LabRPS at 01:13, 26 January 2025

2025-01-26T01:13:50Z

← Older revision		Revision as of 18:13, 25 January 2025
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	This feature aims to simulate a random walk simulation with different options and further implementations. The main implementations are:		This feature aims to simulate a random walk simulation with different options and further implementations. The main implementations are:

	1# Simulation of multiple random walkers with different speeds		# Simulation of multiple random walkers with different speeds
	2# High randomization of speeds, start points, colorization etc.		# High randomization of speeds, start points, colorization etc.
	3# Enabling options to simulate the random walk of your needs like different neighborhood movement patterns (Neumann/Moore), enabling random start points, running the code multiple times, saving the plot and/or results automatically...		# Enabling options to simulate the random walk of your needs like different neighborhood movement patterns (Neumann/Moore), enabling random start points, running the code multiple times, saving the plot and/or results automatically...

	=== Properties ===		=== Properties ===
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	import GeneralToolsGui		import GeneralToolsGui

	~~# Before you run this macro, simulation must be run and there must be a table containing the simulated wind velocities.~~
	def simulateRandomWalk():		def simulateRandomWalk():
	#install the UserLab plugin with all its plugged features		#install the UserLab plugin with all its plugged features

LabRPS: Created page with "{{Plugin |Name=Random Walk Plugin |Description=This plugin implements tools for the simulation of random walk. |Author=Koffi Daniel |Version=1.0 |Date=21/12/2024 |Features= Random Walk |RPSVersion=All }} == Introduction == A random walk is a mathematical object, known as a stochastic or random process, that describes a path that consists of a succession of random steps on some mathematical space such as the integers. An elementary example of a random..."

2025-01-26T01:04:31Z

Created page with "{{Plugin |Name=Random Walk Plugin |Description=This plugin implements tools for the simulation of random walk. |Author=Koffi Daniel |Version=1.0 |Date=21/12/2024 |Features= Random Walk |RPSVersion=All }} == Introduction == A random walk is a mathematical object, known as a stochastic or random process, that describes a path that consists of a succession of random steps on some mathematical space such as the integers. An elementary example of a random..."

New page

{{Plugin
|Name=Random Walk Plugin
|Description=This plugin implements tools for the simulation of random walk.
|Author=Koffi Daniel
|Version=1.0
|Date=21/12/2024
|Features= [[#Random_Walk|Random Walk]]

|RPSVersion=All
}}

== Introduction ==
A random walk is a mathematical object, known as a stochastic or random process, that describes a path that consists of a succession of random steps on some mathematical space such as the integers. An elementary example of a random walk is the random walk on the integer number line, which starts at 0 and at each step moves +1 or -1 with equal probability [https://www.geeksforgeeks.org/random-walk-implementation-python/ (Source)].

[[Image:Plugin_UserLab_RandomWalk_Screenshot_1.png|1024px]]

== QBlade Methods ==
This feature aims to simulate a random walk simulation with different options and further implementations. The main implementations are:

1# Simulation of multiple random walkers with different speeds
2# High randomization of speeds, start points, colorization etc.
3# Enabling options to simulate the random walk of your needs like different neighborhood movement patterns (Neumann/Moore), enabling random start points, running the code multiple times, saving the plot and/or results automatically...

=== Properties ===

* {{PropertyData|TotalSteps}}: Number of total steps every walker shall take.
* {{PropertyData|NumberOfWalker}}: Number of total walkers to be created.
* {{PropertyData|MovePattern}}: Choose neighborhood movement pattern between Neumann (4 directions) or Moore (8 directions).
* {{PropertyData|RandomStart}}: Do you want different (random) start points for each walker or let all plots start at 0,0?.

=== Scripting ===

{{Code|code=
import numpy as np
import math
import time
import matplotlib.pyplot as plt
import LabRPS
import UserLabObjects
import UserLabGui
import UserLab
import GeneralToolsGui

# Before you run this macro, simulation must be run and there must be a table containing the simulated wind velocities.
def simulateRandomWalk():
#install the UserLab plugin with all its plugged features
installResuslt = UserLab.installPlugin("RandomWalkPlugin")

# create new document
doc = LabRPS.newDocument()

# create new simulation with default name "Simulation" in the above document
sim = UserLabObjects.makeSimulation(doc)

# check if the simulation is successfully created
if not sim:
LabRPS.Console.PrintError("The simulation does not exist.\n")

# create the random walk plugin
randomWalk = UserLabObjects.makeFeature("randomWalk", sim.Name, "Random Walk", "Simulation Method")
randomWalk.TotalSteps = 1000
randomWalk.NumberOfWalker = 2

# check if the created tool is good
if not randomWalk:
LabRPS.Console.PrintError("The creation of the random walk simulation method was not successuful.\n")
return None

# run the tool
sim.setActiveFeature(randomWalk)
# Run simulation and output the first(0) sample
# store starting time
begin = time.time()
wlks = sim.simulate(0)
# store end time
end = time.time()
LabRPS.Console.PrintMessage(f"Total runtime of the simulaltion is {end - begin} seconds\n")

if LabRPS.GuiUp:
import UserLabGui
import GeneralToolsGui
UserLabGui.setActiveSimulation(sim)
GeneralToolsGui.GeneralToolsPyTool.showArray(1 + int(randomWalk.TotalSteps), 2*int(randomWalk.NumberOfWalker), wlks, True)
import numpy
arr = numpy.asarray(wlks)
w = 0
plot_walker_path(int(randomWalk.NumberOfWalker), arr[:,w], arr[:,w+1], 1, 1, True, w+1)
plot_walker_path(int(randomWalk.NumberOfWalker), arr[:,w+2], arr[:,w+3], 1, 1, True, w+2)
plot_all_walkers(int(randomWalk.TotalSteps), int(randomWalk.NumberOfWalker), False, int(sim.NumberOfSample))

def plot_walker_path(n_walkers, x, y, walker_type, walker_speed, random_start, plottedNumber):
"""Plot the coords of every step"""
ax = plt.gca() # get current axes
next_col = next(ax._get_lines.prop_cycler)["color"] # iterate through colors
plt.plot(
x,
y,
alpha=0.33,
lw=2,
color=next_col,
label="Walker {}".format(plottedNumber),
)
plt.scatter(x, y, color=next_col, alpha=1, s=2)
if n_walkers <= 12:
ax.legend(fontsize="small", framealpha=0.4, markerscale=1.5)
else:
pass
if random_start == "true":
plt.scatter(
x[0],
y[0],
marker="P",
s=100,
color=next_col,
edgecolors="black",
)
else:
plt.scatter(
0,
0,
marker="P",
s=100,
color="white",
edgecolors="black",
)
plt.scatter(
x[-1],
y[-1],
marker="X",
s=100,
color=next_col,
edgecolors="black",
)

def plot_all_walkers(steps, n_walkers, want_plot_saved, run_num):
"""Generate plot with precalculated paths and show them together in a plot"""
if n_walkers == 1:
plt.title(
"{} walker with {} steps simulated".format(
n_walkers, steps
)
)
else:
plt.title(
"{} walkers with {} steps simulated".format(
n_walkers, steps
)
)
# insert annotation with start and end point
plt.annotate(
"Start points: +\nEnd points: x",
xy=(0, 0),
xytext=(5, 5),
xycoords="figure points",
)

plt.show()

simulateRandomWalk()
}}

Plugin UserLab RandomWalk - Revision history

LabRPS at 01:13, 26 January 2025