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Revised style and fixed filenames for Chapter 9 code.
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@johnmyleswhite
johnmyleswhite committed Feb 17, 2012
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209 changes: 136 additions & 73 deletions 09-MDS/chapter09.R
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Original file line number Diff line number Diff line change
Expand Up @@ -18,18 +18,20 @@
# All rights reserved.

# Load libraries
library(foreign)
library(ggplot2)
library('foreign')
library('ggplot2')

### Simulated analysis to review the technique

# Some sample code to understand matrix multiplication

# First code snippet.
set.seed(851982) # To make sure results are consistent
ex.matrix <- matrix(sample(c(-1,0,1), 24, replace=TRUE), nrow=4, ncol=6)
row.names(ex.matrix) <- c('A','B','C','D')
colnames(ex.matrix) <- c('P1','P2','P3','P4','P5','P6')
ex.matrix <- matrix(sample(c(-1, 0, 1), 24, replace = TRUE),
nrow = 4,
ncol = 6)
row.names(ex.matrix) <- c('A', 'B', 'C', 'D')
colnames(ex.matrix) <- c('P1', 'P2', 'P3', 'P4', 'P5', 'P6')

# Second code snippet
ex.matrix
Expand Down Expand Up @@ -65,7 +67,7 @@ ex.mult
#D 1 -1 -1 3

# Fifth code snippet
sqrt(sum((ex.mult[1,]-ex.mult[4,])^2))
sqrt(sum((ex.mult[1, ] - ex.mult[4, ]) ^ 2))
#[1] 2.236068

ex.dist <- dist(ex.mult)
Expand All @@ -79,14 +81,14 @@ ex.dist
# Sixth code snippet
# Visualize clusters
ex.mds <- cmdscale(ex.dist)
plot(ex.mds, type='n')
text(ex.mds, c('A','B','C','D'))
plot(ex.mds, type = 'n')
text(ex.mds, c('A', 'B', 'C', 'D'))

# Seventh code snippet
library(foreign)
library(ggplot2)
library('foreign')
library('ggplot2')

data.dir <- "data/roll_call/"
data.dir <- file.path("data", "roll_call")
data.files <- list.files(data.dir)

data.files
Expand All @@ -101,7 +103,10 @@ data.files
# Eighth code snippet
# Add all roll call vote data frames to a single list
rollcall.data <- lapply(data.files,
function(f) read.dta(paste(data.dir, f, sep=""), convert.factors=FALSE))
function(f)
{
read.dta(file.path(data.dir, f), convert.factors = FALSE)
})

# Ninth code snippet
dim(rollcall.data[[1]])
Expand Down Expand Up @@ -142,7 +147,7 @@ rollcall.dist <- lapply(rollcall.simple, function(m) dist(m %*% t(m)))

# Do the multidimensional scaling
rollcall.mds <- lapply(rollcall.dist,
function(d) as.data.frame((cmdscale(d, k=2)) * -1))
function(d) as.data.frame((cmdscale(d, k = 2)) * -1))

# Twelfth code snippet
# Add identification information about Senators back into MDS data frames
Expand All @@ -157,9 +162,10 @@ for(i in 1:length(rollcall.mds))
congress.names <- sapply(as.character(congress$name),
function(n) strsplit(n, "[, ]")[[1]][1])

rollcall.mds[[i]] <- transform(rollcall.mds[[i]], name=congress.names,
party=as.factor(congress$party),
congress=congresses[i])
rollcall.mds[[i]] <- transform(rollcall.mds[[i]],
name = congress.names,
party = as.factor(congress$party),
congress = congresses[i])
}

head(rollcall.mds[[1]])
Expand All @@ -176,67 +182,124 @@ head(rollcall.mds[[1]])
# Create a plot of just the 110th Congress
cong.110 <- rollcall.mds[[9]]

base.110 <- ggplot(cong.110, aes(x=x, y=y))+scale_size(to=c(2,2), legend=FALSE)+
scale_alpha(legend=FALSE)+theme_bw()+
opts(axis.ticks=theme_blank(), axis.text.x=theme_blank(), axis.text.y=theme_blank(),
title="Roll Call Vote MDS Clustering for 110th U.S. Senate",
panel.grid.major=theme_blank())+
xlab("")+ylab("")+scale_shape(name="Party", breaks=c("100","200","328"),
labels=c("Dem.", "Rep.", "Ind."), solid=FALSE)+
scale_color_manual(name="Party", values=c("100"="black","200"="dimgray",
"328"="grey"),
breaks=c("100","200","328"), labels=c("Dem.", "Rep.", "Ind."))

print(base.110+geom_point(aes(shape=party, alpha=0.75, size=2)))
print(base.110+geom_text(aes(color=party, alpha=0.75, label=cong.110$name, size=2)))
base.110 <- ggplot(cong.110, aes(x = x, y = y)) +
scale_size(to = c(2,2), legend = FALSE) +
scale_alpha(legend = FALSE) + theme_bw() +
opts(axis.ticks = theme_blank(),
axis.text.x = theme_blank(),
axis.text.y = theme_blank(),
title = "Roll Call Vote MDS Clustering for 110th U.S. Senate",
panel.grid.major = theme_blank()) +
xlab("") +
ylab("") +
scale_shape(name = "Party", breaks = c("100", "200", "328"),
labels = c("Dem.", "Rep.", "Ind."), solid = FALSE) +
scale_color_manual(name = "Party", values = c("100" = "black",
"200" = "dimgray",
"328"="grey"),
breaks = c("100", "200", "328"),
labels = c("Dem.", "Rep.", "Ind."))

print(base.110 + geom_point(aes(shape = party,
alpha = 0.75,
size = 2)))
print(base.110 + geom_text(aes(color = party,
alpha = 0.75,
label = cong.110$name,
size = 2)))

# Fourteenth code snippet
# Create a single visualization of MDS for all Congresses on a grid
all.mds <- do.call(rbind, rollcall.mds)
all.plot <- ggplot(all.mds, aes(x=x, y=y))+
geom_point(aes(shape=party, alpha=0.75, size=2))+
scale_size(to=c(2,2), legend=FALSE)+
scale_alpha(legend=FALSE)+theme_bw()+
opts(axis.ticks=theme_blank(), axis.text.x=theme_blank(),
axis.text.y=theme_blank(),
title="Roll Call Vote MDS Clustering for U.S. Senate
(101st - 111th Congress)",
panel.grid.major=theme_blank())+
xlab("")+ylab("")+
scale_shape(name="Party", breaks=c("100","200","328"),
labels=c("Dem.", "Rep.", "Ind."),
solid=FALSE)+facet_wrap(~ congress)
all.plot <- ggplot(all.mds, aes(x = x, y = y)) +
geom_point(aes(shape = party, alpha = 0.75, size = 2)) +
scale_size(to = c(2, 2), legend = FALSE) +
scale_alpha(legend = FALSE) +
theme_bw() +
opts(axis.ticks = theme_blank(),
axis.text.x = theme_blank(),
axis.text.y = theme_blank(),
title = "Roll Call Vote MDS Clustering for U.S. Senate (101st - 111th Congress)",
panel.grid.major = theme_blank()) +
xlab("") +
ylab("") +
scale_shape(name = "Party",
breaks = c("100", "200", "328"),
labels = c("Dem.", "Rep.", "Ind."),
solid = FALSE) +
facet_wrap(~ congress)

print(all.plot)

# This is the code omitted from the chapter. This is used to create shnazy plots of everything!
for(i in 1:length(rollcall.mds)) {
mds <- rollcall.mds[[i]]
congress <- congresses[i]
plot.title <- paste("Roll Call Vote MDS Clustering for ", congress, " U.S. Senate", sep="")

# Build bas plot
mds.plot <- ggplot(mds, aes(x = x, y = y)) + scale_size(to = c(2, 2), legend = FALSE) +
scale_alpha(legend = FALSE) + theme_bw() + opts(axis.ticks = theme_blank(),
axis.text.x = theme_blank(), axis.text.y = theme_blank(), title = plot.title,
panel.grid.major = theme_blank()) +
xlab("") + ylab("")

# Build up point and text plots separately
mds.point <- mds.plot + geom_point(aes(shape = party, alpha = 0.75, size = 2))
mds.text <- mds.plot + geom_text(aes(color = party, alpha = 0.75, label = mds$name, size = 2))

# Fix labels, shapes and colors
if(length(levels(mds$party)) > 2) {
mds.point <- mds.point+scale_shape(name="Party", breaks=c("100","200","328"),
labels=c("Dem.", "Rep.", "Ind."), solid=FALSE)
mds.text <- mds.text+scale_color_manual(name="Party", values=c("100"="black","200"="dimgray","328"="gray"),
breaks=c("100","200","328"), labels=c("Dem.", "Rep.", "Ind."))
}
else {
mds.point <- mds.point + scale_shape(name = "Party", breaks = c("100", "200"),
labels = c("Dem.", "Rep."), solid = FALSE)
mds.text <- mds.text + scale_color_manual(name = "Party", values = c("100" = "black", "200" = "dimgray"),
breaks = c("100", "200"), labels = c("Dem.", "Rep."))
}
ggsave(plot=mds.point, filename=paste("images/senate_plots/", congress, "_point.pdf", sep=""), width=8, height=5)
ggsave(plot=mds.text, filename=paste("images/senate_plots/", congress, "_names.pdf", sep=""), width=8, height=5)
for(i in 1:length(rollcall.mds))
{
mds <- rollcall.mds[[i]]
congress <- congresses[i]
plot.title <- paste("Roll Call Vote MDS Clustering for ",
congress,
" U.S. Senate",
sep = "")

# Build base plot
mds.plot <- ggplot(mds, aes(x = x, y = y)) +
scale_size(to = c(2, 2), legend = FALSE) +
scale_alpha(legend = FALSE) +
theme_bw() +
opts(axis.ticks = theme_blank(),
axis.text.x = theme_blank(),
axis.text.y = theme_blank(),
title = plot.title,
panel.grid.major = theme_blank()) +
xlab("") +
ylab("")

# Build up point and text plots separately
mds.point <- mds.plot + geom_point(aes(shape = party,
alpha = 0.75,
size = 2))
mds.text <- mds.plot + geom_text(aes(color = party,
alpha = 0.75,
label = mds$name,
size = 2))

# Fix labels, shapes and colors
if(length(levels(mds$party)) > 2)
{
mds.point <- mds.point + scale_shape(name = "Party",
breaks = c("100", "200", "328"),
labels = c("Dem.", "Rep.", "Ind."),
solid = FALSE)
mds.text <- mds.text + scale_color_manual(name = "Party",
values = c("100" = "black",
"200" = "dimgray",
"328" = "gray"),
breaks = c("100", "200", "328"),
labels = c("Dem.", "Rep.", "Ind."))
}
else
{
mds.point <- mds.point + scale_shape(name = "Party",
breaks = c("100", "200"),
labels = c("Dem.", "Rep."),
solid = FALSE)
mds.text <- mds.text + scale_color_manual(name = "Party",
values = c("100" = "black",
"200" = "dimgray"),
breaks = c("100", "200"),
labels = c("Dem.", "Rep."))
}

ggsave(plot = mds.point,
filename = file.path('images',
'senate_plots',
paste(congress, "_point.pdf", sep = "")),
width = 8,
height = 5)
ggsave(plot = mds.text,
filename = file.path('images',
'senate_plots',
paste(congress, "_names.pdf", sep = "")),
width = 8,
height = 5)
}

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