In mbadge/AnalysisToolkitR: Objects and Functions for general data analysis

suppressPackageStartupMessages(library(AnalysisToolkit))
library(knitr)
library(pander)
library(ggplot2)

knitr::opts_chunk$set(collapse=TRUE,
                      comment="#>", results="markup",
                      fig.show='hold', fig.align="center", fig.height=8, fig.width=8,
                      message=FALSE, warning=FALSE, 
                      cache=TRUE)

panderOptions("knitr.auto.asis", FALSE)

theme_set(
    theme_bw(base_size=14) + theme(
#        legend.position="bottom",
        legend.key=element_rect(colour=NA),
        plot.margin=unit(c(0.5, 0.5, 0.5, 0.5), "cm")
    )
)

set.seed(123)
PROJECT_DIR <- Sys.getenv('PROJECT_DIR')

data(classifiers, package="AnalysisToolkit")
str(classifiers, list.len=2)

reduce ggplot layers

accumulate_gg_dots <- function(...) {
    Reduce(`+`, list(...), accumulate=TRUE)
}

accumulate_gg_dots(
    ggplot(mtcars, aes(x=disp, y=cyl)) + geom_point(),
    geom_smooth(),
    xlab(NULL),
    ylab(NULL)
)

Augment data to accession-major df

tidy_curves <- map_dfr(classifiers$classifier_curves, tidy, .id="grader") %>% 
    nest(-id, -Y, .key = pY_by_grader)
tidy_points <- map_dfr(classifiers$classifier_point, tidy, .id = "grader") %>% 
    nest(-id, -Y, .key = Y_by_grader)
tidy_df <- inner_join(tidy_points, tidy_curves, c("id", "Y"))

tidy_df
tidy_df %>% `[`(1, ) %>% use_series(Y_by_grader) %>% kable
tidy_df %>% `[`(1, ) %>% use_series(pY_by_grader) %>% kable