def test_1x1b(self):
data = np.array([
230769.23076923, -76923.07692308, 19230.76923077, -28846.15384615,
-24038.46153846, 230769.23076923, 19230.76923077, -76923.07692308,
-24038.46153846, -28846.15384615, -76923.07692308, 230769.23076923,
-28846.15384615, 24038.46153846, 19230.76923077, 19230.76923077,
230769.23076923, 24038.46153846, -28846.15384615, -76923.07692308,
19230.76923077, -28846.15384615, 24038.46153846, 230769.23076923,
-76923.07692308, -76923.07692308, 24038.46153846, -28846.15384615,
230769.23076923, 19230.76923077, -28846.15384615, -24038.46153846,
19230.76923077, -76923.07692308, 230769.23076923, -24038.46153846,
-28846.15384615, -76923.07692308, 19230.76923077, 230769.23076923
])
row = np.array([
0, 2, 4, 6, 7, 1, 3, 5, 6, 7, 0, 2, 4, 5, 6, 1, 3, 4, 5, 7, 0, 2,
3, 4, 6, 1, 2, 3, 5, 7, 0, 1, 2, 4, 6, 0, 1, 3, 5, 7
])
col = np.array([
0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4,
4, 4, 4, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7
])
A_expected = coo_matrix((data, (row, col)), shape=(8, 8)).toarray()
B_expected = np.array([[1., 0., 0.5], [0., 1., -0.5], [1., 0., 0.5],
[0., 1., 0.5], [1., 0., -0.5], [0., 1., -0.5],
[1., 0., -0.5], [0., 1., 0.5]])
A, B = linear_elasticity((2, 2), E=1e5, nu=0.3)
assert_almost_equal(A.toarray(), A_expected)
assert_almost_equal(B, B_expected)
def test_1x1(self):
data = array([ 230769.23076923, -76923.07692308, 19230.76923077,
-28846.15384615, -24038.46153846, 230769.23076923,
19230.76923077, -76923.07692308, -24038.46153846,
-28846.15384615, -76923.07692308, 230769.23076923,
-28846.15384615, 24038.46153846, 19230.76923077,
19230.76923077, 230769.23076923, 24038.46153846,
-28846.15384615, -76923.07692308, 19230.76923077,
-28846.15384615, 24038.46153846, 230769.23076923,
-76923.07692308, -76923.07692308, 24038.46153846,
-28846.15384615, 230769.23076923, 19230.76923077,
-28846.15384615, -24038.46153846, 19230.76923077,
-76923.07692308, 230769.23076923, -24038.46153846,
-28846.15384615, -76923.07692308, 19230.76923077,
230769.23076923])
row = array([0, 2, 4, 6, 7, 1, 3, 5, 6, 7, 0, 2, 4, 5, 6, 1, 3, 4, 5, 7, 0, 2, 3, 4, 6, 1, 2, 3, 5, 7, 0, 1, 2, 4, 6, 0, 1, 3, 5, 7])
col = array([0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7])
A_expected = coo_matrix((data,(row,col)), shape=(8,8)).todense()
B_expected = array([[ 1. , 0. , 0.5],
[ 0. , 1. , -0.5],
[ 1. , 0. , 0.5],
[ 0. , 1. , 0.5],
[ 1. , 0. , -0.5],
[ 0. , 1. , -0.5],
[ 1. , 0. , -0.5],
[ 0. , 1. , 0.5]])
A,B = linear_elasticity( (2,2), E=1e5, nu=0.3 )
assert_almost_equal(A.todense(),A_expected)
assert_almost_equal(B,B_expected)
def test_1x1(self):
A_expected = np.array([[230769.23076923, 0.], [0., 230769.23076923]])
B_expected = np.array([[1, 0, 0], [0, 1, 0]])
A, B = linear_elasticity((1, 1), E=1e5, nu=0.3)
assert_almost_equal(A.toarray(), A_expected)
assert_almost_equal(B, B_expected)
def test_1x1(self):
A_expected = matrix([[230769.23076923, 0.],
[0., 230769.23076923]])
B_expected = array([[1, 0, 0],
[0, 1, 0]])
A, B = linear_elasticity((1, 1), E=1e5, nu=0.3)
assert_almost_equal(A.todense(), A_expected)
assert_almost_equal(B, B_expected)
