Coordinate_Function.Rmd

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(png)
require(magick)
require(ggplot2)
require(ggimage) 
require(ggrepel)
library(ggpubr)

```


```{r}
source("read_wapData.R")
```

```{r}

test_hill              <- c(42.72861190404861, -73.67421283293787)
max_coordinate_value_x <- 10
max_coordinate_value_y <- 10
max_distance           <- 0.001
grob_length_x          <- 2
grob_length_y          <- 3
min_buffer_x           <- 0.1
min_buffer_y           <- 0.1
starter_y_val          <- 5
  
Map_to_x  <- function(x, max_coordinate_value){ max(x, 1+x-floor(1+x) ) * max_coordinate_value }

shift_y_2 <- function(test_final_matrix, grob_length_y, min_buffer_y, starter_y_val){
  sequencevals <- rep(-1:1, times = floor(nrow(test_final_matrix)/3)+1)*(min_buffer_y+grob_length_y) + 
  starter_y_val
  sequence_trimmed = sequencevals[1:nrow(test_final_matrix)]
  final_matrix = test_final_matrix %>% mutate("yloc" = sequence_trimmed)
  final_matrix
}

correct_bounds_2 <- function(test_final_matrix, grob_length_x, max_coordinate_value, min_buffer_x){
  sorted_matrix <- test_final_matrix[order(test_final_matrix$xloc),]
  bottom_matrix <- sorted_matrix[sorted_matrix$xloc< grob_length_x/2+min_buffer_x ,]
  bottom_matrix$xloc <- bottom_matrix$xloc + grob_length_x/2 + min_buffer_x - bottom_matrix[1,2]
  top_matrix <- sorted_matrix[sorted_matrix$xloc>  max_coordinate_value - (grob_length_x/2+min_buffer_x) ,]
  top_matrix$xloc <- top_matrix$xloc + max_coordinate_value - grob_length_x/2 - min_buffer_x - top_matrix[nrow(top_matrix),2]
  
  middle_matrix = sorted_matrix[sorted_matrix$xloc> grob_length_x/2+min_buffer_x ,]
  middle_matrix = middle_matrix[middle_matrix$xloc< max_coordinate_value - (grob_length_x/2+min_buffer_x) ,]
  
  final_matrix = rbind.data.frame(bottom_matrix, middle_matrix, top_matrix)
  final_matrix = final_matrix[order(final_matrix$xloc),]
  final_matrix
}

Get_x_coordinates <- function(Lat, Lng, max_distance, rpi_wap_last7 = rpi_wap_last7, max_coordinate_value = 10, 
                              grob_length_x=2, grob_length_y=3, min_buffer_x = 0 ,min_buffer_y = 0 , starter_y_val = 5.5){
  
  true_max_coordinate_value = max_coordinate_value-1
  
  position = c(Lng,Lat)
  
  building_coords             <- as.matrix(buildinginfo %>% select(c(3,2)) )
  rownames(building_coords)   <- t(buildinginfo %>% select(1))
  colnames(building_coords)   <- c("lng","lat" )

  signed_building_coords <- scale(building_coords, center = position, scale = FALSE)
  distance_matrix        <- as.matrix(signed_building_coords[,1]^2+signed_building_coords[,2]^2)^(1/2)
  tot_building_info      <- data.frame(signed_building_coords) %>% mutate("Distance" = distance_matrix)
  select_building_info   <- tot_building_info %>% filter(Distance < max_distance)
  unit_coords_lng        <- matrix(select_building_info$lng/select_building_info$Distance)
  unit_coords_lat        <- matrix(             select_building_info$lat /select_building_info$Distance  ) 
  unit_coords            <-  data.frame(unit_coords_lng, unit_coords_lat)
  signed_fraction      <- acos(unit_coords[,2]) * sign(unit_coords[,1])/(2*pi)

  unit_x          <- as.numeric(lapply(signed_fraction, Map_to_x, max_coordinate_value = true_max_coordinate_value) )
  final_df        <- data.frame("Buildings" = row.names(select_building_info), "xloc" =  unit_x, "yloc" = starter_y_val)
  final_df        <- correct_bounds_2(final_df, grob_length_x, true_max_coordinate_value, min_buffer_x)
  final_df$xloc   <- final_df$xloc+1
  final_df$yloc   <- final_df$yloc+1
  final_df        <- shift_y_2(final_df, grob_length_y, min_buffer_y, starter_y_val)
  return(final_df)
}

testans <-Get_x_coordinates( test_hill[1], test_hill[2],max_distance)

testans

ggplot(data = data.frame(testans), aes(x = xloc, y = yloc, color = Buildings)) + geom_point(size = 2) + 
                xlim(1, max_coordinate_value_x)+ylim(1, max_coordinate_value_y)+ 
                geom_hline(yintercept = max_coordinate_value_y, alpha = 0.5) + 
                geom_hline(yintercept = 1, alpha = 0.5) + 
                geom_vline(xintercept = max_coordinate_value_x, alpha = 0.5) +
                geom_vline(xintercept = 1, alpha = 0.5) + 
                theme_classic2()

```
```{r}
name = c("Freshman Hill", "Sophomore Quad", "86 Field", "East Campus Athletic Village")
lat = c(42.728625,42.730407,42.730380,42.731488)
lng = c(-73.674214,-73.680209,-73.678015,-73.668876)
Test_DF = data.frame("Building" = name, "Lat" = lat, "Lng" = lng)

Function_results = mapply(Get_x_coordinates,Test_DF$Lat,Test_DF$Lng, 0.001)
Function_results

```




```{r}
df  <- data.frame(x= c(1:10), y = c(1:10))
df2 <- data.frame(x = 1 , y = 1)

g <- ggplotGrob(ggplot(df2, aes(x, y)) + geom_point() +
            theme(axis.title.x=element_blank(),axis.text.x=element_blank(),axis.ticks.x=element_blank(), 
            axis.title.y=element_blank(),axis.text.y=element_blank(),axis.ticks.y=element_blank()))

df
testplot <- function(data, Df = df,Inset = g){
  Base <- ggplot(Df, aes(x,y)) + geom_blank() + theme_bw() + coord_fixed(ratio = 1, c(0,10), c(0,10))+
                               geom_hline(yintercept = max_coordinate_value_y, alpha = 0.5) + 
                               geom_hline(yintercept = 1, alpha = 0.5) + geom_vline(xintercept = 1, alpha = 0.5) +
                               geom_vline(xintercept = max_coordinate_value_x, alpha = 0.5) 
  for (i in 1:nrow(data)){
  Base <- Base + annotation_custom(grob = Inset, xmin = data[i,2]-grob_length_x/2, xmax = data[i,2]+grob_length_x/2,
                                   ymin = data[i,3]-grob_length_y/2, ymax = data[i,3]+grob_length_y/2)} 
  Base                             
  }
plot = testplot(data.frame(Function_results[,2]) )
plot

```