jtleek

---
title: "How does your BMI measure up?"
output: flexdashboard::flex_dashboard
runtime: shiny
---

Inputs {.sidebar}
-------------------------------------

```{r}

jtleek

# Make the canvas
plot(1:10,1:10,xlim=c(-5,5),ylim=c(0,10),type="n",xlab="",ylab="",xaxt="n",yaxt="n")
# Make the branches
rect(-1,0,1,2,col="tan3",border="tan4",lwd=3)
polygon(c(-5,0,5),c(2,4,2),col="palegreen3",border="palegreen4",lwd=3)
polygon(c(-4,0,4),c(3.5,5.5,3.5),col="palegreen4",border="palegreen3",lwd=3)
polygon(c(-3,0,3),c(5,6.5,5),col="palegreen3",border="palegreen4",lwd=3)
polygon(c(-2,0,2),c(6.25,7.5,6.25),col="palegreen4",border="palegreen3",lwd=3)

jtleek

pvaluesPain = c(0.02, 0.06, 0.75, 0.38, 0.3, 0.07, 0.22, 0.27)
adjustedPvaluesPain = p.adjust(pvaluesPain,method="bonferroni")
adjustedPvaluesPain
sum(adjustedPvaluesPain < 0.05)

pvaluesNoPain = c(0.82, 0.98, 0.65, 0.39, 0.88, 0.95, 0.29, 0.64, 0.81)
adjustedPvaluesNoPain = p.adjust(pvaluesNoPain,method="bonferroni")
adjustedPvaluesNoPain
sum(adjustedPvaluesNoPain < 0.05)

jtleek

## Load libraries
library(XML)
library(dplyr)
library(RCurl)

## Get the results for a specific term
scrape_term = function(search_term,npages){
  base_url = "http://scholar.google.com/scholar?"
  search_string = paste0("q=",paste0(strsplit(search_term," ")[[1]],collapse="+"))
  dat = data.frame(NA,nrow=10*npages,ncol=3)

jtleek

library(hextri)
library(tidyr)

noco = readRDS("/cloud/project/postpi/noco.rds")
truth = readRDS("/cloud/project/postpi/truth.rds")
par = readRDS("/cloud/project/postpi/par_postpi.rds")
nonpar = readRDS("/cloud/project/postpi/nonpar_postpi.rds")


nbins = 20

jtleek

### Let's simulate some data very simply

## Load libraries
library(ggplot2)
library(dplyr)
library(gam)
library(patchwork)

# Set parameters
n_sample = 100

jtleek

---
title: "Tabset Column"
runtime: shiny
output: flexdashboard::flex_dashboard
---
    


```{r setup, include=FALSE}
library(flexdashboard)

jtleek

#library(ggnet)
#library(RkittleBrewer)
#library(network)

plot_net = function(nodes_per_layer, 
                   layer_shape,
                   connection_type, 
                   stride_length,
                   layer_color,
                   node_values,

jtleek

plot_net = function(nodes_per_layer, layer_shape, connection_type, stride_length){
  total_nodes = sum(nodes_per_layer)
  adjacency = matrix(0,nrow=total_nodes,ncol=total_nodes)
  
  for(i in seq_along(connection_type)){
    
    source_nodes = 1:nodes_per_layer[i] + (i-1 > 0)*sum(nodes_per_layer[1:(i-1)])
    sink_nodes = 1:nodes_per_layer[(i+1)] + (i > 0)*sum(nodes_per_layer[1:i])
      
    nsource = length(source_nodes)

jtleek

library(png)
library(ggforce)
library(animation)
library(tweenr)

jhu_png = readPNG("jhudsl.png")
x = rep(1:510,each=555)
y = rep(1:555,510)
val = jhu_png[,,3]
val = round(val)