def strength(self, value):
check_numeric(value, "Strength")
if self.discount < 0:
strength_positive = 1.0 * value / -self.discount <= 0
strength_not_multiple = (1.0 * value / -self.discount) % 1 != 0
if strength_positive or strength_not_multiple:
raise ValueError(
"When discount is negative, strength value must be equal to a multiple of the discount value."
)
elif self.discount < 1:
if value <= -self.discount:
raise ValueError(
"When discount is between 0 and 1, strength value must be greater than the negative of the discount"
)
self._strength = value
def _sample(self, n, initial=1.0):
"""Generate a realization of a diffusion process using Euler-Maruyama."""
check_positive_integer(n)
check_numeric(initial, "Initial")
delta_t = 1.0 * self.t / n
gns = self._sample_gaussian_noise(n)
s = [initial]
t = 0
for k in range(n):
t += delta_t
initial += (self._speed(t) * (self._mean(t) - initial) * delta_t +
self._vol(t) * initial**self._volexp(initial) * gns[k])
s.append(initial)
return np.array(s)
def drift(self, value):
check_numeric(value, "Drift")
self._drift = value
def discount(self, value):
check_numeric(value, "Discount")
if value >= 1:
raise ValueError("Discount value must be less than 1.")
self._discount = value
def beta(self, value):
check_numeric(value, "beta")
self._beta = value
def test_check_numeric(number_fixture, parameter_name_fixture):
if not isinstance(number_fixture, (int, float)):
with pytest.raises(TypeError):
check_numeric(number_fixture, parameter_name_fixture)
else:
assert check_numeric(number_fixture, parameter_name_fixture) is None
def drift(self, value):
check_numeric(value, "Drift coefficient.")
self._drift = ensure_single_arg_constant_function(value)
self.speed = ensure_single_arg_constant_function(-value)
def b(self, value):
check_numeric(value, "Time end")
self._b = value
