diff --git a/.github/scripts/python.sh b/.github/scripts/python.sh index 22098ec089..3f5701281c 100644 --- a/.github/scripts/python.sh +++ b/.github/scripts/python.sh @@ -85,4 +85,4 @@ make -j2 install cd $GITHUB_WORKSPACE/build/python $PYTHON setup.py install --user --prefix= cd $GITHUB_WORKSPACE/python/gtsam/tests -$PYTHON -m unittest discover +$PYTHON -m unittest discover -v diff --git a/gtsam/basis/Fourier.h b/gtsam/basis/Fourier.h index 6943150d72..d264e182dd 100644 --- a/gtsam/basis/Fourier.h +++ b/gtsam/basis/Fourier.h @@ -40,9 +40,13 @@ class GTSAM_EXPORT FourierBasis : public Basis { static Weights CalculateWeights(size_t N, double x) { Weights b(N); b[0] = 1; - for (size_t i = 1, n = 1; i < N; i += 2, n++) { - b[i] = cos(n * x); - b[i + 1] = sin(n * x); + for (size_t i = 1, n = 1; i < N; i++) { + if (i % 2 == 1) { + b[i] = cos(n * x); + } else { + b[i] = sin(n * x); + n++; + } } return b; } diff --git a/python/CMakeLists.txt b/python/CMakeLists.txt index a5fdc80a6b..4254a21c69 100644 --- a/python/CMakeLists.txt +++ b/python/CMakeLists.txt @@ -166,5 +166,6 @@ add_custom_target( COMMAND ${CMAKE_COMMAND} -E env # add package to python path so no need to install "PYTHONPATH=${GTSAM_PYTHON_BUILD_DIRECTORY}/$ENV{PYTHONPATH}" - ${PYTHON_EXECUTABLE} -m unittest discover -s "${GTSAM_PYTHON_BUILD_DIRECTORY}/gtsam/tests" - DEPENDS ${GTSAM_PYTHON_DEPENDENCIES}) + ${PYTHON_EXECUTABLE} -m unittest discover -v -s . + DEPENDS ${GTSAM_PYTHON_DEPENDENCIES} + WORKING_DIRECTORY "${GTSAM_PYTHON_BUILD_DIRECTORY}/gtsam/tests") diff --git a/python/gtsam/tests/test_basis.py b/python/gtsam/tests/test_basis.py index 8d4039249e..5d3c5ace31 100644 --- a/python/gtsam/tests/test_basis.py +++ b/python/gtsam/tests/test_basis.py @@ -18,38 +18,78 @@ class TestBasis(GtsamTestCase): - """Tests Basis module python bindings """ - def test_fit_basis(self): - """Tests FitBasis python binding for FourierBasis, Chebyshev1Basis, Chebyshev2Basis, and - Chebyshev2. - It tests FitBasis by fitting to a ground-truth function that can be represented exactly in - the basis, then checking that the regression (fit result) matches the function. For the - Chebyshev bases, the line y=x is used to generate the data while for Fourier, 0.7*cos(x) is - used. + Tests FitBasis python binding for FourierBasis, Chebyshev1Basis, Chebyshev2Basis, and Chebyshev2. + + It tests FitBasis by fitting to a ground-truth function that can be represented exactly in + the basis, then checking that the regression (fit result) matches the function. For the + Chebyshev bases, the line y=x is used to generate the data while for Fourier, 0.7*cos(x) is + used. + """ + def setUp(self): + self.N = 2 + self.x = [0., 0.5, 0.75] + self.interpx = np.linspace(0., 1., 10) + self.noise = gtsam.noiseModel.Unit.Create(1) + + def evaluate(self, basis, fitparams, x): + """ + Until wrapper for Basis functors are ready, + this is how to evaluate a basis function. """ - f = lambda x: x # line y = x - N = 2 - datax = [0., 0.5, 0.75] - interpx = np.linspace(0., 1., 10) - noise = gtsam.noiseModel.Unit.Create(1) - - def evaluate(basis, fitparams, x): - # until wrapper for Basis functors are ready, this is how to evaluate a basis function. - return basis.WeightMatrix(N, x) @ fitparams - - def testBasis(fitter, basis, f=f): - # test a basis by checking that the fit result matches the function at x-values interpx. - data = {x: f(x) for x in datax} - fit = fitter(data, noise, N) - coeff = fit.parameters() - interpy = evaluate(basis, coeff, interpx) - np.testing.assert_almost_equal(interpy, np.array([f(x) for x in interpx]), decimal=7) - - testBasis(gtsam.FitBasisFourierBasis, gtsam.FourierBasis, f=lambda x: 0.7 * np.cos(x)) - testBasis(gtsam.FitBasisChebyshev1Basis, gtsam.Chebyshev1Basis) - testBasis(gtsam.FitBasisChebyshev2Basis, gtsam.Chebyshev2Basis) - testBasis(gtsam.FitBasisChebyshev2, gtsam.Chebyshev2) + return basis.WeightMatrix(self.N, x) @ fitparams + + def fit_basis_helper(self, fitter, basis, f=lambda x: x): + """Helper method to fit data to a specified fitter using a specified basis.""" + data = {x: f(x) for x in self.x} + fit = fitter(data, self.noise, self.N) + coeff = fit.parameters() + interpy = self.evaluate(basis, coeff, self.interpx) + return interpy + + def test_fit_basis_fourier(self): + """Fit a Fourier basis.""" + + f = lambda x: 0.7 * np.cos(x) + interpy = self.fit_basis_helper(gtsam.FitBasisFourierBasis, + gtsam.FourierBasis, f) + # test a basis by checking that the fit result matches the function at x-values interpx. + np.testing.assert_almost_equal(interpy, + np.array([f(x) for x in self.interpx]), + decimal=7) + + def test_fit_basis_chebyshev1basis(self): + """Fit a Chebyshev1 basis.""" + + f = lambda x: x + interpy = self.fit_basis_helper(gtsam.FitBasisChebyshev1Basis, + gtsam.Chebyshev1Basis, f) + # test a basis by checking that the fit result matches the function at x-values interpx. + np.testing.assert_almost_equal(interpy, + np.array([f(x) for x in self.interpx]), + decimal=7) + + def test_fit_basis_chebyshev2basis(self): + """Fit a Chebyshev2 basis.""" + + f = lambda x: x + interpy = self.fit_basis_helper(gtsam.FitBasisChebyshev2Basis, + gtsam.Chebyshev2Basis) + # test a basis by checking that the fit result matches the function at x-values interpx. + np.testing.assert_almost_equal(interpy, + np.array([f(x) for x in self.interpx]), + decimal=7) + + def test_fit_basis_chebyshev2(self): + """Fit a Chebyshev2 pseudospectral basis.""" + + f = lambda x: x + interpy = self.fit_basis_helper(gtsam.FitBasisChebyshev2, + gtsam.Chebyshev2) + # test a basis by checking that the fit result matches the function at x-values interpx. + np.testing.assert_almost_equal(interpy, + np.array([f(x) for x in self.interpx]), + decimal=7) if __name__ == "__main__":