tyleransom

sysuse auto, clear
logit foreign i.rep78 c.price c.mpg
predict base if e(sample), pr
preserve
	clonevar oldrep78 = rep78
	replace rep78 = 4
	predict new if e(sample), pr
	generat mfx = new-base
	replace rep78 = oldrep78
	tab rep78 , sum(mfx)

tyleransom

using JuMP
using Ipopt

function datagen(N::Int64,T::Int64)
    ## Generate data for a linear model to test optimization
    srand(1234)
    
    # N = convert(Int64,N) #inputs to functions such as -ones- need to be integers!
    # T = convert(Int64,T) #inputs to functions such as -ones- need to be integers!
    n = N*T

tyleransom

#!/bin/bash

# GNU Fortran (gfortran) compiler, OpenBLAS BLAS and LAPACK libraries
gfortran -Wall -ffree-form -ffree-line-length-256 -o ~/ado/plus/r/rcr rcrlib_gnu.f90 rcrutil_gnu.f90 rcr.f90 -L/~/lib/OpenBLAS -lopenblas

rm *.mod

tyleransom

pbp_2016 <- read_csv("~/Downloads/pbp_2016.csv")
a <- pbp_2016 %>% group_by(GameID, posteam) %>% summarize(top = sum(PlayTimeDiff), end_score = max(PosTeamScore, na.rm=TRUE), numplays = n()) %>% filter(posteam != "NA") %>% group_by(GameID) %>% mutate(teamNum = row_number()) %>% select(GameID, top, numplays, teamNum, end_score)

score <- a %>% select(GameID, teamNum, end_score) %>% spread(teamNum, end_score, sep="_")
numplays <- a %>% select(GameID, teamNum, numplays) %>% spread(teamNum, numplays, sep="_")
top <- a %>% select(GameID, teamNum, top) %>% spread(teamNum, top, sep="_")
colnames(top) <- c("GameID", "top_1", "top_2")
colnames(score) <- c("GameID", "score_1", "score_2")
colnames(numplays) <- c("GameID", "numplays_1", "numplays_2")
final <- inner_join(numplays,score, by="GameID") %>% inner_join(top, by="GameID")  %>% mutate(winner_1 = as.integer(score_1 > score_2))

tyleransom

NOTE: Specific examples given for options, flags, commands variations, etc., are not comprehensive.

NORMAL MODE

Vim has 2 main "modes", that chance the behavior of all your keys. The default mode of Vim is Normal Mode and is mostly used for moving the cursor and navigating the current file.

Some important (or longer) commands begin with ":" and you will see the text you enter next at the bottom left of the screen.

:q[uit] - quit (the current window of) Vim. ("Window" here is internal to Vim, not if you have multiple OS-level windows of Vim open at once.)
:q! - force quit (if the current buffer has been changed since the last save)
:e[dit] {filename} - read file {filename} into a new buffer.

tyleransom

Crosswalk between Notepad++ and Vim utilities

Action	Notepad++ shortcut	Vim shortcut
Duplicate line	Ctrl+D	yyp
Cut line	Ctrl+L	dd
Move line up/down	Ctrl+Shift+<up/down>	dd<k/j>p
Compare files	File compare plugin wizard	:vsplit <filename> or vimdiff file1 file2 (from command line)
Select all (from here to top/bottom of file)	Ctrl+Shift+<home/end>	v<gg/G>
Select all (from here up/down one page)	Ctrl+Shift+	v Ctrl+

tyleransom

echo "Downloading gcc source files..."
curl https://ftp.gnu.org/gnu/gcc/gcc-5.4.0/gcc-5.4.0.tar.bz2 -O

echo "extracting files..."
tar xvfj gcc-5.4.0.tar.bz2

echo "Installing dependencies..."
yum install gmp-devel mpfr-devel libmpc-devel

echo "Configure and install..."

tyleransom

Rosetta Stone

This consists of a "Rosetta Stone" of code syntax between R, Python, and Julia. The aim is to help those who are proficient in one language easily translate their code/understanding to another.

Basic actions (REPL, package ecosystem, etc.)

Action	R code	Python code	Julia code
execute script from REPL	source('script.R')	execfile('script.py')	include("script.jl")
install a package	install.packages("pkg")	[from OS terminal]: pip install pkg	Pkg.add("pkg")
load a package	library(pkg) or require(pkg)	import pkg	using pkg

tyleransom

using Optim, NLSolversBase

function datagen(n=5500,k=13)
    b = rand(k)
    l = rand(2)
    x = randn(n,k)
    abil = randn(n,1)
    vabil = randn(n,1)
    sector = 1.0.*(rand(n,1).>0.8)
    weight = rand(n,1)

tyleransom

using BenchmarkTools
using Optim, NLSolversBase

function datagen(n=5500,k=13)
    b = rand(k)
    l = rand(2)
    x = randn(n,k)
    abil = randn(n,1)
    vabil = randn(n,1)
    sector = 1.0.*(rand(n,1).>0.8)