index.Rmd

---
title: "Supplementary Materials"
---


```{r setup, echo=F, include=FALSE, results = FALSE, message=FALSE, error=FALSE, results = "hide"}
library(tsna)
library(ndtv) # also loads animation and networkDynamic
library(igraph)
library(dplyr)

# load dyadic data
load("/Users/simon/Documents/repo/animation-website_1/dyadicdat.RData")

# date from numeric
dyadicdat$date <- as.Date(dyadicdat$time, origin = "1970-01-01")

# restructure data 
dyadicdat <- dyadicdat %>% arrange(date)
dyadicdat$canton1 <- as.factor(dyadicdat$canton1)
dyadicdat$canton2 <- as.factor(dyadicdat$canton2)
dyadicdat$ID_SM <- as.factor(dyadicdat$ID_SM)

library(forcats) # understand why changing levels changes values of factors, too stupid to understand just now
dyadicdat$canton1 <- fct_expand(dyadicdat$canton1, levels = sort(unique(c(as.character(dyadicdat$canton1), as.character(dyadicdat$canton2)))))
dyadicdat$canton2 <- fct_expand(dyadicdat$canton2, levels = sort(unique(c(as.character(dyadicdat$canton1), as.character(dyadicdat$canton2)))))

# subset to bilaterals
dyadicdat <- dyadicdat %>% filter(bilateral == 1)

# quickly look no of mechansims per agreement
rowSums(cbind(dyadicdat$commission, dyadicdat$monitoring, dyadicdat$conflict))
  
# function to transform from dyadic data to network panels for each time stamp
from_dyadic_to_net <- function(dyadicdat){
  lst <- list()
  for (i in as.character(unique(dyadicdat$date))){
  temp_mat1 <- as.matrix(table(dyadicdat$canton1[dyadicdat$date <= i], dyadicdat$ID_SM[dyadicdat$date <= i]))
  temp_mat2 <- as.matrix(table(dyadicdat$canton2[dyadicdat$date <= i], dyadicdat$ID_SM[dyadicdat$date <= i]))
  temp_mat1 <- temp_mat1[sort(rownames(temp_mat1)), sort(colnames(temp_mat1))]
  temp_mat2 <- temp_mat2[sort(rownames(temp_mat2)), sort(colnames(temp_mat2))]
  temp_mat <- temp_mat1 + temp_mat2
  lst[[i]] <- temp_mat %*% t(temp_mat)
  diag(lst[[i]]) <- 0
  lst[[i]] <- as.network(lst[[i]], 
                        vertex.attrnames = rownames(lst[[i]]),
                        directed = F,
                        ignore.eval = F,
                        names.eval = 'weight')
  }
  return(lst)
}

lst <- from_dyadic_to_net(dyadicdat)

# create separate datasets for each mechanism and for those agreements without mechanism
com_list <- from_dyadic_to_net(dyadicdat[dyadicdat$commission == 1,])
mon_list <- from_dyadic_to_net(dyadicdat[dyadicdat$monitoring == 1,])
con_list <- from_dyadic_to_net(dyadicdat[dyadicdat$conflict == 1,])
no_mech_list <- from_dyadic_to_net(dyadicdat[dyadicdat$commission == 0 & dyadicdat$monitoring == 0 & dyadicdat$conflict == 0,])

```

## Plot Animation
```{r, include = FALSE}
dyn <- networkDynamic(network.list = lst,  
                      vertex.TEA.names = TRUE,
                      create.TEAs = TRUE, 
                      edge.TEA.names = c('weight','type'))
```

```{r pressure, echo = FALSE, tidy = FALSE, message = FALSE, error = FALSE, results=-1}
render.d3movie(dyn, 
               displaylabels = TRUE,
               edge.lwd = 'weight',
               output.mode = 'htmlWidget')

timeline(dyn)

proximity.timeline(dyn, 
                   default.dist = 6,
                   mode = 'sammon',
                   labels.at = 17,
                   vertex.cex = 4)

```