WillForan

#' bighead - show subset in each dimension
#' @description like head but in all dimensions
#' @param obj - indexable object: vector, data.frame, matrix, or array
#' @param ntotal - total maximum elements to show
bighead <- function(obj, ntotal=100){
  # dimension of object (dataframe = 2D)
  dims <- dim(obj)
  # vectors has NULL dim. Special case: set dim to length
  if(is.null(dims)) dims <- c(length(obj))
  ndim <- length(dims)

WillForan

global $conf;
$my_pages   = file($conf['indexdir'] . '/page.idx');

# don't care about titles -- but might in the future
#$my_titles  = file($conf['indexdir'] . '/title.idx');
#  $title = trim($my_titles[$id]);
#  $title = empty($title)?($key."**"):$title;

$my_dates_html = array();
foreach($my_pages as $id => $page) {

WillForan

# get needed libraries
install.packages(c('remotes','readxl', 'ggplot2'))
remotes::install_github('LabNeuroCogDevel/LNCDR')
library(LNCDR)

# read in data
# expects a row per visit with a column for id shared across visit and age at visit
# TODO: replace my_data.xlsx with actual excel document path/name
mydata <- readxl::read_xlsx("my_data.xlsx")

WillForan

library(ggplot)
library(gamm4)
library(dplyr)
library(checkmate) # for expect_subset dataframe names test

met_res_for_roi <- function(MRSI_input, this_roi, met_name, minage=18, maxage=25) {
  # have columns we need
  expect_subset(c("roi", "age", "dateNumeric", met_name), names(MRSI_input))
  
  roi_met <- MRSI_input %>% 

WillForan

teapot: teapot.cc
	 g++ -o teapot teapot.cc -lGL -lGLU -lglut

WillForan

library(ggplot2)
library(dplyr)
library(cowplot)
theme_set(theme_cowplot())
load("ds2_long.rdata")

# Smith is different than the other two
combine_ds2_long %>% split(.$study) %>% lapply(function(x) summary(x$value)) %>% bind_rows
# Min.      `1st Qu.`  Median    Mean         `3rd Qu.` Max.     `NA's` 
# <table>   <table>    <table>   <table>      <table>   <table>  <table>

WillForan

colors={'255, 255, 0': 'Yellow', '0, 255, 0': 'Green', '255, 0, 255': 'Magenta', '255, 0, 0': 'Red', '0, 255, 255': 'Cyan', '0, 0, 255': 'Blue' }; 
cnt={};
a=[... document.querySelectorAll('div[style~="background-color:"]')].map(x=>colors[x.getAttribute('style').replace(/.*background-color: rgb\((.*?)\); color.*/,'$1')]).forEach(function(x) {cnt[x] = cnt[x]===undefined?1:cnt[x]+1});
Object.keys(cnt).forEach(k=>$('font[title="'+k+'"]').children[2].innerHTML+= ", " + cnt[k] + "terr.")

WillForan

library(ggplot2)
library(dplyr)
library(tidyr)
theme_set(cowplot::theme_cowplot())
eog <- read.csv('eog_cal/eeg_data_20200921.csv')

subjData <- 
    eog %>%
    unite(ld8, LunaID, ScanDate) %>% # remove LunaID and scanDate columns. replace with ld8
    mutate_at(vars(matches('Error')), abs) %>%  # abs  delta columns

WillForan

import os


def create_key(template, outtype=('nii.gz',), annotation_classes=None):
    if template is None or not template:
        raise ValueError('Template must be a valid format string')
    return template, outtype, annotation_classes


def infotodict(seqinfo):

WillForan

#!/usr/bin/env bash
#
# 20200414WF - init
#    get all neuro study subjects by cursor
#


CURSORS=(
  "eyJvZmZzZXQiOjI1fQ==" \
  "eyJvZmZzZXQiOjEwMH0=" \