---
title: "User Guide"
subtitle: "Package FisPro `r packageVersion('FisPro')`"
author: "Jean-Luc Lablée, Serge Guillaume"
output: 
  rmarkdown::html_vignette:
    toc: true
vignette: >
  %\VignetteIndexEntry{User Guide}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

## Introduction

This package is the R implementation of functions to manage a Fuzzy Inference System (FIS) provided by the open source software [FisPro](https://www.fispro.org).<br>
**FisPro** allows to create Fuzzy Inference Systems and to use them for reasoning purposes, especially for simulating a physical or biological system.<br>
In this brief User Guide we describe how to build and use a FIS to infer input values.<br>
See [Fuzzy Logic Elementary Glossary](https://www.fispro.org/documentation/en/inline-help/node39.html) for more details about Fuzzy Logic.

```{r, setup}
library(FisPro)
```

## Build a FIS from a configuration file

The FIS configuration file can be designed using the [FisPro](https://www.fispro.org) open source software.

```{r}
fis_file <- system.file("extdata", "test.fis", package = "FisPro")
fis <- NewFis(fis_file)
```

## Build a FIS from scratch

Create a new empty FIS.<br>
The design must be completed using the available functions to add inputs, outputs and rules before it can be used for inference.

```{r}
fis <- NewFis()
fis$name <- "foo"
```

### Create inputs

Add 2 inputs to the FIS.

Create the first input with 2 MFs regular standardized fuzzy partition:

```{r}
fisin1 <- NewFisIn(2, 0, 1)
fisin1$name <- "input1"
fis$add_input(fisin1)
```

Create the second input with 3 MFs:

```{r}
fisin2 <- NewFisIn(0, 1)
fisin2$name <- "input2"

mf1 <- NewMfTrapezoidalInf(0, 0.5)
mf1$label <- "Low"
fisin2$add_mf(mf1)

mf2 <- NewMfTriangular(0, 0.5, 1)
mf2$label <- "Average"
fisin2$add_mf(mf2)

mf3 <- NewMfTrapezoidalSup(0.5, 1)
mf3$label <- "High"
fisin2$add_mf(mf3)

fis$add_input(fisin2)
```

### Create outputs

Add 2 outputs to the FIS.

Create a crisp output with range [0, 1]:

```{r}
fisout1 <- NewFisOutCrisp(0, 1)
fisout1$name <- "output1"
fis$add_output(fisout1)
```

Create a fuzzy output with 2 MFs regular standardized fuzzy partition in range [0, 1]:

```{r}
fisout2 <- NewFisOutFuzzy(2, 0, 1)
fisout2$name <- "output2"
fis$add_output(fisout2)
```

### Create the rule base

Add 2 rules to the FIS.<br>
Each rule is initialized with a vector of premises and conclusions.<br>
- a premise is the 1-based index of MF in the input [FisIn], 0 means the rule is incompelete.<br>
- a conclusion is a numeric value for crisp output [FisOutCrisp], or the 1-based index of MF in the fuzzy output [FisOutFuzzy].<br>
In this example the second rule is incomplete, the second input of the FIS has no effect on this rule.

```{r}
fis$add_rule(NewRule(c(1, 2), c(0, 1)))
fis$add_rule(NewRule(c(2, 0), c(1, 2)))
```

### Save the FIS configuration file

Save the FIS to the file "foo.fis":

```{r}
fis$save("foo.fis")
```

```{r, include=FALSE}
file.remove("foo.fis")
```

## FIS inference

Infers all outputs:

```{r}
inferred <- fis$infer(c(0.25, 0.75))
```

Infers first output:

```{r}
inferred_output1 <- fis$infer_output(c(0.25, 0.75), 1)
```

Infers second output:

```{r}
inferred_output2 <- fis$infer_output(c(0.25, 0.75), 2)
```

Infers dataset:

```{r}
test_file <- system.file("extdata", "test_data.csv", package = "FisPro")
dataset <- read.csv(test_file)
inferred_dataset <- fis$infer(dataset)
```
