blame | history | patch | commit | commitdiff | ignore whitespace
jinpengyong
2023-11-01 77fb7786036fd4c7dd16b9b15c6569cdf2d8ba19 
 screen-api/src/main/java/com/moral/api/service/impl/ProfessionServiceImpl.java


@@ -6,14 +6,7 @@


import org.springframework.util.ObjectUtils;




import java.text.NumberFormat;


import java.util.ArrayList;


import java.util.Arrays;


import java.util.Collections;


import java.util.HashMap;


import java.util.HashSet;


import java.util.List;


import java.util.Map;


import java.util.Set;


import java.util.*;


import java.util.stream.Collectors;




import com.alibaba.fastjson.JSONObject;


@@ -86,7 +79,7 @@


    @Autowired


    private SensorService sensorService;




    private static Map<String, String> senorMap = new HashMap<>();


    private static final Map<String, String> senorMap = new HashMap<>();




    static {


        senorMap.put(Constants.SENSOR_CODE_PM25, "PM2_5");


@@ -103,8 +96,10 @@


        List<Map<String, Object>> devices = deviceService.getDevicesByOrganizationId(organizationId);


        Set<Map<String, Object>> result = new HashSet<>();


        for (Map<String, Object> device : devices) {


            List<Map<String, Object>> professions = (List<Map<String, Object>>) device.get("professions");


            result.addAll(professions);


            if(Objects.nonNull(device)&&Objects.nonNull(device.get("professions"))&&device.containsKey("professions")){


                List<Map<String, Object>> professions = (List<Map<String, Object>>) device.get("professions");


                result.addAll(professions);


            }


        }


        return result;


    }


@@ -149,13 +144,13 @@


    }




    @Override


    public List<Map<String, Object>> professionContribution(Map<String, Object> params) {


    public Map<String, Object> professionContribution(Map<String, Object> params) {


        int orgId = Integer.parseInt(params.get("organizationId").toString());


        List<String> professions = Arrays.asList(params.get("professions").toString().split(","));


        String type = params.get("type").toString();


        String time = params.get("time").toString();


        String sensorCode = params.get("sensorCode").toString();


        List<Map<String, Object>> result = new ArrayList<>();


        Map<String, Object> result = new HashMap<>();




        switch (type) {


            case "year":


@@ -174,8 +169,13 @@


    }




    //贡献率，年


    private List<Map<String, Object>> professionContributionOfYear(Integer orgId, List<String> professions, String time, String sensorCode) {


        List<Map<String, Object>> result = new ArrayList<>();


    private Map<String, Object> professionContributionOfYear(Integer orgId, List<String> professions, String time, String sensorCode) {


        Map<String, Object> result = new HashMap<>();




        //1.时间信息结果


        List<String> timeLag = DateUtils.getTimeLag(time);


        result.put("time", timeLag);






        //根据组织获取区域定位


        QueryWrapper<Organization> organizationQueryWrapper = new QueryWrapper<>();


@@ -183,10 +183,6 @@


                .eq("id", orgId);


        Integer locationLevelCode = organizationService.getOne(organizationQueryWrapper).getLocationLevelCode();




        //该组织所有设备信息


        List<String> allMacs = deviceService.getMacsByOrganizationId(orgId);




        List<String> timeLag = DateUtils.getTimeLag(time);




        //本市本年所有月数据


        QueryWrapper<CityAqiMonthly> cityAqiMonthlyQueryWrapper = new QueryWrapper<>();


@@ -202,25 +198,26 @@


        }






        //所有设备本年所有月数据


        //该组织所有设备信息，本年所有月数据


        List<String> allMacs = deviceService.getMacsByOrganizationId(orgId);


        List<HistoryMonthly> allDeviceData = historyMonthlyService.getValueByMacs(allMacs, time);


        //按time分组


        Map<String, List<HistoryMonthly>> allDeviceDataMap = allDeviceData.stream()


                .collect(Collectors.groupingBy(o -> DateUtils.dateToDateString(o.getTime()).substring(0, 7)));






        //本市数据结果集


        Map<String, Object> resultCityDataMap = new HashMap<>();


        List<Map<String, Object>> cityDataList = new ArrayList<>();


        //所有设备每个时间点，和值


        Map<String, Object> allDeviceSumMap = new HashMap<>();


        for (String yearMonth : timeLag) {


            Map<String, Object> resultMap = new HashMap<>();


            resultMap.put("time", yearMonth);






            //所有设备该因子累加值


            Double allDeviceSum = null;


            List<HistoryMonthly> historyMonthlyList = allDeviceDataMap.get(yearMonth);


            if (!ObjectUtils.isEmpty(historyMonthlyList)) {


                allDeviceSum = historyMonthlyService.calculatedValue(historyMonthlyList, sensorCode, "sum");


            }


            resultMap.put("allDeviceSum", allDeviceSum);


            allDeviceSumMap.put(yearMonth, allDeviceSum);






            //本市值


@@ -230,14 +227,26 @@


                //判断城市aqi是否有该因子数据


                String sensorName = senorMap.get(sensorCode);


                if (sensorName != null) {


                    cityValue = (Double) dataValue.get(sensorName);


                    cityValue = Double.parseDouble(dataValue.get(sensorName).toString());


                }


            }


            resultMap.put("cityValue", cityValue);


            result.add(resultMap);


            Map<String, Object> cityDataMap = new HashMap<>();


            //本市数据


            cityDataMap.put("value", cityValue);


            cityDataList.add(cityDataMap);


        }




        //2.本市数据结果


        resultCityDataMap.put("data", cityDataList);


        result.put("本市", resultCityDataMap);






        for (String profession : professions) {


            //每个行业数据结果集


            HashMap<String, Object> professionMap = new HashMap<>();


            List<Map<String, Object>> dataList = new ArrayList<>();






            //查询行业名称


            String professionName = null;


            Map<String, Object> dictData = (Map<String, Object>) redisTemplate.opsForValue().get(RedisConstants.DICT_DATA_KEY);


@@ -250,62 +259,66 @@


            }






            //获取该行业设备


            //获取该行业所有设备信息，年所有月数据


            List<Device> professionDevices = getDevicesOfProfessions(orgId, Collections.singletonList(profession));


            List<String> professionMacs = professionDevices.stream().map(Device::getMac).collect(Collectors.toList());






            //该行业设备本年所有月数据


            List<HistoryMonthly> professionDeviceData = historyMonthlyService.getValueByMacs(professionMacs, time);


            //按time分组


            Map<String, List<HistoryMonthly>> professionDataMap = professionDeviceData.stream()


                    .collect(Collectors.groupingBy(o -> DateUtils.dateToDateString(o.getTime()).substring(0, 7)));






            for (Map<String, Object> map : result) {


                Object allDeviceSum = map.get("allDeviceSum");


                String resultTime = map.get("time").toString();


                List<HistoryMonthly> historyMonthlyList = professionDataMap.get(resultTime);


            for (String resultTime : timeLag) {


                //每个时间点数据


                Map<String, Object> timeDataMap = new HashMap<>();


                Object o = allDeviceSumMap.get(resultTime);


                Double allDeviceSum = null;


                if (o != null) {


                    allDeviceSum = Double.parseDouble(o.toString());


                }




                List<HistoryMonthly> professionDeviceHistoryMonthlyList = professionDataMap.get(resultTime);


                //贡献率


                String contributionRate = null;


                Double professionAvg = null;


                if (!ObjectUtils.isEmpty(historyMonthlyList)) {


                if (!ObjectUtils.isEmpty(professionDeviceHistoryMonthlyList)) {


                    //该行业均值计算


                    professionAvg = historyMonthlyService.calculatedValue(historyMonthlyList, sensorCode, "avg");


                    professionAvg = historyMonthlyService.calculatedValue(professionDeviceHistoryMonthlyList, sensorCode, "avg");


                    //该行业累加值计算


                    Double professionSum = historyMonthlyService.calculatedValue(historyMonthlyList, sensorCode, "sum");


                    Double professionSum = historyMonthlyService.calculatedValue(professionDeviceHistoryMonthlyList, sensorCode, "sum");


                    //行业贡献率计算


                    NumberFormat numberFormat = NumberFormat.getInstance();


                    numberFormat.setMaximumFractionDigits(2);


                    if (allDeviceSum != null) {


                        contributionRate = numberFormat.format(professionSum / ((Double) allDeviceSum) * 100) + "%";


                    if (allDeviceSum != null && allDeviceSum != 0d) {


                        contributionRate = numberFormat.format(professionSum / (allDeviceSum) * 100) + "%";


                    }


                }


                Map<String, Object> professionMap = new HashMap<>();


                professionMap.put("contributionRate", contributionRate);


                professionMap.put("value", professionAvg == null ? null : AmendUtils.sciCal(professionAvg, 0));


                map.put(professionName, professionMap);




                //行业均值


                timeDataMap.put("value", professionAvg == null ? null : AmendUtils.sciCal(professionAvg, 0));


                //贡献率


                timeDataMap.put("name", contributionRate);


                dataList.add(timeDataMap);


            }


            professionMap.put("data", dataList);


            result.put(professionName, professionMap);


        }


        result.forEach(map -> map.remove("allDeviceSum"));


        return result;


    }




    //贡献率，月


    private List<Map<String, Object>> professionContributionOfMonth(Integer orgId, List<String> professions, String time, String sensorCode) {


        List<Map<String, Object>> result = new ArrayList<>();


    private Map<String, Object> professionContributionOfMonth(Integer orgId, List<String> professions, String time, String sensorCode) {


        Map<String, Object> result = new HashMap<>();




        //1.时间信息结果


        List<String> timeLag = DateUtils.getTimeLag(time);


        result.put("time", timeLag);






        //根据组织获取区域定位


        QueryWrapper<Organization> organizationQueryWrapper = new QueryWrapper<>();


        organizationQueryWrapper.select("location_level_code")


                .eq("id", orgId);


        Integer locationLevelCode = organizationService.getOne(organizationQueryWrapper).getLocationLevelCode();




        //该组织所有设备信息


        List<String> allMacs = deviceService.getMacsByOrganizationId(orgId);




        //日时间点


        List<String> timeLag = DateUtils.getTimeLag(time);






        //本市本月所有日数据


@@ -322,24 +335,26 @@


        }






        //所有设备本月所有日数据


        //该组织所有设备信息，本月所有日数据


        List<String> allMacs = deviceService.getMacsByOrganizationId(orgId);


        List<HistoryDaily> allDeviceData = historyDailyService.getValueByMacs(allMacs, time);


        //按time分组


        Map<String, List<HistoryDaily>> allDeviceDataMap = allDeviceData.stream()


                .collect(Collectors.groupingBy(o -> DateUtils.dateToDateString(o.getTime()).substring(0, 10)));






        //本市数据结果集


        Map<String, Object> resultCityDataMap = new HashMap<>();


        List<Map<String, Object>> cityDataList = new ArrayList<>();


        //所有设备每个时间点，和值


        Map<String, Object> allDeviceSumMap = new HashMap<>();


        for (String yearMonthDay : timeLag) {


            Map<String, Object> resultMap = new HashMap<>();


            resultMap.put("time", yearMonthDay);




            //所有设备该因子累加值


            Double allDeviceSum = null;


            List<HistoryDaily> historyDailyList = allDeviceDataMap.get(yearMonthDay);


            if (!ObjectUtils.isEmpty(historyDailyList)) {


                allDeviceSum = historyDailyService.calculatedValue(historyDailyList, sensorCode, "sum");


            }


            resultMap.put("allDeviceSum", allDeviceSum);


            allDeviceSumMap.put(yearMonthDay, allDeviceSum);






            //本市值


@@ -349,14 +364,27 @@


                //判断城市aqi是否有该因子数据


                String sensorName = senorMap.get(sensorCode);


                if (sensorName != null) {


                    cityValue = (Double) dataValue.get(sensorName);


                    cityValue = Double.parseDouble(dataValue.get(sensorName).toString());


                }


            }


            resultMap.put("cityValue", cityValue);


            result.add(resultMap);


            Map<String, Object> cityDataMap = new HashMap<>();


            //本市数据


            cityDataMap.put("value", cityValue);


            cityDataList.add(cityDataMap);


        }




        //2.本市数据结果


        resultCityDataMap.put("data", cityDataList);


        result.put("本市", resultCityDataMap);






        for (String profession : professions) {


            //每个行业数据结果集


            HashMap<String, Object> professionMap = new HashMap<>();


            List<Map<String, Object>> dataList = new ArrayList<>();






            //查询行业名称


            String professionName = null;


            Map<String, Object> dictData = (Map<String, Object>) redisTemplate.opsForValue().get(RedisConstants.DICT_DATA_KEY);


            List<SysDictData> professionInfo = (List<SysDictData>) dictData.get("profession");


@@ -367,49 +395,60 @@


                }


            }




            //获取该行业设备




            //获取该行业所有设备信息，年所有月数据


            List<Device> professionDevices = getDevicesOfProfessions(orgId, Collections.singletonList(profession));


            List<String> professionMacs = professionDevices.stream().map(Device::getMac).collect(Collectors.toList());






            //该行业设备本月所有日数据


            List<HistoryDaily> professionDeviceData = historyDailyService.getValueByMacs(professionMacs, time);


            //按time分组


            Map<String, List<HistoryDaily>> professionDataMap = professionDeviceData.stream()


                    .collect(Collectors.groupingBy(o -> DateUtils.dateToDateString(o.getTime()).substring(0, 10)));






            for (Map<String, Object> map : result) {


                Object allDeviceSum = map.get("allDeviceSum");


                String resultTime = map.get("time").toString();


                List<HistoryDaily> historyDailyList = professionDataMap.get(resultTime);


            for (String resultTime : timeLag) {


                //每个时间点数据


                Map<String, Object> timeDataMap = new HashMap<>();


                Object o = allDeviceSumMap.get(resultTime);


                Double allDeviceSum = null;


                if (o != null) {


                    allDeviceSum = Double.parseDouble(o.toString());


                }




                List<HistoryDaily> preofessionDeviceHistoryDailyList = professionDataMap.get(resultTime);


                //贡献率


                String contributionRate = null;


                Double professionAvg = null;


                if (!ObjectUtils.isEmpty(historyDailyList)) {


                if (!ObjectUtils.isEmpty(preofessionDeviceHistoryDailyList)) {


                    //该行业均值计算


                    professionAvg = historyDailyService.calculatedValue(historyDailyList, sensorCode, "avg");


                    professionAvg = historyDailyService.calculatedValue(preofessionDeviceHistoryDailyList, sensorCode, "avg");


                    //该行业累加值计算


                    Double professionSum = historyDailyService.calculatedValue(historyDailyList, sensorCode, "sum");


                    Double professionSum = historyDailyService.calculatedValue(preofessionDeviceHistoryDailyList, sensorCode, "sum");


                    //行业贡献率计算


                    NumberFormat numberFormat = NumberFormat.getInstance();


                    numberFormat.setMaximumFractionDigits(2);


                    if (allDeviceSum != null) {


                        contributionRate = numberFormat.format(professionSum / ((Double) allDeviceSum) * 100) + "%";


                    if (allDeviceSum != null && allDeviceSum != 0d) {


                        contributionRate = numberFormat.format(professionSum / (allDeviceSum) * 100) + "%";


                    }


                }


                Map<String, Object> professionMap = new HashMap<>();


                professionMap.put("contributionRate", contributionRate);


                professionMap.put("value", professionAvg == null ? null : AmendUtils.sciCal(professionAvg, 0));


                map.put(professionName, professionMap);




                //行业均值


                timeDataMap.put("value", professionAvg == null ? null : AmendUtils.sciCal(professionAvg, 0));


                //贡献率


                timeDataMap.put("name", contributionRate);


                dataList.add(timeDataMap);


            }


            professionMap.put("data", dataList);


            result.put(professionName, professionMap);


        }


        result.forEach(map -> map.remove("allDeviceSum"));


        return result;


    }




    private List<Map<String, Object>> professionContributionOfDay(Integer orgId, List<String> professions, String time, String sensorCode) {


        List<Map<String, Object>> result = new ArrayList<>();


    private Map<String, Object> professionContributionOfDay(Integer orgId, List<String> professions, String time, String sensorCode) {


        Map<String, Object> result = new HashMap<>();




        //1.时间信息结果


        List<String> timeLag = DateUtils.getTimeLag(time);


        result.put("time", timeLag);






        //根据组织获取区域定位


        QueryWrapper<Organization> organizationQueryWrapper = new QueryWrapper<>();


@@ -421,14 +460,12 @@


        QueryWrapper<Sensor> sensorQueryWrapper = new QueryWrapper<>();


        sensorQueryWrapper.select("lower", "upper").eq("code", sensorCode);


        Sensor sensor = sensorService.getOne(sensorQueryWrapper);


        Double sensorLower = sensor.getLower();


        Double sensorUpper = sensor.getUpper();




        //该组织所有设备信息


        List<String> allMacs = deviceService.getMacsByOrganizationId(orgId);




        //小时时间点


        List<String> timeLag = DateUtils.getTimeLag(time);


        Double sensorLower = null;


        Double sensorUpper = null;


        if (sensor != null) {


            sensorLower = sensor.getLower();


            sensorUpper = sensor.getUpper();


        }






        //本市本日所有小时数据


@@ -445,25 +482,26 @@


        }






        //所有设备本日所有小时数据


        //该组织所有设备信息，本日所有小时数据


        List<String> allMacs = deviceService.getMacsByOrganizationId(orgId);


        List<HistoryHourly> allDeviceData = historyHourlyService.getValueByMacs(allMacs, time);


        //按time分组


        Map<String, List<HistoryHourly>> allDeviceDataMap = allDeviceData.stream()


                .collect(Collectors.groupingBy(o -> DateUtils.dateToDateString(o.getTime()).substring(0, 13)));






        //本市数据结果集


        Map<String, Object> resultCityDataMap = new HashMap<>();


        List<Map<String, Object>> cityDataList = new ArrayList<>();


        //所有设备每个时间点，和值


        Map<String, Object> allDeviceSumMap = new HashMap<>();


        for (String yearMonthDayHour : timeLag) {


            Map<String, Object> resultMap = new HashMap<>();


            resultMap.put("time", yearMonthDayHour);






            //所有设备该因子累加值


            Double allDeviceSum = null;


            List<HistoryHourly> historyHourlyList = allDeviceDataMap.get(yearMonthDayHour);


            if (!ObjectUtils.isEmpty(historyHourlyList)) {


                allDeviceSum = historyHourlyService.calculatedValue(historyHourlyList, sensorCode, "sum", sensorLower, sensorUpper);


            }


            resultMap.put("allDeviceSum", allDeviceSum);


            allDeviceSumMap.put(yearMonthDayHour, allDeviceSum);






            //本市值


@@ -473,14 +511,27 @@


                //判断城市aqi是否有该因子数据


                String sensorName = senorMap.get(sensorCode);


                if (sensorName != null) {


                    cityValue = (Double) dataValue.get(sensorName);


                    cityValue = Double.parseDouble(dataValue.get(sensorName).toString());


                }


            }


            resultMap.put("cityValue", cityValue);


            result.add(resultMap);


            Map<String, Object> cityDataMap = new HashMap<>();


            //本市数据


            cityDataMap.put("value", cityValue);


            cityDataList.add(cityDataMap);


        }




        //2.本市数据结果


        resultCityDataMap.put("data", cityDataList);


        result.put("本市", resultCityDataMap);






        for (String profession : professions) {


            //每个行业数据结果集


            HashMap<String, Object> professionMap = new HashMap<>();


            List<Map<String, Object>> dataList = new ArrayList<>();






            //查询行业名称


            String professionName = null;


            Map<String, Object> dictData = (Map<String, Object>) redisTemplate.opsForValue().get(RedisConstants.DICT_DATA_KEY);


            List<SysDictData> professionInfo = (List<SysDictData>) dictData.get("profession");


@@ -491,44 +542,50 @@


                }


            }




            //获取该行业设备




            //获取该行业所有设备信息，年所有月数据


            List<Device> professionDevices = getDevicesOfProfessions(orgId, Collections.singletonList(profession));


            List<String> professionMacs = professionDevices.stream().map(Device::getMac).collect(Collectors.toList());






            //该行业设备本日所有小时数据


            List<HistoryHourly> professionDeviceData = historyHourlyService.getValueByMacs(professionMacs, time);


            //按time分组


            Map<String, List<HistoryHourly>> professionDataMap = professionDeviceData.stream()


                    .collect(Collectors.groupingBy(o -> DateUtils.dateToDateString(o.getTime()).substring(0, 13)));






            for (Map<String, Object> map : result) {


                Object allDeviceSum = map.get("allDeviceSum");


                String resultTime = map.get("time").toString();


                List<HistoryHourly> historyHourlyList = professionDataMap.get(resultTime);


            for (String resultTime : timeLag) {


                //每个时间点数据


                Map<String, Object> timeDataMap = new HashMap<>();


                Object o = allDeviceSumMap.get(resultTime);


                Double allDeviceSum = null;


                if (o != null) {


                    allDeviceSum = Double.parseDouble(o.toString());


                }




                List<HistoryHourly> preofessionDeviceHistoryHourlyList = professionDataMap.get(resultTime);


                //贡献率


                String contributionRate = null;


                Double professionAvg = null;


                if (!ObjectUtils.isEmpty(historyHourlyList)) {


                if (!ObjectUtils.isEmpty(preofessionDeviceHistoryHourlyList)) {


                    //该行业均值计算


                    professionAvg = historyHourlyService.calculatedValue(historyHourlyList, sensorCode, "avg", sensorLower, sensorUpper);


                    professionAvg = historyHourlyService.calculatedValue(preofessionDeviceHistoryHourlyList, sensorCode, "avg", sensorLower, sensorUpper);


                    //该行业累加值计算


                    Double professionSum = historyHourlyService.calculatedValue(historyHourlyList, sensorCode, "sum", sensorLower, sensorUpper);


                    Double professionSum = historyHourlyService.calculatedValue(preofessionDeviceHistoryHourlyList, sensorCode, "sum", sensorLower, sensorUpper);


                    //行业贡献率计算


                    NumberFormat numberFormat = NumberFormat.getInstance();


                    numberFormat.setMaximumFractionDigits(2);


                    if (allDeviceSum != null) {


                        contributionRate = numberFormat.format(professionSum / ((Double) allDeviceSum) * 100) + "%";


                    if (allDeviceSum != null && allDeviceSum != 0d) {


                        contributionRate = numberFormat.format(professionSum / (allDeviceSum) * 100) + "%";


                    }


                }


                Map<String, Object> professionMap = new HashMap<>();


                professionMap.put("contributionRate", contributionRate);


                professionMap.put("value", professionAvg == null ? null : AmendUtils.sciCal(professionAvg, 0));


                map.put(professionName, professionMap);




                //行业均值


                timeDataMap.put("value", professionAvg == null ? null : AmendUtils.sciCal(professionAvg, 0));


                //贡献率


                timeDataMap.put("name", contributionRate);


                dataList.add(timeDataMap);


            }


            professionMap.put("data", dataList);


            result.put(professionName, professionMap);


        }


        result.forEach(map -> map.remove("allDeviceSum"));


        return result;


    }


}