mbjoseph

mbjoseph

# Script to evaluate small sample behavior of Weibull parameter MLEs --------
library(fitdistrplus)
library(dplyr)
library(tidyr)
library(gridExtra)
library(parallel)
library(ggplot2)
library(viridis)

mbjoseph

library(parallel)

# Create matrix to store result -------------------------------------------
M <- 4
N <- 6
A <- matrix(0, nrow = M, ncol = N)

list <- list(3, 4, 6)

# Serial version ----------------------------------------------------------

mbjoseph

mbjoseph

mbjoseph

library(rgdal)
library(rgeos)
library(raster)
library(gdalUtils)


# gdalinfo("GFED40_MQ_199506_BA.hdf")
# sds <- get_subdatasets("GFED40_MQ_199506_BA.hdf")
# sds

mbjoseph

library(RCurl)

# Fetching burn rasters ---------------------------------------------------
# get and read the file listing from the usgs server
prefix  <- 'https://rmgsc.cr.usgs.gov/outgoing/baecv/BAECV_CONUS_v1_2017/'
download.file(prefix, destfile = 'listing.txt')
out <- readLines('listing.txt')

# now create paths to each tar.gz file by processing the html

mbjoseph

# Importing data from USDA into large data file ---------------------------
library(stringr)
library(tidyverse)

convert_to_df <- function(file) {
  # takes a text file as input and parses the file to generate a data.frame
  lines <- readLines(file)

  # identify blank lines which denote separate files

mbjoseph

library(raster)
library(tidyverse)
library(lubridate)
library(mgcv)

# Boulder temperature prediction ------------------------------------------
# Goal: use historical temperature data to predict the weather a week from today

# Fetch raw data from NOAA
data_url <- "https://www.esrl.noaa.gov/psd/boulder/data/boulderdaily.complete"

mbjoseph

print("Hello, world!")