---
title: "KGC Data Resolution Example"
author: "Nicholas R. Wheeler, Chelsey Bryant, Franz Rubel, Roger H. French"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{2 - KGC Data Resolution}
  %\VignetteEngine{knitr::rmarkdown}
  %\usepackage[utf8]{inputenc}
---

Two differing resolutions of climate zone data have been included in this package.

These can be accessed with the parameter `res` in the `RoundCoordinates()` and `LookupCZ()` functions.

## Resolution Details

  * Course Resolution
  
    - Distance between data points, both latitude and longitude, is 0.5 degrees.
  
    - Latitude and longitude values are rounded to the nearest value ending in either 0.25 and 0.75.
  
  * Fine Resolution
  
    - Distance between data points, in both latitude and longitude, is 100 seconds.
  
    - Data originates from a 12960 x 6480 pixel image, and coordinates are rounded to the center coordinates of the nearest pixel.
    
## Example

  - An selection of example cities worldwide, and their reported climate zones from Wikipedia, have been included in this package in the dataframe `kgcities`.

  - Estimated climate zones for each city from both course and fine resolution datasets are queried, and results are shown in tabular format.

```{r, message=FALSE, warning=FALSE}
library("kgc")
print(head(kgcities))

  # Query Course Resolution
  data <- data.frame(kgcities, rndCoord.lon = RoundCoordinates(kgcities$lon), rndCoord.lat = RoundCoordinates(kgcities$lat))
  data <- data.frame(data,CZ.c=LookupCZ(data))
  colnames(data)[which(colnames(data)=='rndCoord.lon')] <- 'rndCoord.lon.course'
  colnames(data)[which(colnames(data)=='rndCoord.lat')] <- 'rndCoord.lat.course'

  # Query Fine Resolution
  data <- data.frame(data, rndCoord.lon = RoundCoordinates(kgcities$lon,res='fine',latlong='lon'), rndCoord.lat = RoundCoordinates(kgcities$lat,res='fine',latlong='lat'))
  data <- data.frame(data,CZ.f=LookupCZ(data,res='fine'))

  # Print Results
  print(data[,c(1,3,8,11)])

```