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
# 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

#' 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

#!/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 Rscript
# Ben Fasoli

library(ncdf4)
library(raster)

files <- dir('raw', full.names = T)
data <- 0

for (file in files) {

benfasoli

#!/usr/bin/env Rscript

library(raster)

# Create gridded example data
xyz <- expand.grid(x = seq(-112.4, -111.6, by = 0.03),
                   y = seq(40.3, 40.9, by = 0.03))
xyz$z <- with(xyz, abs(x * y))
r_coarse <- rasterFromXYZ(xyz, crs = '+proj=longlat')
r_coarse

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

#!/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

#!/usr/bin/python
# GRIMM data collection script
# Ben Fasoli

import serial as ser                   # serial port use
import datetime                        # time stamps (UTC)
import re                              # regular expression matching

# Path to serial device ID
serialpath = '/dev/serial/by-id/usb-Prolific_Technology_Inc._USB-Serial_Controller_D-if00-port0'

benfasoli

#!/usr/bin/env Rscript
# Ben Fasoli
#
# Interpolation utilities for STILT footprints to predict footprints for
# finely gridded receptors using coarse STILT-calculated footprints for
# intermediate receptor locations.
#
# Uses weights derived from 2d Gaussian kernels to average footprints from
# the surrounding spatial area
#