文章目录[隐藏]
WordPress柔性供应链软件开发中的数据中台构建教程
引言：柔性供应链与数据中台的价值
在当今快速变化的市场环境中，企业需要更加灵活、响应迅速的供应链系统。WordPress作为全球最流行的内容管理系统，其强大的扩展性和丰富的插件生态使其成为构建企业级应用的理想平台。柔性供应链软件能够帮助企业应对市场需求波动、供应链中断等挑战，而数据中台则是实现这一目标的核心技术架构。
数据中台通过统一数据标准、整合多源数据、提供数据服务，为供应链决策提供实时、准确的数据支持。本教程将详细介绍如何在WordPress环境中构建一个功能完整的数据中台，以支持柔性供应链软件的开发。
一、数据中台架构设计
1.1 整体架构概述
数据中台采用分层架构设计，包括数据采集层、数据存储层、数据处理层和数据服务层。在WordPress环境中，我们可以利用其现有的数据库结构和插件机制，构建一个既符合WordPress规范又满足企业级需求的数据中台。
<?php
/**
* WordPress数据中台核心架构类
* 负责初始化数据中台各组件和协调数据流
*/
class DataMiddlePlatform {
private $data_collectors = array(); // 数据采集器集合
private $data_processors = array(); // 数据处理器集合
private $data_services = array(); // 数据服务集合
/**
* 初始化数据中台
*/
public function __construct() {
$this->init_components();
$this->setup_hooks();
}
/**
* 初始化各组件
*/
private function init_components() {
// 初始化数据采集器
$this->data_collectors[] = new OrderDataCollector();
$this->data_collectors[] = new InventoryDataCollector();
$this->data_collectors[] = new SupplierDataCollector();
// 初始化数据处理器
$this->data_processors[] = new DataCleaner();
$this->data_processors[] = new DataTransformer();
$this->data_processors[] = new DataAggregator();
// 初始化数据服务
$this->data_services[] = new RealTimeInventoryService();
$this->data_services[] = new DemandForecastService();
$this->data_services[] = new SupplierPerformanceService();
}
/**
* 设置WordPress钩子
*/
private function setup_hooks() {
// 数据采集钩子
add_action('woocommerce_new_order', array($this, 'collect_order_data'));
add_action('save_post_product', array($this, 'collect_inventory_data'));
// 数据更新钩子
add_action('data_middle_platform_daily_process', array($this, 'daily_data_processing'));
}
/**
* 收集订单数据
* @param int $order_id 订单ID
*/
public function collect_order_data($order_id) {
foreach ($this->data_collectors as $collector) {
if ($collector instanceof OrderDataCollector) {
$collector->collect($order_id);
}
}
}
/**
* 每日数据处理
*/
public function daily_data_processing() {
// 数据清洗
foreach ($this->data_processors as $processor) {
if ($processor instanceof DataCleaner) {
$processor->clean();
}
}
// 数据聚合
foreach ($this->data_processors as $processor) {
if ($processor instanceof DataAggregator) {
$processor->aggregate();
}
}
}
}
?>1.2 数据库设计优化
在WordPress默认数据库结构基础上，我们需要为供应链数据中台设计专用数据表：
<?php
/**
* 供应链数据中台数据库表创建类
*/
class SupplyChainDataTables {
/**
* 创建数据中台所需的数据表
*/
public static function create_tables() {
global $wpdb;
$charset_collate = $wpdb->get_charset_collate();
// 实时库存表
$table_name = $wpdb->prefix . 'sc_real_time_inventory';
$sql = "CREATE TABLE IF NOT EXISTS $table_name (
id bigint(20) NOT NULL AUTO_INCREMENT,
product_id bigint(20) NOT NULL,
warehouse_id bigint(20) NOT NULL,
quantity int(11) NOT NULL DEFAULT 0,
reserved_quantity int(11) NOT NULL DEFAULT 0,
available_quantity int(11) NOT NULL DEFAULT 0,
last_updated datetime DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
PRIMARY KEY (id),
KEY product_warehouse (product_id, warehouse_id),
KEY last_updated (last_updated)
) $charset_collate;";
require_once(ABSPATH . 'wp-admin/includes/upgrade.php');
dbDelta($sql);
// 供应商绩效表
$table_name = $wpdb->prefix . 'sc_supplier_performance';
$sql = "CREATE TABLE IF NOT EXISTS $table_name (
id bigint(20) NOT NULL AUTO_INCREMENT,
supplier_id bigint(20) NOT NULL,
on_time_delivery_rate decimal(5,2) DEFAULT 0,
quality_pass_rate decimal(5,2) DEFAULT 0,
avg_response_time int(11) DEFAULT 0,
total_orders int(11) DEFAULT 0,
performance_score decimal(5,2) DEFAULT 0,
evaluation_date date NOT NULL,
PRIMARY KEY (id),
KEY supplier_date (supplier_id, evaluation_date)
) $charset_collate;";
dbDelta($sql);
// 需求预测表
$table_name = $wpdb->prefix . 'sc_demand_forecast';
$sql = "CREATE TABLE IF NOT EXISTS $table_name (
id bigint(20) NOT NULL AUTO_INCREMENT,
product_id bigint(20) NOT NULL,
forecast_date date NOT NULL,
predicted_demand int(11) DEFAULT 0,
confidence_level decimal(5,2) DEFAULT 0,
algorithm_used varchar(50) DEFAULT '',
last_calculated datetime DEFAULT CURRENT_TIMESTAMP,
PRIMARY KEY (id),
UNIQUE KEY product_forecast_date (product_id, forecast_date)
) $charset_collate;";
dbDelta($sql);
}
}
?>二、数据采集与整合模块
2.1 多源数据采集器
柔性供应链涉及多个数据源，包括订单数据、库存数据、供应商数据等。以下是一个多源数据采集器的实现：
<?php
/**
* 多源数据采集器基类
*/
abstract class DataCollector {
protected $source_type;
protected $last_collection_time;
/**
* 采集数据抽象方法
* @param mixed $source 数据源标识
* @return array 采集到的数据
*/
abstract public function collect($source);
/**
* 验证数据完整性
* @param array $data 待验证数据
* @return bool 验证结果
*/
abstract protected function validate_data($data);
/**
* 转换数据格式
* @param array $raw_data 原始数据
* @return array 标准化数据
*/
abstract protected function transform_data($raw_data);
}
/**
* 订单数据采集器
*/
class OrderDataCollector extends DataCollector {
public function __construct() {
$this->source_type = 'woocommerce_order';
}
/**
* 采集订单数据
* @param int $order_id 订单ID
* @return array 订单数据
*/
public function collect($order_id) {
// 获取订单对象
$order = wc_get_order($order_id);
if (!$order) {
return array('error' => '订单不存在');
}
// 提取订单数据
$raw_data = array(
'order_id' => $order_id,
'customer_id' => $order->get_customer_id(),
'order_date' => $order->get_date_created()->date('Y-m-d H:i:s'),
'order_status' => $order->get_status(),
'order_total' => $order->get_total(),
'items' => array()
);
// 提取订单项数据
foreach ($order->get_items() as $item_id => $item) {
$product = $item->get_product();
$raw_data['items'][] = array(
'product_id' => $item->get_product_id(),
'variation_id' => $item->get_variation_id(),
'quantity' => $item->get_quantity(),
'price' => $item->get_total(),
'sku' => $product ? $product->get_sku() : ''
);
}
// 验证数据
if (!$this->validate_data($raw_data)) {
return array('error' => '数据验证失败');
}
// 转换数据格式
$transformed_data = $this->transform_data($raw_data);
// 存储到数据中台
$this->store_to_middle_platform($transformed_data);
return $transformed_data;
}
/**
* 验证订单数据
* @param array $data 订单数据
* @return bool 验证结果
*/
protected function validate_data($data) {
// 检查必要字段
$required_fields = array('order_id', 'order_date', 'order_status', 'items');
foreach ($required_fields as $field) {
if (!isset($data[$field]) || empty($data[$field])) {
error_log("订单数据缺少必要字段: $field");
return false;
}
}
// 检查订单项数据
if (count($data['items']) === 0) {
error_log("订单没有商品项");
return false;
}
return true;
}
/**
* 转换订单数据格式
* @param array $raw_data 原始订单数据
* @return array 标准化订单数据
*/
protected function transform_data($raw_data) {
$transformed = array(
'order_id' => intval($raw_data['order_id']),
'customer_id' => intval($raw_data['customer_id']),
'order_timestamp' => strtotime($raw_data['order_date']),
'order_status' => sanitize_text_field($raw_data['order_status']),
'total_amount' => floatval($raw_data['order_total']),
'item_count' => count($raw_data['items']),
'items' => array()
);
// 转换订单项数据
foreach ($raw_data['items'] as $item) {
$transformed['items'][] = array(
'product_id' => intval($item['product_id']),
'variation_id' => intval($item['variation_id']),
'quantity' => intval($item['quantity']),
'price' => floatval($item['price']),
'sku' => sanitize_text_field($item['sku'])
);
}
return $transformed;
}
/**
* 存储到数据中台
* @param array $data 标准化订单数据
*/
private function store_to_middle_platform($data) {
global $wpdb;
$table_name = $wpdb->prefix . 'sc_order_data';
// 插入订单主数据
$wpdb->insert(
$table_name,
array(
'order_id' => $data['order_id'],
'customer_id' => $data['customer_id'],
'order_timestamp' => date('Y-m-d H:i:s', $data['order_timestamp']),
'order_status' => $data['order_status'],
'total_amount' => $data['total_amount'],
'item_count' => $data['item_count'],
'collected_at' => current_time('mysql')
),
array('%d', '%d', '%s', '%s', '%f', '%d', '%s')
);
$this->last_collection_time = current_time('mysql');
}
}
?>2.2 外部API数据集成
现代供应链通常需要集成外部系统数据，以下是一个供应商API数据集成示例：
<?php
/**
* 外部供应商API数据集成类
*/
class SupplierAPIIntegrator {
private $api_endpoint;
private $api_key;
private $cache_timeout = 3600; // 缓存1小时
public function __construct($endpoint, $api_key) {
$this->api_endpoint = $endpoint;
$this->api_key = $api_key;
}
/**
* 获取供应商库存数据
* @param int $supplier_id 供应商ID
* @param array $product_skus 产品SKU数组
* @return array 供应商库存数据
*/
public function get_supplier_inventory($supplier_id, $product_skus = array()) {
$cache_key = 'supplier_inventory_' . $supplier_id . '_' . md5(serialize($product_skus));
// 尝试从缓存获取
$cached_data = get_transient($cache_key);
if ($cached_data !== false) {
return $cached_data;
}
// 构建API请求
$request_data = array(
'supplier_id' => $supplier_id,
'products' => $product_skus,
'timestamp' => time()
);
// 发送API请求
$response = $this->make_api_request('inventory/check', $request_data);
if ($response && $response['success']) {
// 缓存API响应
set_transient($cache_key, $response['data'], $this->cache_timeout);
// 更新数据中台
$this->update_supplier_inventory_data($supplier_id, $response['data']);
return $response['data'];
}
return array('error' => '无法获取供应商库存数据');
}
/**
* 发送API请求
* @param string $endpoint API端点
* @param array $data 请求数据
* @return array API响应
*/
private function make_api_request($endpoint, $data) {
$url = rtrim($this->api_endpoint, '/') . '/' . $endpoint;
$args = array(
'headers' => array(
'Authorization' => 'Bearer ' . $this->api_key,
'Content-Type' => 'application/json'
),
'body' => json_encode($data),
'timeout' => 30,
'redirection' => 5
);
$response = wp_remote_post($url, $args);
if (is_wp_error($response)) {
error_log('供应商API请求失败: ' . $response->get_error_message());
return false;
}
$body = wp_remote_retrieve_body($response);
$decoded = json_decode($body, true);
return $decoded;
}
/**
* 更新供应商库存数据到数据中台
* @param int $supplier_id 供应商ID
* @param array $inventory_data 库存数据
*/
private function update_supplier_inventory_data($supplier_id, $inventory_data) {
global $wpdb;
$table_name = $wpdb->prefix . 'sc_supplier_inventory';
foreach ($inventory_data as $item) {
$wpdb->replace(
$table_name,
array(
'supplier_id' => $supplier_id,
'product_sku' => sanitize_text_field($item['sku']),
'available_quantity' => intval($item['quantity']),
'lead_time_days' => intval($item['lead_time']),
'unit_price' => floatval($item['price']),
'last_updated' => current_time('mysql')
),
array('%d', '%s', '%d', '%d', '%f', '%s')
);
}
}
}
?>三、数据处理与计算引擎
3.1 实时库存计算引擎
柔性供应链需要实时准确的库存数据，以下是一个实时库存计算引擎的实现：
<?php
/**
* 实时库存计算引擎
*/
class RealTimeInventoryEngine {
private $inventory_adjustments = array();
/**
* 计算实时可用库存
* @param int $product_id 产品ID
* @param int $warehouse_id 仓库ID
* @return array 库存信息
*/
public function calculate_real_time_inventory($product_id, $warehouse_id = 0) {
global $wpdb;
$base_inventory = $this->get_base_inventory($product_id, $warehouse_id);
$reserved_inventory = $this->get_reserved_inventory($product_id, $warehouse_id);
$in_transit_inventory = $this->get_in_transit_inventory($product_id, $warehouse_id);
// 计算可用库存
$available_inventory = $base_inventory['quantity']
- $reserved_inventory
+ $in_transit_inventory;
// 考虑安全库存
$safety_stock = $this->calculate_safety_stock($product_id);
$available_with_safety = $available_inventory - $safety_stock;
// 考虑在途库存预计到达时间
$eta_info = $this->get_in_transit_eta($product_id, $warehouse_id);
$result = array(
'product_id' => $product_id,
'warehouse_id' => $warehouse_id,
'base_quantity' => $base_inventory['quantity'],
'reserved_quantity' => $reserved_inventory,
'in_transit_quantity' => $in_transit_inventory,
'available_quantity' => max(0, $available_inventory),$safety_stock,
'available_with_safety' => max(0, $available_with_safety),
'in_transit_eta' => $eta_info,
'last_calculated' => current_time('mysql'),
'reorder_recommendation' => $this->generate_reorder_recommendation(
$available_inventory,
$safety_stock,
$product_id
)
);
// 更新实时库存表
$this->update_real_time_inventory_table($result);
return $result;
}
/**
* 获取基础库存
* @param int $product_id 产品ID
* @param int $warehouse_id 仓库ID
* @return array 基础库存信息
*/
private function get_base_inventory($product_id, $warehouse_id) {
global $wpdb;
$table_name = $wpdb->prefix . 'wc_product_warehouse_inventory';
$query = $wpdb->prepare(
"SELECT quantity, location FROM $table_name
WHERE product_id = %d AND warehouse_id = %d",
$product_id,
$warehouse_id
);
$result = $wpdb->get_row($query, ARRAY_A);
return $result ?: array('quantity' => 0, 'location' => '');
}
/**
* 获取预留库存
* @param int $product_id 产品ID
* @param int $warehouse_id 仓库ID
* @return int 预留库存数量
*/
private function get_reserved_inventory($product_id, $warehouse_id) {
global $wpdb;
$table_name = $wpdb->prefix . 'sc_reserved_inventory';
$query = $wpdb->prepare(
"SELECT SUM(quantity) as total_reserved FROM $table_name
WHERE product_id = %d AND warehouse_id = %d
AND reservation_expiry > %s",
$product_id,
$warehouse_id,
current_time('mysql')
);
$result = $wpdb->get_var($query);
return intval($result ?: 0);
}
/**
* 计算安全库存
* @param int $product_id 产品ID
* @return float 安全库存数量
*/
private function calculate_safety_stock($product_id) {
// 获取历史销售数据
$sales_data = $this->get_sales_history($product_id, 90); // 最近90天
if (empty($sales_data)) {
return 0;
}
// 计算日均销量
$total_sales = array_sum(array_column($sales_data, 'quantity'));
$average_daily_sales = $total_sales / count($sales_data);
// 计算销售标准差
$variance = 0;
foreach ($sales_data as $day) {
$variance += pow($day['quantity'] - $average_daily_sales, 2);
}
$std_deviation = sqrt($variance / count($sales_data));
// 获取供应商平均交货时间
$lead_time = $this->get_average_lead_time($product_id);
// 安全库存公式：Z * σ * √(L)
// Z值（服务水平95%对应1.65）
$z_score = 1.65;
$safety_stock = $z_score * $std_deviation * sqrt($lead_time);
return ceil($safety_stock);
}
/**
* 生成补货建议
* @param float $available_inventory 可用库存
* @param float $safety_stock 安全库存
* @param int $product_id 产品ID
* @return array 补货建议
*/
private function generate_reorder_recommendation($available_inventory, $safety_stock, $product_id) {
$reorder_point = $safety_stock * 1.5; // 再订货点 = 1.5倍安全库存
$economic_order_quantity = $this->calculate_eoq($product_id);
$recommendation = array(
'current_level' => $available_inventory,
'reorder_point' => $reorder_point,
'economic_order_quantity' => $economic_order_quantity,
'status' => 'adequate',
'message' => ''
);
if ($available_inventory <= $safety_stock) {
$recommendation['status'] = 'critical';
$recommendation['message'] = '库存低于安全库存，建议立即补货';
$recommendation['suggested_order_quantity'] = $economic_order_quantity;
} elseif ($available_inventory <= $reorder_point) {
$recommendation['status'] = 'warning';
$recommendation['message'] = '库存接近再订货点，建议安排补货';
$recommendation['suggested_order_quantity'] = $economic_order_quantity;
}
return $recommendation;
}
/**
* 计算经济订货批量(EOQ)
* @param int $product_id 产品ID
* @return float 经济订货批量
*/
private function calculate_eoq($product_id) {
// 获取年需求量
$annual_demand = $this->get_annual_demand($product_id);
// 获取订货成本（假设值，实际应从系统获取）
$order_cost = 50; // 每次订货成本
// 获取持有成本率（假设为产品价值的20%）
$holding_rate = 0.20;
$product_value = $this->get_product_value($product_id);
$holding_cost_per_unit = $product_value * $holding_rate;
// EOQ公式：√(2DS/H)
if ($holding_cost_per_unit > 0) {
$eoq = sqrt((2 * $annual_demand * $order_cost) / $holding_cost_per_unit);
return ceil($eoq);
}
return 0;
}}
?>
### 3.2 需求预测算法实现
<?php
/**
- 需求预测算法类
- 实现多种预测算法供柔性供应链使用
*/
class DemandForecastAlgorithm {
/**
* 简单移动平均法
* @param array $historical_data 历史数据 [['date' => '2024-01-01', 'demand' => 100], ...]
* @param int $period 移动平均期数
* @param int $forecast_days 预测天数
* @return array 预测结果
*/
public function simple_moving_average($historical_data, $period = 7, $forecast_days = 30) {
if (count($historical_data) < $period) {
return array('error' => '历史数据不足');
}
// 提取需求数据
$demands = array_column($historical_data, 'demand');
// 计算移动平均值
$moving_averages = array();
for ($i = $period - 1; $i < count($demands); $i++) {
$sum = 0;
for ($j = 0; $j < $period; $j++) {
$sum += $demands[$i - $j];
}
$moving_averages[] = $sum / $period;
}
// 使用最近的平均值进行预测
$last_average = end($moving_averages);
$forecast = array();
for ($day = 1; $day <= $forecast_days; $day++) {
$forecast_date = date('Y-m-d', strtotime("+$day days"));
$forecast[] = array(
'date' => $forecast_date,
'predicted_demand' => round($last_average),
'algorithm' => 'simple_moving_average',
'confidence_level' => $this->calculate_confidence($historical_data, $moving_averages)
);
}
return $forecast;
}
/**
* 指数平滑法（Holt-Winters季节性预测）
* @param array $historical_data 历史数据
* @param int $seasonal_period 季节周期（如7天、30天）
* @param int $forecast_days 预测天数
* @return array 预测结果
*/
public function holt_winters($historical_data, $seasonal_period = 7, $forecast_days = 30) {
$n = count($historical_data);
if ($n < 2 * $seasonal_period) {
return $this->simple_moving_average($historical_data, 7, $forecast_days);
}
// 提取需求数据
$demands = array_column($historical_data, 'demand');
// 初始化参数
$alpha = 0.3; // 水平平滑系数
$beta = 0.1; // 趋势平滑系数
$gamma = 0.2; // 季节平滑系数
// 初始化水平、趋势和季节性分量
$level = array();
$trend = array();
$seasonal = array();
// 初始季节性因子
for ($i = 0; $i < $seasonal_period; $i++) {
$sum = 0;
$count = 0;
for ($j = $i; $j < $n; $j += $seasonal_period) {
$sum += $demands[$j];
$count++;
}
$seasonal[$i] = $count > 0 ? $sum / $count : 0;
}
// 归一化季节性因子
$seasonal_sum = array_sum($seasonal);
$normalization_factor = $seasonal_period / $seasonal_sum;
foreach ($seasonal as $key => $value) {
$seasonal[$key] *= $normalization_factor;
}
// 初始水平
$level[0] = $demands[0] / $seasonal[0];
// 初始趋势
$trend[0] = 0;
// Holt-Winters计算
for ($i = 1; $i < $n; $i++) {
$seasonal_index = $i % $seasonal_period;
// 更新水平
$level[$i] = $alpha * ($demands[$i] / $seasonal[$seasonal_index])
+ (1 - $alpha) * ($level[$i-1] + $trend[$i-1]);
// 更新趋势
$trend[$i] = $beta * ($level[$i] - $level[$i-1])
+ (1 - $beta) * $trend[$i-1];
// 更新季节性
$seasonal[$seasonal_index] = $gamma * ($demands[$i] / $level[$i])
+ (1 - $gamma) * $seasonal[$seasonal_index];
}
// 生成预测
$forecast = array();
$last_level = $level[$n-1];
$last_trend = $trend[$n-1];
for ($day = 1; $day <= $forecast_days; $day++) {
$forecast_index = $n + $day - 1;
$seasonal_index = $forecast_index % $seasonal_period;
$predicted = ($last_level + $day * $last_trend) * $seasonal[$seasonal_index];
$forecast_date = date('Y-m-d', strtotime("+$day days"));
$forecast[] = array(
'date' => $forecast_date,
'predicted_demand' => round(max(0, $predicted)),
'algorithm' => 'holt_winters',
'confidence_level' => $this->calculate_holt_winters_confidence(
$demands, $level, $trend, $seasonal, $seasonal_period
)
);
}
return $forecast;
}
/**
* 机器学习预测（使用线性回归）
* @param array $historical_data 历史数据
* @param array $features 特征数据 [['temperature' => 25, 'promotion' => 1], ...]
* @param int $forecast_days 预测天数
* @return array 预测结果
*/
public function linear_regression_forecast($historical_data, $features, $forecast_days = 30) {
if (count($historical_data) < 10 || count($historical_data) !== count($features)) {
return array('error' => '数据不足或不匹配');
}
$demands = array_column($historical_data, 'demand');
$n = count($demands);
// 准备数据
$X = array(); // 特征矩阵
$y = $demands; // 目标变量
foreach ($features as $feature_set) {
$X_row = array(1); // 截距项
foreach ($feature_set as $value) {
$X_row[] = floatval($value);
}
$X[] = $X_row;
}
// 计算线性回归系数 (使用正规方程: β = (X'X)^(-1)X'y)
$X_transpose = $this->matrix_transpose($X);
$X_transpose_X = $this->matrix_multiply($X_transpose, $X);
$X_transpose_y = $this->matrix_vector_multiply($X_transpose, $y);
// 求逆矩阵（简化版，实际应用应使用更稳定的算法）
$coefficients = $this->solve_linear_system($X_transpose_X, $X_transpose_y);
// 生成预测
$forecast = array();
$feature_count = count($features[0]);
for ($day = 1; $day <= $forecast_days; $day++) {
// 构建预测特征（这里使用最近的特征值，实际应根据预测日期生成）
$last_features = $features[$n-1];
$prediction_features = array(1); // 截距项
foreach ($last_features as $key => $value) {
// 简单处理：对数值特征添加微小变化
if (is_numeric($value)) {
$prediction_features[] = $value * (1 + 0.01 * $day);
} else {
$prediction_features[] = $value;
}
}
// 计算预测值
$predicted = 0;
for ($i = 0; $i < count($coefficients); $i++) {
$predicted += $coefficients[$i] * $prediction_features[$i];
}
$forecast_date = date('Y-m-d', strtotime("+$day days"));
$forecast[] = array(
'date' => $forecast_date,
'predicted_demand' => round(max(0, $predicted)),
'algorithm' => 'linear_regression',
'confidence_level' => $this->calculate_regression_confidence($X, $y, $coefficients)
);
}
return $forecast;
}
/**
* 矩阵转置
*/
private function matrix_transpose($matrix) {
$transpose = array();
foreach ($matrix as $i => $row) {
foreach ($row as $j => $value) {
$transpose[$j][$i] = $value;
}
}
return $transpose;
}
/**
* 矩阵乘法
*/
private function matrix_multiply($A, $B) {
$result = array();
$rows_A = count($A);
$cols_A = count($A[0]);
$cols_B = count($B[0]);
for ($i = 0; $i < $rows_A; $i++) {
for ($j = 0; $j < $cols_B; $j++) {
$result[$i][$j] = 0;
for ($k = 0; $k < $cols_A; $k++) {
$result[$i][$j] += $A[$i][$k] * $B[$k][$j];
}
}
}
return $result;
}}
?>
## 四、数据服务与API层
### 4.1 RESTful API 设计
<?php
/**
- 数据中台RESTful API控制器
- 为柔性供应链提供数据服务接口
*/
class DataMiddlePlatformAPI {
private $namespace = 'sc-data/v1';
public function __construct() {
add_action('rest_api_init', array($this, 'register_routes'));
}
/**
* 注册API路由
*/
public function register_routes() {
// 实时库存查询API
register_rest_route($this->namespace, '/inventory/real-time', array(
array(
'methods' => 'GET',
'callback' => array($this, 'get_real_time_inventory'),
'permission_callback' => array($this, 'check_api_permission'),
'args' => array(
'product_id' => array(
'required' => true,
'validate_callback' => function($param) {
return is_numeric($param);
}
),
'warehouse_id' => array(
'required' => false,
'default' => 0
),
'include_recommendations' => array(
'required' => false,
'default' => true
)
)
)
));
// 需求预测API
register_rest_route($this->namespace, '/forecast/demand', array(
array(
'methods' => 'GET',
'callback' => array($this, 'get_demand_forecast'),
'permission_callback' => array($this, 'check_api_permission'),
'args' => array(
'product_id' => array(
'