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# Personal Photo Histry | |
library("rPlotter") | |
library("magrittr") | |
library("grid") | |
library("gridSVG") | |
library("ggplot2") | |
#retreives list of every .jpeg on my hard-drive | |
files_list1 <- list.files(path="//Volumes//Seagate Backup Plus Drive/Pictures/", pattern = ".*(jpg|JPG|jpeg|JPEG)", full.names=T, recursive=T) | |
files_list2 <- list.files(path="//Volumes//Seagate Backup Plus Drive/Picuters /", pattern = ".*(jpg|JPG|jpeg|JPEG)", full.names=T, recursive=T) | |
all_jpgs <- c(files_list1, files_list2) | |
#extracts the file path and creation date | |
info <- file.info(all_jpgs) | |
info_path <- info | |
info_path["file_path"] <- rownames(info) | |
#extracts the most common color from each photo. This took a while... | |
pic_colors <- data.frame() | |
for (i in 1:length(info_path$file_path)) { | |
pic_color <- color(info_path$file_path[i]) | |
pic_colors <- rbind(pic_colors, t(data.frame(pic_color))) | |
print(i) | |
} | |
#combies the files information with the most common color | |
per_photo_color <- cbind(info_path, pic_colors) | |
write.csv(per_photo_color, file = "brett_photo_color.csv") | |
#----- read data in --- | |
per_photo_color <- read.csv("Color_Personal/brett_photo_color.csv") | |
b_photo_color <- per_photo_color[c("mtime", "V1")] | |
colnames(b_photo_color) <- c("create_date", "color") | |
b_photo_color <- b_photo_color[order(b_photo_color$create_date),] | |
#reformats the year coloum | |
year <- strftime(b_photo_color$create_dat, format="%Y") %>% data.frame() | |
b_photo_color <- cbind(b_photo_color, year) | |
b_photo_color["color"] <- as.character(b_photo_color$color) | |
b_photo_color["."] <- as.character(b_photo_color$.) | |
colnames(b_photo_color) <- c("create_date", "color", "year") | |
p_color <- subset(b_photo_color, b_photo_color$color != "NULL") | |
#plotting the distribution of color | |
#distribtion of color by year | |
grid.newpage() | |
xpos <- .05 | |
for (p in 2006:2015) { | |
grid.raster(unlist(subset(p_color, year == p, select = "color")), | |
x = xpos, | |
width = .1, | |
height = .8, | |
interpolate = FALSE) | |
grid.text(p, x = xpos, y = .075, gp = gpar(col = "black", fontsize = 13)) | |
xpos <- xpos + .1 | |
} | |
grid.text("Personal Photo Collection", x =.5, y = .95, just = c("centre","centre"), gp = gpar(col = "black", fontsize = 30)) | |
#exporting data visualization | |
grid.export("Color_Personal/colorYear.svg") | |
# number of photos by year | |
yearFreq <- table(p_color$year) %>% data.frame() | |
colnames(yearFreq) <- c("year", "freq") | |
yearFreq$year <- factor(yearFreq$year, levels = yearFreq$year[order(-as.numeric(yearFreq$year))]) | |
yearFreqPlot <- ggplot(yearFreq, aes(x = year, y = freq)) + | |
geom_bar(stat = "identity", fill = "royal blue") + | |
coord_flip() + | |
labs(title = "Number of photos taken by year", y = "# of Photos", x = "Year") + | |
theme(legend.position="bottom", legend.direction="horizontal") + | |
scale_y_continuous(limits = c(0,4000), breaks = pretty(0:4000, n = 10), labels = pretty(0:4000, n = 10)) + | |
themeBrettrics | |
#crearting the svg image | |
svg(filename = "Color_Personal/yearFreq.svg", | |
width = 7, | |
height = 5, | |
pointsize = 5) | |
print(yearFreqPlot) | |
dev.off() | |
#---functions--- | |
color <- function(x) { | |
return(tryCatch({ | |
extract_colours(x, 1) | |
}, | |
error = function(e) { | |
"NULL" | |
})) | |
} |
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