def test_default(self):
# No value specified for x[1], should be 0
x = piecewise([[True, False]], [2], [1, 2],)
assert_allclose(x, [2, 0])
# Should set x[1] to 3
x = piecewise([[True, False]], [2, 3], [1, 2])
assert_allclose(x, [2, 3])
def test_default(self):
# No value specified for x[1], should be 0
x = piecewise([[True, False]], [2], [1, 2],)
assert_array_equal(x, [2, 0])
# Should set x[1] to 3
x = piecewise([[True, False]], [2, 3], [1, 2])
assert_array_equal(x, [2, 3])
def test_0d(self):
x = np.array(3)
y = piecewise([x > 3], [4, 0], x)
assert_(y.ndim == 0)
assert_(y == 0)
x = 5
y = piecewise([[True], [False]], [1, 0], x)
assert_(y == 1)
assert_(y.ndim == 0)
def test_0d(self):
x = np.array(3)
y = piecewise(x, [x > 3], [4, 0])
assert_(y.ndim == 0)
assert_(y == 0)
x = 5
y = piecewise(x, [[True], [False]], [1, 0])
assert_(y.ndim == 0)
assert_(y == 1)
def test_0d(self):
x = np.array(3)
y = piecewise([x > 3], [4, 0], x)
assert y.ndim == 0
assert y == 0
x = 5
y = piecewise([[True], [False]], [1, 0], x)
assert y == 1
assert y.ndim == 0
def test_function_with_two_args(self):
x = np.linspace(-2, 2, 5)
X, Y = np.meshgrid(x, x)
vals = piecewise([X * Y < 0, ], [lambda x, y: -x * y, lambda x, y: x * y], (X, Y))
assert_allclose(vals, [[4., 2., -0., 2., 4.],
[2., 1., -0., 1., 2.],
[-0., -0., 0., 0., 0.],
[2., 1., 0., 1., 2.],
[4., 2., 0., 2., 4.]])
def adaptive_levin_points(M, delta):
m = M - 1
prm = 0.5
while prm * m / delta >= 1:
delta = 2 * delta
k = np.arange(M)
x = piecewise([k < prm * m, k == np.ceil(prm * m)],
[-1 + k / delta, 0 * k, 1 - (m - k) / delta])
return x
def adaptive_levin_points(m, delta):
m_1 = m - 1
prm = 0.5
while prm * m_1 / delta >= 1:
delta = 2 * delta
k = np.arange(m)
x = piecewise([k < prm * m_1, k == np.ceil(prm * m_1)],
[-1 + k / delta, 0 * k, 1 - (m_1 - k) / delta])
return x
def test_passing_further_args_to_fun(self):
def fun0(x, y, scale=1.):
return -x * y / scale
def fun1(x, y, scale=1.):
return x * y / scale
x = np.linspace(-2.5, 2.5, 6)
vals = piecewise([x < 0, ], [fun0, fun1], (x,), args=(2.,), scale=2.)
assert_array_equal(vals, [2.5, 1.5, 0.5, 0.5, 1.5, 2.5])
def test_passing_further_args_to_fun(self):
def fun0(x, y, scale=1.):
return -x * y / scale
def fun1(x, y, scale=1.):
return x * y / scale
x = np.linspace(-2.5, 2.5, 6)
vals = piecewise([x < 0, ], [fun0, fun1], (x,), args=(2.,), scale=2.)
assert_allclose(vals, [2.5, 1.5, 0.5, 0.5, 1.5, 2.5])
def adaptive_levin_points(M, delta):
m = M - 1
prm = 0.5
while prm * m / delta >= 1:
delta = 2 * delta
k = np.arange(M)
x = piecewise([k < prm * m, k == np.ceil(prm * m)],
[-1 + k / delta, 0 * k, 1 - (m - k) / delta])
return x
def test_function_with_two_args(self):
x = np.linspace(-2, 2, 5)
X, Y = np.meshgrid(x, x)
vals = piecewise(
[X * Y < 0, ], [lambda x, y: -x * y, lambda x, y: x * y], (X, Y))
assert_array_equal(vals, [[4., 2., -0., 2., 4.],
[2., 1., -0., 1., 2.],
[-0., -0., 0., 0., 0.],
[2., 1., 0., 1., 2.],
[4., 2., 0., 2., 4.]])
def test_fill_value2_and_function_with_two_args(self):
x = np.linspace(-2, 2, 5)
X, Y = np.meshgrid(x, x)
vals = piecewise((X, Y), [X * Y < -0.5, X * Y > 0.5],
[lambda x, y: -x * y, lambda x, y: x * y, np.nan])
nan = np.nan
assert_array_equal(vals, [[4., 2., nan, 2., 4.],
[2., 1., nan, 1., 2.],
[nan, nan, nan, nan, nan],
[2., 1., nan, 1., 2.],
[4., 2., nan, 2., 4.]])
def test_fill_value2_and_function_with_two_args(self):
x = np.linspace(-2, 2, 5)
X, Y = np.meshgrid(x, x)
vals = piecewise([X * Y < -0.5, X * Y > 0.5],
[lambda x, y: -x * y, lambda x, y: x * y, np.nan],
(X, Y))
nan = np.nan
assert_array_equal(vals,
[[4., 2., nan, 2., 4.], [2., 1., nan, 1., 2.],
[nan, nan, nan, nan, nan], [2., 1., nan, 1., 2.],
[4., 2., nan, 2., 4.]])
def test_condition_is_list_of_single_int_array(self):
x = piecewise([np.array([1, 0])], [1], [0, 0])
assert_allclose(x, [1, 0])
def test_conditions_is_list_of_single_bool_array(self):
x = piecewise([np.array([True, False])], [1], [0, 0])
assert_allclose(x, [1, 0])
def test_condition_is_list_of_single_bool_list(self):
x = piecewise([[True, False]], [1], [0, 0])
assert_allclose(x, [1, 0])
def test_abs_function(self):
x = np.linspace(-2.5, 2.5, 6)
vals = piecewise([x < 0, x >= 0], [lambda x: -x, lambda x: x], (x,))
assert_array_equal(vals,
[2.5, 1.5, 0.5, 0.5, 1.5, 2.5])
def test_conditions_is_list_of_single_bool_array(self):
x = piecewise([np.array([True, False])], [1], [0, 0])
assert_array_equal(x, [1, 0])
def test_abs_function_with_scalar(self):
x = np.array(-2.5)
vals = piecewise([x < 0, x >= 0], [lambda x: -x, lambda x: x], (x,))
assert vals == 2.5
def test_condition_is_list_of_single_int_array(self):
x = piecewise([0, 0], [np.array([1, 0])], [1])
assert_array_equal(x, [1, 0])
def test_simple(self):
x = piecewise([[False, True]], [lambda x:-1], [0, 0])
assert_array_equal(x, [0, -1])
x = piecewise([[True, False], [False, True]], [3, 4], [1, 2])
assert_array_equal(x, [3, 4])
def test_condition_is_list_of_single_bool_list(self):
x = piecewise([0, 0], [[True, False]], [1])
assert_array_equal(x, [1, 0])
def test_step_function(self):
x = np.linspace(-2.5, 2.5, 6)
vals = piecewise([x < 0, x >= 0], [-1, 1], x)
assert_array_equal(vals, [-1., -1., -1., 1., 1., 1.])
def test_step_function(self):
x = np.linspace(-2.5, 2.5, 6)
vals = piecewise(x, [x < 0, x >= 0], [-1, 1])
assert_array_equal(vals, [-1., -1., -1., 1., 1., 1.])
def test_otherwise_condition(self):
x = np.linspace(-2.5, 2.5, 6)
vals = piecewise([x < 0, ], [lambda x: -x, lambda x: x], (x,))
assert_array_equal(vals, [2.5, 1.5, 0.5, 0.5, 1.5, 2.5])
def test_abs_function_with_scalar(self):
x = np.array(-2.5)
vals = piecewise([x < 0, x >= 0], [lambda x: -x, lambda x: x], (x,))
assert_(vals == 2.5)
def test_simple(self):
x = piecewise([[False, True]], [lambda _: -1], [0, 0])
assert_allclose(x, [0, -1])
x = piecewise([[True, False], [False, True]], [3, 4], [1, 2])
assert_allclose(x, [3, 4])
def test_abs_function(self):
x = np.linspace(-2.5, 2.5, 6)
vals = piecewise((x,), [x < 0, x >= 0], [lambda x: -x, lambda x: x])
assert_array_equal(vals,
[2.5, 1.5, 0.5, 0.5, 1.5, 2.5])
def test_step_function_with_scalar(self):
x = 1
vals = piecewise([x < 0, x >= 0], [-1, 1], x)
assert vals == 1
def test_abs_function(self):
x = np.linspace(-2.5, 2.5, 6)
vals = piecewise([x < 0, x >= 0], [lambda x: -x, lambda x: x], (x,))
assert_allclose(vals, [2.5, 1.5, 0.5, 0.5, 1.5, 2.5])
def test_condition_is_list_of_single_bool_list(self):
x = piecewise([[True, False]], [1], [0, 0])
assert_array_equal(x, [1, 0])
def test_otherwise_condition(self):
x = np.linspace(-2.5, 2.5, 6)
vals = piecewise([x < 0, ], [lambda x: -x, lambda x: x], (x,))
assert_allclose(vals, [2.5, 1.5, 0.5, 0.5, 1.5, 2.5])
def test_condition_is_list_of_single_int_array(self):
x = piecewise([np.array([1, 0])], [1], [0, 0])
assert_array_equal(x, [1, 0])
def test_step_function(self):
x = np.linspace(-2.5, 2.5, 6)
vals = piecewise([x < 0, x >= 0], [-1, 1], x)
assert_allclose(vals, [-1., -1., -1., 1., 1., 1.])
def test_otherwise_condition(self):
x = np.linspace(-2.5, 2.5, 6)
vals = piecewise((x,), [x < 0, ], [lambda x: -x, lambda x: x])
assert_array_equal(vals, [2.5, 1.5, 0.5, 0.5, 1.5, 2.5])
def test_step_function_with_scalar(self):
x = 1
vals = piecewise([x < 0, x >= 0], [-1, 1], x)
assert_(vals == 1)
def test_simple(self):
x = piecewise([[False, True]], [lambda x: -1], [0, 0])
assert_array_equal(x, [0, -1])
x = piecewise([[True, False], [False, True]], [3, 4], [1, 2])
assert_array_equal(x, [3, 4])
