def test_math_utils(self):
a = initializeAutoDiff([1, 2, 3])
np.testing.assert_array_equal(autoDiffToValueMatrix(a),
np.array([[1, 2, 3]]).T)
np.testing.assert_array_equal(autoDiffToGradientMatrix(a), np.eye(3))
a, b = initializeAutoDiffTuple([1], [2, 3])
np.testing.assert_array_equal(autoDiffToValueMatrix(a),
np.array([[1]]))
np.testing.assert_array_equal(autoDiffToValueMatrix(b),
np.array([[2, 3]]).T)
np.testing.assert_array_equal(autoDiffToGradientMatrix(a),
np.eye(1, 3))
np.testing.assert_array_equal(autoDiffToGradientMatrix(b),
np.hstack((np.zeros((2, 1)), np.eye(2))))
def test_math_utils(self):
a = initializeAutoDiff([1, 2, 3])
np.testing.assert_array_equal(autoDiffToValueMatrix(a),
np.array([[1, 2, 3]]).T)
np.testing.assert_array_equal(autoDiffToGradientMatrix(a), np.eye(3))
a, b = initializeAutoDiffTuple([1], [2, 3])
np.testing.assert_array_equal(autoDiffToValueMatrix(a),
np.array([[1]]))
np.testing.assert_array_equal(autoDiffToValueMatrix(b),
np.array([[2, 3]]).T)
np.testing.assert_array_equal(autoDiffToGradientMatrix(a),
np.eye(1, 3))
np.testing.assert_array_equal(autoDiffToGradientMatrix(b),
np.hstack((np.zeros((2, 1)), np.eye(2))))
def test_math_utils(self):
a = initializeAutoDiff([1, 2, 3])
np.testing.assert_array_equal(autoDiffToValueMatrix(a),
np.array([[1, 2, 3]]).T)
np.testing.assert_array_equal(autoDiffToGradientMatrix(a), np.eye(3))
a, b = initializeAutoDiffTuple([1], [2, 3])
np.testing.assert_array_equal(autoDiffToValueMatrix(a),
np.array([[1]]))
np.testing.assert_array_equal(autoDiffToValueMatrix(b),
np.array([[2, 3]]).T)
np.testing.assert_array_equal(autoDiffToGradientMatrix(a),
np.eye(1, 3))
np.testing.assert_array_equal(autoDiffToGradientMatrix(b),
np.hstack((np.zeros((2, 1)), np.eye(2))))
c_grad = [[2, 4, 5], [1, -1, 0]]
c = initializeAutoDiffGivenGradientMatrix([2, 3], c_grad)
np.testing.assert_array_equal(autoDiffToValueMatrix(c),
np.array([2, 3]).reshape((2, 1)))
np.testing.assert_array_equal(autoDiffToGradientMatrix(c),
np.array(c_grad))
def test_deprecated_math_utils(self):
with catch_drake_warnings(expected_count=1):
a = initializeAutoDiff([1, 2, 3])
with catch_drake_warnings(expected_count=1):
np.testing.assert_array_equal(autoDiffToValueMatrix(a),
np.array([[1, 2, 3]]).T)
with catch_drake_warnings(expected_count=1):
np.testing.assert_array_equal(autoDiffToGradientMatrix(a),
np.eye(3))
with catch_drake_warnings(expected_count=1):
a, b = initializeAutoDiffTuple([1], [2, 3])
with catch_drake_warnings(expected_count=1):
np.testing.assert_array_equal(autoDiffToValueMatrix(a),
np.array([[1]]))
with catch_drake_warnings(expected_count=1):
np.testing.assert_array_equal(autoDiffToValueMatrix(b),
np.array([[2, 3]]).T)
with catch_drake_warnings(expected_count=1):
np.testing.assert_array_equal(autoDiffToGradientMatrix(a),
np.eye(1, 3))
with catch_drake_warnings(expected_count=1):
np.testing.assert_array_equal(
autoDiffToGradientMatrix(b),
np.hstack((np.zeros((2, 1)), np.eye(2))))
c_grad = [[2, 4, 5], [1, -1, 0]]
with catch_drake_warnings(expected_count=1):
c = initializeAutoDiffGivenGradientMatrix([2, 3], c_grad)
with catch_drake_warnings(expected_count=1):
np.testing.assert_array_equal(autoDiffToValueMatrix(c),
np.array([2, 3]).reshape((2, 1)))
with catch_drake_warnings(expected_count=1):
np.testing.assert_array_equal(autoDiffToGradientMatrix(c),
np.array(c_grad))