CreateMonteCarloWorkspace v1

Summary

Creates a randomly simulated workspace by sampling from the probability distribution of input data.

Properties

Name	Direction	Type	Default	Description
InputWorkspace	Input	MatrixWorkspace	Mandatory	Input Workspace containing data to be simulated
Seed	Input	number	32	Integer seed that initialises the random-number generator, for reproducibility
MonteCarloEvents	Input	number	0	Number of Monte Carlo events to simulate. Defaults to integral of input workspace if 0.
OutputWorkspace	Output	MatrixWorkspace	Mandatory	Name of output workspace.

Description

The algorithm generates a simulated workspace by sampling from the probability distribution of input data, useful for testing of fitting functions and modeling.

Usage

Example - CreateMonteCarloWorkspace

# import mantid algorithms, numpy and matplotlib
from mantid.simpleapi import *
import matplotlib.pyplot as plt
import numpy as np
from mantid.api import FunctionFactory

func = FunctionWrapper(FunctionFactory.createInitialized("name=BackToBackExponential,I=25000,A=0.06,B=0.015,X0=30000,S=30;name=FlatBackground,A0=50"))
# create input workspace
x = np.linspace(29650.0, 30500.0, 201)
y = func(x)
e = np.sqrt(y)
ws = CreateWorkspace(DataX=x, DataY=y, DataE=e, UnitX="TOF")
# call algorithm
ws_mc = CreateMonteCarloWorkspace(InputWorkspace=ws, Seed=0)

fig, axes = plt.subplots(subplot_kw={'projection': 'mantid'})
axes.plot(ws, label='input', wkspIndex=0)
axes.plot(ws_mc, label='CreateMonteCarloWorkspace output', wkspIndex=0, alpha=0.75)
legend = axes.legend(fontsize=8.0).set_draggable(True).legend
fig.show()

Categories: AlgorithmIndex | Simulation

Source

C++ header: CreateMonteCarloWorkspace.h

C++ source: CreateMonteCarloWorkspace.cpp