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package cn.iocoder.yudao.module.iot.util;
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import java.util.*;
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import java.util.stream.Collectors;
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import java.util.DoubleSummaryStatistics;
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import java.text.DecimalFormat;
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import java.math.BigDecimal;
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import java.math.RoundingMode;
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public class MapListStatsCalculator {
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// 默认保留小数位数
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private static final int DEFAULT_SCALE = 2;
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/**
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* 获取指定key列表的最大值（四舍五入）
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*/
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public static Map<String, Double> getMaxValues(List<Map<String, Object>> dataList, List<String> keys) {
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return getMaxValues(dataList, keys, DEFAULT_SCALE);
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}
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public static Map<String, Double> getMaxValues(List<Map<String, Object>> dataList, List<String> keys, int scale) {
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return keys.stream()
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.collect(Collectors.toMap(
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key -> key,
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key -> {
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OptionalDouble max = dataList.stream()
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.filter(map -> map.containsKey(key) && map.get(key) != null)
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.mapToDouble(map -> convertToDouble(map.get(key)))
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.max();
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return roundValue(max.orElse(Double.NaN), scale);
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}
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));
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}
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/**
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* 获取指定key列表的最小值（四舍五入）
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*/
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public static Map<String, Double> getMinValues(List<Map<String, Object>> dataList, List<String> keys) {
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return getMinValues(dataList, keys, DEFAULT_SCALE);
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}
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public static Map<String, Double> getMinValues(List<Map<String, Object>> dataList, List<String> keys, int scale) {
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return keys.stream()
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.collect(Collectors.toMap(
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key -> key,
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key -> {
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OptionalDouble min = dataList.stream()
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.filter(map -> map.containsKey(key) && map.get(key) != null)
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.mapToDouble(map -> convertToDouble(map.get(key)))
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.min();
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return roundValue(min.orElse(Double.NaN), scale);
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}
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));
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}
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/**
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* 获取指定key列表的平均值（四舍五入）
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*/
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public static Map<String, Double> getAvgValues(List<Map<String, Object>> dataList, List<String> keys) {
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return getAvgValues(dataList, keys, DEFAULT_SCALE);
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}
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public static Map<String, Double> getAvgValues(List<Map<String, Object>> dataList, List<String> keys, int scale) {
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return keys.stream()
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.collect(Collectors.toMap(
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key -> key,
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key -> {
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OptionalDouble avg = dataList.stream()
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.filter(map -> map.containsKey(key) && map.get(key) != null)
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.mapToDouble(map -> convertToDouble(map.get(key)))
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.average();
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return roundValue(avg.orElse(Double.NaN), scale);
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}
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));
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}
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/**
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* 获取指定key列表的最大值与最小值相差（四舍五入）
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*/
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public static Map<String, Double> getRangeValues(List<Map<String, Object>> dataList, List<String> keys) {
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return getRangeValues(dataList, keys, DEFAULT_SCALE);
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}
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public static Map<String, Double> getRangeValues(List<Map<String, Object>> dataList, List<String> keys, int scale) {
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return keys.stream()
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.collect(Collectors.toMap(
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key -> key,
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key -> {
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DoubleSummaryStatistics stats = dataList.stream()
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.filter(map -> map.containsKey(key) && map.get(key) != null)
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.mapToDouble(map -> convertToDouble(map.get(key)))
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.summaryStatistics();
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double range = stats.getCount() > 0 ? stats.getMax() - stats.getMin() : 0.0;
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return roundValue(range, scale);
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}
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));
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}
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/**
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* 一次性获取所有统计信息（四舍五入）
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*/
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public static Map<String, Map<String, Double>> getAllStats(List<Map<String, Object>> dataList, List<String> keys) {
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return getAllStats(dataList, keys, DEFAULT_SCALE);
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}
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public static Map<String, Map<String, Double>> getAllStats(List<Map<String, Object>> dataList, List<String> keys, int scale) {
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return keys.stream()
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.collect(Collectors.toMap(
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key -> key,
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key -> {
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DoubleSummaryStatistics stats = dataList.stream()
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.filter(map -> map.containsKey(key) && map.get(key) != null)
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.mapToDouble(map -> convertToDouble(map.get(key)))
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.summaryStatistics();
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Map<String, Double> result = new HashMap<>();
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result.put("max", roundValue(stats.getCount() > 0 ? stats.getMax() : 0.0, scale));
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result.put("min", roundValue(stats.getCount() > 0 ? stats.getMin() : 0.0, scale));
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result.put("avg", roundValue(stats.getCount() > 0 ? stats.getAverage() : 0.0, scale));
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result.put("range", roundValue(stats.getCount() > 0 ? stats.getMax() - stats.getMin() : 0.0, scale));
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result.put("count", (double) stats.getCount()); // 数量保持整数
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result.put("sum", roundValue(stats.getSum(), scale));
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return result;
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}
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));
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}
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/**
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* 对象转换为Double
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*/
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private static double convertToDouble(Object value) {
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if (value == null) {
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return 0.0;
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}
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if (value instanceof Number) {
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return ((Number) value).doubleValue();
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}
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if (value instanceof String) {
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try {
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return Double.parseDouble(value.toString().trim());
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} catch (NumberFormatException e) {
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return 0.0;
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}
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}
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if (value instanceof Boolean) {
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return (Boolean) value ? 1.0 : 0.0;
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}
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return 0.0;
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}
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/**
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* 四舍五入方法 - 使用BigDecimal（最准确）
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*/
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public static double roundValue(double value, int scale) {
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if (Double.isNaN(value) || Double.isInfinite(value)) {
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return value;
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}
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return BigDecimal.valueOf(value)
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.setScale(scale, RoundingMode.HALF_UP)
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.doubleValue();
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}
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/**
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* 四舍五入方法 - 使用DecimalFormat（格式化输出）
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*/
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public static String roundValueToString(double value, int scale) {
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if (Double.isNaN(value)) {
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return "NaN";
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}
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if (Double.isInfinite(value)) {
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return value > 0 ? "Infinity" : "-Infinity";
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}
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// 构建格式字符串
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StringBuilder pattern = new StringBuilder("0");
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if (scale > 0) {
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pattern.append(".");
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for (int i = 0; i < scale; i++) {
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pattern.append("0");
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}
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}
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DecimalFormat df = new DecimalFormat(pattern.toString());
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df.setRoundingMode(RoundingMode.HALF_UP);
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return df.format(value);
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}
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/**
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* 格式化数字为字符串，自动去除末尾的0
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*/
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public static String formatValue(double value, int maxScale) {
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if (Double.isNaN(value) || Double.isInfinite(value)) {
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return String.valueOf(value);
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}
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// 先四舍五入
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double rounded = roundValue(value, maxScale);
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// 转换为字符串，去除末尾的0
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String str = String.valueOf(rounded);
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if (str.contains(".")) {
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str = str.replaceAll("0*$", "").replaceAll("\\.$", "");
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}
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return str;
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}
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/**
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* 获取统计信息（字符串格式，已四舍五入）
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*/
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public static Map<String, Map<String, String>> getAllStatsAsString(
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List<Map<String, Object>> dataList,
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List<String> keys,
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int scale) {
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return keys.stream()
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.collect(Collectors.toMap(
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key -> key,
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key -> {
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DoubleSummaryStatistics stats = dataList.stream()
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.filter(map -> map.containsKey(key) && map.get(key) != null)
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.mapToDouble(map -> convertToDouble(map.get(key)))
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.summaryStatistics();
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Map<String, String> result = new HashMap<>();
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result.put("max", roundValueToString(stats.getCount() > 0 ? stats.getMax() : 0.0, scale));
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result.put("min", roundValueToString(stats.getCount() > 0 ? stats.getMin() : 0.0, scale));
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result.put("avg", roundValueToString(stats.getCount() > 0 ? stats.getAverage() : 0.0, scale));
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result.put("range", roundValueToString(stats.getCount() > 0 ? stats.getMax() - stats.getMin() : 0.0, scale));
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result.put("count", String.valueOf(stats.getCount()));
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result.put("sum", roundValueToString(stats.getSum(), scale));
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return result;
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}
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));
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}
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/**
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* 使用示例
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*/
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public static void main(String[] args) {
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// 创建测试数据
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List<Map<String, Object>> dataList = new ArrayList<>();
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Map<String, Object> map1 = new HashMap<>();
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map1.put("temperature", 25.56789);
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map1.put("humidity", 60.12345);
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map1.put("pressure", 100.23456);
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dataList.add(map1);
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Map<String, Object> map2 = new HashMap<>();
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map2.put("temperature", 28.33333);
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map2.put("humidity", 55.55555);
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map2.put("pressure", 102.77777);
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dataList.add(map2);
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Map<String, Object> map3 = new HashMap<>();
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map3.put("temperature", 22.11111);
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map3.put("humidity", 65.99999);
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map3.put("pressure", 98.65432);
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dataList.add(map3);
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// 要统计的key
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List<String> keys = Arrays.asList("temperature", "humidity", "pressure");
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System.out.println("=== 默认保留2位小数 ===");
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Map<String, Map<String, Double>> allStats = getAllStats(dataList, keys);
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printStats(allStats);
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System.out.println("\n=== 保留3位小数 ===");
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Map<String, Map<String, Double>> stats3 = getAllStats(dataList, keys, 3);
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printStats(stats3);
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System.out.println("\n=== 字符串格式（保留2位小数）===");
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Map<String, Map<String, String>> stringStats = getAllStatsAsString(dataList, keys, 2);
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printStringStats(stringStats);
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System.out.println("\n=== 单独使用四舍五入方法 ===");
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double testValue = 123.456789;
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System.out.println("原始值: " + testValue);
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System.out.println("保留0位: " + roundValue(testValue, 0));
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System.out.println("保留2位: " + roundValue(testValue, 2));
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System.out.println("保留4位: " + roundValue(testValue, 4));
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System.out.println("格式化输出: " + roundValueToString(testValue, 2));
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System.out.println("智能格式化: " + formatValue(testValue, 2));
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}
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private static void printStats(Map<String, Map<String, Double>> stats) {
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for (Map.Entry<String, Map<String, Double>> entry : stats.entrySet()) {
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System.out.println("\n列: " + entry.getKey());
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Map<String, Double> colStats = entry.getValue();
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System.out.printf(" 最大值: %.4f%n", colStats.get("max"));
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System.out.printf(" 最小值: %.4f%n", colStats.get("min"));
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System.out.printf(" 平均值: %.4f%n", colStats.get("avg"));
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System.out.printf(" 差值: %.4f%n", colStats.get("range"));
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System.out.printf(" 数量: %.0f%n", colStats.get("count"));
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System.out.printf(" 总和: %.4f%n", colStats.get("sum"));
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}
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}
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private static void printStringStats(Map<String, Map<String, String>> stats) {
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for (Map.Entry<String, Map<String, String>> entry : stats.entrySet()) {
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System.out.println("\n列: " + entry.getKey());
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Map<String, String> colStats = entry.getValue();
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System.out.println(" 最大值: " + colStats.get("max"));
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System.out.println(" 最小值: " + colStats.get("min"));
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System.out.println(" 平均值: " + colStats.get("avg"));
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System.out.println(" 差值: " + colStats.get("range"));
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System.out.println(" 数量: " + colStats.get("count"));
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System.out.println(" 总和: " + colStats.get("sum"));
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}
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|
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}
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}
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liutao
1 week ago