benchmark.Rmd

---
title: "benchmark"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{benchmark}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

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

```{r imports}
library(isoregr)
library(isotone)
library(microbenchmark)
library(data.table)
library(ggplot2)
```

```{r}
n<-10
y=sample(n,replace=TRUE)+11:(10+n)+0.0
x=sample(n,replace=TRUE)

res <- isoreg(x,y)
yf<-y
yf[if(res$isOrd) 0:n else res$ord] <-res$yf
print(yf)

gpava(x,y)$x
isoreg_Best_1990(x,y)

isoreg_Best_1990(y,implementation = "R")
isoreg_Best_1990(y)
isoreg(y)



n<-2^(2:25)
benchOneN <- function(n){
  x<-sample(n,replace=TRUE)
  y<-sample(n,replace=TRUE)+0.0
  
  res <- microbenchmark(list=list(
    quote(gpava(x,y)$x),
    quote(gpava(1:n,y)$x),
    quote(isoreg(x,y)$yf),
    quote(isoreg(y)$yf),
    quote(isoreg_Best_1990(x,y)),
    quote(isoreg_Best_1990(y)))[n<=2^c(13,13,21,25,21,27)],
    control=list(order="block"),
    times=5,
    unit="ms")   # conditional arg
  dt<-data.table(res)[,n:=n]
}
dt <- rbindlist(lapply(n, benchOneN))

ggplot(dt,aes(x=n,y=time,color=expr,group=expr))+ 
  geom_point(alpha=0.5)+scale_y_log10()+scale_x_log10()+#stat_smooth(data=dt[n>100],method="lm",size=0.5,fill=NA)+
  stat_smooth(size=1,method = 'loess')+
  #stat_smooth(data=dt[n>100],method="lm",formula = y ~ offset(1*x),size=0.5,fill=NA,color="gray")#+
  geom_abline(data=dt[,.(time=mean(time)),by=.(expr,n)][,.(lower=min(log10(time)-log10(n))),by=expr],aes(intercept = lower, slope=1))
#geom_segment(aes(xend=n*1.99,yend=time*1.99),alpha=0.5)


```