cell <- read.table("cultures antibiotics.txt", header = TRUE, sep = "\t", na.strings = "NA", 
    dec = ".", strip.white = TRUE)
knitr::kable(head(cell))

cell <- gather(cell, X1:X7, key = "day", value = "cell_number")
knitr::kable(head(cell))

cell$day <- as.numeric(str_replace(cell$day, "X", ""))
knitr::kable(head(cell))

cell$Concentration <- as.character(cell$Concentration)
knitr::kable(head(cell))

cell_1 <- cell %>% group_by(RCC, Antibio, Concentration, day) %>% summarise(cell_mean = mean(cell_number), 
    cell_sd = sd(cell_number), cell_se = std.error(cell_number))
knitr::kable(head(cell_1))

Concentration_color <- c(`0.2` = "white", `0.5` = "white", `0.8` = "white", 
    `1` = "black", `1.5` = "black", `2` = "black")
Concentration_linetype <- c(`0.2` = 1, `0.5` = 1, `0.8` = 1, `1` = 2, `1.5` = 2, 
    `2` = 2)
Concentration_shape <- c(`0.2` = 21, `0.5` = 22, `0.8` = 21, `1` = 22, `1.5` = 21, 
    `2` = 22)

scaling_factor = 15
cell_label <- expression(paste("cell.", mL^-1))
cell_breaks = c(100, 1000, 10000, 1e+05, 1e+06)
x_max = 8
x_breaks = c(0, 2, 4, 6, 8)
x_labels = c("0", "2", "4", "6", "8")

plot1 <- ggplot(cell_1, aes(x = day, y = cell_mean, group = Concentration, xmin = 0, 
    xmax = x_max, shape = Concentration, fill = Concentration, linetype = Concentration)) + 
    facet_wrap(~RCC + Antibio, nrow = 4, ncol = 2, scales = "free") + geom_line(size = 0.8, 
    colour = "black") + geom_point(size = 4) + geom_errorbar(aes(ymin = cell_mean - 
    cell_se, ymax = cell_mean + cell_se), width = 0.2, linetype = 1) + theme_bw(scaling_factor) + 
    theme(panel.border = element_rect(colour = "black"), panel.grid.major = element_blank(), 
        panel.grid.minor = element_blank(), axis.line = element_line(colour = "black"), 
        legend.title = element_text(size = scaling_factor), legend.key = element_blank(), 
        axis.title = element_text(size = scaling_factor), legend.text = element_text(size = scaling_factor), 
        legend.key.height = unit(1, "cm"), axis.text = element_text(size = 0.8 * 
            scaling_factor), panel.background = element_rect(fill = "white")) + 
    theme(legend.position = "top", legend.box = "horizontal") + labs(x = "Days", 
    y = cell_label) + scale_x_continuous(breaks = x_breaks, labels = x_labels) + 
    scale_y_log10(breaks = cell_breaks, labels = scales::trans_format("log10", 
        scales::math_format(10^.x))) + annotation_logticks(sides = "lr") + scale_fill_manual(values = Concentration_color) + 
    scale_shape_manual(values = Concentration_shape) + scale_linetype_manual(values = Concentration_linetype)

# Add next line to zoom + coord_cartesian(ylim=c(100, 10000000))

plot1

# Next can be used to save the plot as pdf ggsave(file='Fig 1 version
# 2.0.pdf', plot=plot1, scale=5, width = 7, height = 10, units = 'cm',
# useDingbats=FALSE)

grazing <- read_xlsx("grazing experiment.xlsx", sheet = "RCC2306")

# Compute a new variable with the same scale as the cell concentration to be
# able to plot on the same graph
grazing$cell_beads_pct_scaled <- grazing$cell_beads_pct * 2e+05

knitr::kable(head(grazing))

plot <- ggplot(data = grazing, aes(x = time, y = cell_ml, ymin = 0, fill = treatment)) + 
    geom_point(size = 4, shape = 21) + labs(x = "Time (hours)", y = "Cells per mL - circles") + 
    geom_point(size = 4, shape = 22, aes(x = time, y = cell_beads_pct_scaled, 
        fill = treatment)) + scale_y_continuous(sec.axis = sec_axis(~./2e+05, 
    name = "% of cells with beads - squares"))
print(plot)