WillForan

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\(C = \alpha + \beta Y^{\gamma} + \epsilon\)

\$`x/x={(1,if x!=0),(text{undefined},if x=0):}`\$

WillForan

#!/usr/bin/env bash

# download and modify spacemacs
# s.t. we do not have to overwrite our current emacs configuration
# ideally:
# 0. export PATH="$PATH:$HOME/bin"
# 1. put this script in $HOME/bin/spacemacs
# 2. use "spacemacs" to run spacemacs

cfgd=$HOME/.spacemacs.d/

WillForan

library(ggplot2)
library(dplyr)
library(tidyr)

##DATA
WM <- structure(list(ID = structure(1:32, .Label = c("10843_20151015", 
"11228_20150309", "11339_20141104", "11340_20141031", "11341_20141118", 
"11348_20141119", "11349_20141124", "11351_20141202", "11352_20141230", 
"11354_20141205", "11355_20141230", "11356_20150105", "11357_20150122", 
"11358_20150129", "11359_20150203", "11360_20150129", "11363_20150310", 

WillForan

labelHeat <- function(rsvars,dsivars,Title,tifname) {
 # rsvars="Ramyg_cm2_16"
  #dsivars="Ramyg_cm2_16_final_qa0"
  
#location of completed analyses
rootpath <- "/Users/mariaj/Dropbox/Pitt/Luna/amyg_con/01_data/Z_scores_4_Fig3"
#where I want to put my images
imgpath <- "/Users/mariaj/Dropbox/Pitt/Luna/amyg_con/01_data/Z_scores_4_Fig3"

#make plot in variable that show the age effects identified in spline analyses

WillForan

library(dplyr)     

#options(stringsAsFactors = F)                                                                                                                                                 
#z1=read.delim(file='/Users/jalbrzikowskime/gordon_ci.txt',header=F)                                                                                                          
#z2=read.delim(file='/Users/jalbrzikowskime/infomap_luna_denoise_t9.txt',header=F) 

# fake data
d<-data.frame(                                                                                                                                                                
 id=c(1,2,3,4,5,6,7,8,9,10),                                                                                                                                                  
 z1=c(1,1,1,3,3,3,3,2,2,1),                                                                                                                                                   

WillForan

#!/usr/bin/env bash

# where to transfer folders
locOnGinger=/path/to/new/Siegle/

# make sure we can save logs
[ ! -d rsynclog] && mkdir rsynclog

# get dirs to tx from google doc, only grab those less than 300Gb
curl 'https://docs.google.com/spreadsheets/d/1wfXnWH7zI6H79u6o3fYV59iPBhG-JyaGhys7O9zmDCE/pub?output=tsv'|

WillForan

#!/usr/bin/env R
library(curl)
library(dplyr)
library(tidyr)
library(ggplot2)
library(cowplot)
library(gridExtra)
# get data
url <- 'https://docs.google.com/spreadsheets/d/e/2PACX-1vR0TLhKqeEWZsJqbIuZ38bLc3vVeUpPx9rYnS1QG9kp4Wgv9rvCRHplf1fDy4rFbmC1CAQoVLVW3NX7/pub?output=tsv'
req <- curl_fetch_memory(url)

WillForan

#!/usr/bin/env python
# -*- coding: utf-8 -*-

# ######
# sample short code -- test features
# USAGE:
#   pipenv run pylivetrader run -f AlpacaShortTest.py --backend-config config.yaml
# ######

import pylivetrader.backend.alpaca

WillForan

[2019-03-19 18:27:45.593426] INFO: Algorithm: livetrader start running with backend = alpaca data-frequency = minute
have Portfolio({
 'capital_used': 0.0, 
 'starting_cash': 0.0,
 'portfolio_value': 22924.4,
 'pnl': 0.0,
 'returns': 0.0,
 'cash': 87439.91,
 'positions': {
   Asset(03fb07bb-5db1-4077-8dea-5d711b272625, symbol=AMD, asset_name=AMD, exchange=NASDAQ): Position({

WillForan

# dumpy data
MRSfake <-
   data.frame(age=c(10,20,30),
              roi=c('a','b','c'),
              m1=c(1,2,3),
              m2=c(4,5,NA))

# initial
MRS_age_effect <- function(region, metabolite) {
  temp <- filter(MRS, roi == region)