Fixed tests

master
Per A Brodtkorb 9 years ago
parent 4838347784
commit d40af0da00

@ -47,7 +47,7 @@ def test_rind():
Blo[0, ind] = np.maximum(Blo[0, ind], -infinity * dev[indI[ind + 1]]) Blo[0, ind] = np.maximum(Blo[0, ind], -infinity * dev[indI[ind + 1]])
val, err, terr = rind(Sc, m, Blo, Bup, indI, xc, nt=0) val, err, terr = rind(Sc, m, Blo, Bup, indI, xc, nt=0)
assert_array_almost_equal(val, 0.05494076, decimal=3) assert_array_almost_equal(val, 0.05494076, decimal=3)
assert(err < 0.001) assert(err < 0.0013)
assert_array_almost_equal(terr, 1.00000000e-10) assert_array_almost_equal(terr, 1.00000000e-10)
# Compute expectation E( X1^{+}*X2^{+} ) with random # Compute expectation E( X1^{+}*X2^{+} ) with random

@ -25,7 +25,7 @@ class Gaussq(unittest.TestCase):
def test_gauss_legendre(self): def test_gauss_legendre(self):
val, _err = gaussq(exp, 0, 1) val, _err = gaussq(exp, 0, 1)
self.assertAlmostEqual(val, exp(1)-exp(0)) assert_array_almost_equal(val, exp(1)-exp(0))
a, b, y = [0, 0], [1, 1], np.array([1., 2.]) a, b, y = [0, 0], [1, 1], np.array([1., 2.])
val, _err = gaussq(lambda x, y: x * y, a, b, args=(y, )) val, _err = gaussq(lambda x, y: x * y, a, b, args=(y, ))

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