ggplot2-01-sluoksniai.Rmd

---
title: "Sistemos ggplot2 pagrindai"
subtitle: "Elementų sluoksniai"
output: html_notebook
editor_options: 
  chunk_output_type: inline
---

```{r setup}
library(scales) 
library(MASS)
library(plotly)

library(tidyverse)

knitr::opts_chunk$set(fig.height = 3, fig.width = 6)

Sys.setlocale(locale = "Lithuanian")
```



Sistema `ggplot2`: grafikų sudarymo principai
============================================================================= 


Duomenys
----------------------------------------------------------------------------- 
```{r}
library(MASS)
MASS::mammals
```

```{r}
data(mammals, package = "MASS")
```

```{r}
dim(mammals)
```

```{r}
str(mammals)
```

```{r}
View(mammals)
```

```{r}
# Rezultatas matysis „Help“ kortelėje
?mammals
```


Grafikai sudaromi pridedant `ggplot2` sluoksnius su (grafiniais) elementais.


Sklaidos diagrama – pradinė
----------------------------------------------------------------------------- 
```{r}
library(ggplot2)
ggplot(mammals, aes(x = body, y = brain)) +
      geom_point()
```
	  
Žvalgomasis grafikas
----------------------------------------------------------------------------- 
```{r}
ggplot(mammals, aes(x = body, y = brain)) +
    geom_point(alpha = 0.6) +
    stat_smooth(method = "lm", col = "red", se = FALSE)
```

Žvalgomasis grafikas (patikslintas)
----------------------------------------------------------------------------- 
```{r}
ggplot(mammals, aes(x = body, y = brain)) +
    geom_point(alpha = 0.6) +
    coord_fixed() +
    scale_x_log10() +
    scale_y_log10() +
    stat_smooth(method = "lm",
                col = "#C42126",
                se = FALSE,
                size = 1)
```

Straipsniui parengtas grafikas
----------------------------------------------------------------------------- 
```{r}
library(scales) # funkcijos trans_breaks() ir trans_format()

ggplot(mammals, aes(x = body, y = brain)) +
    annotation_logticks() +
    geom_point(alpha = 0.6) +
    coord_fixed(xlim = c(10^-3, 10^4), ylim = c(10^-1, 10^4)) +
    scale_x_log10(expression("Body weight (log"["10"]*"(Kg))"),
                  breaks = trans_breaks("log10", function(x) 10^x),
                  labels = trans_format("log10", math_format(10^.x))) +
    scale_y_log10(expression("Brain weight (log"["10"]*"(g))"),
                  breaks = trans_breaks("log10", function(x) 10^x),
                  labels = trans_format("log10", math_format(10^.x))) +
    stat_smooth(method = "lm", col = "#C42126", se = FALSE, size = 1) +
    theme_classic()
```



Sistema `ggplot2`: elementų sluoksniai
============================================================================= 

Sistemos ggplot2 grafikus sudaro 7 sluoksniai: pirmus tris nurodyti privaloma.


Sluoksniai (1): duomenys
----------------------------------------------------------------------------- 

```{r}
iris
```

```{r}
ggplot(iris)
```

Sluoksniai (2): estetinis išdėstymas
----------------------------------------------------------------------------- 

```{r}
ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width)) 
```


Sluoksniai (3): geometriniai objektai
----------------------------------------------------------------------------- 
```{r}
ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width)) +
    geom_jitter(alpha = 0.6)
```

Sluoksniai (4): facetės
------------------------------------------------------------------------------ 
```{r}
ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width)) +
    geom_jitter(alpha = 0.6) +
    facet_grid(. ~ Species)
```

Sluoksniai (5): statistiniai elementai
----------------------------------------------------------------------------- 

```{r}
ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width)) +
    geom_jitter(alpha = 0.6) +
    facet_grid(. ~ Species) +
    stat_smooth(method = "lm", se = F, col = "red")
```




Sluoksniai (6): koordinačių sistema
----------------------------------------------------------------------------- 
```{r}
levels(iris$Species) <- c("Setosa", "Versicolor", "Virginica")

ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width)) +
    geom_jitter(alpha = 0.6) +
    facet_grid(. ~ Species) +
    stat_smooth(method = "lm", se = F, col = "red") +
    scale_y_continuous("Sepal Width (cm)",
                       limits = c(2,5), 
                       expand = c(0,0)) +
    scale_x_continuous("Sepal Length (cm)",
                       limits = c(4,8),
                       expand = c(0,0)) +
    coord_equal()
```

Sluoksniai (7): temos elementai
----------------------------------------------------------------------------- 
```{r}
levels(iris$Species) <- c("Setosa", "Versicolor", "Virginica")

ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width)) +
    geom_jitter(alpha = 0.6) +
    facet_grid(. ~ Species) +
    stat_smooth(method = "lm", se = F, col = "red") +
    scale_y_continuous("Sepal Width (cm)",
                       limits = c(2,5), 
                       expand = c(0,0)) +
    scale_x_continuous("Sepal Length (cm)",
                       limits = c(4,8),
                       expand = c(0,0)) +
    coord_equal() +
    theme(panel.background = element_blank(),
          plot.background = element_blank(),
          legend.background = element_blank(),
          legend.key = element_blank(),
          strip.background = element_blank(),
          axis.text = element_text(colour = "black"),
          axis.ticks = element_line(colour = "black"),
          panel.grid.major = element_blank(),
          panel.grid.minor = element_blank(),
          axis.line = element_line(colour = "black"),
          strip.text = element_blank(),
          panel.spacing = unit(1, "lines")
    )
```