513 lines
16 KiB
R
Executable File
513 lines
16 KiB
R
Executable File
sum(x1_array_forward_shooting<0)
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x3_array_forward_shooting[l]
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x3_growth = (x3_array_forward_shooting[l]-x3_array_forward_shooting[l-1])/x3_array_forward_shooting[l-1]/(1*stepsize)
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x3_growth
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sum(x3_array_forward_shooting<0)
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a1_growth = (a1_array_forward_shooting[l]-a1_array_forward_shooting[l-1])/a1_array_forward_shooting[l-1]/stepsize
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a1_growth
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a3_growth = (a3_array_forward_shooting[l]-a3_array_forward_shooting[l-1])/a3_array_forward_shooting[l-1]/stepsize
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a3_growth
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a1_array_forward_shooting[l]/x1_array_forward_shooting[l]
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plot((a1_array_forward_shooting/x1_array_forward_shooting)[(l-100)-l])
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# Forward shooting
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options(digits=7)
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## Evolution
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x1_array_forward_shooting <- c()
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x3_array_forward_shooting <- c()
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a1_array_forward_shooting <- c()
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a3_array_forward_shooting <- c()
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s1_array_forward_shooting <- c()
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s3_array_forward_shooting <- c()
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x1_t = x1_init
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x3_t = x3_init
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#stepsize
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comienzo = Sys.time()
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max = max(times_forward_shooting)
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for(t in times_forward_shooting){
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if((100*t/max) %in% seq(from=0, to=100, by=1)){
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cat(paste(floor(100*t/max), "%", sep=""))
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cat("\n")
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}
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a1_t = a1(t)
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a3_t = a3(t)
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s1_t = s1(t)
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s3_t = s3(t)
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x1_t = x1_t*(1+r1_stepsize) + dx1(t)*stepsize
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x3_t = x3_t*(1+r3_stepsize) + dx3(t)*stepsize
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a1_array_forward_shooting <- c(a1_array_forward_shooting, a1_t)
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a3_array_forward_shooting <- c(a3_array_forward_shooting, a3_t)
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s1_array_forward_shooting <- c(s1_array_forward_shooting, s1_t)
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s3_array_forward_shooting <- c(s3_array_forward_shooting, s3_t)
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x1_array_forward_shooting <- c(x1_array_forward_shooting, x1_t)
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x3_array_forward_shooting <- c(x3_array_forward_shooting, x3_t)
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}
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# Variables
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η = 0.9 ## 1.1
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ρ = 0.005
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r_1 = 0.06
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r_3 = -0.05
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γ_1 = 0.03
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γ_3 = 0.01
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w_3 = 5000 ## Mean on the EA Survey 2018- ~7000
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β_3 = 1 ## 1 ## 0.5 Corresponds to roughly 5 people convincing 10 other people per year on a 50k year budget
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## Dramatic if beta = 0.5, w_3 = 1000
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λ_1 = 0.5
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λ_3 = 0.5
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δ_3 = 0.44
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## k1_forward_shooting
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k1_forward_shooting = 3*10^(-7) ## 1*10^(-7) fails. 2*10^(-7) fails
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k1_reverse_shooting = k1_forward_shooting
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## Artfully guessed, such that s1 < 1
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stepsize = 0.1
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## stepsize = 0.1 => seconds (7s).
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## stepsize = 0.01 => minutes (3 mins).
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r1_stepsize = ((1+r_1)^stepsize)-1
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r3_stepsize = ((1+r_3)^stepsize)-1
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first = 0
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last = 1000
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times_forward_shooting = seq(from=first, to=last, by=stepsize)
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times_reverse_shooting = seq(from=last, to=first, by=-stepsize)
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### Initial conditions. Correspond to "year 0".
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x1_init = 10^10 ## 1 billion? 15 billion? 100 billion? Too much?
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x3_init = 10^5
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# Forward shooting
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options(digits=7)
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## Evolution
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x1_array_forward_shooting <- c()
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x3_array_forward_shooting <- c()
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a1_array_forward_shooting <- c()
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a3_array_forward_shooting <- c()
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s1_array_forward_shooting <- c()
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s3_array_forward_shooting <- c()
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x1_t = x1_init
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x3_t = x3_init
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#stepsize
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comienzo = Sys.time()
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max = max(times_forward_shooting)
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for(t in times_forward_shooting){
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if((100*t/max) %in% seq(from=0, to=100, by=1)){
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cat(paste(floor(100*t/max), "%", sep=""))
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cat("\n")
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}
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a1_t = a1(t)
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a3_t = a3(t)
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s1_t = s1(t)
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s3_t = s3(t)
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x1_t = x1_t*(1+r1_stepsize) + dx1(t)*stepsize
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x3_t = x3_t*(1+r3_stepsize) + dx3(t)*stepsize
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a1_array_forward_shooting <- c(a1_array_forward_shooting, a1_t)
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a3_array_forward_shooting <- c(a3_array_forward_shooting, a3_t)
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s1_array_forward_shooting <- c(s1_array_forward_shooting, s1_t)
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s3_array_forward_shooting <- c(s3_array_forward_shooting, s3_t)
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x1_array_forward_shooting <- c(x1_array_forward_shooting, x1_t)
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x3_array_forward_shooting <- c(x3_array_forward_shooting, x3_t)
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}
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fin = Sys.time()
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fin-comienzo
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## Checking condition
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options(digits=22)
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l = length(times_forward_shooting)
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x1_array_forward_shooting[l]
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x1_growth = (x1_array_forward_shooting[l]-x1_array_forward_shooting[l-1])/x1_array_forward_shooting[l-1]/(1*stepsize)
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x1_growth
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sum(x1_array_forward_shooting<0)
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x3_array_forward_shooting[l]
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x3_growth = (x3_array_forward_shooting[l]-x3_array_forward_shooting[l-1])/x3_array_forward_shooting[l-1]/(1*stepsize)
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x3_growth
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sum(x3_array_forward_shooting<0)
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a1_growth = (a1_array_forward_shooting[l]-a1_array_forward_shooting[l-1])/a1_array_forward_shooting[l-1]/stepsize
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a1_growth
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a3_growth = (a3_array_forward_shooting[l]-a3_array_forward_shooting[l-1])/a3_array_forward_shooting[l-1]/stepsize
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a3_growth
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a1_array_forward_shooting[l]/x1_array_forward_shooting[l]
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plot((a1_array_forward_shooting/x1_array_forward_shooting)[(l-100)-l])
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# Plotting
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## install.packages("tidyverse") <- Not totally necessary.
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## install.packages("ggplot2")
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## install.packages("ggsci")
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library(ggplot2)
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library(ggsci)
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## General variables
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saveplots=TRUE
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times = times_forward_shooting
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## Also for reverse shooting plots; time in reverse shooting is inverted
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shootingtype="reverse"#"forward"#
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shootingtype="forward"#"reverse"#
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directory = paste("/home/nuno/Documents/core/SRF/BackShooting/RCode/plots/satisfactory3/", shootingtype, "shooting", "/", last, "years", sep="")
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directory
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setwd(directory)
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if(shootingtype=="forward"){
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x1_array_plotting <- x1_array_forward_shooting
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x3_array_plotting <- x3_array_forward_shooting
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a1_array_plotting <- a1_array_forward_shooting
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a3_array_plotting <- a3_array_forward_shooting
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s1_array_plotting <- s1_array_forward_shooting
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s3_array_plotting <- s3_array_forward_shooting
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} else if(shootingtype=="reverse"){
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x1_array_plotting <- x1_array_reverse_shooting
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x3_array_plotting <- x3_array_reverse_shooting
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a1_array_plotting <- a1_array_reverse_shooting
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a3_array_plotting <- a3_array_reverse_shooting
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s1_array_plotting <- s1_array_reverse_shooting
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s3_array_plotting <- s3_array_reverse_shooting
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}
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height = 5
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width = floor(height*(1+sqrt(5))/2)
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imagenumbercounter = 1
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saveplot = function(imagename){
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if(saveplots){
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ggsave(paste(imagenumbercounter,"_", imagename, "_",shootingtype, "shooting",".png", sep =""), units="in", width=width, height=height)
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imagenumbercounter <<- imagenumbercounter+1
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## https-//stackoverflow.com/questions/1236620/global-variables-in-r
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}
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}
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options(digits=1) ## Just for display
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xs <- list()
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xs$values <- c(x1_array_plotting, x3_array_plotting)
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xs$var <- c(rep("x1", length(x1_array_plotting)), rep("x3", length(x3_array_plotting)))
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xs$times = rep(times,2)
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xs <- as.data.frame(xs)
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title_text = "Evolution of state variables"
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(ggplot(data = xs, aes(x = times, y= values, color = var)) +
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geom_line(size = 0.5)
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+ labs(
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title=title_text,
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#subtitle="n =303",
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x="Year since start",
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y="Capital and labor"
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#caption="@EA Mental Health Survey"
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)
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+theme(
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legend.title = element_blank(),
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#plot.subtitle = element_text(hjust = 0.5),
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plot.title = element_text(hjust = 0.5),
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#axis.text.y = element_blank(),
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legend.position="bottom",
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legend.box="vertical"
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)
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+ scale_color_lancet(
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breaks=c("x1", "x3"),
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labels=c("Capital", "Labor")
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)
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+ scale_y_continuous(breaks = seq(min(x1_array_plotting), max(x1_array_plotting), length.out=5))
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)
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## x1 and x3- log plot
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title_text = "Evolution of state variables"
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(ggplot(data = xs, aes(x = times, y= values, color = var)) +
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geom_line(size = 0.5)
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+labs(
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title=title_text,
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subtitle="(logarithmic scale)",
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#subtitle="n =303",
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x="Year since start",
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y="Capital and labor"
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#caption="@EA Mental Health Survey"
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)
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+theme(
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legend.title = element_blank(),
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#plot.subtitle = element_text(hjust = 0.5),
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plot.title = element_text(hjust = 0.5),
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plot.subtitle = element_text(hjust = 0.5),
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#axis.text.y = element_blank(),
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legend.position="bottom",
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legend.box="vertical"
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)
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+ scale_color_lancet(
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breaks=c("x1", "x3"),
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labels=c("Capital", "Labor")
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)
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+ scale_y_continuous(trans = 'log2')
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)
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saveplot("StateVariablesX1X3logplot")
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## Only x3
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equis3 <- list()
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equis3$values <- c(x3_array_plotting)
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equis3$times = times
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equis3 <- as.data.frame(equis3)
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title_text = "Evolution of movement size"
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(ggplot(data = equis3, aes(x = times, y= values))
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+geom_line(size = 0.5)
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+labs(
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title=title_text,
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#subtitle="n =303",
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x="Year since start",
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y="Labor"
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#caption="@EA Mental Health Survey"
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)
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+theme(
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legend.title = element_blank(),
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#plot.subtitle = element_text(hjust = 0.5),
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plot.title = element_text(hjust = 0.5),
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#axis.text.y = element_blank(),
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legend.position="bottom",
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legend.box="vertical"
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)
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##+ scale_color_lancet()
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)
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saveplot("StateVariableX3")
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## s1, s3, s4
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sigmas <- list()
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s4_array_plotting=1-s1_array_plotting-s3_array_plotting
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sigmas$values <- c(s1_array_plotting, s3_array_plotting,s4_array_plotting)
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sigmas$fraction <- c(rep("s1", length(s1_array_plotting)), rep("s3", length(s3_array_plotting)),rep("s4", length(s3_array_plotting)))
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sigmas$times = rep(times,3)
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sigmas <- as.data.frame(sigmas)
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title_text = "Evolution of labor fractions"
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(ggplot(data = sigmas, aes(x = times, y= values, color = fraction)) +
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geom_line(size = 0.5)
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+labs(
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title=title_text,
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#subtitle="n =303",
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x="Year since start",
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y="Fraction of total labor"
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#caption="@EA Mental Health Survey"
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)
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+theme(
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legend.title = element_blank(),
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#plot.subtitle = element_text(hjust = 0.5),
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plot.title = element_text(hjust = 0.5),
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#axis.text.y = element_blank(),
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legend.position="bottom",
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legend.direction="vertical"
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)
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+ scale_color_lancet(
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breaks=c("s1", "s3", "s4"),
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labels=c("Direct work", "Movement building", "Money-making")
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)
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)
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# Variables
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η = 0.9 ## 1.1
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ρ = 0.005
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r_1 = 0.06
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r_3 = -0.02
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γ_1 = 0.03
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γ_3 = 0.01
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w_3 = 5000 ## Mean on the EA Survey 2018- ~7000
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β_3 = 1 ## 1 ## 0.5 Corresponds to roughly 5 people convincing 10 other people per year on a 50k year budget
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## Dramatic if beta = 0.5, w_3 = 1000
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λ_1 = 0.5
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λ_3 = 0.5
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δ_3 = 0.44
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## k1_forward_shooting
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k1_forward_shooting = 3*10^(-7) ## 1*10^(-7) fails. 2*10^(-7) fails
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k1_reverse_shooting = k1_forward_shooting
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## Artfully guessed, such that s1 < 1
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stepsize = 0.1
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## stepsize = 0.1 => seconds (7s).
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## stepsize = 0.01 => minutes (3 mins).
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r1_stepsize = ((1+r_1)^stepsize)-1
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r3_stepsize = ((1+r_3)^stepsize)-1
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first = 0
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last = 1000
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times_forward_shooting = seq(from=first, to=last, by=stepsize)
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times_reverse_shooting = seq(from=last, to=first, by=-stepsize)
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### Initial conditions. Correspond to "year 0".
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x1_init = 10^10 ## 1 billion? 15 billion? 100 billion? Too much?
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x3_init = 10^5
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# Forward shooting
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options(digits=7)
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## Evolution
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x1_array_forward_shooting <- c()
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x3_array_forward_shooting <- c()
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a1_array_forward_shooting <- c()
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a3_array_forward_shooting <- c()
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s1_array_forward_shooting <- c()
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s3_array_forward_shooting <- c()
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x1_t = x1_init
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x3_t = x3_init
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#stepsize
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comienzo = Sys.time()
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max = max(times_forward_shooting)
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for(t in times_forward_shooting){
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if((100*t/max) %in% seq(from=0, to=100, by=1)){
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cat(paste(floor(100*t/max), "%", sep=""))
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cat("\n")
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}
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a1_t = a1(t)
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a3_t = a3(t)
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s1_t = s1(t)
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s3_t = s3(t)
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x1_t = x1_t*(1+r1_stepsize) + dx1(t)*stepsize
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x3_t = x3_t*(1+r3_stepsize) + dx3(t)*stepsize
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a1_array_forward_shooting <- c(a1_array_forward_shooting, a1_t)
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a3_array_forward_shooting <- c(a3_array_forward_shooting, a3_t)
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s1_array_forward_shooting <- c(s1_array_forward_shooting, s1_t)
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s3_array_forward_shooting <- c(s3_array_forward_shooting, s3_t)
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x1_array_forward_shooting <- c(x1_array_forward_shooting, x1_t)
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x3_array_forward_shooting <- c(x3_array_forward_shooting, x3_t)
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}
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fin = Sys.time()
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fin-comienzo
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## Checking condition
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options(digits=22)
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l = length(times_forward_shooting)
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x1_array_forward_shooting[l]
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x1_growth = (x1_array_forward_shooting[l]-x1_array_forward_shooting[l-1])/x1_array_forward_shooting[l-1]/(1*stepsize)
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x1_growth
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sum(x1_array_forward_shooting<0)
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x3_array_forward_shooting[l]
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x3_growth = (x3_array_forward_shooting[l]-x3_array_forward_shooting[l-1])/x3_array_forward_shooting[l-1]/(1*stepsize)
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x3_growth
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sum(x3_array_forward_shooting<0)
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a1_growth = (a1_array_forward_shooting[l]-a1_array_forward_shooting[l-1])/a1_array_forward_shooting[l-1]/stepsize
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a1_growth
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a3_growth = (a3_array_forward_shooting[l]-a3_array_forward_shooting[l-1])/a3_array_forward_shooting[l-1]/stepsize
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a3_growth
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a1_array_forward_shooting[l]/x1_array_forward_shooting[l]
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plot((a1_array_forward_shooting/x1_array_forward_shooting)[(l-100)-l])
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# Plotting
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## install.packages("tidyverse") <- Not totally necessary.
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## install.packages("ggplot2")
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## install.packages("ggsci")
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library(ggplot2)
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library(ggsci)
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## General variables
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saveplots=TRUE
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times = times_forward_shooting
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## Also for reverse shooting plots; time in reverse shooting is inverted
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shootingtype="reverse"#"forward"#
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shootingtype="forward"#"reverse"#
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directory = paste("/home/nuno/Documents/core/SRF/BackShooting/RCode/plots/satisfactory3/", shootingtype, "shooting", "/", last, "years", sep="")
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directory
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setwd(directory)
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if(shootingtype=="forward"){
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x1_array_plotting <- x1_array_forward_shooting
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x3_array_plotting <- x3_array_forward_shooting
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a1_array_plotting <- a1_array_forward_shooting
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a3_array_plotting <- a3_array_forward_shooting
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s1_array_plotting <- s1_array_forward_shooting
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s3_array_plotting <- s3_array_forward_shooting
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} else if(shootingtype=="reverse"){
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x1_array_plotting <- x1_array_reverse_shooting
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x3_array_plotting <- x3_array_reverse_shooting
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a1_array_plotting <- a1_array_reverse_shooting
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a3_array_plotting <- a3_array_reverse_shooting
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s1_array_plotting <- s1_array_reverse_shooting
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s3_array_plotting <- s3_array_reverse_shooting
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}
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height = 5
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width = floor(height*(1+sqrt(5))/2)
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imagenumbercounter = 1
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saveplot = function(imagename){
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if(saveplots){
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ggsave(paste(imagenumbercounter,"_", imagename, "_",shootingtype, "shooting",".png", sep =""), units="in", width=width, height=height)
|
||
imagenumbercounter <<- imagenumbercounter+1
|
||
## https-//stackoverflow.com/questions/1236620/global-variables-in-r
|
||
}
|
||
}
|
||
options(digits=1) ## Just for display
|
||
xs <- list()
|
||
xs$values <- c(x1_array_plotting, x3_array_plotting)
|
||
xs$var <- c(rep("x1", length(x1_array_plotting)), rep("x3", length(x3_array_plotting)))
|
||
xs$times = rep(times,2)
|
||
xs <- as.data.frame(xs)
|
||
title_text = "Evolution of state variables"
|
||
(ggplot(data = xs, aes(x = times, y= values, color = var)) +
|
||
geom_line(size = 0.5)
|
||
+ labs(
|
||
title=title_text,
|
||
#subtitle="n =303",
|
||
x="Year since start",
|
||
y="Capital and labor"
|
||
#caption="@EA Mental Health Survey"
|
||
)
|
||
+theme(
|
||
legend.title = element_blank(),
|
||
#plot.subtitle = element_text(hjust = 0.5),
|
||
plot.title = element_text(hjust = 0.5),
|
||
#axis.text.y = element_blank(),
|
||
legend.position="bottom",
|
||
legend.box="vertical"
|
||
)
|
||
+ scale_color_lancet(
|
||
breaks=c("x1", "x3"),
|
||
labels=c("Capital", "Labor")
|
||
)
|
||
+ scale_y_continuous(breaks = seq(min(x1_array_plotting), max(x1_array_plotting), length.out=5))
|
||
)
|
||
saveplot("StateVariablesX1X3")
|
||
## x1 and x3- log plot
|
||
title_text = "Evolution of state variables"
|
||
(ggplot(data = xs, aes(x = times, y= values, color = var)) +
|
||
geom_line(size = 0.5)
|
||
+labs(
|
||
title=title_text,
|
||
subtitle="(logarithmic scale)",
|
||
#subtitle="n =303",
|
||
x="Year since start",
|
||
y="Capital and labor"
|
||
#caption="@EA Mental Health Survey"
|
||
)
|
||
+theme(
|
||
legend.title = element_blank(),
|
||
#plot.subtitle = element_text(hjust = 0.5),
|
||
plot.title = element_text(hjust = 0.5),
|
||
plot.subtitle = element_text(hjust = 0.5),
|
||
#axis.text.y = element_blank(),
|
||
legend.position="bottom",
|
||
legend.box="vertical"
|
||
)
|
||
+ scale_color_lancet(
|
||
breaks=c("x1", "x3"),
|
||
labels=c("Capital", "Labor")
|
||
)
|
||
+ scale_y_continuous(trans = 'log2')
|
||
)
|
||
saveplot("StateVariablesX1X3logplot")
|
||
## Only x3
|
||
equis3 <- list()
|
||
equis3$values <- c(x3_array_plotting)
|
||
equis3$times = times
|
||
equis3 <- as.data.frame(equis3)
|
||
title_text = "Evolution of movement size"
|
||
(ggplot(data = equis3, aes(x = times, y= values))
|
||
+geom_line(size = 0.5)
|
||
+labs(
|
||
title=title_text,
|
||
#subtitle="n =303",
|
||
x="Year since start",
|
||
y="Labor"
|
||
#caption="@EA Mental Health Survey"
|
||
)
|
||
+theme(
|
||
legend.title = element_blank(),
|
||
#plot.subtitle = element_text(hjust = 0.5),
|
||
plot.title = element_text(hjust = 0.5),
|
||
#axis.text.y = element_blank(),
|
||
legend.position="bottom",
|
||
legend.box="vertical"
|
||
)
|
||
##+ scale_color_lancet()
|
||
)
|
||
saveplot("StateVariableX3")
|
||
## s1, s3, s4
|
||
sigmas <- list()
|
||
s4_array_plotting=1-s1_array_plotting-s3_array_plotting
|
||
sigmas$values <- c(s1_array_plotting, s3_array_plotting,s4_array_plotting)
|
||
sigmas$fraction <- c(rep("s1", length(s1_array_plotting)), rep("s3", length(s3_array_plotting)),rep("s4", length(s3_array_plotting)))
|
||
sigmas$times = rep(times,3)
|
||
sigmas <- as.data.frame(sigmas)
|
||
title_text = "Evolution of labor fractions"
|
||
(ggplot(data = sigmas, aes(x = times, y= values, color = fraction)) +
|
||
geom_line(size = 0.5)
|
||
+labs(
|
||
title=title_text,
|
||
#subtitle="n =303",
|
||
x="Year since start",
|
||
y="Fraction of total labor"
|
||
#caption="@EA Mental Health Survey"
|
||
)
|
||
+theme(
|
||
legend.title = element_blank(),
|
||
#plot.subtitle = element_text(hjust = 0.5),
|
||
plot.title = element_text(hjust = 0.5),
|
||
#axis.text.y = element_blank(),
|
||
legend.position="bottom",
|
||
legend.direction="vertical"
|
||
)
|
||
+ scale_color_lancet(
|
||
breaks=c("s1", "s3", "s4"),
|
||
labels=c("Direct work", "Movement building", "Money-making")
|
||
)
|
||
)
|