dholstius

eval({
  ensure_nonnull <- ensures_that(!is.null(.) ~ "Must not be NULL" )
  ensure_nonempty <- ensures_that(length(.) > 0 ~ "Must not be empty", +ensure_nonnull )
  ensure_finite <- ensures_that(all(is.finite(.)) ~ "Must be finite", +ensure_nonempty )
  ensure_positive <- ensures_that(all(. > 0) ~ "Must be positive", +ensure_finite )
  ensure_nonnegative <- ensures_that(all(. >= 0) ~ "Must be positive or zero", +ensure_finite )
  ensure_unique <- ensures_that(length(unique(.)) == 1)
})

# Wrapped in `eval({...})` b/c otherwise RStudio will complain about syntax

dholstius

#' Filter (subset) a Spatial*DataFrame object
#'
#' @param object a \code{Spatial*DataFrame}
#' @param ... see \link{subset}
#' @param .dots
#'
#' @importFrom lazyeval all_dots lazy_eval
#'
#' @return a subset of the original \code{Spatial*DataFrame}
#'

dholstius

# via https://support.rstudio.com/hc/en-us/articles/200552326-Running-RStudio-Server-with-a-Proxy

user nginx;
worker_processes 4;
# daemon off;
pid /run/nginx.pid;

events {
        worker_connections 768;
        # multi_accept on;

dholstius

#
#/**
# * Copyright 2007 The Apache Software Foundation
# *
# * Licensed to the Apache Software Foundation (ASF) under one
# * or more contributor license agreements.  See the NOTICE file
# * distributed with this work for additional information
# * regarding copyright ownership.  The ASF licenses this file
# * to you under the Apache License, Version 2.0 (the
# * "License"); you may not use this file except in compliance

dholstius

<?xml version="1.0"?>
<?xml-stylesheet type="text/xsl" href="configuration.xsl"?>

<!-- Put site-specific property overrides in this file. -->

<configuration>
  <property>
    <name>fs.default.name</name>
    <value>hdfs://localhost:9000</value>
  </property>

dholstius

#' (Left) join with a custom comparator
#'
#' @param left  data.frame
#' @param right data.frame
#' @param by    names of columns to join by
#' @param fun   custom comparator (see examples)
#'
#' @examples
#' my_df <- data.frame(cyl = c(4, 4, 6, 8), vs = c(0, 1, NA, NA), foo = c("A", "B", "C", "D"))
#' my_fun <- function (e1, e2) (e1 == e2) | is.na(e2)

dholstius

#' format_signif
#'
#' Format numbers with a given number of significant digits
#'
#' @param	x		numeric vector
#' @param	digits	number of significant digits
#' @return	character vector
#' @examples
#' x <- c(0.800, 1704.1, 43.5e6, 10, NaN, NA, Inf, 0.00)
#' format_signif(x, digits=3)

dholstius

require(ggplot2)
require(scales)

seq_range <- function(x, by) seq(min(x), max(x), by=by)

time_breaks <- function(width) {
  function(limits) seq_range(limits, by=width)
}

scale_x_hours <- function(

dholstius

#' fast_POSIXct
#'
#' Quickly convert local timestamps to a POSIXct vector
#'
#' @param   x   timestamps (YYYY-mm-dd HH:MM:SS)
#' @param   tz  local timezone
#' @return      POSIXct vector
#' @export
fast_POSIXct <- function(x, tz) {
    stopifnot(is.character(x))

dholstius

#' aggregate.data.table
#' 
#' Use to quickly aggregate rows from a data.frame
#'
#' @param   x           data.table
#' @param   by          list of columns to use for grouping
#' @param   FUN         summary function
#' @param   \dots       further arguments to summary function
#' @param   is.value    determines which of the remaining columns should be aggregated (numeric, POSIXct, character, etc.)
#' @author              David Holstius \email{david.holstius@berkeley.edu}