monteCarloRun

R2026b

Monte Carlo realization of tracking scenario

Syntax

recordings = monteCarloRun(scenario,numRuns)

recordings = monteCarloRun(scenario,numRuns,Name,Value)

[recordings,rngs] = monteCarloRun(___)

Description

recordings = monteCarloRun(scenario,numRuns) runs a tracking scenario multiple times and saves the running recording of every run. Each run, called a realization of the scenario, is with a different random seed.

recordings = monteCarloRun(scenario,numRuns,Name,Value) specifies options using one or more name-value pair arguments. Enclose each Name in quotes.

[recordings,rngs] = monteCarloRun(___) also returns the random number generator values at the beginning of each realization run.

Examples

Run Scenario Twice with Automatic Random Seeds

Load a prerecorded tracking scenario.

  load ATCScenario.mat scenario

Execute two Monte Carlo runs and display the running time. The actual running time will depend on the computation ability of your machine.

  tic
  recordings = monteCarloRun(scenario,2);
  disp("Time to run the scenarios: " + toc + " sec")

Time to run the scenarios: 153.2316 sec

Run the Monte Carlo simulations again using parallel computing.

  tic
  recordings = monteCarloRun(scenario,2,'UseParallel',true);

Starting parallel pool (parpool) using the 'local' profile ...
Connected to the parallel pool (number of workers: 6).

  disp("Time to run the scenarios in parallel: " + toc + " sec")

Time to run the scenarios in parallel: 118.1509 sec

Input Arguments

scenario — Tracking scenario

M-element array of trackingScenario objects | M-element cell array of trackingScenario objects

Tracking scenario, specified as an M-element array of trackingScenario objects or an M-element cell array of trackingScenario objects.

numRuns — Number of Monte Carlo runs

positive integer

Numbers of Monte Carlo runs, specified as a positive integer.

Name-Value Arguments

Specify optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

Before R2021a, use commas to separate each name and value, and enclose Name in quotes.

Example: monteCarloRun(sc,3,UseParallel="auto")

UseParallel — Option to perform computations in parallel

"off" (default) | "auto" | "on"

Option to perform computations in parallel using a parallel pool of workers, specified as one of these values:

• "off" — Run in serial on the MATLAB client.

• "auto" — Use a parallel pool if one is open or if MATLAB can automatically create one. If a parallel pool is not available, run in serial on the MATLAB client.

• "on" — Use a parallel pool if one is open or if MATLAB can automatically create one. If a parallel pool is not available, throw an error.

If you do not have a parallel pool open and automatic pool creation is enabled, MATLAB opens a pool using the default cluster profile. To use a parallel pool to run computations in MATLAB, you must have Parallel Computing Toolbox™. For more information, see Run MATLAB Functions with Automatic Parallel Support (Parallel Computing Toolbox).

Before R2026b: To run in parallel, set UseParallel to true (1).

Data Types: char | string

InitialSeeds — Initial random seeds

integer in [0, 2^32-1] | numRuns-element array of integers in [0, 2^32-1]

Initial random seeds for obtaining repeatable results, specified as an integer in [0, 2^32-1] or an array of integers in [0, 2^32-1]. If specified as an integer, an array of seed values is randomly generated using the integer as an initial seed. If unspecified, the function uses the current random number generator to randomly generate an array of initial seeds.

Output Arguments

recordings — Monte Carlo recordings of tracking scenario

M-by-numRuns array of trackingScenarioRecording objects

Monte Carlo recordings of a tracking scenario, returned as a M-by-numRuns array of trackingScenarioRecording objects.

rngs — Random number generator values

M-by-numRuns array of structures

Random number generator values, returned as a M-by-numRuns array of structures. The fields of each structure are the same as the output of the rng function.

Extended Capabilities

Automatic Parallel Support

Accelerate code by automatically running computation in parallel using Parallel Computing Toolbox™. (since R2026b)

Accelerate code by automatically running computation in parallel using Parallel Computing Toolbox. (since R2026b)

The monteCarloRun function has automatic parallel support. To run computations in parallel, set the UseParallel argument to "on" or "auto". For more information, see Run MATLAB Functions with Automatic Parallel Support (Parallel Computing Toolbox).

Version History

Introduced in R2020a

R2026b: Enhanced control over parallel execution with UseParallel argument

The UseParallel name-value argument now accepts "off", "auto", or "on" values instead of true or false. This change gives you more control over when to use a parallel pool for parallel execution.

Specifying the UseParallel name-value argument as true or false is not recommended.

Goal	Not recommended	Recommended
Write code that runs on the MATLAB client.	monteCarloRun(UseParallel=false)	monteCarloRun(UseParallel="off") (default)
Write portable code that runs on a parallel pool and, if a pool is not available, runs on the MATLAB client.	monteCarloRun(UseParallel=true)	monteCarloRun(UseParallel="auto")
Write code that runs on a parallel pool and errors if a pool is not available.	N/A	monteCarloRun(UseParallel="on")

There are no plans to remove support for the true or false values.