forked from M-Labs/nalgebra
CSR/CSC: Provide constructor for unsorted but otherwise valid data
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@ -170,6 +170,24 @@ impl<T> CsrMatrix<T> {
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Self::try_from_pattern_and_values(pattern, values)
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}
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/// Try to construct a CSR matrix from raw CSR data with unsorted columns.
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pub fn try_from_unsorted_csr_data(
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num_rows: usize,
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num_cols: usize,
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row_offsets: Vec<usize>,
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col_indices: Vec<usize>,
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values: Vec<T>,
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) -> Result<Self, SparseFormatError> {
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let sorted_num_cols: Vec<usize> = row_offsets[0..row_offsets.len() - 1]
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.iter()
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.enumerate()
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.flat_map(|(index, &offset)| {
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Self::sorted(col_indices[offset..row_offsets[index + 1]].to_vec())
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})
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.collect();
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return Self::try_from_csr_data(num_rows, num_cols, row_offsets, sorted_num_cols, values);
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}
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/// Try to construct a CSR matrix from a sparsity pattern and associated non-zero values.
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///
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/// Returns an error if the number of values does not match the number of minor indices
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@ -190,6 +208,15 @@ impl<T> CsrMatrix<T> {
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}
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}
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/// Return sorted vector.
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#[inline]
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#[must_use]
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pub fn sorted(row_offsets: Vec<usize>) -> Vec<usize> {
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let mut sorted = row_offsets.clone();
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sorted.sort();
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return sorted;
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}
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/// The number of rows in the matrix.
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#[inline]
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#[must_use]
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@ -171,6 +171,29 @@ fn csr_matrix_valid_data() {
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}
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}
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#[test]
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fn csr_matrix_valid_data_unsorted_column_indices() {
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let csr = CsrMatrix::try_from_unsorted_csr_data(
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3,
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4,
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vec![0, 1, 2, 5],
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vec![1, 3, 2, 3, 0],
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vec![5, 4, 1, 1, 4],
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)
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.unwrap();
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let expected_csr = CsrMatrix::try_from_csr_data(
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3,
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4,
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vec![0, 1, 2, 5],
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vec![1, 3, 0, 2, 3],
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vec![5, 4, 1, 1, 4],
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)
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.unwrap();
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assert_eq!(csr, expected_csr);
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}
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#[test]
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fn csr_matrix_try_from_invalid_csr_data() {
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{
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