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5_panel4.R
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source("R/tests.R", local = T)
source("R/utils.R", local = T)
source("R/constants.R", local = T)
source("R/Cbind.R", local = T)
source("R/plot.R", local = T)
source("R/themes.R", local = T)
source("R/learning_plot.R", local = T)
source("R/summary_plot.R", local = T)
source("R/prism_compat.R", local = T)
source("5_1_panel4_sleep_data.R", local = T)
source("5_2_panel4_sleep_data.R", local = T)
experiments <- c("24hr LTM")
trainings <- c("6X_Massed", "6X_Spaced")
all_levels <- c(trainings, "No_training")
genotypes <- c("Iso31")
intervals <- c("No_stimulator")
valid_reasons <- c("", "?", "Human-override", "Machine-override", "AOJ-override")
periods <- list(
c(5, 11),
c(12, 18)
)
data <- data.table::fread(file = "tidy_data_wide.csv")
data[, date := as.character(date)]
panel4_data <- data[
PRE_Reason %in% valid_reasons &
POST_Reason %in% valid_reasons &
Training %in% trainings &
Genotype %in% genotypes &
interval %in% intervals &
experiment %in% experiments &
region_id != "NONE" &
US %in% c("75V 0Ω", "75V")
]
panel4_data[, Training := factor(Training, levels = trainings)]
columns <- c(
"Files", "idoc_folder", "PRE_ROI", "POST_ROI",
"User", "Genotype", "experiment",
"PRE", "POST", "SD_status", "interval"
)
export_csvs(panel4_data, "Training", trainings, "4A", columns)
panel4_data[, .N, by=Genotype]
panel4_data[, .N, by=.(experiment, Files)]
dt_bin <- load_ethoscope_data_fig4()
yaml::write_yaml(
x = unique(sapply(dt_bin[, meta=TRUE]$file_info, function(fi) fi$path)),
file = file.path(OUTPUT_FOLDER, "Fig4/fig4_ethoscope_database.yaml")
)
sleep_dataset <- process_sleep_dataset_fig4(panel4_data, periods, all_levels, dt_bin)
sleep_data <- sleep_dataset$data
significance_data <- sleep_dataset$significance
sleep_accum <- sleep_dataset$periods
panel4_data <- keep_only_with_ethoscope_data(panel4_data, sleep_accum)
panel4_data_long <- melt_idoc_data(panel4_data)
panel4A <- learning_plot(
data = panel4_data_long[Training %in% c("6X_Spaced", "6X_Massed"), ],
"Training",
y_annotation = .7,
y_annotation_n = -1,
y_limits = c(-1, 1),
text_vjust = +2.5,
text_hjust = 1,
textsize = 4,
colors = colors_panel4[1:2],
correction = "bonferroni"
)
panel4A$gg <- panel4A$gg + scale_x_discrete(expand = expansion(add=c(.25,.25)))
breaks <- behavr::hours(seq(4, 24, 2))
panel4C <- ggplot() +
ggetho::stat_ld_annotations(
data = sleep_data[t >= behavr::hours(4) & t <= behavr::hours(24), ],
mapping = aes(x = t, y = mu, col = Training),
height=1, alpha=0.2
) +
geom_line(
data = sleep_data[t >= behavr::hours(4) & t <= behavr::hours(24), ],
mapping = aes(x = t, y = mu, col = Training),
linewidth = 1
) +
geom_errorbar(
data = sleep_data[t >= behavr::hours(4) & t <= behavr::hours(24), ],
aes(x = t, fill = Training, ymin = mu - sem, ymax = mu + sem),
linewidth = .5, col = "black", width=behavr:::hours(0.25)
) +
geom_point(
data = sleep_data[t >= behavr::hours(4) & t <= behavr::hours(24), ],
aes(x = t, y = mu, fill = Training, col = Training),
size=2
) +
scale_x_hours(
name = "ZT", breaks = breaks,
labels = (breaks %% behavr::hours(24)) / behavr::hours(1)
) +
scale_color_manual(values = colors_panel4[1:length(all_levels)]) +
scale_y_continuous(name = "Time asleep per\n30 min bin (min)", expand = expansion(add = c(0, 0))) +
geom_signif(
data = significance_data[Training == "No_training", ],
mapping = aes(
xmin = t - behavr::mins(10),
xmax = t + behavr::mins(10),
group = t,
annotations = symbol_ml
), hjust = 0,
segment_color = "white",
tip_length = 0, y_position = 25, manual = TRUE, textsize = STARSIZE, lineheight=.35
) +
coord_cartesian(clip = "off", ylim = c(0, 30), xlim = behavr::hours(c(4, 24))) +
sleep_plot_theme
panel4C
panel4C <- list(gg = panel4C)
sleep_accum[, Training := factor(as.character(Training), levels = all_levels)]
export_csvs(sleep_accum, "Training", all_levels, "4C", NULL, "asleep")
preprocess_function <- function(data, group, test, value.var = "PI") {
data$group__ <- data[[group]]
data[[value.var]] <- data$asleep
return(data)
}
sleep_spaced <- sleep_accum[interval=="ZT05-ZT11" & Training == "6X_Spaced", .(Files, PRE_ROI = as.integer(PRE_ROI), POST_ROI = as.integer(POST_ROI), asleep)]
learning_spaced <- panel4_data[Training == "6X_Spaced", .(Files, PRE_ROI = as.integer(PRE_ROI), POST_ROI = as.integer(POST_ROI), PRE, POST, POST_1, POST_2)]
spaced_data <- merge(sleep_spaced, learning_spaced, by = c("Files", "PRE_ROI", "POST_ROI"))
ggplot(data=spaced_data, mapping = aes(x=asleep, y = POST)) + geom_point() + geom_smooth(method="lm") + labs(y="POST PI")
y_max <- 360
panel4D_all <- lapply(periods, function(period) {
period_str <- paste0(
"ZT",
stringr::str_pad(string = period[1], pad = "0", width = 2),
"-ZT",
stringr::str_pad(string = period[2], pad = "0", width = 2)
)
df <- sleep_accum[interval == period_str & Training %in% all_levels, ]
panel <- summary_plot(
data = df,
group = "Training",
comparisons = list(
c("6X_Spaced", "6X_Massed"),
c("6X_Spaced", "No_training"),
c("No_training", "6X_Massed")
),
map_signif_level = T,
annotation_y = c(375, 355, 415),
colors = colors_panel4[1:length(all_levels)],
y_limits = c(0, y_max),
percentile = c(0.025, 0.975),
preprocess_function = preprocess_function,
y_axis_label = paste0(period_str, " sleep (min)"),
y_breaks = seq(0, y_max, 60),
geom = "violin+sina",
text_hjust = 1,
text_vjust = 2.5,
textsize = 4,
angle_n = 45,
correction = "bonferroni"
)
panel$gg <- panel$gg +
scale_color_manual(
values = colors_panel4[1:length(all_levels)],
labels = all_levels
) +
guides(color = guide_legend(override.aes = list(
linetype = 1, # Set line type to solid
shape = 15, # Remove points from the legend
size = 10
))) + guides(fill = "none")
panel
})
layout <- "
AAAAAAAABBBBBBBBBB
#FFFFFFFFFFFFFFFFF
CCCCCCDDDDDDEEEEEE
"
bottom_height <- 2.5
middle_height <- 2.2
gg <- ggplot() +
learning_plot_theme +
ggplot() +
learning_plot_theme +
panel4A$gg +
guides(color = "none", fill = "none") + theme(
plot.margin = unit(c(0, 0, 30, 0), "pt"),
axis.title.y = element_blank()
) +
panel4D_all[[1]]$gg +
guides(color = "none", fill = "none") + theme(plot.margin = unit(c(0, 0, 30, 0), "pt")) +
panel4D_all[[2]]$gg +
guides(color = "none", fill = "none") + theme(plot.margin = unit(c(0, 0, 30, 0), "pt")) +
(
panel4C$gg +
guides(color = "none", fill = "none") +
theme(
plot.margin = unit(c(0, 0, 60, 0), "pt"),
axis.title.y = element_blank()
)
) +
plot_annotation(tag_levels = list(c("A", "B", "C", "D", "E", "F"))) +
plot_layout(design = layout, heights = c(3, middle_height, bottom_height)) &
theme(
legend.position = "bottom"
)
gg
ggsave(plot = gg, filename = paste0(OUTPUT_FOLDER, "/Fig4/Figure_4.pdf"), width = 190, height = 280, unit = "mm", dpi = "retina")
ggsave(plot = gg, filename = paste0(OUTPUT_FOLDER, "/Fig4/Figure_4.svg"), width = 190, height = 280, unit = "mm", dpi = "retina")