In CollinErickson/CGGP: Composite Grid Gaussian Processes

knitr::opts_chunk$set(echo = TRUE)
knitr::opts_chunk$set(fig.width=13)
knitr::opts_chunk$set(fig.height=9)
library(ggplot2)
library(magrittr)

Rerunning redTime on already gathered data with supplementary data

I took a sequence of SGGP objects from an already completed redTime run. I gave it supplementary data and had it refit, then checked on test set. So the points chosen had nothing to do with supp data, but we should see that it gets better with more data. And we can compare it to other models.

Output dimension 10

# s10 <- readRDS("./scratch/redTime/redTimeSuppExp2/redTimeSuppExp2_od10_object.rds")
s10 <- readRDS("../redTimeSuppExp2/redTimeSuppExp2_od10_object.rds")
s10$completed_runs %>% table

df10 <- s10$outcleandf

ggplot(data=df10, mapping=aes(Ngrid, RMSE, color=as.factor(Nsupp))) + geom_point(size=4) + facet_grid(. ~ package+Supp, scales="free_y") + scale_y_log10()

ggplot(data=df10, mapping=aes(Ngrid, score, color=as.factor(Nsupp))) + geom_point(size=4) + facet_grid(. ~ package+Supp, scales="free_y")# + scale_y_log10()

ggplot(data=df10, mapping=aes(Ngrid, CRPscore, color=as.factor(Nsupp))) + geom_point(size=4) + facet_grid(. ~ package+Supp, scales="free_y") + scale_y_log10()

rm(df10)

Output dimension 50

# s50 <- readRDS("./scratch/redTime/redTimeSuppExp2/redTimeSuppExp2_od50_object.rds")
s50 <- readRDS("../redTimeSuppExp2/redTimeSuppExp2_od50_object.rds")
s50$completed_runs %>% table

df50 <- s50$outcleandf

ggplot(data=df50, mapping=aes(Ngrid, RMSE, color=as.factor(Nsupp))) + geom_point(size=4) + facet_grid(. ~ package+Supp, scales="free_y") + scale_y_log10()

ggplot(data=df50, mapping=aes(Ngrid, score, color=as.factor(Nsupp))) + geom_point(size=4) + facet_grid(. ~ package+Supp, scales="free_y")# + scale_y_log10()

ggplot(data=df50, mapping=aes(Ngrid, CRPscore, color=as.factor(Nsupp))) + geom_point(size=4) + facet_grid(. ~ package+Supp, scales="free_y") + scale_y_log10()