In raefuhrman/262_Final_Package: Various climate impacts on plant growth

knitr::opts_chunk$set(echo = TRUE)

Potential threshold for tree death with certain levels of fog, tmax, and precipitation. Insert parameters for the species and models whether it meets that requirement. IF tmax is over a certain threshold for a certain number of days, precip below threshold, fog below threshold. summary functions -- temp average, precip sum. etc.

##load packages and read data
library(tidyverse)
library(lubridate)
climate_data <- read_csv("Climate_Data_SB_2018.csv")

##parse date to use group by and summarize functions later
climate_data$DATE <- parse_date_time(x = climate_data$DATE,
                orders = c("d m y", "d B Y", "mdy"))
climate_data$DATE <- as.Date(climate_data$DATE, format = "%m/%d/%y")

##pick one station
select_station_data <- function(cl_data,  st = "USC00047902") {
  station_1 <- cl_data %>% 
    filter(STATION == st) %>% 
    select(STATION, PRCP, TMAX, TMIN, TOBS, DATE)
  return(station_1)
}
x <- select_station_data(cl_data = climate_data)


##average observed temperature by month
average_temp <- station_1 %>% 
  mutate(Month = format(station_1$DATE, "%m")) %>% 
  group_by(Month) %>% 
  summarize(Average_Monthly_Temp = mean(TOBS))

##total yearly precipitation 
yearly_precip <- as.data.frame(sum(station_1$PRCP))
colnames(yearly_precip) <- "Total Rain (2018) at Station 1"




#, year = format(station_1$DATE, "%Y")
##test with group by year since there is only one year

###take this long vector and put it in a matrix with x columns and y rows to create a 2-d array, a 3-d array observations per year, plus another vector for the next station. take this long thing and fold it. 
  #with matrix or array everything in the vector must be the same type of data and is representing the same data i.e. this is a vector of temps over a certain period of time so the. i.e. months, years, stations - all temp
  #dataframe with month, year, station, and temp 


##will set up testing framework
##usethis::use_test() 

source("Average_Monthly_Temperature.R")
x <- Average_Monthly_Temperature(climate_data)
x

raefuhrman/262_Final_Package documentation built on June 15, 2019, 2:44 p.m.