tests: move block-matrix.cpp test to core tests, split up gar test util

Author: ManifoldFR

examples/clqr.cpp

@@ -7,7 +7,7 @@
 #include "aligator/modelling/constraints.hpp"
 #include <aligator/fmt-eigen.hpp>
 #include <iostream>
-#include <random>
+#include "../tests/test_util.hpp"
 
 using namespace aligator;
 
@@ -23,20 +23,15 @@ using context::StageModel;
 using context::TrajOptProblem;
 using context::VectorXs;
 
-static std::mt19937_64 urng{42};
-struct NormalGen {
-  double operator()() const { return norm(urng); }
-  mutable std::normal_distribution<double> norm;
-};
-
 int main() {
+  std::mt19937 rng{42};
   std::srand(42);
   const size_t nsteps = 100;
   const auto nx = 4;
   const auto nu = 2;
   const auto space = Space(nx);
 
-  NormalGen norm_gen;
+  normal_unary_op norm_gen{rng};
   MatrixXs A;
   // clang-format off
   A.setIdentity(nx, nx);

tests/CMakeLists.txt

@@ -36,6 +36,7 @@ endfunction()
 set(
   TEST_NAMES
   arena-matrix
+  block-matrix
   continuous
   constraints
   costs

tests/gar/block-matrix.cpp tests/block-matrix.cpptests/gar/block-matrix.cpp renamed to tests/block-matrix.cpp

@@ -4,7 +4,7 @@
 #include <catch2/catch_get_random_seed.hpp>
 
 #include "aligator/context.hpp"
-#include "aligator/gar/blk-matrix.hpp"
+#include "aligator/core/blk-matrix.hpp"
 #include "aligator/gar/block-tridiagonal.hpp"
 #include "aligator/core/bunchkaufman.hpp"
 #include <Eigen/Cholesky>
@@ -13,11 +13,10 @@
 #include <aligator/fmt-eigen.hpp>
 
 using namespace aligator;
-using namespace aligator::context;
-
-using MatrixXs = math_types<Scalar>::MatrixXs;
-using MatrixRef = Eigen::Ref<MatrixXs>;
-using VectorXs = math_types<Scalar>::VectorXs;
+using context::MatrixRef;
+using context::MatrixXs;
+using context::VectorXs;
+using BlkVec = BlkMatrix<VectorXs, -1, 1>;
 
 TEST_CASE("blk22", "[gar]") {
   std::array<long, 2> dims = {4, 6};
@@ -63,7 +62,6 @@ struct BTAG_Fixture {
   std::vector<MatrixXs> diagonal;
   std::vector<MatrixXs> sup;
   std::vector<MatrixXs> sub;
-  using BlkVec = BlkMatrix<VectorXs, -1, 1>;
   BlkVec vec;
   MatrixXs densemat;
   BlkVec rhs;

tests/gar/CMakeLists.txt

@@ -1,4 +1,4 @@
-set(TEST_NAMES riccati block-matrix knot)
+set(TEST_NAMES riccati knot)
 
 if(BUILD_WITH_OPENMP_SUPPORT)
   list(APPEND TEST_NAMES parallel)

tests/gar/test_util.cpp

@@ -1,5 +1,5 @@
 /// @copyright Copyright (C) 2023-2024 LAAS-CNRS, 2023-2025 INRIA
-#include "./test_util.hpp"
+#include "test_util.hpp"
 #include "aligator/gar/utils.hpp"
 
 #include <Eigen/Dense>
@@ -11,13 +11,6 @@ compute_conditioning(const Eigen::SelfAdjointView<Mat, Eigen::Lower> &view) {
   return eigvals(0) / eigvals(eigvals.size() - 1);
 }
 
-/// Generate a Wishart-distributed matrix in @p n dimensions with @p p DoF
-MatrixXs sampleWishartDistributedMatrix(uint n, uint p) {
-  std::mt19937 rng;
-  MatrixXs root = MatrixXs::NullaryExpr(n, p, normal_unary_op(rng));
-  return root * root.transpose();
-};
-
 knot_t generateKnot(std::mt19937 rng, knot_gen_opts_t opts,
                     const aligator::polymorphic_allocator &alloc) {
   normal_unary_op normal_op{rng};

tests/gar/test_util.hpp

@@ -2,7 +2,7 @@
 #pragma once
 
 #include "aligator/gar/lqr-problem.hpp"
-#include <random>
+#include "../test_util.hpp"
 
 ALIGATOR_DYNAMIC_TYPEDEFS(double);
 using problem_t = aligator::gar::LqrProblemTpl<double>;
@@ -48,21 +48,6 @@ computeKktError(const problem_t &problem, const VectorOfVectors &xs,
                          verbose);
 }
 
-struct normal_unary_op {
-  mutable std::mt19937 rng;
-  mutable std::normal_distribution<double> gen;
-
-  explicit normal_unary_op(std::mt19937 rng, double stddev = 1.0)
-      : rng(rng)
-      , gen(0.0, stddev) {}
-
-  void set_seed(size_t sd) { rng.seed(sd); }
-
-  double operator()() const { return gen(rng); }
-};
-
-MatrixXs sampleWishartDistributedMatrix(uint n, uint p);
-
 struct knot_gen_opts_t {
   uint nx;
   uint nu;

tests/test_util.hpp

@@ -0,0 +1,23 @@
+#include <Eigen/Core>
+#include <random>
+
+struct normal_unary_op {
+  mutable std::mt19937 rng;
+  mutable std::normal_distribution<double> gen;
+
+  explicit normal_unary_op(std::mt19937 rng, double stddev = 1.0)
+      : rng(rng)
+      , gen(0.0, stddev) {}
+
+  void set_seed(size_t sd) { rng.seed(sd); }
+
+  double operator()() const { return gen(rng); }
+};
+
+/// Generate a Wishart-distributed matrix in @p n dimensions with @p p DoF
+inline Eigen::MatrixXd sampleWishartDistributedMatrix(uint n, uint p) {
+  using Eigen::MatrixXd;
+  std::mt19937 rng;
+  MatrixXd root = MatrixXd::NullaryExpr(n, p, normal_unary_op(rng));
+  return root * root.transpose();
+}