homeproz/wp-content/plugins/mls-by-hansonxyz/includes/class-mls-cluster.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
        // Exclude properties with invalid coordinates from map display
        // Also exclude properties with no price or price < 100 (invalid data)
        $where = array('mlg_can_view = 1', 'latitude IS NOT NULL', 'longitude IS NOT NULL', 'coordinates_invalid = 0', 'list_price >= 100');
        $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 (BETWEEN is efficient for rectangular viewport queries)
        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 9-15: Always use server-side clusters (let server handle grouping)
        if ($zoom <= self::ZOOM_CLUSTER_MAX) {
            return $this->get_cluster_data($where_sql, $values, $zoom, $center_lat, $total);
        }

        // Zoom 16+: Individual markers (no clustering needed at this zoom)
        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;

            // Get image URL with signature
            $image_url = function_exists('mls_get_image_url')
                ? mls_get_image_url($property->listing_key, 1, 'thumb')
                : '';

            $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,
                'image' => $image_url,
            );
        }

        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();
        // Exclude properties with invalid coordinates or invalid price
        $where = array('mlg_can_view = 1', 'latitude IS NOT NULL', 'longitude IS NOT NULL', 'coordinates_invalid = 0', 'list_price >= 100');
        $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);
    }
}