File:Wiener-process-trace.svg

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Original file ‎(SVG file, nominally 520 × 340 pixels, file size: 62 KB)

Captions

Captions

A sampled traces of a Wiener process

Summary[edit]

Description
English: A sampled traces of a Wiener process with diffusion σ=1, D=1/2.
Date
Source Own work
Author Geek3
SVG development
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The SVG code is valid.
 
This plot was created with Matplotlib.
Source code
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Matplotlib source code

The plot was generated with Matplotlib 
#! /usr/bin/env python3
# -*- coding:utf8 -*-

import matplotlib.pyplot as plt
import numpy as np
from math import *

plt.rcParams['font.sans-serif'] = 'DejaVu Sans'
np.random.seed(28)

a = 0. # starting value of X
sigma = 1. # diffusion
D = sigma**2 / 2 # diffusion constant
t = np.linspace(0, 3, 3001)

dt = t[1:] - t[:-1]
randnorm = np.random.normal(0, 1, len(t))
X = np.empty_like(t)
X[0] = a

for i in range(len(t) - 1):
    X[i+1] = X[i] + sigma * sqrt(dt[i]) * randnorm[i+1]

fig = plt.figure(figsize=(520 / 90.0, 340 / 90.0), dpi=72)
plt.plot(t, X)
plt.grid(True)
plt.xlim(t[0], t[-1])
plt.ylim(-3, 3)
plt.xlabel('t')
plt.ylabel('X')
plt.tight_layout()
plt.savefig('Wiener-process-trace.svg')

Licensing[edit]

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w:en:Creative Commons
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  • share alike – If you remix, transform, or build upon the material, you must distribute your contributions under the same or compatible license as the original.

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Date/TimeThumbnailDimensionsUserComment
current15:01, 26 November 2022Thumbnail for version as of 15:01, 26 November 2022520 × 340 (62 KB)Geek3 (talk | contribs)Uploaded own work with UploadWizard

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