def test_parameter_arithmetic(self, p, q):
"""Test parameter arithmetic works as expected,"""
pp = FreeParameter("x")
qq = FreeParameter("y")
pp.val = p
qq.val = q
binary_arithmetic(pp, qq, p, q)
def test_par_evaluate_dtype_TF(self, p, dtype):
"""Test the TF parameter evaluation works when a dtype is provided"""
pytest.importorskip("tensorflow", minversion="2.0")
import tensorflow as tf
x = FreeParameter("x")
x.val = tf.Variable(p)
res = par_evaluate(x, dtype=dtype)
assert res.dtype is tf.as_dtype(dtype)
def test_par_evaluate(self, p):
x = FreeParameter("x")
with pytest.raises(ParameterError, match="unbound parameter with no default value"):
par_evaluate(x)
# val only
x.val = p
assert np.all(par_evaluate(x) == p)
# default only
x.val = None
x.default = p
assert np.all(par_evaluate(x) == p)
# both val and default
x.val = p
x.default = 0.0
assert np.all(par_evaluate(x) == p)
def test_parameter_unary_negation(self, p):
"""Test unary negation works as expected."""
pp = FreeParameter("x")
pp.val = p
assert par_evaluate(-p) == pytest.approx(-p)
assert par_evaluate(-pp) == pytest.approx(-p)
def test_parameter_right_literal_arithmetic(self, p, q):
"""Test parameter arithmetic works as expected."""
pp = FreeParameter("x")
pp.val = p
binary_arithmetic(pp, q, p, q)
def test_parameter_left_literal_arithmetic(self, p, q):
"""Test parameter arithmetic works as expected."""
qq = FreeParameter("x")
qq.val = q
binary_arithmetic(p, qq, p, q)
def test_par_evaluate_dtype_numpy(self, p, dtype):
"""Test the numpy parameter evaluation works when a dtype is provided"""
x = FreeParameter("x")
x.val = p
res = par_evaluate(x, dtype=dtype)
assert res.dtype.type is dtype