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))
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Metadata
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Release files for stoch 1.0.0
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