var plan_key = '';
var meet_loc_url = '/unc/meet-location';

// handy images
var img_zipmarker, img_youarehere, img_nomatch, img_expanded, img_unknown;
img_youarehere = "/images/zipmarker-youarehere.png";
img_nomatch = "/images/zipmarker-reserved.png";
img_expanded = "/images/zipmarker-viewing.png";
img_zipmarker = "/images/zipmarker.png";
img_unknown = "/images/zipmarker-unknown.png";
img_shadow = "/images/zipshadow.png";


// create a data structure for all the locations
var locs = [ [7809804,'Beard+Lot',35.906998485557,-79.05354002045729],[3853414,'Bynum+Hall+-+North+Campus',35.9117819105,-79.0505889916],[88875536,'Medical+Drive',35.907162148019154,-79.05184507369995],[3853400,'Swain+Hall+-+North+Campus',35.9117584105,-79.0531089916],[3853450,'UNC+Department+of+Public+Safety',35.9033292124,-79.0480200487],[7239389,'Wilson+Library+Lot',35.908937064184535,-79.05001848936081]];

// create a data structure for all the location groups
var loc_grps = [ [3998280, 35.90832787186011483333333333333333333333, -79.05118693590300833333333333333333333333, 15]];

// even though we have vehicle_id, it is not relevant at this stage since it will just be used for
// counting up how many vehicles match said criteria. we will leave it out of the array.
// make, model, location, amenity list
var vehicles = [ [94564,742432,7239389,['']],[94564,742432,7809804,[49167247,'']],[4264850,4264865,3853400,[49167247,'']],[94564,3398752,3853450,[49167247,'']],[94564,742432,3853414,[49167247,'']],[94563,163026706,88875536,[49167247,'']] ];

// local array of makes and models so we can tell which is which
var mks_mos = [[94563,1],[163026706,0],[4264850,1],[4264865,0],[94564,1],[742432,0],[3398752,0]];

// get a local set of ids for the amenities (we dont really need the description, unless
// we want to get really fancy and have the form adjust itself based on selections made
// (only show relevant body styles / amenities / neighborhoods based on the chosen make/model)
var amenities = [49167247];

// get a local set of ids for the styles so we can easily figure out what styles are needed
var styles = [142802904,8586495,8577473];

// get a local mapping of locations to location groups. this allows us to trim accordion
// results by neighborhood.
var lgmap = [[3853400,3998280],[3853414,3998280],[3853450,3998280],[7239389,3998280],[7809804,3998280],[88875536,3998280]];

// get a local mapping of models to styles. this allows us to trim accordion results by style
var stylemap = [[742432,8577473],[3398752,8586495],[4264865,8577473],[163026706,8586495],[163026706,142802904]];


// globals for finding your local address in the search box
var closestaddr = new Object();
var firstaddr = new Object();
var addrstr;
// TODO: right now, this just returns the coords for one address,
// we should expand this to support multiple address geocoding
function refreshCarsByAddress() {
    var addr = document.getElementById('gmaps-address').value;
    
    addrstr = addr;
    var new_addr;
    if (addr.match(/[ ]*/) != null && addr != "enter some or all of an address") {
        geocode(addrstr, function (p) {
            // see if this address is closer to the current fleet of a modified address is closer
            if (p) {
                firstaddr.lat = p.lat();
                firstaddr.lng = p.lng();
            } else {
                // this is kinda lame, but at least it is in the ocean
                firstaddr.lat = 0;
                firstaddr.lng = 0;
            }

            geocode(addrstr + ', North Carolina', function (s) {
                var old_dist, new_dist, e;
                if (!s && (firstaddr.lat == 0 && firstaddr.lng == 0)) {
                    closestaddr.lat = 0;
                    closestaddr.lng = 0;
                } else if (!s) {
                    closestaddr.lat = firstaddr.lat;
                    closestaddr.lng = firstaddr.lng;
                } else if (firstaddr.lat == 0 && firstaddr.lng == 0) {
                    closestaddr.lat = s.lat();
                    closestaddr.lng = s.lng();
                } else {
                    
                    old_dist = Math.sqrt(Math.pow(firstaddr.lat - 35.90832787, 2) + Math.pow(firstaddr.lng - -79.05118694, 2));
                    new_dist = Math.sqrt(Math.pow(s.lat() - 35.90832787, 2) + Math.pow(s.lng() - -79.05118694, 2));

                    if (old_dist >= new_dist) {
                        closestaddr.lat = s.lat();
                        closestaddr.lng = s.lng();
                    } else {
                        closestaddr.lat = firstaddr.lat;
                        closestaddr.lng = firstaddr.lng;
                    }
                    
                }

                if (!(closestaddr.lat == 0 && closestaddr.lng == 0)) {
                    find_loc.in_progress = 1;
                    find_loc.retry = 1;
                    place_home(closestaddr.lat, closestaddr.lng);
                    recenter(eval(find_loc.map), closestaddr.lat, closestaddr.lng, 16, 0);
                    e = document.getElementById('location_group_id');
                    if (e) {
                        e.selectedIndex = 0;
                    }
                    $('#new-type-filter').hide();
                    find_loc.in_progress = 0;
                    refreshAccordion(find_loc);
                } else {
                    alert("sorry, we couldn't find that address");
                }               
            });

        });
    }
}