benfasoli

#!/usr/bin/env Rscript

library(parallel)

fun <- function(x) {
  x^2
}

cl <- makeForkCluster(nnodes = 2, outfile = '')
out <- parSapply(cl, 1:2, fun)

benfasoli

#!/usr/bin/env python3
# Automated backup of lin-group CHPC resources
# Ben Fasoli
#
# Requires rclone to be installed
# Depends on access_token found in ~/.config/rclone/rclone.conf
# To create an access token, run
#   module load rclone
#   rclone config
#     Name: {anything short, e.g. gcloud}

benfasoli

#' Generates a KMZ file
#' @author Ben Fasoli
#'
#' \code{make_kmz} generates a KMZ representation of surface observations.
#'
#' @param data to be plotted on Z axis
#' @param time vector of times for data observations
#' @param lat latitude, in dd.dddd
#' @param lon longitude, in dd.dddd
#' @param filepath character path to output file, ending in '.kmz'

benfasoli

# Ben Fasoli
# Check that rslurm::slurm_apply accepts a list as a dataframe column

library(rslurm)

slurm_options <- list(
  time      = '300:00:00',
  account   = 'lin-kp',
  partition = 'lin-kp'
)

benfasoli

# Ben Fasoli
# Testing for met file identification
rm(list = ls())

# Source find_met_files()
# https://github.com/uataq/stilt/blob/master/r/src/find_met_files.r
source('https://raw.githubusercontent.com/uataq/stilt/master/r/src/find_met_files.r')

# Create pseudo-met files
system('touch ex_d01.arl ex_d02.arl ex_d03.arl')

benfasoli

# Ben Fasoli
# Wait for rslurm::slurm_apply to complete

library(rslurm)

fun <- function(x) {
  Sys.sleep(x)
  return(T)
}

benfasoli

#!/usr/bin/env python3

import numpy as np
import os
import pandas as pd

DATA_PATH = '/home/data/alta_udot/grimm_1109/'

BIN_SIZE_UPPER = np.array([0.25,
                           0.28,

benfasoli

<form action="https://formspree.io/info@wwtrek.com" method="POST">
  <input type="text" name="name" placeholder="Name">
  <input type="email" name="_replyto" placeholder="Email Address">
  <textarea name="message" placeholder="Message"></textarea>
  <input type="submit" value="Send">
</form>

benfasoli

library(ggmap)
library(tidyverse)

# Fetch SLC-centric grayscale Google Map terrain layer
basemap <- get_googlemap(center = c(lon = -112.0, lat = 40.6), zoom = 10,
                         scale = 2, maptype = 'terrain', color = 'bw')

# Display downloaded map
ggmap(basemap)

benfasoli

# Ben Fasoli

library(sp)
library(rgdal)

shape <- readOGR(dsn = 'data', layer = 'four_samples')

head(shape@polygons[[1]]@Polygons[[1]]@coords)
#           [,1]     [,2]
# [1,] -111.6227 40.75247