In krisrs1128/MSLF: Package accompanying "Bootstrap Confidence Regions for Learned Feature Embeddings"

library(tidyverse)
library(LFBCR)
library(reshape2)
library(reticulate)
np <- import("numpy")
theme_set(min_theme())

exdir <- str_remove(params$tnbc_data, ".tar.gz")
untar(params$tnbc_data, exdir = exdir)
Xy <- read_csv(file.path(exdir, "stability_data", "Xy.csv"), col_types = cols())
cell_types <- c("B", "CD4", "CD8", "Keratin+ tumor", "Macrophages", "Mesenchymal-like", "Other")

n_patch <- nrow(Xy)
ix <- order(Xy$y)[seq(1, n_patch, length.out = 16)]
ims <- map(ix, ~ np$load(file.path(exdir,"stability_data",  Xy$path[.])))

mim <- melt(ims, varnames = c("w", "h", "cell_type")) %>%
  mutate(cell_type = cell_types[cell_type]) %>%
  filter(value == 1)

ggplot(mim) +
  geom_raster(aes(w, h, fill = cell_type)) +
  coord_fixed() +
  scale_x_continuous(expand = c(0, 0)) +
  scale_y_continuous(expand = c(0, 0)) +
  scale_alpha(range = c(0, 1), guide = "none") +
  scale_fill_brewer(palette = "Set3") +
  labs(fill = "Cell Type") +
  facet_wrap(~L1, ncol = 8) +
  theme(
    panel.grid = element_blank(),
    panel.spacing = unit(0, "cm"),
    axis.text = element_blank(),
    axis.title = element_blank(),
    axis.ticks = element_blank(),
    legend.position = "bottom"
  )

ggsave("example_cells.png", dpi = 500)

krisrs1128/MSLF documentation built on March 21, 2023, 10:21 a.m.