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@@ -321,4 +321,819 @@ function renderRegionSalesComparisonTable($comparison_data) {
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</table>
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</div>
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<?php
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+}
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+
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+/**
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+ * 获取地区总销售额及增长率
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+ *
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+ * @param mysqli $conn 数据库连接
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+ * @param string $start_date 开始日期
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+ * @param string $end_date 结束日期
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+ * @return array 总销售额和增长率
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+ */
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+function getRegionTotalSales($conn, $start_date, $end_date) {
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+ // 计算当前周期销售额
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+ $sql = "SELECT SUM(o.total_amount) as total_amount
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+ FROM orders o
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+ WHERE o.order_date BETWEEN ? AND ?";
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+
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+ $stmt = $conn->prepare($sql);
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+ $stmt->bind_param("ss", $start_date, $end_date);
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+ $stmt->execute();
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+ $result = $stmt->get_result();
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+ $row = $result->fetch_assoc();
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+ $current_amount = $row['total_amount'] ?? 0;
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+
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+ // 计算上一个相同时长的周期
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+ $current_start_date = new DateTime($start_date);
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+ $current_end_date = new DateTime($end_date);
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+ $interval = $current_start_date->diff($current_end_date);
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+
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+ $prev_end_date = clone $current_start_date;
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+ $prev_end_date->modify('-1 day');
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+ $prev_start_date = clone $prev_end_date;
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+ $prev_start_date->sub($interval);
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+
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+ $prev_start = $prev_start_date->format('Y-m-d');
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+ $prev_end = $prev_end_date->format('Y-m-d') . ' 23:59:59';
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+
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+ // 获取上一周期销售额
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+ $stmt = $conn->prepare($sql);
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+ $stmt->bind_param("ss", $prev_start, $prev_end);
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+ $stmt->execute();
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+ $result = $stmt->get_result();
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+ $row = $result->fetch_assoc();
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+ $prev_amount = $row['total_amount'] ?? 0;
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+
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+ // 计算增长率
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+ $growth = 0;
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+ if ($prev_amount > 0) {
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+ $growth = (($current_amount - $prev_amount) / $prev_amount) * 100;
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+ }
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+
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+ return [
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+ 'total_amount' => $current_amount,
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+ 'growth' => $growth
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+ ];
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+}
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+
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+/**
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+ * 获取活跃国家数
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+ *
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+ * @param mysqli $conn 数据库连接
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+ * @param string $start_date 开始日期
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+ * @param string $end_date 结束日期
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+ * @return array 活跃国家信息
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+ */
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+function getActiveCountries($conn, $start_date, $end_date) {
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+ $sql = "SELECT COUNT(DISTINCT cu.cs_country) as country_count
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+ FROM orders o
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+ JOIN customer cu ON o.customer_id = cu.id
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+ WHERE o.order_date BETWEEN ? AND ?";
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+
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+ $stmt = $conn->prepare($sql);
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+ $stmt->bind_param("ss", $start_date, $end_date);
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+ $stmt->execute();
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+ $result = $stmt->get_result();
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+ $row = $result->fetch_assoc();
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+
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+ return [
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+ 'count' => $row['country_count'] ?? 0
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+ ];
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+}
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+
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+/**
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+ * 获取各地区平均订单金额
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+ *
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+ * @param mysqli $conn 数据库连接
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+ * @param string $start_date 开始日期
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+ * @param string $end_date 结束日期
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+ * @return array 各地区平均订单金额数据
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+ */
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+function getAverageOrderByRegion($conn, $start_date, $end_date) {
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+ $sql = "SELECT
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+ c.countryName,
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+ AVG(o.total_amount) as avg_amount,
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+ COUNT(o.id) as order_count
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+ FROM orders o
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+ JOIN customer cu ON o.customer_id = cu.id
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+ JOIN country c ON cu.cs_country = c.id
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+ WHERE o.order_date BETWEEN ? AND ?
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+ GROUP BY cu.cs_country
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+ HAVING order_count >= 5
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+ ORDER BY avg_amount DESC
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+ LIMIT 10";
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+
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+ $stmt = $conn->prepare($sql);
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+ $stmt->bind_param("ss", $start_date, $end_date);
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+ $stmt->execute();
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+ $result = $stmt->get_result();
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+
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+ $regions = [];
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+ $total_avg = 0;
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+ $total_orders = 0;
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+
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+ while ($row = $result->fetch_assoc()) {
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+ $regions[] = [
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+ 'countryName' => $row['countryName'],
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+ 'avg_amount' => $row['avg_amount'],
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+ 'order_count' => $row['order_count']
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+ ];
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+
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+ $total_avg += $row['avg_amount'] * $row['order_count'];
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+ $total_orders += $row['order_count'];
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+ }
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+
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+ // 计算全球平均订单金额
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+ $global_avg = $total_orders > 0 ? $total_avg / $total_orders : 0;
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+
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+ return [
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+ 'regions' => $regions,
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+ 'global_avg' => $global_avg
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+ ];
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+}
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+
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+/**
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+ * 获取各地区产品类别偏好
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+ *
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+ * @param mysqli $conn 数据库连接
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+ * @param string $start_date 开始日期
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+ * @param string $end_date 结束日期
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+ * @return array 各地区产品类别偏好数据
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+ */
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+function getRegionCategoryPreferences($conn, $start_date, $end_date) {
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+ $sql = "SELECT
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+ c.countryName,
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+ pc.name as category_name,
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+ SUM(oi.quantity) as total_quantity
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+ FROM orders o
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+ JOIN customer cu ON o.customer_id = cu.id
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+ JOIN country c ON cu.cs_country = c.id
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+ JOIN order_items oi ON o.id = oi.order_id
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+ JOIN products p ON oi.product_id = p.id
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+ JOIN product_categories pc ON p.category_id = pc.id
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+ WHERE o.order_date BETWEEN ? AND ?
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+ GROUP BY cu.cs_country, p.category_id
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+ ORDER BY c.countryName, total_quantity DESC";
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+
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+ $stmt = $conn->prepare($sql);
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+ $stmt->bind_param("ss", $start_date, $end_date);
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+ $stmt->execute();
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+ $result = $stmt->get_result();
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+
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+ $preferences = [];
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+ $current_country = '';
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+ $country_data = [];
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+
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+ while ($row = $result->fetch_assoc()) {
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+ if ($current_country != $row['countryName']) {
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+ if (!empty($current_country)) {
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+ $preferences[$current_country] = $country_data;
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+ }
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+ $current_country = $row['countryName'];
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+ $country_data = [];
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+ }
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+
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+ $country_data[] = [
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+ 'category' => $row['category_name'],
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+ 'quantity' => $row['total_quantity']
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+ ];
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+ }
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+
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+ // 添加最后一个国家的数据
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+ if (!empty($current_country)) {
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+ $preferences[$current_country] = $country_data;
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+ }
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+
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+ // 只保留前5个主要市场
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+ $top_markets = array_slice(array_keys($preferences), 0, 5);
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+ $filtered_preferences = [];
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+
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+ foreach ($top_markets as $market) {
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+ $filtered_preferences[$market] = array_slice($preferences[$market], 0, 5);
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+ }
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+
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+ return $filtered_preferences;
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+}
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+
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+/**
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+ * 获取地区销售增长趋势
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+ *
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+ * @param mysqli $conn 数据库连接
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+ * @param string $start_date 开始日期
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+ * @param string $end_date 结束日期
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+ * @param string $period 时间粒度 (day/week/month)
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+ * @return array 地区销售增长趋势数据
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+ */
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+function getRegionGrowthTrends($conn, $start_date, $end_date, $period = 'month') {
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+ $period_format = getPeriodFormat($period);
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+
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+ $sql = "SELECT
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+ c.countryName,
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+ DATE_FORMAT(o.order_date, ?) as time_period,
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+ SUM(o.total_amount) as total_amount
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+ FROM orders o
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+ JOIN customer cu ON o.customer_id = cu.id
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+ JOIN country c ON cu.cs_country = c.id
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+ WHERE o.order_date BETWEEN ? AND ?
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+ GROUP BY cu.cs_country, time_period
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+ ORDER BY c.countryName, time_period";
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+
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+ $stmt = $conn->prepare($sql);
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+ $stmt->bind_param("sss", $period_format, $start_date, $end_date);
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+ $stmt->execute();
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+ $result = $stmt->get_result();
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+
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+ $trends = [];
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+ $time_periods = [];
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+
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+ while ($row = $result->fetch_assoc()) {
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+ if (!in_array($row['time_period'], $time_periods)) {
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+ $time_periods[] = $row['time_period'];
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+ }
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+
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+ if (!isset($trends[$row['countryName']])) {
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+ $trends[$row['countryName']] = [];
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+ }
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+
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+ $trends[$row['countryName']][$row['time_period']] = $row['total_amount'];
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+ }
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+
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+ // 只保留前5个主要市场
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+ $top_markets = array_slice(array_keys($trends), 0, 5);
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+ $filtered_trends = [];
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+
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+ foreach ($top_markets as $market) {
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+ $filtered_trends[$market] = $trends[$market];
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+ }
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+
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+ return [
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+ 'time_periods' => $time_periods,
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+ 'trends' => $filtered_trends
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+ ];
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+}
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+
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+/**
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+ * 获取地区季节性销售分析
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+ *
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+ * @param mysqli $conn 数据库连接
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+ * @return array 地区季节性销售分析数据
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+ */
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+function getRegionSeasonalAnalysis($conn) {
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+ $sql = "SELECT
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+ c.countryName,
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+ MONTH(o.order_date) as month,
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+ SUM(o.total_amount) as total_amount
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+ FROM orders o
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+ JOIN customer cu ON o.customer_id = cu.id
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+ JOIN country c ON cu.cs_country = c.id
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+ WHERE o.order_date >= DATE_SUB(CURDATE(), INTERVAL 2 YEAR)
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+ GROUP BY cu.cs_country, month
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+ ORDER BY c.countryName, month";
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+
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+ $result = $conn->query($sql);
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+
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+ $seasonal = [];
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+ $months = range(1, 12);
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+
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+ while ($row = $result->fetch_assoc()) {
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+ if (!isset($seasonal[$row['countryName']])) {
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+ $seasonal[$row['countryName']] = array_fill(1, 12, 0);
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+ }
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+
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+ $seasonal[$row['countryName']][$row['month']] += $row['total_amount'];
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+ }
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+
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+ // 只保留前5个主要市场
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+ $top_markets = array_slice(array_keys($seasonal), 0, 5);
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+ $filtered_seasonal = [];
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+
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+ foreach ($top_markets as $market) {
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+ $filtered_seasonal[$market] = array_values($seasonal[$market]);
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+ }
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+
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+ return [
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+ 'months' => ['一月', '二月', '三月', '四月', '五月', '六月', '七月', '八月', '九月', '十月', '十一月', '十二月'],
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+ 'data' => $filtered_seasonal
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+ ];
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+}
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+
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+/**
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+ * 获取地区销售预测数据
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+ *
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+ * @param mysqli $conn 数据库连接
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+ * @param string $start_date 开始日期
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+ * @param string $end_date 结束日期
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+ * @return array 地区销售预测数据
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+ */
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+function getRegionSalesForecast($conn, $start_date, $end_date) {
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+ // 获取过去12个月的销售数据作为基础
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+ $sql = "SELECT
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+ c.countryName,
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+ MONTH(o.order_date) as month,
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+ YEAR(o.order_date) as year,
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+ SUM(o.total_amount) as total_amount
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+ FROM orders o
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+ JOIN customer cu ON o.customer_id = cu.id
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+ JOIN country c ON cu.cs_country = c.id
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+ WHERE o.order_date >= DATE_SUB(CURDATE(), INTERVAL 12 MONTH)
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+ GROUP BY cu.cs_country, year, month
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+ ORDER BY c.countryName, year, month";
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+
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+ $result = $conn->query($sql);
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+
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+ $historical = [];
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+
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+ while ($row = $result->fetch_assoc()) {
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+ $period = $row['year'] . '-' . str_pad($row['month'], 2, '0', STR_PAD_LEFT);
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+
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+ if (!isset($historical[$row['countryName']])) {
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+ $historical[$row['countryName']] = [];
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+ }
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+
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+ $historical[$row['countryName']][$period] = $row['total_amount'];
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+ }
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+
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+ // 生成未来6个月的预测
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+ $forecast = [];
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+ $periods = [];
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+ $current_month = (int)date('m');
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+ $current_year = (int)date('Y');
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+
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+ // 收集所有历史数据点时间
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+ $all_periods = [];
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+ foreach ($historical as $country => $data) {
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+ foreach (array_keys($data) as $period) {
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+ $all_periods[$period] = true;
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+ }
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+ }
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+ $all_periods = array_keys($all_periods);
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+ sort($all_periods);
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+
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+ // 生成未来6个月的预测点
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+ $future_periods = [];
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+ for ($i = 1; $i <= 6; $i++) {
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+ $forecast_month = ($current_month + $i) % 12;
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+ $forecast_month = $forecast_month == 0 ? 12 : $forecast_month;
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+ $forecast_year = $current_year + floor(($current_month + $i - 1) / 12);
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+ $period = $forecast_year . '-' . str_pad($forecast_month, 2, '0', STR_PAD_LEFT);
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+ $future_periods[] = $period;
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+ }
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+
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+ // 合并历史和预测时间点
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+ $all_chart_periods = array_merge($all_periods, $future_periods);
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+
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+ // 只选取主要的5个市场做预测
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+ $top_markets = array_slice(array_keys($historical), 0, 5);
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+ $forecast_data = [];
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+
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+ foreach ($top_markets as $market) {
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+ $forecast_data[$market] = [];
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+
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+ // 为每个市场生成简单的预测
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+ // 这里使用简单的线性增长预测
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+ // 实际应用中可以采用更复杂的时间序列预测算法
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+
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+ // 计算过去几个月的平均增长率
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+ $growth_rate = 0.05; // 默认月度增长率为5%
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+
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+ if (count($historical[$market]) >= 2) {
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+ $values = array_values($historical[$market]);
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+ $start_val = array_shift($values);
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+ $end_val = array_pop($values);
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+
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+ if ($start_val > 0) {
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+ $periods_count = count($historical[$market]) - 1;
|
|
|
+ $total_growth = ($end_val / $start_val) - 1;
|
|
|
+ $growth_rate = pow(1 + $total_growth, 1 / $periods_count) - 1;
|
|
|
+
|
|
|
+ // 限制增长率在合理范围内
|
|
|
+ $growth_rate = max(-0.2, min(0.2, $growth_rate));
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ // 对于历史数据，直接使用实际值
|
|
|
+ foreach ($all_periods as $period) {
|
|
|
+ $forecast_data[$market][$period] = [
|
|
|
+ 'value' => $historical[$market][$period] ?? null,
|
|
|
+ 'is_forecast' => false
|
|
|
+ ];
|
|
|
+ }
|
|
|
+
|
|
|
+ // 对于预测数据，基于最后一个历史数据点和增长率计算
|
|
|
+ $last_period = end($all_periods);
|
|
|
+ $last_value = $historical[$market][$last_period] ?? array_values($historical[$market])[count($historical[$market])-1];
|
|
|
+
|
|
|
+ foreach ($future_periods as $i => $period) {
|
|
|
+ $forecast_value = $last_value * pow(1 + $growth_rate, $i + 1);
|
|
|
+ $forecast_data[$market][$period] = [
|
|
|
+ 'value' => $forecast_value,
|
|
|
+ 'is_forecast' => true
|
|
|
+ ];
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ return [
|
|
|
+ 'periods' => $all_chart_periods,
|
|
|
+ 'forecast' => $forecast_data
|
|
|
+ ];
|
|
|
+}
|
|
|
+
|
|
|
+/**
|
|
|
+ * 渲染平均订单金额分析图表
|
|
|
+ *
|
|
|
+ * @param array $region_data 地区平均订单金额数据
|
|
|
+ * @return void
|
|
|
+ */
|
|
|
+function renderAverageOrderByRegionChart($region_data) {
|
|
|
+ $region_labels = [];
|
|
|
+ $avg_amounts = [];
|
|
|
+ $order_counts = [];
|
|
|
+
|
|
|
+ foreach ($region_data as $region) {
|
|
|
+ $region_labels[] = $region['countryName'];
|
|
|
+ $avg_amounts[] = $region['avg_amount'];
|
|
|
+ $order_counts[] = $region['order_count'];
|
|
|
+ }
|
|
|
+ ?>
|
|
|
+ <div class="chart-header">
|
|
|
+ <h2 class="chart-title">地区平均订单金额分析</h2>
|
|
|
+ </div>
|
|
|
+ <canvas id="avgOrderChart"></canvas>
|
|
|
+
|
|
|
+ <script>
|
|
|
+ // 地区平均订单金额分析图
|
|
|
+ var avgOrderCtx = document.getElementById('avgOrderChart').getContext('2d');
|
|
|
+ var avgOrderChart = new Chart(avgOrderCtx, {
|
|
|
+ type: 'bar',
|
|
|
+ data: {
|
|
|
+ labels: <?php echo json_encode($region_labels); ?>,
|
|
|
+ datasets: [
|
|
|
+ {
|
|
|
+ label: '平均订单金额',
|
|
|
+ data: <?php echo json_encode($avg_amounts); ?>,
|
|
|
+ backgroundColor: 'rgba(75, 192, 192, 0.6)',
|
|
|
+ borderColor: 'rgba(75, 192, 192, 1)',
|
|
|
+ borderWidth: 1,
|
|
|
+ yAxisID: 'y-amount'
|
|
|
+ },
|
|
|
+ {
|
|
|
+ type: 'line',
|
|
|
+ label: '订单数量',
|
|
|
+ data: <?php echo json_encode($order_counts); ?>,
|
|
|
+ backgroundColor: 'rgba(255, 159, 64, 0.6)',
|
|
|
+ borderColor: 'rgba(255, 159, 64, 1)',
|
|
|
+ borderWidth: 2,
|
|
|
+ fill: false,
|
|
|
+ yAxisID: 'y-count'
|
|
|
+ }
|
|
|
+ ]
|
|
|
+ },
|
|
|
+ options: {
|
|
|
+ responsive: true,
|
|
|
+ scales: {
|
|
|
+ x: {
|
|
|
+ title: {
|
|
|
+ display: true,
|
|
|
+ text: '地区'
|
|
|
+ }
|
|
|
+ },
|
|
|
+ 'y-amount': {
|
|
|
+ type: 'linear',
|
|
|
+ position: 'left',
|
|
|
+ title: {
|
|
|
+ display: true,
|
|
|
+ text: '平均订单金额'
|
|
|
+ }
|
|
|
+ },
|
|
|
+ 'y-count': {
|
|
|
+ type: 'linear',
|
|
|
+ position: 'right',
|
|
|
+ title: {
|
|
|
+ display: true,
|
|
|
+ text: '订单数量'
|
|
|
+ },
|
|
|
+ grid: {
|
|
|
+ drawOnChartArea: false
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ });
|
|
|
+ </script>
|
|
|
+ <?php
|
|
|
+}
|
|
|
+
|
|
|
+/**
|
|
|
+ * 渲染地区产品类别偏好图表
|
|
|
+ *
|
|
|
+ * @param array $preferences 地区产品类别偏好数据
|
|
|
+ * @return void
|
|
|
+ */
|
|
|
+function renderRegionCategoryPreferencesChart($preferences) {
|
|
|
+ ?>
|
|
|
+ <div class="chart-header">
|
|
|
+ <h2 class="chart-title">各地区产品类别偏好</h2>
|
|
|
+ </div>
|
|
|
+
|
|
|
+ <div class="row">
|
|
|
+ <?php foreach ($preferences as $country => $categories): ?>
|
|
|
+ <?php
|
|
|
+ $category_labels = [];
|
|
|
+ $category_data = [];
|
|
|
+
|
|
|
+ foreach ($categories as $cat) {
|
|
|
+ $category_labels[] = $cat['category'];
|
|
|
+ $category_data[] = $cat['quantity'];
|
|
|
+ }
|
|
|
+ ?>
|
|
|
+ <div class="col-md-6">
|
|
|
+ <div class="subchart-container">
|
|
|
+ <h3 class="subchart-title"><?php echo $country; ?></h3>
|
|
|
+ <canvas id="categoryChart<?php echo md5($country); ?>"></canvas>
|
|
|
+ </div>
|
|
|
+ </div>
|
|
|
+
|
|
|
+ <script>
|
|
|
+ // <?php echo $country; ?> 产品类别偏好
|
|
|
+ var categoryCtx<?php echo md5($country); ?> = document.getElementById('categoryChart<?php echo md5($country); ?>').getContext('2d');
|
|
|
+ var categoryChart<?php echo md5($country); ?> = new Chart(categoryCtx<?php echo md5($country); ?>, {
|
|
|
+ type: 'doughnut',
|
|
|
+ data: {
|
|
|
+ labels: <?php echo json_encode($category_labels); ?>,
|
|
|
+ datasets: [{
|
|
|
+ data: <?php echo json_encode($category_data); ?>,
|
|
|
+ backgroundColor: [
|
|
|
+ 'rgba(255, 99, 132, 0.7)',
|
|
|
+ 'rgba(54, 162, 235, 0.7)',
|
|
|
+ 'rgba(255, 206, 86, 0.7)',
|
|
|
+ 'rgba(75, 192, 192, 0.7)',
|
|
|
+ 'rgba(153, 102, 255, 0.7)'
|
|
|
+ ],
|
|
|
+ borderWidth: 1
|
|
|
+ }]
|
|
|
+ },
|
|
|
+ options: {
|
|
|
+ responsive: true,
|
|
|
+ plugins: {
|
|
|
+ legend: {
|
|
|
+ position: 'right',
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ });
|
|
|
+ </script>
|
|
|
+ <?php endforeach; ?>
|
|
|
+ </div>
|
|
|
+ <?php
|
|
|
+}
|
|
|
+
|
|
|
+/**
|
|
|
+ * 渲染地区销售增长趋势图表
|
|
|
+ *
|
|
|
+ * @param array $growth_data 地区销售增长趋势数据
|
|
|
+ * @return void
|
|
|
+ */
|
|
|
+function renderRegionGrowthTrendsChart($growth_data) {
|
|
|
+ $time_periods = $growth_data['time_periods'];
|
|
|
+ $trends = $growth_data['trends'];
|
|
|
+
|
|
|
+ $datasets = [];
|
|
|
+ $colors = [
|
|
|
+ ['rgba(255, 99, 132, 0.6)', 'rgba(255, 99, 132, 1)'],
|
|
|
+ ['rgba(54, 162, 235, 0.6)', 'rgba(54, 162, 235, 1)'],
|
|
|
+ ['rgba(255, 206, 86, 0.6)', 'rgba(255, 206, 86, 1)'],
|
|
|
+ ['rgba(75, 192, 192, 0.6)', 'rgba(75, 192, 192, 1)'],
|
|
|
+ ['rgba(153, 102, 255, 0.6)', 'rgba(153, 102, 255, 1)']
|
|
|
+ ];
|
|
|
+
|
|
|
+ $i = 0;
|
|
|
+ foreach ($trends as $country => $data) {
|
|
|
+ $dataset = [
|
|
|
+ 'label' => $country,
|
|
|
+ 'data' => [],
|
|
|
+ 'backgroundColor' => $colors[$i % count($colors)][0],
|
|
|
+ 'borderColor' => $colors[$i % count($colors)][1],
|
|
|
+ 'borderWidth' => 2,
|
|
|
+ 'fill' => false,
|
|
|
+ 'tension' => 0.1
|
|
|
+ ];
|
|
|
+
|
|
|
+ foreach ($time_periods as $period) {
|
|
|
+ $dataset['data'][] = $data[$period] ?? null;
|
|
|
+ }
|
|
|
+
|
|
|
+ $datasets[] = $dataset;
|
|
|
+ $i++;
|
|
|
+ }
|
|
|
+ ?>
|
|
|
+ <div class="chart-header">
|
|
|
+ <h2 class="chart-title">地区销售增长趋势</h2>
|
|
|
+ </div>
|
|
|
+ <canvas id="growthTrendsChart"></canvas>
|
|
|
+
|
|
|
+ <script>
|
|
|
+ // 地区销售增长趋势图
|
|
|
+ var growthTrendsCtx = document.getElementById('growthTrendsChart').getContext('2d');
|
|
|
+ var growthTrendsChart = new Chart(growthTrendsCtx, {
|
|
|
+ type: 'line',
|
|
|
+ data: {
|
|
|
+ labels: <?php echo json_encode($time_periods); ?>,
|
|
|
+ datasets: <?php echo json_encode($datasets); ?>
|
|
|
+ },
|
|
|
+ options: {
|
|
|
+ responsive: true,
|
|
|
+ scales: {
|
|
|
+ x: {
|
|
|
+ title: {
|
|
|
+ display: true,
|
|
|
+ text: '时间段'
|
|
|
+ }
|
|
|
+ },
|
|
|
+ y: {
|
|
|
+ title: {
|
|
|
+ display: true,
|
|
|
+ text: '销售额'
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ });
|
|
|
+ </script>
|
|
|
+ <?php
|
|
|
+}
|
|
|
+
|
|
|
+/**
|
|
|
+ * 渲染地区季节性分析图表
|
|
|
+ *
|
|
|
+ * @param array $seasonal_data 地区季节性分析数据
|
|
|
+ * @return void
|
|
|
+ */
|
|
|
+function renderRegionSeasonalAnalysisChart($seasonal_data) {
|
|
|
+ $months = $seasonal_data['months'];
|
|
|
+ $data = $seasonal_data['data'];
|
|
|
+
|
|
|
+ $datasets = [];
|
|
|
+ $colors = [
|
|
|
+ ['rgba(255, 99, 132, 0.6)', 'rgba(255, 99, 132, 1)'],
|
|
|
+ ['rgba(54, 162, 235, 0.6)', 'rgba(54, 162, 235, 1)'],
|
|
|
+ ['rgba(255, 206, 86, 0.6)', 'rgba(255, 206, 86, 1)'],
|
|
|
+ ['rgba(75, 192, 192, 0.6)', 'rgba(75, 192, 192, 1)'],
|
|
|
+ ['rgba(153, 102, 255, 0.6)', 'rgba(153, 102, 255, 1)']
|
|
|
+ ];
|
|
|
+
|
|
|
+ $i = 0;
|
|
|
+ foreach ($data as $country => $values) {
|
|
|
+ $datasets[] = [
|
|
|
+ 'label' => $country,
|
|
|
+ 'data' => $values,
|
|
|
+ 'backgroundColor' => $colors[$i % count($colors)][0],
|
|
|
+ 'borderColor' => $colors[$i % count($colors)][1],
|
|
|
+ 'borderWidth' => 2,
|
|
|
+ 'fill' => false,
|
|
|
+ 'tension' => 0.1
|
|
|
+ ];
|
|
|
+ $i++;
|
|
|
+ }
|
|
|
+ ?>
|
|
|
+ <div class="chart-header">
|
|
|
+ <h2 class="chart-title">地区季节性销售分析</h2>
|
|
|
+ </div>
|
|
|
+ <canvas id="seasonalAnalysisChart"></canvas>
|
|
|
+
|
|
|
+ <script>
|
|
|
+ // 地区季节性销售分析图
|
|
|
+ var seasonalCtx = document.getElementById('seasonalAnalysisChart').getContext('2d');
|
|
|
+ var seasonalChart = new Chart(seasonalCtx, {
|
|
|
+ type: 'line',
|
|
|
+ data: {
|
|
|
+ labels: <?php echo json_encode($months); ?>,
|
|
|
+ datasets: <?php echo json_encode($datasets); ?>
|
|
|
+ },
|
|
|
+ options: {
|
|
|
+ responsive: true,
|
|
|
+ scales: {
|
|
|
+ x: {
|
|
|
+ title: {
|
|
|
+ display: true,
|
|
|
+ text: '月份'
|
|
|
+ }
|
|
|
+ },
|
|
|
+ y: {
|
|
|
+ title: {
|
|
|
+ display: true,
|
|
|
+ text: '销售额'
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ });
|
|
|
+ </script>
|
|
|
+ <?php
|
|
|
+}
|
|
|
+
|
|
|
+/**
|
|
|
+ * 渲染地区销售预测图表
|
|
|
+ *
|
|
|
+ * @param array $forecast_data 地区销售预测数据
|
|
|
+ * @return void
|
|
|
+ */
|
|
|
+function renderRegionSalesForecastChart($forecast_data) {
|
|
|
+ $periods = $forecast_data['periods'];
|
|
|
+ $forecast = $forecast_data['forecast'];
|
|
|
+
|
|
|
+ $datasets = [];
|
|
|
+ $colors = [
|
|
|
+ ['rgba(255, 99, 132, 0.6)', 'rgba(255, 99, 132, 1)'],
|
|
|
+ ['rgba(54, 162, 235, 0.6)', 'rgba(54, 162, 235, 1)'],
|
|
|
+ ['rgba(255, 206, 86, 0.6)', 'rgba(255, 206, 86, 1)'],
|
|
|
+ ['rgba(75, 192, 192, 0.6)', 'rgba(75, 192, 192, 1)'],
|
|
|
+ ['rgba(153, 102, 255, 0.6)', 'rgba(153, 102, 255, 1)']
|
|
|
+ ];
|
|
|
+
|
|
|
+ $i = 0;
|
|
|
+ foreach ($forecast as $country => $data) {
|
|
|
+ $historical_data = [];
|
|
|
+ $forecast_data = [];
|
|
|
+
|
|
|
+ foreach ($periods as $period) {
|
|
|
+ if (isset($data[$period])) {
|
|
|
+ if ($data[$period]['is_forecast']) {
|
|
|
+ $historical_data[] = null;
|
|
|
+ $forecast_data[] = $data[$period]['value'];
|
|
|
+ } else {
|
|
|
+ $historical_data[] = $data[$period]['value'];
|
|
|
+ $forecast_data[] = null;
|
|
|
+ }
|
|
|
+ } else {
|
|
|
+ $historical_data[] = null;
|
|
|
+ $forecast_data[] = null;
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ $datasets[] = [
|
|
|
+ 'label' => $country . ' (历史)',
|
|
|
+ 'data' => $historical_data,
|
|
|
+ 'backgroundColor' => $colors[$i % count($colors)][0],
|
|
|
+ 'borderColor' => $colors[$i % count($colors)][1],
|
|
|
+ 'borderWidth' => 2,
|
|
|
+ 'fill' => false
|
|
|
+ ];
|
|
|
+
|
|
|
+ $datasets[] = [
|
|
|
+ 'label' => $country . ' (预测)',
|
|
|
+ 'data' => $forecast_data,
|
|
|
+ 'backgroundColor' => $colors[$i % count($colors)][0],
|
|
|
+ 'borderColor' => $colors[$i % count($colors)][1],
|
|
|
+ 'borderWidth' => 2,
|
|
|
+ 'borderDash' => [5, 5],
|
|
|
+ 'fill' => false
|
|
|
+ ];
|
|
|
+
|
|
|
+ $i++;
|
|
|
+ }
|
|
|
+ ?>
|
|
|
+ <div class="chart-header">
|
|
|
+ <h2 class="chart-title">地区销售预测 (未来6个月)</h2>
|
|
|
+ </div>
|
|
|
+ <canvas id="forecastChart"></canvas>
|
|
|
+
|
|
|
+ <script>
|
|
|
+ // 地区销售预测图
|
|
|
+ var forecastCtx = document.getElementById('forecastChart').getContext('2d');
|
|
|
+ var forecastChart = new Chart(forecastCtx, {
|
|
|
+ type: 'line',
|
|
|
+ data: {
|
|
|
+ labels: <?php echo json_encode($periods); ?>,
|
|
|
+ datasets: <?php echo json_encode($datasets); ?>
|
|
|
+ },
|
|
|
+ options: {
|
|
|
+ responsive: true,
|
|
|
+ scales: {
|
|
|
+ x: {
|
|
|
+ title: {
|
|
|
+ display: true,
|
|
|
+ text: '时间段'
|
|
|
+ }
|
|
|
+ },
|
|
|
+ y: {
|
|
|
+ title: {
|
|
|
+ display: true,
|
|
|
+ text: '销售额'
|
|
|
+ }
|
|
|
+ }
|
|
|
+ },
|
|
|
+ plugins: {
|
|
|
+ tooltip: {
|
|
|
+ callbacks: {
|
|
|
+ title: function(tooltipItems) {
|
|
|
+ return tooltipItems[0].label;
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ });
|
|
|
+ </script>
|
|
|
+ <?php
|
|
|
}
|
igb