Thesis: ES1

.gitignore

@@ -0,0 +1,8 @@
+__pycache__/
+/results/
+/R/plots/
+/R/pdfs/
+/R/data/
+/R/scratch/
+/R/.RData
+/R/.Rhistory

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2022 Simon C Stanton
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

R/ch-4-graphs-NBS-summary_multi-model.Rmd

@@ -0,0 +1,130 @@
+---
+title: "ch 4 graphs"
+author: "Simon C Stanton"
+date: "2023-06-09"
+output: html_document
+
+params:
+ exp_id: 478692
+ sj_id: all # all
+ game: "" # All RGS
+ tournament_set: "Final Round"
+ model: "Multi-Model"
+ model_type: "_multi" # "_single"
+ #reward_upper_bound_game: 20000 # game-theoretic
+ #mc_upper_bound_game: 5000 # game-theoretic
+ #reward_upper_bound_game: 64000 # binary bandit
+ #mc_upper_bound_game: 16000 # binary bandit
+ #reward_upper_bound_game: 52000 # foundational RL, 1k
+ #mc_upper_bound_game: 13000 # foundational RL, 1k
+
+ #reward_upper_bound_rgs: 2880000 # game-theoretic
+ #mc_upper_bound_rgs: 720000 # game-theoretic
+ #reward_upper_bound_rgs: 9216000 # binary bandit
+ #mc_upper_bound_rgs: 2304000 # binary bandit
+ #reward_upper_bound_rgs: 7488000 # foundational RL, 1k
+ #mc_upper_bound_rgs: 1872000 # foundational RL, 1k
+ #reward_upper_bound_rgs: 74880000 # foundational RL, 10k
+ #mc_upper_bound_rgs: 18720000 # foundational RL, 10k
+ reward_upper_bound_rgs: 6336000 # Tourney 4, 1k
+ mc_upper_bound_rgs: 1584000 # Tourney 4, 1k
+
+---
+
+```{r setup, include=FALSE}
+knitr::opts_chunk$set(echo = TRUE)
+library(ggplot2)
+library(dplyr)
+library(ggrepel)
+library(ggpubr)
+library(stringr)
+
+
+cbPalette <- c("#999999", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
+```
+
+## R Markdown
+
+
+```{r, import-data, echo=FALSE, include=FALSE}
+
+path_to_data = "~/results/observations/tournament/"
+view_path = "/view/ep_o/view_"
+file_suffix_pre = "_sj_"
+#file_suffix_post = "_model_g111_trial_NBS_summary.csv" 
+file_suffix_post = "_models_trials_NBS_summary_total-RGS.csv" 
+
+filename = paste(path_to_data, params$exp_id, view_path, params$exp_id, file_suffix_pre, params$sj_id, file_suffix_post, sep="")
+filename
+df_data <- read.csv(file= filename, header=TRUE, check.names=FALSE)
+df_data$Agent <- as.factor(df_data$Agent)
+summary(df_data)
+
+
+```
+
+## Alter data and plot
+
+```{r plot, echo=FALSE}
+
+min_max_norm <- function(y, x) {
+ (x - min(x)) / (y - min(x))
+ }
+
+#df_data$Reward_scaled = min_max_norm(params$reward_upper_bound_rgs, df_data$Reward) 
+#df_data$MC_scaled = min_max_norm(params$mc_upper_bound_rgs, df_data$MC)
+
+df_data$Reward_scaled = df_data$Reward / params$reward_upper_bound_rgs
+df_data$MC_scaled = df_data$MC / params$mc_upper_bound_rgs
+
+
+z <- df_data$Agent
+z2 <- str_pad(z, width = max(str_width(z)+2), side="both")
+
+
+options(repr.plot.width = 8, repr.plot.height =6)
+
+ggplot(df_data, aes(x=MC_scaled, y=Reward_scaled)) + 
+ geom_point(color = "black", size = 1) +
+ expand_limits(x=c(0,1), y=c(0,1)) +
+ scale_y_continuous(breaks = seq(0, 1, by = .1)) +
+ scale_x_continuous(breaks = seq(0, 1, by = .1)) +
+ theme_bw() +
+ theme(panel.grid.major = element_line(color = "lightgrey", linewidth = 0.2, linetype = 1),
+ panel.grid.minor = element_line(color = "lightgrey", linewidth = 0.2, linetype = 3)) +
+ labs(x="Mutual Cooperation") +
+ labs(y="Reward") +
+ theme(
+ axis.title.x = element_text(margin = margin(t = 11), size=10, hjust=0.5),
+ axis.title.y = element_text(margin = margin(r = 11), size=10),
+ ) +
+ geom_label_repel(aes(label = z2),
+ force=500,
+ size = 2.5, # 3.5
+ label.padding = .28,
+ label.size = .2,
+ label.r = .25,
+ min.segment.length = unit(0, 'lines'),
+ segment.size=.18,
+ arrow = arrow(length = unit(0, "line"), type = "open"),
+ max.overlaps = Inf,
+ nudge_x=0.5, 
+ nudge_y=0.09,
+
+ ) +
+ stat_cor(method="pearson", label.x = .845, label.y = 0, size=3) +
+ labs(title = paste(params$model, "Tournament Summary"),
+ subtitle = paste(params$tournament_set, "Algorithm Performance")
+ ) +
+ theme(plot.title = element_text(hjust = 0.5, size = 12), # Center title position and size
+ plot.subtitle = element_text(hjust = 0.5, size=10), # Center subtitle
+ ) +
+ annotate("text", x = 0.12, y = 0, label = paste("Model: ", params$game, " Exp_ID: ", params$exp_id, " 1k", sep=""), cex=3) 
+
+ggsave(path=".", filename=paste(params$exp_id, params$model_type, "-model-reward-mc.png", sep=""), bg='white', width=8, height=6 ) 
+cor.test(df_data$MC_scaled, df_data$Reward_scaled)
+
+
+```
+
+Note that the `echo = FALSE` parameter was added to the code chunk to prevent printing of the R code that generated the plot.

R/ch-4-graphs-NBS-summary_single-model-Matches.Rmd

@@ -0,0 +1,136 @@
+---
+title: "ch 4 graphs"
+author: "Simon C Stanton"
+date: "2023-06-09"
+output: html_document
+
+params:
+ exp_id: 398741
+ sj_id: 0 # all
+ game: "g111" # All RGS
+ tournament_set: "Final Round"
+ model: "Single-Model"
+ model_type: "_single" # 
+ reward_upper_bound_game: 4000 # game-theoretic
+ mc_upper_bound_game: 1000 # game-theoretic
+ #reward_upper_bound_game: 64000 # binary bandit
+ #mc_upper_bound_game: 16000 # binary bandit
+ #reward_upper_bound_game: 52000 # foundational RL, 1k
+ #mc_upper_bound_game: 13000 # foundational RL, 1k
+ #reward_upper_bound_game: 520000 # foundational RL, 10k
+ #mc_upper_bound_game: 130000 # foundational RL, 10k
+ reward_upper_bound_rgs: 6336000 # Tourney 4, 1k
+ mc_upper_bound_rgs: 1584000 # Tourney 4, 1k
+
+---
+
+```{r setup, include=FALSE}
+knitr::opts_chunk$set(echo = TRUE)
+library(ggplot2)
+library(dplyr)
+library(ggrepel)
+library(ggpubr)
+library(stringr)
+
+
+cbPalette <- c("#999999", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
+```
+
+## R Markdown
+
+
+```{r, import-data, echo=FALSE, include=FALSE}
+
+path_to_data = "~/results/observations/tournament/"
+view_path = "/view/ep_o/view_"
+file_suffix_pre = "_sj_"
+file_suffix_post = "_model_g111_trial_NBS.csv" 
+
+
+filename = paste(path_to_data, params$exp_id, view_path, params$exp_id, file_suffix_pre, params$sj_id, file_suffix_post, sep="")
+filename
+df_data <- read.csv(file= filename, header=TRUE, check.names=FALSE)
+#df_data$Agent <- as.factor(df_data$Agent)
+summary(df_data)
+
+
+```
+
+## Alter data and plot
+
+```{r plot, echo=FALSE}
+
+
+
+
+df_data$A0_Reward_proportion = df_data$R0 / params$reward_upper_bound_game
+df_data$A1_Reward_proportion = df_data$R1 / params$reward_upper_bound_game
+df_data$MC_proportion = df_data$MC / params$mc_upper_bound_game
+
+z0 <- df_data$A0
+z1 <- df_data$A1
+df_data$z2 <- paste(z0, "&", z1) #str_pad(z, width = max(str_width(z)+2), side="both")
+df_data$z2
+
+df_data
+
+```
+
+
+
+
+```{r plot, echo=FALSE}
+options(repr.plot.width = 8, repr.plot.height =6)
+
+ggplot(df_data, aes(x=A0_Reward_proportion, y=A1_Reward_proportion, color=MC_proportion)) + 
+ geom_point(color = "black", shape=1, aes(size=MC_proportion)) +
+ expand_limits(x=c(0,1), y=c(0,1)) +
+ scale_y_continuous(breaks = seq(0, 1, by = .25)) +
+ scale_x_continuous(breaks = seq(0, 1, by = .25)) +
+ theme_bw() +
+ theme(panel.grid.major = element_line(color = "lightgrey", linewidth = 0.2, linetype = 1),
+ panel.grid.minor = element_line(color = "lightgrey", linewidth = 0.2, linetype = 3)) +
+ labs(x="Agent Zero TR") +
+ labs(y="Agent One TR") +
+ theme(
+ axis.title.x = element_text(margin = margin(t = 11), size=10, hjust=0.5),
+ axis.title.y = element_text(margin = margin(r = 11), size=10),
+ ) +
+ geom_label_repel(aes(label = z2),
+ size = 2.5, # 3.5
+ label.padding = .28,
+ label.size = .2,
+ label.r = .25,
+ min.segment.length = unit(0, 'lines'),
+ segment.size=.18,
+ arrow = arrow(length = unit(0, "line"), type = "open"),
+ max.overlaps = Inf,
+ nudge_x=-0.099, 
+ nudge_y=0.014,
+ force=10
+
+ 
+ ) +
+ labs(title = paste(params$model, "Tournament Summary"),
+ subtitle = paste(params$tournament_set, "Match Pairings"),
+ color="MC"
+ ) +
+ theme(plot.title = element_text(hjust = 0.5, size = 12), # Center title position and size
+ plot.subtitle = element_text(hjust = 0.5, size=10), # Center subtitle
+ ) +
+ guides(color = FALSE) +
+ guides(size=guide_legend(title="MC")) +
+ theme(legend.title.align=0.5) +
+ annotate("text", x = 0.12, y = 0, label = paste("Model: ", params$game, " Exp_ID: ", params$exp_id, " 1k", sep=""), cex=3) 
+#+
+ #scale_fill_discrete(name = "New Legend Title") #
+
+ggsave(path=".", filename=paste(params$exp_id, params$model_type, "-model", "_sj_", params$sj_id, "_", params$game, "_match-pairings.png", sep=""), bg='white', width=8, height=6 ) 
+
+
+```
+
+Note that the `echo = FALSE` parameter was added to the code chunk to prevent printing of the R code that generated the plot.
+
+
+