adamhsparks

# Download any data file from a private GitHub repo
# regardless of how large it is.
# Returns a string that will then need to be parsed
# by read_csv or the like to turn it into a data frame.

# Dependencies
require(tidyverse)
require(httr) 
require(rlist)
require(jsonlite)

adamhsparks

# Entering data
week <- c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
YLI <- c(3, 4, 5, 2, 6, 5, 4, 3, 5, 6, 2, 4)
YLS <- c(10, 11, 11, 12, 10, 11, 11, 10, 12, 13, 10, 11)
rainfall <- c(1, 10, 8, 6, 65, 30, 2, 10, 8, 6, 65, 30)

# Creating Data Frame
perf <- data.frame(week, YLI, YLS, rainfall)

# Plotting Charts and adding a secondary axis

adamhsparks

function audpc(evaluation, dates)
    n = length(evaluation) - 1
    disvec = Base.zeros(n)
    datevec = Base.zeros(n)
    out = 0.0

    for i in 1:n
        disvec[i] = (evaluation[i] + evaluation[i + 1]) / 2
        datevec[i] = dates[i + 1] - dates[i]
        out = sum(disvec .* datevec)

adamhsparks

dat <-
  dat %>%
  left_join(wind, by = c("field" = "FIELD")) %>%
  mutate(
    field = factor(field),
    trap_coord_deg = case_when(
      trap_coord == "N" ~ 0,
      trap_coord == "NbE" ~ 11.25,
      trap_coord == "NNE" ~ 22.5,
      trap_coord == "NEbN" ~ 33.75,

adamhsparks

##############################################################################
# title         : EPIRICE-sim-bs-lb.R;
# purpose       : Install the epicrop package and simulate rice brown spot and
#                 rice leaf blast epidemics;
# producer      : prepared by A. Sparks;
# last update   : in Perth, WA, Australia, Jun 2021;
# inputs        : na;
# outputs       : leaf blast and brown spot model outputs of unmanaged disase
#                 epidemics;
# remarks       : Prepared for Jean Fabrice Adanve;

adamhsparks

library("GSODR")
library("tidyr")
library("dplyr")
library("countrycode")

w <- get_GSOD(years = 1929:1931)

w <-
  w %>%
  group_by(CTRY, YEAR) %>%

adamhsparks

function leaf_wet(wth = wth, simple = TRUE)

    rh = diurnal_rh(
      doy = wth[, DOY],
      rh = wth[, RHUM],
      tmin = wth[, TMIN],
      tmax = wth[, TMAX],
      tmp = wth[, TEMP],
      lat = wth[, LAT]

adamhsparks

#' Get weather data from NASA POWER API
#'
#' @param lonlat A numeric vector of geographic coordinates for a cell or region
#'  entered as x, y coordinates.
#' @param dates A character vector of start and end dates in that order.
#'
#' @return A \code{\link[data.table]{data.table}} of weather data, dates and

adamhsparks

library("ggplot2")
library("ggthemes")
theme_set(theme_map())
library("sf")
library("rnaturalearth")
library("rnaturalearthdata")

world <- ne_countries(scale = "medium", returnclass = "sf")

ctry <- world[world$name == "Philippines", ]

adamhsparks

library(dplyr)
library(ggplot2)
library(lubridate)
library(cranlogs)
library(janitor)

dl <-
  cran_downloads(
    package = c(
      "bomrang",