scripts/Behprob_3stripes.R

library(tidyverse)
library(reshape2)
library(ggplot2)
library(stats)
library(dplyr)
library(boot)
library(splines)
library(scales)
library(tcltk)
library(devtools)
#devtools::install_github('SenguptaLab/MF.matR')
library(MF.matR)




# import - process data ---------------------------------------------------


tot.mat<-beh_merge_all(400) # enter # frames to bin
tot.mat<-fix_reversals(tot.mat)
#bounds<-c(0, -3.2,-6.75, -9.67, -12.875, -16) # enter boundaries of dye (cue) - used for oct
bounds<-c(0, -3, -6, -9, -12)


tot.mat.enter<-norm_beh_enter_3(tot.mat)
tot.mat.exit<-norm_beh_exit_3(tot.mat)


# aggregate - calculate mean by groupings ---------------------------------


# calculate mean for each worm by time bin and norm.pos
norm_timbin_beh_exit<-aggregate(cbind(Pir, For, Rev, Curve, Pau) ~ genotype + norm.pos + bin + condition, data = tot.mat.exit, FUN=mean)
norm_timbin_beh_enter<-aggregate(cbind(Pir, For, Rev, Curve, Pau) ~ genotype + norm.pos + bin + condition, data = tot.mat.enter, FUN=mean)


# plot_exit ---------------------------------------------------------------


plot1<-ggplot(norm_timbin_beh_exit, aes(x=norm.pos)) +
  annotate("rect", 0,0,-2.5,0,0,1, fill="lightblue", alpha=0.3) +
  geom_smooth(aes(y=Pir, linetype=condition), size = 1.25, method = loess, level=0.99, alpha=0.15, colour="blue") +
  geom_smooth(aes(y=Rev, linetype=condition), size = 1.25, method = loess, level=0.99, alpha=0.15,colour="red") +
  geom_smooth(aes(y=Curve, linetype=condition), size = 1.25, method = loess, level=0.99, alpha=0.15,colour="orange") +
  geom_smooth(aes(y=For, linetype=condition), size = 1.25, method = loess, level=0.99, alpha=0.15,colour="darkgreen") +
  geom_smooth(aes(y=Pau, linetype=condition),  size = 1.25, method = loess, level=0.99, alpha=0.15,colour="yellow") +
  coord_cartesian(ylim=c(0, 1)) +
  facet_grid(genotype~.) +
  theme_my
plot1


# plot enter --------------------------------------------------------------


plot2<-ggplot(norm_timbin_beh_enter, aes(x=norm.pos)) +
  annotate("rect", 0,0,2.5,-0,0,1, fill="lightblue", alpha=0.3) +
#   geom_smooth(aes(y=Pir, linetype=condition), size = 1.25, method = loess, level=0.99, alpha=0.15, colour="blue") +
#   geom_smooth(aes(y=Rev, linetype=condition), size = 1.25, method = loess, level=0.99, alpha=0.15,colour="red") +
#   geom_smooth(aes(y=Curve, linetype=condition),  size = 1.25, method = loess, level=0.99, alpha=0.15,colour="orange") +
#   geom_smooth(aes(y=For, linetype=condition), size = 1.25, method = loess, level=0.99, alpha=0.15,colour="darkgreen") +
#   geom_smooth(aes(y=Pau, linetype=condition),  size = 1.25, method = loess, level=0.99, alpha=0.15,colour="yellow") +
  coord_cartesian(ylim=c(0, 1)) +
  facet_grid(genotype~.) +
  theme_my
plot2

sanity<-ggplot(tot.mat.enter, aes(x=norm.pos)) +
  geom_density(aes(linetype=condition)) +
  theme_my
sanity

sanity2<-ggplot(tot.mat.exit, aes(x=norm.pos)) +
  geom_density(aes(linetype=condition)) +
  theme_my
sanity2
SenguptaLab/MF.matR documentation built on March 25, 2020, 4:30 p.m.