## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----setup--------------------------------------------------------------------
library(clidatajp)
library(magrittr)
library(dplyr)
library(tibble)
library(ggplot2)
library(stringi)

## ----station_links, eval = FALSE----------------------------------------------
#   # existing data
# data(station_links)
# station_links %>%
#   dplyr::mutate("station" := stringi::stri_unescape_unicode(station)) %>%
#   print() %>%
#   `$`("station") %>%
#   clean_station() %>%
#   dplyr::bind_cols(station_links["url"])
# 
#   # Download new data
#   # If you want links for all countries and all sations, remove head().
# url <- "https://www.data.jma.go.jp/gmd/cpd/monitor/nrmlist/"
# res <- gracefully_fail(url)
# if(!is.null(res)){
#   area_links <- download_area_links()
#   station_links <- NULL
#   area_links <- head(area_links)  # for test
#   for(i in seq_along(area_links)){
#       print(stringr::str_c("area: ", i, " / ", length(area_links)))
#       country_links <- download_links(area_links[i])
#       country_links <- head(country_links)  # for test
#       for(j in seq_along(country_links)){
#           print(stringr::str_c("    country: ", j, " / ", length(country_links)))
#           station_links <- c(station_links, download_links(country_links[j]))
#       }
#   }
#   station_links <- tibble::tibble(url = station_links)
#   station_links
# }

## ----climate_data, eval = FALSE-----------------------------------------------
#   # existing data
# data(climate_jp)
# climate_jp %>%
#   dplyr::mutate_if(is.character, stringi::stri_unescape_unicode)
# 
# data(climate_world)
# climate_world %>%
#   dplyr::mutate_if(is.character, stringi::stri_unescape_unicode)
# 
#   # Download new data
#   # If you want links for all countries and all sations, remove head().
# url <- "https://www.data.jma.go.jp/gmd/cpd/monitor/nrmlist/"
# res <- gracefully_fail(url)
# if(!is.null(res)){
#   station_links <-
#     station_links %>%
#     head() %>%
#     `$`("url")
#   climate <- list()
#   for(i in seq_along(station_links)){
#     print(stringr::str_c(i, " / ", length(station_links)))
#     climate[[i]] <- download_climate(station_links[i])
#   }
#   world_climate <- dplyr::bind_rows(climate)
#   world_climate
# }

## ----clean_data---------------------------------------------------------------
data(climate_world)
data(climate_jp)
climate <- 
  dplyr::bind_rows(climate_world, climate_jp) %>%
  dplyr::mutate_if(is.character, stringi::stri_unescape_unicode)  %>%
  dplyr::group_by(country, station) %>%
  dplyr::filter(sum(is.na(temperature), is.na(precipitation)) == 0) %>%
  dplyr::filter(period != "1991-2020" | is.na(period))

climate <- 
  climate %>%
  dplyr::summarise(temp = mean(as.numeric(temperature)), prec = sum(as.numeric(precipitation))) %>%
  dplyr::left_join(dplyr::distinct(dplyr::select(climate, station:altitude))) %>%
  dplyr::left_join(tibble::tibble(NS = c("S", "N"), ns = c(-1, 1))) %>%
  dplyr::left_join(tibble::tibble(WE = c("W", "E"), we = c(-1, 1))) %>%
  dplyr::group_by(station) %>%
  dplyr::mutate(lat = latitude * ns, lon = longitude * we)

## ----temperature--------------------------------------------------------------
climate %>%
  ggplot2::ggplot(aes(lon, lat, colour = temp)) +
    scale_colour_gradient2(low = "blue", mid = "gray", high = "red", midpoint = 15) + 
    geom_point() + 
    coord_fixed() + 
    theme_bw() + 
    theme(legend.key.size = unit(0.3, 'cm'))
    # ggsave("temperature.png")

## ----precipitation------------------------------------------------------------
climate %>%
  dplyr::filter(prec < 5000) %>%
  ggplot2::ggplot(aes(lon, lat, colour = prec)) +
    scale_colour_gradient2(low = "yellow", mid = "gray", high = "blue", midpoint = 1500) + 
    geom_point() + 
    coord_fixed() + 
    theme_bw() + 
    theme(legend.key.size = unit(0.3, 'cm'))
  # ggsave("precipitation.png")

## ----except_japan-------------------------------------------------------------
japan <- stringi::stri_unescape_unicode("\\u65e5\\u672c")
climate %>%
  dplyr::filter(country != japan) %>%
  ggplot2::ggplot(aes(temp, prec)) + 
  geom_point() + 
  theme_bw() + 
  theme(legend.position="none")
  # ggsave("climate_nojp.png")

## ----all_data-----------------------------------------------------------------
climate %>%
  ggplot2::ggplot(aes(temp, prec)) + 
    geom_point() + 
    theme_bw()
  # ggsave("climate_all.png")

## ----compare_japan------------------------------------------------------------
climate %>%
  dplyr::mutate(jp = (country == japan)) %>%
  ggplot2::ggplot(aes(temp, prec, colour = jp)) + 
    geom_point() + 
    theme_bw() +
    theme(legend.position="none")
  # ggsave("climate_compare_jp.png")

