Dataset object (Multivariate Analysis Toolbox for Matlab®)

A dataset typically comprises a collection of many different core objects (variables, groupings, and samplesets). For example, during the initial phase of a project, many versions of the data may be kept simultaneously. The dataset serves as a repository, keeping the raw data. Typically, before an actual analysis begins, a more structured object, like datamatrix, is extracted.

Navigate to:     General Description     Class Structure     Class Construction     Class Functions

Each field can be accessed by the dot (.) operation, or by the GET function. Most fields can be modified using the SET function, except for those designated as READ-ONLY which are computed automatically by the class methods and cannot be handled by the user. Some fields, which we found to be more commonly accessed, have specific SET/GET functions that are listed in the table.

		Field	Description	Type	Default	Dedicated Get/Set Function
		name	name of object, should be short and used as identifier. This field can never be empty.	string	'unnamed'
		description	verbal description of the class content.	string	''
		source	verbal description of the source of information.	string	''
		variables	a vector of length nv, holding the variables aggregated in the dataset.	vector of variables	[]	variables
	read only	no_variables	a vector [nnom nord nnum nunk nv], indicating the number of nominal variables, ordinal variables, numerical variables, variables of unknown level, and the number of total variables, respectively.	5-vector of nonnegative integers	[0 0 0 0 0]	novariables
		groupings	a vector of length ng, holding the groupings aggregated in the dataset.	vector of groupings	[]
	read only	no_groupings	number of groupings, ng. Set to zero for void objects.	integer scalar	0	nogroupings
		samplesets	a vector of length ns, holding the samplesets aggregated in the dataset.	vector of samplesets	[]	samplesets
	read only	no_samplesets	number of samplesets, ns. Set to zero for void objects.	integer scalar	0	nosamplesets
		matrix	a vector of length nm, holding the datamatrices aggregated in the dataset.	vector of datamatrices	[]
	read only	no_matrices	number of datamatrices, nm. Set to zero for void objects.	integer scalar	0
		var2sampset	a vector of length nv, holding for each variable the ID of its corresponding sampleset.	vector of nonnegative integers	[]
		grp2sampset	a vector of length ng, holding for each grouping the ID of its corresponding sampleset.	vector of nonnegative integers	[]

Empty instance (scalar)

an empty dataset instance, with all fields initialized to their default values.

syntax: ds = dataset;

Empty instance (vector)

a vector of empty dataset instances.

syntax: ds = dataset(no_instances);

Copy constructor

a dataset instance is copied into another.

syntax: ds_destination = dataset(ds_origin);

Construction by field names

an instance is formed by directly providing field values. Any field which is not read-only is permitted.

syntax: ds = dataset(field_name, field_value, ...);

example: ds = dataset('name','demo dataset', 'description','no data inside');

Computations:

correlate

computes covariance/correlation matrix

Constructors:

dataset

constructor method

Display functions:

display

display method

Housekeeping functions:

grpname2grpidx

index of groupings in dataset by their name

guessgrp2sampset

guess the mapping of groupings to their sampleset

guessvar2sampset

guess the mapping of variables to their sampleset

ssname2ssidx

index of samplesets in dataset by their name

varname2varidx

index of variables in dataset by their name

Indexing:

end

end keyword

instance

extracts a specific instance from a dataset array

subsref

basic indexing method

Operators:

deletesamples

eliminate samples from a dataset instance

deletevariables

eliminate variables from a dataset instance

+ (plus)

adds samplesets, variables and groupings to a dataset

SET/GET functions:

get

get method

nogroupings

number of groupings in dataset(s)

nosamples

number of samples in the different variables

nosamplesets

number of samplesets in dataset(s)

novariables

number of variables of a specific type

samplenames

sample names of a specific sampleset

samplesets

samplesets of dataset(s)

set

set method

variables

variables of dataset(s)