docstrings and formatting

python/gtsam/tests/test_basis.py

@@ -16,23 +16,41 @@ import gtsam
 from gtsam.utils.test_case import GtsamTestCase
 from gtsam.symbol_shorthand import B
 
+
 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.
+        """
         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 = basis.WeightMatrix(N, interpx) @ coeff
+            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)
 
+
 if __name__ == "__main__":
     unittest.main()