidCsrDataExamples = InvalidCsrDataExamples::new();
+    let invalid_data: InvalidCsDataExamples = InvalidCsDataExamples::new();
     {
         // Empty offset array (invalid length)
         let (offsets, indices, values) = invalid_data.empty_offset_array;
@@ -293,7 +283,7 @@ fn csr_matrix_try_from_invalid_csr_data() {
 
 #[test]
 fn csr_matrix_try_from_unsorted_invalid_csr_data() {
-    let invalid_data: InvalidCsrDataExamples = InvalidCsrDataExamples::new();
+    let invalid_data: InvalidCsDataExamples = InvalidCsDataExamples::new();
     {
         // Empty offset array (invalid length)
         let (offsets, indices, values) = invalid_data.empty_offset_array;
@@ -355,6 +345,16 @@ fn csr_matrix_try_from_unsorted_invalid_csr_data() {
         );
     }
 
+    {
+        // Major offset out of bounds
+        let (offsets, indices, values) = invalid_data.major_offset_out_of_bounds;
+        let matrix = CsrMatrix::try_from_unsorted_csr_data(3, 6, offsets, indices, values);
+        assert_eq!(
+            matrix.unwrap_err().kind(),
+            &SparseFormatErrorKind::IndexOutOfBounds
+        );
+    }
+
     {
         // Minor index out of bounds
         let (offsets, indices, values) = invalid_data.minor_index_out_of_bounds;
@@ -374,6 +374,26 @@ fn csr_matrix_try_from_unsorted_invalid_csr_data() {
             &SparseFormatErrorKind::DuplicateEntry
         );
     }
+
+    {
+        // Duplicate entry in unsorted lane
+        let (offsets, indices, values) = invalid_data.duplicate_entry_unsorted;
+        let matrix = CsrMatrix::try_from_unsorted_csr_data(3, 6, offsets, indices, values);
+        assert_eq!(
+            matrix.unwrap_err().kind(),
+            &SparseFormatErrorKind::DuplicateEntry
+        );
+    }
+
+    {
+        // Wrong values length
+        let (offsets, indices, values) = invalid_data.wrong_values_length;
+        let matrix = CsrMatrix::try_from_unsorted_csr_data(6, 3, offsets, indices, values);
+        assert_eq!(
+            matrix.unwrap_err().kind(),
+            &SparseFormatErrorKind::InvalidStructure
+        );
+    }
 }
 
 #[test]

nalgebra-sparse/tests/unit_tests/test_data_examples.rs

@@ -1,5 +1,31 @@
-/// Examples of *invalid* raw CSR data `(offsets, indices, values)`.
+/// Examples of *valid* raw CS data `(offsets, indices, values)`.
-pub struct InvalidCsrDataExamples {
+pub struct ValidCsDataExamples {
+    pub valid_cs_data: (Vec<usize>, Vec<usize>, Vec<i32>),
+    pub valid_unsorted_cs_data: (Vec<usize>, Vec<usize>, Vec<i32>),
+}
+
+impl ValidCsDataExamples {
+    pub fn new() -> Self {
+        let valid_cs_data = (
+            vec![0, 3, 5, 8, 11],
+            vec![1, 3, 4, 1, 3, 0, 2, 3, 1, 3, 4],
+            vec![1, 4, 5, 4, 7, 1, 2, 3, 6, 8, 9],
+        );
+        let valid_unsorted_cs_data = (
+            vec![0, 3, 5, 8, 11],
+            vec![4, 1, 3, 3, 1, 2, 3, 0, 3, 4, 1],
+            vec![5, 1, 4, 7, 4, 2, 3, 1, 8, 9, 6],
+        );
+
+        return Self {
+            valid_cs_data,
+            valid_unsorted_cs_data,
+        };
+    }
+}
+
+/// Examples of *invalid* raw CS data `(offsets, indices, values)`.
+pub struct InvalidCsDataExamples {
     pub empty_offset_array: (Vec<usize>, Vec<usize>, Vec<i32>),
     pub offset_array_invalid_length_for_arbitrary_data: (Vec<usize>, Vec<usize>, Vec<i32>),
     pub invalid_first_entry_in_offsets_array: (Vec<usize>, Vec<usize>, Vec<i32>),
@@ -7,11 +33,14 @@ pub struct InvalidCsrDataExamples {
     pub invalid_length_of_offsets_array: (Vec<usize>, Vec<usize>, Vec<i32>),
     pub nonmonotonic_offsets: (Vec<usize>, Vec<usize>, Vec<i32>),
     pub nonmonotonic_minor_indices: (Vec<usize>, Vec<usize>, Vec<i32>),
+    pub major_offset_out_of_bounds: (Vec<usize>, Vec<usize>, Vec<i32>),
     pub minor_index_out_of_bounds: (Vec<usize>, Vec<usize>, Vec<i32>),
     pub duplicate_entry: (Vec<usize>, Vec<usize>, Vec<i32>),
+    pub duplicate_entry_unsorted: (Vec<usize>, Vec<usize>, Vec<i32>),
+    pub wrong_values_length: (Vec<usize>, Vec<usize>, Vec<i32>),
 }
 
-impl InvalidCsrDataExamples {
+impl InvalidCsDataExamples {
     pub fn new() -> Self {
         let empty_offset_array = (Vec::<usize>::new(), Vec::<usize>::new(), Vec::<i32>::new());
         let offset_array_invalid_length_for_arbitrary_data =
@@ -25,9 +54,13 @@ impl InvalidCsrDataExamples {
         let nonmonotonic_offsets = (vec![0, 3, 2, 5], vec![0, 1, 2, 3, 4], vec![0, 1, 2, 3, 4]);
         let nonmonotonic_minor_indices =
             (vec![0, 2, 2, 5], vec![0, 2, 3, 1, 4], vec![0, 1, 2, 3, 4]);
+        let major_offset_out_of_bounds =
+            (vec![0, 7, 2, 5], vec![0, 2, 3, 1, 4], vec![0, 1, 2, 3, 4]);
         let minor_index_out_of_bounds =
             (vec![0, 2, 2, 5], vec![0, 6, 1, 2, 3], vec![0, 1, 2, 3, 4]);
-        let duplicate_entry = (vec![0, 2, 2, 5], vec![0, 5, 2, 2, 3], vec![0, 1, 2, 3, 4]);
+        let duplicate_entry = (vec![0, 1, 2, 5], vec![1, 3, 2, 3, 3], vec![0, 1, 2, 3, 4]);
+        let duplicate_entry_unsorted = (vec![0, 1, 4, 5], vec![1, 3, 2, 3, 3], vec![0, 1, 2, 3, 4]);
+        let wrong_values_length = (vec![0, 1, 2, 5], vec![1, 3, 2, 3, 0], vec![5, 4]);
 
         return Self {
             empty_offset_array,
@@ -37,8 +70,11 @@ impl InvalidCsrDataExamples {
             invalid_length_of_offsets_array,
             nonmonotonic_minor_indices,
             nonmonotonic_offsets,
+            major_offset_out_of_bounds,
             minor_index_out_of_bounds,
             duplicate_entry,
+            duplicate_entry_unsorted,
+            wrong_values_length,
         };
     }
 }

src/linalg/svd.rs

@@ -98,7 +98,7 @@ where
             matrix,
             compute_u,
             compute_v,
-            T::RealField::default_epsilon(),
+            T::RealField::default_epsilon() * crate::convert(5.0),
             0,
         )
         .unwrap()
@@ -888,13 +888,13 @@ fn compute_2x2_uptrig_svd<T: RealField>(
             v_t = Some(csv.clone());
         }
 
-        if compute_u {
         let cu = (m11.scale(csv.c()) + m12 * csv.s()) / v1.clone();
         let su = (m22 * csv.s()) / v1.clone();
         let (csu, sgn_u) = GivensRotation::new(cu, su);
-
         v1 *= sgn_u.clone();
         v2 *= sgn_u;
+
+        if compute_u {
             u = Some(csu);
         }
     }

tests/linalg/svd.rs

@@ -460,3 +460,42 @@ fn svd_sorted() {
         epsilon = 1.0e-5
     );
 }
+
+#[test]
+// Exercises bug reported in issue #983 of nalgebra (https://github.com/dimforge/nalgebra/issues/983)
+fn svd_regression_issue_983() {
+    let m = nalgebra::dmatrix![
+        10.74785316637712f64, -5.994983325167452, -6.064492921857296;
+        -4.149751381521569, 20.654504205822462, -4.470436210703133;
+        -22.772715014220207, -1.4554372570788008, 18.108113992170573
+    ]
+    .transpose();
+    let svd1 = m.clone().svd(true, true);
+    let svd2 = m.clone().svd(false, true);
+    let svd3 = m.clone().svd(true, false);
+    let svd4 = m.svd(false, false);
+
+    assert_relative_eq!(svd1.singular_values, svd2.singular_values, epsilon = 1e-9);
+    assert_relative_eq!(svd1.singular_values, svd3.singular_values, epsilon = 1e-9);
+    assert_relative_eq!(svd1.singular_values, svd4.singular_values, epsilon = 1e-9);
+    assert_relative_eq!(
+        svd1.singular_values,
+        nalgebra::dvector![3.16188022e+01, 2.23811978e+01, 0.],
+        epsilon = 1e-6
+    );
+}
+
+#[test]
+// Exercises bug reported in issue #1072 of nalgebra (https://github.com/dimforge/nalgebra/issues/1072)
+fn svd_regression_issue_1072() {
+    let x = nalgebra::dmatrix![-6.206610118536945f64, -3.67612186839874; -1.2755730783423473, 6.047238193479124];
+    let mut x_svd = x.svd(true, true);
+    x_svd.singular_values = nalgebra::dvector![1.0, 0.0];
+    let y = x_svd.recompose().unwrap();
+    let y_svd = y.svd(true, true);
+    assert_relative_eq!(
+        y_svd.singular_values,
+        nalgebra::dvector![1.0, 0.0],
+        epsilon = 1e-9
+    );
+}