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[wpimath] Clean up Eigen usage

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* Replace Matrix<> with Vector<> where vectors are explicitly intended.
  I found these via `rg "Eigen::Matrix<double, \w+, 1>"`.
* Pass all Eigen matrices by const reference. I found these via `rg
  "\(Eigen"` on main (the initializer list constructors make more false
  positives).
* Replace MakeMatrix() and operator<< usage with initializer list
  constructors. I found these via `rg MakeMatrix` and `rg "<<"`
  respectively.
* Deprecate MakeMatrix()
This commit is contained in:
Tyler Veness
2021-08-19 00:23:48 -07:00
committed by Peter Johnson
parent 72716f51ce
commit 9359431bad
63 changed files with 821 additions and 955 deletions
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28
wpimath/src/test/native/cpp/StateSpaceUtilTest.cpp
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@@ -12,12 +12,12 @@
TEST(StateSpaceUtilTest, MakeMatrix) {
// Column vector
Eigen::Matrix<double, 2, 1> mat1 = frc::MakeMatrix<2, 1>(1.0, 2.0);
Eigen::Vector<double, 2> mat1 = frc::MakeMatrix<2, 1>(1.0, 2.0);
EXPECT_NEAR(mat1(0), 1.0, 1e-3);
EXPECT_NEAR(mat1(1), 2.0, 1e-3);
// Row vector
Eigen::Matrix<double, 1, 2> mat2 = frc::MakeMatrix<1, 2>(1.0, 2.0);
Eigen::RowVector<double, 2> mat2 = frc::MakeMatrix<1, 2>(1.0, 2.0);
EXPECT_NEAR(mat2(0), 1.0, 1e-3);
EXPECT_NEAR(mat2(1), 2.0, 1e-3);
@@ -102,44 +102,42 @@ TEST(StateSpaceUtilTest, CovArray) {
}
TEST(StateSpaceUtilTest, WhiteNoiseVectorParameterPack) {
Eigen::Matrix<double, 2, 1> vec = frc::MakeWhiteNoiseVector(2.0, 3.0);
Eigen::Vector<double, 2> vec = frc::MakeWhiteNoiseVector(2.0, 3.0);
static_cast<void>(vec);
}
TEST(StateSpaceUtilTest, WhiteNoiseVectorArray) {
Eigen::Matrix<double, 2, 1> vec = frc::MakeWhiteNoiseVector<2>({2.0, 3.0});
Eigen::Vector<double, 2> vec = frc::MakeWhiteNoiseVector<2>({2.0, 3.0});
static_cast<void>(vec);
}
TEST(StateSpaceUtilTest, IsStabilizable) {
Eigen::Matrix<double, 2, 2> A;
Eigen::Matrix<double, 2, 1> B;
B << 0, 1;
Eigen::Matrix<double, 2, 1> B{0, 1};
// We separate the result of IsStabilizable from the assertion because
// templates break gtest.
// First eigenvalue is uncontrollable and unstable.
// Second eigenvalue is controllable and stable.
A << 1.2, 0, 0, 0.5;
bool ret = frc::IsStabilizable<2, 1>(A, B);
Eigen::Matrix<double, 2, 2> A1{{1.2, 0}, {0, 0.5}};
bool ret = frc::IsStabilizable<2, 1>(A1, B);
EXPECT_FALSE(ret);
// First eigenvalue is uncontrollable and marginally stable.
// Second eigenvalue is controllable and stable.
A << 1, 0, 0, 0.5;
ret = frc::IsStabilizable<2, 1>(A, B);
Eigen::Matrix<double, 2, 2> A2{{1, 0}, {0, 0.5}};
ret = frc::IsStabilizable<2, 1>(A2, B);
EXPECT_FALSE(ret);
// First eigenvalue is uncontrollable and stable.
// Second eigenvalue is controllable and stable.
A << 0.2, 0, 0, 0.5;
ret = frc::IsStabilizable<2, 1>(A, B);
Eigen::Matrix<double, 2, 2> A3{{0.2, 0}, {0, 0.5}};
ret = frc::IsStabilizable<2, 1>(A3, B);
EXPECT_TRUE(ret);
// First eigenvalue is uncontrollable and stable.
// Second eigenvalue is controllable and unstable.
A << 0.2, 0, 0, 1.2;
ret = frc::IsStabilizable<2, 1>(A, B);
Eigen::Matrix<double, 2, 2> A4{{0.2, 0}, {0, 1.2}};
ret = frc::IsStabilizable<2, 1>(A4, B);
EXPECT_TRUE(ret);
}