Pequeño arreglo en la entrada anterior.

Al final enconté la solución en la extraña representación. Los ejes estaban alrevés.
Aquí os dejo los nuevos scripts y como queadarían bien representadas las solucioens.
En el resto de scripts bastaría cambiar lo siguiente :
  annotation_custom(grob = image_1, # Image
                    xmin= 0, # Coordinates to represent the image
                    xmax= 1000,
                    ymin= 0,
                    ymax= 700 # Ahora ya ajustará bien
                   
  ) +

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En este script solo hay que fijarse en las dos últimas lineas donde hago el cambio de coordenas para que ajuste correctamente en las gráficas.

	needed <- list("dplyr", "data.table", # Libraries for data mining
	"jpeg", "ggplot2", "png", "grid", "geoR", "rgl", # Libraries for
	"repmis" # Libraries for web scrapping [3]
	)
	if(FALSE){ # If you want to install change for TRUE
	lapply(X = needed ,FUN =
	function(x){
	if(!require(x, character.only = T)){
	install.packages(x)
	}
	library(x,character.only = T)
	})
	}else{
	lapply(X = needed ,FUN =
	function(x){
	library(x,character.only = T)
	})
	}
	dir <- # "C:/Users/Javier Villacampa/Dropbox/Chabi/Blog/Eye track/"
	"C:/Users/usuario/Dropbox/Chabi/Blog/5 Eye track/" # Put your dir
	setwd(dir)
	dir.create(path = "Results")
	dir.create(path = "Data")
	rm(list = ls()); gc()
	# S read data -------------------------------------------------------------
	# Download the image
	url <- "http://2.bp.blogspot.com/-Qo8JF_ux808/VlEAanXvltI/AAAAAAAACds/TkzNkifUK4M/s1600/Imagen1.jpeg"
	download.file(url = url, destfile = "Data/Imagen1.jpeg", mode = "wb")
	image_1 <- readJPEG( source = "Data/Imagen1.jpeg")
	image_1 <- rasterGrob(image = image_1, interpolate=TRUE)
	# Download the csv from dropbox
	# https://www.dropbox.com/s/1s4uo7u340snqtv/sample-1.txt?dl=0
	d <- repmis::source_DropboxData(file = "sample-1.txt", key = "1s4uo7u340snqtv", sep ="\t") %>% data.table()
	# E read data -------------------------------------------------------------
	# S Clean data ------------------------------------------------------------
	d[ , TRIAL_INDEX := factor(TRIAL_INDEX)]
	d[ , Subject := factor(Subject)]
	d <- d[ d$CURRENT_FIX_X <= 1000 & d$CURRENT_FIX_X >= 0 &
	d$CURRENT_FIX_Y <= 700 & d$CURRENT_FIX_Y >= 0, ]
	# S Clean data ------------------------------------------------------------
	# S Plot ------------------------------------------------------------------
	d <- d %>% data.frame()
	d2 <- copy(d) # Save a copy from the old data
	d <- d2[, c("CURRENT_FIX_X", "CURRENT_FIX_Y")]
	d$CURRENT_FIX_Y_2 <- d$CURRENT_FIX_Y
	d$CURRENT_FIX_Y <-
	-d$CURRENT_FIX_Y + 700
	# E Plot ------------------------------------------------------------------

view raw Bloog005.b 01 read.r hosted with ❤ by GitHub

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