问题
I was wondering if there is a good way to test two Eigen matrices for approximate equality using Google Test, or Google Mock.
Take the following test-case as a simplified example: I am multiplying two complex valued matrices A
, and B
, and expect a certain result C_expect
. I calculate the numerical result C_actual = A * B
, using Eigen. Now, I want to compare C_expect
, and C_actual
. Right now, the corresponding code looks like this:
#include <complex>
#include <Eigen/Dense>
#include <gtest/gtest.h>
#include <gmock/gmock.h>
typedef std::complex<double> Complex;
typedef Eigen::Matrix2cd Matrix;
TEST(Eigen, MatrixMultiplication) {
Matrix A, B, C_expect, C_actual;
A << Complex(1, 1), Complex(2, 3),
Complex(3, 2), Complex(4, 4);
B << Complex(4, 4), Complex(3, 2),
Complex(2, 3), Complex(1, 1);
C_expect << Complex(-5, 20), Complex(0, 10),
Complex(0, 40), Complex(5, 20);
C_actual = A * B;
// !!! These are the lines that bother me.
for (int j = 0; j < C_actual.cols(); ++j) {
for (int i = 0; i < C_actual.rows(); ++i) {
EXPECT_NEAR(C_expect(i, j).real(), C_actual(i, j).real(), 1e-7)
<< "Re(" << i << "," << j << ")";
EXPECT_NEAR(C_expect(i, j).imag(), C_actual(i, j).imag(), 1e-7)
<< "Im(" << i << "," << j << ")";
}
}
}
What's wrong with this? Well, I have to manually iterate through all indices of the matrix, and then compare the real-part and imaginary-part individually. I would much prefer something along the lines of Google Mock's ElementsAreArray
matcher. E.g.
EXPECT_THAT(C_actual, ElementsAreArray(C_expect));
// or
EXPECT_THAT(C_actual, Pointwise(MyComplexNear(1e-7), C_expect));
Unfortunately, the built-in capabilities of Google Mock only seem to work on 1-dimensional C-style, or STL-type containers. Furthermore, I need an approximate comparison for the complex values of my matrix.
My question: Do you know if (and how) it is possible to teach Google Mock to iterate over multiple dimensions, and compare complex floating point numbers to approximate equality?
Please note, that I cannot just handle the data-pointers as C-style arrays, because the storage layout might differ between C_expect
, and C_actual
. Also, in reality, the matrices are larger than just 2x2 matrices. I.e. some sort of loop is definitely necessary.
回答1:
Why not use the isApprox
or isMuchSmallerThan
member functions of Eigen Matrix types?
The documentation of these above functions are available here
So for most cases ASSERT_TRUE(C_actual.isApprox(C_expect));
is what you need. You can also provide a precision parameter as the second arguement to isApprox.
回答2:
A simplified solution would be to compare the norm of the difference with some epsilon, i.e.
(C_expect - C_actual).norm() < 1e-6
In a vector space || X - Y || == 0 if and only if X == Y, and the norm is always non-negative (real). This way, you won't have to manually do the loop and compare element-wise (of course the norm will perform more calculations in the background than simple element-wise comparisons)
PS: the Matrix::norm()
implemented in Eigen is the Frobenius norm, which is computationally very fast to evaluate, see http://mathworld.wolfram.com/FrobeniusNorm.html
回答3:
EXPECT_PRED2
from GoogleTest can be used for this.
Under C++11 using a lambda works fine but looks unseemly:
ASSERT_PRED2([](const MatrixXf &lhs, const MatrixXf &rhs) {
return lhs.isApprox(rhs, 1e-4);
},
C_expect, C_actual);
If that fails, you get a print-out of the input arguments.
Instead of using a lambda, a normal predicate function can be defined like this:
bool MatrixEquality(const MatrixXf &lhs, const MatrixXf &rhs) {
return lhs.isApprox(rhs, 1e-4);
}
TEST(Eigen, MatrixMultiplication) {
...
ASSERT_PRED2(MatrixEquality, C_expected, C_actual);
}
The later version also works on pre-C++11.
来源:https://stackoverflow.com/questions/25094989/compare-eigen-matrices-in-google-test-or-google-mock