versioninfo()

#= To Install RCall:
  using Pkg
  Pkg.add("RCall")
=#
using RCall

X = randn(3,2)
b = reshape([2.0, 3.0], 2,1)
y = X * b + randn(3,1)

# Note that X and y are julia variables. @rput sends y and X to R with the same names
@rput y
@rput X

# Fit a model in R
R"mod <- lm(y ~ X-1)"
R"summary(mod)"

# If you want to retrieve a variable from R, look at this example
R"z <- y * 3"
@rget z
z

# In this example, we really need to use reval
R_lm(some_str_expr) = reval(rparse("lm(" * some_str_expr * ")"))
R_summary = R"summary"
R_mod = R_lm("y ~ X-1")
R_summary(R_mod)

# Finally, plotting. Note that if you don't set ylab and xlab, you'll get a very messy plot...
R_plot = R"plot"
R_plot(x=rand(100),y=rand(100),pch=20,cex=2,fg="grey",bty="n",ylab="",xlab="")
R"plot(X[,1],y)"
# Now, you can call R_plot in julia quite like you call plot in R

R"plot(rnorm(2000))"

R_plot = R"plot";
R_plot(x=randn(2000),ylab="")

R"""
library(ggplot2)
str(iris)
"""

# http://motw.mods.jp/R/ggplot_facet.html

R"""
p <- ggplot(iris, aes(x=Sepal.Length, y=Sepal.Width))
p + geom_point(colour="gray50", size=3) + geom_point(aes(colour=Species))
"""

# http://motw.mods.jp/R/ggplot_geom_histogram.html

R"""
p <- ggplot(iris, aes(x=Sepal.Length))
p + geom_histogram(aes(colour=Species),bins=30)
"""

R"""
p + geom_histogram(aes(fill=Species),bins=30)
"""

R"""
str(diamonds)
"""

# http://motw.mods.jp/R/ggplot_facet.html

R"""
p <- ggplot(diamonds, aes(x=carat, y=price))
p + geom_point(aes(colour=clarity)) + facet_grid(cut ~ color, margins=TRUE)
"""

# https://mrunadon.github.io/ggplot2/

R"""
g3<-ggplot(iris,aes(x=Sepal.Length)) #確率密度曲線を描いていきたいので、ｙ軸の宣言は不要です。確率密度がy軸になるので。
g3<-g3+geom_density(aes(fill=Species),size=0.5,alpha=0.5) #geom_density()を使います
g3<-g3+xlim(3,10) #ｘ軸は3から１０の範囲としましょう。
g3
"""

# https://mrunadon.github.io/ggplot2/

R"""
g3<-ggplot(iris,aes(x=Sepal.Length))
g3<-g3+geom_density(aes(fill=Species),size=0.5,alpha=0.5)
g3<-g3+xlim(3,10)
g3
"""

R"hoge <- 3"

@rget hoge

moge = Float64(pi)

@rput moge

R"moge"

poge = [
    1 2 3;
    4 5 6;
    7 8 9;
]

@rput poge

R"poge"

pogecopy = deepcopy(poge)

R"poge <- 2*poge"

@rget poge

poge

pogecopy