---
title: "Demo with mtcars"
vignette: >
  %\VignetteIndexEntry{Demo with mtcars}
  %\VignetteEncoding{UTF-8}
  %\VignetteEngine{knitr::rmarkdown}
---


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

<!--
rerun this to update tribble formatting:
```r
dynbenchmark::reformat_tribbles("vignettes/mtcars.Rmd")
```
-->

Load data
```{r load-data}
library(funkyheatmap)
library(dplyr, warn.conflicts = FALSE)
library(tibble, warn.conflicts = FALSE)
library(purrr, warn.conflicts = FALSE)

data("mtcars")

data <- mtcars %>%
  rownames_to_column("id") %>%
  arrange(desc(mpg)) %>%
  head(20) %>%
  mutate(type = c(rep("images/ice.png", 10), rep("images/electric.png", 10)))
```

We can plot this data frame without any additional formatting, though it doesn't look very nice:

```{r}
g <- funky_heatmap(data)
```

```{r include=FALSE}
# set width and height for upcoming plot
knitr::opts_chunk$set(fig.width = g$width, fig.height = g$height)
```

```{r heatmap_preview}
g
```


By defining a few additional formatting parameters, we can get the plot to look much nicer.

## Column info 

```{r column-info}
column_info <- tribble(
  ~id,     ~group,         ~name,                      ~geom,        ~palette,    ~options,
  "id",    NA,             "",                         "text",       NA,          list(hjust = 0, width = 6),
  "mpg",   "overall",      "Miles / gallon",           "bar",        "palette1",  list(width = 4, legend = FALSE),
  "cyl",   "overall",      "Number of cylinders",      "bar",        "palette2",  list(width = 4, legend = FALSE),
  "disp",  "group1",       "Displacement (cu.in.)",    "funkyrect",  "palette1",  lst(),
  "hp",    "group1",       "Gross horsepower",         "funkyrect",  "palette1",  lst(),
  "drat",  "group1",       "Rear axle ratio",          "funkyrect",  "palette1",  lst(),
  "wt",    "group1",       "Weight (1000 lbs)",        "funkyrect",  "palette1",  lst(),
  "qsec",  "group2",       "1/4 mile time",            "circle",     "palette2",  lst(),
  "vs",    "group2",       "Engine",                   "circle",     "palette2",  lst(),
  "am",    "group2",       "Transmission",             "circle",     "palette2",  lst(),
  "gear",  "group2",       "# Forward gears",          "circle",     "palette2",  lst(),
  "carb",  "group2",       "# Carburetors",            "circle",     "palette2",  lst(),
  "type",  "group2",       "Type of engine",           "image",      NA,          lst()
)
```

Define column groups

```{r column-groups}
column_groups <- tribble( # tribble_start
  ~Category,  ~group,         ~palette,
  "Overall",  "overall",      "overall",
  "Group 1",  "group1",       "palette1",
  "Group 2",  "group2",       "palette2"
) # tribble_end
```

## Row info

Determine method grouping

```{r method-grouping}
row_info <- data %>% transmute(id, group = "test")
row_groups <- tibble(Group = "Test", group = "test")
```


## Palettes

Determine palettes

```{r column-grouping}
palettes <- tribble(
  ~palette,             ~colours,
  "overall",            grDevices::colorRampPalette(rev(RColorBrewer::brewer.pal(9, "Greys")[-1]))(101),
  "palette1",           grDevices::colorRampPalette(rev(RColorBrewer::brewer.pal(9, "Blues") %>% c("#011636")))(101),
  "palette2",           grDevices::colorRampPalette(rev(RColorBrewer::brewer.pal(9, "Reds")[-8:-9]))(101)
)
```

## Funky heatmap

Generate funky heatmap

```{r make-plot}
g <- funky_heatmap(
  data = data,
  column_info = column_info,
  column_groups = column_groups,
  row_info = row_info,
  row_groups = row_groups,
  palettes = palettes,
  position_args = position_arguments(
    expand_xmax = 4,
    col_annot_offset = 4
  ),
  add_abc = FALSE
)
```

```{r include=FALSE}
# set width and height for upcoming plot
knitr::opts_chunk$set(fig.width = g$width, fig.height = g$height)
```

```{r heatmap}
g
```

`funkyheatmap` automatically recommends a width and height for the generated plot.
To save your plot, run:

``` r
ggsave("path_to_plot.pdf", g, device = cairo_pdf, width = g$width, height = g$height)
```