stoch 1.0.0

Stochastic Process

stoch: a package for stochastic calculations

Generators of stochastic process

• gaussian_process(mean=0, std=1, dt=1, size=None)

• ornstein_uhlenbeck_process(x0=0, mu=0, theta=1, sigma=1, dt=1, size=None)

Note: The parameter size follows the convention in numpy. When it is None, it generates float; When it is int(s), it generates np.array of shape size.

Usage Examples

from stoch import gaussian_process, ornstein_uhlenbeck_process
gen = gaussian_process(mean=0, std=0.1, dt=0.01)  # generate scaler
gen = gaussian_process(mean=0, std=0.1, dt=0.01, size=(2, 4))  # generate np.array of shape (2, 4)
gen = ornstein_uhlenbeck_process(x0=0., mu=0.1, theta=0.5, sigma=0.3, dt=0.01)  # generate scaler
gen = ornstein_uhlenbeck_process(x0=0., mu=0.1, theta=0.5, sigma=0.3, dt=0.01, size=3)  # generate np.array of shape (3,)
for i in range(10):
    print(next(gen))