knor_final.Rmd

---
title: "Knor Benchmark"
output:
  pdf_document: default
  html_notebook: default
---
# Benchmarking Results From Knor package


## Load Data
```{r}
# Load libraries
library(knor)
```


```{r}
## Installed packages
installed.packages()[names(sessionInfo()$otherPkgs), "Version"]
``` 
```{r}
## R Version
version[['version.string']]
```

```{r}
X_1m = as.matrix(read.csv("data_1m.csv", header = FALSE))
```

```{r}
X_100k = as.matrix(read.csv("data_100k.csv", header = FALSE))
```


```{r}
X_10k = as.matrix(read.csv("data_10k.csv", header = FALSE))
```


```{r}
X_1k = as.matrix(read.csv("data_1k.csv", header = FALSE))
```



## Elbow Method Speed Test
```{r}
# Just a convenient function to test execution speed of the 'Elbow method'
test_multicore_speed <- function(x){
    
  rng <- 2:10
  iters <-  rng * 0
    
  for (i in rng) {
    m <- knor::Kmeans(data = x, centers = i,
                      iter.max = 100000, nthread = -1, 
                      init = "kmeanspp",
                      tolerance = 1e-06,
                      dist.type = "eucl")
    iters[i] = m$iters
  }
    
  return(iters)
}
```







```{r}
check_run_time_speed <- function(x){
  # Replicate the number samples to get a mean time
  time.taken <- c(1:7)*0
  
  for (i in 1:7) {
    start.time <- Sys.time()
    
    test_multicore_speed(x)
    
    end.time <- Sys.time()
    
    time.taken[i] <- (as.numeric(end.time) - as.numeric(start.time))
    
  }
  return(summary(time.taken))
}
```



## Check Speed For Each Sample

```{r}
check_run_time_speed(X_1m)
```


```{r}
check_run_time_speed(X_100k)
```


```{r}
check_run_time_speed(X_10k)
```


```{r}
check_run_time_speed(X_1k)
```