Files
homeproz/wp-content/plugins/mls-by-hansonxyz/includes/class-mls-cluster.php
T
Hanson.xyz Dev dfad0f57e6 Add hover pins for clustered properties, disable grouping under 30 markers
- Add data-lat/data-lng attributes to MLS property cards
- Create temporary highlighted pin on card hover when marker is clustered
- Show individual pins (no grouping) when <= 30 properties in viewport
- Add markerLayer for unclustered markers to bypass client-side clustering
- Show loading spinner immediately on map move to abort image loads

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-12-17 02:31:23 -06:00

603 lines
20 KiB
PHP

<?php
/**
* MLS Map Clustering
*
* Server-side geohash-based clustering for efficient map rendering.
* Handles ~30k properties by returning clustered markers based on zoom level.
*/
if (!defined('ABSPATH')) {
exit;
}
class MLS_Cluster {
/**
* Geohash characters
*/
const GEOHASH_CHARS = '0123456789bcdefghjkmnpqrstuvwxyz';
/**
* Target pixel spacing between cluster centers
* With 30px cluster icons, 45px gap gives 75px total spacing
*/
const CLUSTER_PIXEL_SPACING = 60;
/**
* Pixel spacing for density dots (smaller, more numerous)
*/
const DENSITY_DOT_SPACING = 40;
/**
* Denser spacing for very zoomed out views (40% more dense = 60% of normal)
*/
const DENSITY_DOT_SPACING_DENSE = 24;
/**
* Maximum properties to return as individual markers
* Above this threshold, return clusters
*/
const MAX_INDIVIDUAL_MARKERS = 500;
/**
* Minimum properties before any grouping kicks in
* Below this, always show individual markers
*/
const MIN_FOR_GROUPING = 30;
/**
* Zoom thresholds for visualization modes
*/
const ZOOM_DENSE_MAX = 5; // 1-5: density dots (40% more dense)
const ZOOM_DENSITY_MAX = 8; // 6-8: density dots (normal)
const ZOOM_CLUSTER_MAX = 15; // 9-15: numbered clusters
// 16+: individual markers
/**
* Database instance
*/
private $db;
/**
* Constructor
*/
public function __construct(MLS_DB $db) {
$this->db = $db;
}
/**
* Get state filter SQL clause
*
* @return string SQL clause or empty string
*/
private function get_state_filter() {
if (!defined('MLS_ALLOWED_STATES') || empty(MLS_ALLOWED_STATES)) {
return '';
}
global $wpdb;
$states = array_map(function($state) use ($wpdb) {
return $wpdb->prepare('%s', $state);
}, MLS_ALLOWED_STATES);
return 'state_or_province IN (' . implode(',', $states) . ')';
}
/**
* Get the TBD address exclusion filter
* Excludes properties with "TBD" as street number
*
* @return string SQL clause
*/
private function get_tbd_exclusion_filter() {
return "(street_number IS NULL OR (street_number != 'TBD' AND street_number NOT LIKE 'TBD %'))";
}
/**
* Encode latitude/longitude to geohash
*
* @param float $lat Latitude
* @param float $lng Longitude
* @param int $precision Geohash precision (1-12)
* @return string Geohash string
*/
public function encode($lat, $lng, $precision = 6) {
$lat_range = array(-90.0, 90.0);
$lng_range = array(-180.0, 180.0);
$hash = '';
$bits = array(16, 8, 4, 2, 1);
$bit = 0;
$ch = 0;
$is_lng = true;
while (strlen($hash) < $precision) {
if ($is_lng) {
$mid = ($lng_range[0] + $lng_range[1]) / 2;
if ($lng >= $mid) {
$ch |= $bits[$bit];
$lng_range[0] = $mid;
} else {
$lng_range[1] = $mid;
}
} else {
$mid = ($lat_range[0] + $lat_range[1]) / 2;
if ($lat >= $mid) {
$ch |= $bits[$bit];
$lat_range[0] = $mid;
} else {
$lat_range[1] = $mid;
}
}
$is_lng = !$is_lng;
$bit++;
if ($bit === 5) {
$hash .= self::GEOHASH_CHARS[$ch];
$bit = 0;
$ch = 0;
}
}
return $hash;
}
/**
* Decode geohash to latitude/longitude bounds
*
* @param string $hash Geohash string
* @return array Array with lat_min, lat_max, lng_min, lng_max, lat_center, lng_center
*/
public function decode($hash) {
$lat_range = array(-90.0, 90.0);
$lng_range = array(-180.0, 180.0);
$is_lng = true;
for ($i = 0; $i < strlen($hash); $i++) {
$c = $hash[$i];
$cd = strpos(self::GEOHASH_CHARS, $c);
for ($j = 0; $j < 5; $j++) {
$mask = 1 << (4 - $j);
if ($is_lng) {
$mid = ($lng_range[0] + $lng_range[1]) / 2;
if ($cd & $mask) {
$lng_range[0] = $mid;
} else {
$lng_range[1] = $mid;
}
} else {
$mid = ($lat_range[0] + $lat_range[1]) / 2;
if ($cd & $mask) {
$lat_range[0] = $mid;
} else {
$lat_range[1] = $mid;
}
}
$is_lng = !$is_lng;
}
}
return array(
'lat_min' => $lat_range[0],
'lat_max' => $lat_range[1],
'lng_min' => $lng_range[0],
'lng_max' => $lng_range[1],
'lat_center' => ($lat_range[0] + $lat_range[1]) / 2,
'lng_center' => ($lng_range[0] + $lng_range[1]) / 2,
);
}
/**
* Calculate grid cell size in degrees for a given zoom level
*
* Uses Leaflet/OSM tile math to determine what geographic distance
* corresponds to the target pixel spacing at the given zoom.
*
* @param int $zoom Map zoom level (1-20)
* @param float $lat Center latitude (affects Mercator projection)
* @param int $pixel_spacing Target pixel spacing (defaults to CLUSTER_PIXEL_SPACING)
* @return array [lat_step, lng_step] in degrees
*/
public function get_grid_step_for_zoom($zoom, $lat = 45.0, $pixel_spacing = null) {
$zoom = max(3, min(20, (int) $zoom));
$pixel_spacing = $pixel_spacing ?: self::CLUSTER_PIXEL_SPACING;
// Degrees per pixel at zoom level (longitude)
// 360 degrees / (256 pixels * 2^zoom tiles)
$degrees_per_pixel_lng = 360.0 / (256 * pow(2, $zoom));
// Latitude degrees per pixel (adjusted for Mercator at given latitude)
// At the equator it's the same, at poles it's compressed
$lat_rad = deg2rad(abs($lat));
$degrees_per_pixel_lat = $degrees_per_pixel_lng * cos($lat_rad);
// Calculate step size to achieve target pixel spacing
$lng_step = $pixel_spacing * $degrees_per_pixel_lng;
$lat_step = $pixel_spacing * $degrees_per_pixel_lat;
return array($lat_step, $lng_step);
}
/**
* Get clustered markers for map viewport
*
* @param array $args Query arguments
* - bounds: array(sw_lat, sw_lng, ne_lat, ne_lng)
* - zoom: int Map zoom level
* - status: string Property status filter
* - property_type: string Property type filter
* - city: string City filter
* - min_price, max_price: int Price range
* - min_beds: int Minimum bedrooms
* @return array Array with 'clusters' or 'markers' depending on density
*/
public function get_clusters($args = array()) {
global $wpdb;
$defaults = array(
'bounds' => null,
'zoom' => 10,
'status' => 'Active',
'property_type' => null,
'city' => null,
'min_price' => null,
'max_price' => null,
'min_beds' => null,
);
$args = wp_parse_args($args, $defaults);
$table = $this->db->properties_table();
// Build WHERE clause
$where = array('mlg_can_view = 1', 'latitude IS NOT NULL', 'longitude IS NOT NULL');
$values = array();
// Add state filter (MN, IA only)
$state_filter = $this->get_state_filter();
if ($state_filter) {
$where[] = $state_filter;
}
// Exclude TBD addresses
$where[] = $this->get_tbd_exclusion_filter();
if ($args['status']) {
$where[] = 'standard_status = %s';
$values[] = $args['status'];
}
if ($args['property_type']) {
$where[] = 'property_type = %s';
$values[] = $args['property_type'];
}
if ($args['city']) {
$where[] = 'city = %s';
$values[] = $args['city'];
}
if ($args['min_price']) {
$where[] = 'list_price >= %d';
$values[] = (int) $args['min_price'];
}
if ($args['max_price']) {
$where[] = 'list_price <= %d';
$values[] = (int) $args['max_price'];
}
if ($args['min_beds']) {
$where[] = 'bedrooms_total >= %d';
$values[] = (int) $args['min_beds'];
}
// Add bounds filter if provided
if ($args['bounds'] && is_array($args['bounds']) && count($args['bounds']) === 4) {
list($sw_lat, $sw_lng, $ne_lat, $ne_lng) = $args['bounds'];
$where[] = 'latitude BETWEEN %f AND %f';
$where[] = 'longitude BETWEEN %f AND %f';
$values[] = (float) $sw_lat;
$values[] = (float) $ne_lat;
$values[] = (float) $sw_lng;
$values[] = (float) $ne_lng;
}
$where_sql = implode(' AND ', $where);
// First, get total count to decide clustering strategy
$count_sql = "SELECT COUNT(*) FROM {$table} WHERE {$where_sql}";
if (!empty($values)) {
$total = (int) $wpdb->get_var($wpdb->prepare($count_sql, $values));
} else {
$total = (int) $wpdb->get_var($count_sql);
}
// If few properties, always show individual markers (no grouping)
if ($total <= self::MIN_FOR_GROUPING) {
return $this->get_individual_markers($where_sql, $values, $total);
}
// Calculate center latitude for Mercator adjustment
$center_lat = 45.0; // Default Minnesota
if ($args['bounds'] && count($args['bounds']) === 4) {
$center_lat = ($args['bounds'][0] + $args['bounds'][2]) / 2;
}
$zoom = (int) $args['zoom'];
// Determine visualization mode based on zoom level
// Zoom 1-5: Density dots (40% more dense)
if ($zoom <= self::ZOOM_DENSE_MAX) {
return $this->get_density_data($where_sql, $values, $zoom, $center_lat, $total, self::DENSITY_DOT_SPACING_DENSE);
}
// Zoom 6-11: Density dots (normal spacing)
if ($zoom <= self::ZOOM_DENSITY_MAX) {
return $this->get_density_data($where_sql, $values, $zoom, $center_lat, $total, self::DENSITY_DOT_SPACING);
}
// Zoom 12-15: Numbered clusters (or individual if low count)
if ($zoom <= self::ZOOM_CLUSTER_MAX) {
if ($total <= self::MAX_INDIVIDUAL_MARKERS) {
return $this->get_individual_markers($where_sql, $values, $total);
}
return $this->get_cluster_data($where_sql, $values, $zoom, $center_lat, $total);
}
// Zoom 16+: Individual markers
return $this->get_individual_markers($where_sql, $values, $total);
}
/**
* Get heatmap data (just coordinates for client-side rendering)
*
* @param string $where_sql WHERE clause
* @param array $values Prepared values
* @param int $total Total count
* @return array
*/
private function get_heatmap_data($where_sql, $values, $total) {
global $wpdb;
$table = $this->db->properties_table();
// Get sampled points for heatmap (limit to prevent overwhelming the client)
// Use grid-based sampling to get representative distribution
$sql = "SELECT latitude, longitude
FROM {$table}
WHERE {$where_sql}
LIMIT 10000";
if (!empty($values)) {
$results = $wpdb->get_results($wpdb->prepare($sql, $values));
} else {
$results = $wpdb->get_results($sql);
}
$points = array();
foreach ($results as $row) {
$points[] = array(
(float) $row->latitude,
(float) $row->longitude,
1.0 // intensity
);
}
return array(
'type' => 'heatmap',
'total' => $total,
'point_count' => count($points),
'points' => $points,
);
}
/**
* Get density dot data (clustered points with count for coloring)
*
* @param string $where_sql WHERE clause
* @param array $values Prepared values
* @param int $zoom Map zoom level
* @param float $center_lat Center latitude for Mercator adjustment
* @param int $total Total count
* @param int $pixel_spacing Pixel spacing for grid cells
* @return array
*/
private function get_density_data($where_sql, $values, $zoom, $center_lat, $total, $pixel_spacing = null) {
global $wpdb;
$table = $this->db->properties_table();
$pixel_spacing = $pixel_spacing ?: self::DENSITY_DOT_SPACING;
// Use smaller grid cells for density dots
list($lat_step, $lng_step) = $this->get_grid_step_for_zoom($zoom, $center_lat, $pixel_spacing);
$sql = "SELECT
FLOOR(latitude / %f) as lat_cell,
FLOOR(longitude / %f) as lng_cell,
COUNT(*) as count,
AVG(latitude) as avg_lat,
AVG(longitude) as avg_lng
FROM {$table}
WHERE {$where_sql}
GROUP BY lat_cell, lng_cell
HAVING count >= 1";
$grid_values = array_merge(array($lat_step, $lng_step), $values);
$results = $wpdb->get_results($wpdb->prepare($sql, $grid_values));
$dots = array();
foreach ($results as $row) {
$dots[] = array(
'lat' => (float) $row->avg_lat,
'lng' => (float) $row->avg_lng,
'count' => (int) $row->count,
);
}
return array(
'type' => 'density',
'total' => $total,
'dot_count' => count($dots),
'zoom' => $zoom,
'dots' => $dots,
);
}
/**
* Get individual property markers
*
* @param string $where_sql WHERE clause
* @param array $values Prepared values
* @param int $total Total count
* @return array
*/
private function get_individual_markers($where_sql, $values, $total) {
global $wpdb;
$table = $this->db->properties_table();
$sql = "SELECT listing_key, latitude, longitude, list_price, street_number,
street_name, street_suffix, city, bedrooms_total,
bathrooms_total, living_area, standard_status
FROM {$table}
WHERE {$where_sql}
ORDER BY modification_timestamp DESC
LIMIT 5000";
if (!empty($values)) {
$results = $wpdb->get_results($wpdb->prepare($sql, $values));
} else {
$results = $wpdb->get_results($sql);
}
$markers = array();
foreach ($results as $property) {
// Format address
$address_parts = array();
if ($property->street_number) {
$address_parts[] = $property->street_number;
}
if ($property->street_name) {
$address_parts[] = $property->street_name;
}
if ($property->street_suffix) {
$address_parts[] = $property->street_suffix;
}
$street = implode(' ', $address_parts);
$full_address = $street ? $street . ', ' . $property->city : $property->city;
$markers[] = array(
'id' => $property->listing_key,
'lat' => (float) $property->latitude,
'lng' => (float) $property->longitude,
'price' => '$' . number_format($property->list_price),
'address' => $full_address,
'url' => home_url('/properties/?listing=' . urlencode($property->listing_key)),
'beds' => $property->bedrooms_total,
'baths' => $property->bathrooms_total,
'sqft' => $property->living_area,
'status' => $property->standard_status,
);
}
return array(
'type' => 'markers',
'total' => $total,
'count' => count($markers),
'markers' => $markers,
);
}
/**
* Get clustered data using grid-based grouping
*
* @param string $where_sql WHERE clause
* @param array $values Prepared values
* @param int $zoom Map zoom level
* @param float $center_lat Center latitude for Mercator adjustment
* @param int $total Total count
* @return array
*/
private function get_cluster_data($where_sql, $values, $zoom, $center_lat, $total) {
global $wpdb;
$table = $this->db->properties_table();
// Calculate grid cell size based on zoom level and target pixel spacing
list($lat_step, $lng_step) = $this->get_grid_step_for_zoom($zoom, $center_lat);
// Use FLOOR to group coordinates into cells
$sql = "SELECT
FLOOR(latitude / %f) as lat_cell,
FLOOR(longitude / %f) as lng_cell,
COUNT(*) as count,
AVG(latitude) as avg_lat,
AVG(longitude) as avg_lng,
MIN(list_price) as min_price,
MAX(list_price) as max_price
FROM {$table}
WHERE {$where_sql}
GROUP BY lat_cell, lng_cell
HAVING count >= 1";
$grid_values = array_merge(array($lat_step, $lng_step), $values);
$results = $wpdb->get_results($wpdb->prepare($sql, $grid_values));
$clusters = array();
foreach ($results as $row) {
$clusters[] = array(
'lat' => (float) $row->avg_lat,
'lng' => (float) $row->avg_lng,
'count' => (int) $row->count,
'min_price' => (int) $row->min_price,
'max_price' => (int) $row->max_price,
);
}
return array(
'type' => 'clusters',
'total' => $total,
'cluster_count' => count($clusters),
'zoom' => $zoom,
'grid_size_deg' => array('lat' => $lat_step, 'lng' => $lng_step),
'clusters' => $clusters,
);
}
/**
* Get total count with coordinates
*
* @param array $args Filter arguments
* @return int
*/
public function get_total_with_coords($args = array()) {
global $wpdb;
$table = $this->db->properties_table();
$where = array('mlg_can_view = 1', 'latitude IS NOT NULL', 'longitude IS NOT NULL');
$values = array();
// Add state filter (MN, IA only)
$state_filter = $this->get_state_filter();
if ($state_filter) {
$where[] = $state_filter;
}
// Exclude TBD addresses
$where[] = $this->get_tbd_exclusion_filter();
if (!empty($args['status'])) {
$where[] = 'standard_status = %s';
$values[] = $args['status'];
}
$sql = "SELECT COUNT(*) FROM {$table} WHERE " . implode(' AND ', $where);
if (!empty($values)) {
return (int) $wpdb->get_var($wpdb->prepare($sql, $values));
}
return (int) $wpdb->get_var($sql);
}
}