library(readr)
library(yarrr) # Load the packages (may need to install these if you don't have them)
library(plotrix)
library(ggplot2)
library(rcartocolor) # For colourblind-friendly palettes

AB_TemporalPredictability <- read_csv("AB_TemporalPredictability_for_R.csv") # Read the CSV (make sure this is in the working directory)
AB_TemporalPredictability_Blink <- read_csv("AB_TemporalPredictability_Blink_for_R.csv") # Read the CSV (make sure this is in the working directory)

png('Figure3.png', width = 7.5, height = 5, units = 'in', res = 300)
par(mar=c(4,5,2,1))
layout(matrix(c(1,2), 1, 2, byrow = TRUE),
       widths=c(3,2))
pirateplot(formula = Accuracy ~ Lag + ITI,
           data = AB_TemporalPredictability,
           xlab = "Condition + Lag", #x label
           ylab = "Proportion T2 correct", # ylabel 
           main = "T2 Accuracy", # uncomment this if you want a title
           theme = 2, # uses one of the inbuilt themes
           pal = "google", # colour palette 
           back.col = gray(.98), # Add light gray background
           gl.col = "gray", # Gray gridlines
           gl.lwd = c(.75, 0), # grid line weight 
           sortx = 'sequential', # sort x in the order it's in in the data
           inf.f.o = .6, # Turn up inf filling
           # inf.disp = "bean", # Wrap inference around bean
           bean.b.o = .2, # Turn down bean borders
           bean.f.o = .1, # Turn down bean fill
           quant = c(.1, .9), # 10th and 90th quantiles
           point.o = .5, point.pch = 21,  point.bg = "white", point.col = "black",
           quant.col = "black")# Black quantile lines

pirateplot(formula = BlinkMagnitude ~ ITI,
           data = AB_TemporalPredictability_Blink,
          # xlab = "Condition + Lag", #x label
           ylab = "Blink Magnitude (Lag 8 - Lag 3)", # ylabel 
           main = "Blink Magnitude", # uncomment this if you want a title
           theme = 2, # uses one of the inbuilt themes
           pal = "google", # colour palette 
           back.col = gray(.98), # Add light gray background
           gl.col = "gray", # Gray gridlines
           gl.lwd = c(.75, 0), # grid line weight 
           sortx = 'sequential', # sort x in the order it's in in the data
           inf.f.o = .6, # Turn up inf filling
           # inf.disp = "bean", # Wrap inference around bean
           bean.b.o = .2, # Turn down bean borders
           bean.f.o = .1, # Turn down bean fill
           quant = c(.1, .9), # 10th and 90th quantiles
           point.o = .5, point.pch = 21,  point.bg = "white", point.col = "black",
           quant.col = "black")# Black quantile lines
dev.off()

### Order effects

png('TrialOrder.png', width = 8, height = 6.5, units = 'in', res = 300)

q <- ggplot(data = AB_TemporalPredictability_Blink, aes(x = ITI, y = BlinkMagnitude, color = TrialOrder, group = Participant))

## Seprate colours on the graph based on the Trial Order variable
q + geom_line() + geom_point() + theme_classic() + 
  theme(text = element_text(size=14)) + 
  ylab("Blink Magnitude (Lag 8 - Lag 3)")+ 
  xlab ("ITI Condition") +  
  scale_color_carto_d(name = "Trial Order ",  palette = "Safe")
dev.off()