}
}
detach("package:MuMIn", unload = TRUE)
-36.4*(-2)+(2*(2+1)*12/(12-2-2))
-36.51*(-2)+(2*(1+1)*12/(12-1-2))
-36.02*(-2)+(2*(3+1)*12/(12-3-2))
1.96*0.08
(0.475-0.427^2)/(1-0.427^2)
0.427-0.427*0.3579325
1.15/(1-0.274*0.427-0.358*0.475)
(0.169-0.274*0.475-0.358*0.427)/(1-0.274*0.427-0.358*0.475)
1.96/sqrt(200)
(0.427-0.475*0.427)/(1-0.427^2)
0.475-0.274*0.427
1.15/(1-0.274*0.427-0.358+0.475)
1.15/(1-0.274*0.427-0.358*0.475)
1.15*(1-0.274*0.427-0.358*0.475)
setwd("~/Documents/Third Year Project/Pointing Task/HeatMap Visualization")
library(foreign)
library(tidyverse)
library(RColorBrewer)
pDSP_G1 <- read.csv("PointingDSP_Coords_G1.csv")
pDSP_G2 <- read.csv("PointingDSP_Coords_G2.csv")
pDSP <- rbind(pDSP_G1,pDSP_G2)
pDSP$PartNo <- as.factor(pDSP$PartNo)
pDSP$PartGen <- as.factor(pDSP$PartGen)
unique(pDSP[pDSP$PartGen=="1",]$PartNo)
length(unique(pDSP[pDSP$PartGen=="1",]$PartNo))
unique(pDSP[pDSP$PartGen=="0",]$PartNo)
length(unique(pDSP[pDSP$PartGen=="0",]$PartNo))
#Delete duplicate rows
pDSP_nodup <- pDSP %>% distinct(PartNo,x,z,.keep_all = T)
p <- ggplot(pDSP_nodup, aes(x=x, y=z) ) +
stat_density_2d(aes(fill = ..density..), geom = "raster", contour = FALSE) +
#scale_fill_distiller(palette= "RdYlGn", direction=-1) +
scale_fill_distiller(palette= "RdYlGn", direction=-1) +
scale_x_continuous(expand = c(0, 0)) +
scale_y_continuous(expand = c(0, 0)) +
theme_void()+
theme(legend.position='none')+
facet_grid(vars(PartGen))
p
View(p)
View(p)
p <- ggplot(pDSP_nodup, aes(x=x, y=z) ) +
stat_density_2d(aes(fill = ..density..), geom = "raster", contour = FALSE) +
#scale_fill_distiller(palette= "RdYlGn", direction=-1) +
scale_fill_distiller(palette= "RdYlGn", direction=-1) +
scale_x_continuous(expand = c(0, 0)) +
scale_y_continuous(expand = c(0, 0)) +
theme_void()+
theme(legend.position='none')
#+facet_grid(vars(PartGen))
p
View(p)
#library(plyr)
counts <- plyr::ddply(pDSP_nodup, .(pDSP_nodup$x, pDSP_nodup$z), nrow)
library(plyr)
counts <- plyr::ddply(pDSP_nodup, .(pDSP_nodup$x, pDSP_nodup$z), nrow)
names(counts) <- c("x", "z", "Freq")
View(counts)
library(dbplyr)
detach("package:plyr", unload = TRUE)
rm(counts)
setwd("~/Documents/PSTAT274/Homework")
2.637+0.252 * 2.93 + 0.061 * 4.62 - 0.202 * 2.12
(-0.79)^2*(8.50-8.01)+8.01
18.72+1.96*sqrt(2.32)
18.72-1.96*sqrt(2.32)
0.75^2 *(20.25-16.75)+16.75
(76.7/51)*(1-0.75^4)/(1-0.75^2)
(75.7/51)*(1-0.75^4)/(1-0.75^2)
18.71875-1.96*sqrt(2.31924)
18.71875+1.96*sqrt(2.31924)
#library(dplyr)
pDSP_round <- pDSP_nodup
pDSP_round$x <- round(pDSP_round,1)
pDSP_round$x <- round(pDSP_round$x,1)
View(pDSP_round)
pDSP_round$x <- round(pDSP_round$x,0)
View(pDSP_round)
#library(dplyr)
pDSP_round <- pDSP_nodup
pDSP_round$x <- round(pDSP_round$x,1)
pDSP_round$z <- round(pDSP_round$z,1)
rename(count(pDSP_round, x, z), Freq = n)
count <- rename(count(pDSP_round, x, z), Freq = n)
View(count)
ggplot(count,aes(x=Freq))+
geom_histogram()
ggplot(count,aes(x=Freq))+
geom_histogram()+
xlim(0,5)
ggplot(count,aes(x=Freq))+
geom_histogram()+
xlim(0,10)
pDSP_round$x <- round(pDSP_round$x,0)
pDSP_round$z <- round(pDSP_round$z,0)
#library(dplyr)
pDSP_round <- pDSP_nodup
pDSP_round$x <- round(pDSP_round$x,0)
pDSP_round$z <- round(pDSP_round$z,0)
count <- rename(count(pDSP_round, x, z), Freq = n)
ggplot(count,aes(x=Freq))+
geom_histogram()+
xlim(0,10)
ggplot(count,aes(x=Freq))+
geom_histogram()+
xlim(0,15)
ggplot(count,aes(x=Freq))+
geom_histogram()+
xlim(0,20)
ggplot(count,aes(x=Freq))+
geom_histogram()+
xlim(0,50)
ggplot(count,aes(x=Freq))+
geom_histogram()+
xlim(0,100)
ggplot(count,aes(x=Freq))+
geom_histogram()+
xlim(0,120)
ggplot(count,aes(x=Freq))+
geom_histogram()+
xlim(0,130)
ggplot(count,aes(x=Freq))+
geom_histogram()+
xlim(0,150)
ggplot(count,aes(x=Freq))+
geom_histogram()+
xlim(0,250)
summary(count$Freq)
ggplot(count,aes(x=Freq))+
geom_histogram()
ggplot(count,aes(x=Freq))+
geom_histogram()+
xlim(0,900)
ggplot(count,aes(x=Freq))+
geom_histogram()+
xlim(0,750)
setwd("~/Documents/Third Year Project/Pointing Task/20Winter/Analysis/Shortcutting Visualization")
setwd("~/Documents/Third Year Project/Pointing Task/20Winter/Analysis/Shortcutting Visualization")
library(tidyverse)
library(RColorBrewer)
setwd("~/Documents/Third Year Project/Pointing Task/20Winter/Analysis/Shortcutting Visualization")
library(tidyverse)
library(RColorBrewer)
pDSP_G1 <- read.csv("20WPointingDSP_Coords_F.csv")
pDSP_G2 <- read.csv("20WPointingDSP_Coords_M.csv")
pDSP <- rbind(pDSP_G1,pDSP_G2)
pDSP <- pDSP[!duplicated(pDSP[,c(1,2,5,7,8,9)])]
pDSP <- pDSP[!duplicated(pDSP[c(1,2,5,7,8,9)]),]
pDSP$PartNo <- as.factor(pDSP$PartNo)
pDSP$PartGen <- as.factor(pDSP$PartGen)
unique(pDSP[pDSP$PartGen=="1",]$PartNo)
length(unique(pDSP[pDSP$PartGen=="1",]$PartNo))
unique(pDSP[pDSP$PartGen=="0",]$PartNo)
length(unique(pDSP[pDSP$PartGen=="0",]$PartNo))
#library(dplyr)
pDSP_round <- pDSP
pDSP_round$x <- round(pDSP_round$x,0)
View(pDSP_G1)
View(pDSP_G1)
setwd("~/Documents/Third Year Project/Pointing Task/20Winter/Analysis/Shortcutting Visualization")
library(tidyverse)
library(RColorBrewer)
pDSP_G1 <- read.csv("20WPointingDSP_Coords_F.csv")
pDSP_G2 <- read.csv("20WPointingDSP_Coords_M.csv")
pDSP <- rbind(pDSP_G1,pDSP_G2)
pDSP <- pDSP[!duplicated(pDSP[c(1,2,5,7,8,9)]),]
pDSP$PartNo <- as.factor(pDSP$PartNo)
pDSP$PartGen <- as.factor(pDSP$PartGen)
unique(pDSP[pDSP$PartGen=="1",]$PartNo)
length(unique(pDSP[pDSP$PartGen=="1",]$PartNo))
unique(pDSP[pDSP$PartGen=="0",]$PartNo)
length(unique(pDSP[pDSP$PartGen=="0",]$PartNo))
pDSP_round <- pDSP
pDSP_round$x <- round(pDSP_round$x,0)
pDSP_round$z <- round(pDSP_round$z,0)
count <- rename(count(pDSP_round, x, z), Freq = n)
ggplot(count,aes(x=Freq))+
geom_histogram()
summary(count$Freq)
ggplot(count,aes(x=Freq))+
geom_histogram()+
xlim(0,700)
View(count)
summary(count)
#Delete duplicate rows
pDSP_nodup <- pDSP %>% distinct(PartNo,x,z,.keep_all = T)
#library(dplyr)
pDSP_round <- pDSP_nodup
pDSP_round$x <- round(pDSP_round$x,0)
pDSP_round$z <- round(pDSP_round$z,0)
count <- rename(count(pDSP_round, x, z), Freq = n)
ggplot(count,aes(x=Freq))+
geom_histogram()+
xlim(0,700)
summary(count)
write.csv(count,"3DHeatmap_landscape.csv")
setwd("~/Documents/Third Year Project/Pointing Task/20Winter/Analysis/Shortcutting Visualization")
library(tidyverse)
library(RColorBrewer)
pDSP_G1 <- read.csv("20WPointingDSP_Coords_F.csv")
pDSP_G2 <- read.csv("20WPointingDSP_Coords_M.csv")
pDSP <- rbind(pDSP_G1,pDSP_G2)
pDSP <- pDSP[!duplicated(pDSP[c(1,2,5,7,8,9)]),]
pDSP$PartNo <- as.factor(pDSP$PartNo)
pDSP$PartGen <- as.factor(pDSP$PartGen)
unique(pDSP[pDSP$PartGen=="1",]$PartNo)
length(unique(pDSP[pDSP$PartGen=="1",]$PartNo))
unique(pDSP[pDSP$PartGen=="0",]$PartNo)
length(unique(pDSP[pDSP$PartGen=="0",]$PartNo))
#Delete duplicate rows
pDSP_nodup <- pDSP %>% distinct(PartNo,x,z,.keep_all = T)
pDSP_nodup_F <- pDSP_G1 %>% distinct(PartNo,x,z,.keep_all = T)
write.csv(pDSP_nodup_F,"Female-Landscape.csv");
summary(pDSP_nodup)
pDSP_nodup_F <- pDSP_nodup_F[pDSP_nodup_F$PartNo %in% c("607","621","623","624","625","628","630","631"),]
write.csv(pDSP_nodup_F,"Female-Landscape.csv");
pDSP_nodup_F <- pDSP_nodup_F[pDSP_nodup_F$PartNo %in% c("607","621","623","624"),]
write.csv(pDSP_nodup_F,"Female-Landscape.csv");
View(pDSP_G1)
pDSP_G1$Trial
pDSP_nodup_F <- pDSP_G1 %>% distinct(PartNo,x,z,.keep_all = T)
pDSP_nodup_F <- pDSP_nodup_F[pDSP_nodup_F$PartNo %in% c("607","621","623","624"),]
pDSP_G1 <- read.csv("20WPointingDSP_Coords_F.csv")
pDSP_G1 <- read.csv("20WPointingDSP_Coords_F.csv")
pDSP_G1$x <- round(pDSP_G1$x,1)
pDSP_G1$z <- round(pDSP_G1$z,1)
pDSP_G1 <- pDSP_G1[!duplicated(pDSP[c(1,2,5,7,8,9)]),]
pDSP_G1 <- read.csv("20WPointingDSP_Coords_F.csv")
pDSP_G1$x <- round(pDSP_G1$x,1)
pDSP_G1$z <- round(pDSP_G1$z,1)
pDSP_G1 <- pDSP_G1[!duplicated(pDSP_G1[c(1,2,5,7,8,9)]),]
pDSP_G1 <- pDSP_G1 %>% distinct(PartNo,x,z,.keep_all = T)
View(pDSP_G1)
pDSP_part_G1 <- pDSP_G1[pDSP_G1$PartNo %in% c("607","621","623","624"),]
write.csv(pDSP_nodup_F,"Female-Landscape.csv");
View(pDSP_part_G1)
setwd("~/Documents/Third Year Project/Pointing Task/20Winter/Analysis/Shortcutting Visualization")
library(tidyverse)
setwd("~/Documents/MAT259/Final Project/HE_FinalProject/data")
library(tidyverse)
trialperform <- read.csv("Trialpointing.csv")
trialfeature <- read.csv("trialfeature.csv")
joint <- merge(x=trialperform,y=trialfeature,by="TrialID")
names(joint)
write.csv(joint,"Pointingperformance.csv")
setwd("~/Documents/Third Year Project/Pointing Task/20Winter/Analysis/Shortcutting Visualization")
library(tidyverse)
library(RColorBrewer)
pDSP_G1 <- read.csv("20WPointingDSP_Coords_F.csv")
pDSP_G2 <- read.csv("20WPointingDSP_Coords_M.csv")
pDSP_G1$x <- round(pDSP_G1$x,1)
pDSP_G1$z <- round(pDSP_G1$z,1)
pDSP_G1 <- pDSP_G1[!duplicated(pDSP_G1[c(1,2,5,7,8,9)]),]
pDSP_G1 <- pDSP_G1 %>% distinct(PartNo,x,z,.keep_all = T)
pDSP_G1$PartNo <- as.factor(pDSP_G1$PartNo)
pDSP_G1$PartGen <- as.factor(pDSP_G1$PartGen)
count <- rename(count(pDSP_G1, x, z), Freq = n)
ggplot(count,aes(x=Freq))+
geom_histogram()+
xlim(0,700)
summary(count)
heatmapmatrix <- matrix(data=NA, nrow = max(count$x)-min(count$x)+1,ncol = max(count$z)-min(count$z)+1)
for(i in 1:(max(count$x)-min(count$x)+1)) {
for(j in 1:(max(count$z)-min(count$z)+1)){
if(sum((count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1))>0){
heatmapmatrix[i,j]=count[(count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1),]$Freq
}else{
heatmapmatrix[i,j]=0
}
}
}
#library(dplyr)
pDSP_G1$x <- round(pDSP_G1$x,0)
pDSP_G1$z <- round(pDSP_G1$z,0)
count <- rename(count(pDSP_G1, x, z), Freq = n)
ggplot(count,aes(x=Freq))+
geom_histogram()+
xlim(0,700)
summary(count)
heatmapmatrix <- matrix(data=NA, nrow = max(count$x)-min(count$x)+1,ncol = max(count$z)-min(count$z)+1)
for(i in 1:(max(count$x)-min(count$x)+1)) {
for(j in 1:(max(count$z)-min(count$z)+1)){
if(sum((count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1))>0){
heatmapmatrix[i,j]=count[(count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1),]$Freq
}else{
heatmapmatrix[i,j]=0
}
}
}
write.csv(heatmapmatrix,"Female_landscape.csv")
for(i in 1:(max(count$x)-min(count$x)+1)) {
for(j in 1:(max(count$z)-min(count$z)+1)){
if(sum((count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1))>0){
heatmapmatrix[i,j]=count[(count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1),]$Freq
}else{
heatmapmatrix[i,j]=0
}
}
}
View(heatmapmatrix)
View(heatmapmatrix)
heatmapmatrix <- matrix(data=NA, nrow = max(count$x)-min(count$x)+1,ncol = max(count$z)-min(count$z)+1)
View(heatmapmatrix)
for(i in 1:(max(count$x)-min(count$x)+1)) {
for(j in 1:(max(count$z)-min(count$z)+1)){
if(sum((count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1))>0){
heatmapmatrix[i,j]=count[(count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1),]$Freq
}else{
heatmapmatrix[i,j]=0
}
}
}
View(heatmapmatrix)
write.csv(heatmapmatrix,"Female_landscape.csv")
#library(dplyr)
pDSP_G2$x <- round(pDSP_G1$x,0)
pDSP_G2 <- read.csv("20WPointingDSP_Coords_M.csv")
pDSP_G1 <- pDSP_G1[!duplicated(pDSP_G1[c(1,2,5,7,8,9)]),]
pDSP_G1 <- pDSP_G1 %>% distinct(PartNo,x,z,.keep_all = T)
pDSP_G2 <- pDSP_G2[!duplicated(pDSP_G1[c(1,2,5,7,8,9)]),]
pDSP_G2 <- pDSP_G2 %>% distinct(PartNo,x,z,.keep_all = T)
#library(dplyr)
pDSP_G2$x <- round(pDSP_G1$x,0)
View(pDSP_G2)
#library(dplyr)
pDSP_G2$x <- round(pDSP_G2$x,0)
pDSP_G2$z <- round(pDSP_G2$z,0)
count <- rename(count(pDSP_G2, x, z), Freq = n)
#ggplot(count,aes(x=Freq))+
#  geom_histogram()+
#  xlim(0,700)
summary(count)
heatmapmatrix <- matrix(data=NA, nrow = max(count$x)-min(count$x)+1,ncol = max(count$z)-min(count$z)+1)
for(i in 1:(max(count$x)-min(count$x)+1)) {
for(j in 1:(max(count$z)-min(count$z)+1)){
if(sum((count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1))>0){
heatmapmatrix[i,j]=count[(count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1),]$Freq
}else{
heatmapmatrix[i,j]=0
}
}
}
write.csv(heatmapmatrix,"Female_landscape.csv")
count <- rename(count(pDSP_G1, x, z), Freq = n)
#ggplot(count,aes(x=Freq))+
#  geom_histogram()+
#  xlim(0,700)
summary(count)
heatmapmatrix <- matrix(data=NA, nrow = max(count$x)-min(count$x)+1,ncol = max(count$z)-min(count$z)+1)
for(i in 1:(max(count$x)-min(count$x)+1)) {
for(j in 1:(max(count$z)-min(count$z)+1)){
if(sum((count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1))>0){
heatmapmatrix[i,j]=count[(count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1),]$Freq/length(unique(pDSP_G2$PartNo))
}else{
heatmapmatrix[i,j]=0
}
}
}
write.csv(heatmapmatrix,"Female_landscape.csv")
len <- length(unique(pDSP_G2$PartNo))
len <- length(unique(pDSP_G2$PartNo))
len
pDSP_G1$x <- round(pDSP_G1$x,0)
pDSP_G1$z <- round(pDSP_G1$z,0)
count <- rename(count(pDSP_G1, x, z), Freq = n)
len <- length(unique(pDSP_G1$PartNo))
len
heatmapmatrix <- matrix(data=NA, nrow = max(count$x)-min(count$x)+1,ncol = max(count$z)-min(count$z)+1)
for(i in 1:(max(count$x)-min(count$x)+1)) {
for(j in 1:(max(count$z)-min(count$z)+1)){
if(sum((count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1))>0){
heatmapmatrix[i,j]=count[(count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1),]$Freq/len
}else{
heatmapmatrix[i,j]=0
}
}
}
write.csv(heatmapmatrix,"Female_landscape.csv")
#library(dplyr)
pDSP_G2$x <- round(pDSP_G2$x,0)
pDSP_G2$z <- round(pDSP_G2$z,0)
count <- rename(count(pDSP_G2, x, z), Freq = n)
#ggplot(count,aes(x=Freq))+
#  geom_histogram()+
#  xlim(0,700)
summary(count)
len <- length(unique(pDSP_G2$PartNo))
len
heatmapmatrix <- matrix(data=NA, nrow = max(count$x)-min(count$x)+1,ncol = max(count$z)-min(count$z)+1)
for(i in 1:(max(count$x)-min(count$x)+1)) {
for(j in 1:(max(count$z)-min(count$z)+1)){
if(sum((count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1))>0){
heatmapmatrix[i,j]=count[(count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1),]$Freq/len
}else{
heatmapmatrix[i,j]=0
}
}
}
write.csv(heatmapmatrix,"Male_landscape.csv")
#library(dplyr)
pDSP_G1$x <- round(pDSP_G1$x,0)
pDSP_G1$z <- round(pDSP_G1$z,0)
count <- rename(count(pDSP_G1, x, z), Freq = n)
#ggplot(count,aes(x=Freq))+
#  geom_histogram()+
#  xlim(0,700)
summary(count)
len <- length(unique(pDSP_G1$PartNo))
len
heatmapmatrix <- matrix(data=NA, nrow = max(count$x)-min(count$x)+1,ncol = max(count$z)-min(count$z)+1)
for(i in 1:(max(count$x)-min(count$x)+1)) {
for(j in 1:(max(count$z)-min(count$z)+1)){
if(sum((count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1))>0){
heatmapmatrix[i,j]=count[(count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1),]$Freq/len
}else{
heatmapmatrix[i,j]=0
}
}
}
write.csv(heatmapmatrix,"Female_landscape.csv")
pDSP_G1 <- read.csv("20WPointingDSP_Coords_F.csv")
pDSP_G1 <- pDSP_G1[!duplicated(pDSP_G1[c(1,2,5,7,8,9)]),]
pDSP_G1 <- pDSP_G1 %>% distinct(PartNo,x,z,.keep_all = T)
pDSP_G1$PartNo <- as.factor(pDSP_G1$PartNo)
pDSP_G1$PartGen <- as.factor(pDSP_G1$PartGen)
pDSP_G1$x <- round(pDSP_G1$x,0)
pDSP_G1$z <- round(pDSP_G1$z,0)
count <- rename(count(pDSP_G1, x, z), Freq = n)
#ggplot(count,aes(x=Freq))+
#  geom_histogram()+
#  xlim(0,700)
summary(count)
len <- length(unique(pDSP_G1$PartNo))
len
heatmapmatrix <- matrix(data=NA, nrow = max(count$x)-min(count$x)+1,ncol = max(count$z)-min(count$z)+1)
for(i in 1:(max(count$x)-min(count$x)+1)) {
for(j in 1:(max(count$z)-min(count$z)+1)){
if(sum((count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1))>0){
heatmapmatrix[i,j]=count[(count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1),]$Freq/len
}else{
heatmapmatrix[i,j]=0
}
}
}
write.csv(heatmapmatrix,"Female_landscape.csv")
pDSP <- rbind(pDSP_G1,pDSP_G2)
pDSP <- pDSP[!duplicated(pDSP_G1[c(1,2,5,7,8,9)]),]
pDSP <- pDSP %>% distinct(PartNo,x,z,.keep_all = T)
pDSP$PartNo <- as.factor(pDSP$PartNo)
pDSP$PartGen <- as.factor(pDSP$PartGen)
unique(pDSP[pDSP$PartGen=="1",]$PartNo)
length(unique(pDSP[pDSP$PartGen=="1",]$PartNo))
unique(pDSP[pDSP$PartGen=="0",]$PartNo)
length(unique(pDSP[pDSP$PartGen=="0",]$PartNo))
pDSP <- rbind(pDSP_G1,pDSP_G2)
pDSP <- pDSP[!duplicated(pDSP[c(1,2,5,7,8,9)]),]
pDSP <- pDSP %>% distinct(PartNo,x,z,.keep_all = T)
pDSP$PartNo <- as.factor(pDSP$PartNo)
pDSP$PartGen <- as.factor(pDSP$PartGen)
unique(pDSP[pDSP$PartGen=="1",]$PartNo)
length(unique(pDSP[pDSP$PartGen=="1",]$PartNo))
unique(pDSP[pDSP$PartGen=="0",]$PartNo)
length(unique(pDSP[pDSP$PartGen=="0",]$PartNo))
pDSP <- rbind(pDSP_G1,pDSP_G2)
pDSP <- pDSP[!duplicated(pDSP[c(1,2,5,7,8,9)]),]
pDSP <- pDSP %>% distinct(PartNo,x,z,.keep_all = T)
pDSP <- rbind(pDSP_G1,pDSP_G2)
pDSP <- pDSP[!duplicated(pDSP[c(1,2,5,7,8,9)]),]
pDSP_G1 <- read.csv("20WPointingDSP_Coords_F.csv")
pDSP_G2 <- read.csv("20WPointingDSP_Coords_M.csv")
pDSP <- rbind(pDSP_G1,pDSP_G2)
pDSP <- pDSP[!duplicated(pDSP[c(1,2,5,7,8)]),]
pDSP$PartNo <- as.factor(pDSP$PartNo)
pDSP$PartGen <- as.factor(pDSP$PartGen)
unique(pDSP[pDSP$PartGen=="1",]$PartNo)
length(unique(pDSP[pDSP$PartGen=="1",]$PartNo))
unique(pDSP[pDSP$PartGen=="0",]$PartNo)
length(unique(pDSP[pDSP$PartGen=="0",]$PartNo))
#library(dplyr)
pDSP_round <- pDSP
pDSP_round$x <- round(pDSP_round$x,0)
pDSP_round$z <- round(pDSP_round$z,0)
count <- rename(count(pDSP_round, x, z), Freq = n)
#ggplot(count,aes(x=Freq))+
#  geom_histogram()+
#  xlim(0,700)
summary(count)
len <- length(unique(pDSP$PartNo))
len
heatmapmatrix <- matrix(data=NA, nrow = max(count$x)-min(count$x)+1,ncol = max(count$z)-min(count$z)+1)
for(i in 1:(max(count$x)-min(count$x)+1)) {
for(j in 1:(max(count$z)-min(count$z)+1)){
if(sum((count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1))>0){
heatmapmatrix[i,j]=count[(count$x==i+min(count$x)-1)&(count$z==j+min(count$z)-1),]$Freq/len
}else{
heatmapmatrix[i,j]=0
}
}
}
#write.csv(heatmapmatrix,"3DHeatmap_landscape.csv")
write.csv(heatmapmatrix,"3DHeatmap_landscape.csv")
count <- rename(count(pDSP_round, x, z), Freq = n/len)
count$Precent <- count$Freq/len
#ggplot(count,aes(x=Freq))+
#  geom_histogram()+
#  xlim(0,700)
summary(count)
500/27
500/57
