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Brownian Motion#
Simulate and visualise paths
# Author: Dialid Santiago <d.santiago@outlook.com>
# License: MIT
# Description: Simulate and visualise a Brownian Motion
from aleatory.processes import BrownianMotion
from aleatory.styles import qp_style
qp_style() # Use quant-pastel-style
process = BrownianMotion()
fig = process.draw(n=100, N=200, figsize=(12, 7), dpi=150)
fig.show()
![Brownian Motion, Monte Carlo Simulated Paths $\{{X_t, t \in [t_0, T]\}}$, $X_T$ Marginal](../_images/sphx_glr_plot_brownian_motion_001.png)
process = BrownianMotion()
fig = process.plot(n=100, N=10, figsize=(12, 7), dpi=250)
fig.show()
process = BrownianMotion()
fig = process.plot_paths_and_kernel(n=100, N=5)
fig.show()
Total running time of the script: (0 minutes 5.548 seconds)