gfx-price-compar.R

#/usr/bin/env RScript
require("readODS")
require("reshape2")
require("ggplot2")
rm(list=ls())
setwd("~/RWD")
sheet <- read_ods("gfx_linux_comp.ods", sheet="data", col_names=TRUE)
melted <- melt(sheet, id.vars=c("model", "brand", "manufacturer", "price", "price-msrp", "price-low"))

lm_model <- lm(log(value)~log(price)+brand, data=melted)
fitline <- data.frame(price=log(220:780))
fitline$amd <- lm_model$coefficients["(Intercept)"]+fitline$price*lm_model$coefficients["log(price)"]
fitline$nvidia <- lm_model$coefficients["(Intercept)"]+fitline$price*lm_model$coefficients["log(price)"]+lm_model$coefficients["brandnvidia"]
fitline <- exp(fitline)
summary(lm_model)

lm_model.msrp <- lm(log(value)~log(`price-msrp`)+brand, data=melted)
fitline.msrp <- data.frame(price=log(229:709))
fitline.msrp$amd <- lm_model.msrp$coefficients["(Intercept)"]+fitline.msrp$price*lm_model.msrp$coefficients["log(`price-msrp`)"]
fitline.msrp$nvidia <- lm_model.msrp$coefficients["(Intercept)"]+fitline.msrp$price*lm_model.msrp$coefficients["log(`price-msrp`)"]+lm_model.msrp$coefficients["brandnvidia"]
fitline.msrp <- exp(fitline.msrp)
summary(lm_model.msrp)

lm_model.low <- lm(log(value)~log(`price-low`)+brand, data=melted)
fitline.low <- data.frame(price=log(229:709))
fitline.low$amd <- lm_model.low$coefficients["(Intercept)"]+fitline.low$price*lm_model.low$coefficients["log(`price-low`)"]
fitline.low$nvidia <- lm_model.low$coefficients["(Intercept)"]+fitline.low$price*lm_model.low$coefficients["log(`price-low`)"]+lm_model.low$coefficients["brandnvidia"]
fitline.low <- exp(fitline.low)
summary(lm_model.low)

plot_data <- ggplot() +
	geom_point(data=melted, aes(x=price, y=value, color=brand), size=2, alpha=0.5, stroke=0) +
	scale_colour_manual(values=c("#ed1c24", "#b9e700")) +
	geom_line(data=fitline, size=1, alpha=0.5, aes(x=price, y=amd), color="#ed1c24") +
	geom_line(data=fitline, size=1, alpha=0.5, aes(x=price, y=nvidia), color="#b9e700") +
	labs(x="Price", y="frames per second", title="Frames per second based on the graphic card price", subtitle="Using log-log fit: log(value)~log(price)+brand", caption="Source: https://www.phoronix.com/scan.php?page=article&item=nvidia387-linux415-mesa174
	Prices were acquired from newegg.com in 2017-12-09 with care to select the lowest-priced matching card.
	The coefficients of the fit can be interpreted as for every 1% of increased price,
	you get 0.5101% of increased performance. And Nvidia cards have 19.68% bigger performance overall.
	The interaction of ogl and vulcan and different resolutions were not considered in this study.")
png("price-fps-liunx.png", width=640, height=640)
plot_data

dev.off()

plot_data_adj <- ggplot() +
	geom_point(data=melted, aes(x=`price-msrp`, y=value, color=brand), size=2, alpha=0.5, stroke=0, shape=4) +
	geom_point(data=melted, aes(x=`price-low`, y=value, color=brand), size=2, alpha=0.5, stroke=0, shape=1) +
	scale_colour_manual(values=c("#ed1c24", "#b9e700")) +
	geom_line(data=fitline.msrp, size=0.5, alpha=1, aes(x=price, y=amd), color="#ed1c24", linetype="dotted") +
	geom_line(data=fitline.msrp, size=0.5, alpha=1, aes(x=price, y=nvidia), color="#5C6F06", linetype="dotted") +
	geom_line(data=fitline.low, size=0.5, alpha=1, aes(x=price, y=amd), color="#ed1c24", linetype="dashed") +
	geom_line(data=fitline.low, size=0.5, alpha=1, aes(x=price, y=nvidia), color="#b9e700", linetype="dashed") +
	labs(x="Price", y="frames per second", title="Frames per second based on the graphic card price with data from /u/mad_mesa", subtitle="Using log-log fit: log(value)~log(price)+brand", caption="Source: https://www.phoronix.com/scan.php?page=article&item=nvidia387-linux415-mesa174
	Using data from user /u/mad_mesa. Crosses and dotted line corresponds to MSRP price
	and circles with dashed line corresponds to low price.
	The coefficients for MSRP were 0.50638% performance increase per 1% of price
	and nvidia being 14.646% more performant.
	The coefficients for low price were 0.64273% performance increase per 1% of price
	and nvidia being 6.318% more performant.")
ggsave(plot_data_adj, filename= "price-fps-liunx-adj.png")
png("price-fps-liunx-adj.png", width=640, height=640, type="cairo")
plot_data_adj

dev.off()

gfx_linux_comp.csv