dlCHOMPDataOptions

Options for generating training and validation data samples

Since R2024a

Description

The dlCHOMPDataOptions object enables you to specify options for generating training and validation samples using the generateSamples function.

The dlCHOMPDataOptions object requires Deep Learning Toolbox™.

Creation

Syntax

opts = dlCHOMPDataOptions

opts = dlCHOMPDataOptions(Name=Value)

Description

opts = dlCHOMPDataOptions returns default options for generating training and validation samples.

opts = dlCHOMPDataOptions(Name=Value) specifies properties using one or more name-value arguments. The properties specify options for generating training and validation samples.

Properties

RadiusRangeOfObstacles — Radius range for spherical obstacles in sample generation environment

[0.2 0.5] (default) | two-element vector of positive scalars

Radius range for the spherical obstacles in the sample generation environment, specified as a two-element vector of positive scalars, in the form [MinimumRadius MaximumRadius]. The value of MaximumRadius must be greater than the value of MinimumRadius.

Set RadiusRangeOfObstacles based on the size of obstacles in the robot workspace.

Each of the obstacles in each of the data sample JSON files that generateSamples generates during the environment-creation phase has a radius at a random position within the specified radius range based on the RandomStream and Seed property values.

CountRangeOfObstacles — Minimum and maximum number of spherical obstacles in sample generation environment

[20 30] (default) | two-element vector of positive integers

Minimum and maximum number of spherical obstacles in the sample generation environment, specified as a two-element vector of positive scalars, in the form [MinNumSpheres MinNumSpheres]. The value of MaxNumSpheres must be greater than the value of MinNumSpheres.

Set CountRangeOfObstacles based on the number of and size of obstacles in the robot workspace.

The number of obstacles in each of the data sample JSON files that generateSamples generates during the environment-creation phase is a random integer in the specified range based on the RandomStream and Seed property values.

MinDistanceFromBase — Minimum distance of spherical obstacles from robot base in sample generation environment

0.2 (default) | positive numeric scalar

Minimum distance of spherical obstacles from the robot base in the sample generation environment, specified as a positive numeric scalar. The distance is measured from the origin of the robot base to the surface mesh of an obstacle, in meters.

NumSamples — Number of samples to generate

2000 (default) | positive integer

Number of samples to generate, specified as a positive integer.

ValidationSplit — Percentage of training samples to include in validation data set

0.2 (default) | numeric scalar in range [0, 1]

Percentage of training samples to include in the validation data set, specified as a numeric scalar in the range [0, 1].

RandomStream — Random number algorithm for sample generation

"threefry" (default) | "global"

Random number algorithm for sample generation, specified as either "threefry" or "global".

• "threefry" — Use the Threefry 4x64 generator with 20 rounds.

• "global" — Use the global random number stream. You can get and set the global number stream using the RandStream.getGlobalStream and RandStream.setGlobalStream functions, respectively. When RandomStream is set to "global", the dlCHOMPDataOptions object ignores the Seed property.

For more information on generator algorithms, see Creating and Controlling a Random Number Stream.

Seed — Random number seed

0 (default) | nonnegative integer

Random number seed, specified as a nonnegative integer.

Version History

Introduced in R2024a