Merge pull request #538 from jcarpent/devel

Fix issue for sparse matrix conversions

Author: jcarpent

CHANGELOG.md

@@ -6,6 +6,10 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
 
 ## [Unreleased]
 
+### Fixed
+
+- Fix handling of non sorted sparse matrix ([#538](https://github.com/stack-of-tasks/eigenpy/pull/538))
+
 ## [3.10.3] - 2025-02-11
 
 ### Added

include/eigenpy/sparse/eigen-from-python.hpp

@@ -1,5 +1,5 @@
 //
-// Copyright (c) 2024 INRIA
+// Copyright (c) 2024-2025 INRIA
 //
 
 #ifndef __eigenpy_sparse_eigen_from_python_hpp__
@@ -156,6 +156,10 @@ void eigen_sparse_matrix_from_py_construct(
     }
     MapMatOrRefType sparse_map(m, n, nnz, indptr.data(), indices_ptr, data_ptr);
 
+#if EIGEN_VERSION_AT_LEAST(3, 4, 90)
+    sparse_map.sortInnerIndices();
+#endif
+
     new (raw_ptr) MatOrRefType(sparse_map);
   }
 

unittest/python/decompositions/sparse/test_SimplicialLLT.py

@@ -1,4 +1,5 @@
 import numpy as np
+import scipy
 from scipy.sparse import csc_matrix
 
 import eigenpy
@@ -30,3 +31,14 @@
 llt.analyzePattern(A)
 llt.factorize(A)
 permutation = llt.permutationP()
+
+X_sparse = scipy.sparse.random(dim, 10)
+B_sparse = A.dot(X_sparse)
+B_sparse = B_sparse.tocsc(True)
+
+if not B_sparse.has_sorted_indices:
+    B_sparse.sort_indices()
+
+X_est = llt.solve(B_sparse)
+assert eigenpy.is_approx(X_est.toarray(), X_sparse.toarray())
+assert eigenpy.is_approx(A.dot(X_est.toarray()), B_sparse.toarray())