Add weighted ctor and its test

1 files changed, 82 insertions, 0 deletions

diff --git a/src/Alpha_complex/test/Weighted_alpha_complex_unit_test.cpp b/src/Alpha_complex/test/Weighted_alpha_complex_unit_test.cpp
new file mode 100644
index 00000000..b4fc76de
--- /dev/null
+++ b/src/Alpha_complex/test/Weighted_alpha_complex_unit_test.cpp
@@ -0,0 +1,82 @@
+/*    This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+ *    See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+ *    Author(s):       Vincent Rouvreau
+ *
+ *    Copyright (C) 2020 Inria
+ *
+ *    Modification(s):
+ *      - YYYY/MM Author: Description of the modification
+ */
+
+#define BOOST_TEST_DYN_LINK
+#define BOOST_TEST_MODULE "weighted_alpha_complex"
+#include <boost/test/unit_test.hpp>
+#include <boost/mpl/list.hpp>
+
+#include <CGAL/Epick_d.h>
+#include <CGAL/Epeck_d.h>
+
+#include <cmath>  // float comparison
+#include <vector>
+#include <random>
+
+#include <gudhi/Alpha_complex.h>
+#include <gudhi/Simplex_tree.h>
+#include <gudhi/Unitary_tests_utils.h>
+
+// Use dynamic_dimension_tag for the user to be able to set dimension
+typedef CGAL::Epeck_d< CGAL::Dynamic_dimension_tag > Exact_kernel_d;
+// Use static dimension_tag for the user not to be able to set dimension
+typedef CGAL::Epeck_d< CGAL::Dimension_tag<4> > Exact_kernel_s;
+// Use dynamic_dimension_tag for the user to be able to set dimension
+typedef CGAL::Epick_d< CGAL::Dynamic_dimension_tag > Inexact_kernel_d;
+// Use static dimension_tag for the user not to be able to set dimension
+typedef CGAL::Epick_d< CGAL::Dimension_tag<4> > Inexact_kernel_s;
+// The triangulation uses the default instantiation of the TriangulationDataStructure template parameter
+
+typedef boost::mpl::list<Exact_kernel_d, Exact_kernel_s, Inexact_kernel_d, Inexact_kernel_s> list_of_kernel_variants;
+
+BOOST_AUTO_TEST_CASE_TEMPLATE(Zero_weighted_alpha_complex, Kernel, list_of_kernel_variants) {
+  // Random points construction
+  using Point_d = typename Kernel::Point_d;
+  std::vector<Point_d> points;
+  std::uniform_real_distribution<double> rd_pts(-10., 10.);
+  std::random_device rand_dev;
+  std::mt19937 rand_engine(rand_dev());
+  for (int idx = 0; idx < 20; idx++) {
+    std::vector<double> point {rd_pts(rand_engine), rd_pts(rand_engine), rd_pts(rand_engine), rd_pts(rand_engine)};
+    points.emplace_back(Point_d(point.begin(), point.end()));
+  }
+  
+  // Alpha complex from points
+  Gudhi::alpha_complex::Alpha_complex<Kernel, false> alpha_complex_from_points(points);
+  Gudhi::Simplex_tree<> simplex;
+  BOOST_CHECK(alpha_complex_from_points.create_complex(simplex));
+  std::clog << "Iterator on alpha complex simplices in the filtration order, with [filtration value]:" << std::endl;
+  for (auto f_simplex : simplex.filtration_simplex_range()) {
+    std::clog << "   ( ";
+    for (auto vertex : simplex.simplex_vertex_range(f_simplex)) {
+      std::clog << vertex << " ";
+    }
+    std::clog << ") -> " << "[" << simplex.filtration(f_simplex) << "] ";
+    std::clog << std::endl;
+  }
+
+  // Alpha complex from zero weighted points
+  std::vector<typename Kernel::FT> weights(20, 0.);
+  Gudhi::alpha_complex::Alpha_complex<Kernel, true> alpha_complex_from_zero_weighted_points(points, weights);
+  Gudhi::Simplex_tree<> zw_simplex;
+  BOOST_CHECK(alpha_complex_from_zero_weighted_points.create_complex(zw_simplex));
+
+  std::clog << "Iterator on zero weighted alpha complex simplices in the filtration order, with [filtration value]:" << std::endl;
+  for (auto f_simplex : zw_simplex.filtration_simplex_range()) {
+    std::clog << "   ( ";
+    for (auto vertex : zw_simplex.simplex_vertex_range(f_simplex)) {
+      std::clog << vertex << " ";
+    }
+    std::clog << ") -> " << "[" << zw_simplex.filtration(f_simplex) << "] ";
+    std::clog << std::endl;
+  }
+
+  BOOST_CHECK(zw_simplex == simplex);
+}
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