moved pruning code to SparseVector.h

Eigen/src/SparseCore/CompressedStorage.h

@@ -225,22 +225,6 @@ class CompressedStorage
       }
     }
 
-    void prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision())
-    {
-      Index k = 0;
-      Index n = size();
-      for (Index i=0; i<n; ++i)
-      {
-        if (!internal::isMuchSmallerThan(value(i), reference, epsilon))
-        {
-          value(k) = value(i);
-          index(k) = index(i);
-          ++k;
-        }
-      }
-      resize(k,0);
-    }
-
   protected:
 
     inline void reallocate(Index size)

Eigen/src/SparseCore/SparseVector.h

@@ -209,9 +209,33 @@ class SparseVector
     inline void finalize() {}
 
     /** \copydoc SparseMatrix::prune(const Scalar&,const RealScalar&) */
-    void prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision())
+    Index prune(const Scalar& reference, const RealScalar& epsilon = NumTraits<RealScalar>::dummy_precision()) {
+      return prune([&](const Scalar& val){ return !internal::isMuchSmallerThan(val, reference, epsilon); });
+    }
+
+    /**
+     * \brief Prunes the entries of the vector based on a `predicate`
+     * \tparam F Type of the predicate.
+     * \param keep_predicate The predicate that is used to test whether a value should be kept. A callable that
+     * gets passed om a `Scalar` value and returns a boolean. If the predicate returns true, the value is kept.
+     * \return The new number of structural non-zeros.
+     */
+    template<class F>
+    Index prune(F&& keep_predicate)
     {
-      m_data.prune(reference,epsilon);
+      Index k = 0;
+      Index n = m_data.size();
+      for (Index i = 0; i < n; ++i)
+      {
+        if (keep_predicate(m_data.value(i)))
+        {
+          m_data.value(k) = std::move(m_data.value(i));
+          m_data.index(k) = m_data.index(i);
+          ++k;
+        }
+      }
+      m_data.resize(k);
+      return k;
     }
 
     /** Resizes the sparse vector to \a rows x \a cols

test/sparse_vector.cpp

@@ -111,7 +111,7 @@ template<typename Scalar,typename StorageIndex> void sparse_vector(int rows, int
   // check copy to dense vector with transpose
   refV3.resize(0);
   VERIFY_IS_APPROX(refV3 = v1.transpose(),v1.toDense()); 
-  VERIFY_IS_APPROX(DenseVector(v1),v1.toDense()); 
+  VERIFY_IS_APPROX(DenseVector(v1),v1.toDense());
 
   // test conservative resize
   {
@@ -144,6 +144,31 @@ template<typename Scalar,typename StorageIndex> void sparse_vector(int rows, int
   }
 
 }
+void test_pruning() {
+    using SparseVectorType = SparseVector<double, 0, int>;
+
+    SparseVectorType vec;
+    auto init_vec = [&](){;
+        vec.resize(10);
+        vec.insert(3) = 0.1;
+        vec.insert(5) = 1.0;
+        vec.insert(8) = -0.1;
+        vec.insert(9) = -0.2;
+    };
+    init_vec();
+
+    VERIFY_IS_EQUAL(vec.nonZeros(), 4);
+    VERIFY_IS_EQUAL(vec.prune(0.1, 1.0), 2);
+    VERIFY_IS_EQUAL(vec.nonZeros(), 2);
+    VERIFY_IS_EQUAL(vec.coeff(5), 1.0);
+    VERIFY_IS_EQUAL(vec.coeff(9), -0.2);
+
+    init_vec();
+    VERIFY_IS_EQUAL(vec.prune([](double v) { return v >= 0; }), 2);
+    VERIFY_IS_EQUAL(vec.nonZeros(), 2);
+    VERIFY_IS_EQUAL(vec.coeff(3), 0.1);
+    VERIFY_IS_EQUAL(vec.coeff(5), 1.0);
+}
 
 EIGEN_DECLARE_TEST(sparse_vector)
 {
@@ -159,5 +184,7 @@ EIGEN_DECLARE_TEST(sparse_vector)
     CALL_SUBTEST_1(( sparse_vector<double,long int>(r, c) ));
     CALL_SUBTEST_1(( sparse_vector<double,short>(r, c) ));
   }
+
+  CALL_SUBTEST_1(test_pruning());
 }