Shiny, Event reactive, running several functions

Question

I am new in shiny, at the moment I am trying to set up a code where I can calculate activity clusters (through DBSCAN package) based on input variables: "eps" (minimum distances between points to be part of a cluster), "minpts" (minimum number of points to certain categories as Health), "maxpts" (minimum number of points for general categories as pubs, restaurants etc).

I did a test only through leaflet (without shiny) and the code runs smoothly, but once I bring-in shiny, I'm not able to make it work

the idea is that the user can modify these 3 variables on the side panel, and click an action button in order to trigger the calculation.

   #----------LIBRARIES----------#

library(plyr)
library(geosphere)
library(dbscan)
library(osmdata)
library(sf)
library(tidyr)
library(sp)
library(rgdal)
library(leaflet)
library(shiny)

#-------LOAD FILES-------#

OSM_merged <- read.csv(file = "C:\\Users\\jsainz\\Documents\\R\\Shiny_test\\OSM_merged.csv")

OSM_points <- OSM_merged

OSM_points$color <- OSM_points$category

OSM_points$color <- str_replace_all(OSM_points$color, "Culture", "#3073A")
OSM_points$color <- str_replace_all(OSM_points$color, "Educational", "# 887CAF")
OSM_points$color <- str_replace_all(OSM_points$color,"Financial", "#540002")
OSM_points$color <- str_replace_all(OSM_points$color,"Health", "#D6E899")
OSM_points$color <- str_replace_all(OSM_points$color,"Leisure", "#D2D68D")
OSM_points$color <- str_replace_all(OSM_points$color,"Office", "#D3696C")
OSM_points$color <- str_replace_all(OSM_points$color,"Shop", "#AA9739")
OSM_points$color <- str_replace_all(OSM_points$color,"Sport", "#378B2E")
OSM_points$color <- str_replace_all(OSM_points$color,"Sustain", "#554600")
OSM_points$color <- str_replace_all(OSM_points$color,"Toursim", "#5FAE57")

xy <- OSM_points[,c(2,3)]
OSM_points <- SpatialPointsDataFrame(coords = xy, data = OSM_points,proj4string = CRS("+proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0"))

#-------FUNCTIONS-------#

assign_clusters <- function(poi_df, minPts = NA) {
  if(is.na(minPts)) {
    if(poi_df[1, "category"] %in% c("Culture", "Leisure", "Education", "Health", "Financial")) {
      minPts <- "minpts"
    } else minPts <- "maxpts"
  }

  eps <- "epsilon"

  poi_df[c("lng", "lat")] %>% 
    distm(fun = distHaversine) %>%
    as.dist() %>% 
    dbscan(eps = eps, minPts = minPts) %>% 
    .[["cluster"]] %>% 
    cbind(poi_df, cluster = .)
}

get_hull<- function(df) {

  cbind(df$lng, df$lat) %>% 
    as.matrix() %>%
    st_multipoint() %>% 
    st_convex_hull() %>% 
    st_sfc(crs = 4326) %>% 
    {st_sf(category = df$category[1], cluster = df$cluster[1], geom = .)}
}

hulls <- function(df) {

  df %>%
    split(.$cluster) %>% 
    map(get_hull)

}

#----------SHINY CODE----------#

ui <- fluidPage(

  titlePanel("Jorge_Test"),

  sidebarPanel(
  numericInput(inputId = "epsilon", label = "distance in meters to calculate activity clusters", 200),
  numericInput(inputId = "minpts", label = "minimum points to calculate clusters", 5),
  numericInput(inputId = "maxpts", label = "maximum points to calculate clusters", 10),
  actionButton("run", "Run Calculation"),
  actionButton("view", "generate plan"),
  width = 2),

  mainPanel(
  leafletOutput("mymap", width = 1550, height = 850)
  )
)

server <- function(input, output, session) {

  output$mymap <- renderLeaflet({
    leaflet("mymap")%>%
      setView(lng = 0.0982, lat = 51.7674, zoom = 15)%>%
      addProviderTiles(providers$CartoDB.Positron, options = providerTileOptions(noWrap = TRUE))%>%
      addCircleMarkers(data = OSM_points,
                       radius = .7,
                       popup = ~category,
                       color = ~color)})

  oberveEvent(input$run, {

  updateNumericInput(session, "epsilon")
  updateNumericInput(session, "minpts")
  updateNumericInput(session, "maxpts")

  })

  Clean_data <- OSM_merged %>%
    split(OSM_merged$category) %>%  
    map_df(assign_clusters)

  hulls_cat <- Clean_data %>%
    group_by(category) %>%
    summarise()

  map_cluster_hulls <- Clean_data %>%
    filter(cluster != 0) %>%
    select(lng, lat, category, cluster) %>% 
    split(.$category) %>% 
    map(hulls)

  mdata <- melt(map_cluster_hulls, id = c("category", "cluster", "geom"))
  mch <- data.frame(mdata$category, mdata$cluster, mdata$geom)

  observeEvent(input$view, {
    leafletProxy("mymap", session) %>%
    addPolygons(data = mch$geom,
                fill = NA,
                fillOpacity = .01,
                weight = 2,
                color = "red",
                opacity = .8)
  }
 )

}

shinyApp(ui, server)

any idea of how to solve it?

here is a link to the OSM_merged.csv file: https://www.dropbox.com/s/5ok9frcvx8oj16y/OSM_merged.csv?dl=0