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@grosscol
grosscol / target.sh
Last active Jul 31, 2019
Hacking at alternatives for symbolic link resolution that work across OSX, BSD, and GNU.
View target.sh
#!/bin/bash
# Consider the following structure where this script is target.sh
# /tmp/
# ├── target.sh
# └── l1
#    ├── one.sh -> ../target.sh
#    └── l2
# └── two.sh -> ../one.sh
# From your home directory run:
@grosscol
grosscol / performance_dimension.json
Last active Apr 22, 2019
Illustrating performance as a dimension or not.
View performance_dimension.json
{
"MAPT_data_points":[
{ "performer": "Alice",
"time": "2019-01-01",
"measure": "Documentation Rate",
"performance": "0.90"
},
{ "performer": "Alice",
"time": "2019-02-01",
"measure": "Documentation Rate",
View str_combinations.R
library(gtools)
demo_input <- c("fname midname lname","doe john e") #only 2 'names' in this example list.
split_list <- strsplit(demo_input, " |-")
make_combinations <- function(x){
# Use permutations from the gtools package
name_grid <- permutations(3,3,x)
apply(X=name_grid, MARGIN=1, FUN=paste0, collapse=' ')
@grosscol
grosscol / draw_shape.R
Created Jan 30, 2019
R homework help: monospace ascii art
View draw_shape.R
# DrawShape
#' @title Draw Shape
#' @param n height of shape in number of rows
#' @description If n is odd, draw a diamond pattern.
#' If n is even, draw an hourglass pattern.
#' @note e.g. n = 6
#' #####
#' ###
#' #
@grosscol
grosscol / munge_mapt_obs.r
Created Jul 30, 2018
Munge mapt obs from tape format to data table.
View munge_mapt_obs.r
library(readr)
library(dplyr)
library(tibble)
# Input CSV
input_path <- '/tmp/dahee_coding.csv'
input_df <- read_csv(input_path)
# Veena's observations are row 1
@grosscol
grosscol / bkgd_ave.R
Created Apr 24, 2018
Background mean per id from count data.
View bkgd_ave.R
library(tibble)
library(dplyr)
count_data <- tibble::tribble(
~id, ~numerator, ~denominator,
"Aly", 14, 20,
"Aly", 13, 20,
"Aly", 12, 20,
"Bob", 11, 20,
"Bob", 12, 20,
@grosscol
grosscol / dopar_options.r
Created Mar 23, 2018
Do parallel for A2MADS
View dopar_options.r
library(tidyverse)
library(broom)
library(doParallel)
# set variables to define data
n_samples <- 1000000
n_vars <- 10
n_group1 <- 500
n_group2 <- 2
@grosscol
grosscol / filter_ranges_in_df.r
Created Feb 5, 2018
Filter ranges of values where the ranger upper and lower bounds are stored in their own data frame.
View filter_ranges_in_df.r
filters_df <- data.frame(lower = c(0, 10, 20),
upper = c(2, 12, 22),
filter_name = paste('filter',c('A','B','C'), sep='_'))
df <- data.frame(x = 1:30)
named_range <- function( lower, upper, name, data) {
data > lower & data < upper
}
@grosscol
grosscol / impute_missing.R
Created Jan 23, 2018
Impute missing dates per id
View impute_missing.R
library(dplyr)
df <- structure(
list(
ID = structure(
c(
1L,
1L,
1L,
1L,
1L,
View perf-log.csv
1500055623049 59 PUT Perf Container 201 Created Fedora4 Create New Containers 1-1 text true 397 1 1 59
1500055623144 5 OPTIONS Perf Container 200 OK Fedora4 Create New Containers 1-1 true 373 1 1 5
1500055623186 16 GET Perf Container 200 OK Fedora4 Create New Containers 1-1 text true 2396 1 1 15
1500055623221 33 PATCH Perf Container 204 No Content Fedora4 Create New Containers 1-1 true 208 1 1 0
1500055623268 11 DELETE Perf Container 204 No Content Fedora4 Create New Containers 1-1 true 110 1 1 0
1500055640870 18 PUT Perf Container 201 Created Fedora4 Create New Containers 1-1 text true 397 1 1 18
1500055640901 4 OPTIONS Perf Container 200 OK Fedora4 Create New Containers 1-1 true 373 1 1 4
1500055640920 19 GET Perf Container 200 OK Fedora4 Create New Containers 1-1 text true 2396 1 1 19
1500055640951 23 PATCH Perf Container 204 No Content Fedora4 Create New Containers 1-1 true 208 1 1 0
1500055641005 17 DELETE Perf Container 204 No Content Fedora4 Create New Containers 1-1 true 110 1 1 0
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