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

devtools::load_all()
library(stringr)
library(ggplot2)
suppressPackageStartupMessages(library(cowplot))
library(knitr)
theme_set(theme_classic())
knitr::opts_chunk$set(collapse=TRUE,
                      comment="#>", fig.show='hold',
                      message=FALSE, warning=FALSE, cache=FALSE)

set.seed(123)

PROJECT_DIR <- Sys.getenv('PROJECT_DIR')

btlnck_fps <- list.files(file.path(PROJECT_DIR, 'data', 'dl', 'pretrained'),pattern = "Btlncks.csv", full.names = TRUE) %>% 
    purrr::set_names(., stem(.))
btlnck_df <- map(btlnck_fps, readr::read_csv, n_max=1000)
btlnck_df[[1]]["img_id"]
btlnck_df[[2]]["X1"]

#! TODO: fix ids

NEED TO RECONCILE

library(AnalysisToolkit)


# # Cumulative variance explained
# by_model_plotter %>%
#     unnest(cve) %>%
#     {ggplot(., aes(x=x, y=y, col=model))} + gg_cve_style
# # Scatter
# by_model_plotter %>%
#     unnest(scat) %>%
#     {ggplot(., aes(x=x, y=y)) + geom_point(alpha=0.2) +
#             facet_grid(.~model)} + gg_scat_style
# by_model_plotter %>%
#     unnest(scat) %>%
#     mutate(dataset=revalue(ids, id2dat),
#            dataset=pretty_dataset(dataset)) %>%
#     {ggplot(., aes(x=x, y=y, col=dataset)) + geom_point(alpha=0.2) +
#             facet_grid(.~model)} + gg_scat_style + color_dataset

data(scalars_df, package="ProjUtils")

######
# Independent Datasets
by_dataset_model <- pilot_df %>%
    nest(-dataset, -model)
# Compute plotting list-cols
by_dataset_model_plotter <- by_dataset_model %>%
    mutate(pcs = map(data, compute_pcs),
           cve = map(pcs, gg_cve),
           scat = map(pcs, gg_scatter),
           model = pretty_model(model),
           dataset= pretty_dataset(dataset))


# Integrated
by_model_plotter$dataset <- "Pooled"
integrated_plotter <- by_dataset_model_plotter %>%
    bind_rows(by_model_plotter) %>%
    mutate(dataset = factor(dataset, levels=c("CXR", "Hips", "Pooled")))

# Cumulative variance explained
gg1 <- integrated_plotter %>%
    unnest(cve) %>%
    {
        ggplot(., aes(x=x, y=y, col=model)) +
            facet_grid(dataset~.) +
            theme(panel.spacing = unit(1, "lines"),
                  legend.position="right") +
            gg_cve_style
    }
gg2 <- integrated_plotter %>%
    unnest(scat) %>%
    mutate(COLOR = revalue(ids, id2dat)) %>%
    {
        ggplot(., aes(x=x, y=y, col=COLOR)) +
            geom_point(alpha=kALPHA) +
            facet_grid(dataset~model) +
            theme(legend.position = "bottom")
    } + gg_scat_style + color_dataset


grid.arrange(gg2, gg1, ncol=2)
g <- arrangeGrob(gg2, gg1, ncol=2)
ggsave(filename = kOUT_FIG_PTH, g, width = 9, height=4, dpi=300)

beepr::beep(11)