discrete.Rmd

---
title: "PhyloWizard Discrete"
output: github_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

```{r, include = FALSE}
library(knitr)
```

```{r, echo = FALSE}
# hidden from user, these are the functions to provide the summaries

type_data <- function(data) {
  if (length(unique(data)) > 2) {
    type <- "is multi state"
  } else if (length(unique(data)) == 2) {
    type <- "is binary"
  } else if (length(unique(data)) == 1) {
    type <- "has no variation"
  } else {
    type <- "uh oh!! unknown error"
  }
  return(type)
}

num_states <- function(data) {
  length(unique(data))
}

num_obs <- function(data) {
  length(data)
}

make_discr_plot <- function(data, char_name = NA) {
  counts <- table(data)
  barplot(counts, main = char_name, 
          xlab = "character states",
          ylab = "number of tips")
}

make_discr_table <- function(data, char_name = NA) {
  counts <- table(data)
  kable(counts, col.names = c("Char. States","Num. of Tips"))
}

```

## Let's make up test data 

Here we go!! 

```{r cars}

test_multi <- sample(c(0,1,2), size = 100, replace = TRUE)
test_binary <- sample(c(0,1), size = 100, replace = TRUE)

```


Your data `r type_data(test_multi)`. You have `r num_obs(test_multi)` observations and `r num_states(test_multi)` character states. 

```{r, echo = FALSE}
make_discr_table(test_multi)
```

```{r, echo = FALSE}
make_discr_plot(test_multi)
```