BacterAI/main.Rmd at master · jensenlab/BacterAI · GitHub

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---
title: "R Notebook"
output: html_notebook
---

```{r}

sample_test_train <- function(test=0.0, train=0.0, n=NULL, X=NULL) {
  stopifnot(!is.null(n) || !is.null(X))
  stopifnot(test + train <= 1.0)
  if (is.null(n)) {
    n <- nrow(X)
  }
  n_test <- floor(test*n)
  n_train <- floor(train*n)
  all_indices <- sample.int(n, size=n_test+n_train)
  list(
    test = all_indices[1:n_test],
    n_test = n_test,
    train = all_indices[(n_test+1):(n_test+n_train)],
    n_train = n_train
  )
}

```


```{r}

raw <- readr::read_csv("data/L1IO-L2IO-L3O All Rands SMU UA159 Processed-Aerobic.csv")

Xall <- as.matrix(raw[ ,1:20])
yall <- raw$growth

spl <- sample_test_train(test=0.1, train=0.1, X=Xall)

X <- Xall[spl$train, ]
y <- yall[spl$train]

Xt <- Xall[spl$test, ]
yt <- yall[spl$test]

```


```{r}

raw <- readr::read_csv("data/L1IO-L2IO-L3O All Rands SMU UA159 Processed-Aerobic.csv")

Xall <- as.matrix(raw[ ,1:20])
yall <- raw$growth

spl <- sample_test_train(test=0.1, train=0.1, X=Xall)

X <- Xall[spl$train, ]
y <- yall[spl$train]

Xt <- Xall[spl$test, ]
yt <- yall[spl$test]

```

```{r}
eps <- sqrt(.Machine$double.eps)
gpi <- laGP::newGPsep(X, y, d=0.1, g=0.1*var(y), dK=TRUE)
ndim <- dim(X)[[2]]
tmin <- rep(eps, ndim+1)
tmax <- c(rep(100, ndim), var(y))
mle <- laGP::mleGPsep(gpi, para="both", tmin=tmin, tmax=tmax, verb=2)
```
```{r}

order_plot <- function(ytrue, ypred) {
  so <- order(ytrue)
  cex <- 0.5
  plot(1:length(ypred), ypred[so], col="orange", xlab="sorted index", ylab="", cex=cex)
  points(1:length(ytrue), ytrue[so], col="blue", cex=cex)
}

yp <- laGP::predGPsep(gpi, Xt, lite=TRUE)
order_plot(yt, yp$mean)
```