def test_chisq(self):
x = 1.
d = {'x': 1, 'a*x': 2}
ls = linsolve.LinearSolver(d, a=1.0, sparse=self.sparse)
sol = ls.solve()
chisq = ls.chisq(sol)
np.testing.assert_equal(chisq, .5)
x = 1.
d = {'x': 1, '1.0*x': 2}
ls = linsolve.LinearSolver(d, sparse=self.sparse)
sol = ls.solve()
chisq = ls.chisq(sol)
np.testing.assert_equal(chisq, .5)
def setUp(self):
eqs = ['x+y', 'x-y']
x, y = 1, 2
d, w = {}, {}
for eq in eqs:
d[eq], w[eq] = eval(eq), 1.
self.ls = linsolve.LinearSolver(d, w)
def test_wgt_const_arrays(self):
x,y = 1.,2.
a,b = 3.*np.ones(4),1.
eqs = ['a*x+y','x+b*y']
d,w = {}, {}
for eq in eqs: d[eq],w[eq] = eval(eq)*np.ones(4), np.ones(4)
ls = linsolve.LinearSolver(d,w,a=a,b=b)
sol = ls.solve()
np.testing.assert_almost_equal(sol['x'], x*np.ones(4,dtype=np.float))
np.testing.assert_almost_equal(sol['y'], y*np.ones(4,dtype=np.float))
def test_solve_arrays(self):
x = np.arange(100,dtype=np.float); x.shape = (10,10)
y = np.arange(100,dtype=np.float); y.shape = (10,10)
eqs = ['2*x+y','-x+3*y']
d,w = {}, {}
for eq in eqs: d[eq],w[eq] = eval(eq), 1.
ls = linsolve.LinearSolver(d,w)
sol = ls.solve()
np.testing.assert_almost_equal(sol['x'], x)
np.testing.assert_almost_equal(sol['y'], y)
def test_const_arrays(self):
x,y = 1.,2.
a = np.array([3.,4,5])
b = np.array([1.,2,3])
eqs = ['a*x+y','x+b*y']
d,w = {}, {}
for eq in eqs: d[eq],w[eq] = eval(eq), 1.
ls = linsolve.LinearSolver(d,w,a=a,b=b)
sol = ls.solve()
np.testing.assert_almost_equal(sol['x'], x*np.ones(3,dtype=np.float))
np.testing.assert_almost_equal(sol['y'], y*np.ones(3,dtype=np.float))
def test_eval(self):
x, y = 1., 2.
a, b = 3. * np.ones(4), 1.
eqs = ['a*x+y', 'x+b*y']
d, w = {}, {}
for eq in eqs:
d[eq], w[eq] = eval(eq) * np.ones(4), np.ones(4)
ls = linsolve.LinearSolver(d, w, a=a, b=b, sparse=self.sparse)
sol = ls.solve()
np.testing.assert_almost_equal(sol['x'],
x * np.ones(4, dtype=np.float))
np.testing.assert_almost_equal(sol['y'],
y * np.ones(4, dtype=np.float))
result = ls.eval(sol)
for eq in d:
np.testing.assert_almost_equal(d[eq], result[eq])
result = ls.eval(sol, 'a*x+b*y')
np.testing.assert_almost_equal(3 * 1 + 1 * 2, result.values()[0])
def test_dtypes(self):
ls = linsolve.LinearSolver({'x_': 1.0 + 1.0j}, sparse=self.sparse)
self.assertEqual(ls.dtype, float)
ls = linsolve.LinearSolver({'x': 1.0 + 1.0j}, sparse=self.sparse)
self.assertEqual(ls.dtype, complex)
ls = linsolve.LinearSolver({'x_': np.ones(1, dtype=np.complex64)[0]},
sparse=self.sparse)
self.assertEqual(ls.dtype, np.float32)
ls = linsolve.LinearSolver({'x': np.ones(1, dtype=np.complex64)[0]},
sparse=self.sparse)
self.assertEqual(ls.dtype, np.complex64)
ls = linsolve.LinearSolver({'c*x': 1.0},
c=1.0 + 1.0j,
sparse=self.sparse)
self.assertEqual(ls.dtype, complex)
d = {'c*x': np.ones(1, dtype=np.float32)[0]}
wgts = {'c*x': np.ones(1, dtype=np.float64)[0]}
c = np.ones(1, dtype=np.float32)[0]
ls = linsolve.LinearSolver(d, wgts=wgts, c=c, sparse=self.sparse)
self.assertEqual(ls.dtype, np.float64)
def test_A_shape(self):
consts = {'a': np.arange(10), 'b': np.zeros((1, 10))}
ls = linsolve.LinearSolver({'a*x+b*y': 0.}, {'a*x+b*y': 1}, **consts)
self.assertEqual(ls._A_shape(), [1, 2, 10, 10])
