term_project.Rmd

---
title: "MA703 Term Project"
author: "Tom Morin"
date: "11/20/2019"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(igraph)
library(tidyr)
library(ggplot2)
library(RColorBrewer)
library(data.table)

YEO7_COLORS <- c("Vis"="#781180", "SomMot"="#4680B3", "DorsAttn"="#007607", 
                 "SalVentAttn"="#C43AFB", "Limbic"="#DCF8A3", "Cont"="#E69421",
                 "Default"="#CD3E48", "WholeBrain"="FFFFFF")
YEO7_NAMES <- c("Vis", "SomMot", "DorsAttn", "SalVentAttn",
                "Limbic", "Cont", "Default")
names(YEO7_COLORS) <- YEO7_NAMES
YEO7_SCALE <- scale_color_manual(name="Community", values=YEO7_COLORS)
```

```{r, include=FALSE}
# Read in data
fpath <- "/Volumes/CogNeuroimaging/Tom/Classes/3_Year/1_Semester/MA703_SAND_Kolaczyk/Project/"
all.ts <- read.csv(paste(fpath, "data/s04_run-1_Schaefer400ts.txt", sep=""))
comms <- read.csv(paste(fpath, "data/s04_Schaefer400_communities.txt", sep=""))

corr.ts <- cor(all.ts)
sorted_corrs <- sort(c(corr.ts))
top_ten_pct_thrsh <- sorted_corrs[0.9*length(sorted_corrs)]
```

```{r, include=FALSE}
THRSH <- 0.5
corr.ts.thrsh <- corr.ts * (corr.ts > THRSH)
bin.corr.ts <- 1 * (corr.ts > THRSH)
corr.ts.top_ten_pct <- corr.ts * (corr.ts > top_ten_pct_thrsh)
mx_to_plot <- corr.ts.thrsh
igraph.options(vertex.size = 7, vertex.label=NA)


```