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# Script to make a plot of density of a given vector of numbers with quantile
# areas colored

# Package -------------------------------------------------------------------
library(ggplot2)
library(dplyr)

# Function ------------------------------------------------------------------
make_quantile_density = function(ex_vector, probs = NULL) {
        

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# Matrix of presence-absence
m = structure(c(1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1), .Dim = c(4L, 
4L), .Dimnames = list(c("a", "b", "c", "d"), c("site1", "site2", 
"site3", "site4")))


# Distance matrix
dist = structure(c(0, 0.2, 0.7, 0.33, 0.2, 0, 0.5, 0.15, 0.7, 0.5, 0, 
0.23, 0.33, 0.15, 0.23, 0), .Dim = c(4L, 4L), .Dimnames = list(
    c("a", "b", "c", "d"), c("a", "b", "c", "d")))

Rekyt

# Example of a function that creates a biased distribution

# Packages --------------------------------------------------------------------
library(ggplot2)

# Constants -------------------------------------------------------------------

data_size = 10000
test_index = 10

Rekyt

# Compute R squared from a list of computed and selected models

# Packages ---------------------------------------------------------------------------------------
library(MuMIn)


# Fit general model ------------------------------------------------------------------------------

global_mod = lm(mpg ~ ., data = mtcars)

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# List of qqplots using 'apply()' function
#

library(ggplot2)

data(mtcars)

plot_list = apply(mtcars, 2, function(line) {
    my_plot = ggplot(data.frame(x = line), aes(sample = x)) +
        stat_qq() +

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# Create a map with ggplot2
# Packages
library(ggplot2)
library(ggmap)

# Get France base map (using 'ggplot2::map_data()' function)
france_map = map_data("france")

# Get cities longitude and latitude (using 'ggmap::geocode()' function)
cities = c("Montpellier", "Rouen", "Poil")

Rekyt

# Add groups from a multiple kruskal wallis test
add_groups = function(given_plot, ks_tests) {
    y_range = ggplot_build(given_plot)$panel$ranges[[1]]$y.range
    
    y_upper = max(y_range)
    
    group_df = ks_tests$groups %>%
        select(trt, M) %>%
        mutate(y = y_upper)
    group_df$trt = factor(trimws(group_df$trt), levels = iucn_groups)

Rekyt

# Script to add a trait matrix over a circular phylogenetic tree

# Packages ---------------------------------------------------------------------

library(ape)
library(ggtree)


# Generate Tree and Traits -----------------------------------------------------

Rekyt

# Programmatically use 'microbenchmark()'
# Author: Matthias Grenié

library(microbenchmark)

# Get two functions
my_func = function(x) {
    5^x
}

Rekyt

---
title: "Writing EML files"
author: "Matthias Grenié"
date: "9 mars 2017"
output: pdf_document
---

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