SparseSet: R6 class for a fuzzy set with sparse internal representation

In neuroimaginador/fcaR: Formal Concept Analysis

Description

This class implements the data structure and methods for fuzzy sets.

Methods

Public methods

• SparseSet$new()

• SparseSet$assign()

• SparseSet$[()

• SparseSet$cardinal()

• SparseSet$get_vector()

• SparseSet$get_attributes()

• SparseSet$length()

• SparseSet$print()

• SparseSet$to_latex()

• SparseSet$clone()

---

Method new()

Creator for objects of class SparseSet

Usage

SparseSet$new(attributes, M = NULL)

Arguments

attributes

(character vector) Names of the attributes that will be available in the fuzzy set.

M

(numeric vector or column Matrix) Values (grades) to be assigned to the attributes.

Details

If M is omitted, the fuzzy set is the empty set. Later, one can use the assign method to assign grades to any of its attributes.

Returns

An object of class SparseSet.

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Method assign()

Assign grades to attributes in the set

Usage

SparseSet$assign(attributes = c(), values = c(), ...)

Arguments

attributes

(character vector) Names of the attributes to assign a grade to.

values

(numeric vector) Grades to be assigned to the previous attributes.

...

key = value pairs, where the value value is assigned to the key attribute name.

Details

One can use both of: S$assign(A = 1, B = 0.3) S$assign(attributes = c(A, B), values = c(1, 0.3)).

---

Method [()

Get elements by index

Usage

SparseSet$[(indices)

Arguments

indices

(numeric, logical or character vector) The indices of the elements to return. It can be a vector of logicals where TRUE elements are to be retained.

Returns

A SparseSet but with only the required elements.

---

Method cardinal()

Cardinal of the SparseSet

Usage

SparseSet$cardinal()

Returns

the cardinal of the SparseSet, counted as the sum of the degrees of each element.

---

Method get_vector()

Internal Matrix

Usage

SparseSet$get_vector()

Returns

The internal sparse Matrix representation of the set.

---

Method get_attributes()

Attributes defined for the set

Usage

SparseSet$get_attributes()

Returns

A character vector with the names of the attributes.

---

Method length()

Number of attributes

Usage

SparseSet$length()

Returns

The number of attributes that are defined for this fuzzy set.

---

Method print()

Prints the set to console

Usage

SparseSet$print()

Returns

A string with the elements of the set and their grades between brackets .

---

Method to_latex()

Write the set in LaTeX format

Usage

SparseSet$to_latex(print = TRUE)

Arguments

print

(logical) Print to output?

Returns

The fuzzy set in LaTeX.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

SparseSet$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

S <- SparseSet$new(attributes = c("A", "B", "C"))
S$assign(A = 1)
print(S)
S$to_latex()

neuroimaginador/fcaR documentation built on Dec. 9, 2020, 5:42 a.m.