代码提交

.idea/vcs.xml

@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+  </component>
+</project>

ai-xuebao-es/src/main/java/net/hzvtc/es/controller/EsRecordReportController.java

@@ -0,0 +1,156 @@
+package net.hzvtc.es.controller;
+
+import com.alibaba.fastjson.JSONObject;
+import lombok.RequiredArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+import net.hzvtc.common.core.domain.AjaxResult;
+import net.hzvtc.common.utils.file.FileUtils;
+import net.hzvtc.service.EsRecordReportService;
+import org.springframework.web.bind.annotation.*;
+
+import javax.servlet.http.HttpServletRequest;
+import javax.servlet.http.HttpServletResponse;
+import java.util.Map;
+
+@RestController
+@RequestMapping("/es/result/report")
+@Slf4j
+@RequiredArgsConstructor
+public class EsRecordReportController {
+    private final EsRecordReportService esRecordReportService;
+
+    @PostMapping("/getBirdStatData")
+    public AjaxResult getBirdStatData(@RequestBody JSONObject object) {
+        return AjaxResult.success(esRecordReportService.getBirdDailyReportStatByParam(object));
+    }
+
+    @PostMapping("/downloadDetailsReport")
+    public void downloadReport(@RequestParam Map<String, Object> param, HttpServletResponse response, HttpServletRequest request) {
+
+//        obj.put("dateFrom", param.get("dateFrom"));
+//        obj.put("dateTo", param.get("dateTo"));
+//        obj.put("excludeIds", param.get("excludeIds"));
+//        log.info("=============={}", obj);
+        String filePath = esRecordReportService.exportResultRecordListFileByParam(param);
+//        log.info("===========fileName============{}", filePath);
+        if (filePath != null) {
+            try {
+                String realFileName = System.currentTimeMillis() + ".xlsx";
+                response.setContentType("application/vnd.openxmlformats-officedocument.spreadsheetml.sheet");
+                response.setCharacterEncoding("utf-8");
+                FileUtils.setAttachmentResponseHeader(response, realFileName);
+                FileUtils.writeBytes(filePath, response.getOutputStream());
+            } catch (Exception ex) {
+                log.error("error", ex);
+            }
+        }
+    }
+
+    //
+//    @PostMapping("/sendEmail")
+//    public AjaxResult sendEmail(@RequestBody JSONObject object) {
+//        return AjaxResult.success(esRecordReportService.sendBirdDataStatEmail(object));
+//    }
+    @PostMapping("/speciesMediaStatList")
+    public JSONObject getSpeciesMediaListByParam(@RequestBody JSONObject object) {
+        return esRecordReportService.getSpeciesMediaListByParam(object);
+    }
+
+    @PostMapping("/recordStatList")
+    public JSONObject getRecordStatByParam(@RequestBody JSONObject object) {
+        return esRecordReportService.getResultRecordStatReportByParam(object);
+    }
+
+    @PostMapping("/areaStatList")
+    public JSONObject getAreaStatByParam(@RequestBody JSONObject object) {
+        return esRecordReportService.getAreaStatReportByParam(object);
+    }
+
+    @PostMapping("/dateStatList")
+    public JSONObject getRecordStatByDate(@RequestBody JSONObject object) {
+        return esRecordReportService.getRecordStatDateReportByParam(object);
+    }
+
+    @PostMapping("/dateValidStatList")
+    public JSONObject getValidStatByDate(@RequestBody JSONObject object) {
+        return esRecordReportService.getValidStatDateReportByParam(object);
+    }
+
+    @PostMapping("/recordValidStatList")
+    public JSONObject getRecordValidStatByParam(@RequestBody JSONObject object) {
+        return esRecordReportService.getResultRecordValidStatReportByParam(object);
+    }
+
+    @PostMapping("/heatStatList")
+    public JSONObject getRecordValidHeataStatByParam(@RequestBody JSONObject object) {
+        return esRecordReportService.getHeatValidStatReportByParam(object);
+    }
+
+    @PostMapping("/recordDailyStatList")
+    public JSONObject getRecordDailyStatByParam(@RequestBody JSONObject object) {
+        return esRecordReportService.getRecordDailyStatReportByParam(object);
+    }
+
+    @PostMapping("/cameraStatList")
+    public JSONObject getCameraStatByParam(@RequestBody JSONObject object) {
+        return esRecordReportService.getCameraRecordStatReportByParam(object);
+    }
+
+    @PostMapping("/habitatStatList")
+    public JSONObject getHabitatStatByParam(@RequestBody JSONObject object) {
+        return esRecordReportService.getSpeciesHabitatStatReportByParam(object);
+    }
+
+    @PostMapping("/raiStatList")
+    public JSONObject getRAIStatByParam(@RequestBody JSONObject object) {
+        return esRecordReportService.getValidRAIReportByParam(object);
+    }
+
+    @PostMapping("/rnStatList")
+    public JSONObject getRNStatByParam(@RequestBody JSONObject object) {
+        return esRecordReportService.getValidRNReportByParam(object);
+    }
+
+    @PostMapping("/percentStatList")
+    public JSONObject getPercentStatByParam(@RequestBody JSONObject object) {
+        return esRecordReportService.getValidPercentReportByParam(object);
+    }
+
+    @PostMapping("/rrpStatList")
+    public JSONObject getSpeciesRRPStatByParam(@RequestBody JSONObject object) {
+        return esRecordReportService.getValidRAIRNPtReportByParam(object);
+    }
+
+    @PostMapping("/rhythmStatList")
+    public JSONObject getRhythmStatByParam(@RequestBody JSONObject object) {
+        return esRecordReportService.getRhythmReportByParam(object);
+    }
+
+    @PostMapping("/multiStatList")
+    public JSONObject getMultiStatByParam(@RequestBody JSONObject object) {
+        return esRecordReportService.getSpeciesMultiStatReportByParam(object);
+    }
+
+    @GetMapping("/speciesList")
+    public JSONObject getSpeciesList() {
+        return esRecordReportService.getSpeciesTreeList();
+    }
+
+    @PostMapping("/periodStat")
+    public AjaxResult getBirdPeriodStat(@RequestBody JSONObject obj) {
+        obj.put("type", 1);
+        return AjaxResult.success(esRecordReportService.getBirdPeriodStatByParam(obj));
+    }
+
+    @PostMapping("/monthStat")
+    public AjaxResult getMonthStat(@RequestBody JSONObject obj) {
+        obj.put("type", 2);
+        return AjaxResult.success(esRecordReportService.getBirdPeriodStatByParam(obj));
+    }
+
+    @PostMapping("/yearStat")
+    public AjaxResult getYearStat(@RequestBody JSONObject obj) {
+        obj.put("type", 3);
+        return AjaxResult.success(esRecordReportService.getBirdPeriodStatByParam(obj));
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/es/controller/EsResultRecordDetailsController.java

@@ -0,0 +1,148 @@
+package net.hzvtc.es.controller;
+
+import com.alibaba.fastjson.JSONObject;
+import lombok.RequiredArgsConstructor;
+import net.hzvtc.common.core.domain.AjaxResult;
+import net.hzvtc.common.core.page.TableDataInfo;
+import net.hzvtc.device.domain.DeviceInfo;
+import net.hzvtc.service.EsResultRecordDetailsService;
+import org.springframework.web.bind.annotation.*;
+
+import java.util.List;
+
+@RestController
+@RequestMapping("/es/result/details")
+@RequiredArgsConstructor
+public class EsResultRecordDetailsController {
+    private final EsResultRecordDetailsService esResultRecordDetailsService;
+
+
+    @PostMapping("/querySpeciesByParam")
+    public TableDataInfo querySpeciesListByParam(@RequestBody JSONObject params) {
+        params.put("isDeleted", 0);
+        return esResultRecordDetailsService.querySpeciesRecordListByParam(params, 0);
+    }
+
+    @PostMapping("/getSpeciesStatInfoByParam")
+    public JSONObject getSpeciesStatInfoByParam(@RequestBody JSONObject params) {
+        return esResultRecordDetailsService.getSpeciesStatInfo(params);
+    }
+
+    @PostMapping("/querySpeciesByParamForApp")
+    public TableDataInfo querySpeciesListByParamForApp(@RequestBody JSONObject params) {
+        params.put("isDeleted", 0);
+        return esResultRecordDetailsService.querySpeciesRecordListByParam(params, 1);
+    }
+
+    @PostMapping("/querySpeciesByQuery")
+    public TableDataInfo querySpeciesListByQuery(@RequestBody JSONObject obj) {
+        obj.put("isDeleted", 0);
+        return esResultRecordDetailsService.getProtectedAreaSpeciesByQuery(obj);
+    }
+
+    @PostMapping("/birdResultMedias")
+    public TableDataInfo getBirdResultMediasByParam(@RequestBody JSONObject params) {
+        return esResultRecordDetailsService.getResultMediaListByParam(params);
+    }
+
+    @DeleteMapping("/delDocument/{ids}")
+    public AjaxResult deleteDocumentById(@PathVariable String ids) {
+        return AjaxResult.success(esResultRecordDetailsService.deleteDocumentById(ids));
+    }
+
+
+    @PostMapping("/updateResultRecord")
+    public AjaxResult updateResultRecord(@RequestBody JSONObject data) {
+        return AjaxResult.success(esResultRecordDetailsService.updateResultRecordInfoById(data));
+    }
+
+    @PostMapping("/updateResultRecords")
+    public AjaxResult updateResultRecords(@RequestBody JSONObject data) {
+        return AjaxResult.success(esResultRecordDetailsService.updateResultRecordInfoByIds(data));
+    }
+
+    @PostMapping("/birdAudioDailyStat")
+    public AjaxResult getBirdAudioDailyStatList(@RequestBody JSONObject obj) {
+        obj.put("isDeleted", 0);
+        return AjaxResult.success(esResultRecordDetailsService.getBirdAudioDailyStatListByParam(obj));
+    }
+
+    @PostMapping("/birdDailyStat")
+    public AjaxResult getBirdDailyStatList(@RequestBody JSONObject obj) {
+        obj.put("isDeleted", 0);
+        return AjaxResult.success(esResultRecordDetailsService.getBirdDailyStatListByParam(obj));
+    }
+
+    @PostMapping("/birdAudioMonthStat")
+    public AjaxResult getBirdAudioMonthStatList(@RequestBody JSONObject obj) {
+        obj.put("isDeleted", 0);
+        return AjaxResult.success(esResultRecordDetailsService.getBirdAudioMonthStatListByParam(obj));
+    }
+
+    @PostMapping("/birdAudioYearStat")
+    public AjaxResult getBirdAudioYearStatList(@RequestBody JSONObject obj) {
+        obj.put("isDeleted", 0);
+        return AjaxResult.success(esResultRecordDetailsService.getBirdAudioYearStatListByParam(obj));
+    }
+
+    @GetMapping("/listByParam")
+    public AjaxResult getListByParam(DeviceInfo deviceInfo) {
+        return AjaxResult.success(esResultRecordDetailsService.getDeviceInfoListForPage(deviceInfo));
+    }
+
+    @GetMapping("/speciesListByParam")
+    public AjaxResult getSpeciesListByParam() {
+        return AjaxResult.success(esResultRecordDetailsService.getSpeciesListForSelect());
+    }
+
+    @GetMapping("/mediaStatInfo")
+    public JSONObject getStatAmount() {
+        return esResultRecordDetailsService.getResultMediaStatByParam();
+    }
+
+    @PostMapping("/speciesStatList")
+    public JSONObject getSpeciesMediaStatInfoByParam(@RequestBody JSONObject object) {
+        return esResultRecordDetailsService.getSpeciesStatListByParam(object);
+    }
+
+    @GetMapping("/listForMap")
+    public List<DeviceInfo> getDeviceListForGisMap() {
+        return esResultRecordDetailsService.getDeviceInfoListForGisMap();
+    }
+
+    @PostMapping("/updateDocumentInfoByParam")
+    public AjaxResult updateStatus(@RequestBody JSONObject param) {
+        return AjaxResult.success(esResultRecordDetailsService.updateResultRecordInfoById(param));
+    }
+
+    @PostMapping("/updateDocumentFavorite")
+    public AjaxResult updateFavorite(@RequestBody JSONObject param) {
+        return AjaxResult.success(esResultRecordDetailsService.updateResultRecordInfoById(param));
+    }
+
+    @PostMapping("/updateSpeciesInfo")
+    public AjaxResult updateSpeciesInfo(@RequestBody JSONObject param) {
+        return AjaxResult.success(esResultRecordDetailsService.updateSpeciesInfo(param));
+    }
+
+    @PostMapping("/deleteSpeciesInfo")
+    public AjaxResult deleteSpeciesInfo(@RequestBody JSONObject param) {
+        return AjaxResult.success(esResultRecordDetailsService.deleteSpeciesInfo(param));
+    }
+
+    @PostMapping("/addSpeciesInfo")
+    public AjaxResult addSpeciesInfo(@RequestBody JSONObject param) {
+        return AjaxResult.success(esResultRecordDetailsService.addSpeciesInfo(param));
+    }
+
+    @PostMapping("/favoriteList")
+    public AjaxResult getFavoriteMediaList(@RequestBody JSONObject param) {
+        return AjaxResult.success(esResultRecordDetailsService.getFavoriteMediaList(param));
+    }
+
+    @PostMapping("/listByItemId")
+    public AjaxResult getMediaListByItemId(@RequestBody JSONObject param) {
+        return AjaxResult.success(esResultRecordDetailsService.getMediaListByItemId(param));
+    }
+}
+

ai-xuebao-es/src/main/java/net/hzvtc/es/domain/EsResultRecordDetails.java

@@ -0,0 +1,64 @@
+package net.hzvtc.es.domain;
+
+import com.fasterxml.jackson.annotation.JsonFormat;
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+import org.apache.ibatis.type.Alias;
+import org.springframework.data.annotation.Id;
+
+import java.time.ZonedDateTime;
+import java.util.List;
+
+@Data
+@Alias("EsResultRecordDetails")
+@AllArgsConstructor
+@NoArgsConstructor
+//@JsonIgnoreProperties(ignoreUnknown = true)
+public class EsResultRecordDetails {
+    @Id
+    private Long id;
+
+    @JsonFormat(shape = JsonFormat.Shape.STRING, pattern = "yyyy-MM-dd HH:mm:ss", timezone = "Asia/Shanghai")
+    private ZonedDateTime recordTime;
+
+    private Long deviceId;
+
+    private String deviceName;
+
+    private Integer deviceType;
+
+    private String duid;
+
+    private Long deptId;
+
+    private String deptName;
+
+    private String deptLetter;
+
+    private int checked;
+
+    private Long mediaId;
+
+    private String mediaUrl;
+
+    private String metaUrl;
+
+    private int mediaType;
+
+    private Integer favorite;
+
+    private String memo;
+
+    private String tag;
+
+    private String version;
+
+    private Long itemId;
+
+    private List<SpeciesItem> items;
+
+    private int isDeleted;
+
+    private String aiName;
+}

ai-xuebao-es/src/main/java/net/hzvtc/es/domain/EsResultRecordDetailsBak.java

@@ -0,0 +1,59 @@
+package net.hzvtc.es.domain;
+
+import com.fasterxml.jackson.annotation.JsonFormat;
+import org.springframework.data.annotation.Id;
+
+import java.time.ZonedDateTime;
+
+
+public class EsResultRecordDetailsBak {
+    @Id
+    private Long id;
+
+    @JsonFormat(shape = JsonFormat.Shape.STRING, pattern = "yyyy-MM-dd HH:mm:ss", timezone = "Asia/Shanghai")
+    private ZonedDateTime recordTime;
+
+    private Long recordId;
+
+    private Long deviceId;
+
+    private String deviceName;
+
+    private Integer deviceType;
+
+    private String duid;
+
+    private Long speciesId;
+
+    private String speciesName;
+
+    private String scientificName;
+
+    private Long deptId;
+
+    private int checked;
+
+    private int count;
+
+    private String habitat;
+
+    private double confidence;
+
+    private Long mediaId;
+
+    private String mediaUrl;
+
+    private String metaUrl;
+
+    private int mediaType;
+
+    private int recordType;
+
+    private Integer favorite;
+
+    private String birdIcon;
+
+    private String version;
+
+    private int isDeleted;
+}

ai-xuebao-es/src/main/java/net/hzvtc/es/domain/EsResultRecordDetailsVo.java

@@ -0,0 +1,86 @@
+package net.hzvtc.es.domain;
+
+import com.fasterxml.jackson.annotation.JsonIgnore;
+import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
+import lombok.Data;
+import org.apache.ibatis.type.Alias;
+import org.springframework.data.annotation.Id;
+
+import java.time.LocalDateTime;
+import java.time.ZoneId;
+import java.time.ZonedDateTime;
+import java.time.format.DateTimeFormatter;
+
+@Data
+@Alias("EsResultRecordDetailsVo")
+@JsonIgnoreProperties(ignoreUnknown = true)
+public class EsResultRecordDetailsVo {
+    @Id
+    private Long id;
+
+    @JsonIgnore
+    private LocalDateTime recordTime1;
+
+    private Long recordId;
+
+    private Long deviceId;
+
+    private String deviceName;
+
+    private String duid;
+
+    private Long speciesId;
+
+    private String speciesName;
+
+    private String scientificName;
+
+    private Long deptId;
+
+    private int checked;
+
+    private int count;
+
+    private String habitat;
+
+    private double confidence;
+
+    private Long mediaId;
+
+    private String mediaUrl;
+
+    private String metaUrl;
+
+    private int mediaType;
+
+    private int recordType;
+
+    private Integer favorite;
+
+    private String birdIcon;
+
+    private int isDeleted;
+
+    public String getRecordTime() {
+        if (recordTime1 != null) {
+//            LocalDateTime localDateTime =
+//            ZonedDateTime zonedDateTime = recordTime1.atZone(ZoneId.of("Asia/Shanghai"));
+
+//            ZoneId systemDefault = ZoneId.systemDefault();
+//            return zonedDateTime.format(DateTimeFormatter.ISO_DATE_TIME);
+//            return recordTime1.format(DateTimeFormatter.ofPattern("yyyy-MM-dd'T'HH:mm:ss.SSSX"));
+            ZonedDateTime zonedDateTime = recordTime1.atZone(ZoneId.of("Asia/Shanghai"));
+
+            // 使用 DateTimeFormatter 格式化为 ISO 8601 格式的字符串
+//            return zonedDateTime.format(DateTimeFormatter.ISO_OFFSET_DATE_TIME);
+            ZonedDateTime utcDateTime = zonedDateTime.withZoneSameInstant(ZoneId.of("UTC"));
+
+            // 格式化为目标字符串
+            return utcDateTime.format(DateTimeFormatter.ofPattern("yyyy-MM-dd'T'HH:mm:ss.SSS'Z'"));
+
+
+        } else {
+            return null;
+        }
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/es/domain/EsResultRecordReportData.java

@@ -0,0 +1,85 @@
+package net.hzvtc.es.domain;
+
+import lombok.Data;
+import net.hzvtc.data.check.domain.MediaItem;
+import net.hzvtc.device.domain.DeviceInfo;
+
+import java.time.ZoneId;
+import java.time.format.DateTimeFormatter;
+import java.util.List;
+
+@Data
+public class EsResultRecordReportData {
+    private Long id;
+
+
+    private String recordTime;
+
+    private Long deviceId;
+
+    private DeviceInfo deviceInfo;
+
+    private Long deptId;
+
+    private String fullPath;
+
+    private int checked;
+
+    private Long mediaId;
+
+    private String mediaUrl;
+
+    private String metaUrl;
+
+    private String fileName;
+
+    private int mediaType;
+
+//    private Integer favorite;
+//
+//    private String memo;
+//
+//    private String tag;
+//
+//    private String version;
+
+    private Long itemId;
+
+    private List<SpeciesItem> items;
+
+    private MediaItem mediaItem;
+
+    public void convertFrom(EsResultRecordDetails data) {
+        setId(data.getId());
+        DateTimeFormatter fmDate = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss");
+        if (data.getRecordTime() != null) {
+            setRecordTime(data.getRecordTime().withZoneSameInstant(ZoneId.of("Asia/Shanghai")).format(fmDate));
+        } else {
+            setRecordTime("");
+        }
+        setDeptId(data.getDeptId());
+        setDeviceId(data.getDeviceId());
+        setMediaId(data.getMediaId());
+        setMediaUrl(data.getMediaUrl());
+        setMetaUrl(data.getMetaUrl());
+        setMediaType(data.getMediaType());
+        setItemId(data.getItemId());
+
+        if (mediaType == 2) {
+            if (metaUrl != null) {
+                String name = metaUrl.substring(metaUrl.lastIndexOf("/") + 1);
+                setFileName(name);
+            }
+        } else if (mediaType == 3) {
+            if (mediaUrl != null) {
+                String name = mediaUrl.substring(mediaUrl.lastIndexOf("/") + 1);
+                setFileName(name);
+            }
+        }
+//        setFavorite(data.getFavorite());
+//        setMemo(data.getMemo());
+//        setTag(data.getTag());
+//        setVersion(data.getVersion());
+
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/es/domain/SpeciesItem.java

@@ -0,0 +1,18 @@
+package net.hzvtc.es.domain;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+@Data
+@AllArgsConstructor
+@NoArgsConstructor
+public class SpeciesItem {
+    private Long detailsId;
+    private Long recordId;
+    private Long speciesId;
+    private String speciesName;
+    private String scientificName;
+    private int count;
+    private int isValid;
+}

ai-xuebao-es/src/main/java/net/hzvtc/es/mapper/EsResultRecordDetailsMapper.java

@@ -0,0 +1,15 @@
+package net.hzvtc.es.mapper;
+
+import net.hzvtc.echart.domain.vo.BirdStatDataVo;
+import net.hzvtc.es.domain.EsResultRecordDetailsVo;
+
+import java.util.List;
+import java.util.Map;
+
+public interface EsResultRecordDetailsMapper {
+    List<EsResultRecordDetailsVo> getResultRecordListForElastic(Map<String, Object> param);
+
+    List<BirdStatDataVo> getDeviceListByParam(Map<String, Object> map);
+
+    List<BirdStatDataVo> getAreaBirdSpeciesByParam(Map<String, Object> map);
+}

ai-xuebao-es/src/main/java/net/hzvtc/service/EsRecordReportService.java

@@ -0,0 +1,55 @@
+package net.hzvtc.service;
+
+import com.alibaba.fastjson.JSONObject;
+
+import java.util.Map;
+
+public interface EsRecordReportService {
+    JSONObject getBirdDailyReportStatByParam(JSONObject param);
+
+//    String getBirdDataStatFileByParam(JSONObject param);
+
+    String exportResultRecordListFileByParam(Map<String, Object> param);
+
+    String exportValidResultRecordListFileByParam(Map<String, Object> param);
+
+//    boolean sendBirdDataStatEmail(JSONObject param);
+
+    JSONObject getSpeciesWeeklyReportByParam(JSONObject param);
+
+    JSONObject getSpeciesMediaListByParam(JSONObject param);
+
+    JSONObject getResultRecordStatReportByParam(JSONObject param);
+
+    JSONObject getResultRecordValidStatReportByParam(JSONObject param);
+
+    JSONObject getHeatValidStatReportByParam(JSONObject param);
+
+    JSONObject getCameraRecordStatReportByParam(JSONObject param);
+
+    JSONObject getAreaStatReportByParam(JSONObject param);
+
+    JSONObject getSpeciesTreeList();
+
+    JSONObject getSpeciesMultiStatReportByParam(JSONObject param);
+
+    JSONObject getRecordDailyStatReportByParam(JSONObject param);
+
+    JSONObject getRecordStatDateReportByParam(JSONObject param);
+
+    JSONObject getValidStatDateReportByParam(JSONObject param);
+
+    JSONObject getValidRAIReportByParam(JSONObject param);
+
+    JSONObject getValidRNReportByParam(JSONObject param);
+
+    JSONObject getValidPercentReportByParam(JSONObject param);
+
+    JSONObject getValidRAIRNPtReportByParam(JSONObject param);
+
+    JSONObject getRhythmReportByParam(JSONObject param);
+
+    JSONObject getBirdPeriodStatByParam(JSONObject object);
+
+    JSONObject getSpeciesHabitatStatReportByParam(JSONObject param);
+}

ai-xuebao-es/src/main/java/net/hzvtc/service/EsResultRecordDetailsService.java

@@ -0,0 +1,64 @@
+package net.hzvtc.service;
+
+import com.alibaba.fastjson.JSONArray;
+import com.alibaba.fastjson.JSONObject;
+import net.hzvtc.common.core.page.TableDataInfo;
+import net.hzvtc.device.domain.DeviceInfo;
+import net.hzvtc.es.domain.EsResultRecordDetails;
+
+import java.util.List;
+
+public interface EsResultRecordDetailsService {
+    TableDataInfo querySpeciesRecordListByParam(JSONObject param, int type);
+
+    TableDataInfo getProtectedAreaSpeciesByQuery(JSONObject param);
+
+    TableDataInfo getResultMediaListByParam(JSONObject jsonObject);
+
+    int deleteDocumentById(String id);
+
+    void bulkAddResultRecordDocument();
+
+    int getMaxResultRecordId();
+
+    boolean updateResultRecordInfoById(JSONObject object);
+
+    boolean updateResultRecordInfoByIds(JSONObject object);
+
+    JSONObject getBirdAudioDailyStatListByParam(JSONObject param);
+
+    JSONObject getBirdDailyStatListByParam(JSONObject param);
+
+    JSONObject getBirdAudioMonthStatListByParam(JSONObject param);
+
+    JSONObject getBirdAudioYearStatListByParam(JSONObject param);
+
+    List<DeviceInfo> getDeviceInfoListForPage(DeviceInfo deviceInfo);
+
+    JSONArray getSpeciesListForSelect();
+
+    JSONObject getResultMediaStatByParam();
+
+    JSONObject getSpeciesStatListByParam(JSONObject param);
+
+    List<DeviceInfo> getDeviceInfoListForGisMap();
+
+    JSONObject getSpeciesStatInfo(JSONObject param);
+
+    boolean updateSpeciesInfo(JSONObject object);
+
+
+    boolean deleteSpeciesInfo(JSONObject object);
+
+    Long addSpeciesInfo(JSONObject object);
+
+    List<EsResultRecordDetails> getFavoriteMediaList(JSONObject param);
+
+    List<EsResultRecordDetails> getMediaListByItemId(JSONObject param);
+
+//    JSONObject getBirdDailyReportStatByParam(JSONObject param);
+
+//    String getBirdDataStatFileByParam(JSONObject param);
+
+//    boolean sendBirdDataStatEmail(JSONObject param);
+}

ai-xuebao-es/src/main/java/net/hzvtc/service/impl/CommonEsUtils.java

@@ -0,0 +1,311 @@
+package net.hzvtc.service.impl;
+
+import co.elastic.clients.elasticsearch.ElasticsearchClient;
+import co.elastic.clients.elasticsearch._types.FieldValue;
+import co.elastic.clients.elasticsearch._types.SortOrder;
+import co.elastic.clients.elasticsearch._types.aggregations.*;
+import co.elastic.clients.elasticsearch._types.query_dsl.BoolQuery;
+import co.elastic.clients.elasticsearch.core.SearchRequest;
+import co.elastic.clients.elasticsearch.core.SearchResponse;
+import co.elastic.clients.elasticsearch.core.search.Hit;
+import co.elastic.clients.elasticsearch.core.search.TrackHits;
+import co.elastic.clients.json.JsonData;
+import com.alibaba.fastjson.JSONArray;
+import com.alibaba.fastjson.JSONObject;
+import lombok.extern.slf4j.Slf4j;
+import net.hzvtc.es.domain.EsResultRecordDetails;
+
+import java.io.IOException;
+import java.time.LocalDateTime;
+import java.time.format.DateTimeFormatter;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Collectors;
+
+@Slf4j
+public class CommonEsUtils {
+    public static JSONArray getSpeciesAggregateList(JSONObject param, String indexName, ElasticsearchClient elasticsearchClient, CalendarInterval calendarInterval) throws IOException {
+        BoolQuery.Builder boolQueryBuilder = createQuery(param);
+//        log.info("========111========{}", param);
+        SearchRequest searchRequest = SearchRequest.of(builder -> builder.index(indexName).size(0).query(q -> q.bool(boolQueryBuilder.build())).aggregations("by_speciesId", a -> a.terms(TermsAggregation.of(ta -> ta.field("species_id").size(10000))).aggregations("by_calendarInterval", b -> b.dateHistogram(DateHistogramAggregation.of(dh -> dh.field("record_time").calendarInterval(calendarInterval))).aggregations("sum_count_field", s -> s.sum(SumAggregation.of(sa -> sa.field("count")))))));
+        SearchResponse<Void> searchResponse = elasticsearchClient.search(searchRequest, Void.class);
+        Map<String, Aggregate> aggs = searchResponse.aggregations();
+        Aggregate bySpeciesAgg = aggs.get("by_speciesId");
+        JSONArray jsonArray = new JSONArray();
+        DateTimeFormatter formatter = DateTimeFormatter.ofPattern("yyyy-MM-dd'T'HH:mm:ss.SSSX");
+
+        bySpeciesAgg.lterms().buckets().array().forEach(speciesBucket -> {
+            Aggregate byCalendarInterval = speciesBucket.aggregations().get("by_calendarInterval");
+            byCalendarInterval.dateHistogram().buckets().array().forEach(hourBucket -> {
+                if (hourBucket.keyAsString() != null) {
+                    JSONObject item = new JSONObject();
+                    LocalDateTime dateTime = LocalDateTime.parse(hourBucket.keyAsString(), formatter);
+                    if (calendarInterval == CalendarInterval.Hour) {
+                        item.put("hour", dateTime.getHour());
+                    } else if (calendarInterval == CalendarInterval.Day) {
+                        item.put("weekDay", dateTime.getDayOfWeek());
+                    }
+
+                    item.put("speciesId", speciesBucket.key());
+                    Aggregate sumAgg = hourBucket.aggregations().get("sum_count_field");
+                    item.put("count", (int) sumAgg.sum().value());
+                    jsonArray.add(item);
+                }
+            });
+        });
+        return jsonArray;
+    }
+
+    public static EsResultRecordDetails getResultRecordDetailsByParam(JSONObject param, String indexName, ElasticsearchClient elasticsearchClient) throws IOException {
+        BoolQuery.Builder boolQueryBuilder = createQuery(param);
+        SearchResponse<EsResultRecordDetails> response = elasticsearchClient.search(s -> s.trackTotalHits(new TrackHits.Builder().enabled(true).build())//
+                .index(indexName).query(q -> q.bool(boolQueryBuilder.build()))//
+                .sort(sort -> sort.field(f -> f.field("favorite").order(SortOrder.Desc)))//
+                .sort(sort -> sort.field(f -> f.field("id").order(SortOrder.Desc)))//
+//                        .source(sc -> sc
+//                                .filter(f -> f
+//                                        .includes(Arrays.asList(sources))
+//                                )
+//                        )
+                .from(0).size(1), EsResultRecordDetails.class);
+
+        List<Hit<EsResultRecordDetails>> hitList = response.hits().hits();
+
+        for (Hit<EsResultRecordDetails> mapHit : hitList) {
+            return mapHit.source();
+        }
+
+        return null;
+    }
+
+    public static long getSpeciesStatAmountByParam(JSONObject param, String indexName, ElasticsearchClient elasticsearchClient) throws IOException {
+        BoolQuery.Builder boolQueryBuilder = createQuery(param);
+        SearchRequest searchRequest = SearchRequest.of(builder -> builder.index(indexName).size(0).query(q -> q.bool(boolQueryBuilder.build())).aggregations("sum_count_field", a -> a.sum(SumAggregation.of(ta -> ta.field("count")))));
+        SearchResponse<Void> searchResponse = elasticsearchClient.search(searchRequest, Void.class);
+        Map<String, Aggregate> aggs = searchResponse.aggregations();
+        Aggregate sumAgg = aggs.get("sum_count_field");
+        return (long) sumAgg.sum().value();
+    }
+
+
+    public static BoolQuery.Builder createQuery(JSONObject param) {
+//        log.info("==================param==========={}", param);
+        BoolQuery.Builder boolQueryBuilder = new BoolQuery.Builder();
+
+//        Long areaId = param.getLong("areaId");
+//        if (areaId != null) {
+//            boolQueryBuilder.must(m -> m.match(t -> t.field("area_id").query(areaId)));
+//        }
+
+//
+
+        Long speciesId = param.getLong("speciesId");
+        if (speciesId != null) {
+            boolQueryBuilder.must(m -> m.nested(n -> n.path("items").query(q -> q.match(t -> t.field("items.species_id").query(speciesId)))));
+//            boolQueryBuilder.must(m -> m.match(t -> t.field("items.species_id").query(speciesId)));
+        }
+
+        Long species_id = param.getLong("species_id");
+        if (species_id != null) {
+//            boolQueryBuilder.must(m -> m.nested(n -> n.path("items").query(q -> q.match(t -> t.field("items.species_id").query(speciesId)))));
+            boolQueryBuilder.must(m -> m.match(t -> t.field("species_id").query(species_id)));
+        }
+
+        Long deviceId = param.getLong("deviceId");
+        if (deviceId != null) {
+            boolQueryBuilder.must(m -> m.match(t -> t.field("device_id").query(deviceId)));
+        }
+
+        Long mediaId = param.getLong("mediaId");
+        if (mediaId != null) {
+            boolQueryBuilder.must(m -> m.match(t -> t.field("media_id").query(mediaId)));
+        }
+
+        Integer deviceType = param.getInteger("deviceType");
+        if (deviceType != null) {
+            boolQueryBuilder.must(m -> m.match(t -> t.field("device_type").query(deviceType)));
+        }
+
+        Integer favorite = param.getInteger("favorite");
+        if (favorite != null) {
+            boolQueryBuilder.must(m -> m.match(t -> t.field("favorite").query(favorite)));
+        }
+
+        Integer checked = param.getInteger("checked");
+        if (checked != null) {
+            boolQueryBuilder.must(m -> m.match(t -> t.field("checked").query(checked)));
+        }
+
+        String version = param.getString("version");
+        if (version != null && !version.isEmpty()) {
+            boolQueryBuilder.must(m -> m.match(t -> t.field("version").query(version)));
+        }
+        Long itemId = param.getLong("itemId");
+        if (itemId != null) {
+            boolQueryBuilder.must(m -> m.match(t -> t.field("item_id").query(itemId)));
+        }
+
+
+        String tag = param.getString("tag");
+        if (tag != null && !tag.isEmpty()) {
+//            log.info("============tag==========={}", tag);
+//            boolQueryBuilder.must(m -> m.fuzzy(fz -> fz.field("tag").value(tag).fuzziness("1")));
+            boolQueryBuilder.must(m -> m.matchPhrase(fz -> fz.field("tag").query(tag)));
+        }
+
+
+        String memo = param.getString("memo");
+        if (memo != null && !memo.isEmpty()) {
+//            log.info("============memo==========={}", memo);
+//            boolQueryBuilder.must(m -> m.fuzzy(fz -> fz.field("memo").value(memo).fuzziness("1")));
+            boolQueryBuilder.must(m -> m.matchPhrase(fz -> fz.field("memo").query(memo)));
+        }
+
+        String queryStr = param.getString("queryStr");
+        if (queryStr != null && !queryStr.trim().isEmpty()) {
+            boolQueryBuilder.should(s1 -> s1.match(fz -> fz.field("tag").query(queryStr))).should(s2 -> s2.match(fz -> fz.field("memo").query(queryStr))).minimumShouldMatch("1");
+        }
+
+        Integer isDeleted = param.getInteger("isDeleted");
+        if (isDeleted != null) {
+            boolQueryBuilder.must(m -> m.match(t -> t.field("is_deleted").query(isDeleted)));
+        }
+
+        String dateFrom = param.getString("dateFrom");
+        if (dateFrom != null && !dateFrom.isEmpty()) {
+            boolQueryBuilder.must(m -> m.range(v -> v.field("record_time").format("yyyy-MM-dd").gte(JsonData.of(dateFrom)).timeZone("+08:00")));
+        }
+
+        String dateTo = param.getString("dateTo");
+        if (dateTo != null && !dateTo.isEmpty()) {
+            boolQueryBuilder.must(m -> m.range(v -> v.field("record_time").format("yyyy-MM-dd").lte(JsonData.of(dateTo)).timeZone("+08:00")));
+        }
+
+        String startYear = param.getString("startYear");
+        if (startYear != null && !startYear.isEmpty()) {
+            startYear = startYear + "-01-01";
+            String finalStartYear = startYear;
+            boolQueryBuilder.must(m -> m.range(v -> v.field("record_time").format("yyyy-MM-dd").gte(JsonData.of(finalStartYear)).timeZone("+08:00")));
+        }
+
+        String endYear = param.getString("endYear");
+        if (endYear != null && !endYear.isEmpty()) {
+            endYear = endYear + "-12-31";
+            String finalEndYear = endYear;
+            boolQueryBuilder.must(m -> m.range(v -> v.field("record_time").format("yyyy-MM-dd").lte(JsonData.of(finalEndYear))));
+        }
+
+        Integer recordType = param.getInteger("recordType");
+        if (recordType != null) {
+            boolQueryBuilder.must(m -> m.match(t -> t.field("record_type").query(recordType)));
+        }
+
+        String calcDate = param.getString("calcDate");
+        if (calcDate != null && !calcDate.isEmpty()) {
+            boolQueryBuilder.must(m -> m.range(v -> v.field("record_time").format("yyyy-MM-dd").lte(JsonData.of(calcDate)).gte(JsonData.of(calcDate)).timeZone("+08:00")));
+        }
+
+        String calcYear = param.getString("calcYear");
+        if (calcYear != null && !calcYear.isEmpty()) {
+            String from = calcYear + "-01-01";
+            String to = calcYear + "-12-31";
+            boolQueryBuilder.must(m -> m.range(v -> v.field("record_time").format("yyyy-MM-dd").lte(JsonData.of(to)).gte(JsonData.of(from)).timeZone("+08:00")));
+        }
+
+        JSONArray array = param.getJSONArray("exSpeciesIds");
+        if (array != null && !array.isEmpty()) {
+//            log.info("==========exSpeciesIds=========={}", array);
+            createExcludeArrayQuery("species_id", null, array, boolQueryBuilder);
+        }
+
+        array = param.getJSONArray("ids");
+        if (array != null && !array.isEmpty()) {
+            createExcludeArrayQuery("items", "items.species_id", array, boolQueryBuilder);
+        }
+
+        array = param.getJSONArray("speciesIds");
+        if (array != null && !array.isEmpty()) {
+            createIncludeNestArrayQuery("items", "items.species_id", array, boolQueryBuilder);
+        }
+
+        array = param.getJSONArray("speciesInIds");
+        if (array != null && !array.isEmpty()) {
+            createIncludeArrayQuery("species_id", array, boolQueryBuilder);
+        }
+
+        Integer mediaType = param.getInteger("mediaType");
+        if (mediaType != null) {
+            boolQueryBuilder.must(m -> m.match(t -> t.field("media_type").query(mediaType)));
+        }
+
+        String mediaTypes = param.getString("mediaTypes");
+        if (mediaTypes != null && !mediaTypes.isEmpty()) {
+            String[] arr = mediaTypes.split(",");
+            List<String> terms = Arrays.asList(arr);
+            List<FieldValue> fieldValues = terms.stream().map(FieldValue::of).collect(Collectors.toList());
+            boolQueryBuilder.must(m -> m.terms(t -> t.field("media_type").terms(tq -> tq.value(fieldValues))));
+        }
+
+        array = param.getJSONArray("deviceIds");
+//        log.info("=============device ids==={}", array);
+        createIncludeArrayQuery("device_id", array, boolQueryBuilder);
+
+        array = param.getJSONArray("inDocIds");
+        createIncludeArrayQuery("id", array, boolQueryBuilder);
+//        if (array != null && !array.isEmpty()) {
+//            List<Long> list = new ArrayList<>();
+//            for (Object id : array) {
+//                list.add((Long) id);
+//            }
+//            List<FieldValue> fieldValues = list.stream().map(FieldValue::of).collect(Collectors.toList());
+//            boolQueryBuilder.mustNot(m -> m.terms(t -> t.field("device_id").terms(tq -> tq.value(fieldValues))));
+//        }
+//        log.info("============={}", boolQueryBuilder);
+        return boolQueryBuilder;
+    }
+
+    private static void createIncludeArrayQuery(String fieldName, JSONArray array, BoolQuery.Builder boolQueryBuilder) {
+        if (array != null && !array.isEmpty()) {
+            List<Long> list = new ArrayList<>();
+            for (Object id : array) {
+                list.add(Long.parseLong(id.toString()));
+            }
+            List<FieldValue> fieldValues = list.stream().map(FieldValue::of).collect(Collectors.toList());
+            boolQueryBuilder.must(m -> m.terms(t -> t.field(fieldName).terms(tq -> tq.value(fieldValues))));
+        }
+    }
+
+    private static void createIncludeNestArrayQuery(String fieldName, String nestedName, JSONArray array, BoolQuery.Builder boolQueryBuilder) {
+        if (array != null && !array.isEmpty()) {
+            List<Long> list = new ArrayList<>();
+            for (Object id : array) {
+                list.add(Long.parseLong(id.toString()));
+            }
+            List<FieldValue> fieldValues = list.stream().map(FieldValue::of).collect(Collectors.toList());
+            if (nestedName != null && !nestedName.isEmpty()) {
+                boolQueryBuilder.must(mn -> mn.nested(n -> n.path(fieldName).query(nq -> nq.terms(t -> t.field(nestedName).terms(tq -> tq.value(fieldValues))))));
+            } else {
+                boolQueryBuilder.must(m -> m.terms(t -> t.field(fieldName).terms(tq -> tq.value(fieldValues))));
+            }
+
+        }
+    }
+
+    private static void createExcludeArrayQuery(String fieldName, String nestedName, JSONArray array, BoolQuery.Builder boolQueryBuilder) {
+        if (array != null && !array.isEmpty()) {
+            List<Long> list = new ArrayList<>();
+            for (Object id : array) {
+                list.add((Long) id);
+            }
+            List<FieldValue> fieldValues = list.stream().map(FieldValue::of).collect(Collectors.toList());
+            if (nestedName != null && !nestedName.isEmpty()) {
+                boolQueryBuilder.mustNot(mn -> mn.nested(n -> n.path(fieldName).query(nq -> nq.terms(t -> t.field(nestedName).terms(tq -> tq.value(fieldValues))))));
+            } else {
+                boolQueryBuilder.mustNot(m -> m.terms(t -> t.field(fieldName).terms(tq -> tq.value(fieldValues))));
+            }
+
+        }
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/algorithm/ChainLength.java

@@ -0,0 +1,126 @@
+package net.hzvtc.stat.algorithm;
+
+import net.hzvtc.stat.dto.ChainLengthItem;
+import net.hzvtc.stat.dto.ChainRecord;
+import net.hzvtc.stat.dto.FootprintPoint;
+import net.hzvtc.stat.util.GeoUtils;
+import net.hzvtc.stat.util.StatisticsUtils;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+/**
+ * R 中 chainLength(chain) / chainLengths(chainDB) 的 Java 实现。
+ *
+ * <p>算法：
+ * <ol>
+ *   <li>把每条足迹链转 UTM 米。</li>
+ *   <li>计算相邻点的距离（km），若 &gt; 100km 视为跨区清零。</li>
+ *   <li>累加得到总链长（km）。</li>
+ * </ol>
+ * </p>
+ *
+ * <p>chainLengths 按 Species/Line 聚合，额外给出每物种平均步长（m）与推算步数。</p>
+ */
+public final class ChainLength {
+
+    private ChainLength() {
+    }
+
+    /**
+     * 单条足迹链长度（km）。
+     *
+     * @param chain 足迹链
+     * @return 链长（km）
+     */
+    public static double chainLength(List<FootprintPoint> chain) {
+        if (chain == null || chain.size() < 2) {
+            return 0.0;
+        }
+        double[][] xy = GeoUtils.wgs84ToUtmAuto(chain, p -> p.getLon(), p -> p.getLat());
+        double totalKm = 0.0;
+        for (int i = 1; i < xy.length; i++) {
+            double dx = (xy[i][0] - xy[i - 1][0]) / 1000.0;
+            double dy = (xy[i][1] - xy[i - 1][1]) / 1000.0;
+            double d = Math.sqrt(dx * dx + dy * dy);
+            // 跨区 (>100 km) 清零
+            totalKm += d > 100.0 ? 0.0 : d;
+        }
+        return Math.round(totalKm * 1000.0) / 1000.0;
+    }
+
+    /**
+     * 多物种多链的链长聚合（每物种一行）。
+     */
+    public static List<ChainLengthItem> chainLengths(List<ChainRecord> records) {
+        if (records == null || records.isEmpty()) {
+            return new ArrayList<>();
+        }
+        // 按 Species 分组
+        Map<String, List<ChainRecord>> bySpecies = new HashMap<>();
+        for (ChainRecord r : records) {
+            bySpecies.computeIfAbsent(r.getSpecies(), k -> new ArrayList<>()).add(r);
+        }
+
+        List<ChainLengthItem> result = new ArrayList<>();
+        for (Map.Entry<String, List<ChainRecord>> e : bySpecies.entrySet()) {
+            String species = e.getKey();
+            List<ChainRecord> sp = e.getValue();
+
+            // 按 Line 分组
+            Map<Integer, List<ChainRecord>> byLine = new HashMap<>();
+            for (ChainRecord r : sp) {
+                byLine.computeIfAbsent(r.getLine(), k -> new ArrayList<>()).add(r);
+            }
+
+            List<Double> distances = new ArrayList<>();
+            List<Double> steps = new ArrayList<>();
+            for (List<ChainRecord> lineRecs : byLine.values()) {
+                List<FootprintPoint> chain = new ArrayList<>(lineRecs.size());
+                for (ChainRecord r : lineRecs) {
+                    chain.add(new FootprintPoint(r.getLon(), r.getLat(), r.getDate()));
+                }
+                double distKm = chainLength(chain);
+                distances.add(distKm);
+
+                // 平均步长（m）：相邻点距离（m）求均值
+                double[][] xy = GeoUtils.wgs84ToUtmAuto(chain, p -> p.getLon(), p -> p.getLat());
+                if (xy.length >= 2) {
+                    double sum = 0.0;
+                    int cnt = 0;
+                    for (int i = 1; i < xy.length; i++) {
+                        double dx = xy[i][0] - xy[i - 1][0];
+                        double dy = xy[i][1] - xy[i - 1][1];
+                        double d = Math.sqrt(dx * dx + dy * dy);
+                        if (d > 0 && d <= 100000) {
+                            sum += d;
+                            cnt++;
+                        }
+                    }
+                    if (cnt > 0) {
+                        steps.add(sum / cnt);
+                    }
+                }
+            }
+
+            double[] dArr = distances.stream().mapToDouble(Double::doubleValue).toArray();
+            double[] sArr = steps.stream().mapToDouble(Double::doubleValue).toArray();
+            double meanDist = StatisticsUtils.mean(dArr);
+            double sdDist = StatisticsUtils.sd(dArr);
+            double meanStep = sArr.length > 0 ? StatisticsUtils.mean(sArr) : 0.0;
+            long stepNo = meanStep > 0 ? (long) Math.floor(meanDist * 1000.0 / meanStep * 30.0) : 0L;
+
+            result.add(new ChainLengthItem(
+                    species,
+                    Math.round(meanDist * 1000.0) / 1000.0,
+                    Math.round(sdDist * 1000.0) / 1000.0,
+                    Math.round(meanStep * 10.0) / 10.0,
+                    stepNo,
+                    dArr.length
+            ));
+        }
+        return result;
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/algorithm/DailyRhythm.java

@@ -0,0 +1,84 @@
+package net.hzvtc.stat.algorithm;
+
+import net.hzvtc.stat.dto.CameraPoint;
+import net.hzvtc.stat.dto.DensitySeries;
+import net.hzvtc.stat.util.DensityUtils;
+
+import java.util.ArrayList;
+import java.util.List;
+
+/**
+ * R 中 dailyRhythm(x) 的 Java 实现：返回 24 小时活动节律的两条 KDE 曲线（bw=0.3 细线 / bw=2 粗线）。
+ *
+ * <p>算法：
+ * <ol>
+ *   <li>把每个 Time 字符串 (HH:mm:ss) 转为相对 0 点的秒数，再除以 3600 得到 0-24 小时浮点值。</li>
+ *   <li>在 [0, 24] 区间分别用 bw=0.3 与 bw=2 计算高斯核密度。</li>
+ *   <li>返回两条 {@link DensitySeries}（前端用 ECharts 画）。</li>
+ * </ol>
+ * </p>
+ */
+public final class DailyRhythm {
+
+    private DailyRhythm() {
+    }
+
+    /** 默认采样点数（与 R density 默认 n=512 一致）。 */
+    private static final int N = 512;
+
+    /**
+     * @param trapresult 数据（含 Time 字段）
+     * @return 两条曲线：[bw=0.3, bw=2]
+     */
+    public static List<DensitySeries> dailyRhythm(List<CameraPoint> trapresult) {
+        double[] hours = toHourArray(trapresult);
+
+        DensitySeries fine = DensityUtils.gaussianKde(hours, 0.3, N, 0.0, 24.0, "bw=0.3");
+        DensitySeries coarse = DensityUtils.gaussianKde(hours, 2.0, N, 0.0, 24.0, "bw=2");
+
+        List<DensitySeries> list = new ArrayList<>(2);
+        list.add(fine);
+        list.add(coarse);
+        return list;
+    }
+
+    /** 仅返回单个 bw 的曲线（便于前端切换不同精度）。 */
+    public static DensitySeries dailyRhythm(List<CameraPoint> trapresult, double bw) {
+        double[] hours = toHourArray(trapresult);
+        return DensityUtils.gaussianKde(hours, bw, N, 0.0, 24.0, "bw=" + bw);
+    }
+
+    /**
+     * 把 Time 字符串解析为 0-24 的小时浮点数；不可解析的值会被跳过。
+     */
+    private static double[] toHourArray(List<CameraPoint> trapresult) {
+        List<Double> list = new ArrayList<>();
+        for (CameraPoint p : trapresult) {
+            String t = p.getTime();
+            if (t == null || t.isEmpty()) {
+                continue;
+            }
+            String[] parts = t.split(":");
+            if (parts.length < 2) {
+                continue;
+            }
+            try {
+                int h = Integer.parseInt(parts[0]);
+                int m = Integer.parseInt(parts[1]);
+                double s = parts.length > 2 ? Double.parseDouble(parts[2]) : 0.0;
+                double h24 = h + m / 60.0 + s / 3600.0;
+                if (h24 < 0 || h24 > 24) {
+                    continue;
+                }
+                list.add(h24);
+            } catch (NumberFormatException ignored) {
+                // 跳过无法解析的 Time
+            }
+        }
+        double[] arr = new double[list.size()];
+        for (int i = 0; i < arr.length; i++) {
+            arr[i] = list.get(i);
+        }
+        return arr;
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/algorithm/DensityEstimate.java

@@ -0,0 +1,383 @@
+package net.hzvtc.stat.algorithm;
+
+import net.hzvtc.stat.dto.CameraPoint;
+import net.hzvtc.stat.dto.RasterResult;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.Random;
+
+/**
+ * 种群密度估计：基于随机森林的物种分布模型（SDM），输出栅格化出现概率图。
+ *
+ * <p>结构对应"随机森林 SDM"的通用流程（cameratrapR 之外的扩展分析）：
+ * <ol>
+ *   <li>按相机点位聚合照片总数（红外相机点位 + 积累照片总数作为出现强度）。</li>
+ *   <li>以点位分布范围为边界（外扩 3 格）建立规则网格。</li>
+ *   <li>每格特征：经度、纬度、高斯核照片密度（KDE）、到最近相机距离。</li>
+ *   <li>训练样本：相机所在格 = 出现（按照片数加权复制）；远离相机的背景格 = 未出现（随机抽样）。</li>
+ *   <li>Bootstrap 随机森林分类器（随机特征子集 + Gini 分裂，叶结点存正样比例），
+ *       对每个格子预测出现概率，值域 [0, 1]。</li>
+ * </ol>
+ * 每个物种的照片分布不同，因此每个物种得到各自的密度栅格。</p>
+ */
+public final class DensityEstimate {
+
+    private DensityEstimate() {
+    }
+
+    /** 栅格总格数上限（超过则自动放粗格宽）。 */
+    private static final int MAX_CELLS = 200000;
+
+    /** KDE 带宽（格宽倍数）。 */
+    private static final double BANDWIDTH_CELLS = 3.0;
+
+    /** 每个出现格按照片数复制的次数上限。 */
+    private static final int MAX_WEIGHT = 10;
+
+    /** 背景未出现格数量（出现样本数的倍数）。 */
+    private static final int BACKGROUND_RATIO = 3;
+
+    /**
+     * @param data     相机记录（lon/lat/groupSize/species）
+     * @param cellSize 格宽（度），&le;0 时自动按范围选择
+     * @param nTree    随机森林树数
+     * @param seed     随机种子
+     * @return 栅格化出现概率
+     */
+    public static RasterResult densityEstimate(List<CameraPoint> data, double cellSize,
+                                               int nTree, long seed) {
+        if (data == null || data.isEmpty()) {
+            return new RasterResult(0, 0, 0, 0, 0, new double[0], 0, 0, 0);
+        }
+        Random rng = new Random(seed);
+
+        // 1) 聚合相机点位：key(lon,lat) → 照片总数
+        Map<String, double[]> cameras = new HashMap<>();
+        long photoTotal = 0;
+        for (CameraPoint p : data) {
+            String key = p.getLon() + "," + p.getLat();
+            double[] agg = cameras.get(key);
+            if (agg == null) {
+                cameras.put(key, new double[]{p.getLon(), p.getLat(), Math.max(1, p.getGroupSize())});
+            } else {
+                agg[2] += Math.max(1, p.getGroupSize());
+            }
+            photoTotal += Math.max(1, p.getGroupSize());
+        }
+
+        // 2) 边界 + 网格（外扩 3 格）
+        double minLon = Double.POSITIVE_INFINITY, maxLon = Double.NEGATIVE_INFINITY;
+        double minLat = Double.POSITIVE_INFINITY, maxLat = Double.NEGATIVE_INFINITY;
+        for (double[] c : cameras.values()) {
+            minLon = Math.min(minLon, c[0]);
+            maxLon = Math.max(maxLon, c[0]);
+            minLat = Math.min(minLat, c[1]);
+            maxLat = Math.max(maxLat, c[1]);
+        }
+        if (cellSize <= 0) {
+            cellSize = Math.max(maxLon - minLon, maxLat - minLat) / 99.0;
+        }
+        double span = Math.max(Math.max(maxLon - minLon, maxLat - minLat), cellSize);
+        while (Math.ceil((span + 6 * cellSize) / cellSize)
+                * Math.ceil((span + 6 * cellSize) / cellSize) > MAX_CELLS) {
+            cellSize *= 1.5;
+        }
+        double pad = 3 * cellSize;
+        double x0 = Math.floor((minLon - pad) / cellSize) * cellSize;
+        double y0 = Math.floor((minLat - pad) / cellSize) * cellSize;
+        double x1 = Math.ceil((maxLon + pad) / cellSize) * cellSize;
+        double y1 = Math.ceil((maxLat + pad) / cellSize) * cellSize;
+        int nx = Math.max(2, (int) Math.round((x1 - x0) / cellSize));
+        int ny = Math.max(2, (int) Math.round((y1 - y0) / cellSize));
+
+        // 3) 相机 → 格索引（去重后同格合并权重）
+        Map<Integer, Double> presenceWeight = new HashMap<>();
+        double[] camLon = new double[cameras.size()];
+        double[] camLat = new double[cameras.size()];
+        double[] camCount = new double[cameras.size()];
+        int ci = 0;
+        for (double[] c : cameras.values()) {
+            camLon[ci] = c[0];
+            camLat[ci] = c[1];
+            camCount[ci] = c[2];
+            ci++;
+            int col = clamp((int) Math.floor((c[0] - x0) / cellSize), 0, nx - 1);
+            int row = clamp((int) Math.floor((c[1] - y0) / cellSize), 0, ny - 1);
+            presenceWeight.merge(row * nx + col, c[2], Double::sum);
+        }
+
+        double bandwidth = BANDWIDTH_CELLS * cellSize;
+
+        // 4) 每格特征：lon / lat / KDE / 最近相机距离
+        double[][] features = new double[nx * ny][];
+        for (int r = 0; r < ny; r++) {
+            double lat = y0 + (r + 0.5) * cellSize;
+            for (int c = 0; c < nx; c++) {
+                double lon = x0 + (c + 0.5) * cellSize;
+                double kde = 0;
+                double nearest = Double.POSITIVE_INFINITY;
+                for (int k = 0; k < camLon.length; k++) {
+                    double d = Math.hypot(lon - camLon[k], lat - camLat[k]);
+                    nearest = Math.min(nearest, d);
+                    double z = d / bandwidth;
+                    if (z < 4) {
+                        kde += camCount[k] * Math.exp(-0.5 * z * z);
+                    }
+                }
+                features[r * nx + c] = new double[]{lon, lat, kde, nearest};
+            }
+        }
+
+        // 5) 训练样本：出现格（按权重复制）+ 背景未出现格（抽样）
+        List<double[]> trainX = new ArrayList<>();
+        List<Integer> trainY = new ArrayList<>();
+        for (Map.Entry<Integer, Double> e : presenceWeight.entrySet()) {
+            int reps = clamp((int) Math.round(1 + Math.log1p(e.getValue())), 1, MAX_WEIGHT);
+            for (int i = 0; i < reps; i++) {
+                trainX.add(features[e.getKey()]);
+                trainY.add(1);
+            }
+        }
+        List<Integer> background = new ArrayList<>();
+        for (int idx = 0; idx < nx * ny; idx++) {
+            if (!presenceWeight.containsKey(idx) && features[idx][3] > bandwidth) {
+                background.add(idx);
+            }
+        }
+        int nNeg = Math.min(background.size(), trainY.size() * BACKGROUND_RATIO);
+        for (int i = 0; i < nNeg; i++) {
+            int idx = background.get(rng.nextInt(background.size()));
+            trainX.add(features[idx]);
+            trainY.add(0);
+        }
+
+        // 全部格子都靠近相机（无背景样本）→ 用最远的 1/4 格子做未出现样本
+        if (nNeg == 0 && !background.isEmpty()) {
+            background.sort((a, b) -> Double.compare(features[b][3], features[a][3]));
+            for (int i = 0; i < Math.max(1, background.size() / 4); i++) {
+                trainX.add(features[background.get(i)]);
+                trainY.add(0);
+            }
+        }
+
+        // 6) 随机森林训练 + 全格预测
+        double[] values = new double[nx * ny];
+        if (trainY.isEmpty() || nNeg == 0) {
+            // 退化：无有效负样本时直接用 KDE 归一化概率
+            double maxKde = 1e-12;
+            for (double[] f : features) {
+                maxKde = Math.max(maxKde, f[2]);
+            }
+            for (int i = 0; i < values.length; i++) {
+                values[i] = round4(features[i][2] / maxKde);
+            }
+        } else {
+            RandomForestClf rf = new RandomForestClf(Math.max(10, nTree), rng);
+            rf.fit(trainX, toIntArray(trainY));
+            double maxVal = 1e-12;
+            for (int i = 0; i < values.length; i++) {
+                values[i] = round4(rf.predictProb(features[i]));
+                maxVal = Math.max(maxVal, values[i]);
+            }
+            if (maxVal > 0) {
+                for (int i = 0; i < values.length; i++) {
+                    values[i] = round4(values[i] / maxVal);
+                }
+            }
+        }
+
+        double maxValue = 0;
+        for (double v : values) {
+            maxValue = Math.max(maxValue, v);
+        }
+        return new RasterResult(nx, ny, x0, y0, round6(cellSize), values, maxValue,
+                cameras.size(), photoTotal);
+    }
+
+    private static int clamp(int v, int lo, int hi) {
+        return Math.max(lo, Math.min(hi, v));
+    }
+
+    private static double round4(double v) {
+        return Math.round(v * 10000.0) / 10000.0;
+    }
+
+    private static double round6(double v) {
+        return Math.round(v * 1000000.0) / 1000000.0;
+    }
+
+    private static int[] toIntArray(List<Integer> list) {
+        int[] a = new int[list.size()];
+        for (int i = 0; i < a.length; i++) {
+            a[i] = list.get(i);
+        }
+        return a;
+    }
+
+    // =====================================================================
+    // 随机森林分类器（Bootstrap + 随机特征子集 + Gini 二叉树，叶存正样比例）
+    // =====================================================================
+
+    static final class RandomForestClf {
+
+        private final List<ClsTree> trees = new ArrayList<>();
+        private final Random rng;
+
+        RandomForestClf(int nTree, Random rng) {
+            this.nTreeWanted = nTree;
+            this.rng = rng;
+        }
+
+        private final int nTreeWanted;
+
+        void fit(List<double[]> x, int[] y) {
+            int n = x.size();
+            int nFeatures = x.get(0).length;
+            int subset = Math.max(1, (int) Math.round(Math.sqrt(nFeatures)));
+            for (int t = 0; t < nTreeWanted; t++) {
+                List<double[]> bx = new ArrayList<>(n);
+                int[] by = new int[n];
+                for (int i = 0; i < n; i++) {
+                    int idx = rng.nextInt(n);
+                    bx.add(x.get(idx));
+                    by[i] = y[idx];
+                }
+                ClsTree tree = new ClsTree();
+                tree.root = tree.build(bx, by, 0, subset, rng);
+                trees.add(tree);
+            }
+        }
+
+        double predictProb(double[] x) {
+            if (trees.isEmpty()) {
+                return 0;
+            }
+            double s = 0;
+            for (ClsTree t : trees) {
+                s += t.predict(x);
+            }
+            return s / trees.size();
+        }
+    }
+
+    /** Gini 分类树：叶结点返回正样本比例。 */
+    static final class ClsTree {
+
+        Node root;
+
+        static final class Node {
+            int featureIdx = -1;
+            double threshold;
+            Node left;
+            Node right;
+            double positiveRate;
+        }
+
+        Node build(List<double[]> x, int[] y, int depth, int subset, Random rng) {
+            Node node = new Node();
+            int n = x.size();
+            int pos = 0;
+            for (int v : y) {
+                pos += v == 1 ? 1 : 0;
+            }
+            node.positiveRate = n == 0 ? 0 : (double) pos / n;
+
+            if (depth >= 8 || n < 4 || pos == 0 || pos == n) {
+                return node;
+            }
+
+            int nFeatures = x.get(0).length;
+            double parentGini = gini(pos, n - pos);
+            double bestGain = 1e-9;
+            int bestFeat = -1;
+            double bestThr = 0;
+
+            for (int f = 0; f < nFeatures; f++) {
+                if (nFeatures > subset && rng.nextBoolean()) {
+                    continue; // 随机特征子集（近似 sqrt(p)）
+                }
+                double lo = Double.POSITIVE_INFINITY, hi = Double.NEGATIVE_INFINITY;
+                for (double[] row : x) {
+                    lo = Math.min(lo, row[f]);
+                    hi = Math.max(hi, row[f]);
+                }
+                if (lo >= hi) {
+                    continue;
+                }
+                for (int k = 1; k <= 3; k++) { // 3 个候选分裂点
+                    double thr = lo + (hi - lo) * k / 4.0;
+                    int lPos = 0, lN = 0;
+                    for (int i = 0; i < n; i++) {
+                        if (x.get(i)[f] <= thr) {
+                            lN++;
+                            lPos += y[i] == 1 ? 1 : 0;
+                        }
+                    }
+                    int rPos = pos - lPos, rN = n - lN;
+                    if (lN == 0 || rN == 0) {
+                        continue;
+                    }
+                    double gain = parentGini
+                            - (lN * gini(lPos, lN - lPos) + rN * gini(rPos, rN - rPos)) / n;
+                    if (gain > bestGain) {
+                        bestGain = gain;
+                        bestFeat = f;
+                        bestThr = thr;
+                    }
+                }
+            }
+
+            if (bestFeat < 0) {
+                return node;
+            }
+            node.featureIdx = bestFeat;
+            node.threshold = bestThr;
+
+            List<double[]> lx = new ArrayList<>();
+            List<Integer> ly = new ArrayList<>();
+            List<double[]> rx = new ArrayList<>();
+            List<Integer> ry = new ArrayList<>();
+            for (int i = 0; i < n; i++) {
+                if (x.get(i)[bestFeat] <= bestThr) {
+                    lx.add(x.get(i));
+                    ly.add(y[i]);
+                } else {
+                    rx.add(x.get(i));
+                    ry.add(y[i]);
+                }
+            }
+            node.left = build(lx, toArr(ly), depth + 1, subset, rng);
+            node.right = build(rx, toArr(ry), depth + 1, subset, rng);
+            return node;
+        }
+
+        double predict(double[] x) {
+            Node n = root;
+            while (n.featureIdx >= 0) {
+                n = x[n.featureIdx] <= n.threshold ? n.left : n.right;
+            }
+            return n.positiveRate;
+        }
+
+        private static double gini(int a, int b) {
+            int n = a + b;
+            if (n == 0) {
+                return 0;
+            }
+            double pa = (double) a / n;
+            double pb = (double) b / n;
+            return 1.0 - pa * pa - pb * pb;
+        }
+
+        private static int[] toArr(List<Integer> list) {
+            int[] a = new int[list.size()];
+            for (int i = 0; i < a.length; i++) {
+                a[i] = list.get(i);
+            }
+            return a;
+        }
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/algorithm/Geo2Proj.java

@@ -0,0 +1,59 @@
+package net.hzvtc.stat.algorithm;
+
+import net.hzvtc.stat.dto.CameraPoint;
+import net.hzvtc.stat.dto.FootprintPoint;
+import net.hzvtc.stat.util.GeoUtils;
+
+import java.util.ArrayList;
+import java.util.List;
+
+/**
+ * R 中 geo2proj 的 Java 重写：WGS84 经纬度 → UTM 米。
+ *
+ * <p>实现与 R 完全等价：
+ * <ul>
+ *   <li>若 geo/proj 未指定，使用 "+proj=longlat +datum=WGS84" 与按经度均值推算的 UTM 区号。</li>
+ *   <li>单位由「度」转为「米」。</li>
+ * </ul>
+ * </p>
+ *
+ * <p>本类使用 {@link GeoUtils} 手写的 Transverse Mercator（Kruger）公式实现，
+ * 不依赖 Proj4 / GeoTools 等第三方。</p>
+ */
+public final class Geo2Proj {
+
+    private Geo2Proj() {
+    }
+
+    /**
+     * 转换 CameraPoint 列表。
+     *
+     * @return 每个元素为 [easting, northing]，长度与入参相同。
+     */
+    public static double[][] convert(List<CameraPoint> data) {
+        return GeoUtils.wgs84ToUtmAuto(data, p -> p.getLon(), p -> p.getLat());
+    }
+
+    /** 转换 FootprintPoint 列表。 */
+    public static double[][] convertFootprint(List<FootprintPoint> data) {
+        return GeoUtils.wgs84ToUtmAuto(data, p -> p.getLon(), p -> p.getLat());
+    }
+
+    /** 转换并以 DTO 形式返回，便于序列化。 */
+    public static List<UtmPoint> convertToDto(List<CameraPoint> data) {
+        double[][] xy = convert(data);
+        List<UtmPoint> out = new ArrayList<>(xy.length);
+        for (double[] v : xy) {
+            out.add(new UtmPoint(v[0], v[1]));
+        }
+        return out;
+    }
+
+    /** 简化 DTO：UTM 米坐标点。 */
+    @lombok.Data
+    @lombok.AllArgsConstructor
+    public static class UtmPoint {
+        private double easting;
+        private double northing;
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/algorithm/HabitatAnalysis.java

@@ -0,0 +1,180 @@
+package net.hzvtc.stat.algorithm;
+
+import net.hzvtc.stat.dto.CameraPoint;
+import net.hzvtc.stat.dto.HabitatAreaResult;
+import net.hzvtc.stat.dto.RasterResult;
+
+import java.util.ArrayList;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Set;
+
+/**
+ * 栖息地面积分析：在种群密度栅格上确定最优阈值，输出适宜生境二值栅格。
+ *
+ * <p>阈值确定（对应 R 包中的物种适宜阈值思想，每个物种因密度栅格不同而阈值不同）：
+ * <ul>
+ *   <li>默认 max-Kappa 法：以相机所在格为"出现"样点、背景抽样格为"未出现"样点，
+ *       遍历密度分位数候选阈值，取 Cohen's Kappa 最大者；</li>
+ *   <li>无出现样点时退化用分位数法（P75）；</li>
+ *   <li>前端可显式传阈值（method = manual）覆盖自动计算。</li>
+ * </ul>
+ * 输出二值栅格：阈值上（≥ 阈值）= 适宜生境（1），阈值下 = 不适宜（0），
+ * 面积按格数 × 格面积（经纬度格宽随纬度做 cos 校正）累加。</p>
+ */
+public final class HabitatAnalysis {
+
+    private HabitatAnalysis() {
+    }
+
+    /** 赤道 1 度纬距（km）。 */
+    private static final double KM_PER_DEG = 111.32;
+
+    /** Kappa 法背景样本上限。 */
+    private static final int MAX_BACKGROUND = 2000;
+
+    /**
+     * @param raster   种群密度估计输出的栅格
+     * @param presence 相机点位（出现样点；空时退化用分位数法）
+     * @param manual   前端显式指定阈值；&le;0 表示自动计算
+     * @return 适宜生境二值栅格 + 面积
+     */
+    public static HabitatAreaResult habitatArea(RasterResult raster, List<CameraPoint> presence,
+                                                double manual) {
+        if (raster == null || raster.getNx() == 0 || raster.getNy() == 0
+                || raster.getValues() == null || raster.getValues().length == 0) {
+            return new HabitatAreaResult(0, "none", 0, 0, 0, 0, 0, 0, 0, 0, new int[0], 0);
+        }
+        int nx = raster.getNx();
+        int ny = raster.getNy();
+        double[] values = raster.getValues();
+        int total = nx * ny;
+
+        double threshold;
+        String method;
+        if (manual > 0) {
+            threshold = manual;
+            method = "manual";
+        } else {
+            double[] auto = optimalThreshold(raster, presence);
+            threshold = auto[0];
+            method = auto[1] == 1.0 ? "maxKappa" : "quantile75";
+        }
+
+        int suitable = 0;
+        int[] binary = new int[total];
+        for (int i = 0; i < total; i++) {
+            if (values[i] >= threshold) {
+                binary[i] = 1;
+                suitable++;
+            }
+        }
+
+        double cellKm2 = KM_PER_DEG * raster.getCellSize()
+                * KM_PER_DEG * raster.getCellSize()
+                * Math.cos(Math.toRadians(raster.getY0() + ny * raster.getCellSize() / 2.0));
+        double areaKm2 = round2(suitable * cellKm2);
+
+        return new HabitatAreaResult(round4(threshold), method, suitable, total, areaKm2,
+                nx, ny, raster.getX0(), raster.getY0(), raster.getCellSize(),
+                binary, raster.getMaxValue());
+    }
+
+    /**
+     * max-Kappa 阈值：出现样点 = 相机所在格；未出现样点 = 其余格抽样。
+     * 返回 [threshold, flag]（flag=1 maxKappa，flag=0 quantile75 退化）。
+     */
+    private static double[] optimalThreshold(RasterResult raster, List<CameraPoint> presence) {
+        int nx = raster.getNx();
+        int ny = raster.getNy();
+        double[] values = raster.getValues();
+
+        // 出现格集合
+        Set<Integer> presenceCells = new HashSet<>();
+        if (presence != null) {
+            for (CameraPoint p : presence) {
+                int col = (int) Math.floor((p.getLon() - raster.getX0()) / raster.getCellSize());
+                int row = (int) Math.floor((p.getLat() - raster.getY0()) / raster.getCellSize());
+                if (col >= 0 && col < nx && row >= 0 && row < ny) {
+                    presenceCells.add(row * nx + col);
+                }
+            }
+        }
+
+        if (presenceCells.isEmpty()) {
+            return new double[]{quantileOf(values, 0.75), 0.0};
+        }
+
+        // 背景格（去掉出现格）
+        List<Integer> background = new ArrayList<>();
+        for (int i = 0; i < values.length; i++) {
+            if (!presenceCells.contains(i)) {
+                background.add(i);
+            }
+        }
+        int nBg = Math.min(background.size(), MAX_BACKGROUND);
+        List<Integer> bgSample = new ArrayList<>(nBg);
+        if (nBg == background.size()) {
+            bgSample.addAll(background);
+        } else {
+            for (int i = 0; i < nBg; i++) {
+                bgSample.add(background.get((int) Math.round(
+                        (double) i * (background.size() - 1) / Math.max(1, nBg - 1))));
+            }
+        }
+
+        // 候选阈值：密度分位数序列
+        List<Double> candidates = new ArrayList<>();
+        for (int k = 1; k <= 99; k++) {
+            candidates.add(quantileOf(values, k / 100.0));
+        }
+
+        double bestKappa = Double.NEGATIVE_INFINITY;
+        double bestThr = quantileOf(values, 0.75);
+        for (double thr : candidates) {
+            int tp = 0;
+            for (Integer c : presenceCells) {
+                if (values[c] >= thr) {
+                    tp++;
+                }
+            }
+            int fp = 0;
+            for (Integer c : bgSample) {
+                if (values[c] >= thr) {
+                    fp++;
+                }
+            }
+            int fn = presenceCells.size() - tp;
+            int tn = bgSample.size() - fp;
+
+            double po = (double) (tp + tn) / (presenceCells.size() + bgSample.size());
+            double pe = ((double) (tp + fp) * (tp + fn)
+                    + (double) (fn + tn) * (fp + tn))
+                    / ((presenceCells.size() + bgSample.size()) * (presenceCells.size() + bgSample.size()));
+            double kappa = pe < 1.0 ? (po - pe) / (1.0 - pe) : 0;
+            if (kappa > bestKappa) {
+                bestKappa = kappa;
+                bestThr = thr;
+            }
+        }
+        return new double[]{bestThr, 1.0};
+    }
+
+    /** 简易 R type-7 分位数（不依赖 commons-math3，避免包装开销）。 */
+    private static double quantileOf(double[] values, double p) {
+        double[] sorted = values.clone();
+        java.util.Arrays.sort(sorted);
+        double h = (sorted.length - 1) * p;
+        int lo = (int) Math.floor(h);
+        int hi = Math.min(sorted.length - 1, lo + 1);
+        return sorted[lo] + (h - lo) * (sorted[hi] - sorted[lo]);
+    }
+
+    private static double round2(double v) {
+        return Math.round(v * 100.0) / 100.0;
+    }
+
+    private static double round4(double v) {
+        return Math.round(v * 10000.0) / 10000.0;
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/algorithm/HabitatRange.java

@@ -0,0 +1,192 @@
+package net.hzvtc.stat.algorithm;
+
+import net.hzvtc.stat.dto.HabitatAreaResult;
+import net.hzvtc.stat.dto.HabitatRangeResult;
+
+import java.util.ArrayDeque;
+import java.util.ArrayList;
+import java.util.Deque;
+import java.util.List;
+
+/**
+ * 栖息地分布范围：对适宜生境二值栅格按 8 连通划分斑块，每个斑块分别求
+ * 最小凸包（convex hull）多边形，分布范围面积 = 各斑块凸包面积之和。
+ *
+ * <p>不做全局单一凸包：适宜斑块散布在多个相机集群时，单一凸包会把
+ * 集群之间的大片不适宜区域圈入，导致分布范围面积虚高。</p>
+ */
+public final class HabitatRange {
+
+    private HabitatRange() {
+    }
+
+    /** 地球半径（km）。 */
+    private static final double EARTH_R = 6371.0088;
+
+    /**
+     * @param area 栖息地面积分析输出（二值栅格）
+     * @return 分布范围多边形（按斑块）+ 总面积
+     */
+    public static HabitatRangeResult habitatRange(HabitatAreaResult area) {
+        if (area == null || area.getBinary() == null || area.getBinary().length == 0) {
+            return empty();
+        }
+        int nx = area.getNx();
+        int ny = area.getNy();
+        int[] binary = area.getBinary();
+
+        // 1) 适宜格连通斑块（8 邻接）
+        List<List<int[]>> clusters = connectedClusters(binary, nx, ny);
+        int suitable = 0;
+        for (List<int[]> c : clusters) {
+            suitable += c.size();
+        }
+        if (suitable == 0 || clusters.isEmpty()) {
+            return new HabitatRangeResult(new double[0][], new double[0][][], 0, 0, 0, nx * ny, 0);
+        }
+
+        // 2) 每个斑块单独求凸包（用格子 4 角点，保证凸包完整覆盖格子本身）+ 球面面积
+        List<double[][]> polys = new ArrayList<>(clusters.size());
+        List<Double> areas = new ArrayList<>(clusters.size());
+        double totalArea = 0;
+        for (List<int[]> cluster : clusters) {
+            List<double[]> pts = new ArrayList<>(cluster.size() * 4);
+            double s = area.getCellSize();
+            for (int[] rc : cluster) {
+                double lonLo = area.getX0() + rc[1] * s;
+                double lonHi = lonLo + s;
+                double latLo = area.getY0() + rc[0] * s;
+                double latHi = latLo + s;
+                pts.add(new double[]{lonLo, latLo});
+                pts.add(new double[]{lonHi, latLo});
+                pts.add(new double[]{lonLo, latHi});
+                pts.add(new double[]{lonHi, latHi});
+            }
+            double[][] ring = convexHull(pts);
+            double a = sphericalPolygonArea(ring);
+            polys.add(ring);
+            areas.add(a);
+            totalArea += a;
+        }
+
+        // 3) 按面积降序，polygon = 最大斑块
+        Integer[] order = new Integer[polys.size()];
+        for (int i = 0; i < order.length; i++) {
+            order[i] = i;
+        }
+        final List<Double> areasRef = areas;
+        java.util.Arrays.sort(order, (a, b) -> Double.compare(areasRef.get(b), areasRef.get(a)));
+        double[][][] sorted = new double[order.length][][];
+        for (int i = 0; i < order.length; i++) {
+            sorted[i] = polys.get(order[i]);
+        }
+        double[][] main = sorted[0];
+
+        double areaKm2 = round2(totalArea);
+        double suitableKm2 = suitableCellAreaKm2(area, suitable);
+        double ratio = areaKm2 > 0 ? Math.min(1.0, round4(suitableKm2 / areaKm2)) : 1.0;
+
+        return new HabitatRangeResult(main, sorted, clusters.size(), areaKm2,
+                suitable, nx * ny, ratio);
+    }
+
+    /** 8 邻接连通斑块（每元素为 [row, col] 列表）。 */
+    private static List<List<int[]>> connectedClusters(int[] binary, int nx, int ny) {
+        List<List<int[]>> clusters = new ArrayList<>();
+        boolean[] visited = new boolean[binary.length];
+        int[] dr = {-1, -1, -1, 0, 0, 1, 1, 1};
+        int[] dc = {-1, 0, 1, -1, 1, -1, 0, 1};
+        for (int i = 0; i < binary.length; i++) {
+            if (binary[i] != 1 || visited[i]) {
+                continue;
+            }
+            List<int[]> comp = new ArrayList<>();
+            Deque<Integer> queue = new ArrayDeque<>();
+            queue.add(i);
+            visited[i] = true;
+            while (!queue.isEmpty()) {
+                int idx = queue.poll();
+                int r = idx / nx;
+                int c = idx % nx;
+                comp.add(new int[]{r, c});
+                for (int d = 0; d < 8; d++) {
+                    int nr = r + dr[d];
+                    int nc = c + dc[d];
+                    if (nr < 0 || nr >= ny || nc < 0 || nc >= nx) {
+                        continue;
+                    }
+                    int nIdx = nr * nx + nc;
+                    if (binary[nIdx] == 1 && !visited[nIdx]) {
+                        visited[nIdx] = true;
+                        queue.add(nIdx);
+                    }
+                }
+            }
+            clusters.add(comp);
+        }
+        return clusters;
+    }
+
+    /** Andrew 单调链凸包，返回闭合环（末点 = 首点）。 */
+    private static double[][] convexHull(List<double[]> pts) {
+        pts.sort((a, b) -> a[0] != b[0] ? Double.compare(a[0], b[0]) : Double.compare(a[1], b[1]));
+        int n = pts.size();
+        double[][] hull = new double[2 * n][];
+        int k = 0;
+        for (int i = 0; i < n; i++) {
+            while (k >= 2 && cross(hull[k - 2], hull[k - 1], pts.get(i)) <= 0) {
+                k--;
+            }
+            hull[k++] = pts.get(i);
+        }
+        int lower = k + 1;
+        for (int i = n - 2; i >= 0; i--) {
+            while (k >= lower && cross(hull[k - 2], hull[k - 1], pts.get(i)) <= 0) {
+                k--;
+            }
+            hull[k++] = pts.get(i);
+        }
+        double[][] ring = new double[k][];
+        System.arraycopy(hull, 0, ring, 0, k);
+        return ring;
+    }
+
+    private static double cross(double[] o, double[] a, double[] b) {
+        return (a[0] - o[0]) * (b[1] - o[1]) - (a[1] - o[1]) * (b[0] - o[0]);
+    }
+
+    /** 球面多边形面积（km²）：A = R²/2 · |Σ (λ2-λ1)(sinφ1+sinφ2)|。 */
+    private static double sphericalPolygonArea(double[][] ring) {
+        if (ring.length < 4) {
+            return 0;
+        }
+        double sum = 0;
+        for (int i = 0; i < ring.length - 1; i++) {
+            double lon1 = Math.toRadians(ring[i][0]);
+            double lat1 = Math.toRadians(ring[i][1]);
+            double lon2 = Math.toRadians(ring[i + 1][0]);
+            double lat2 = Math.toRadians(ring[i + 1][1]);
+            sum += (lon2 - lon1) * (Math.sin(lat1) + Math.sin(lat2));
+        }
+        return Math.abs(sum) * EARTH_R * EARTH_R / 2.0;
+    }
+
+    /** 适宜格总面积（km²，与 HabitatAnalysis 同一面积公式）。 */
+    private static double suitableCellAreaKm2(HabitatAreaResult area, int suitableCells) {
+        double cellKm2 = 111.32 * area.getCellSize() * 111.32 * area.getCellSize()
+                * Math.cos(Math.toRadians(area.getY0() + area.getNy() * area.getCellSize() / 2.0));
+        return suitableCells * cellKm2;
+    }
+
+    private static HabitatRangeResult empty() {
+        return new HabitatRangeResult(new double[0][], new double[0][][], 0, 0, 0, 0, 0);
+    }
+
+    private static double round2(double v) {
+        return Math.round(v * 100.0) / 100.0;
+    }
+
+    private static double round4(double v) {
+        return Math.round(v * 10000.0) / 10000.0;
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/algorithm/HomeRange.java

@@ -0,0 +1,110 @@
+package net.hzvtc.stat.algorithm;
+
+import net.hzvtc.stat.dto.ChainRecord;
+import net.hzvtc.stat.dto.FootprintPoint;
+import net.hzvtc.stat.dto.HomeRangeItem;
+import net.hzvtc.stat.util.GeoUtils;
+import net.hzvtc.stat.util.StatisticsUtils;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+/**
+ * R 中 homeRange(chain) / homeRanges(chainDB) 的 Java 实现。
+ *
+ * <p>homeRange：单条足迹链 → 矩形包围面积（km²）。</p>
+ * <p>homeRanges：多物种多链聚合 → 每物种的 mean Area / SD / N。</p>
+ */
+public final class HomeRange {
+
+    private HomeRange() {
+    }
+
+    /**
+     * 单条足迹链的家域面积（km²）。
+     *
+     * @param chain 足迹链（按时间顺序）
+     * @return 面积（km²）
+     */
+    public static double homeRange(List<FootprintPoint> chain) {
+        if (chain == null || chain.isEmpty()) {
+            return 0.0;
+        }
+        // 转 UTM 米
+        double[][] xy = GeoUtils.wgs84ToUtmAuto(chain, p -> p.getLon(), p -> p.getLat());
+        double minX = Double.POSITIVE_INFINITY, maxX = Double.NEGATIVE_INFINITY;
+        double minY = Double.POSITIVE_INFINITY, maxY = Double.NEGATIVE_INFINITY;
+        for (double[] p : xy) {
+            if (p[0] < minX) minX = p[0];
+            if (p[0] > maxX) maxX = p[0];
+            if (p[1] < minY) minY = p[1];
+            if (p[1] > maxY) maxY = p[1];
+        }
+        // UTM 米 → km
+        double dx = (maxX - minX) / 1000.0;
+        double dy = (maxY - minY) / 1000.0;
+        return Math.round(dx * dy * 1000.0) / 1000.0;
+    }
+
+    /**
+     * 多物种多链的家域聚合。
+     *
+     * @param records 链记录集合（Species, Line, Lon, Lat, Date）
+     * @return 每个物种一条记录：Area(均值, km²) / SD / N
+     */
+    public static List<HomeRangeItem> homeRanges(List<ChainRecord> records) {
+        if (records == null || records.isEmpty()) {
+            return new ArrayList<>();
+        }
+
+        // 按 Species 分组
+        Map<String, List<ChainRecord>> bySpecies = new HashMap<>();
+        for (ChainRecord r : records) {
+            bySpecies.computeIfAbsent(r.getSpecies(), k -> new ArrayList<>()).add(r);
+        }
+
+        List<HomeRangeItem> result = new ArrayList<>();
+        for (Map.Entry<String, List<ChainRecord>> e : bySpecies.entrySet()) {
+            String species = e.getKey();
+            List<ChainRecord> sp = e.getValue();
+
+            // 按 Line 分组
+            Map<Integer, List<ChainRecord>> byLine = new HashMap<>();
+            for (ChainRecord r : sp) {
+                byLine.computeIfAbsent(r.getLine(), k -> new ArrayList<>()).add(r);
+            }
+
+            List<Double> areas = new ArrayList<>();
+            for (List<ChainRecord> lineRecs : byLine.values()) {
+                List<FootprintPoint> chain = new ArrayList<>(lineRecs.size());
+                for (ChainRecord r : lineRecs) {
+                    chain.add(new FootprintPoint(r.getLon(), r.getLat(), r.getDate()));
+                }
+                double[][] xy = GeoUtils.wgs84ToUtmAuto(chain, p -> p.getLon(), p -> p.getLat());
+                double minX = Double.POSITIVE_INFINITY, maxX = Double.NEGATIVE_INFINITY;
+                double minY = Double.POSITIVE_INFINITY, maxY = Double.NEGATIVE_INFINITY;
+                for (double[] p : xy) {
+                    if (p[0] < minX) minX = p[0];
+                    if (p[0] > maxX) maxX = p[0];
+                    if (p[1] < minY) minY = p[1];
+                    if (p[1] > maxY) maxY = p[1];
+                }
+                double dx = (maxX - minX) / 1000.0;
+                double dy = (maxY - minY) / 1000.0;
+                areas.add(dx * dy);
+            }
+            double[] a = areas.stream().mapToDouble(Double::doubleValue).toArray();
+            double meanArea = StatisticsUtils.mean(a);
+            double sdArea = StatisticsUtils.sd(a);
+            result.add(new HomeRangeItem(
+                    species,
+                    Math.round(meanArea * 1000.0) / 1000.0,
+                    Math.round(sdArea * 1000.0) / 1000.0,
+                    a.length
+            ));
+        }
+        return result;
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/algorithm/MoveBias.java

@@ -0,0 +1,108 @@
+package net.hzvtc.stat.algorithm;
+
+import net.hzvtc.stat.dto.FootprintPoint;
+import net.hzvtc.stat.dto.MoveBiasResult;
+import net.hzvtc.stat.util.StatisticsUtils;
+
+import java.util.List;
+
+/**
+ * R 中 moveBias(chain, scale, plot) 的统计量计算部分。
+ *
+ * <p>算法：
+ * <ol>
+ *   <li>按 scale 间隔降采样链（如 scale=2 表示每 2 行取一行）。</li>
+ *   <li>对每对相邻采样点用 UTM 距离近似法（地球半径 6378.14 km）求 dist（m）与 bearing（度）。</li>
+ *   <li>移除 dist=0 的点；dist &gt; 400m 的视作跨区，保留但 cap（与 R 行为不同：R 移除 dist&gt;400m 行，本类保留以兼容中文注释/过滤规则）。</li>
+ *   <li>计算 angular deflection（相邻 bearing 差），输出 mean(dist)、sd(dist)、sd(delta.th)。</li>
+ * </ol>
+ * </p>
+ */
+public final class MoveBias {
+
+    private MoveBias() {
+    }
+
+    /**
+     * 地球半径（km），与 R moveBias 中 39946.79 / (2π) ≈ 6356.7 不同：R 取极半径 6356.7523。
+     */
+    private static final double KM_PER_DEG_LAT = 111.32;
+
+    /**
+     * WGS84 赤道 1° 经度 ≈ 111.32 × cos(lat) km。
+     */
+    private static double kmPerDegLon(double latDeg) {
+        return 111.32 * Math.cos(Math.toRadians(latDeg));
+    }
+
+    /**
+     * @param chain 原始足迹链（按时间顺序、约 1 秒间隔）
+     * @param scale 步长倍率（每隔 scale 行取一行）
+     * @return 三个统计量：mean(dist/m)、sd(dist/m)、sd(delta.th/°)
+     */
+    public static MoveBiasResult moveBias(List<FootprintPoint> chain, int scale) {
+        if (chain == null || chain.size() < 2) {
+            return new MoveBiasResult(0.0, 0.0, 0.0);
+        }
+        // 降采样
+        List<FootprintPoint> sampled = new java.util.ArrayList<>();
+        for (int i = 0; i < chain.size(); i += Math.max(1, scale)) {
+            sampled.add(chain.get(i));
+        }
+        if (sampled.size() < 2) {
+            return new MoveBiasResult(0.0, 0.0, 0.0);
+        }
+
+        int n = sampled.size();
+        double[] distKm = new double[n];
+        double[] bearing = new double[n];
+
+        for (int i = 1; i < n; i++) {
+            FootprintPoint a = sampled.get(i - 1);
+            FootprintPoint b = sampled.get(i);
+            double meanLat = (a.getLat() + b.getLat()) / 2.0;
+            double dx = (b.getLon() - a.getLon()) * kmPerDegLon(meanLat);
+            double dy = (b.getLat() - a.getLat()) * KM_PER_DEG_LAT;
+            distKm[i] = Math.sqrt(dx * dx + dy * dy);
+            bearing[i] = Math.toDegrees(Math.asin(dy / (distKm[i] == 0 ? 1e-12 : distKm[i])));
+        }
+
+        // 移除 dist==0 的点
+        java.util.List<Double> validDist = new java.util.ArrayList<>();
+        java.util.List<Double> validBearing = new java.util.ArrayList<>();
+        for (int i = 1; i < n; i++) {
+            if (distKm[i] > 0) {
+                validDist.add(distKm[i]);
+                validBearing.add(bearing[i]);
+            }
+        }
+        if (validDist.isEmpty()) {
+            return new MoveBiasResult(0.0, 0.0, 0.0);
+        }
+
+        double[] distM = new double[validDist.size()];
+        for (int i = 0; i < distM.length; i++) {
+            distM[i] = validDist.get(i) * 1000.0; // km → m
+        }
+        double[] bear = new double[validBearing.size()];
+        for (int i = 0; i < bear.length; i++) {
+            bear[i] = validBearing.get(i);
+        }
+
+        // angular deflection
+        double[] delta = new double[Math.max(0, bear.length - 1)];
+        for (int i = 1; i < bear.length; i++) {
+            delta[i - 1] = bear[i] - bear[i - 1];
+        }
+
+        double meanDist = StatisticsUtils.mean(distM);
+        double sdDist = StatisticsUtils.sd(distM);
+        double sdDelta = delta.length > 1 ? StatisticsUtils.sd(delta) : 0.0;
+
+        return new MoveBiasResult(round(meanDist), round(sdDist), round(sdDelta));
+    }
+
+    private static double round(double v) {
+        return Math.round(v * 100.0) / 100.0;
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/algorithm/PlotCamtrap.java

@@ -0,0 +1,78 @@
+package net.hzvtc.stat.algorithm;
+
+import net.hzvtc.stat.dto.CamtrapAggPoint;
+import net.hzvtc.stat.dto.CamtrapScatter;
+import net.hzvtc.stat.dto.CameraPoint;
+import net.hzvtc.stat.util.RandomUtils;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.TreeMap;
+
+/**
+ * R 中 plotCamtrap 的数据准备部分（不负责 R 的 plot 渲染，前端用 ECharts/Map 展示）。
+ *
+ * <p>算法流程（与 R 一致）：
+ * <ol>
+ *   <li>按 (Lat, Lon) 聚合 Group_size 之和 → 相机点位 + Count（决定圆点大小）。</li>
+ *   <li>对 Group_size &gt; 0 的记录，在 (Lon, Lat) 上做 jitter（factor=point.scatter）→ 散点。</li>
+ * </ol>
+ * </p>
+ */
+public final class PlotCamtrap {
+
+    private PlotCamtrap() {
+    }
+
+    /**
+     * @param trapresult   trap 数据（Lon/Lat/Group_size/Date/Time）
+     * @param circleSize   圆点尺寸系数（R plot 中 cex=Count*circle.size；本函数不直接绘图，仅返回数据）
+     * @param pointScatter jitter 因子（R 中 jitter(x, factor=point.scatter)）
+     * @return {@link Result}，包含 aggPoints（点位+计数）和 scatterPoints（jitter 后散点）
+     */
+    public static Result plotCamtrap(List<CameraPoint> trapresult, double circleSize, double pointScatter) {
+        // 1) 按 (Lat, Lon) 聚合
+        Map<String, CamtrapAggPoint> agg = new HashMap<>();
+        for (CameraPoint p : trapresult) {
+            String key = p.getLat() + "," + p.getLon();
+            CamtrapAggPoint a = agg.get(key);
+            if (a == null) {
+                a = new CamtrapAggPoint(p.getLat(), p.getLon(), 0);
+                agg.put(key, a);
+            }
+            a.setCount(a.getCount() + p.getGroupSize());
+        }
+        List<CamtrapAggPoint> aggPoints = new ArrayList<>(agg.values());
+
+        // 2) jitter 散点（仅 Group_size > 0 的记录）
+        List<CamtrapScatter> scatter = new ArrayList<>();
+        for (CameraPoint p : trapresult) {
+            if (p.getGroupSize() > 0) {
+                double jLon = jitter(p.getLon(), pointScatter);
+                double jLat = jitter(p.getLat(), pointScatter);
+                scatter.add(new CamtrapScatter(jLon, jLat, p.getDate(), p.getTime(), p.getGroupSize()));
+            }
+        }
+
+        return new Result(aggPoints, scatter, circleSize);
+    }
+
+    /**
+     * R 的 jitter(x, factor) 等价物：在 ±factor 范围内均匀抖动（与 R jitter 默认 amount 行为近似）。
+     * 使用种子化随机源（见 {@link RandomUtils}），保证同条件结果可复现。
+     */
+    private static double jitter(double value, double factor) {
+        return value + RandomUtils.uniform(-factor, factor);
+    }
+
+    /** plotCamtrap 输出结果。 */
+    @lombok.Data
+    @lombok.AllArgsConstructor
+    public static class Result {
+        private List<CamtrapAggPoint> aggPoints;
+        private List<CamtrapScatter> scatterPoints;
+        private double circleSize;
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/algorithm/PlotFootprint.java

@@ -0,0 +1,29 @@
+package net.hzvtc.stat.algorithm;
+
+import net.hzvtc.stat.dto.FootprintPoint;
+import net.hzvtc.stat.dto.FootprintTrace;
+
+import java.util.Collections;
+import java.util.List;
+
+/**
+ * R 中 plotFootprint(chain) 的数据准备：返回折线轨迹 + 起止点高亮坐标。
+ */
+public final class PlotFootprint {
+
+    private PlotFootprint() {
+    }
+
+    /**
+     * @param chain 按时间顺序的足迹链节点（Lon/Lat/Date），按 1 秒间隔采样
+     * @return {@link FootprintTrace}，前端用 ECharts polyline + scatter 渲染
+     */
+    public static FootprintTrace plotFootprint(List<FootprintPoint> chain) {
+        if (chain == null || chain.isEmpty()) {
+            return new FootprintTrace(Collections.emptyList(), 0, 0, 0, 0);
+        }
+        FootprintPoint first = chain.get(0);
+        FootprintPoint last = chain.get(chain.size() - 1);
+        return new FootprintTrace(chain, first.getLon(), first.getLat(), last.getLon(), last.getLat());
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/algorithm/PredictCamtrap.java

@@ -0,0 +1,295 @@
+package net.hzvtc.stat.algorithm;
+
+import net.hzvtc.stat.dto.CameraPoint;
+import net.hzvtc.stat.dto.PredictionResult;
+import net.hzvtc.stat.dto.SimulationResult;
+import net.hzvtc.stat.util.StatisticsUtils;
+
+import java.util.HashMap;
+import java.util.Map;
+
+/**
+ * R 中 predictCamtrap(simu, x, plot) 的 Java 实现。
+ *
+ * <p>算法：
+ * <ol>
+ *   <li>用 simu 的 camera counts 训练一棵简化随机森林（Bagging 多数表决回归）。</li>
+ *   <li>把真实 trap 数据按 (Lat, Lon) 聚合得到与 simu 列数等长的 obs（sort 后）。</li>
+ *   <li>RF 对 obs 做 1000 棵树预测，统计 quantile(0.025, 0.5, 0.975)。</li>
+ * </ol>
+ * </p>
+ *
+ * <p>说明：cameratrapR 使用 randomForest 包做 RF。本类用基于 Bootstrap 的简化 RF 自实现（无外部依赖）：
+ * 每棵树从训练集有放回采样 n 个样本，在每个分裂节点随机选 sqrt(p) 个特征，
+ * 选最小方差分裂，直到桶内样本 ≤ leafSize 取均值预测。1000 棵树的均值预测即最终 No_ind，
+ * 置信区间来自 1000 棵树各自预测的 2.5% / 97.5% 分位。</p>
+ */
+public final class PredictCamtrap {
+
+    private PredictCamtrap() {
+    }
+
+    /**
+     * @param simu      simuCamtrap 输出
+     * @param data      真实 trap 数据
+     * @param nTree     随机森林规模（默认 1000）
+     * @param seed      随机种子（保证可复现）
+     * @return 预测结果（中位数 + 95% CI）
+     */
+    public static PredictionResult predictCamtrap(SimulationResult simu,
+                                                  java.util.List<CameraPoint> data,
+                                                  int nTree,
+                                                  long seed) {
+        if (simu == null || simu.getInd() == null || simu.getInd().length == 0 || data == null || data.isEmpty()) {
+            return new PredictionResult(0.0, 0.0, 0.0, new double[0]);
+        }
+
+        // 1) 训练样本：X = simu camera counts, y = Ind
+        long[][] simX = simu.getCameraCounts();
+        int[] simY = simu.getInd();
+        int nSamples = simX.length;
+        int nFeatures = nSamples > 0 ? simX[0].length : 0;
+
+        // 2) 真实 obs：按 (Lat, Lon) 聚合 Group_size，排序（不保留空间信息）
+        Map<String, Long> agg = new HashMap<>();
+        for (CameraPoint p : data) {
+            String key = p.getLat() + "," + p.getLon();
+            agg.merge(key, (long) p.getGroupSize(), Long::sum);
+        }
+        long[] obs = new long[agg.size()];
+        int i = 0;
+        for (Long v : agg.values()) {
+            obs[i++] = v;
+        }
+        java.util.Arrays.sort(obs);
+
+        // 3) 训练 RF 并对 obs 预测
+        java.util.Random rng = new java.util.Random(seed);
+        SimpleRandomForest rf = new SimpleRandomForest(nTree, rng);
+        rf.fit(simX, simY, nFeatures);
+        double[] predictions = rf.predict(obs);
+
+        // 4) 统计中位数 / 2.5% / 97.5%
+        double median = StatisticsUtils.quantile(predictions, 0.5);
+        double ciLow = StatisticsUtils.quantile(predictions, 0.025);
+        double ciHigh = StatisticsUtils.quantile(predictions, 0.975);
+
+        return new PredictionResult(round1(median), round1(ciLow), round1(ciHigh), sample(predictions, 200));
+    }
+
+    /** 等距下采样，控制返回体大小（箱线图统计量用 200 个样本已足够）。 */
+    private static double[] sample(double[] values, int max) {
+        if (values == null || values.length <= max) {
+            return values == null ? new double[0] : values;
+        }
+        double[] out = new double[max];
+        for (int i = 0; i < max; i++) {
+            out[i] = values[(int) Math.round((double) i * (values.length - 1) / (max - 1))];
+        }
+        return out;
+    }
+
+    private static double round1(double v) {
+        return Math.round(v * 10.0) / 10.0;
+    }
+
+    /**
+     * 简化随机森林（Bootstrap + 随机特征子集 + 回归树）。
+     * 不追求精度等价 randomForest R 包，仅在结构上保持同源：1000 棵树 / OOB bootstrap / sqrt(p) 特征。
+     */
+    static final class SimpleRandomForest {
+
+        private final int nTree;
+        private final java.util.Random rng;
+        private final java.util.List<RegressionTree> trees = new java.util.ArrayList<>();
+
+        SimpleRandomForest(int nTree, java.util.Random rng) {
+            this.nTree = nTree;
+            this.rng = rng;
+        }
+
+        void fit(long[][] x, int[] y, int nFeatures) {
+            int n = x.length;
+            int subsetSize = Math.max(1, (int) Math.sqrt(nFeatures));
+            for (int t = 0; t < nTree; t++) {
+                long[][] bx = new long[n][];
+                int[] by = new int[n];
+                for (int i = 0; i < n; i++) {
+                    int idx = rng.nextInt(n);
+                    bx[i] = x[idx];
+                    by[i] = y[idx];
+                }
+                RegressionTree tree = new RegressionTree();
+                tree.root = tree.build(bx, by, 0, subsetSize, rng);
+                trees.add(tree);
+            }
+        }
+
+        double[] predict(long[] obs) {
+            double[] perTree = new double[trees.size()];
+            for (int t = 0; t < trees.size(); t++) {
+                perTree[t] = trees.get(t).predict(obs);
+            }
+            return perTree;
+        }
+    }
+
+    /** 极简回归树：节点递归按中位数二分，叶子存均值。 */
+    static final class RegressionTree {
+
+        Node root;
+
+        static final class Node {
+            int featureIdx;
+            double threshold;
+            Node left;
+            Node right;
+            double leafValue;
+
+            boolean isLeaf() {
+                return left == null && right == null;
+            }
+        }
+
+        Node build(long[][] x, int[] y, int depth, int subsetSize, java.util.Random rng) {
+            Node node = new Node();
+            if (x.length <= 1 || depth >= 12) {
+                node.leafValue = mean(y);
+                return node;
+            }
+
+            int nFeatures = x[0].length;
+            int[] featIdx = randomFeatures(nFeatures, subsetSize, rng);
+
+            double bestVar = Double.POSITIVE_INFINITY;
+            int bestFeat = -1;
+            double bestThr = 0;
+
+            for (int f : featIdx) {
+                double[] vals = new double[x.length];
+                for (int i = 0; i < x.length; i++) {
+                    vals[i] = x[i][f];
+                }
+                double thr = median(vals);
+                // 拆分子集
+                int nLeft = 0, nRight = 0;
+                double sumL = 0, sumR = 0;
+                for (int i = 0; i < x.length; i++) {
+                    if (x[i][f] <= thr) {
+                        nLeft++;
+                        sumL += y[i];
+                    } else {
+                        nRight++;
+                        sumR += y[i];
+                    }
+                }
+                if (nLeft == 0 || nRight == 0) {
+                    continue;
+                }
+                double mL = sumL / nLeft;
+                double mR = sumR / nRight;
+                double varL = 0, varR = 0;
+                for (int i = 0; i < x.length; i++) {
+                    double dev = y[i] - (x[i][f] <= thr ? mL : mR);
+                    if (x[i][f] <= thr) {
+                        varL += dev * dev;
+                    } else {
+                        varR += dev * dev;
+                    }
+                }
+                double weighted = (varL + varR) / x.length;
+                if (weighted < bestVar) {
+                    bestVar = weighted;
+                    bestFeat = f;
+                    bestThr = thr;
+                }
+            }
+
+            if (bestFeat < 0) {
+                node.leafValue = mean(y);
+                return node;
+            }
+
+            node.featureIdx = bestFeat;
+            node.threshold = bestThr;
+
+            java.util.List<long[]> leftX = new java.util.ArrayList<>();
+            java.util.List<Integer> leftY = new java.util.ArrayList<>();
+            java.util.List<long[]> rightX = new java.util.ArrayList<>();
+            java.util.List<Integer> rightY = new java.util.ArrayList<>();
+            for (int i = 0; i < x.length; i++) {
+                if (x[i][bestFeat] <= bestThr) {
+                    leftX.add(x[i]);
+                    leftY.add(y[i]);
+                } else {
+                    rightX.add(x[i]);
+                    rightY.add(y[i]);
+                }
+            }
+            node.left = build(toArray(leftX), toInt(leftY), depth + 1, subsetSize, rng);
+            node.right = build(toArray(rightX), toInt(rightY), depth + 1, subsetSize, rng);
+            return node;
+        }
+
+        double predict(long[] obs) {
+            Node n = root;
+            while (!n.isLeaf()) {
+                n = obs[n.featureIdx] <= n.threshold ? n.left : n.right;
+                if (n == null) {
+                    return 0;
+                }
+            }
+            return n.leafValue;
+        }
+
+        private static int[] randomFeatures(int n, int subset, java.util.Random rng) {
+            java.util.Set<Integer> s = new java.util.HashSet<>();
+            while (s.size() < Math.min(subset, n)) {
+                s.add(rng.nextInt(n));
+            }
+            int[] out = new int[s.size()];
+            int i = 0;
+            for (Integer v : s) {
+                out[i++] = v;
+            }
+            return out;
+        }
+
+        private static long[][] toArray(java.util.List<long[]> list) {
+            long[][] arr = new long[list.size()][];
+            for (int i = 0; i < arr.length; i++) {
+                arr[i] = list.get(i);
+            }
+            return arr;
+        }
+
+        private static int[] toInt(java.util.List<Integer> list) {
+            int[] arr = new int[list.size()];
+            for (int i = 0; i < arr.length; i++) {
+                arr[i] = list.get(i);
+            }
+            return arr;
+        }
+
+        private static double mean(int[] y) {
+            if (y.length == 0) {
+                return 0;
+            }
+            double s = 0;
+            for (int v : y) {
+                s += v;
+            }
+            return s / y.length;
+        }
+
+        private static double median(double[] v) {
+            double[] s = v.clone();
+            java.util.Arrays.sort(s);
+            int m = s.length / 2;
+            if (s.length % 2 == 1) {
+                return s[m];
+            }
+            return (s[m - 1] + s[m]) / 2.0;
+        }
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/algorithm/Rowcliffe.java

@@ -0,0 +1,69 @@
+package net.hzvtc.stat.algorithm;
+
+import net.hzvtc.stat.dto.CameraPoint;
+import net.hzvtc.stat.util.StatisticsUtils;
+
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+/**
+ * R 中 Rowcliffe(x, r, theta, v, duration) 的 Java 实现：
+ * Rowcliffe (2008) 随机相遇模型估计物种密度。
+ *
+ * <p>公式（与 R 完全一致）：
+ * <pre>
+ *   D_i = Count_i * π / (duration * v * r * (2 + θ * 2π/360))
+ *   result = c(mean(D), sd(D))
+ * </pre>
+ * </p>
+ *
+ * <p>字段单位约定：
+ * <ul>
+ *   <li>r：相机检测距离（km）</li>
+ *   <li>theta：相机检测角度（°）</li>
+ *   <li>v：动物平均移动速度（km/h）</li>
+ *   <li>duration：调查持续天数（day）</li>
+ * </ul>
+ * </p>
+ */
+public final class Rowcliffe {
+
+    private Rowcliffe() {
+    }
+
+    /**
+     * @param data     trap 数据
+     * @param r        检测距离（km）
+     * @param theta    检测角度（°）
+     * @param v        动物平均速度（km/h）
+     * @param duration 调查天数（day）
+     * @return [mean(D), sd(D)]
+     */
+    public static double[] rowcliffe(List<CameraPoint> data, double r, double theta, double v, double duration) {
+        // 按 (Lat, Lon) 聚合 Group_size 之和
+        Map<String, Double> sumMap = new HashMap<>();
+        for (CameraPoint p : data) {
+            String key = p.getLat() + "," + p.getLon();
+            sumMap.merge(key, (double) p.getGroupSize(), Double::sum);
+        }
+        double[] counts = sumMap.values().stream().mapToDouble(Double::doubleValue).toArray();
+        if (counts.length == 0) {
+            return new double[]{0.0, 0.0};
+        }
+
+        double denom = duration * v * r * (2.0 + theta * 2.0 * Math.PI / 360.0);
+        double[] d = new double[counts.length];
+        for (int i = 0; i < counts.length; i++) {
+            d[i] = counts[i] * Math.PI / denom;
+        }
+
+        double mean = StatisticsUtils.mean(d);
+        double sd = StatisticsUtils.sd(d);
+        return new double[]{round2(mean), round2(sd)};
+    }
+
+    private static double round2(double v) {
+        return Math.round(v * 100.0) / 100.0;
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/algorithm/SimuCamtrap.java

@@ -0,0 +1,203 @@
+package net.hzvtc.stat.algorithm;
+
+import net.hzvtc.stat.dto.CameraPoint;
+import net.hzvtc.stat.dto.SimulationResult;
+import net.hzvtc.stat.util.RandomUtils;
+
+import java.util.Arrays;
+
+/**
+ * R 中 simuCamtrap(x, ...) 的 Java 实现。
+ *
+ * <p>算法（与 R 一致）：
+ * <ol>
+ *   <li>使用业务层从 MySQL 读取的 Step.L / Bias / Range。</li>
+ *   <li>取 unique(Lon, Lat) 作为相机位（含 Count=0 列）。</li>
+ *   <li>共进行 ind × iteration 次随机游走模拟。每次：
+ *     <ul>
+ *       <li>在网格中央 25%-75% 范围随机生成初始位置。</li>
+ *       <li>每一步判断是否落入任一相机的检测半径（detect m）+ 检测角度（±25°）内，是则 Count+1。</li>
+ *       <li>步长 = Step.L × N(1, Step.V)；偏向角叠加 N(0, Bias)（度→弧度）。</li>
+ *       <li>按 (1 - dist/range) vs (dist/range) 概率选择"前进 vs 回原点"方向。</li>
+ *     </ul>
+ *   </li>
+ *   <li>每次模拟结束：Count 排序（不保留空间信息），写入 out[k+(ite-1)*ind, ]。</li>
+ * </ol>
+ * </p>
+ */
+public final class SimuCamtrap {
+
+    private SimuCamtrap() {
+    }
+
+    /** 检测角半角 50° → 弧度。 */
+    private static final double DETECT_HALF_ARC = Math.toRadians(50.0);
+
+    /** 中心 50% 区域边界系数。 */
+    private static final double CENTER_FRAC = 0.25;
+
+    /**
+     * @param data      真实 trap 数据
+     * @param species   物种名称（用于标识本次模拟）
+     * @param detect    检测半径（m）。注意：R 默认 50，传给函数前已用米
+     * @param bearing   每台相机的朝向（弧度数组，长度=camera.N）。NULL 时随机生成
+     * @param stepN     模拟步数
+     * @param stepV     步长标准差系数（与 stepL 相乘的 N(1, stepV)）
+     * @param stepL     步长均值（m）
+     * @param biasDeg   偏向角标准差（度）
+     * @param rangeM    家域半径（m），R 中 Range(km²)*1000 仅示意，实际是直径 m
+     * @param ind       个体数
+     * @param iteration 迭代次数
+     */
+    public static SimulationResult simuCamtrap(java.util.List<CameraPoint> data,
+                                               String species,
+                                               double detect,
+                                               double[] bearing,
+                                               int stepN,
+                                               double stepV,
+                                               double stepL,
+                                               double biasDeg,
+                                               double rangeM,
+                                               int ind,
+                                               int iteration) {
+        if (data == null || data.isEmpty()) {
+            return new SimulationResult(new int[0], new long[0][0], new double[0], new double[0]);
+        }
+
+        // 1) unique cameras
+        double[] camLon = uniqueLon(data);
+        double[] camLat = uniqueLat(data);
+        int cameraN = camLon.length;
+        if (bearing == null || bearing.length != cameraN) {
+            bearing = new double[cameraN];
+            for (int i = 0; i < cameraN; i++) {
+                bearing[i] = RandomUtils.uniform(0.0, 2.0 * Math.PI);
+            }
+        }
+
+        // 经纬度边界
+        double minLon = Double.POSITIVE_INFINITY, maxLon = Double.NEGATIVE_INFINITY;
+        double minLat = Double.POSITIVE_INFINITY, maxLat = Double.NEGATIVE_INFINITY;
+        for (CameraPoint p : data) {
+            if (p.getLon() < minLon) minLon = p.getLon();
+            if (p.getLon() > maxLon) maxLon = p.getLon();
+            if (p.getLat() < minLat) minLat = p.getLat();
+            if (p.getLat() > maxLat) maxLat = p.getLat();
+        }
+        double lonLo = minLon + CENTER_FRAC * (maxLon - minLon);
+        double lonHi = maxLon - CENTER_FRAC * (maxLon - minLon);
+        double latLo = minLat + CENTER_FRAC * (maxLat - minLat);
+        double latHi = maxLat - CENTER_FRAC * (maxLat - minLat);
+
+        // 2) ind × iteration 次模拟
+        int totalRows = ind * iteration;
+        int[] indArr = new int[totalRows];
+        long[][] out = new long[totalRows][cameraN];
+        long[] count = new long[cameraN];
+
+        double biasRad = biasDeg / 360.0 * 2.0 * Math.PI;
+
+        for (int ite = 1; ite <= iteration; ite++) {
+            for (int k = 1; k <= ind; k++) {
+                // 初始位置（中心区域随机）
+                double locX = RandomUtils.uniform(lonLo, lonHi);
+                double locY = RandomUtils.uniform(latLo, latHi);
+                double x0 = locX, y0 = locY;
+
+                // 初始朝向
+                double theta = RandomUtils.uniform(0.0, 2.0 * Math.PI);
+                Arrays.fill(count, 0L);
+
+                for (int i = 1; i <= stepN; i++) {
+                    // 相机检测判定
+                    for (int j = 0; j < cameraN; j++) {
+                        double dx = locX - camLon[j];
+                        double dy = locY - camLat[j];
+                        double d = Math.sqrt(dx * dx + dy * dy);
+                        if (d < detect) {
+                            double bear;
+                            if (dx == 0 && dy == 0) {
+                                bear = 0;
+                            } else {
+                                bear = Math.atan2(dy, dx);
+                            }
+                            double diff = Math.abs(normalizeAngle(bear - bearing[j]));
+                            if (diff < DETECT_HALF_ARC) {
+                                count[j]++;
+                            }
+                        }
+                    }
+
+                    // 步长
+                    double move = stepL * RandomUtils.gaussian(1.0, stepV);
+                    locX += move * Math.cos(theta);
+                    locY += move * Math.sin(theta);
+
+                    // 前进 vs 回原点
+                    double thetaF = theta + RandomUtils.gaussian(0.0, biasRad);
+                    double thetaB;
+                    if (locX > x0) {
+                        thetaB = Math.PI + Math.atan2(locY - y0, locX - x0) + RandomUtils.gaussian(0.0, biasRad * 2);
+                    } else {
+                        thetaB = Math.atan2(locY - y0, locX - x0) + RandomUtils.gaussian(0.0, biasRad * 2);
+                    }
+                    double dist = Math.sqrt((locX - x0) * (locX - x0) + (locY - y0) * (locY - y0));
+                    double pForward = Math.abs(1.0 - dist / rangeM);
+                    double pBackward = dist / rangeM;
+                    theta = RandomUtils.weightedSample(new double[]{pForward, pBackward}) == 0 ? thetaF : thetaB;
+                }
+
+                // 排序后写入（R 中 sort(camera$Count)）
+                long[] sorted = count.clone();
+                Arrays.sort(sorted);
+                int rowIdx = k + (ite - 1) * ind - 1;
+                indArr[rowIdx] = k;
+                out[rowIdx] = sorted;
+            }
+        }
+
+        return new SimulationResult(indArr, out, camLon, camLat);
+    }
+
+    private static double[] uniqueLon(java.util.List<CameraPoint> data) {
+        java.util.LinkedHashMap<String, double[]> map = new java.util.LinkedHashMap<>();
+        for (CameraPoint p : data) {
+            map.put(p.getLon() + "," + p.getLat(), new double[]{p.getLon(), p.getLat()});
+        }
+        double[] lons = new double[map.size()];
+        double[] lats = new double[map.size()];
+        int i = 0;
+        for (double[] v : map.values()) {
+            lons[i] = v[0];
+            lats[i] = v[1];
+            i++;
+        }
+        // 共享给 uniqueLat 通过线程局部？简单起见直接重写为返回 pair
+        return lons;
+    }
+
+    private static double[] uniqueLat(java.util.List<CameraPoint> data) {
+        java.util.LinkedHashMap<String, double[]> map = new java.util.LinkedHashMap<>();
+        for (CameraPoint p : data) {
+            map.put(p.getLon() + "," + p.getLat(), new double[]{p.getLon(), p.getLat()});
+        }
+        double[] lats = new double[map.size()];
+        int i = 0;
+        for (double[] v : map.values()) {
+            lats[i] = v[1];
+            i++;
+        }
+        return lats;
+    }
+
+    /** 把角度规整到 [-π, π]。 */
+    private static double normalizeAngle(double a) {
+        while (a > Math.PI) {
+            a -= 2.0 * Math.PI;
+        }
+        while (a < -Math.PI) {
+            a += 2.0 * Math.PI;
+        }
+        return a;
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/controller/CameraTrapStatController.java

@@ -0,0 +1,609 @@
+package net.hzvtc.stat.controller;
+
+import com.alibaba.fastjson.JSONArray;
+import com.alibaba.fastjson.JSONObject;
+import lombok.RequiredArgsConstructor;
+import net.hzvtc.stat.algorithm.Geo2Proj;
+import net.hzvtc.stat.algorithm.PlotCamtrap;
+import net.hzvtc.stat.dto.CameraPoint;
+import net.hzvtc.stat.dto.ChainLengthItem;
+import net.hzvtc.stat.dto.ChainRecord;
+import net.hzvtc.stat.dto.DensitySeries;
+import net.hzvtc.stat.dto.FootprintPoint;
+import net.hzvtc.stat.dto.FootprintTrace;
+import net.hzvtc.stat.dto.HabitatAreaResult;
+import net.hzvtc.stat.dto.HabitatRangeResult;
+import net.hzvtc.stat.dto.HomeRangeItem;
+import net.hzvtc.stat.dto.MoveBiasResult;
+import net.hzvtc.stat.dto.PopulationEstimateItem;
+import net.hzvtc.stat.dto.PredictionResult;
+import net.hzvtc.stat.dto.RasterResult;
+import net.hzvtc.stat.dto.SimulationResult;
+import net.hzvtc.stat.service.CameraTrapStatService;
+import net.hzvtc.stat.service.StatEsDataService;
+import org.springframework.web.bind.annotation.PostMapping;
+import org.springframework.web.bind.annotation.RequestBody;
+import org.springframework.web.bind.annotation.RequestMapping;
+import org.springframework.web.bind.annotation.RestController;
+
+import java.util.List;
+
+/**
+ * cameratrapR 11 个函数的 REST 入口（前端调用）。
+ *
+ * <p>所有 endpoint 均接收 JSON body，数据来源二选一：
+ * <ul>
+ *   <li>body 中直接传 <code>data</code> 数组（列字段见各方法注释，用于调试 / 自定义数据）；</li>
+ *   <li>缺省 <code>data</code> 时按查询参数从 ES 索引 <code>animal_valid_record</code> 加载：
+ *       支持 species_id / speciesInIds / deviceIds / dateFrom / dateTo / checked /
+ *       recordType / mediaType 等参数（与报表模块一致），经纬度由 device_id
+ *       关联 device_info 表补齐。</li>
+ * </ul></p>
+ *
+ * <p>返回 JSON 对象包含算法结果，便于前端直接渲染。</p>
+ *
+ * <p>路径前缀：<code>/es/stat</code></p>
+ */
+@RestController
+@RequestMapping("/es/stat")
+@RequiredArgsConstructor
+public class CameraTrapStatController {
+
+    private final CameraTrapStatService service;
+
+    private final StatEsDataService statEsDataService;
+
+    /**
+     * 数据来源：body 中带非空 data 数组则直接使用（调试 / 自定义数据）；
+     * 否则按查询参数（species_id / speciesInIds / deviceIds / dateFrom / dateTo / checked 等）
+     * 从 ES 索引 animal_valid_record 加载，并关联 device_info 补齐经纬度。
+     */
+    private List<CameraPoint> cameraData(JSONObject param) {
+        com.alibaba.fastjson.JSONArray data = param.getJSONArray("data");
+        if (data != null && !data.isEmpty()) {
+            return CameraTrapStatService.toCameraPoints(data);
+        }
+        return statEsDataService.loadCameraPoints(param);
+    }
+
+    private List<FootprintPoint> footprintData(JSONObject param) {
+        com.alibaba.fastjson.JSONArray data = param.getJSONArray("data");
+        if (data != null && !data.isEmpty()) {
+            return CameraTrapStatService.toFootprintPoints(data);
+        }
+        return statEsDataService.loadFootprintPoints(param);
+    }
+
+    private List<ChainRecord> chainData(JSONObject param) {
+        com.alibaba.fastjson.JSONArray data = param.getJSONArray("data");
+        if (data != null && !data.isEmpty()) {
+            return CameraTrapStatService.toChainRecords(data);
+        }
+        return statEsDataService.loadChainRecords(param);
+    }
+
+    /**
+     * POST /es/stat/plotCamtrap
+     * body: { circleSize: 0.2, pointScatter: 5, data: [{lon,lat,groupSize,date,time}, ...] }
+     */
+    @PostMapping("/plotCamtrap")
+    public JSONObject plotCamtrap(@RequestBody JSONObject param) {
+        double circleSize = getDouble(param, "circleSize", 0.2);
+        double pointScatter = getDouble(param, "pointScatter", 5.0);
+        List<CameraPoint> data = cameraData(param);
+        PlotCamtrap.Result result = service.plotCamtrap(data, circleSize, pointScatter);
+
+        JSONObject out = new JSONObject();
+        JSONArray agg = new JSONArray();
+        for (CamtrapAggView p : toAggViews(result)) {
+            JSONObject o = new JSONObject();
+            o.put("lat", p.lat);
+            o.put("lon", p.lon);
+            o.put("count", p.count);
+            agg.add(o);
+        }
+        JSONArray scatter = new JSONArray();
+        result.getScatterPoints().forEach(p -> {
+            JSONObject o = new JSONObject();
+            o.put("lon", p.getLon());
+            o.put("lat", p.getLat());
+            o.put("date", p.getDate());
+            o.put("time", p.getTime());
+            o.put("groupSize", p.getGroupSize());
+            scatter.add(o);
+        });
+        out.put("aggPoints", agg);
+        out.put("scatterPoints", scatter);
+        out.put("circleSize", result.getCircleSize());
+        return out;
+    }
+
+    /**
+     * POST /es/stat/dailyRhythm
+     * body: { data: [{lon,lat,groupSize,date,time}, ...] }
+     */
+    @PostMapping("/dailyRhythm")
+    public JSONObject dailyRhythm(@RequestBody JSONObject param) {
+        List<CameraPoint> data = cameraData(param);
+        List<DensitySeries> series = service.dailyRhythm(data);
+        JSONObject out = new JSONObject();
+        JSONArray arr = new JSONArray();
+        for (DensitySeries s : series) {
+            JSONObject o = new JSONObject();
+            o.put("x", s.getX());
+            o.put("y", s.getY());
+            o.put("bandwidth", s.getBandwidth());
+            o.put("label", s.getLabel());
+            arr.add(o);
+        }
+        out.put("series", arr);
+        return out;
+    }
+
+    /**
+     * POST /es/stat/geo2proj
+     * body: { data: [{lon,lat,...}, ...] }
+     */
+    @PostMapping("/geo2proj")
+    public JSONObject geo2proj(@RequestBody JSONObject param) {
+        List<CameraPoint> data = cameraData(param);
+        List<Geo2Proj.UtmPoint> utm = service.geo2proj(data);
+        JSONObject out = new JSONObject();
+        JSONArray arr = new JSONArray();
+        utm.forEach(p -> {
+            JSONObject o = new JSONObject();
+            o.put("easting", p.getEasting());
+            o.put("northing", p.getNorthing());
+            arr.add(o);
+        });
+        out.put("points", arr);
+        return out;
+    }
+
+    /**
+     * POST /es/stat/simuCamtrap
+     * body: { species: "Red fox", ind: 10, iteration: 3, data: [...] }
+     */
+    @PostMapping("/simuCamtrap")
+    public JSONObject simuCamtrap(@RequestBody JSONObject param) {
+        List<CameraPoint> data = cameraData(param);
+        String species = param.getString("species");
+        int ind = getInt(param, "ind", 10);
+        int iteration = getInt(param, "iteration", 3);
+        SimulationResult res = service.simuCamtrap(data, species, ind, iteration);
+        JSONObject out = new JSONObject();
+        out.put("ind", res.getInd());
+        out.put("cameraCounts", res.getCameraCounts());
+        out.put("cameraLon", res.getCameraLon());
+        out.put("cameraLat", res.getCameraLat());
+        return out;
+    }
+
+    /**
+     * POST /es/stat/predictCamtrap
+     * body: { simu: {ind, cameraCounts, cameraLon, cameraLat}, data: [...], nTree: 1000, seed: 1234 }
+     */
+    @PostMapping("/predictCamtrap")
+    public JSONObject predictCamtrap(@RequestBody JSONObject param) {
+        // 解析 simu
+        JSONObject simuObj = param.getJSONObject("simu");
+        SimulationResult simu = new SimulationResult();
+        JSONArray indArr = simuObj.getJSONArray("ind");
+        int[] ind = new int[indArr.size()];
+        for (int i = 0; i < ind.length; i++) {
+            ind[i] = indArr.getIntValue(i);
+        }
+        simu.setInd(ind);
+
+        JSONArray counts = simuObj.getJSONArray("cameraCounts");
+        long[][] cc = new long[counts.size()][];
+        for (int i = 0; i < cc.length; i++) {
+            JSONArray row = counts.getJSONArray(i);
+            cc[i] = new long[row.size()];
+            for (int j = 0; j < row.size(); j++) {
+                cc[i][j] = row.getLongValue(j);
+            }
+        }
+        simu.setCameraCounts(cc);
+
+        JSONArray lonArr = simuObj.getJSONArray("cameraLon");
+        JSONArray latArr = simuObj.getJSONArray("cameraLat");
+        double[] lon = new double[lonArr.size()];
+        double[] lat = new double[latArr.size()];
+        for (int i = 0; i < lon.length; i++) {
+            lon[i] = lonArr.getDoubleValue(i);
+            lat[i] = latArr.getDoubleValue(i);
+        }
+        simu.setCameraLon(lon);
+        simu.setCameraLat(lat);
+
+        List<CameraPoint> real = cameraData(param);
+        int nTree = getInt(param, "nTree", 1000);
+        long seed = getLong(param, "seed", 1234L);
+
+        PredictionResult res = service.predictCamtrap(simu, real, nTree, seed);
+        JSONObject out = new JSONObject();
+        out.put("noInd", res.getNoInd());
+        out.put("ciLow", res.getCiLow());
+        out.put("ciHigh", res.getCiHigh());
+        return out;
+    }
+
+    /**
+     * POST /es/stat/plotFootprint
+     * body: { data: [{lon,lat,date}, ...] }
+     */
+    @PostMapping("/plotFootprint")
+    public JSONObject plotFootprint(@RequestBody JSONObject param) {
+        List<FootprintPoint> chain = footprintData(param);
+        FootprintTrace trace = service.plotFootprint(chain);
+        JSONObject out = new JSONObject();
+        JSONArray pts = new JSONArray();
+        trace.getPoints().forEach(p -> {
+            JSONObject o = new JSONObject();
+            o.put("lon", p.getLon());
+            o.put("lat", p.getLat());
+            o.put("date", p.getDate());
+            pts.add(o);
+        });
+        out.put("points", pts);
+        out.put("startLon", trace.getStartLon());
+        out.put("startLat", trace.getStartLat());
+        out.put("endLon", trace.getEndLon());
+        out.put("endLat", trace.getEndLat());
+        return out;
+    }
+
+    /**
+     * POST /es/stat/moveBias
+     * body: { scale: 2, data: [{lon,lat,date}, ...] }
+     */
+    @PostMapping("/moveBias")
+    public JSONObject moveBias(@RequestBody JSONObject param) {
+        List<FootprintPoint> chain = footprintData(param);
+        int scale = getInt(param, "scale", 2);
+        MoveBiasResult res = service.moveBias(chain, scale);
+        JSONObject out = new JSONObject();
+        out.put("meanStepLength", res.getMeanStepLength());
+        out.put("sdStepLength", res.getSdStepLength());
+        out.put("sdAngularDeflection", res.getSdAngularDeflection());
+        return out;
+    }
+
+    /**
+     * POST /es/stat/rowcliffe
+     * body: { r: 0.02, theta: 40, v: 2, duration: 40, data: [...] }
+     */
+    @PostMapping("/rowcliffe")
+    public JSONObject rowcliffe(@RequestBody JSONObject param) {
+        List<CameraPoint> data = cameraData(param);
+        double r = getDouble(param, "r", 0.02);
+        double theta = getDouble(param, "theta", 40);
+        double v = getDouble(param, "v", 2);
+        double duration = getDouble(param, "duration", 40);
+        double[] res = service.rowcliffe(data, r, theta, v, duration);
+        JSONObject out = new JSONObject();
+        out.put("density", res[0]);
+        out.put("sd", res[1]);
+        return out;
+    }
+
+    /**
+     * POST /es/stat/homeRange
+     * body: { data: [{lon,lat,date}, ...] }
+     */
+    @PostMapping("/homeRange")
+    public JSONObject homeRange(@RequestBody JSONObject param) {
+        List<FootprintPoint> chain = footprintData(param);
+        double area = service.homeRange(chain);
+        JSONObject out = new JSONObject();
+        out.put("area", area);
+        return out;
+    }
+
+    /**
+     * POST /es/stat/homeRanges
+     * body: { data: [{species, line, lon, lat, date}, ...] }
+     */
+    @PostMapping("/homeRanges")
+    public JSONObject homeRanges(@RequestBody JSONObject param) {
+        List<ChainRecord> recs = chainData(param);
+        List<HomeRangeItem> list = service.homeRanges(recs);
+        JSONObject out = new JSONObject();
+        JSONArray arr = new JSONArray();
+        list.forEach(it -> {
+            JSONObject o = new JSONObject();
+            o.put("species", it.getSpecies());
+            o.put("area", it.getArea());
+            o.put("sd", it.getSd());
+            o.put("n", it.getN());
+            arr.add(o);
+        });
+        out.put("items", arr);
+        return out;
+    }
+
+    /**
+     * POST /es/stat/chainLength
+     * body: { data: [{lon,lat,date}, ...] }
+     */
+    @PostMapping("/chainLength")
+    public JSONObject chainLength(@RequestBody JSONObject param) {
+        List<FootprintPoint> chain = footprintData(param);
+        double dist = service.chainLength(chain);
+        JSONObject out = new JSONObject();
+        out.put("distance", dist);
+        return out;
+    }
+
+    /**
+     * POST /es/stat/chainLengths
+     * body: { data: [{species, line, lon, lat, date}, ...] }
+     */
+    @PostMapping("/chainLengths")
+    public JSONObject chainLengths(@RequestBody JSONObject param) {
+        List<ChainRecord> recs = chainData(param);
+        List<ChainLengthItem> list = service.chainLengths(recs);
+        JSONObject out = new JSONObject();
+        JSONArray arr = new JSONArray();
+        list.forEach(it -> {
+            JSONObject o = new JSONObject();
+            o.put("species", it.getSpecies());
+            o.put("distance", it.getDistance());
+            o.put("distSd", it.getDistSd());
+            o.put("stepL", it.getStepL());
+            o.put("stepNo", it.getStepNo());
+            o.put("n", it.getN());
+            arr.add(o);
+        });
+        out.put("items", arr);
+        return out;
+    }
+
+    // =====================================================================
+    // 报表四步：种群大小估计 → 种群密度估计 → 栖息地面积分析 → 栖息地分布范围
+    // =====================================================================
+
+    /**
+     * POST /es/stat/populationEstimate（报表步骤 1：种群大小估计）
+     * body: { speciesList: ["Red fox", ...]（空 = 全部物种）, ind: 10, iteration: 3,
+     *        nTree: 500, seed: 1234, data: [{lon,lat,groupSize,date,time,species}, ...] 或 ES 查询参数 }
+     * 返回 items: [{species, noInd, ciLow, ciHigh, individual[], recordCount, cameraCount}]
+     */
+    @PostMapping("/populationEstimate")
+    public JSONObject populationEstimate(@RequestBody JSONObject param) {
+        List<String> speciesList = new java.util.ArrayList<>();
+        JSONArray spArr = param.getJSONArray("speciesList");
+        if (spArr != null) {
+            for (int i = 0; i < spArr.size(); i++) {
+                speciesList.add(spArr.getString(i));
+            }
+        }
+        List<CameraPoint> data = cameraData(param);
+        int ind = getInt(param, "ind", 10);
+        int iteration = getInt(param, "iteration", 3);
+        int nTree = getInt(param, "nTree", 500);
+        long seed = getLong(param, "seed", 1234L);
+        List<PopulationEstimateItem> items = service.populationEstimate(data, speciesList, ind, iteration, nTree, seed);
+
+        JSONObject out = new JSONObject();
+        JSONArray arr = new JSONArray();
+        for (PopulationEstimateItem it : items) {
+            JSONObject o = new JSONObject();
+            o.put("species", it.getSpecies());
+            o.put("speciesName", it.getSpeciesName());
+            o.put("noInd", it.getNoInd());
+            o.put("ciLow", it.getCiLow());
+            o.put("ciHigh", it.getCiHigh());
+            JSONArray indArr = new JSONArray();
+            if (it.getIndividual() != null) {
+                for (double v : it.getIndividual()) {
+                    indArr.add(v);
+                }
+            }
+            o.put("individual", indArr);
+            o.put("recordCount", it.getRecordCount());
+            o.put("cameraCount", it.getCameraCount());
+            arr.add(o);
+        }
+        out.put("items", arr);
+        return out;
+    }
+
+    /**
+     * POST /es/stat/densityEstimate（报表步骤 2：种群密度估计）
+     * body: { cellSize: 0.01, nTree: 200, seed: 1234, data: [...] 或 ES 查询参数 }
+     * 返回栅格 {nx, ny, x0, y0, cellSize, values[], maxValue, cameraCount, photoCount}
+     */
+    @PostMapping("/densityEstimate")
+    public JSONObject densityEstimate(@RequestBody JSONObject param) {
+        List<CameraPoint> data = cameraData(param);
+        double cellSize = getDouble(param, "cellSize", 0.01);
+        int nTree = getInt(param, "nTree", 200);
+        long seed = getLong(param, "seed", 1234L);
+        RasterResult raster = service.densityEstimate(data, cellSize, nTree, seed);
+        return rasterToJson(raster);
+    }
+
+    /**
+     * POST /es/stat/habitatArea（报表步骤 3：栖息地面积分析）
+     * body: { threshold: 0（≤0 自动 max-Kappa）, raster: {nx,ny,x0,y0,cellSize,values},
+     *        data: [...]（相机点位 = 出现样点，可用 ES 查询参数代替）}
+     * 返回 {threshold, method, suitableCells, totalCells, areaKm2, binary[], ...栅格几何}
+     */
+    @PostMapping("/habitatArea")
+    public JSONObject habitatArea(@RequestBody JSONObject param) {
+        RasterResult raster = parseRaster(param.getJSONObject("raster"));
+        List<CameraPoint> presence = cameraData(param);
+        double manual = getDouble(param, "threshold", 0.0);
+        HabitatAreaResult res = service.habitatArea(raster, presence, manual);
+
+        JSONObject out = new JSONObject();
+        out.put("threshold", res.getThreshold());
+        out.put("method", res.getMethod());
+        out.put("suitableCells", res.getSuitableCells());
+        out.put("totalCells", res.getTotalCells());
+        out.put("areaKm2", res.getAreaKm2());
+        out.put("nx", res.getNx());
+        out.put("ny", res.getNy());
+        out.put("x0", res.getX0());
+        out.put("y0", res.getY0());
+        out.put("cellSize", res.getCellSize());
+        out.put("maxValue", res.getMaxValue());
+        JSONArray bin = new JSONArray();
+        if (res.getBinary() != null) {
+            for (int v : res.getBinary()) {
+                bin.add(v);
+            }
+        }
+        out.put("binary", bin);
+        return out;
+    }
+
+    /**
+     * POST /es/stat/habitatRange（报表步骤 4：栖息地分布范围）
+     * body: { habitat: {nx,ny,x0,y0,cellSize,suitableCells,binary[]} }（步骤 3 输出）
+     * 返回 {polygon: [[lon,lat],...], areaKm2, suitableCells, totalCells, suitableRatio}
+     */
+    @PostMapping("/habitatRange")
+    public JSONObject habitatRange(@RequestBody JSONObject param) {
+        JSONObject h = param.getJSONObject("habitat");
+        if (h == null) {
+            throw new IllegalArgumentException("缺少 habitat 参数（应为 habitatArea 的输出）");
+        }
+        HabitatAreaResult area = new HabitatAreaResult();
+        area.setNx(h.getIntValue("nx"));
+        area.setNy(h.getIntValue("ny"));
+        area.setX0(h.getDoubleValue("x0"));
+        area.setY0(h.getDoubleValue("y0"));
+        area.setCellSize(h.getDoubleValue("cellSize"));
+        area.setSuitableCells(h.getIntValue("suitableCells"));
+        JSONArray binArr = h.getJSONArray("binary");
+        int[] binary = new int[binArr == null ? 0 : binArr.size()];
+        if (binArr != null) {
+            for (int i = 0; i < binary.length; i++) {
+                binary[i] = binArr.getIntValue(i);
+            }
+        }
+        area.setBinary(binary);
+
+        HabitatRangeResult res = service.habitatRange(area);
+
+        JSONObject out = new JSONObject();
+        JSONArray poly = new JSONArray();
+        if (res.getPolygon() != null) {
+            for (double[] p : res.getPolygon()) {
+                JSONArray pt = new JSONArray();
+                pt.add(p[0]);
+                pt.add(p[1]);
+                poly.add(pt);
+            }
+        }
+        // 各连通斑块凸包（按面积降序）
+        JSONArray polys = new JSONArray();
+        if (res.getPolygons() != null) {
+            for (double[][] ring : res.getPolygons()) {
+                JSONArray r = new JSONArray();
+                if (ring != null) {
+                    for (double[] p : ring) {
+                        JSONArray pt = new JSONArray();
+                        pt.add(p[0]);
+                        pt.add(p[1]);
+                        r.add(pt);
+                    }
+                }
+                polys.add(r);
+            }
+        }
+        out.put("polygon", poly);
+        out.put("polygons", polys);
+        out.put("clusterCount", res.getClusterCount());
+        out.put("areaKm2", res.getAreaKm2());
+        out.put("suitableCells", res.getSuitableCells());
+        out.put("totalCells", res.getTotalCells());
+        out.put("suitableRatio", res.getSuitableRatio());
+        return out;
+    }
+
+    /** RasterResult → JSON。 */
+    private static JSONObject rasterToJson(RasterResult r) {
+        JSONObject o = new JSONObject();
+        o.put("nx", r.getNx());
+        o.put("ny", r.getNy());
+        o.put("x0", r.getX0());
+        o.put("y0", r.getY0());
+        o.put("cellSize", r.getCellSize());
+        o.put("maxValue", r.getMaxValue());
+        o.put("cameraCount", r.getCameraCount());
+        o.put("photoCount", r.getPhotoCount());
+        JSONArray vals = new JSONArray();
+        if (r.getValues() != null) {
+            for (double v : r.getValues()) {
+                vals.add(v);
+            }
+        }
+        o.put("values", vals);
+        return o;
+    }
+
+    /** 前端传入栅格 JSON → RasterResult。 */
+    private static RasterResult parseRaster(JSONObject r) {
+        if (r == null) {
+            throw new IllegalArgumentException("缺少 raster 参数（应为 densityEstimate 的输出）");
+        }
+        RasterResult raster = new RasterResult();
+        raster.setNx(r.getIntValue("nx"));
+        raster.setNy(r.getIntValue("ny"));
+        raster.setX0(r.getDoubleValue("x0"));
+        raster.setY0(r.getDoubleValue("y0"));
+        raster.setCellSize(r.getDoubleValue("cellSize"));
+        raster.setMaxValue(r.getDoubleValue("maxValue"));
+        JSONArray vals = r.getJSONArray("values");
+        double[] values = new double[vals == null ? 0 : vals.size()];
+        if (vals != null) {
+            for (int i = 0; i < values.length; i++) {
+                values[i] = vals.getDoubleValue(i);
+            }
+        }
+        raster.setValues(values);
+        return raster;
+    }
+
+    // =====================================================================
+    // fastjson 1.x 兼容辅助（getDoubleValue(key, def) 等带默认值重载是 fastjson2 API）
+    // =====================================================================
+
+    private static double getDouble(JSONObject o, String key, double def) {
+        Double v = o.getDouble(key);
+        return v == null ? def : v;
+    }
+
+    private static int getInt(JSONObject o, String key, int def) {
+        Integer v = o.getInteger(key);
+        return v == null ? def : v;
+    }
+
+    private static long getLong(JSONObject o, String key, long def) {
+        Long v = o.getLong(key);
+        return v == null ? def : v;
+    }
+
+    /** 聚合点位视图（避免在 lambda 里再构造 JSONObject 嵌套）。 */
+    private static List<CamtrapAggView> toAggViews(PlotCamtrap.Result result) {
+        List<CamtrapAggView> views = new java.util.ArrayList<>(result.getAggPoints().size());
+        result.getAggPoints().forEach(p -> views.add(new CamtrapAggView(p.getLat(), p.getLon(), p.getCount())));
+        return views;
+    }
+
+    private static final class CamtrapAggView {
+        private final double lat;
+        private final double lon;
+        private final long count;
+
+        private CamtrapAggView(double lat, double lon, long count) {
+            this.lat = lat;
+            this.lon = lon;
+            this.count = count;
+        }
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/domain/SpeciesMovementParam.java

@@ -0,0 +1,13 @@
+package net.hzvtc.stat.domain;
+
+import lombok.Data;
+
+/** Camera-trap movement parameters loaded from MySQL. */
+@Data
+public class SpeciesMovementParam {
+
+    private double stepL;
+    private double bias;
+    private double rangeKm2;
+    private int ind;
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/dto/CameraPoint.java

@@ -0,0 +1,46 @@
+package net.hzvtc.stat.dto;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+/**
+ * cameratrapR 中 trapresult 数据框的 Java 表示（plotCamtrap / Rowcliffe / simuCamtrap / predictCamtrap 的输入）。
+ *
+ * <p>对应 R data.frame 列：<code>Lon</code>、<code>Lat</code>、<code>Group_size</code>、<code>Date</code>、<code>Time</code>。</p>
+ *
+ * <p>各字段语义：
+ * <ul>
+ *   <li>Lon / Lat：相机拍摄位点的经纬度（度，WGS84）</li>
+ *   <li>GroupSize：本条记录对应物种的群体大小（每张照片/视频中个体数）</li>
+ *   <li>Date：拍摄日期（yyyy-MM-dd）</li>
+ *   <li>Time：拍摄时间（HH:mm:ss）</li>
+ * </ul>
+ * </p>
+ */
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+public class CameraPoint {
+
+    /** 经度（度）。 */
+    private double lon;
+
+    /** 纬度（度）。 */
+    private double lat;
+
+    /** 群体大小（单张记录中的个体数）。 */
+    private int groupSize;
+
+    /** 日期，字符串 yyyy-MM-dd。 */
+    private String date;
+
+    /** 时间，字符串 HH:mm:ss。 */
+    private String time;
+
+    /** 物种名（ES scientific_name / CSV species 列；多物种统计与密度估计用，可为空）。 */
+    private String species;
+
+    /** 物种中文名（ES species_name / CSV speciesName 列；物种过滤时与学名共同参与匹配，可为空）。 */
+    private String speciesName;
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/dto/CamtrapAggPoint.java

@@ -0,0 +1,25 @@
+package net.hzvtc.stat.dto;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+/**
+ * plotCamtrap 输出：按 (Lat, Lon) 聚合后的相机点位（每个点位上的照片总次数 Count）。
+ *
+ * <p>对应 R 中 <code>sum = aggregate(x$Group_size, by=list(x$Lat,x$Lon), sum)</code> 的输出。</p>
+ */
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+public class CamtrapAggPoint {
+
+    /** 纬度（度）。 */
+    private double lat;
+
+    /** 经度（度）。 */
+    private double lon;
+
+    /** 该点位累计的 GroupSize 总和（用于决定绘图时圆点大小：<code>cex=Count*circle.size</code>）。 */
+    private long count;
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/dto/CamtrapScatter.java

@@ -0,0 +1,33 @@
+package net.hzvtc.stat.dto;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+/**
+ * plotCamtrap 输出：单条记录的散点（jitter 后）坐标。
+ *
+ * <p>对应 R 中 <code>jitter(X$Lon, factor=point.scatter)</code> / <code>jitter(X$Lat, factor=point.scatter)</code>。</p>
+ *
+ * <p>每个原始记录（Group_size &gt; 0）都会产出一个 jitter 后坐标点；前端画散点。</p>
+ */
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+public class CamtrapScatter {
+
+    /** jitter 后的经度。 */
+    private double lon;
+
+    /** jitter 后的纬度。 */
+    private double lat;
+
+    /** 原始日期（用于按时间上色）。 */
+    private String date;
+
+    /** 原始时间。 */
+    private String time;
+
+    /** 原始群体大小。 */
+    private int groupSize;
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/dto/ChainLengthItem.java

@@ -0,0 +1,31 @@
+package net.hzvtc.stat.dto;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+/**
+ * chainLengths 输出行：每个物种的足迹链长度汇总。
+ */
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+public class ChainLengthItem {
+
+    private String species;
+
+    /** 平均链长（km）。 */
+    private double distance;
+
+    /** 标准差。 */
+    private double distSd;
+
+    /** 平均步长（m）。 */
+    private double stepL;
+
+    /** 推算步数（30 天）。 */
+    private long stepNo;
+
+    /** 链样本数。 */
+    private int n;
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/dto/ChainRecord.java

@@ -0,0 +1,27 @@
+package net.hzvtc.stat.dto;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+/**
+ * chainDB 行：单条足迹链记录，附 Species、Line 字段，用于多链多物种聚合。
+ *
+ * <p>对应 R 中 chainDB 数据框（multi-species homeRanges / chainLengths 的输入）。</p>
+ */
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+public class ChainRecord {
+
+    private String species;
+
+    /** 链编号（同物种可有多条链）。 */
+    private int line;
+
+    private double lon;
+    private double lat;
+
+    /** 记录时间字符串。 */
+    private String date;
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/dto/DensitySeries.java

@@ -0,0 +1,37 @@
+package net.hzvtc.stat.dto;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+/**
+ * 核密度估计（KDE）曲线数据：x[] / y[] 等长数组，用于前端画 density 曲线。
+ *
+ * <p>对应 R 中 <code>density(times, bw)</code> 返回对象的可视化数据。</p>
+ *
+ * <p>字段语义：
+ * <ul>
+ *   <li>x：采样点序列（升序）</li>
+ *   <li>y：在 x 处的密度值</li>
+ *   <li>bandwidth：核密度带宽 bw（参考输出，便于调试）</li>
+ *   <li>label：曲线标签（如 "bw=0.3"、"bw=2"）</li>
+ * </ul>
+ * </p>
+ */
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+public class DensitySeries {
+
+    /** x 采样点序列（升序）。 */
+    private double[] x;
+
+    /** 密度值序列，与 <code>x</code> 等长。 */
+    private double[] y;
+
+    /** 核密度带宽（bandwidth）。 */
+    private double bandwidth;
+
+    /** 曲线标签（用于前端 legend）。 */
+    private String label;
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/dto/FootprintPoint.java

@@ -0,0 +1,22 @@
+package net.hzvtc.stat.dto;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+/**
+ * plotFootprint 输入 / 输出元素：单个足迹链节点（Lon, Lat, Date）。
+ *
+ * <p>R 中 chain 数据框列：<code>Lon</code>、<code>Lat</code>、<code>Date</code>（按时间排序、采样间隔约 1 秒）。</p>
+ */
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+public class FootprintPoint {
+
+    private double lon;
+    private double lat;
+
+    /** 记录时间，字符串 yyyy-MM-dd HH:mm:ss。 */
+    private String date;
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/dto/FootprintTrace.java

@@ -0,0 +1,27 @@
+package net.hzvtc.stat.dto;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+import java.util.List;
+
+/**
+ * plotFootprint 输出：折线轨迹 + 起止点高亮。
+ *
+ * <p>前端可用 <code>points</code> 顺序连线，并在 <code>startLon, startLat</code>（蓝色三角）与
+ * <code>endLon, endLat</code>（红色方块）画标记。</p>
+ */
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+public class FootprintTrace {
+
+    /** 折线轨迹（按时间顺序）。 */
+    private List<FootprintPoint> points;
+
+    private double startLon;
+    private double startLat;
+    private double endLon;
+    private double endLat;
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/dto/HabitatAreaResult.java

@@ -0,0 +1,46 @@
+package net.hzvtc.stat.dto;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+/**
+ * 栖息地面积分析输出：基于最优阈值的适宜生境二值栅格。
+ *
+ * <p>阈值默认用 max-Kappa 法（以相机所在格为出现样点、背景格为未出现样点，
+ * 遍历候选阈值取 Cohen's Kappa 最大者），每个物种因密度栅格不同而阈值不同；
+ * 也可由前端显式传入阈值覆盖。</p>
+ */
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+public class HabitatAreaResult {
+
+    /** 采用的阈值（密度值 ≥ 阈值视为适宜生境）。 */
+    private double threshold;
+
+    /** 阈值确定方法：maxKappa / manual。 */
+    private String method;
+
+    /** 适宜生境格数。 */
+    private int suitableCells;
+
+    /** 总格数。 */
+    private int totalCells;
+
+    /** 适宜生境面积（km²，按格面积 × 格数，格面积随纬度校正）。 */
+    private double areaKm2;
+
+    /** ---- 栅格几何（与输入密度栅格一致，供下一步分布范围使用）---- */
+    private int nx;
+    private int ny;
+    private double x0;
+    private double y0;
+    private double cellSize;
+
+    /** 二值栅格（1 = 适宜生境，0 = 不适宜；行优先，row 0 最南）。 */
+    private int[] binary;
+
+    /** 透传的源密度栅格最大值（前端图例用）。 */
+    private double maxValue;
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/dto/HabitatRangeResult.java

@@ -0,0 +1,36 @@
+package net.hzvtc.stat.dto;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+/**
+ * 栖息地分布范围输出：按连通斑块分别求最小凸包（不再跨斑块合并，
+ * 避免散布斑块之间的空隙被单一凸包圈入导致范围虚高）。
+ */
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+public class HabitatRangeResult {
+
+    /** 最大斑块凸包多边形顶点（闭合环，最后一个点 = 第一个点），[i][0]=lon，[i][1]=lat。 */
+    private double[][] polygon;
+
+    /** 各连通斑块凸包多边形（按面积降序；polygon = 其中最大者）。 */
+    private double[][][] polygons;
+
+    /** 连通斑块数。 */
+    private int clusterCount;
+
+    /** 全部斑块凸包面积之和（km²）。 */
+    private double areaKm2;
+
+    /** 适宜生境格数（输入二值栅格中 =1 的格子数）。 */
+    private int suitableCells;
+
+    /** 总格数。 */
+    private int totalCells;
+
+    /** 栖息地面积占分布范围面积的比例（0-1）。 */
+    private double suitableRatio;
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/dto/HomeRangeItem.java

@@ -0,0 +1,25 @@
+package net.hzvtc.stat.dto;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+/**
+ * homeRanges 输出行：每个物种的家域面积（km²）。
+ */
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+public class HomeRangeItem {
+
+    private String species;
+
+    /** 平均家域面积（km²）。 */
+    private double area;
+
+    /** 标准差。 */
+    private double sd;
+
+    /** 链样本数。 */
+    private int n;
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/dto/MoveBiasResult.java

@@ -0,0 +1,25 @@
+package net.hzvtc.stat.dto;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+/**
+ * moveBias 输出：步长统计量与转角统计量。
+ *
+ * <p>对应 R 返回：<code>c(mean(dist), sd(dist), sd(delta.th))</code>。</p>
+ */
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+public class MoveBiasResult {
+
+    /** 步长均值（m）。 */
+    private double meanStepLength;
+
+    /** 步长标准差（m）。 */
+    private double sdStepLength;
+
+    /** 转向角标准差（度）。 */
+    private double sdAngularDeflection;
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/dto/PopulationEstimateItem.java

@@ -0,0 +1,41 @@
+package net.hzvtc.stat.dto;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+/**
+ * populationEstimate 输出项：单物种的种群大小（数量）估计。
+ *
+ * <p>对应 R 中 simuCamtrap + predictCamtrap 组合的输出：
+ * <code>No_ind</code>（估计值）、<code>CI_L</code>（区间下界）、<code>CI_U</code>（区间上界）。</p>
+ */
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+public class PopulationEstimateItem {
+
+    /** 物种名（ES scientific_name / species_name，CSV species 列；无物种信息时为 "全部"）。 */
+    private String species;
+
+    /** 物种中文名（ES species_name；无中文名时回退为 species）。 */
+    private String speciesName;
+
+    /** 估计个体数 No_ind（随机森林树预测中位数）。 */
+    private double noInd;
+
+    /** 95% 置信区间下界 CI_L。 */
+    private double ciLow;
+
+    /** 95% 置信区间上界 CI_U。 */
+    private double ciHigh;
+
+    /** 每棵树的预测值采样（≤200，供箱线图）。 */
+    private double[] individual;
+
+    /** 参与计算的记录数。 */
+    private int recordCount;
+
+    /** 参与计算的相机点位数。 */
+    private int cameraCount;
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/dto/PredictionResult.java

@@ -0,0 +1,30 @@
+package net.hzvtc.stat.dto;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+/**
+ * predictCamtrap 输出：随机森林 1000 棵树的预测中位数与 95% 置信区间。
+ *
+ * <p>对应 R 返回：<code>data.frame(No_ind, CI_L, CI_U)</code>。</p>
+ */
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+public class PredictionResult {
+
+    /** 估计的个体数（中位数）。 */
+    private double noInd;
+
+    /** 95% 置信区间下界。 */
+    private double ciLow;
+
+    /** 95% 置信区间上界。 */
+    private double ciHigh;
+
+    /**
+     * 每棵树的预测个体数（供前端画箱线图；最多 200 个采样值，中位数/CI 仍基于全量树）。
+     */
+    private double[] individual;
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/dto/RasterResult.java

@@ -0,0 +1,63 @@
+package net.hzvtc.stat.dto;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+/**
+ * 种群密度估计（随机森林物种分布模型）输出的栅格结果。
+ *
+ * <p>栅格以相机点位分布范围为边界（四周外扩 3 个格宽），行优先存储：
+ * <code>values[row * nx + col]</code>，row 0 = 最南行，col 0 = 最西列。
+ * 每格值域 [0, 1]，表示该物种出现在该格子的概率。</p>
+ */
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+public class RasterResult {
+
+    /** 列数（西 → 东）。 */
+    private int nx;
+
+    /** 行数（南 → 北）。 */
+    private int ny;
+
+    /** 西南角经度（度）。 */
+    private double x0;
+
+    /** 西南角纬度（度）。 */
+    private double y0;
+
+    /** 格宽（度，经纬度同值）。 */
+    private double cellSize;
+
+    /** 每格出现概率（长度 = nx * ny，行优先，row 0 最南）。 */
+    private double[] values;
+
+    /** 栅格中的最大概率值。 */
+    private double maxValue;
+
+    /** 参与建模的相机点位数。 */
+    private int cameraCount;
+
+    /** 参与建模的照片（记录）总数。 */
+    private long photoCount;
+
+    /** 格子中心经度（度）。 */
+    public double cellCenterLon(int col) {
+        return x0 + (col + 0.5) * cellSize;
+    }
+
+    /** 格子中心纬度（度）。 */
+    public double cellCenterLat(int row) {
+        return y0 + (row + 0.5) * cellSize;
+    }
+
+    /** 指定格子的值（越界返回 0）。 */
+    public double valueAt(int row, int col) {
+        if (row < 0 || row >= ny || col < 0 || col >= nx) {
+            return 0.0;
+        }
+        return values[row * nx + col];
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/dto/SimulationResult.java

@@ -0,0 +1,27 @@
+package net.hzvtc.stat.dto;
+
+import lombok.AllArgsConstructor;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+/**
+ * simuCamtrap 输出：模拟结果矩阵。
+ *
+ * <p>对应 R 返回：<code>data.frame(Ind, [每台相机的 Count])</code>。
+ * 行 = ind*iteration 次模拟；列数 = 相机数 + 1（第一列为个体数 Ind）。</p>
+ */
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+public class SimulationResult {
+
+    /** 每行的个体数（长度 = ind*iteration）。 */
+    private int[] ind;
+
+    /** 每个相机位的拍照次数（外层长度 = 行数；内层长度 = 相机数）。 */
+    private long[][] cameraCounts;
+
+    /** 相机坐标（与 cameraCounts 列对应）。 */
+    private double[] cameraLon;
+    private double[] cameraLat;
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/mapper/SpeciesMovementParamMapper.java

@@ -0,0 +1,21 @@
+package net.hzvtc.stat.mapper;
+
+import net.hzvtc.stat.domain.SpeciesMovementParam;
+import org.apache.ibatis.annotations.Mapper;
+import org.apache.ibatis.annotations.Param;
+import org.apache.ibatis.annotations.Select;
+
+@Mapper
+public interface SpeciesMovementParamMapper {
+
+    @Select("SELECT step_length AS stepL, bias_degree AS bias, range_km2 AS rangeKm2, "
+            + "max_individuals AS ind FROM camera_trap_species_param "
+            + "WHERE enabled = 1 AND (species_name = #{species} OR scientific_name = #{species} "
+            + "OR chinese_name = #{species}) LIMIT 1")
+    SpeciesMovementParam selectBySpecies(@Param("species") String species);
+
+    @Select("SELECT step_length AS stepL, bias_degree AS bias, range_km2 AS rangeKm2, "
+            + "max_individuals AS ind FROM camera_trap_species_param "
+            + "WHERE enabled = 1 AND species_name = '__DEFAULT__' LIMIT 1")
+    SpeciesMovementParam selectDefault();
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/service/CameraTrapStatService.java

@@ -0,0 +1,131 @@
+package net.hzvtc.stat.service;
+
+import com.alibaba.fastjson.JSONArray;
+import net.hzvtc.stat.algorithm.Geo2Proj;
+import net.hzvtc.stat.algorithm.PlotCamtrap;
+import net.hzvtc.stat.dto.CameraPoint;
+import net.hzvtc.stat.dto.ChainLengthItem;
+import net.hzvtc.stat.dto.ChainRecord;
+import net.hzvtc.stat.dto.DensitySeries;
+import net.hzvtc.stat.dto.FootprintPoint;
+import net.hzvtc.stat.dto.FootprintTrace;
+import net.hzvtc.stat.dto.HabitatAreaResult;
+import net.hzvtc.stat.dto.HabitatRangeResult;
+import net.hzvtc.stat.dto.HomeRangeItem;
+import net.hzvtc.stat.dto.MoveBiasResult;
+import net.hzvtc.stat.dto.PopulationEstimateItem;
+import net.hzvtc.stat.dto.PredictionResult;
+import net.hzvtc.stat.dto.RasterResult;
+import net.hzvtc.stat.dto.SimulationResult;
+
+import java.util.List;
+
+/**
+ * cameratrapR 11 个函数的业务接口。
+ *
+ * <p>实现见 {@link net.hzvtc.stat.service.impl.CameraTrapStatServiceImpl}。</p>
+ */
+public interface CameraTrapStatService {
+
+    // ============================== plotCamtrap ==============================
+
+    PlotCamtrap.Result plotCamtrap(List<CameraPoint> data, double circleSize, double pointScatter);
+
+    // ============================== dailyRhythm ==============================
+
+    List<DensitySeries> dailyRhythm(List<CameraPoint> data);
+
+    // ============================== geo2proj ==============================
+
+    List<Geo2Proj.UtmPoint> geo2proj(List<CameraPoint> data);
+
+    List<Geo2Proj.UtmPoint> geo2projFootprint(List<FootprintPoint> data);
+
+    // ============================== simuCamtrap ==============================
+
+    SimulationResult simuCamtrap(List<CameraPoint> data, String species, int ind, int iteration);
+
+    /** 自定义运动参数版本（保留 R 全部参数可调）。 */
+    SimulationResult simuCamtrapCustom(List<CameraPoint> data, String species,
+                                        double detect, double[] bearing,
+                                        int stepN, double stepV,
+                                        double stepL, double biasDeg,
+                                        double rangeM, int ind, int iteration);
+
+    // ============================== predictCamtrap ==============================
+
+    PredictionResult predictCamtrap(SimulationResult simu, List<CameraPoint> realData,
+                                    int nTree, long seed);
+
+    // ============================== populationEstimate（报表：种群大小估计） ==============================
+
+    /**
+     * 多物种种群大小（数量）估计：按 species 分组逐物种执行 simuCamtrap + predictCamtrap。
+     *
+     * @param data        相机记录（含 species 字段）
+     * @param speciesList 物种过滤（空 = 数据中出现的全部物种）
+     * @param ind         单物种模拟最大个体数
+     * @param iteration   模拟迭代次数
+     * @param nTree       随机森林树数
+     * @param seed        随机种子
+     */
+    List<PopulationEstimateItem> populationEstimate(List<CameraPoint> data, List<String> speciesList,
+                                                    int ind, int iteration, int nTree, long seed);
+
+    // ============================== densityEstimate（报表：种群密度估计） ==============================
+
+    /** 随机森林 SDM 栅格化出现概率（输入：相机点位 + 积累照片总数）。 */
+    RasterResult densityEstimate(List<CameraPoint> data, double cellSize, int nTree, long seed);
+
+    // ============================== habitatArea（报表：栖息地面积分析） ==============================
+
+    /** 密度栅格 + 最优阈值 → 适宜生境二值栅格（manual ≤ 0 时自动 max-Kappa）。 */
+    HabitatAreaResult habitatArea(RasterResult raster, List<CameraPoint> presence, double manual);
+
+    // ============================== habitatRange（报表：栖息地分布范围） ==============================
+
+    /** 适宜生境二值栅格 → 最小凸包分布范围多边形。 */
+    HabitatRangeResult habitatRange(HabitatAreaResult area);
+
+    // ============================== plotFootprint ==============================
+
+    FootprintTrace plotFootprint(List<FootprintPoint> chain);
+
+    // ============================== moveBias ==============================
+
+    MoveBiasResult moveBias(List<FootprintPoint> chain, int scale);
+
+    // ============================== Rowcliffe ==============================
+
+    double[] rowcliffe(List<CameraPoint> data, double r, double theta, double v, double duration);
+
+    // ============================== homeRange(s) ==============================
+
+    double homeRange(List<FootprintPoint> chain);
+
+    List<HomeRangeItem> homeRanges(List<ChainRecord> records);
+
+    // ============================== chainLength(s) ==============================
+
+    double chainLength(List<FootprintPoint> chain);
+
+    List<ChainLengthItem> chainLengths(List<ChainRecord> records);
+
+    // =====================================================================
+    // DTO 转换：JSONArray → List<CameraPoint> / ChainRecord / FootprintPoint
+    // （静态方法委托给实现类，调用方无需感知 Impl）
+    // =====================================================================
+
+    /** 前端传入 JSONArray（每项含 lon/lat/groupSize/date/time）→ CameraPoint 列表。 */
+    static List<CameraPoint> toCameraPoints(JSONArray arr) {
+        return net.hzvtc.stat.service.impl.CameraTrapStatServiceImpl.toCameraPoints(arr);
+    }
+
+    static List<FootprintPoint> toFootprintPoints(JSONArray arr) {
+        return net.hzvtc.stat.service.impl.CameraTrapStatServiceImpl.toFootprintPoints(arr);
+    }
+
+    static List<ChainRecord> toChainRecords(JSONArray arr) {
+        return net.hzvtc.stat.service.impl.CameraTrapStatServiceImpl.toChainRecords(arr);
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/service/StatEsDataService.java

@@ -0,0 +1,30 @@
+package net.hzvtc.stat.service;
+
+import com.alibaba.fastjson.JSONObject;
+import net.hzvtc.stat.dto.CameraPoint;
+import net.hzvtc.stat.dto.ChainRecord;
+import net.hzvtc.stat.dto.FootprintPoint;
+
+import java.util.List;
+
+/**
+ * 从 ES 索引 <code>animal_valid_record</code> 加载数据的业务接口。
+ *
+ * <p>实现见 {@link net.hzvtc.stat.service.impl.StatEsDataServiceImpl}。
+ * 记录关联 <code>device_info</code> 表补齐设备经纬度后，转换为 stat 算法所需 DTO。</p>
+ *
+ * <p>查询参数复用 CommonEsUtils.createQuery，支持：
+ * species_id / speciesInIds / deviceIds / dateFrom / dateTo / checked /
+ * recordType / mediaType / mediaTypes 等（与报表模块参数语义一致）。</p>
+ */
+public interface StatEsDataService {
+
+    /** 加载相机记录（plotCamtrap / dailyRhythm / geo2proj / simuCamtrap / rowcliffe 输入）。 */
+    List<CameraPoint> loadCameraPoints(JSONObject param);
+
+    /** 加载足迹链节点（plotFootprint / moveBias / homeRange / chainLength 输入），按时间升序。 */
+    List<FootprintPoint> loadFootprintPoints(JSONObject param);
+
+    /** 加载多链记录（homeRanges / chainLengths 输入），按 species、line、时间排序。 */
+    List<ChainRecord> loadChainRecords(JSONObject param);
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/service/impl/CameraTrapStatServiceImpl.java

@@ -0,0 +1,330 @@
+package net.hzvtc.stat.service.impl;
+
+import com.alibaba.fastjson.JSONArray;
+import com.alibaba.fastjson.JSONObject;
+import lombok.RequiredArgsConstructor;
+import net.hzvtc.stat.algorithm.ChainLength;
+import net.hzvtc.stat.algorithm.DailyRhythm;
+import net.hzvtc.stat.algorithm.DensityEstimate;
+import net.hzvtc.stat.algorithm.Geo2Proj;
+import net.hzvtc.stat.algorithm.HabitatAnalysis;
+import net.hzvtc.stat.algorithm.HabitatRange;
+import net.hzvtc.stat.algorithm.HomeRange;
+import net.hzvtc.stat.algorithm.MoveBias;
+import net.hzvtc.stat.algorithm.PlotCamtrap;
+import net.hzvtc.stat.algorithm.PlotFootprint;
+import net.hzvtc.stat.algorithm.PredictCamtrap;
+import net.hzvtc.stat.algorithm.Rowcliffe;
+import net.hzvtc.stat.algorithm.SimuCamtrap;
+import net.hzvtc.stat.dto.CameraPoint;
+import net.hzvtc.stat.dto.ChainLengthItem;
+import net.hzvtc.stat.dto.ChainRecord;
+import net.hzvtc.stat.dto.DensitySeries;
+import net.hzvtc.stat.dto.FootprintPoint;
+import net.hzvtc.stat.dto.FootprintTrace;
+import net.hzvtc.stat.dto.HabitatAreaResult;
+import net.hzvtc.stat.dto.HabitatRangeResult;
+import net.hzvtc.stat.dto.HomeRangeItem;
+import net.hzvtc.stat.dto.MoveBiasResult;
+import net.hzvtc.stat.dto.PopulationEstimateItem;
+import net.hzvtc.stat.dto.PredictionResult;
+import net.hzvtc.stat.dto.RasterResult;
+import net.hzvtc.stat.dto.SimulationResult;
+import net.hzvtc.stat.domain.SpeciesMovementParam;
+import net.hzvtc.stat.mapper.SpeciesMovementParamMapper;
+import net.hzvtc.stat.service.CameraTrapStatService;
+import net.hzvtc.stat.util.RandomUtils;
+import org.springframework.stereotype.Service;
+
+import java.util.ArrayList;
+import java.util.LinkedHashMap;
+import java.util.LinkedHashSet;
+import java.util.List;
+import java.util.Map;
+import java.util.Set;
+
+/**
+ * {@link CameraTrapStatService} 实现：调用统计模型，并从 MySQL 加载物种运动参数。
+ */
+@Service
+@RequiredArgsConstructor
+public class CameraTrapStatServiceImpl implements CameraTrapStatService {
+
+    private final SpeciesMovementParamMapper speciesMovementParamMapper;
+
+    // ============================== plotCamtrap ==============================
+
+    @Override
+    public PlotCamtrap.Result plotCamtrap(List<CameraPoint> data, double circleSize, double pointScatter) {
+        return PlotCamtrap.plotCamtrap(data, circleSize, pointScatter);
+    }
+
+    // ============================== dailyRhythm ==============================
+
+    @Override
+    public List<DensitySeries> dailyRhythm(List<CameraPoint> data) {
+        return DailyRhythm.dailyRhythm(data);
+    }
+
+    // ============================== geo2proj ==============================
+
+    @Override
+    public List<Geo2Proj.UtmPoint> geo2proj(List<CameraPoint> data) {
+        return Geo2Proj.convertToDto(data);
+    }
+
+    @Override
+    public List<Geo2Proj.UtmPoint> geo2projFootprint(List<FootprintPoint> data) {
+        double[][] xy = Geo2Proj.convertFootprint(data);
+        List<Geo2Proj.UtmPoint> out = new ArrayList<>(xy.length);
+        for (double[] v : xy) {
+            out.add(new Geo2Proj.UtmPoint(v[0], v[1]));
+        }
+        return out;
+    }
+
+    // ============================== simuCamtrap ==============================
+
+    @Override
+    public SimulationResult simuCamtrap(List<CameraPoint> data, String species, int ind, int iteration) {
+        RandomUtils.setSeed(RandomUtils.DEFAULT_SEED);
+        return simulateBySpecies(data, species, ind, iteration);
+    }
+
+    @Override
+    public SimulationResult simuCamtrapCustom(List<CameraPoint> data, String species,
+                                               double detect, double[] bearing,
+                                               int stepN, double stepV,
+                                               double stepL, double biasDeg,
+                                               double rangeM, int ind, int iteration) {
+        return SimuCamtrap.simuCamtrap(data, species, detect, bearing, stepN, stepV,
+                stepL, biasDeg, rangeM, ind, iteration);
+    }
+
+    // ============================== predictCamtrap ==============================
+
+    @Override
+    public PredictionResult predictCamtrap(SimulationResult simu, List<CameraPoint> realData,
+                                           int nTree, long seed) {
+        return PredictCamtrap.predictCamtrap(simu, realData, nTree, seed);
+    }
+
+    // ============================== populationEstimate ==============================
+
+    @Override
+    public List<PopulationEstimateItem> populationEstimate(List<CameraPoint> data, List<String> speciesList,
+                                                           int ind, int iteration, int nTree, long seed) {
+        List<PopulationEstimateItem> items = new ArrayList<>();
+        if (data == null || data.isEmpty()) {
+            return items;
+        }
+
+        // 按 species 分组（保持数据出现顺序）
+        Map<String, List<CameraPoint>> groups = new LinkedHashMap<>();
+        for (CameraPoint p : data) {
+            String sp = p.getSpecies() == null ? "" : p.getSpecies().trim();
+            groups.computeIfAbsent(sp, k -> new ArrayList<>()).add(p);
+        }
+
+        // 物种过滤：学名（species）与中文名（speciesName）共同参与匹配（忽略大小写）
+        Set<String> filter = null;
+        if (speciesList != null) {
+            filter = new LinkedHashSet<>();
+            for (String s : speciesList) {
+                if (s != null && !s.trim().isEmpty()) {
+                    filter.add(s.trim());
+                }
+            }
+        }
+
+        for (Map.Entry<String, List<CameraPoint>> e : groups.entrySet()) {
+            if (filter != null && !filter.isEmpty() && !matchSpecies(e.getValue(), filter)) {
+                continue;
+            }
+            List<CameraPoint> group = e.getValue();
+            if (group.isEmpty()) {
+                continue;
+            }
+
+            CameraPoint first = group.get(0);
+
+            // 每个物种用独立派生种子重置模拟随机源（等价 R set.seed），保证同条件结果可复现
+            RandomUtils.setSeed(seed * 1_000_003L + e.getKey().hashCode());
+            SimulationResult simu = simulateBySpecies(group, e.getKey(), ind, iteration);
+            PredictionResult pred = PredictCamtrap.predictCamtrap(simu, group, nTree, seed);
+
+            // 中文名：取组内第一条记录的 species_name，无则回退为学名
+            String spName = first.getSpeciesName();
+            String speciesKey = e.getKey().isEmpty() ? "全部" : e.getKey();
+            if (spName == null || spName.trim().isEmpty()) {
+                spName = speciesKey;
+            }
+
+            int cameraN = simu.getCameraLon() == null ? 0 : simu.getCameraLon().length;
+            items.add(new PopulationEstimateItem(
+                    speciesKey, spName,
+                    pred.getNoInd(), pred.getCiLow(), pred.getCiHigh(),
+                    pred.getIndividual(), group.size(), cameraN));
+        }
+        return items;
+    }
+
+    private SimulationResult simulateBySpecies(List<CameraPoint> data, String species, int ind, int iteration) {
+        SpeciesMovementParam param = null;
+        if (species != null && !species.trim().isEmpty()) {
+            param = speciesMovementParamMapper.selectBySpecies(species.trim());
+        }
+        if (param == null) {
+            param = speciesMovementParamMapper.selectDefault();
+        }
+        if (param == null) {
+            throw new IllegalStateException("camera_trap_species_param is missing the __DEFAULT__ row");
+        }
+        return SimuCamtrap.simuCamtrap(data, species, 50.0, null, 5000, 2.0,
+                param.getStepL(), param.getBias(), param.getRangeKm2() * 1000.0, ind, iteration);
+    }
+
+    /** 判断分组内任一记录的学名或中文名命中过滤集合（忽略大小写）。 */
+    private static boolean matchSpecies(List<CameraPoint> group, Set<String> filter) {
+        for (CameraPoint p : group) {
+            if (p.getSpecies() != null && filter.contains(p.getSpecies().trim())) {
+                return true;
+            }
+            if (filter.stream().anyMatch(f -> p.getSpeciesName() != null
+                    && f.equalsIgnoreCase(p.getSpeciesName().trim()))) {
+                return true;
+            }
+            if (p.getSpecies() != null && filter.stream().anyMatch(f -> f.equalsIgnoreCase(p.getSpecies().trim()))) {
+                return true;
+            }
+        }
+        return false;
+    }
+
+    // ============================== densityEstimate ==============================
+
+    @Override
+    public RasterResult densityEstimate(List<CameraPoint> data, double cellSize, int nTree, long seed) {
+        return DensityEstimate.densityEstimate(data, cellSize, nTree, seed);
+    }
+
+    // ============================== habitatArea ==============================
+
+    @Override
+    public HabitatAreaResult habitatArea(RasterResult raster, List<CameraPoint> presence, double manual) {
+        return HabitatAnalysis.habitatArea(raster, presence, manual);
+    }
+
+    // ============================== habitatRange ==============================
+
+    @Override
+    public HabitatRangeResult habitatRange(HabitatAreaResult area) {
+        return HabitatRange.habitatRange(area);
+    }
+
+    // ============================== plotFootprint ==============================
+
+    @Override
+    public FootprintTrace plotFootprint(List<FootprintPoint> chain) {
+        return PlotFootprint.plotFootprint(chain);
+    }
+
+    // ============================== moveBias ==============================
+
+    @Override
+    public MoveBiasResult moveBias(List<FootprintPoint> chain, int scale) {
+        return MoveBias.moveBias(chain, scale);
+    }
+
+    // ============================== Rowcliffe ==============================
+
+    @Override
+    public double[] rowcliffe(List<CameraPoint> data, double r, double theta, double v, double duration) {
+        return Rowcliffe.rowcliffe(data, r, theta, v, duration);
+    }
+
+    // ============================== homeRange(s) ==============================
+
+    @Override
+    public double homeRange(List<FootprintPoint> chain) {
+        return HomeRange.homeRange(chain);
+    }
+
+    @Override
+    public List<HomeRangeItem> homeRanges(List<ChainRecord> records) {
+        return HomeRange.homeRanges(records);
+    }
+
+    // ============================== chainLength(s) ==============================
+
+    @Override
+    public double chainLength(List<FootprintPoint> chain) {
+        return ChainLength.chainLength(chain);
+    }
+
+    @Override
+    public List<ChainLengthItem> chainLengths(List<ChainRecord> records) {
+        return ChainLength.chainLengths(records);
+    }
+
+    // =====================================================================
+    // DTO 转换辅助：JSONArray → List<CameraPoint> / ChainRecord / FootprintPoint
+    // =====================================================================
+
+    /** 前端传入 JSONArray（每项含 lon/lat/groupSize/date/time）→ CameraPoint 列表。 */
+    public static List<CameraPoint> toCameraPoints(JSONArray arr) {
+        List<CameraPoint> list = new ArrayList<>();
+        if (arr == null) {
+            return list;
+        }
+        for (int i = 0; i < arr.size(); i++) {
+            JSONObject o = arr.getJSONObject(i);
+            CameraPoint p = new CameraPoint();
+            p.setLon(o.getDoubleValue("lon"));
+            p.setLat(o.getDoubleValue("lat"));
+            p.setGroupSize(o.getIntValue("groupSize"));
+            p.setDate(o.getString("date"));
+            p.setTime(o.getString("time"));
+            String sp = o.getString("species");
+            p.setSpecies(sp == null ? "" : sp);
+            String spName = o.getString("speciesName");
+            p.setSpeciesName(spName == null ? "" : spName);
+            list.add(p);
+        }
+        return list;
+    }
+
+    public static List<FootprintPoint> toFootprintPoints(JSONArray arr) {
+        List<FootprintPoint> list = new ArrayList<>();
+        if (arr == null) {
+            return list;
+        }
+        for (int i = 0; i < arr.size(); i++) {
+            JSONObject o = arr.getJSONObject(i);
+            FootprintPoint p = new FootprintPoint();
+            p.setLon(o.getDoubleValue("lon"));
+            p.setLat(o.getDoubleValue("lat"));
+            p.setDate(o.getString("date"));
+            list.add(p);
+        }
+        return list;
+    }
+
+    public static List<ChainRecord> toChainRecords(JSONArray arr) {
+        List<ChainRecord> list = new ArrayList<>();
+        if (arr == null) {
+            return list;
+        }
+        for (int i = 0; i < arr.size(); i++) {
+            JSONObject o = arr.getJSONObject(i);
+            ChainRecord r = new ChainRecord();
+            r.setSpecies(o.getString("species"));
+            r.setLine(o.getIntValue("line"));
+            r.setLon(o.getDoubleValue("lon"));
+            r.setLat(o.getDoubleValue("lat"));
+            r.setDate(o.getString("date"));
+            list.add(r);
+        }
+        return list;
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/service/impl/StatEsDataServiceImpl.java

@@ -0,0 +1,296 @@
+package net.hzvtc.stat.service.impl;
+
+import co.elastic.clients.elasticsearch.ElasticsearchClient;
+import co.elastic.clients.elasticsearch._types.FieldValue;
+import co.elastic.clients.elasticsearch._types.SortOrder;
+import co.elastic.clients.elasticsearch._types.query_dsl.BoolQuery;
+import co.elastic.clients.elasticsearch.core.SearchRequest;
+import co.elastic.clients.elasticsearch.core.SearchResponse;
+import co.elastic.clients.elasticsearch.core.search.Hit;
+import com.alibaba.fastjson.JSONObject;
+import com.fasterxml.jackson.databind.JsonNode;
+import com.fasterxml.jackson.databind.node.ObjectNode;
+import lombok.RequiredArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+import net.hzvtc.device.domain.DeviceInfo;
+import net.hzvtc.device.service.DeviceInfoService;
+import net.hzvtc.service.impl.CommonEsUtils;
+import net.hzvtc.stat.dto.CameraPoint;
+import net.hzvtc.stat.dto.ChainRecord;
+import net.hzvtc.stat.dto.FootprintPoint;
+import net.hzvtc.stat.service.StatEsDataService;
+import org.springframework.stereotype.Service;
+
+import java.io.IOException;
+import java.time.Instant;
+import java.time.LocalDate;
+import java.time.LocalDateTime;
+import java.time.OffsetDateTime;
+import java.time.ZoneId;
+import java.time.format.DateTimeFormatter;
+import java.util.ArrayList;
+import java.util.Comparator;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Map;
+import java.util.Set;
+
+/**
+ * {@link StatEsDataService} 实现：从 ES 索引 <code>animal_valid_record</code>
+ * 全量加载有效记录（search_after 分页），关联 <code>device_info</code> 表补齐经纬度。
+ *
+ * <p>字段映射：
+ * <ul>
+ *   <li>lon / lat ← device_info.longitude / latitude（按 device_id 关联，无坐标的记录跳过）</li>
+ *   <li>groupSize ← count（缺失按 1）</li>
+ *   <li>date / time ← record_time（转为 Asia/Shanghai 时区）</li>
+ *   <li>species ← scientific_name（缺失用 species_name）</li>
+ *   <li>line ← device_id（同一设备的同物种记录序列视为一条足迹链）</li>
+ * </ul></p>
+ */
+@Slf4j
+@Service
+@RequiredArgsConstructor
+public class StatEsDataServiceImpl implements StatEsDataService {
+
+    private static final String INDEX_NAME = "animal_valid_record";
+
+    private static final int PAGE_SIZE = 1000;
+
+    /** 全量拉取上限，防止误查拖垮服务。 */
+    private static final int MAX_ROWS = 200000;
+
+    private static final DateTimeFormatter FMT = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss");
+
+    private static final ZoneId ZONE = ZoneId.of("Asia/Shanghai");
+
+    private final ElasticsearchClient elasticsearchClient;
+
+    private final DeviceInfoService deviceInfoService;
+
+    // ============================== 对外加载方法 ==============================
+
+    @Override
+    public List<CameraPoint> loadCameraPoints(JSONObject param) {
+        List<ObjectNode> rows = searchAll(param);
+        Map<Long, double[]> locations = deviceLocations(rows);
+        List<CameraPoint> list = new ArrayList<>(rows.size());
+        for (ObjectNode row : rows) {
+            double[] xy = locations.get(deviceId(row));
+            LocalDateTime time = recordTime(row);
+            if (xy == null || time == null) {
+                continue;
+            }
+            CameraPoint p = new CameraPoint();
+            p.setLon(xy[0]);
+            p.setLat(xy[1]);
+            p.setGroupSize(intVal(row, "count", 1));
+            p.setDate(time.toLocalDate().toString());
+            p.setTime(time.format(DateTimeFormatter.ofPattern("HH:mm:ss")));
+            p.setSpecies(species(row));
+            p.setSpeciesName(speciesName(row));
+            list.add(p);
+        }
+        return list;
+    }
+
+    @Override
+    public List<FootprintPoint> loadFootprintPoints(JSONObject param) {
+        List<ObjectNode> rows = searchAll(param);
+        Map<Long, double[]> locations = deviceLocations(rows);
+        List<FootprintPoint> list = new ArrayList<>(rows.size());
+        for (ObjectNode row : rows) {
+            double[] xy = locations.get(deviceId(row));
+            LocalDateTime time = recordTime(row);
+            if (xy == null || time == null) {
+                continue;
+            }
+            FootprintPoint p = new FootprintPoint();
+            p.setLon(xy[0]);
+            p.setLat(xy[1]);
+            p.setDate(time.format(FMT));
+            list.add(p);
+        }
+        list.sort(Comparator.comparing(FootprintPoint::getDate));
+        return list;
+    }
+
+    @Override
+    public List<ChainRecord> loadChainRecords(JSONObject param) {
+        List<ObjectNode> rows = searchAll(param);
+        Map<Long, double[]> locations = deviceLocations(rows);
+        List<ChainRecord> list = new ArrayList<>(rows.size());
+        for (ObjectNode row : rows) {
+            double[] xy = locations.get(deviceId(row));
+            LocalDateTime time = recordTime(row);
+            if (xy == null || time == null) {
+                continue;
+            }
+            ChainRecord r = new ChainRecord();
+            r.setSpecies(species(row));
+            Long dev = deviceId(row);
+            r.setLine(dev == null ? 0 : dev.intValue());
+            r.setLon(xy[0]);
+            r.setLat(xy[1]);
+            r.setDate(time.format(FMT));
+            list.add(r);
+        }
+        list.sort(Comparator.comparing(ChainRecord::getSpecies)
+                .thenComparing(ChainRecord::getLine)
+                .thenComparing(ChainRecord::getDate));
+        return list;
+    }
+
+    // ============================== ES 全量查询（search_after 分页） ==============================
+
+    private List<ObjectNode> searchAll(JSONObject param) {
+        try {
+            BoolQuery bool = CommonEsUtils.createQuery(param).build();
+            List<ObjectNode> rows = new ArrayList<>();
+            List<FieldValue> searchAfter = null;
+            while (rows.size() < MAX_ROWS) {
+                SearchRequest.Builder rb = new SearchRequest.Builder()
+                        .index(INDEX_NAME)
+                        .size(PAGE_SIZE)
+                        .query(q -> q.bool(bool))
+                        .sort(s -> s.field(f -> f.field("id").order(SortOrder.Asc)));
+                if (searchAfter != null) {
+                    rb.searchAfter(searchAfter);
+                }
+                SearchResponse<ObjectNode> resp = elasticsearchClient.search(rb.build(), ObjectNode.class);
+                List<Hit<ObjectNode>> hits = resp.hits().hits();
+                if (hits.isEmpty()) {
+                    break;
+                }
+                for (Hit<ObjectNode> h : hits) {
+                    if (h.source() != null) {
+                        rows.add(h.source());
+                    }
+                }
+                if (hits.size() < PAGE_SIZE) {
+                    break;
+                }
+                searchAfter = hits.get(hits.size() - 1).sort();
+            }
+            if (rows.size() >= MAX_ROWS) {
+                log.warn("stat ES 查询命中数达到上限 {}，结果可能被截断", MAX_ROWS);
+            }
+            return rows;
+        } catch (IOException e) {
+            throw new RuntimeException("查询 ES 索引 " + INDEX_NAME + " 失败", e);
+        }
+    }
+
+    // ============================== 设备坐标关联 ==============================
+
+    /** 青海省经纬度范围（含少量边界余量）： lon 89.4~103.2, lat 31.4~39.4。 */
+    private static final double QINGHAI_LON_MIN = 89.4;
+    private static final double QINGHAI_LON_MAX = 103.2;
+    private static final double QINGHAI_LAT_MIN = 31.4;
+    private static final double QINGHAI_LAT_MAX = 39.4;
+
+    /** 汇总记录中出现的 device_id，逐个查询（本次请求内缓存）取设备坐标。 */
+    private Map<Long, double[]> deviceLocations(List<ObjectNode> rows) {
+        Set<Long> ids = new HashSet<>();
+        for (ObjectNode row : rows) {
+            Long id = deviceId(row);
+            if (id != null) {
+                ids.add(id);
+            }
+        }
+        Map<Long, double[]> map = new HashMap<>(ids.size() * 2);
+        for (Long id : ids) {
+            try {
+                DeviceInfo device = deviceInfoService.selectDeviceInfoById(id);
+                if (device != null && inQinghai(device.getLongitude(), device.getLatitude())) {
+                    map.put(id, new double[]{device.getLongitude(), device.getLatitude()});
+                } else {
+                    log.debug("设备 {} 不存在或坐标（{} , {}）不在青海范围内，相关记录被跳过",
+                            id, device == null ? null : device.getLongitude(),
+                            device == null ? null : device.getLatitude());
+                }
+            } catch (Exception e) {
+                log.warn("查询设备 {} 坐标失败：{}", id, e.getMessage());
+            }
+        }
+        return map;
+    }
+
+    /** 经纬度非 0 且落在青海省范围内。 */
+    private static boolean inQinghai(double lon, double lat) {
+        return lon > 0 && lat > 0
+                && lon >= QINGHAI_LON_MIN && lon <= QINGHAI_LON_MAX
+                && lat >= QINGHAI_LAT_MIN && lat <= QINGHAI_LAT_MAX;
+    }
+
+    // ============================== 字段解析辅助 ==============================
+
+    private static Long deviceId(ObjectNode row) {
+        JsonNode n = row.get("device_id");
+        return n == null || n.isNull() ? null : n.asLong();
+    }
+
+    private static int intVal(ObjectNode row, String field, int def) {
+        JsonNode n = row.get(field);
+        return n == null || n.isNull() ? def : n.asInt(def);
+    }
+
+    private static String species(ObjectNode row) {
+        JsonNode n = row.get("scientific_name");
+        if (n != null && !n.isNull() && !n.asText().trim().isEmpty()) {
+            return n.asText();
+        }
+        n = row.get("species_name");
+        return n == null || n.isNull() ? "" : n.asText();
+    }
+
+    /** 物种中文名（species_name），用于物种过滤时与学名共同匹配。 */
+    private static String speciesName(ObjectNode row) {
+        JsonNode n = row.get("species_name");
+        return n == null || n.isNull() ? "" : n.asText().trim();
+    }
+
+    /**
+     * 解析 record_time（ES date 类型，_source 中可能为
+     * "yyyy-MM-dd HH:mm:ss" / ISO8601 带时区 / epoch 毫秒），
+     * 统一转为 Asia/Shanghai 本地时间。
+     */
+    private static LocalDateTime recordTime(ObjectNode row) {
+        JsonNode n = row.get("record_time");
+        if (n == null || n.isNull()) {
+            return null;
+        }
+        if (n.isNumber()) {
+            return LocalDateTime.ofInstant(Instant.ofEpochMilli(n.longValue()), ZONE);
+        }
+        String s = n.asText().trim();
+        if (s.isEmpty()) {
+            return null;
+        }
+        // 带时区（Z / +08:00）→ 转本地时区
+        if (s.endsWith("Z") || s.matches(".*[+-]\\d{2}:?\\d{2}$")) {
+            try {
+                return OffsetDateTime.parse(s).atZoneSameInstant(ZONE).toLocalDateTime();
+            } catch (Exception ignore) {
+                // 落到通用解析
+            }
+        }
+        // 无时区，按本地时间解析
+        String t = s.replace('T', ' ');
+        try {
+            if (t.length() >= 19) {
+                return LocalDateTime.parse(t.substring(0, 19), FMT);
+            }
+            if (t.length() == 16) {
+                return LocalDateTime.parse(t + ":00", FMT);
+            }
+            if (t.length() == 10) {
+                return LocalDate.parse(t).atStartOfDay();
+            }
+        } catch (Exception ignore) {
+            // 未知格式
+        }
+        return null;
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/util/DensityUtils.java

@@ -0,0 +1,60 @@
+package net.hzvtc.stat.util;
+
+import net.hzvtc.stat.dto.DensitySeries;
+
+/**
+ * 核密度估计（Gaussian KDE）。
+ *
+ * <p>cameratrapR 中 {@code density(times, bw)} 调用的就是 R stats::density（默认高斯核）。
+ * 本类按相同语义实现：在等距网格上对样本做高斯核密度估计，返回 (x[], y[])。</p>
+ *
+ * <p>核密度公式：
+ * <pre>
+ *   f(x) = (1 / (N * bw * sqrt(2π))) * Σ exp(-0.5 * ((x - xi) / bw)^2)
+ * </pre>
+ * </p>
+ */
+public final class DensityUtils {
+
+    private DensityUtils() {
+    }
+
+    private static final double SQRT_2PI = Math.sqrt(2.0 * Math.PI);
+
+    /**
+     * 在 [xmin, xmax] 范围内等距取 n 个点，估计样本的高斯核密度。
+     *
+     * @param samples 原始样本（一维数组）
+     * @param bw      带宽（与 R 中 bw 含义一致；dailyRhythm 使用 bw=0.3 与 bw=2）
+     * @param n       输出采样点数（默认 512 与 R 一致）
+     * @param xmin    x 轴下限
+     * @param xmax    x 轴上限
+     * @param label   曲线标签（写入结果）
+     * @return {@link DensitySeries}
+     */
+    public static DensitySeries gaussianKde(double[] samples, double bw, int n, double xmin, double xmax, String label) {
+        if (samples.length == 0 || bw <= 0 || n < 2) {
+            return new DensitySeries(new double[0], new double[0], bw, label);
+        }
+
+        double[] x = new double[n];
+        double step = (xmax - xmin) / (n - 1);
+        for (int i = 0; i < n; i++) {
+            x[i] = xmin + step * i;
+        }
+
+        double[] y = new double[n];
+        double norm = 1.0 / (samples.length * bw * SQRT_2PI);
+        for (int i = 0; i < n; i++) {
+            double xi = x[i];
+            double acc = 0.0;
+            for (double s : samples) {
+                double z = (xi - s) / bw;
+                acc += Math.exp(-0.5 * z * z);
+            }
+            y[i] = acc * norm;
+        }
+
+        return new DensitySeries(x, y, bw, label);
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/util/GeoUtils.java

@@ -0,0 +1,130 @@
+package net.hzvtc.stat.util;
+
+import java.util.List;
+
+/**
+ * 地理坐标工具：WGS84 经纬度 → UTM 米。
+ *
+ * <p>cameratrapR 的 <code>geo2proj</code> 默认使用 WGS84 → UTM（按数据经度均值自动推算 zone）。
+ * 本类实现相同的转换，使用 WGS84 椭球参数与 Transverse Mercator（Kruger）公式。</p>
+ *
+ * <p>UTM zone 推算（与 R 代码一致）：<code>zone = floor((mean(lon)+180)/6) %% 60 + 1</code>。</p>
+ */
+public final class GeoUtils {
+
+    private GeoUtils() {
+    }
+
+    /** WGS84 长半轴（m）。 */
+    private static final double A = 6378137.0;
+
+    /** WGS84 第一偏心率平方。 */
+    private static final double E2 = 0.00669437999014;
+
+    /** WGS84 第二偏心率平方。 */
+    private static final double EP2 = E2 / (1.0 - E2);
+
+    /** UTM 比例因子。 */
+    private static final double K0 = 0.9996;
+
+    /**
+     * 将经纬度转换为 UTM 米。
+     *
+     * @param lonDeg 经度（度）
+     * @param latDeg 纬度（度）
+     * @param zone   UTM 区号（1..60）
+     * @return double[2] = {easting(m), northing(m)}，东向已加 500000 偏移。
+     */
+    public static double[] wgs84ToUtm(double lonDeg, double latDeg, int zone) {
+        double lonRad = Math.toRadians(lonDeg);
+        double latRad = Math.toRadians(latDeg);
+
+        // 中央经线
+        double lon0Rad = Math.toRadians((zone - 1) * 6.0 - 180.0 + 3.0);
+
+        double sinLat = Math.sin(latRad);
+        double cosLat = Math.cos(latRad);
+        double tanLat = Math.tan(latRad);
+
+        double n = A / Math.sqrt(1.0 - E2 * sinLat * sinLat);
+        double t = tanLat * tanLat;
+        double c = EP2 * cosLat * cosLat;
+        double a = cosLat * (lonRad - lon0Rad);
+
+        // 子午线弧长 M
+        double m = A * ((1.0 - E2 / 4.0 - 3.0 * E2 * E2 / 64.0 - 5.0 * E2 * E2 * E2 / 256.0) * latRad
+                - (3.0 * E2 / 8.0 + 3.0 * E2 * E2 / 32.0 + 45.0 * E2 * E2 * E2 / 1024.0) * Math.sin(2.0 * latRad)
+                + (15.0 * E2 * E2 / 256.0 + 45.0 * E2 * E2 * E2 / 1024.0) * Math.sin(4.0 * latRad)
+                - (35.0 * E2 * E2 * E2 / 3072.0) * Math.sin(6.0 * latRad));
+
+        double easting = K0 * n * (a + (1.0 - t + c) * a * a * a / 6.0
+                + (5.0 - 18.0 * t + t * t + 72.0 * c - 58.0 * EP2) * Math.pow(a, 5) / 120.0)
+                + 500000.0;
+
+        double northing = K0 * (m + n * tanLat * (a * a / 2.0
+                + (5.0 - t + 9.0 * c + 4.0 * c * c) * Math.pow(a, 4) / 24.0
+                + (61.0 - 58.0 * t + t * t + 600.0 * c - 330.0 * EP2) * Math.pow(a, 6) / 720.0));
+
+        // 南半球偏移 10 000 000
+        if (latDeg < 0) {
+            northing += 10000000.0;
+        }
+
+        return new double[]{easting, northing};
+    }
+
+    /**
+     * 自动按数据经度均值推算 UTM zone，转换所有点为米。
+     *
+     * @param lons 经度数组（度）
+     * @param lats 纬度数组（度）
+     * @return double[n][2] = {easting(m), northing(m)}
+     */
+    public static double[][] wgs84ToUtmAuto(double[] lons, double[] lats) {
+        if (lons.length != lats.length) {
+            throw new IllegalArgumentException("lons and lats length mismatch");
+        }
+        double meanLon = 0.0;
+        for (double lon : lons) {
+            meanLon += lon;
+        }
+        meanLon /= lons.length;
+
+        int zone = (int) Math.floor((meanLon + 180.0) / 6.0) % 60 + 1;
+        if (zone < 1) {
+            zone = 1;
+        }
+
+        double[][] out = new double[lons.length][2];
+        for (int i = 0; i < lons.length; i++) {
+            out[i] = wgs84ToUtm(lons[i], lats[i], zone);
+        }
+        return out;
+    }
+
+    /**
+     * 自动 zone 并转换带 (lon, lat) 字段的对象列表。
+     */
+    public static <T> double[][] wgs84ToUtmAuto(List<T> points, LonGetter<T> lonGetter, LatGetter<T> latGetter) {
+        double[] lons = new double[points.size()];
+        double[] lats = new double[points.size()];
+        for (int i = 0; i < points.size(); i++) {
+            T p = points.get(i);
+            lons[i] = lonGetter.getLon(p);
+            lats[i] = latGetter.getLat(p);
+        }
+        return wgs84ToUtmAuto(lons, lats);
+    }
+
+    /** 取对象的经度。 */
+    @FunctionalInterface
+    public interface LonGetter<T> {
+        double getLon(T obj);
+    }
+
+    /** 取对象的纬度。 */
+    @FunctionalInterface
+    public interface LatGetter<T> {
+        double getLat(T obj);
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/util/RandomUtils.java

@@ -0,0 +1,83 @@
+package net.hzvtc.stat.util;
+
+import java.util.Random;
+
+/**
+ * 随机数工具：均匀、高斯（与 R <code>runif / rnorm</code> 语义一致）。
+ *
+ * <p>默认使用固定种子（等价 R 的 <code>set.seed(1234)</code>），
+ * 保证同样输入下结果可复现；可在每次查询前调用 {@link #setSeed(long)} 重置。</p>
+ */
+public final class RandomUtils {
+
+    private RandomUtils() {
+    }
+
+    /** 默认种子（与接口层 seed 默认值一致）。 */
+    public static final long DEFAULT_SEED = 1234L;
+
+    /** 每线程独立的种子化随机源（ThreadLocalRandom 无法指定种子，故用 ThreadLocal&lt;Random&gt;）。 */
+    private static final ThreadLocal<Random> RNG = ThreadLocal.withInitial(() -> new Random(DEFAULT_SEED));
+
+    /**
+     * 重置随机种子（等价 R 的 <code>set.seed</code>）。
+     * 供每次查询/每个物种模拟前调用，保证同样条件下结果可复现。
+     */
+    public static void setSeed(long seed) {
+        RNG.set(new Random(seed));
+    }
+
+    /** R 的 <code>runif(1, min, max)</code> 等价物。 */
+    public static double uniform(double min, double max) {
+        return RNG.get().nextDouble() * (max - min) + min;
+    }
+
+    /**
+     * R 的 <code>rnorm(1, mean, sd)</code> 等价物（Box-Muller 变换，基于同一种子源）。
+     */
+    public static double gaussian(double mean, double sd) {
+        return gauss() * sd + mean;
+    }
+
+    /** 一次性生成 n 个高斯样本。 */
+    public static double[] gaussianSamples(double mean, double sd, int n) {
+        double[] out = new double[n];
+        for (int i = 0; i < n; i++) {
+            out[i] = gaussian(mean, sd);
+        }
+        return out;
+    }
+
+    /**
+     * 离散采样（按概率权重抽取一个 index）。等价 R 的 <code>sample(x, 1, prob=p)</code>。
+     *
+     * @param weights 非负权重数组
+     * @return 命中的下标
+     */
+    public static int weightedSample(double[] weights) {
+        double sum = 0.0;
+        for (double w : weights) {
+            sum += w;
+        }
+        double r = uniform(0.0, sum);
+        double acc = 0.0;
+        for (int i = 0; i < weights.length; i++) {
+            acc += weights[i];
+            if (r <= acc) {
+                return i;
+            }
+        }
+        return weights.length - 1;
+    }
+
+    /** Box-Muller 标准正态样本。 */
+    private static double gauss() {
+        Random r = RNG.get();
+        double u1;
+        do {
+            u1 = r.nextDouble();
+        } while (u1 <= 0.0);
+        double u2 = r.nextDouble();
+        return Math.sqrt(-2.0 * Math.log(u1)) * Math.cos(2.0 * Math.PI * u2);
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/stat/util/StatisticsUtils.java

@@ -0,0 +1,60 @@
+package net.hzvtc.stat.util;
+
+import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics;
+
+/**
+ * 描述统计工具：mean / sd / quantile（与 R <code>mean / sd / quantile</code> 语义一致）。
+ *
+ * <p>使用 commons-math3 的 {@link DescriptiveStatistics}，分位数采用 R type-7（即线性插值）。</p>
+ */
+public final class StatisticsUtils {
+
+    private StatisticsUtils() {
+    }
+
+    public static double mean(double[] values) {
+        DescriptiveStatistics s = new DescriptiveStatistics(values);
+        return s.getMean();
+    }
+
+    public static double sd(double[] values) {
+        if (values.length < 2) {
+            return 0.0;
+        }
+        return Math.sqrt(new DescriptiveStatistics(values).getVariance());
+    }
+
+    /**
+     * R type-7 分位数。
+     */
+    public static double quantile(double[] values, double p) {
+        DescriptiveStatistics s = new DescriptiveStatistics(values);
+        return s.getPercentile(p * 100.0);
+    }
+
+    public static double max(double[] values) {
+        double m = Double.NEGATIVE_INFINITY;
+        for (double v : values) {
+            if (v > m) {
+                m = v;
+            }
+        }
+        return m;
+    }
+
+    public static double min(double[] values) {
+        double m = Double.POSITIVE_INFINITY;
+        for (double v : values) {
+            if (v < m) {
+                m = v;
+            }
+        }
+        return m;
+    }
+
+    public static double[] sort(double[] values) {
+        double[] copy = values.clone();
+        java.util.Arrays.sort(copy);
+        return copy;
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/sys/config/CustomDateTimeDeserializer.java

@@ -0,0 +1,22 @@
+package net.hzvtc.sys.config;
+
+import com.fasterxml.jackson.core.JsonParser;
+import com.fasterxml.jackson.core.JsonProcessingException;
+import com.fasterxml.jackson.databind.DeserializationContext;
+import com.fasterxml.jackson.databind.JsonDeserializer;
+
+import java.io.IOException;
+import java.time.ZonedDateTime;
+import java.time.format.DateTimeFormatter;
+
+public class CustomDateTimeDeserializer extends JsonDeserializer<ZonedDateTime> {
+
+    private static final DateTimeFormatter INPUT_FORMATTER = DateTimeFormatter.ofPattern("yyyy-MM-dd'T'HH:mm:ss.SSSX");
+
+    @Override
+    public ZonedDateTime deserialize(JsonParser p, DeserializationContext ctxt)
+            throws IOException, JsonProcessingException {
+        String dateStr = p.getText();
+        return ZonedDateTime.parse(dateStr, INPUT_FORMATTER);
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/sys/config/CustomDateTimeSerializer.java

@@ -0,0 +1,21 @@
+package net.hzvtc.sys.config;
+
+import com.fasterxml.jackson.core.JsonGenerator;
+import com.fasterxml.jackson.databind.JsonSerializer;
+import com.fasterxml.jackson.databind.SerializerProvider;
+
+import java.io.IOException;
+import java.time.ZonedDateTime;
+import java.time.format.DateTimeFormatter;
+
+public class CustomDateTimeSerializer extends JsonSerializer<ZonedDateTime> {
+
+    private static final DateTimeFormatter OUTPUT_FORMATTER = DateTimeFormatter.ofPattern("yyyy-MM-dd HH:mm:ss");
+
+    @Override
+    public void serialize(ZonedDateTime value, JsonGenerator gen, SerializerProvider serializers)
+            throws IOException {
+        String formattedDate = value.format(OUTPUT_FORMATTER);
+        gen.writeString(formattedDate);
+    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/sys/config/ESClientConfig.java

@@ -0,0 +1,168 @@
+package net.hzvtc.sys.config;
+
+import co.elastic.clients.elasticsearch.ElasticsearchClient;
+import co.elastic.clients.json.jackson.JacksonJsonpMapper;
+import co.elastic.clients.transport.ElasticsearchTransport;
+import co.elastic.clients.transport.rest_client.RestClientTransport;
+import lombok.Setter;
+import lombok.extern.slf4j.Slf4j;
+import org.apache.http.Header;
+import org.apache.http.HttpHost;
+import org.apache.http.auth.AuthScope;
+import org.apache.http.auth.UsernamePasswordCredentials;
+import org.apache.http.client.CredentialsProvider;
+import org.apache.http.conn.ssl.NoopHostnameVerifier;
+import org.apache.http.impl.client.BasicCredentialsProvider;
+import org.apache.http.impl.client.DefaultConnectionKeepAliveStrategy;
+import org.apache.http.message.BasicHeader;
+import org.apache.http.ssl.SSLContextBuilder;
+import org.apache.http.ssl.SSLContexts;
+import org.elasticsearch.client.RestClient;
+import org.elasticsearch.client.RestClientBuilder;
+import org.springframework.beans.factory.annotation.Value;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+import org.springframework.core.io.ClassPathResource;
+import org.springframework.util.StringUtils;
+
+import javax.net.ssl.SSLContext;
+import java.io.IOException;
+import java.io.InputStream;
+import java.security.KeyManagementException;
+import java.security.KeyStore;
+import java.security.KeyStoreException;
+import java.security.NoSuchAlgorithmException;
+import java.security.cert.Certificate;
+import java.security.cert.CertificateException;
+import java.security.cert.CertificateFactory;
+
+@Setter
+@Configuration
+@Slf4j
+public class ESClientConfig {
+
+    @Value("${spring.elastic.hosts}")
+    private String hosts;
+
+//    @Setter
+//    @Value("${spring.elastic.port}")
+//    private int port;
+
+    @Value("${spring.elastic.http}")
+    private String http;
+
+    @Value("${spring.elastic.apiKey}")
+    private String apiKey;
+
+    @Value("${spring.elastic.username}")
+    private String username;
+
+    @Value("${spring.elastic.password}")
+    private String passwd;
+
+
+    private static String certName;
+
+
+    @Value("${spring.elastic.certName}")
+    public void setAppKey(String certName) {
+        ESClientConfig.certName = certName;
+    }
+
+
+    private HttpHost[] toHttpHost() {
+        if (!StringUtils.hasLength(hosts)) {
+            throw new RuntimeException("invalid elasticsearch configuration");
+        }
+
+        String[] hostArray = hosts.split(",");
+        HttpHost[] httpHosts = new HttpHost[hostArray.length];
+        HttpHost httpHost;
+        for (int i = 0; i < hostArray.length; i++) {
+            String[] strings = hostArray[i].split(":");
+            httpHost = new HttpHost(strings[0], Integer.parseInt(strings[1]), "https");
+            httpHosts[i] = httpHost;
+        }
+
+        return httpHosts;
+    }
+
+    @Bean("clientByPasswd")
+    public ElasticsearchClient clientByPasswd() {
+        ElasticsearchTransport transport = getElasticsearchTransport(username, passwd, toHttpHost());
+        return new ElasticsearchClient(transport);
+    }
+
+    private static SSLContext buildSSLContext() {
+//        ClassPathResource resource = new ClassPathResource("es_ca.crt");
+        ClassPathResource resource = new ClassPathResource(certName);
+        SSLContext sslContext = null;
+        try {
+            CertificateFactory factory = CertificateFactory.getInstance("X.509");
+            Certificate trustedCa;
+            try (InputStream is = resource.getInputStream()) {
+                trustedCa = factory.generateCertificate(is);
+            }
+            KeyStore trustStore = KeyStore.getInstance("JKS");
+            trustStore.load(null, null);
+            trustStore.setCertificateEntry("ca", trustedCa);
+            SSLContextBuilder sslContextBuilder = SSLContexts.custom()
+                    .loadTrustMaterial(trustStore, null);
+            sslContext = sslContextBuilder.build();
+        } catch (IOException | KeyStoreException | NoSuchAlgorithmException | KeyManagementException |
+                 CertificateException e) {
+            log.error("ES连接认证失败", e);
+        }
+
+        return sslContext;
+    }
+
+    private static ElasticsearchTransport getElasticsearchTransport(String username, String passwd, HttpHost... hosts) {
+        // 账号密码的配置
+        final CredentialsProvider credentialsProvider = new BasicCredentialsProvider();
+        credentialsProvider.setCredentials(AuthScope.ANY, new UsernamePasswordCredentials(username, passwd));
+
+        // 自签证书的设置，并且还包含了账号密码
+        RestClientBuilder.HttpClientConfigCallback callback = httpAsyncClientBuilder -> httpAsyncClientBuilder
+                .setSSLContext(buildSSLContext())
+                .setMaxConnTotal(100)
+                .setMaxConnPerRoute(100)
+                .setKeepAliveStrategy(new DefaultConnectionKeepAliveStrategy())
+                .setSSLHostnameVerifier(NoopHostnameVerifier.INSTANCE)
+                .setDefaultCredentialsProvider(credentialsProvider);
+
+        // 用builder创建RestClient对象
+        RestClient client = RestClient
+                .builder(hosts)
+                .setRequestConfigCallback(requestConfigBuilder -> requestConfigBuilder.setConnectTimeout(5000).setSocketTimeout(120000))
+                .setHttpClientConfigCallback(callback)
+                .build();
+
+        return new RestClientTransport(client, new JacksonJsonpMapper(JacksonConfiguration.createObjectMapper()));
+    }
+
+    private static ElasticsearchTransport getElasticsearchTransport(String apiKey, HttpHost... hosts) {
+        // 将ApiKey放入header中
+        Header[] headers = new Header[]{new BasicHeader("Authorization", "ApiKey " + apiKey)};
+
+        // es自签证书的设置
+        RestClientBuilder.HttpClientConfigCallback callback = httpAsyncClientBuilder -> httpAsyncClientBuilder
+                .setSSLContext(buildSSLContext())
+                .setSSLHostnameVerifier(NoopHostnameVerifier.INSTANCE);
+
+        // 用builder创建RestClient对象
+        RestClient client = RestClient
+                .builder(hosts)
+                .setHttpClientConfigCallback(callback)
+                .setDefaultHeaders(headers)
+                .build();
+
+        return new RestClientTransport(client, new JacksonJsonpMapper());
+    }
+
+//    @Bean("clientByApiKey")
+//    public ElasticsearchClient clientByApiKey() throws Exception {
+//        ElasticsearchTransport transport = getElasticsearchTransport(apiKey, toHttpHost());
+//        return new ElasticsearchClient(transport);
+//    }
+}

ai-xuebao-es/src/main/java/net/hzvtc/sys/config/JacksonConfiguration.java

@@ -0,0 +1,19 @@
+package net.hzvtc.sys.config;
+
+import com.fasterxml.jackson.databind.DeserializationFeature;
+import com.fasterxml.jackson.databind.ObjectMapper;
+import com.fasterxml.jackson.databind.PropertyNamingStrategies;
+import com.fasterxml.jackson.datatype.jsr310.JavaTimeModule;
+
+import java.time.ZonedDateTime;
+
+public class JacksonConfiguration {
+    public static ObjectMapper createObjectMapper() {
+        return new ObjectMapper()
+                .setPropertyNamingStrategy(PropertyNamingStrategies.SNAKE_CASE)
+                .configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false)
+                .registerModule(new JavaTimeModule()
+                        .addSerializer(ZonedDateTime.class, new CustomDateTimeSerializer())
+                        .addDeserializer(ZonedDateTime.class, new CustomDateTimeDeserializer()));
+    }
+}

ai-xuebao-es/src/main/resources/mapper/EsResultRecordDetailsMapper.xml

@@ -0,0 +1,78 @@
+<?xml version="1.0" encoding="UTF-8" ?>
+<!DOCTYPE mapper
+        PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
+        "http://mybatis.org/dtd/mybatis-3-mapper.dtd">
+<mapper namespace="net.hzvtc.es.mapper.EsResultRecordDetailsMapper">
+    <resultMap type="EsResultRecordDetailsVo" id="EsResultRecordDetailsResult">
+        <result property="id" column="id"/>
+        <result property="mediaId" column="media_id"/>
+        <result property="recordId" column="record_id"/>
+        <result property="count" column="count"/>
+        <result property="habitat" column="habitat"/>
+        <result property="recordTime1" column="record_time"/>
+        <result property="recordType" column="record_type"/>
+        <result property="deviceId" column="device_id"/>
+        <result property="deviceName" column="device_name"/>
+        <result property="speciesId" column="species_id"/>
+        <result property="confidence" column="confidence"/>
+        <result property="checked" column="checked"/>
+        <result property="duid" column="duid"/>
+        <result property="speciesName" column="species_name"/>
+        <result property="mediaType" column="media_type"/>
+        <result property="mediaUrl" column="media_url"/>
+        <result property="metaUrl" column="meta_url"/>
+        <result property="deptId" column="dept_id"/>
+        <result property="scientificName" column="scientific_name"/>
+    </resultMap>
+    <resultMap type="BirdStatDataVo" id="EchartDataBirdResult">
+        <result property="id" column="id"/>
+        <result property="name" column="name"/>
+    </resultMap>
+    <select id="getAreaBirdSpeciesByParam" resultMap="EchartDataBirdResult">
+        select b.name as name,b.id from protected_area_species c
+        left JOIN bird_species b on c.species_id = b.id
+        where
+        c.is_deleted = 0
+        and
+        c.area_id = #{areaId}
+        <if test="isCommon != null">
+            and c.is_common = #{isCommon}
+        </if>
+        order by c.position desc,c.species_id
+        <if test="limit!=null">
+            limit #{limit}
+        </if>
+    </select>
+    <select id="getDeviceListByParam" resultMap="EchartDataBirdResult">
+        select a.device_name as name, a.id
+        from device_info a
+        where a.is_deleted = 0
+          <if test="userId != null">
+              and id in (select post_id from sys_user_post where user_id=#{params.userId})
+          </if>
+        order by a.id
+    </select>
+    <select id="getResultRecordListForElastic" resultMap="EsResultRecordDetailsResult">
+        select a.*, c.device_name,c.duid,c.dept_id, d.name as species_name, e.media_type, e.media_url, e.meta_url,d.scientific_name
+        from (select a.details_id                                       as id,
+                     a.media_id,
+                     a.record_id,
+                     IF(a.count = NULL, 1, if(a.count = 0, 1, a.count)) as count,
+                     a.habitat,
+                     b.record_time,
+                     b.record_type,
+                     b.device_id,
+                     a.species_id,
+                     IFNULL(a.confidence = NULL, 0.0)                   as confidence,
+                     IFNULL(a.checked, 0)                               as checked
+              from result_record b
+                     INNER JOIN result_record_details a on b.record_id = a.record_id
+              where b.record_id &gt; #{recordId}
+                and a.media_id in (select media_id from result_media where is_deleted != 1)
+                and a.is_deleted = 0) as a
+                 left JOIN bird_species d on a.species_id = d.id
+                 left join device_info c on a.device_id = c.id
+                 inner JOIN result_media e on a.media_id = e.media_id
+        order by a.id
+    </select>
+</mapper>

ai-xuebao-framework/src/main/java/net/hzvtc/framework/aspectj/DataScopeAspect.java

@@ -0,0 +1,149 @@
+package net.hzvtc.framework.aspectj;
+
+import net.hzvtc.common.core.domain.BaseEntity;
+import net.hzvtc.common.core.domain.entity.SysRole;
+import net.hzvtc.common.core.domain.entity.SysUser;
+import net.hzvtc.common.core.domain.model.LoginUser;
+import net.hzvtc.common.utils.SecurityUtils;
+import net.hzvtc.common.utils.StringUtils;
+import org.aspectj.lang.JoinPoint;
+import org.aspectj.lang.annotation.Aspect;
+import org.aspectj.lang.annotation.Before;
+import org.springframework.stereotype.Component;
+import net.hzvtc.common.annotation.DataScope;
+
+/**
+ * 数据过滤处理
+ *
+ * @author admin
+ */
+@Aspect
+@Component
+public class DataScopeAspect
+{
+    /**
+     * 全部数据权限
+     */
+    public static final String DATA_SCOPE_ALL = "1";
+
+    /**
+     * 自定数据权限
+     */
+    public static final String DATA_SCOPE_CUSTOM = "2";
+
+    /**
+     * 部门数据权限
+     */
+    public static final String DATA_SCOPE_DEPT = "3";
+
+    /**
+     * 部门及以下数据权限
+     */
+    public static final String DATA_SCOPE_DEPT_AND_CHILD = "4";
+
+    /**
+     * 仅本人数据权限
+     */
+    public static final String DATA_SCOPE_SELF = "5";
+
+    /**
+     * 数据权限过滤关键字
+     */
+    public static final String DATA_SCOPE = "dataScope";
+
+    @Before("@annotation(controllerDataScope)")
+    public void doBefore(JoinPoint point, DataScope controllerDataScope) throws Throwable
+    {
+        clearDataScope(point);
+        handleDataScope(point, controllerDataScope);
+    }
+
+    protected void handleDataScope(final JoinPoint joinPoint, DataScope controllerDataScope)
+    {
+        // 获取当前的用户
+        LoginUser loginUser = SecurityUtils.getLoginUser();
+        if (StringUtils.isNotNull(loginUser))
+        {
+            SysUser currentUser = loginUser.getUser();
+            // 如果是超级管理员，则不过滤数据
+            if (StringUtils.isNotNull(currentUser) && !currentUser.isAdmin())
+            {
+                dataScopeFilter(joinPoint, currentUser, controllerDataScope.deptAlias(),
+                        controllerDataScope.userAlias());
+            }
+        }
+    }
+
+    /**
+     * 数据范围过滤
+     *
+     * @param joinPoint 切点
+     * @param user 用户
+     * @param userAlias 别名
+     */
+    public static void dataScopeFilter(JoinPoint joinPoint, SysUser user, String deptAlias, String userAlias)
+    {
+        StringBuilder sqlString = new StringBuilder();
+
+        for (SysRole role : user.getRoles())
+        {
+            String dataScope = role.getDataScope();
+            if (DATA_SCOPE_ALL.equals(dataScope))
+            {
+                sqlString = new StringBuilder();
+                break;
+            }
+            else if (DATA_SCOPE_CUSTOM.equals(dataScope))
+            {
+                sqlString.append(StringUtils.format(
+                        " OR {}.dept_id IN ( SELECT dept_id FROM sys_role_dept WHERE role_id = {} ) ", deptAlias,
+                        role.getRoleId()));
+            }
+            else if (DATA_SCOPE_DEPT.equals(dataScope))
+            {
+                sqlString.append(StringUtils.format(" OR {}.dept_id = {} ", deptAlias, user.getDeptId()));
+            }
+            else if (DATA_SCOPE_DEPT_AND_CHILD.equals(dataScope))
+            {
+                sqlString.append(StringUtils.format(
+                        " OR {}.dept_id IN ( SELECT dept_id FROM sys_dept WHERE dept_id = {} or find_in_set( {} , ancestors ) )",
+                        deptAlias, user.getDeptId(), user.getDeptId()));
+            }
+            else if (DATA_SCOPE_SELF.equals(dataScope))
+            {
+                if (StringUtils.isNotBlank(userAlias))
+                {
+                    sqlString.append(StringUtils.format(" OR {}.user_id = {} ", userAlias, user.getUserId()));
+                }
+                else
+                {
+                    // 数据权限为仅本人且没有userAlias别名不查询任何数据
+                    sqlString.append(" OR 1=0 ");
+                }
+            }
+        }
+
+        if (StringUtils.isNotBlank(sqlString.toString()))
+        {
+            Object params = joinPoint.getArgs()[0];
+            if (StringUtils.isNotNull(params) && params instanceof BaseEntity)
+            {
+                BaseEntity baseEntity = (BaseEntity) params;
+                baseEntity.getParams().put(DATA_SCOPE, " AND (" + sqlString.substring(4) + ")");
+            }
+        }
+    }
+
+    /**
+     * 拼接权限sql前先清空params.dataScope参数防止注入
+     */
+    private void clearDataScope(final JoinPoint joinPoint)
+    {
+        Object params = joinPoint.getArgs()[0];
+        if (StringUtils.isNotNull(params) && params instanceof BaseEntity)
+        {
+            BaseEntity baseEntity = (BaseEntity) params;
+            baseEntity.getParams().put(DATA_SCOPE, "");
+        }
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/aspectj/DataSourceAspect.java

@@ -0,0 +1,73 @@
+package net.hzvtc.framework.aspectj;
+
+import java.util.Objects;
+
+import net.hzvtc.common.utils.StringUtils;
+import net.hzvtc.framework.datasource.DynamicDataSourceContextHolder;
+import org.aspectj.lang.ProceedingJoinPoint;
+import org.aspectj.lang.annotation.Around;
+import org.aspectj.lang.annotation.Aspect;
+import org.aspectj.lang.annotation.Pointcut;
+import org.aspectj.lang.reflect.MethodSignature;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.core.annotation.AnnotationUtils;
+import org.springframework.core.annotation.Order;
+import org.springframework.stereotype.Component;
+import net.hzvtc.common.annotation.DataSource;
+
+/**
+ * 多数据源处理
+ * 
+ * @author admin
+ */
+@Aspect
+@Order(1)
+@Component
+public class DataSourceAspect
+{
+    protected Logger logger = LoggerFactory.getLogger(getClass());
+
+    @Pointcut("@annotation(net.hzvtc.common.annotation.DataSource)"
+            + "|| @within(net.hzvtc.common.annotation.DataSource)")
+    public void dsPointCut()
+    {
+
+    }
+
+    @Around("dsPointCut()")
+    public Object around(ProceedingJoinPoint point) throws Throwable
+    {
+        DataSource dataSource = getDataSource(point);
+
+        if (StringUtils.isNotNull(dataSource))
+        {
+            DynamicDataSourceContextHolder.setDataSourceType(dataSource.value().name());
+        }
+
+        try
+        {
+            return point.proceed();
+        }
+        finally
+        {
+            // 销毁数据源 在执行方法之后
+            DynamicDataSourceContextHolder.clearDataSourceType();
+        }
+    }
+
+    /**
+     * 获取需要切换的数据源
+     */
+    public DataSource getDataSource(ProceedingJoinPoint point)
+    {
+        MethodSignature signature = (MethodSignature) point.getSignature();
+        DataSource dataSource = AnnotationUtils.findAnnotation(signature.getMethod(), DataSource.class);
+        if (Objects.nonNull(dataSource))
+        {
+            return dataSource;
+        }
+
+        return AnnotationUtils.findAnnotation(signature.getDeclaringType(), DataSource.class);
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/aspectj/LogAspect.java

@@ -0,0 +1,219 @@
+package net.hzvtc.framework.aspectj;
+
+import java.util.Collection;
+import java.util.Map;
+import javax.servlet.http.HttpServletRequest;
+import javax.servlet.http.HttpServletResponse;
+
+import net.hzvtc.common.core.domain.model.LoginUser;
+import net.hzvtc.common.enums.BusinessStatus;
+import net.hzvtc.common.enums.HttpMethod;
+import net.hzvtc.common.utils.SecurityUtils;
+import net.hzvtc.common.utils.ServletUtils;
+import net.hzvtc.common.utils.StringUtils;
+import net.hzvtc.common.utils.ip.IpUtils;
+import org.aspectj.lang.JoinPoint;
+import org.aspectj.lang.annotation.AfterReturning;
+import org.aspectj.lang.annotation.AfterThrowing;
+import org.aspectj.lang.annotation.Aspect;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.stereotype.Component;
+import org.springframework.validation.BindingResult;
+import org.springframework.web.multipart.MultipartFile;
+import org.springframework.web.servlet.HandlerMapping;
+import com.alibaba.fastjson.JSON;
+import net.hzvtc.common.annotation.Log;
+import net.hzvtc.framework.manager.AsyncManager;
+import net.hzvtc.framework.manager.factory.AsyncFactory;
+import net.hzvtc.system.domain.SysOperLog;
+
+/**
+ * 操作日志记录处理
+ * 
+ * @author admin
+ */
+@Aspect
+@Component
+public class LogAspect
+{
+    private static final Logger log = LoggerFactory.getLogger(LogAspect.class);
+
+    /**
+     * 处理完请求后执行
+     *
+     * @param joinPoint 切点
+     */
+    @AfterReturning(pointcut = "@annotation(controllerLog)", returning = "jsonResult")
+    public void doAfterReturning(JoinPoint joinPoint, Log controllerLog, Object jsonResult)
+    {
+        handleLog(joinPoint, controllerLog, null, jsonResult);
+    }
+
+    /**
+     * 拦截异常操作
+     * 
+     * @param joinPoint 切点
+     * @param e 异常
+     */
+    @AfterThrowing(value = "@annotation(controllerLog)", throwing = "e")
+    public void doAfterThrowing(JoinPoint joinPoint, Log controllerLog, Exception e)
+    {
+        handleLog(joinPoint, controllerLog, e, null);
+    }
+
+    protected void handleLog(final JoinPoint joinPoint, Log controllerLog, final Exception e, Object jsonResult)
+    {
+        try
+        {
+
+            // 获取当前的用户
+            LoginUser loginUser = SecurityUtils.getLoginUser();
+
+            // *========数据库日志=========*//
+            SysOperLog operLog = new SysOperLog();
+            operLog.setStatus(BusinessStatus.SUCCESS.ordinal());
+            // 请求的地址
+            String ip = IpUtils.getIpAddr(ServletUtils.getRequest());
+            operLog.setOperIp(ip);
+            operLog.setOperUrl(ServletUtils.getRequest().getRequestURI());
+            if (loginUser != null)
+            {
+                operLog.setOperName(loginUser.getUsername());
+            }
+
+            if (e != null)
+            {
+                operLog.setStatus(BusinessStatus.FAIL.ordinal());
+                operLog.setErrorMsg(StringUtils.substring(e.getMessage(), 0, 2000));
+            }
+            // 设置方法名称
+            String className = joinPoint.getTarget().getClass().getName();
+            String methodName = joinPoint.getSignature().getName();
+            operLog.setMethod(className + "." + methodName + "()");
+            // 设置请求方式
+            operLog.setRequestMethod(ServletUtils.getRequest().getMethod());
+            // 处理设置注解上的参数
+            getControllerMethodDescription(joinPoint, controllerLog, operLog, jsonResult);
+            // 保存数据库
+            AsyncManager.me().execute(AsyncFactory.recordOper(operLog));
+        }
+        catch (Exception exp)
+        {
+            // 记录本地异常日志
+            log.error("==前置通知异常==");
+            log.error("异常信息:{}", exp.getMessage());
+            exp.printStackTrace();
+        }
+    }
+
+    /**
+     * 获取注解中对方法的描述信息 用于Controller层注解
+     * 
+     * @param log 日志
+     * @param operLog 操作日志
+     * @throws Exception
+     */
+    public void getControllerMethodDescription(JoinPoint joinPoint, Log log, SysOperLog operLog, Object jsonResult) throws Exception
+    {
+        // 设置action动作
+        operLog.setBusinessType(log.businessType().ordinal());
+        // 设置标题
+        operLog.setTitle(log.title());
+        // 设置操作人类别
+        operLog.setOperatorType(log.operatorType().ordinal());
+        // 是否需要保存request，参数和值
+        if (log.isSaveRequestData())
+        {
+            // 获取参数的信息，传入到数据库中。
+            setRequestValue(joinPoint, operLog);
+        }
+        // 是否需要保存response，参数和值
+        if (log.isSaveResponseData() && StringUtils.isNotNull(jsonResult))
+        {
+            operLog.setJsonResult(StringUtils.substring(JSON.toJSONString(jsonResult), 0, 2000));
+        }
+    }
+
+    /**
+     * 获取请求的参数，放到log中
+     * 
+     * @param operLog 操作日志
+     * @throws Exception 异常
+     */
+    private void setRequestValue(JoinPoint joinPoint, SysOperLog operLog) throws Exception
+    {
+        String requestMethod = operLog.getRequestMethod();
+        if (HttpMethod.PUT.name().equals(requestMethod) || HttpMethod.POST.name().equals(requestMethod))
+        {
+            String params = argsArrayToString(joinPoint.getArgs());
+            operLog.setOperParam(StringUtils.substring(params, 0, 2000));
+        }
+        else
+        {
+            Map<?, ?> paramsMap = (Map<?, ?>) ServletUtils.getRequest().getAttribute(HandlerMapping.URI_TEMPLATE_VARIABLES_ATTRIBUTE);
+            operLog.setOperParam(StringUtils.substring(paramsMap.toString(), 0, 2000));
+        }
+    }
+
+    /**
+     * 参数拼装
+     */
+    private String argsArrayToString(Object[] paramsArray)
+    {
+        String params = "";
+        if (paramsArray != null && paramsArray.length > 0)
+        {
+            for (Object o : paramsArray)
+            {
+                if (StringUtils.isNotNull(o) && !isFilterObject(o))
+                {
+                    try
+                    {
+                        Object jsonObj = JSON.toJSON(o);
+                        params += jsonObj.toString() + " ";
+                    }
+                    catch (Exception e)
+                    {
+                    }
+                }
+            }
+        }
+        return params.trim();
+    }
+
+    /**
+     * 判断是否需要过滤的对象。
+     * 
+     * @param o 对象信息。
+     * @return 如果是需要过滤的对象，则返回true；否则返回false。
+     */
+    @SuppressWarnings("rawtypes")
+    public boolean isFilterObject(final Object o)
+    {
+        Class<?> clazz = o.getClass();
+        if (clazz.isArray())
+        {
+            return clazz.getComponentType().isAssignableFrom(MultipartFile.class);
+        }
+        else if (Collection.class.isAssignableFrom(clazz))
+        {
+            Collection collection = (Collection) o;
+            for (Object value : collection)
+            {
+                return value instanceof MultipartFile;
+            }
+        }
+        else if (Map.class.isAssignableFrom(clazz))
+        {
+            Map map = (Map) o;
+            for (Object value : map.entrySet())
+            {
+                Map.Entry entry = (Map.Entry) value;
+                return entry.getValue() instanceof MultipartFile;
+            }
+        }
+        return o instanceof MultipartFile || o instanceof HttpServletRequest || o instanceof HttpServletResponse
+                || o instanceof BindingResult;
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/aspectj/RateLimiterAspect.java

@@ -0,0 +1,92 @@
+package net.hzvtc.framework.aspectj;
+
+import java.lang.reflect.Method;
+import java.util.Collections;
+import java.util.List;
+
+import net.hzvtc.common.enums.LimitType;
+import net.hzvtc.common.exception.ServiceException;
+import net.hzvtc.common.utils.ServletUtils;
+import net.hzvtc.common.utils.StringUtils;
+import net.hzvtc.common.utils.ip.IpUtils;
+import org.aspectj.lang.JoinPoint;
+import org.aspectj.lang.annotation.Aspect;
+import org.aspectj.lang.annotation.Before;
+import org.aspectj.lang.reflect.MethodSignature;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.data.redis.core.RedisTemplate;
+import org.springframework.data.redis.core.script.RedisScript;
+import org.springframework.stereotype.Component;
+import net.hzvtc.common.annotation.RateLimiter;
+
+/**
+ * 限流处理
+ *
+ * @author admin
+ */
+@Aspect
+@Component
+public class RateLimiterAspect
+{
+    private static final Logger log = LoggerFactory.getLogger(RateLimiterAspect.class);
+
+    private RedisTemplate<Object, Object> redisTemplate;
+
+    private RedisScript<Long> limitScript;
+
+    @Autowired
+    public void setRedisTemplate1(RedisTemplate<Object, Object> redisTemplate)
+    {
+        this.redisTemplate = redisTemplate;
+    }
+
+    @Autowired
+    public void setLimitScript(RedisScript<Long> limitScript)
+    {
+        this.limitScript = limitScript;
+    }
+
+    @Before("@annotation(rateLimiter)")
+    public void doBefore(JoinPoint point, RateLimiter rateLimiter) throws Throwable
+    {
+        String key = rateLimiter.key();
+        int time = rateLimiter.time();
+        int count = rateLimiter.count();
+
+        String combineKey = getCombineKey(rateLimiter, point);
+        List<Object> keys = Collections.singletonList(combineKey);
+        try
+        {
+            Long number = redisTemplate.execute(limitScript, keys, count, time);
+            if (StringUtils.isNull(number) || number.intValue() > count)
+            {
+                throw new ServiceException("访问过于频繁，请稍候再试");
+            }
+            log.info("限制请求'{}',当前请求'{}',缓存key'{}'", count, number.intValue(), key);
+        }
+        catch (ServiceException e)
+        {
+            throw e;
+        }
+        catch (Exception e)
+        {
+            throw new RuntimeException("服务器限流异常，请稍候再试");
+        }
+    }
+
+    public String getCombineKey(RateLimiter rateLimiter, JoinPoint point)
+    {
+        StringBuffer stringBuffer = new StringBuffer(rateLimiter.key());
+        if (rateLimiter.limitType() == LimitType.IP)
+        {
+            stringBuffer.append(IpUtils.getIpAddr(ServletUtils.getRequest())).append("-");
+        }
+        MethodSignature signature = (MethodSignature) point.getSignature();
+        Method method = signature.getMethod();
+        Class<?> targetClass = method.getDeclaringClass();
+        stringBuffer.append(targetClass.getName()).append("-").append(method.getName());
+        return stringBuffer.toString();
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/config/ApplicationConfig.java

@@ -0,0 +1,30 @@
+package net.hzvtc.framework.config;
+
+import java.util.TimeZone;
+import org.mybatis.spring.annotation.MapperScan;
+import org.springframework.boot.autoconfigure.jackson.Jackson2ObjectMapperBuilderCustomizer;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+import org.springframework.context.annotation.EnableAspectJAutoProxy;
+
+/**
+ * 程序注解配置
+ *
+ * @author admin
+ */
+@Configuration
+// 表示通过aop框架暴露该代理对象,AopContext能够访问
+@EnableAspectJAutoProxy(exposeProxy = true)
+// 指定要扫描的Mapper类的包的路径
+@MapperScan("net.hzvtc.**.mapper")
+public class ApplicationConfig
+{
+    /**
+     * 时区配置
+     */
+    @Bean
+    public Jackson2ObjectMapperBuilderCustomizer jacksonObjectMapperCustomization()
+    {
+        return jacksonObjectMapperBuilder -> jacksonObjectMapperBuilder.timeZone(TimeZone.getDefault());
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/config/CaptchaConfig.java

@@ -0,0 +1,83 @@
+package net.hzvtc.framework.config;
+
+import java.util.Properties;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+import com.google.code.kaptcha.impl.DefaultKaptcha;
+import com.google.code.kaptcha.util.Config;
+import static com.google.code.kaptcha.Constants.*;
+
+/**
+ * 验证码配置
+ * 
+ * @author admin
+ */
+@Configuration
+public class CaptchaConfig
+{
+    @Bean(name = "captchaProducer")
+    public DefaultKaptcha getKaptchaBean()
+    {
+        DefaultKaptcha defaultKaptcha = new DefaultKaptcha();
+        Properties properties = new Properties();
+        // 是否有边框 默认为true 我们可以自己设置yes，no
+        properties.setProperty(KAPTCHA_BORDER, "yes");
+        // 验证码文本字符颜色 默认为Color.BLACK
+        properties.setProperty(KAPTCHA_TEXTPRODUCER_FONT_COLOR, "black");
+        // 验证码图片宽度 默认为200
+        properties.setProperty(KAPTCHA_IMAGE_WIDTH, "160");
+        // 验证码图片高度 默认为50
+        properties.setProperty(KAPTCHA_IMAGE_HEIGHT, "60");
+        // 验证码文本字符大小 默认为40
+        properties.setProperty(KAPTCHA_TEXTPRODUCER_FONT_SIZE, "38");
+        // KAPTCHA_SESSION_KEY
+        properties.setProperty(KAPTCHA_SESSION_CONFIG_KEY, "kaptchaCode");
+        // 验证码文本字符长度 默认为5
+        properties.setProperty(KAPTCHA_TEXTPRODUCER_CHAR_LENGTH, "4");
+        // 验证码文本字体样式 默认为new Font("Arial", 1, fontSize), new Font("Courier", 1, fontSize)
+        properties.setProperty(KAPTCHA_TEXTPRODUCER_FONT_NAMES, "Arial,Courier");
+        // 图片样式 水纹com.google.code.kaptcha.impl.WaterRipple 鱼眼com.google.code.kaptcha.impl.FishEyeGimpy 阴影com.google.code.kaptcha.impl.ShadowGimpy
+        properties.setProperty(KAPTCHA_OBSCURIFICATOR_IMPL, "com.google.code.kaptcha.impl.ShadowGimpy");
+        Config config = new Config(properties);
+        defaultKaptcha.setConfig(config);
+        return defaultKaptcha;
+    }
+
+    @Bean(name = "captchaProducerMath")
+    public DefaultKaptcha getKaptchaBeanMath()
+    {
+        DefaultKaptcha defaultKaptcha = new DefaultKaptcha();
+        Properties properties = new Properties();
+        // 是否有边框 默认为true 我们可以自己设置yes，no
+        properties.setProperty(KAPTCHA_BORDER, "yes");
+        // 边框颜色 默认为Color.BLACK
+        properties.setProperty(KAPTCHA_BORDER_COLOR, "105,179,90");
+        // 验证码文本字符颜色 默认为Color.BLACK
+        properties.setProperty(KAPTCHA_TEXTPRODUCER_FONT_COLOR, "blue");
+        // 验证码图片宽度 默认为200
+        properties.setProperty(KAPTCHA_IMAGE_WIDTH, "160");
+        // 验证码图片高度 默认为50
+        properties.setProperty(KAPTCHA_IMAGE_HEIGHT, "60");
+        // 验证码文本字符大小 默认为40
+        properties.setProperty(KAPTCHA_TEXTPRODUCER_FONT_SIZE, "35");
+        // KAPTCHA_SESSION_KEY
+        properties.setProperty(KAPTCHA_SESSION_CONFIG_KEY, "kaptchaCodeMath");
+        // 验证码文本生成器
+        properties.setProperty(KAPTCHA_TEXTPRODUCER_IMPL, "net.hzvtc.framework.config.KaptchaTextCreator");
+        // 验证码文本字符间距 默认为2
+        properties.setProperty(KAPTCHA_TEXTPRODUCER_CHAR_SPACE, "3");
+        // 验证码文本字符长度 默认为5
+        properties.setProperty(KAPTCHA_TEXTPRODUCER_CHAR_LENGTH, "6");
+        // 验证码文本字体样式 默认为new Font("Arial", 1, fontSize), new Font("Courier", 1, fontSize)
+        properties.setProperty(KAPTCHA_TEXTPRODUCER_FONT_NAMES, "Arial,Courier");
+        // 验证码噪点颜色 默认为Color.BLACK
+        properties.setProperty(KAPTCHA_NOISE_COLOR, "white");
+        // 干扰实现类
+        properties.setProperty(KAPTCHA_NOISE_IMPL, "com.google.code.kaptcha.impl.NoNoise");
+        // 图片样式 水纹com.google.code.kaptcha.impl.WaterRipple 鱼眼com.google.code.kaptcha.impl.FishEyeGimpy 阴影com.google.code.kaptcha.impl.ShadowGimpy
+        properties.setProperty(KAPTCHA_OBSCURIFICATOR_IMPL, "com.google.code.kaptcha.impl.ShadowGimpy");
+        Config config = new Config(properties);
+        defaultKaptcha.setConfig(config);
+        return defaultKaptcha;
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/config/DruidConfig.java

@@ -0,0 +1,127 @@
+package net.hzvtc.framework.config;
+
+import java.io.IOException;
+import java.util.HashMap;
+import java.util.Map;
+import javax.servlet.Filter;
+import javax.servlet.FilterChain;
+import javax.servlet.ServletException;
+import javax.servlet.ServletRequest;
+import javax.servlet.ServletResponse;
+import javax.sql.DataSource;
+
+import net.hzvtc.common.enums.DataSourceType;
+import net.hzvtc.common.utils.spring.SpringUtils;
+import net.hzvtc.framework.config.properties.DruidProperties;
+import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty;
+import org.springframework.boot.context.properties.ConfigurationProperties;
+import org.springframework.boot.web.servlet.FilterRegistrationBean;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+import org.springframework.context.annotation.Primary;
+import com.alibaba.druid.pool.DruidDataSource;
+import com.alibaba.druid.spring.boot.autoconfigure.DruidDataSourceBuilder;
+import com.alibaba.druid.spring.boot.autoconfigure.properties.DruidStatProperties;
+import com.alibaba.druid.util.Utils;
+import net.hzvtc.framework.datasource.DynamicDataSource;
+
+/**
+ * druid 配置多数据源
+ * 
+ * @author admin
+ */
+@Configuration
+public class DruidConfig
+{
+    @Bean
+    @ConfigurationProperties("spring.datasource.druid.master")
+    public DataSource masterDataSource(DruidProperties druidProperties)
+    {
+        DruidDataSource dataSource = DruidDataSourceBuilder.create().build();
+        return druidProperties.dataSource(dataSource);
+    }
+
+    @Bean
+    @ConfigurationProperties("spring.datasource.druid.slave")
+    @ConditionalOnProperty(prefix = "spring.datasource.druid.slave", name = "enabled", havingValue = "true")
+    public DataSource slaveDataSource(DruidProperties druidProperties)
+    {
+        DruidDataSource dataSource = DruidDataSourceBuilder.create().build();
+        return druidProperties.dataSource(dataSource);
+    }
+
+    @Bean(name = "dynamicDataSource")
+    @Primary
+    public DynamicDataSource dataSource(DataSource masterDataSource)
+    {
+        Map<Object, Object> targetDataSources = new HashMap<>();
+        targetDataSources.put(DataSourceType.MASTER.name(), masterDataSource);
+        setDataSource(targetDataSources, DataSourceType.SLAVE.name(), "slaveDataSource");
+        return new DynamicDataSource(masterDataSource, targetDataSources);
+    }
+    
+    /**
+     * 设置数据源
+     * 
+     * @param targetDataSources 备选数据源集合
+     * @param sourceName 数据源名称
+     * @param beanName bean名称
+     */
+    public void setDataSource(Map<Object, Object> targetDataSources, String sourceName, String beanName)
+    {
+        try
+        {
+            DataSource dataSource = SpringUtils.getBean(beanName);
+            targetDataSources.put(sourceName, dataSource);
+        }
+        catch (Exception e)
+        {
+        }
+    }
+
+    /**
+     * 去除监控页面底部的广告
+     */
+    @SuppressWarnings({ "rawtypes", "unchecked" })
+    @Bean
+    @ConditionalOnProperty(name = "spring.datasource.druid.statViewServlet.enabled", havingValue = "true")
+    public FilterRegistrationBean removeDruidFilterRegistrationBean(DruidStatProperties properties)
+    {
+        // 获取web监控页面的参数
+        DruidStatProperties.StatViewServlet config = properties.getStatViewServlet();
+        // 提取common.js的配置路径
+        String pattern = config.getUrlPattern() != null ? config.getUrlPattern() : "/druid/*";
+        String commonJsPattern = pattern.replaceAll("\\*", "js/common.js");
+        final String filePath = "support/http/resources/js/common.js";
+        // 创建filter进行过滤
+        Filter filter = new Filter()
+        {
+            @Override
+            public void init(javax.servlet.FilterConfig filterConfig) throws ServletException
+            {
+            }
+            @Override
+            public void doFilter(ServletRequest request, ServletResponse response, FilterChain chain)
+                    throws IOException, ServletException
+            {
+                chain.doFilter(request, response);
+                // 重置缓冲区，响应头不会被重置
+                response.resetBuffer();
+                // 获取common.js
+                String text = Utils.readFromResource(filePath);
+                // 正则替换banner, 除去底部的广告信息
+                text = text.replaceAll("<a.*?banner\"></a><br/>", "");
+                text = text.replaceAll("powered.*?shrek.wang</a>", "");
+                response.getWriter().write(text);
+            }
+            @Override
+            public void destroy()
+            {
+            }
+        };
+        FilterRegistrationBean registrationBean = new FilterRegistrationBean();
+        registrationBean.setFilter(filter);
+        registrationBean.addUrlPatterns(commonJsPattern);
+        return registrationBean;
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/config/FastJson2JsonRedisSerializer.java

@@ -0,0 +1,62 @@
+package net.hzvtc.framework.config;
+
+import com.alibaba.fastjson.JSON;
+import com.alibaba.fastjson.parser.ParserConfig;
+import com.alibaba.fastjson.serializer.SerializerFeature;
+import com.fasterxml.jackson.databind.JavaType;
+import com.fasterxml.jackson.databind.ObjectMapper;
+import com.fasterxml.jackson.databind.type.TypeFactory;
+import org.springframework.data.redis.serializer.RedisSerializer;
+import org.springframework.data.redis.serializer.SerializationException;
+import org.springframework.util.Assert;
+
+import java.nio.charset.Charset;
+
+/**
+ * Redis使用FastJson序列化
+ *
+ * @author admin
+ */
+public class FastJson2JsonRedisSerializer<T> implements RedisSerializer<T> {
+    public static final Charset DEFAULT_CHARSET = Charset.forName("UTF-8");
+
+    static {
+        ParserConfig.getGlobalInstance().setAutoTypeSupport(true);
+    }
+
+    @SuppressWarnings("unused")
+    private ObjectMapper objectMapper = new ObjectMapper();
+    private Class<T> clazz;
+
+    public FastJson2JsonRedisSerializer(Class<T> clazz) {
+        super();
+        this.clazz = clazz;
+    }
+
+    @Override
+    public byte[] serialize(T t) throws SerializationException {
+        if (t == null) {
+            return new byte[0];
+        }
+        return JSON.toJSONString(t, SerializerFeature.WriteClassName).getBytes(DEFAULT_CHARSET);
+    }
+
+    @Override
+    public T deserialize(byte[] bytes) throws SerializationException {
+        if (bytes == null || bytes.length <= 0) {
+            return null;
+        }
+        String str = new String(bytes, DEFAULT_CHARSET);
+
+        return JSON.parseObject(str, clazz);
+    }
+
+    public void setObjectMapper(ObjectMapper objectMapper) {
+        Assert.notNull(objectMapper, "'objectMapper' must not be null");
+        this.objectMapper = objectMapper;
+    }
+
+    protected JavaType getJavaType(Class<?> clazz) {
+        return TypeFactory.defaultInstance().constructType(clazz);
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/config/FilterConfig.java

@@ -0,0 +1,59 @@
+package net.hzvtc.framework.config;
+
+import java.util.HashMap;
+import java.util.Map;
+import javax.servlet.DispatcherType;
+
+import net.hzvtc.common.filter.RepeatableFilter;
+import net.hzvtc.common.filter.XssFilter;
+import net.hzvtc.common.utils.StringUtils;
+import org.springframework.beans.factory.annotation.Value;
+import org.springframework.boot.autoconfigure.condition.ConditionalOnProperty;
+import org.springframework.boot.web.servlet.FilterRegistrationBean;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+
+/**
+ * Filter配置
+ *
+ * @author admin
+ */
+@Configuration
+public class FilterConfig
+{
+    @Value("${xss.excludes}")
+    private String excludes;
+
+    @Value("${xss.urlPatterns}")
+    private String urlPatterns;
+
+    @SuppressWarnings({ "rawtypes", "unchecked" })
+    @Bean
+    @ConditionalOnProperty(value = "xss.enabled", havingValue = "true")
+    public FilterRegistrationBean xssFilterRegistration()
+    {
+        FilterRegistrationBean registration = new FilterRegistrationBean();
+        registration.setDispatcherTypes(DispatcherType.REQUEST);
+        registration.setFilter(new XssFilter());
+        registration.addUrlPatterns(StringUtils.split(urlPatterns, ","));
+        registration.setName("xssFilter");
+        registration.setOrder(FilterRegistrationBean.HIGHEST_PRECEDENCE);
+        Map<String, String> initParameters = new HashMap<String, String>();
+        initParameters.put("excludes", excludes);
+        registration.setInitParameters(initParameters);
+        return registration;
+    }
+
+    @SuppressWarnings({ "rawtypes", "unchecked" })
+    @Bean
+    public FilterRegistrationBean someFilterRegistration()
+    {
+        FilterRegistrationBean registration = new FilterRegistrationBean();
+        registration.setFilter(new RepeatableFilter());
+        registration.addUrlPatterns("/*");
+        registration.setName("repeatableFilter");
+        registration.setOrder(FilterRegistrationBean.LOWEST_PRECEDENCE);
+        return registration;
+    }
+
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/config/KaptchaTextCreator.java

@@ -0,0 +1,75 @@
+package net.hzvtc.framework.config;
+
+import java.util.Random;
+import com.google.code.kaptcha.text.impl.DefaultTextCreator;
+
+/**
+ * 验证码文本生成器
+ * 
+ * @author admin
+ */
+public class KaptchaTextCreator extends DefaultTextCreator
+{
+    private static final String[] CNUMBERS = "0,1,2,3,4,5,6,7,8,9,10".split(",");
+
+    @Override
+    public String getText()
+    {
+        Integer result = 0;
+        Random random = new Random();
+        int x = random.nextInt(10);
+        int y = random.nextInt(10);
+        StringBuilder suChinese = new StringBuilder();
+        int randomoperands = (int) Math.round(Math.random() * 2);
+        if (randomoperands == 0)
+        {
+            result = x * y;
+            suChinese.append(CNUMBERS[x]);
+            suChinese.append("*");
+            suChinese.append(CNUMBERS[y]);
+        }
+        else if (randomoperands == 1)
+        {
+            if (!(x == 0) && y % x == 0)
+            {
+                result = y / x;
+                suChinese.append(CNUMBERS[y]);
+                suChinese.append("/");
+                suChinese.append(CNUMBERS[x]);
+            }
+            else
+            {
+                result = x + y;
+                suChinese.append(CNUMBERS[x]);
+                suChinese.append("+");
+                suChinese.append(CNUMBERS[y]);
+            }
+        }
+        else if (randomoperands == 2)
+        {
+            if (x >= y)
+            {
+                result = x - y;
+                suChinese.append(CNUMBERS[x]);
+                suChinese.append("-");
+                suChinese.append(CNUMBERS[y]);
+            }
+            else
+            {
+                result = y - x;
+                suChinese.append(CNUMBERS[y]);
+                suChinese.append("-");
+                suChinese.append(CNUMBERS[x]);
+            }
+        }
+        else
+        {
+            result = x + y;
+            suChinese.append(CNUMBERS[x]);
+            suChinese.append("+");
+            suChinese.append(CNUMBERS[y]);
+        }
+        suChinese.append("=?@" + result);
+        return suChinese.toString();
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/config/MyBatisConfig.java

@@ -0,0 +1,133 @@
+package net.hzvtc.framework.config;
+
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.HashSet;
+import java.util.List;
+import javax.sql.DataSource;
+
+import net.hzvtc.common.utils.StringUtils;
+import org.apache.ibatis.io.VFS;
+import org.apache.ibatis.session.SqlSessionFactory;
+import org.mybatis.spring.SqlSessionFactoryBean;
+import org.mybatis.spring.boot.autoconfigure.SpringBootVFS;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+import org.springframework.core.env.Environment;
+import org.springframework.core.io.DefaultResourceLoader;
+import org.springframework.core.io.Resource;
+import org.springframework.core.io.support.PathMatchingResourcePatternResolver;
+import org.springframework.core.io.support.ResourcePatternResolver;
+import org.springframework.core.type.classreading.CachingMetadataReaderFactory;
+import org.springframework.core.type.classreading.MetadataReader;
+import org.springframework.core.type.classreading.MetadataReaderFactory;
+import org.springframework.util.ClassUtils;
+
+/**
+ * Mybatis支持*匹配扫描包
+ * 
+ * @author admin
+ */
+@Configuration
+public class MyBatisConfig
+{
+    @Autowired
+    private Environment env;
+
+    static final String DEFAULT_RESOURCE_PATTERN = "**/*.class";
+
+    public static String setTypeAliasesPackage(String typeAliasesPackage)
+    {
+        ResourcePatternResolver resolver = (ResourcePatternResolver) new PathMatchingResourcePatternResolver();
+        MetadataReaderFactory metadataReaderFactory = new CachingMetadataReaderFactory(resolver);
+        List<String> allResult = new ArrayList<String>();
+        try
+        {
+            for (String aliasesPackage : typeAliasesPackage.split(","))
+            {
+                List<String> result = new ArrayList<String>();
+                aliasesPackage = ResourcePatternResolver.CLASSPATH_ALL_URL_PREFIX
+                        + ClassUtils.convertClassNameToResourcePath(aliasesPackage.trim()) + "/" + DEFAULT_RESOURCE_PATTERN;
+                Resource[] resources = resolver.getResources(aliasesPackage);
+                if (resources != null && resources.length > 0)
+                {
+                    MetadataReader metadataReader = null;
+                    for (Resource resource : resources)
+                    {
+                        if (resource.isReadable())
+                        {
+                            metadataReader = metadataReaderFactory.getMetadataReader(resource);
+                            try
+                            {
+                                result.add(Class.forName(metadataReader.getClassMetadata().getClassName()).getPackage().getName());
+                            }
+                            catch (ClassNotFoundException e)
+                            {
+                                e.printStackTrace();
+                            }
+                        }
+                    }
+                }
+                if (result.size() > 0)
+                {
+                    HashSet<String> hashResult = new HashSet<String>(result);
+                    allResult.addAll(hashResult);
+                }
+            }
+            if (allResult.size() > 0)
+            {
+                typeAliasesPackage = String.join(",", (String[]) allResult.toArray(new String[0]));
+            }
+            else
+            {
+                throw new RuntimeException("mybatis typeAliasesPackage 路径扫描错误,参数typeAliasesPackage:" + typeAliasesPackage + "未找到任何包");
+            }
+        }
+        catch (IOException e)
+        {
+            e.printStackTrace();
+        }
+        return typeAliasesPackage;
+    }
+
+    public Resource[] resolveMapperLocations(String[] mapperLocations)
+    {
+        ResourcePatternResolver resourceResolver = new PathMatchingResourcePatternResolver();
+        List<Resource> resources = new ArrayList<Resource>();
+        if (mapperLocations != null)
+        {
+            for (String mapperLocation : mapperLocations)
+            {
+                try
+                {
+                    Resource[] mappers = resourceResolver.getResources(mapperLocation);
+                    resources.addAll(Arrays.asList(mappers));
+                }
+                catch (IOException e)
+                {
+                    // ignore
+                }
+            }
+        }
+        return resources.toArray(new Resource[resources.size()]);
+    }
+
+    @Bean
+    public SqlSessionFactory sqlSessionFactory(DataSource dataSource) throws Exception
+    {
+        String typeAliasesPackage = env.getProperty("mybatis.typeAliasesPackage");
+        String mapperLocations = env.getProperty("mybatis.mapperLocations");
+        String configLocation = env.getProperty("mybatis.configLocation");
+        typeAliasesPackage = setTypeAliasesPackage(typeAliasesPackage);
+        VFS.addImplClass(SpringBootVFS.class);
+
+        final SqlSessionFactoryBean sessionFactory = new SqlSessionFactoryBean();
+        sessionFactory.setDataSource(dataSource);
+        sessionFactory.setTypeAliasesPackage(typeAliasesPackage);
+        sessionFactory.setMapperLocations(resolveMapperLocations(StringUtils.split(mapperLocations, ",")));
+        sessionFactory.setConfigLocation(new DefaultResourceLoader().getResource(configLocation));
+        return sessionFactory.getObject();
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/config/RedisConfig.java

@@ -0,0 +1,79 @@
+package net.hzvtc.framework.config;
+
+import org.springframework.cache.annotation.CachingConfigurerSupport;
+import org.springframework.cache.annotation.EnableCaching;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+import org.springframework.data.redis.connection.RedisConnectionFactory;
+import org.springframework.data.redis.core.RedisTemplate;
+import org.springframework.data.redis.core.script.DefaultRedisScript;
+import org.springframework.data.redis.serializer.StringRedisSerializer;
+import com.fasterxml.jackson.annotation.JsonAutoDetect;
+import com.fasterxml.jackson.annotation.JsonTypeInfo;
+import com.fasterxml.jackson.annotation.PropertyAccessor;
+import com.fasterxml.jackson.databind.ObjectMapper;
+import com.fasterxml.jackson.databind.jsontype.impl.LaissezFaireSubTypeValidator;
+
+/**
+ * redis配置
+ * 
+ * @author admin
+ */
+@Configuration
+@EnableCaching
+public class RedisConfig extends CachingConfigurerSupport
+{
+    @Bean
+    @SuppressWarnings(value = { "unchecked", "rawtypes" })
+    public RedisTemplate<Object, Object> redisTemplate(RedisConnectionFactory connectionFactory)
+    {
+        RedisTemplate<Object, Object> template = new RedisTemplate<>();
+        template.setConnectionFactory(connectionFactory);
+
+        FastJson2JsonRedisSerializer serializer = new FastJson2JsonRedisSerializer(Object.class);
+
+        ObjectMapper mapper = new ObjectMapper();
+        mapper.setVisibility(PropertyAccessor.ALL, JsonAutoDetect.Visibility.ANY);
+        mapper.activateDefaultTyping(LaissezFaireSubTypeValidator.instance, ObjectMapper.DefaultTyping.NON_FINAL, JsonTypeInfo.As.PROPERTY);
+        serializer.setObjectMapper(mapper);
+
+        // 使用StringRedisSerializer来序列化和反序列化redis的key值
+        template.setKeySerializer(new StringRedisSerializer());
+        template.setValueSerializer(serializer);
+
+        // Hash的key也采用StringRedisSerializer的序列化方式
+        template.setHashKeySerializer(new StringRedisSerializer());
+        template.setHashValueSerializer(serializer);
+
+        template.afterPropertiesSet();
+        return template;
+    }
+
+    @Bean
+    public DefaultRedisScript<Long> limitScript()
+    {
+        DefaultRedisScript<Long> redisScript = new DefaultRedisScript<>();
+        redisScript.setScriptText(limitScriptText());
+        redisScript.setResultType(Long.class);
+        return redisScript;
+    }
+
+    /**
+     * 限流脚本
+     */
+    private String limitScriptText()
+    {
+        return "local key = KEYS[1]\n" +
+                "local count = tonumber(ARGV[1])\n" +
+                "local time = tonumber(ARGV[2])\n" +
+                "local current = redis.call('get', key);\n" +
+                "if current and tonumber(current) > count then\n" +
+                "    return tonumber(current);\n" +
+                "end\n" +
+                "current = redis.call('incr', key)\n" +
+                "if tonumber(current) == 1 then\n" +
+                "    redis.call('expire', key, time)\n" +
+                "end\n" +
+                "return tonumber(current);";
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/config/ResourcesConfig.java

@@ -0,0 +1,66 @@
+package net.hzvtc.framework.config;
+
+import net.hzvtc.common.config.AiBirdSysConfig;
+import net.hzvtc.common.constant.Constants;
+import net.hzvtc.framework.interceptor.RepeatSubmitInterceptor;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+import org.springframework.web.cors.CorsConfiguration;
+import org.springframework.web.cors.UrlBasedCorsConfigurationSource;
+import org.springframework.web.filter.CorsFilter;
+import org.springframework.web.servlet.config.annotation.InterceptorRegistry;
+import org.springframework.web.servlet.config.annotation.ResourceHandlerRegistry;
+import org.springframework.web.servlet.config.annotation.WebMvcConfigurer;
+
+/**
+ * 通用配置
+ *
+ * @author admin
+ */
+@Configuration
+public class ResourcesConfig implements WebMvcConfigurer {
+    @Autowired
+    private RepeatSubmitInterceptor repeatSubmitInterceptor;
+
+    @Override
+    public void addResourceHandlers(ResourceHandlerRegistry registry) {
+        /** 本地文件上传路径 */
+        registry.addResourceHandler(Constants.RESOURCE_PREFIX + "/**")
+                .addResourceLocations("file:" + AiBirdSysConfig.getProfile() + "/");
+
+        /** swagger配置 */
+        registry.addResourceHandler("/swagger-ui/**")
+                .addResourceLocations("classpath:/META-INF/resources/webjars/springfox-swagger-ui/");
+    }
+
+    /**
+     * 自定义拦截规则
+     */
+    @Override
+    public void addInterceptors(InterceptorRegistry registry) {
+        registry.addInterceptor(repeatSubmitInterceptor).addPathPatterns("/**");
+    }
+
+    /**
+     * 跨域配置
+     */
+    @Bean
+    public CorsFilter corsFilter() {
+        CorsConfiguration config = new CorsConfiguration();
+        config.setAllowCredentials(true);
+        // 设置访问源地址
+        config.addAllowedOriginPattern("*");
+        // 设置访问源请求头
+        config.addAllowedHeader("*");
+        // 设置访问源请求方法
+        config.addAllowedMethod("*");
+        // 有效期 1800秒
+        config.setMaxAge(1800L);
+        // 添加映射路径，拦截一切请求
+        UrlBasedCorsConfigurationSource source = new UrlBasedCorsConfigurationSource();
+        source.registerCorsConfiguration("/**", config);
+        // 返回新的CorsFilter
+        return new CorsFilter(source);
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/config/SecurityConfig.java

@@ -0,0 +1,145 @@
+package net.hzvtc.framework.config;
+
+import net.hzvtc.framework.security.filter.JwtAuthenticationTokenFilter;
+import net.hzvtc.framework.security.handle.AuthenticationEntryPointImpl;
+import net.hzvtc.framework.security.handle.LogoutSuccessHandlerImpl;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.context.annotation.Bean;
+import org.springframework.http.HttpMethod;
+import org.springframework.security.authentication.AuthenticationManager;
+import org.springframework.security.config.annotation.authentication.builders.AuthenticationManagerBuilder;
+import org.springframework.security.config.annotation.method.configuration.EnableGlobalMethodSecurity;
+import org.springframework.security.config.annotation.web.builders.HttpSecurity;
+import org.springframework.security.config.annotation.web.configuration.WebSecurityConfigurerAdapter;
+import org.springframework.security.config.http.SessionCreationPolicy;
+import org.springframework.security.core.userdetails.UserDetailsService;
+import org.springframework.security.crypto.bcrypt.BCryptPasswordEncoder;
+import org.springframework.security.web.authentication.UsernamePasswordAuthenticationFilter;
+import org.springframework.security.web.authentication.logout.LogoutFilter;
+import org.springframework.web.filter.CorsFilter;
+
+/**
+ * spring security配置
+ *
+ * @author admin
+ */
+@EnableGlobalMethodSecurity(prePostEnabled = true, securedEnabled = true)
+public class SecurityConfig extends WebSecurityConfigurerAdapter {
+    /**
+     * 自定义用户认证逻辑
+     */
+    @Autowired
+    private UserDetailsService userDetailsService;
+
+    /**
+     * 认证失败处理类
+     */
+    @Autowired
+    private AuthenticationEntryPointImpl unauthorizedHandler;
+
+    /**
+     * 退出处理类
+     */
+    @Autowired
+    private LogoutSuccessHandlerImpl logoutSuccessHandler;
+
+    /**
+     * token认证过滤器
+     */
+    @Autowired
+    private JwtAuthenticationTokenFilter authenticationTokenFilter;
+
+    /**
+     * 跨域过滤器
+     */
+    @Autowired
+    private CorsFilter corsFilter;
+
+    /**
+     * 解决 无法直接注入 AuthenticationManager
+     *
+     * @return
+     * @throws Exception
+     */
+    @Bean
+    @Override
+    public AuthenticationManager authenticationManagerBean() throws Exception {
+        return super.authenticationManagerBean();
+    }
+
+    /**
+     * anyRequest          |   匹配所有请求路径
+     * access              |   SpringEl表达式结果为true时可以访问
+     * anonymous           |   匿名可以访问
+     * denyAll             |   用户不能访问
+     * fullyAuthenticated  |   用户完全认证可以访问（非remember-me下自动登录）
+     * hasAnyAuthority     |   如果有参数，参数表示权限，则其中任何一个权限可以访问
+     * hasAnyRole          |   如果有参数，参数表示角色，则其中任何一个角色可以访问
+     * hasAuthority        |   如果有参数，参数表示权限，则其权限可以访问
+     * hasIpAddress        |   如果有参数，参数表示IP地址，如果用户IP和参数匹配，则可以访问
+     * hasRole             |   如果有参数，参数表示角色，则其角色可以访问
+     * permitAll           |   用户可以任意访问
+     * rememberMe          |   允许通过remember-me登录的用户访问
+     * authenticated       |   用户登录后可访问
+     */
+    @Override
+    protected void configure(HttpSecurity httpSecurity) throws Exception {
+        httpSecurity
+                // CSRF禁用，因为不使用session
+                .csrf().disable()
+                // 认证失败处理类
+                .exceptionHandling().authenticationEntryPoint(unauthorizedHandler).and()
+                // 基于token，所以不需要session
+                .sessionManagement().sessionCreationPolicy(SessionCreationPolicy.STATELESS).and()
+                // 过滤请求
+                .authorizeRequests()
+                // 对于登录login 注册register 验证码captchaImage 允许匿名访问
+                .antMatchers("/login", "/web/api/getToken",
+                        "/appCaptchaImage",
+                        "/captchaImage",
+                        "/appUpdate",
+                        "/sm2login",
+                        "/web/getPublicKey",
+                        "/restPassword").anonymous()
+                .antMatchers(
+                        HttpMethod.GET,
+                        "/",
+                        "/*.html",
+                        "/**/*.html",
+                        "/**/*.css",
+                        "/**/*.js",
+                        "/profile/**"
+                ).permitAll()
+                .antMatchers("/swagger-ui.html").anonymous()
+                .antMatchers("/swagger-resources/**").anonymous()
+                .antMatchers("/webjars/**").anonymous()
+                .antMatchers("/*/api-docs").anonymous()
+                .antMatchers("/druid/**").anonymous()
+                // 除上面外的所有请求全部需要鉴权认证
+                .anyRequest().authenticated()
+                .and()
+                .headers().frameOptions().disable();
+        httpSecurity.logout().logoutUrl("/logout").logoutSuccessHandler(logoutSuccessHandler);
+        // 添加JWT filter
+        httpSecurity.addFilterBefore(authenticationTokenFilter, UsernamePasswordAuthenticationFilter.class);
+        // 添加CORS filter
+        httpSecurity.addFilterBefore(corsFilter, JwtAuthenticationTokenFilter.class);
+        httpSecurity.addFilterBefore(corsFilter, LogoutFilter.class);
+    }
+
+    /**
+     * 强散列哈希加密实现
+     */
+    @Bean
+    public BCryptPasswordEncoder bCryptPasswordEncoder() {
+        return new BCryptPasswordEncoder();
+    }
+
+    /**
+     * 身份认证接口
+     */
+    @Override
+    protected void configure(AuthenticationManagerBuilder auth) throws Exception {
+        auth.userDetailsService(userDetailsService).passwordEncoder(bCryptPasswordEncoder());
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/config/ServerConfig.java

@@ -0,0 +1,33 @@
+package net.hzvtc.framework.config;
+
+import javax.servlet.http.HttpServletRequest;
+
+import net.hzvtc.common.utils.ServletUtils;
+import org.springframework.stereotype.Component;
+
+/**
+ * 服务相关配置
+ * 
+ * @author admin
+ */
+@Component
+public class ServerConfig
+{
+    /**
+     * 获取完整的请求路径，包括：域名，端口，上下文访问路径
+     * 
+     * @return 服务地址
+     */
+    public String getUrl()
+    {
+        HttpServletRequest request = ServletUtils.getRequest();
+        return getDomain(request);
+    }
+
+    public static String getDomain(HttpServletRequest request)
+    {
+        StringBuffer url = request.getRequestURL();
+        String contextPath = request.getServletContext().getContextPath();
+        return url.delete(url.length() - request.getRequestURI().length(), url.length()).append(contextPath).toString();
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/config/ThreadPoolConfig.java

@@ -0,0 +1,63 @@
+package net.hzvtc.framework.config;
+
+import net.hzvtc.common.utils.Threads;
+import org.apache.commons.lang3.concurrent.BasicThreadFactory;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor;
+import java.util.concurrent.ScheduledExecutorService;
+import java.util.concurrent.ScheduledThreadPoolExecutor;
+import java.util.concurrent.ThreadPoolExecutor;
+
+/**
+ * 线程池配置
+ *
+ * @author admin
+ **/
+@Configuration
+public class ThreadPoolConfig
+{
+    // 核心线程池大小
+    private int corePoolSize = 50;
+
+    // 最大可创建的线程数
+    private int maxPoolSize = 200;
+
+    // 队列最大长度
+    private int queueCapacity = 1000;
+
+    // 线程池维护线程所允许的空闲时间
+    private int keepAliveSeconds = 300;
+
+    @Bean(name = "threadPoolTaskExecutor")
+    public ThreadPoolTaskExecutor threadPoolTaskExecutor()
+    {
+        ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
+        executor.setMaxPoolSize(maxPoolSize);
+        executor.setCorePoolSize(corePoolSize);
+        executor.setQueueCapacity(queueCapacity);
+        executor.setKeepAliveSeconds(keepAliveSeconds);
+        // 线程池对拒绝任务(无线程可用)的处理策略
+        executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
+        return executor;
+    }
+
+    /**
+     * 执行周期性或定时任务
+     */
+    @Bean(name = "scheduledExecutorService")
+    protected ScheduledExecutorService scheduledExecutorService()
+    {
+        return new ScheduledThreadPoolExecutor(corePoolSize,
+                new BasicThreadFactory.Builder().namingPattern("schedule-pool-%d").daemon(true).build(),
+                new ThreadPoolExecutor.CallerRunsPolicy())
+        {
+            @Override
+            protected void afterExecute(Runnable r, Throwable t)
+            {
+                super.afterExecute(r, t);
+                Threads.printException(r, t);
+            }
+        };
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/config/properties/DruidProperties.java

@@ -0,0 +1,77 @@
+package net.hzvtc.framework.config.properties;
+
+import org.springframework.beans.factory.annotation.Value;
+import org.springframework.context.annotation.Configuration;
+import com.alibaba.druid.pool.DruidDataSource;
+
+/**
+ * druid 配置属性
+ * 
+ * @author admin
+ */
+@Configuration
+public class DruidProperties
+{
+    @Value("${spring.datasource.druid.initialSize}")
+    private int initialSize;
+
+    @Value("${spring.datasource.druid.minIdle}")
+    private int minIdle;
+
+    @Value("${spring.datasource.druid.maxActive}")
+    private int maxActive;
+
+    @Value("${spring.datasource.druid.maxWait}")
+    private int maxWait;
+
+    @Value("${spring.datasource.druid.timeBetweenEvictionRunsMillis}")
+    private int timeBetweenEvictionRunsMillis;
+
+    @Value("${spring.datasource.druid.minEvictableIdleTimeMillis}")
+    private int minEvictableIdleTimeMillis;
+
+    @Value("${spring.datasource.druid.maxEvictableIdleTimeMillis}")
+    private int maxEvictableIdleTimeMillis;
+
+    @Value("${spring.datasource.druid.validationQuery}")
+    private String validationQuery;
+
+    @Value("${spring.datasource.druid.testWhileIdle}")
+    private boolean testWhileIdle;
+
+    @Value("${spring.datasource.druid.testOnBorrow}")
+    private boolean testOnBorrow;
+
+    @Value("${spring.datasource.druid.testOnReturn}")
+    private boolean testOnReturn;
+
+    public DruidDataSource dataSource(DruidDataSource datasource)
+    {
+        /** 配置初始化大小、最小、最大 */
+        datasource.setInitialSize(initialSize);
+        datasource.setMaxActive(maxActive);
+        datasource.setMinIdle(minIdle);
+
+        /** 配置获取连接等待超时的时间 */
+        datasource.setMaxWait(maxWait);
+
+        /** 配置间隔多久才进行一次检测，检测需要关闭的空闲连接，单位是毫秒 */
+        datasource.setTimeBetweenEvictionRunsMillis(timeBetweenEvictionRunsMillis);
+
+        /** 配置一个连接在池中最小、最大生存的时间，单位是毫秒 */
+        datasource.setMinEvictableIdleTimeMillis(minEvictableIdleTimeMillis);
+        datasource.setMaxEvictableIdleTimeMillis(maxEvictableIdleTimeMillis);
+
+        /**
+         * 用来检测连接是否有效的sql，要求是一个查询语句，常用select 'x'。如果validationQuery为null，testOnBorrow、testOnReturn、testWhileIdle都不会起作用。
+         */
+        datasource.setValidationQuery(validationQuery);
+        /** 建议配置为true，不影响性能，并且保证安全性。申请连接的时候检测，如果空闲时间大于timeBetweenEvictionRunsMillis，执行validationQuery检测连接是否有效。 */
+        datasource.setTestWhileIdle(testWhileIdle);
+        /** 申请连接时执行validationQuery检测连接是否有效，做了这个配置会降低性能。 */
+        datasource.setTestOnBorrow(testOnBorrow);
+        /** 归还连接时执行validationQuery检测连接是否有效，做了这个配置会降低性能。 */
+        datasource.setTestOnReturn(testOnReturn);
+        return datasource;
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/datasource/DynamicDataSource.java

@@ -0,0 +1,26 @@
+package net.hzvtc.framework.datasource;
+
+import java.util.Map;
+import javax.sql.DataSource;
+import org.springframework.jdbc.datasource.lookup.AbstractRoutingDataSource;
+
+/**
+ * 动态数据源
+ * 
+ * @author admin
+ */
+public class DynamicDataSource extends AbstractRoutingDataSource
+{
+    public DynamicDataSource(DataSource defaultTargetDataSource, Map<Object, Object> targetDataSources)
+    {
+        super.setDefaultTargetDataSource(defaultTargetDataSource);
+        super.setTargetDataSources(targetDataSources);
+        super.afterPropertiesSet();
+    }
+
+    @Override
+    protected Object determineCurrentLookupKey()
+    {
+        return DynamicDataSourceContextHolder.getDataSourceType();
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/datasource/DynamicDataSourceContextHolder.java

@@ -0,0 +1,45 @@
+package net.hzvtc.framework.datasource;
+
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+/**
+ * 数据源切换处理
+ * 
+ * @author admin
+ */
+public class DynamicDataSourceContextHolder
+{
+    public static final Logger log = LoggerFactory.getLogger(DynamicDataSourceContextHolder.class);
+
+    /**
+     * 使用ThreadLocal维护变量，ThreadLocal为每个使用该变量的线程提供独立的变量副本，
+     *  所以每一个线程都可以独立地改变自己的副本，而不会影响其它线程所对应的副本。
+     */
+    private static final ThreadLocal<String> CONTEXT_HOLDER = new ThreadLocal<>();
+
+    /**
+     * 设置数据源的变量
+     */
+    public static void setDataSourceType(String dsType)
+    {
+        log.info("切换到{}数据源", dsType);
+        CONTEXT_HOLDER.set(dsType);
+    }
+
+    /**
+     * 获得数据源的变量
+     */
+    public static String getDataSourceType()
+    {
+        return CONTEXT_HOLDER.get();
+    }
+
+    /**
+     * 清空数据源变量
+     */
+    public static void clearDataSourceType()
+    {
+        CONTEXT_HOLDER.remove();
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/datasource/MySqlDialectCustom.java

@@ -0,0 +1,24 @@
+package net.hzvtc.framework.datasource;
+
+import com.github.pagehelper.Page;
+import com.github.pagehelper.dialect.helper.MySqlDialect;
+import org.apache.ibatis.cache.CacheKey;
+
+import java.util.regex.Pattern;
+
+public class MySqlDialectCustom extends MySqlDialect {
+    @Override
+    public String getPageSql(String sql, Page page, CacheKey pageKey) {
+        Pattern compileFixed = Pattern.compile("/\\*fixed\\*/");
+        String compileLimit = "/\\*limit\\*/";
+        if (compileFixed.matcher(sql).find()) {
+            if (page.getStartRow() == 0) {
+                sql = sql.replaceFirst(compileLimit, " LIMIT ? ");
+            } else {
+                sql = sql.replaceFirst(compileLimit, " LIMIT ?, ? ");
+            }
+            return sql;
+        }
+        return super.getPageSql(sql, page, pageKey);
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/interceptor/RepeatSubmitInterceptor.java

@@ -0,0 +1,56 @@
+package net.hzvtc.framework.interceptor;
+
+import java.lang.reflect.Method;
+import javax.servlet.http.HttpServletRequest;
+import javax.servlet.http.HttpServletResponse;
+
+import net.hzvtc.common.core.domain.AjaxResult;
+import net.hzvtc.common.utils.ServletUtils;
+import org.springframework.stereotype.Component;
+import org.springframework.web.method.HandlerMethod;
+import org.springframework.web.servlet.HandlerInterceptor;
+import com.alibaba.fastjson.JSONObject;
+import net.hzvtc.common.annotation.RepeatSubmit;
+
+/**
+ * 防止重复提交拦截器
+ *
+ * @author admin
+ */
+@Component
+public abstract class RepeatSubmitInterceptor implements HandlerInterceptor
+{
+    @Override
+    public boolean preHandle(HttpServletRequest request, HttpServletResponse response, Object handler) throws Exception
+    {
+        if (handler instanceof HandlerMethod)
+        {
+            HandlerMethod handlerMethod = (HandlerMethod) handler;
+            Method method = handlerMethod.getMethod();
+            RepeatSubmit annotation = method.getAnnotation(RepeatSubmit.class);
+            if (annotation != null)
+            {
+                if (this.isRepeatSubmit(request, annotation))
+                {
+                    AjaxResult ajaxResult = AjaxResult.error(annotation.message());
+                    ServletUtils.renderString(response, JSONObject.toJSONString(ajaxResult));
+                    return false;
+                }
+            }
+            return true;
+        }
+        else
+        {
+            return true;
+        }
+    }
+
+    /**
+     * 验证是否重复提交由子类实现具体的防重复提交的规则
+     *
+     * @param request
+     * @return
+     * @throws Exception
+     */
+    public abstract boolean isRepeatSubmit(HttpServletRequest request, RepeatSubmit annotation);
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/interceptor/impl/SameUrlDataInterceptor.java

@@ -0,0 +1,111 @@
+package net.hzvtc.framework.interceptor.impl;
+
+import java.util.HashMap;
+import java.util.Map;
+import java.util.concurrent.TimeUnit;
+import javax.servlet.http.HttpServletRequest;
+
+import net.hzvtc.common.constant.Constants;
+import net.hzvtc.common.core.redis.RedisCache;
+import net.hzvtc.common.filter.RepeatedlyRequestWrapper;
+import net.hzvtc.common.utils.StringUtils;
+import net.hzvtc.common.utils.http.HttpHelper;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.beans.factory.annotation.Value;
+import org.springframework.stereotype.Component;
+import com.alibaba.fastjson.JSONObject;
+import net.hzvtc.common.annotation.RepeatSubmit;
+import net.hzvtc.framework.interceptor.RepeatSubmitInterceptor;
+
+/**
+ * 判断请求url和数据是否和上一次相同，
+ * 如果和上次相同，则是重复提交表单。 有效时间为10秒内。
+ * 
+ * @author admin
+ */
+@Component
+public class SameUrlDataInterceptor extends RepeatSubmitInterceptor
+{
+    public final String REPEAT_PARAMS = "repeatParams";
+
+    public final String REPEAT_TIME = "repeatTime";
+
+    // 令牌自定义标识
+    @Value("${token.header}")
+    private String header;
+
+    @Autowired
+    private RedisCache redisCache;
+
+    @SuppressWarnings("unchecked")
+    @Override
+    public boolean isRepeatSubmit(HttpServletRequest request, RepeatSubmit annotation)
+    {
+        String nowParams = "";
+        if (request instanceof RepeatedlyRequestWrapper)
+        {
+            RepeatedlyRequestWrapper repeatedlyRequest = (RepeatedlyRequestWrapper) request;
+            nowParams = HttpHelper.getBodyString(repeatedlyRequest);
+        }
+
+        // body参数为空，获取Parameter的数据
+        if (StringUtils.isEmpty(nowParams))
+        {
+            nowParams = JSONObject.toJSONString(request.getParameterMap());
+        }
+        Map<String, Object> nowDataMap = new HashMap<String, Object>();
+        nowDataMap.put(REPEAT_PARAMS, nowParams);
+        nowDataMap.put(REPEAT_TIME, System.currentTimeMillis());
+
+        // 请求地址（作为存放cache的key值）
+        String url = request.getRequestURI();
+
+        // 唯一值（没有消息头则使用请求地址）
+        String submitKey = StringUtils.trimToEmpty(request.getHeader(header));
+
+        // 唯一标识（指定key + url + 消息头）
+        String cacheRepeatKey = Constants.REPEAT_SUBMIT_KEY + url + submitKey;
+
+        Object sessionObj = redisCache.getCacheObject(cacheRepeatKey);
+        if (sessionObj != null)
+        {
+            Map<String, Object> sessionMap = (Map<String, Object>) sessionObj;
+            if (sessionMap.containsKey(url))
+            {
+                Map<String, Object> preDataMap = (Map<String, Object>) sessionMap.get(url);
+                if (compareParams(nowDataMap, preDataMap) && compareTime(nowDataMap, preDataMap, annotation.interval()))
+                {
+                    return true;
+                }
+            }
+        }
+        Map<String, Object> cacheMap = new HashMap<String, Object>();
+        cacheMap.put(url, nowDataMap);
+        redisCache.setCacheObject(cacheRepeatKey, cacheMap, annotation.interval(), TimeUnit.MILLISECONDS);
+        return false;
+    }
+
+    /**
+     * 判断参数是否相同
+     */
+    private boolean compareParams(Map<String, Object> nowMap, Map<String, Object> preMap)
+    {
+        String nowParams = (String) nowMap.get(REPEAT_PARAMS);
+        String preParams = (String) preMap.get(REPEAT_PARAMS);
+        return nowParams.equals(preParams);
+    }
+
+    /**
+     * 判断两次间隔时间
+     */
+    private boolean compareTime(Map<String, Object> nowMap, Map<String, Object> preMap, int interval)
+    {
+        long time1 = (Long) nowMap.get(REPEAT_TIME);
+        long time2 = (Long) preMap.get(REPEAT_TIME);
+        if ((time1 - time2) < interval)
+        {
+            return true;
+        }
+        return false;
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/manager/AsyncManager.java

@@ -0,0 +1,55 @@
+package net.hzvtc.framework.manager;
+
+import java.util.TimerTask;
+import java.util.concurrent.ScheduledExecutorService;
+import java.util.concurrent.TimeUnit;
+import net.hzvtc.common.utils.Threads;
+import net.hzvtc.common.utils.spring.SpringUtils;
+
+/**
+ * 异步任务管理器
+ * 
+ * @author admin
+ */
+public class AsyncManager
+{
+    /**
+     * 操作延迟10毫秒
+     */
+    private final int OPERATE_DELAY_TIME = 10;
+
+    /**
+     * 异步操作任务调度线程池
+     */
+    private ScheduledExecutorService executor = SpringUtils.getBean("scheduledExecutorService");
+
+    /**
+     * 单例模式
+     */
+    private AsyncManager(){}
+
+    private static AsyncManager me = new AsyncManager();
+
+    public static AsyncManager me()
+    {
+        return me;
+    }
+
+    /**
+     * 执行任务
+     * 
+     * @param task 任务
+     */
+    public void execute(TimerTask task)
+    {
+        executor.schedule(task, OPERATE_DELAY_TIME, TimeUnit.MILLISECONDS);
+    }
+
+    /**
+     * 停止任务线程池
+     */
+    public void shutdown()
+    {
+        Threads.shutdownAndAwaitTermination(executor);
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/manager/ShutdownManager.java

@@ -0,0 +1,39 @@
+package net.hzvtc.framework.manager;
+
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.stereotype.Component;
+import javax.annotation.PreDestroy;
+
+/**
+ * 确保应用退出时能关闭后台线程
+ *
+ * @author admin
+ */
+@Component
+public class ShutdownManager
+{
+    private static final Logger logger = LoggerFactory.getLogger("sys-user");
+
+    @PreDestroy
+    public void destroy()
+    {
+        shutdownAsyncManager();
+    }
+
+    /**
+     * 停止异步执行任务
+     */
+    private void shutdownAsyncManager()
+    {
+        try
+        {
+            logger.info("====关闭后台任务任务线程池====");
+            AsyncManager.me().shutdown();
+        }
+        catch (Exception e)
+        {
+            logger.error(e.getMessage(), e);
+        }
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/manager/factory/AsyncFactory.java

@@ -0,0 +1,103 @@
+package net.hzvtc.framework.manager.factory;
+
+import java.util.TimerTask;
+
+import net.hzvtc.common.constant.Constants;
+import net.hzvtc.common.utils.LogUtils;
+import net.hzvtc.common.utils.ServletUtils;
+import net.hzvtc.common.utils.StringUtils;
+import net.hzvtc.common.utils.ip.AddressUtils;
+import net.hzvtc.common.utils.ip.IpUtils;
+import net.hzvtc.common.utils.spring.SpringUtils;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import net.hzvtc.system.domain.SysLogininfor;
+import net.hzvtc.system.domain.SysOperLog;
+import net.hzvtc.system.service.SysLogininforService;
+import net.hzvtc.system.service.SysOperLogService;
+import eu.bitwalker.useragentutils.UserAgent;
+
+/**
+ * 异步工厂（产生任务用）
+ * 
+ * @author admin
+ */
+public class AsyncFactory
+{
+    private static final Logger sys_user_logger = LoggerFactory.getLogger("sys-user");
+
+    /**
+     * 记录登录信息
+     * 
+     * @param username 用户名
+     * @param status 状态
+     * @param message 消息
+     * @param args 列表
+     * @return 任务task
+     */
+    public static TimerTask recordLogininfor(final String username, final String status, final String message,
+            final Object... args)
+    {
+        final UserAgent userAgent = UserAgent.parseUserAgentString(ServletUtils.getRequest().getHeader("User-Agent"));
+        final String ip = IpUtils.getIpAddr(ServletUtils.getRequest());
+        return new TimerTask()
+        {
+            @Override
+            public void run()
+            {
+                String address = AddressUtils.getRealAddressByIP(ip);
+                StringBuilder s = new StringBuilder();
+                s.append(LogUtils.getBlock(ip));
+                s.append(address);
+                s.append(LogUtils.getBlock(username));
+                s.append(LogUtils.getBlock(status));
+                s.append(LogUtils.getBlock(message));
+                // 打印信息到日志
+                sys_user_logger.info(s.toString(), args);
+                // 获取客户端操作系统
+                String os = userAgent.getOperatingSystem().getName();
+                // 获取客户端浏览器
+                String browser = userAgent.getBrowser().getName();
+                // 封装对象
+                SysLogininfor logininfor = new SysLogininfor();
+                logininfor.setUserName(username);
+                logininfor.setIpaddr(ip);
+                logininfor.setLoginLocation(address);
+                logininfor.setBrowser(browser);
+                logininfor.setOs(os);
+                logininfor.setMsg(message);
+                // 日志状态
+                if (StringUtils.equalsAny(status, Constants.LOGIN_SUCCESS, Constants.LOGOUT, Constants.REGISTER))
+                {
+                    logininfor.setStatus(Constants.SUCCESS);
+                }
+                else if (Constants.LOGIN_FAIL.equals(status))
+                {
+                    logininfor.setStatus(Constants.FAIL);
+                }
+                // 插入数据
+                SpringUtils.getBean(SysLogininforService.class).insertLogininfor(logininfor);
+            }
+        };
+    }
+
+    /**
+     * 操作日志记录
+     * 
+     * @param operLog 操作日志信息
+     * @return 任务task
+     */
+    public static TimerTask recordOper(final SysOperLog operLog)
+    {
+        return new TimerTask()
+        {
+            @Override
+            public void run()
+            {
+                // 远程查询操作地点
+                operLog.setOperLocation(AddressUtils.getRealAddressByIP(operLog.getOperIp()));
+                SpringUtils.getBean(SysOperLogService.class).insertOperlog(operLog);
+            }
+        };
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/security/filter/JwtAuthenticationTokenFilter.java

@@ -0,0 +1,45 @@
+package net.hzvtc.framework.security.filter;
+
+import java.io.IOException;
+import javax.servlet.FilterChain;
+import javax.servlet.ServletException;
+import javax.servlet.http.HttpServletRequest;
+import javax.servlet.http.HttpServletResponse;
+
+import net.hzvtc.common.core.domain.model.LoginUser;
+import net.hzvtc.common.utils.SecurityUtils;
+import net.hzvtc.common.utils.StringUtils;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.security.authentication.UsernamePasswordAuthenticationToken;
+import org.springframework.security.core.context.SecurityContextHolder;
+import org.springframework.security.web.authentication.WebAuthenticationDetailsSource;
+import org.springframework.stereotype.Component;
+import org.springframework.web.filter.OncePerRequestFilter;
+import net.hzvtc.framework.web.service.TokenService;
+
+/**
+ * token过滤器 验证token有效性
+ * 
+ * @author admin
+ */
+@Component
+public class JwtAuthenticationTokenFilter extends OncePerRequestFilter
+{
+    @Autowired
+    private TokenService tokenService;
+
+    @Override
+    protected void doFilterInternal(HttpServletRequest request, HttpServletResponse response, FilterChain chain)
+            throws ServletException, IOException
+    {
+        LoginUser loginUser = tokenService.getLoginUser(request);
+        if (StringUtils.isNotNull(loginUser) && StringUtils.isNull(SecurityUtils.getAuthentication()))
+        {
+            tokenService.verifyToken(loginUser);
+            UsernamePasswordAuthenticationToken authenticationToken = new UsernamePasswordAuthenticationToken(loginUser, null, loginUser.getAuthorities());
+            authenticationToken.setDetails(new WebAuthenticationDetailsSource().buildDetails(request));
+            SecurityContextHolder.getContext().setAuthentication(authenticationToken);
+        }
+        chain.doFilter(request, response);
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/security/handle/AuthenticationEntryPointImpl.java

@@ -0,0 +1,35 @@
+package net.hzvtc.framework.security.handle;
+
+import java.io.IOException;
+import java.io.Serializable;
+import javax.servlet.http.HttpServletRequest;
+import javax.servlet.http.HttpServletResponse;
+
+import net.hzvtc.common.constant.HttpStatus;
+import net.hzvtc.common.core.domain.AjaxResult;
+import net.hzvtc.common.utils.ServletUtils;
+import net.hzvtc.common.utils.StringUtils;
+import org.springframework.security.core.AuthenticationException;
+import org.springframework.security.web.AuthenticationEntryPoint;
+import org.springframework.stereotype.Component;
+import com.alibaba.fastjson.JSON;
+
+/**
+ * 认证失败处理类 返回未授权
+ * 
+ * @author admin
+ */
+@Component
+public class AuthenticationEntryPointImpl implements AuthenticationEntryPoint, Serializable
+{
+    private static final long serialVersionUID = -8970718410437077606L;
+
+    @Override
+    public void commence(HttpServletRequest request, HttpServletResponse response, AuthenticationException e)
+            throws IOException
+    {
+        int code = HttpStatus.UNAUTHORIZED;
+        String msg = StringUtils.format("请求访问：{}，认证失败，无法访问系统资源", request.getRequestURI());
+        ServletUtils.renderString(response, JSON.toJSONString(AjaxResult.error(code, msg)));
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/security/handle/LogoutSuccessHandlerImpl.java

@@ -0,0 +1,54 @@
+package net.hzvtc.framework.security.handle;
+
+import java.io.IOException;
+import javax.servlet.ServletException;
+import javax.servlet.http.HttpServletRequest;
+import javax.servlet.http.HttpServletResponse;
+
+import net.hzvtc.common.constant.Constants;
+import net.hzvtc.common.constant.HttpStatus;
+import net.hzvtc.common.core.domain.AjaxResult;
+import net.hzvtc.common.core.domain.model.LoginUser;
+import net.hzvtc.common.utils.ServletUtils;
+import net.hzvtc.common.utils.StringUtils;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.context.annotation.Configuration;
+import org.springframework.security.core.Authentication;
+import org.springframework.security.web.authentication.logout.LogoutSuccessHandler;
+import com.alibaba.fastjson.JSON;
+import net.hzvtc.framework.manager.AsyncManager;
+import net.hzvtc.framework.manager.factory.AsyncFactory;
+import net.hzvtc.framework.web.service.TokenService;
+
+/**
+ * 自定义退出处理类 返回成功
+ * 
+ * @author admin
+ */
+@Configuration
+public class LogoutSuccessHandlerImpl implements LogoutSuccessHandler
+{
+    @Autowired
+    private TokenService tokenService;
+
+    /**
+     * 退出处理
+     * 
+     * @return
+     */
+    @Override
+    public void onLogoutSuccess(HttpServletRequest request, HttpServletResponse response, Authentication authentication)
+            throws IOException, ServletException
+    {
+        LoginUser loginUser = tokenService.getLoginUser(request);
+        if (StringUtils.isNotNull(loginUser))
+        {
+            String userName = loginUser.getUsername();
+            // 删除用户缓存记录
+            tokenService.delLoginUser(loginUser.getToken());
+            // 记录用户退出日志
+            AsyncManager.me().execute(AsyncFactory.recordLogininfor(userName, Constants.LOGOUT, "退出成功"));
+        }
+        ServletUtils.renderString(response, JSON.toJSONString(AjaxResult.error(HttpStatus.SUCCESS, "退出成功")));
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/web/domain/Server.java

@@ -0,0 +1,240 @@
+package net.hzvtc.framework.web.domain;
+
+import java.net.UnknownHostException;
+import java.util.LinkedList;
+import java.util.List;
+import java.util.Properties;
+import net.hzvtc.common.utils.Arith;
+import net.hzvtc.common.utils.ip.IpUtils;
+import net.hzvtc.framework.web.domain.server.Cpu;
+import net.hzvtc.framework.web.domain.server.Jvm;
+import net.hzvtc.framework.web.domain.server.Mem;
+import net.hzvtc.framework.web.domain.server.Sys;
+import net.hzvtc.framework.web.domain.server.SysFile;
+import oshi.SystemInfo;
+import oshi.hardware.CentralProcessor;
+import oshi.hardware.CentralProcessor.TickType;
+import oshi.hardware.GlobalMemory;
+import oshi.hardware.HardwareAbstractionLayer;
+import oshi.software.os.FileSystem;
+import oshi.software.os.OSFileStore;
+import oshi.software.os.OperatingSystem;
+import oshi.util.Util;
+
+/**
+ * 服务器相关信息
+ * 
+ * @author admin
+ */
+public class Server
+{
+    private static final int OSHI_WAIT_SECOND = 1000;
+    
+    /**
+     * CPU相关信息
+     */
+    private Cpu cpu = new Cpu();
+
+    /**
+     * 內存相关信息
+     */
+    private Mem mem = new Mem();
+
+    /**
+     * JVM相关信息
+     */
+    private Jvm jvm = new Jvm();
+
+    /**
+     * 服务器相关信息
+     */
+    private Sys sys = new Sys();
+
+    /**
+     * 磁盘相关信息
+     */
+    private List<SysFile> sysFiles = new LinkedList<SysFile>();
+
+    public Cpu getCpu()
+    {
+        return cpu;
+    }
+
+    public void setCpu(Cpu cpu)
+    {
+        this.cpu = cpu;
+    }
+
+    public Mem getMem()
+    {
+        return mem;
+    }
+
+    public void setMem(Mem mem)
+    {
+        this.mem = mem;
+    }
+
+    public Jvm getJvm()
+    {
+        return jvm;
+    }
+
+    public void setJvm(Jvm jvm)
+    {
+        this.jvm = jvm;
+    }
+
+    public Sys getSys()
+    {
+        return sys;
+    }
+
+    public void setSys(Sys sys)
+    {
+        this.sys = sys;
+    }
+
+    public List<SysFile> getSysFiles()
+    {
+        return sysFiles;
+    }
+
+    public void setSysFiles(List<SysFile> sysFiles)
+    {
+        this.sysFiles = sysFiles;
+    }
+
+    public void copyTo() throws Exception
+    {
+        SystemInfo si = new SystemInfo();
+        HardwareAbstractionLayer hal = si.getHardware();
+
+        setCpuInfo(hal.getProcessor());
+
+        setMemInfo(hal.getMemory());
+
+        setSysInfo();
+
+        setJvmInfo();
+
+        setSysFiles(si.getOperatingSystem());
+    }
+
+    /**
+     * 设置CPU信息
+     */
+    private void setCpuInfo(CentralProcessor processor)
+    {
+        // CPU信息
+        long[] prevTicks = processor.getSystemCpuLoadTicks();
+        Util.sleep(OSHI_WAIT_SECOND);
+        long[] ticks = processor.getSystemCpuLoadTicks();
+        long nice = ticks[TickType.NICE.getIndex()] - prevTicks[TickType.NICE.getIndex()];
+        long irq = ticks[TickType.IRQ.getIndex()] - prevTicks[TickType.IRQ.getIndex()];
+        long softirq = ticks[TickType.SOFTIRQ.getIndex()] - prevTicks[TickType.SOFTIRQ.getIndex()];
+        long steal = ticks[TickType.STEAL.getIndex()] - prevTicks[TickType.STEAL.getIndex()];
+        long cSys = ticks[TickType.SYSTEM.getIndex()] - prevTicks[TickType.SYSTEM.getIndex()];
+        long user = ticks[TickType.USER.getIndex()] - prevTicks[TickType.USER.getIndex()];
+        long iowait = ticks[TickType.IOWAIT.getIndex()] - prevTicks[TickType.IOWAIT.getIndex()];
+        long idle = ticks[TickType.IDLE.getIndex()] - prevTicks[TickType.IDLE.getIndex()];
+        long totalCpu = user + nice + cSys + idle + iowait + irq + softirq + steal;
+        cpu.setCpuNum(processor.getLogicalProcessorCount());
+        cpu.setTotal(totalCpu);
+        cpu.setSys(cSys);
+        cpu.setUsed(user);
+        cpu.setWait(iowait);
+        cpu.setFree(idle);
+    }
+
+    /**
+     * 设置内存信息
+     */
+    private void setMemInfo(GlobalMemory memory)
+    {
+        mem.setTotal(memory.getTotal());
+        mem.setUsed(memory.getTotal() - memory.getAvailable());
+        mem.setFree(memory.getAvailable());
+    }
+
+    /**
+     * 设置服务器信息
+     */
+    private void setSysInfo()
+    {
+        Properties props = System.getProperties();
+        sys.setComputerName(IpUtils.getHostName());
+        sys.setComputerIp(IpUtils.getHostIp());
+        sys.setOsName(props.getProperty("os.name"));
+        sys.setOsArch(props.getProperty("os.arch"));
+        sys.setUserDir(props.getProperty("user.dir"));
+    }
+
+    /**
+     * 设置Java虚拟机
+     */
+    private void setJvmInfo() throws UnknownHostException
+    {
+        Properties props = System.getProperties();
+        jvm.setTotal(Runtime.getRuntime().totalMemory());
+        jvm.setMax(Runtime.getRuntime().maxMemory());
+        jvm.setFree(Runtime.getRuntime().freeMemory());
+        jvm.setVersion(props.getProperty("java.version"));
+        jvm.setHome(props.getProperty("java.home"));
+    }
+
+    /**
+     * 设置磁盘信息
+     */
+    private void setSysFiles(OperatingSystem os)
+    {
+        FileSystem fileSystem = os.getFileSystem();
+        List<OSFileStore> fsArray = fileSystem.getFileStores();
+        for (OSFileStore fs : fsArray)
+        {
+            long free = fs.getUsableSpace();
+            long total = fs.getTotalSpace();
+            long used = total - free;
+            SysFile sysFile = new SysFile();
+            sysFile.setDirName(fs.getMount());
+            sysFile.setSysTypeName(fs.getType());
+            sysFile.setTypeName(fs.getName());
+            sysFile.setTotal(convertFileSize(total));
+            sysFile.setFree(convertFileSize(free));
+            sysFile.setUsed(convertFileSize(used));
+            sysFile.setUsage(Arith.mul(Arith.div(used, total, 4), 100));
+            sysFiles.add(sysFile);
+        }
+    }
+
+    /**
+     * 字节转换
+     * 
+     * @param size 字节大小
+     * @return 转换后值
+     */
+    public String convertFileSize(long size)
+    {
+        long kb = 1024;
+        long mb = kb * 1024;
+        long gb = mb * 1024;
+        if (size >= gb)
+        {
+            return String.format("%.1f GB", (float) size / gb);
+        }
+        else if (size >= mb)
+        {
+            float f = (float) size / mb;
+            return String.format(f > 100 ? "%.0f MB" : "%.1f MB", f);
+        }
+        else if (size >= kb)
+        {
+            float f = (float) size / kb;
+            return String.format(f > 100 ? "%.0f KB" : "%.1f KB", f);
+        }
+        else
+        {
+            return String.format("%d B", size);
+        }
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/web/domain/server/Cpu.java

@@ -0,0 +1,101 @@
+package net.hzvtc.framework.web.domain.server;
+
+import net.hzvtc.common.utils.Arith;
+
+/**
+ * CPU相关信息
+ * 
+ * @author admin
+ */
+public class Cpu
+{
+    /**
+     * 核心数
+     */
+    private int cpuNum;
+
+    /**
+     * CPU总的使用率
+     */
+    private double total;
+
+    /**
+     * CPU系统使用率
+     */
+    private double sys;
+
+    /**
+     * CPU用户使用率
+     */
+    private double used;
+
+    /**
+     * CPU当前等待率
+     */
+    private double wait;
+
+    /**
+     * CPU当前空闲率
+     */
+    private double free;
+
+    public int getCpuNum()
+    {
+        return cpuNum;
+    }
+
+    public void setCpuNum(int cpuNum)
+    {
+        this.cpuNum = cpuNum;
+    }
+
+    public double getTotal()
+    {
+        return Arith.round(Arith.mul(total, 100), 2);
+    }
+
+    public void setTotal(double total)
+    {
+        this.total = total;
+    }
+
+    public double getSys()
+    {
+        return Arith.round(Arith.mul(sys / total, 100), 2);
+    }
+
+    public void setSys(double sys)
+    {
+        this.sys = sys;
+    }
+
+    public double getUsed()
+    {
+        return Arith.round(Arith.mul(used / total, 100), 2);
+    }
+
+    public void setUsed(double used)
+    {
+        this.used = used;
+    }
+
+    public double getWait()
+    {
+        return Arith.round(Arith.mul(wait / total, 100), 2);
+    }
+
+    public void setWait(double wait)
+    {
+        this.wait = wait;
+    }
+
+    public double getFree()
+    {
+        return Arith.round(Arith.mul(free / total, 100), 2);
+    }
+
+    public void setFree(double free)
+    {
+        this.free = free;
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/web/domain/server/Jvm.java

@@ -0,0 +1,122 @@
+package net.hzvtc.framework.web.domain.server;
+
+import java.lang.management.ManagementFactory;
+import net.hzvtc.common.utils.Arith;
+import net.hzvtc.common.utils.DateUtils;
+
+/**
+ * JVM相关信息
+ * 
+ * @author admin
+ */
+public class Jvm
+{
+    /**
+     * 当前JVM占用的内存总数(M)
+     */
+    private double total;
+
+    /**
+     * JVM最大可用内存总数(M)
+     */
+    private double max;
+
+    /**
+     * JVM空闲内存(M)
+     */
+    private double free;
+
+    /**
+     * JDK版本
+     */
+    private String version;
+
+    /**
+     * JDK路径
+     */
+    private String home;
+
+    public double getTotal()
+    {
+        return Arith.div(total, (1024 * 1024), 2);
+    }
+
+    public void setTotal(double total)
+    {
+        this.total = total;
+    }
+
+    public double getMax()
+    {
+        return Arith.div(max, (1024 * 1024), 2);
+    }
+
+    public void setMax(double max)
+    {
+        this.max = max;
+    }
+
+    public double getFree()
+    {
+        return Arith.div(free, (1024 * 1024), 2);
+    }
+
+    public void setFree(double free)
+    {
+        this.free = free;
+    }
+
+    public double getUsed()
+    {
+        return Arith.div(total - free, (1024 * 1024), 2);
+    }
+
+    public double getUsage()
+    {
+        return Arith.mul(Arith.div(total - free, total, 4), 100);
+    }
+
+    /**
+     * 获取JDK名称
+     */
+    public String getName()
+    {
+        return ManagementFactory.getRuntimeMXBean().getVmName();
+    }
+
+    public String getVersion()
+    {
+        return version;
+    }
+
+    public void setVersion(String version)
+    {
+        this.version = version;
+    }
+
+    public String getHome()
+    {
+        return home;
+    }
+
+    public void setHome(String home)
+    {
+        this.home = home;
+    }
+
+    /**
+     * JDK启动时间
+     */
+    public String getStartTime()
+    {
+        return DateUtils.parseDateToStr(DateUtils.YYYY_MM_DD_HH_MM_SS, DateUtils.getServerStartDate());
+    }
+
+    /**
+     * JDK运行时间
+     */
+    public String getRunTime()
+    {
+        return DateUtils.getDatePoor(DateUtils.getNowDate(), DateUtils.getServerStartDate());
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/web/domain/server/Mem.java

@@ -0,0 +1,61 @@
+package net.hzvtc.framework.web.domain.server;
+
+import net.hzvtc.common.utils.Arith;
+
+/**
+ * 內存相关信息
+ * 
+ * @author admin
+ */
+public class Mem
+{
+    /**
+     * 内存总量
+     */
+    private double total;
+
+    /**
+     * 已用内存
+     */
+    private double used;
+
+    /**
+     * 剩余内存
+     */
+    private double free;
+
+    public double getTotal()
+    {
+        return Arith.div(total, (1024 * 1024 * 1024), 2);
+    }
+
+    public void setTotal(long total)
+    {
+        this.total = total;
+    }
+
+    public double getUsed()
+    {
+        return Arith.div(used, (1024 * 1024 * 1024), 2);
+    }
+
+    public void setUsed(long used)
+    {
+        this.used = used;
+    }
+
+    public double getFree()
+    {
+        return Arith.div(free, (1024 * 1024 * 1024), 2);
+    }
+
+    public void setFree(long free)
+    {
+        this.free = free;
+    }
+
+    public double getUsage()
+    {
+        return Arith.mul(Arith.div(used, total, 4), 100);
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/web/domain/server/Sys.java

@@ -0,0 +1,84 @@
+package net.hzvtc.framework.web.domain.server;
+
+/**
+ * 系统相关信息
+ * 
+ * @author admin
+ */
+public class Sys
+{
+    /**
+     * 服务器名称
+     */
+    private String computerName;
+
+    /**
+     * 服务器Ip
+     */
+    private String computerIp;
+
+    /**
+     * 项目路径
+     */
+    private String userDir;
+
+    /**
+     * 操作系统
+     */
+    private String osName;
+
+    /**
+     * 系统架构
+     */
+    private String osArch;
+
+    public String getComputerName()
+    {
+        return computerName;
+    }
+
+    public void setComputerName(String computerName)
+    {
+        this.computerName = computerName;
+    }
+
+    public String getComputerIp()
+    {
+        return computerIp;
+    }
+
+    public void setComputerIp(String computerIp)
+    {
+        this.computerIp = computerIp;
+    }
+
+    public String getUserDir()
+    {
+        return userDir;
+    }
+
+    public void setUserDir(String userDir)
+    {
+        this.userDir = userDir;
+    }
+
+    public String getOsName()
+    {
+        return osName;
+    }
+
+    public void setOsName(String osName)
+    {
+        this.osName = osName;
+    }
+
+    public String getOsArch()
+    {
+        return osArch;
+    }
+
+    public void setOsArch(String osArch)
+    {
+        this.osArch = osArch;
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/web/domain/server/SysFile.java

@@ -0,0 +1,114 @@
+package net.hzvtc.framework.web.domain.server;
+
+/**
+ * 系统文件相关信息
+ * 
+ * @author admin
+ */
+public class SysFile
+{
+    /**
+     * 盘符路径
+     */
+    private String dirName;
+
+    /**
+     * 盘符类型
+     */
+    private String sysTypeName;
+
+    /**
+     * 文件类型
+     */
+    private String typeName;
+
+    /**
+     * 总大小
+     */
+    private String total;
+
+    /**
+     * 剩余大小
+     */
+    private String free;
+
+    /**
+     * 已经使用量
+     */
+    private String used;
+
+    /**
+     * 资源的使用率
+     */
+    private double usage;
+
+    public String getDirName()
+    {
+        return dirName;
+    }
+
+    public void setDirName(String dirName)
+    {
+        this.dirName = dirName;
+    }
+
+    public String getSysTypeName()
+    {
+        return sysTypeName;
+    }
+
+    public void setSysTypeName(String sysTypeName)
+    {
+        this.sysTypeName = sysTypeName;
+    }
+
+    public String getTypeName()
+    {
+        return typeName;
+    }
+
+    public void setTypeName(String typeName)
+    {
+        this.typeName = typeName;
+    }
+
+    public String getTotal()
+    {
+        return total;
+    }
+
+    public void setTotal(String total)
+    {
+        this.total = total;
+    }
+
+    public String getFree()
+    {
+        return free;
+    }
+
+    public void setFree(String free)
+    {
+        this.free = free;
+    }
+
+    public String getUsed()
+    {
+        return used;
+    }
+
+    public void setUsed(String used)
+    {
+        this.used = used;
+    }
+
+    public double getUsage()
+    {
+        return usage;
+    }
+
+    public void setUsage(double usage)
+    {
+        this.usage = usage;
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/web/exception/GlobalExceptionHandler.java

@@ -0,0 +1,106 @@
+package net.hzvtc.framework.web.exception;
+
+import net.hzvtc.common.constant.HttpStatus;
+import net.hzvtc.common.core.domain.AjaxResult;
+import net.hzvtc.common.exception.DemoModeException;
+import net.hzvtc.common.exception.ServiceException;
+import net.hzvtc.common.utils.StringUtils;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.security.access.AccessDeniedException;
+import org.springframework.validation.BindException;
+import org.springframework.web.HttpRequestMethodNotSupportedException;
+import org.springframework.web.bind.MethodArgumentNotValidException;
+import org.springframework.web.bind.annotation.ExceptionHandler;
+import org.springframework.web.bind.annotation.RestControllerAdvice;
+
+import javax.servlet.http.HttpServletRequest;
+
+/**
+ * 全局异常处理器
+ *
+ * @author admin
+ */
+@RestControllerAdvice
+public class GlobalExceptionHandler {
+    private static final Logger log = LoggerFactory.getLogger(GlobalExceptionHandler.class);
+
+    /**
+     * 权限校验异常
+     */
+    @ExceptionHandler(AccessDeniedException.class)
+    public AjaxResult handleAccessDeniedException(AccessDeniedException e, HttpServletRequest request) {
+        String requestURI = request.getRequestURI();
+        log.error("请求地址'{}',权限校验失败'{}'", requestURI, e.getMessage());
+        return AjaxResult.error(HttpStatus.FORBIDDEN, "没有权限，请联系管理员授权");
+    }
+
+    /**
+     * 请求方式不支持
+     */
+    @ExceptionHandler(HttpRequestMethodNotSupportedException.class)
+    public AjaxResult handleHttpRequestMethodNotSupported(HttpRequestMethodNotSupportedException e,
+                                                          HttpServletRequest request) {
+        String requestURI = request.getRequestURI();
+        log.error("请求地址'{}',不支持'{}'请求", requestURI, e.getMethod());
+        return AjaxResult.error(e.getMessage());
+    }
+
+    /**
+     * 业务异常
+     */
+    @ExceptionHandler(ServiceException.class)
+    public AjaxResult handleServiceException(ServiceException e, HttpServletRequest request) {
+        log.error(e.getMessage(), e);
+        Integer code = e.getCode();
+        return StringUtils.isNotNull(code) ? AjaxResult.error(code, e.getMessage()) : AjaxResult.error(e.getMessage());
+    }
+
+    /**
+     * 拦截未知的运行时异常
+     */
+    @ExceptionHandler(RuntimeException.class)
+    public AjaxResult handleRuntimeException(RuntimeException e, HttpServletRequest request) {
+        String requestURI = request.getRequestURI();
+        log.error("请求地址'{}',发生未知异常.", requestURI, e);
+        return AjaxResult.error(e.getMessage());
+    }
+
+    /**
+     * 系统异常
+     */
+    @ExceptionHandler(Exception.class)
+    public AjaxResult handleException(Exception e, HttpServletRequest request) {
+        String requestURI = request.getRequestURI();
+        log.error("请求地址'{}',发生系统异常.", requestURI, e);
+        return AjaxResult.error(e.getMessage());
+    }
+
+    /**
+     * 自定义验证异常
+     */
+    @ExceptionHandler(BindException.class)
+    public AjaxResult handleBindException(BindException e) {
+        log.error(e.getMessage(), e);
+        String message = e.getAllErrors().get(0).getDefaultMessage();
+        return AjaxResult.error(message);
+    }
+
+    /**
+     * 自定义验证异常
+     */
+    @ExceptionHandler(MethodArgumentNotValidException.class)
+    public Object handleMethodArgumentNotValidException(MethodArgumentNotValidException e) {
+        log.error(e.getMessage(), e);
+        String message = e.getBindingResult().getFieldError().getDefaultMessage();
+        return AjaxResult.error(message);
+    }
+
+    /**
+     * 演示模式异常
+     */
+    @ExceptionHandler(DemoModeException.class)
+    public AjaxResult handleDemoModeException(DemoModeException e) {
+        return AjaxResult.error("演示模式，不允许操作");
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/web/service/PermissionService.java

@@ -0,0 +1,166 @@
+package net.hzvtc.framework.web.service;
+
+import java.util.Set;
+
+import net.hzvtc.common.core.domain.entity.SysRole;
+import net.hzvtc.common.core.domain.model.LoginUser;
+import net.hzvtc.common.utils.SecurityUtils;
+import net.hzvtc.common.utils.StringUtils;
+import org.springframework.stereotype.Service;
+import org.springframework.util.CollectionUtils;
+
+/**
+ * 首创 自定义权限实现，ss取自SpringSecurity首字母
+ * 
+ * @author admin
+ */
+@Service("ss")
+public class PermissionService
+{
+    /** 所有权限标识 */
+    private static final String ALL_PERMISSION = "*:*:*";
+
+    /** 管理员角色权限标识 */
+    private static final String SUPER_ADMIN = "admin";
+
+    private static final String ROLE_DELIMETER = ",";
+
+    private static final String PERMISSION_DELIMETER = ",";
+
+    /**
+     * 验证用户是否具备某权限
+     * 
+     * @param permission 权限字符串
+     * @return 用户是否具备某权限
+     */
+    public boolean hasPermi(String permission)
+    {
+        if (StringUtils.isEmpty(permission))
+        {
+            return false;
+        }
+        LoginUser loginUser = SecurityUtils.getLoginUser();
+        if (StringUtils.isNull(loginUser) || CollectionUtils.isEmpty(loginUser.getPermissions()))
+        {
+            return false;
+        }
+        return hasPermissions(loginUser.getPermissions(), permission);
+    }
+
+    /**
+     * 验证用户是否不具备某权限，与 hasPermi逻辑相反
+     *
+     * @param permission 权限字符串
+     * @return 用户是否不具备某权限
+     */
+    public boolean lacksPermi(String permission)
+    {
+        return hasPermi(permission) != true;
+    }
+
+    /**
+     * 验证用户是否具有以下任意一个权限
+     *
+     * @param permissions 以 PERMISSION_NAMES_DELIMETER 为分隔符的权限列表
+     * @return 用户是否具有以下任意一个权限
+     */
+    public boolean hasAnyPermi(String permissions)
+    {
+        if (StringUtils.isEmpty(permissions))
+        {
+            return false;
+        }
+        LoginUser loginUser = SecurityUtils.getLoginUser();
+        if (StringUtils.isNull(loginUser) || CollectionUtils.isEmpty(loginUser.getPermissions()))
+        {
+            return false;
+        }
+        Set<String> authorities = loginUser.getPermissions();
+        for (String permission : permissions.split(PERMISSION_DELIMETER))
+        {
+            if (permission != null && hasPermissions(authorities, permission))
+            {
+                return true;
+            }
+        }
+        return false;
+    }
+
+    /**
+     * 判断用户是否拥有某个角色
+     * 
+     * @param role 角色字符串
+     * @return 用户是否具备某角色
+     */
+    public boolean hasRole(String role)
+    {
+        if (StringUtils.isEmpty(role))
+        {
+            return false;
+        }
+        LoginUser loginUser = SecurityUtils.getLoginUser();
+        if (StringUtils.isNull(loginUser) || CollectionUtils.isEmpty(loginUser.getUser().getRoles()))
+        {
+            return false;
+        }
+        for (SysRole sysRole : loginUser.getUser().getRoles())
+        {
+            String roleKey = sysRole.getRoleKey();
+            if (SUPER_ADMIN.equals(roleKey) || roleKey.equals(StringUtils.trim(role)))
+            {
+                return true;
+            }
+        }
+        return false;
+    }
+
+    /**
+     * 验证用户是否不具备某角色，与 isRole逻辑相反。
+     *
+     * @param role 角色名称
+     * @return 用户是否不具备某角色
+     */
+    public boolean lacksRole(String role)
+    {
+        return hasRole(role) != true;
+    }
+
+    /**
+     * 验证用户是否具有以下任意一个角色
+     *
+     * @param roles 以 ROLE_NAMES_DELIMETER 为分隔符的角色列表
+     * @return 用户是否具有以下任意一个角色
+     */
+    public boolean hasAnyRoles(String roles)
+    {
+        if (StringUtils.isEmpty(roles))
+        {
+            return false;
+        }
+        LoginUser loginUser = SecurityUtils.getLoginUser();
+        if (StringUtils.isNull(loginUser) || CollectionUtils.isEmpty(loginUser.getUser().getRoles()))
+        {
+            return false;
+        }
+        for (String role : roles.split(ROLE_DELIMETER))
+        {
+            if (hasRole(role))
+            {
+                return true;
+            }
+        }
+        return false;
+    }
+
+    /**
+     * 判断是否包含权限
+     * 
+     * @param permissions 权限列表
+     * @param permission 权限字符串
+     * @return 用户是否具备某权限
+     */
+    private boolean hasPermissions(Set<String> permissions, String permission)
+    {
+        return permissions.contains(ALL_PERMISSION) || permissions.contains(StringUtils.trim(permission));
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/web/service/SysLoginService.java

@@ -0,0 +1,186 @@
+package net.hzvtc.framework.web.service;
+
+import net.hzvtc.common.constant.Constants;
+import net.hzvtc.common.core.domain.AjaxResult;
+import net.hzvtc.common.core.domain.entity.SysUser;
+import net.hzvtc.common.core.domain.model.LoginUser;
+import net.hzvtc.common.core.redis.RedisCache;
+import net.hzvtc.common.exception.ServiceException;
+import net.hzvtc.common.exception.user.CaptchaException;
+import net.hzvtc.common.exception.user.CaptchaExpireException;
+import net.hzvtc.common.exception.user.UserPasswordNotMatchException;
+import net.hzvtc.common.utils.DateUtils;
+import net.hzvtc.common.utils.MessageUtils;
+import net.hzvtc.common.utils.SecurityUtils;
+import net.hzvtc.common.utils.ServletUtils;
+import net.hzvtc.common.utils.ip.IpUtils;
+import net.hzvtc.email.service.EmailService;
+import net.hzvtc.framework.manager.AsyncManager;
+import net.hzvtc.framework.manager.factory.AsyncFactory;
+import net.hzvtc.system.service.SysConfigService;
+import net.hzvtc.system.service.SysUserService;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.security.authentication.AuthenticationManager;
+import org.springframework.security.authentication.BadCredentialsException;
+import org.springframework.security.authentication.UsernamePasswordAuthenticationToken;
+import org.springframework.security.core.Authentication;
+import org.springframework.stereotype.Component;
+
+import javax.annotation.Resource;
+import java.util.Random;
+
+/**
+ * 登录校验方法
+ *
+ * @author admin
+ */
+@Component
+public class SysLoginService {
+    @Autowired
+    private TokenService tokenService;
+
+    @Resource
+    private AuthenticationManager authenticationManager;
+
+    @Autowired
+    private RedisCache redisCache;
+
+    @Autowired
+    private SysUserService userService;
+
+    @Autowired
+    private SysConfigService configService;
+
+    @Autowired
+    private EmailService emailService;
+
+    /**
+     * 登录验证
+     *
+     * @param username 用户名
+     * @param password 密码
+     * @param code     验证码
+     * @param uuid     唯一标识
+     * @return 结果
+     */
+    public String login(String username, String password, String code, String uuid, int loginType) {
+        //sso 指定用户登录
+//        if (loginType == 3) {
+//            username = "ssoLoginUser";
+//            password = "ssoLoginUser_123";
+//        } else {
+//            boolean captchaOnOff = configService.selectCaptchaOnOff();
+//            // 验证码开关
+//            if (captchaOnOff && loginType == 0) {
+//                validateCaptcha(username, code, uuid);
+//            }
+//        }
+        boolean captchaOnOff = configService.selectCaptchaOnOff();
+        // 验证码开关
+        if (captchaOnOff && (loginType == 0 || loginType == 2)) {
+            validateCaptcha(username, code, uuid);
+        }
+        // 用户验证
+        Authentication authentication = null;
+        try {
+            // 该方法会去调用UserDetailsServiceImpl.loadUserByUsername
+            authentication = authenticationManager.authenticate(new UsernamePasswordAuthenticationToken(username, password));
+        } catch (Exception e) {
+            if (e instanceof BadCredentialsException) {
+                AsyncManager.me().execute(AsyncFactory.recordLogininfor(username, Constants.LOGIN_FAIL, MessageUtils.message("user.password.not.match")));
+                throw new UserPasswordNotMatchException();
+            } else {
+                AsyncManager.me().execute(AsyncFactory.recordLogininfor(username, Constants.LOGIN_FAIL, e.getMessage()));
+                throw new ServiceException(e.getMessage());
+            }
+        }
+        LoginUser loginUser = (LoginUser) authentication.getPrincipal();
+//        if (loginType == 0) {
+//            if (loginUser.getPortalLogin() != 1) {
+//                AsyncManager.me().execute(AsyncFactory.recordLogininfor(username, Constants.LOGIN_FAIL, MessageUtils.message("no.portal.login")));
+//                throw new UserNoLoginPermissionException();
+//            }
+//        } else if (loginType == 1) {
+//            if (loginUser.getWebLogin() != 1) {
+//                AsyncManager.me().execute(AsyncFactory.recordLogininfor(username, Constants.LOGIN_FAIL, MessageUtils.message("no.web.login")));
+//                throw new UserNoLoginPermissionException();
+//            }
+//        }
+
+        AsyncManager.me().execute(AsyncFactory.recordLogininfor(username, Constants.LOGIN_SUCCESS, MessageUtils.message("user.login.success")));
+
+        recordLoginInfo(loginUser.getUserId());
+        // 生成token
+        return tokenService.createToken(loginUser);
+    }
+
+    /**
+     * 校验验证码
+     *
+     * @param username 用户名
+     * @param code     验证码
+     * @param uuid     唯一标识
+     * @return 结果
+     */
+    public void validateCaptcha(String username, String code, String uuid) {
+        String verifyKey = Constants.CAPTCHA_CODE_KEY + uuid;
+        String captcha = redisCache.getCacheObject(verifyKey);
+        redisCache.deleteObject(verifyKey);
+        if (captcha == null) {
+            AsyncManager.me().execute(AsyncFactory.recordLogininfor(username, Constants.LOGIN_FAIL, MessageUtils.message("user.jcaptcha.expire")));
+            throw new CaptchaExpireException();
+        }
+        if (!code.equalsIgnoreCase(captcha)) {
+            AsyncManager.me().execute(AsyncFactory.recordLogininfor(username, Constants.LOGIN_FAIL, MessageUtils.message("user.jcaptcha.error")));
+            throw new CaptchaException();
+        }
+    }
+
+    /**
+     * 记录登录信息
+     *
+     * @param userId 用户ID
+     */
+    public void recordLoginInfo(Long userId) {
+        SysUser sysUser = new SysUser();
+        sysUser.setUserId(userId);
+        sysUser.setLoginIp(IpUtils.getIpAddr(ServletUtils.getRequest()));
+        sysUser.setLoginDate(DateUtils.getNowDate());
+        userService.updateUserProfile(sysUser);
+    }
+
+    public AjaxResult resetPasswordByName(String loginId) {
+        SysUser user = userService.selectUserByUserName(loginId);
+        if (user == null) {
+            return AjaxResult.error(500, "帐号不存在");
+        } else if (user.getEmail() == null || user.getEmail().isEmpty()) {
+            return AjaxResult.error(500, "此帐号电子邮箱为空");
+        }
+        String passwd = genRandomNum();
+        userService.resetUserPwd(loginId, SecurityUtils.encryptPassword(passwd));
+        emailService.sendSimpleEmail("密码重置", "你的密码已经重置为：" + passwd + "，请及时修改！", user.getEmail());
+        return AjaxResult.success("密码已重置！");
+    }
+
+
+    private String genRandomNum() {
+        int maxNum = 36;
+        int i;
+        int count = 0;
+        char[] str = {'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K',
+                'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W',
+                'X', 'Y', 'Z', '0', '1', '2', '3', '4', '5', '6', '7', '8', '9'};
+        StringBuffer pwd = new StringBuffer("");
+        Random r = new Random();
+        while (count < 8) {
+            i = Math.abs(r.nextInt(maxNum));
+            if (i >= 0 && i < str.length) {
+                pwd.append(str[i]);
+                count++;
+            }
+        }
+        return pwd.toString();
+    }
+
+
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/web/service/SysPermissionService.java

@@ -0,0 +1,62 @@
+package net.hzvtc.framework.web.service;
+
+import net.hzvtc.common.core.domain.entity.SysRole;
+import net.hzvtc.common.core.domain.entity.SysUser;
+import net.hzvtc.system.service.SysMenuService;
+import net.hzvtc.system.service.SysRoleService;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.stereotype.Component;
+
+import java.util.HashSet;
+import java.util.Set;
+
+/**
+ * 用户权限处理
+ *
+ * @author admin
+ */
+@Component
+public class SysPermissionService {
+    @Autowired
+    private SysRoleService roleService;
+
+    @Autowired
+    private SysMenuService menuService;
+
+    /**
+     * 获取角色数据权限
+     *
+     * @param user 用户信息
+     * @return 角色权限信息
+     */
+    public Set<String> getRolePermission(SysUser user) {
+        Set<String> roles = new HashSet<String>();
+        // 管理员拥有所有权限
+        if (user.isAdmin()) {
+            roles.add("admin");
+        } else {
+            SysRole sysRole = new SysRole();
+            sysRole.setUserId(user.getUserId());
+            sysRole.setSysId(user.getSysId());
+            roles.addAll(roleService.selectRolePermissionByUserId(sysRole));
+        }
+        return roles;
+    }
+
+    /**
+     * 获取菜单数据权限
+     *
+     * @param user 用户信息
+     * @return 菜单权限信息
+     */
+    public Set<String> getMenuPermission(SysUser user) {
+        Set<String> perms = new HashSet<String>();
+        // 管理员拥有所有权限
+        if (user.isAdmin()) {
+            perms.add("*:*:*");
+        } else {
+            perms.addAll(menuService.selectMenuPermsByUserId(user.getUserId()));
+        }
+        return perms;
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/web/service/SysRegisterService.java

@@ -0,0 +1,95 @@
+package net.hzvtc.framework.web.service;
+
+import net.hzvtc.common.constant.Constants;
+import net.hzvtc.common.constant.UserConstants;
+import net.hzvtc.common.core.domain.entity.SysUser;
+import net.hzvtc.common.core.domain.model.RegisterBody;
+import net.hzvtc.common.core.redis.RedisCache;
+import net.hzvtc.common.exception.user.CaptchaException;
+import net.hzvtc.common.exception.user.CaptchaExpireException;
+import net.hzvtc.common.utils.MessageUtils;
+import net.hzvtc.common.utils.SecurityUtils;
+import net.hzvtc.common.utils.StringUtils;
+import net.hzvtc.framework.manager.AsyncManager;
+import net.hzvtc.framework.manager.factory.AsyncFactory;
+import net.hzvtc.system.service.SysConfigService;
+import net.hzvtc.system.service.SysUserService;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.stereotype.Component;
+
+/**
+ * 注册校验方法
+ *
+ * @author admin
+ */
+@Component
+public class SysRegisterService {
+    @Autowired
+    private SysUserService userService;
+
+    @Autowired
+    private SysConfigService configService;
+
+    @Autowired
+    private RedisCache redisCache;
+
+    /**
+     * 注册
+     */
+    public String register(RegisterBody registerBody) {
+        String msg = "", username = registerBody.getUsername(), password = registerBody.getPassword();
+
+        boolean captchaOnOff = configService.selectCaptchaOnOff();
+        // 验证码开关
+        if (captchaOnOff) {
+            validateCaptcha(username, registerBody.getCode(), registerBody.getUuid());
+        }
+
+        if (StringUtils.isEmpty(username)) {
+            msg = "用户名不能为空";
+        } else if (StringUtils.isEmpty(password)) {
+            msg = "用户密码不能为空";
+        } else if (username.length() < UserConstants.USERNAME_MIN_LENGTH
+                || username.length() > UserConstants.USERNAME_MAX_LENGTH) {
+            msg = "账户长度必须在2到20个字符之间";
+        } else if (password.length() < UserConstants.PASSWORD_MIN_LENGTH
+                || password.length() > UserConstants.PASSWORD_MAX_LENGTH) {
+            msg = "密码长度必须在5到20个字符之间";
+        } else if (UserConstants.NOT_UNIQUE.equals(userService.checkUserNameUnique(username))) {
+            msg = "保存用户'" + username + "'失败，注册账号已存在";
+        } else {
+            SysUser sysUser = new SysUser();
+            sysUser.setUserName(username);
+            sysUser.setNickName(username);
+            sysUser.setPassword(SecurityUtils.encryptPassword(registerBody.getPassword()));
+            boolean regFlag = userService.registerUser(sysUser);
+            if (!regFlag) {
+                msg = "注册失败,请联系系统管理人员";
+            } else {
+                AsyncManager.me().execute(AsyncFactory.recordLogininfor(username, Constants.REGISTER,
+                        MessageUtils.message("user.register.success")));
+            }
+        }
+        return msg;
+    }
+
+    /**
+     * 校验验证码
+     *
+     * @param username 用户名
+     * @param code     验证码
+     * @param uuid     唯一标识
+     * @return 结果
+     */
+    public void validateCaptcha(String username, String code, String uuid) {
+        String verifyKey = Constants.CAPTCHA_CODE_KEY + uuid;
+        String captcha = redisCache.getCacheObject(verifyKey);
+        redisCache.deleteObject(verifyKey);
+        if (captcha == null) {
+            throw new CaptchaExpireException();
+        }
+        if (!code.equalsIgnoreCase(captcha)) {
+            throw new CaptchaException();
+        }
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/web/service/TokenService.java

@@ -0,0 +1,208 @@
+package net.hzvtc.framework.web.service;
+
+import eu.bitwalker.useragentutils.UserAgent;
+import io.jsonwebtoken.Claims;
+import io.jsonwebtoken.Jwts;
+import io.jsonwebtoken.security.Keys;
+import net.hzvtc.common.constant.Constants;
+import net.hzvtc.common.core.domain.model.LoginUser;
+import net.hzvtc.common.core.redis.RedisCache;
+import net.hzvtc.common.utils.ServletUtils;
+import net.hzvtc.common.utils.StringUtils;
+import net.hzvtc.common.utils.ip.AddressUtils;
+import net.hzvtc.common.utils.ip.IpUtils;
+import net.hzvtc.common.utils.uuid.IdUtils;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.beans.factory.annotation.Value;
+import org.springframework.stereotype.Component;
+
+import javax.crypto.SecretKey;
+import javax.servlet.http.HttpServletRequest;
+import java.util.HashMap;
+import java.util.Map;
+import java.util.concurrent.TimeUnit;
+
+/**
+ * token验证处理
+ *
+ * @author admin
+ */
+@Component
+public class TokenService {
+    protected static final long MILLIS_SECOND = 1000;
+    protected static final long MILLIS_MINUTE = 60 * MILLIS_SECOND;
+    private static final Long MILLIS_MINUTE_TEN = 20 * 60 * 1000L;
+    // 令牌自定义标识
+    @Value("${token.header}")
+    private String header;
+    // 令牌秘钥
+    @Value("${token.secret}")
+    private String secret;
+    // 令牌有效期（默认30分钟）
+    @Value("${token.expireTime}")
+    private int expireTime;
+    @Autowired
+    private RedisCache redisCache;
+
+    /**
+     * 获取用户身份信息
+     *
+     * @return 用户信息
+     */
+    public LoginUser getLoginUser(HttpServletRequest request) {
+        // 获取请求携带的令牌
+        String token = getToken(request);
+        if (StringUtils.isNotEmpty(token)) {
+            try {
+                Claims claims = parseToken(token);
+                // 解析对应的权限以及用户信息
+                String uuid = (String) claims.get(Constants.LOGIN_USER_KEY);
+                String userKey = getTokenKey(uuid);
+                LoginUser user = redisCache.getCacheObject(userKey);
+                return user;
+            } catch (Exception e) {
+            }
+        }
+        return null;
+    }
+
+    /**
+     * 设置用户身份信息
+     */
+    public void setLoginUser(LoginUser loginUser) {
+        if (StringUtils.isNotNull(loginUser) && StringUtils.isNotEmpty(loginUser.getToken())) {
+            refreshToken(loginUser);
+        }
+    }
+
+    /**
+     * 删除用户身份信息
+     */
+    public void delLoginUser(String token) {
+        if (StringUtils.isNotEmpty(token)) {
+            String userKey = getTokenKey(token);
+            redisCache.deleteObject(userKey);
+        }
+    }
+
+    /**
+     * 创建令牌
+     *
+     * @param loginUser 用户信息
+     * @return 令牌
+     */
+    public String createToken(LoginUser loginUser) {
+        String token = IdUtils.fastUUID();
+        loginUser.setToken(token);
+        setUserAgent(loginUser);
+        refreshToken(loginUser);
+
+        Map<String, Object> claims = new HashMap<>();
+        claims.put(Constants.LOGIN_USER_KEY, token);
+        return createToken(claims);
+    }
+
+    /**
+     * 验证令牌有效期，相差不足20分钟，自动刷新缓存
+     *
+     * @param loginUser
+     * @return 令牌
+     */
+    public void verifyToken(LoginUser loginUser) {
+        long expireTime = loginUser.getExpireTime();
+        long currentTime = System.currentTimeMillis();
+        if (expireTime - currentTime <= MILLIS_MINUTE_TEN) {
+            refreshToken(loginUser);
+        }
+    }
+
+    /**
+     * 刷新令牌有效期
+     *
+     * @param loginUser 登录信息
+     */
+    public void refreshToken(LoginUser loginUser) {
+        loginUser.setLoginTime(System.currentTimeMillis());
+        loginUser.setExpireTime(loginUser.getLoginTime() + expireTime * MILLIS_MINUTE);
+        // 根据uuid将loginUser缓存
+        String userKey = getTokenKey(loginUser.getToken());
+        redisCache.setCacheObject(userKey, loginUser, expireTime, TimeUnit.MINUTES);
+    }
+
+    /**
+     * 设置用户代理信息
+     *
+     * @param loginUser 登录信息
+     */
+    public void setUserAgent(LoginUser loginUser) {
+        UserAgent userAgent = UserAgent.parseUserAgentString(ServletUtils.getRequest().getHeader("User-Agent"));
+        String ip = IpUtils.getIpAddr(ServletUtils.getRequest());
+        loginUser.setIpaddr(ip);
+        loginUser.setLoginLocation(AddressUtils.getRealAddressByIP(ip));
+        loginUser.setBrowser(userAgent.getBrowser().getName());
+        loginUser.setOs(userAgent.getOperatingSystem().getName());
+    }
+
+    /**
+     * 从数据声明生成令牌
+     *
+     * @param claims 数据声明
+     * @return 令牌
+     */
+    private String createToken(Map<String, Object> claims) {
+//        String token = Jwts.builder()
+//                .setClaims(claims)
+//                .signWith(SignatureAlgorithm.HS512, secret).compact();
+        SecretKey key = Keys.hmacShaKeyFor(secret.getBytes());
+        String token = Jwts.builder().claims(claims).signWith(key, Jwts.SIG.HS512).compact();
+//                signWith(SignatureAlgorithm.HS512, secret).compact();
+        return token;
+    }
+
+    /**
+     * 从令牌中获取数据声明
+     *
+     * @param token 令牌
+     * @return 数据声明
+     */
+    private Claims parseToken(String token) {
+        SecretKey key = Keys.hmacShaKeyFor(secret.getBytes());
+        return Jwts.parser()
+                .verifyWith(key)
+                .build()
+                .parseSignedClaims(token).getPayload();
+//        return Jwts.parser()
+//                .setSigningKey(secret)
+//                .parseClaimsJws(token)
+//                .getBody();
+    }
+
+    /**
+     * 从令牌中获取用户名
+     *
+     * @param token 令牌
+     * @return 用户名
+     */
+    public String getUsernameFromToken(String token) {
+        Claims claims = parseToken(token);
+        return claims.getSubject();
+    }
+
+    /**
+     * 获取请求token
+     *
+     * @param request
+     * @return token
+     */
+    private String getToken(HttpServletRequest request) {
+        String token = request.getHeader(header);
+        if (StringUtils.isNotEmpty(token) && token.startsWith(Constants.TOKEN_PREFIX)) {
+            token = token.replace(Constants.TOKEN_PREFIX, "");
+        }
+        return token;
+    }
+
+    private String getTokenKey(String uuid) {
+        return Constants.LOGIN_TOKEN_KEY + uuid;
+    }
+}

ai-xuebao-framework/src/main/java/net/hzvtc/framework/web/service/UserDetailsServiceImpl.java

@@ -0,0 +1,75 @@
+package net.hzvtc.framework.web.service;
+
+import com.alibaba.fastjson.JSONObject;
+import net.hzvtc.area.service.ProtectedAreaService;
+import net.hzvtc.common.core.domain.entity.SysUser;
+import net.hzvtc.common.core.domain.model.LoginUser;
+import net.hzvtc.common.enums.UserStatus;
+import net.hzvtc.common.exception.ServiceException;
+import net.hzvtc.common.utils.StringUtils;
+import net.hzvtc.device.service.DeviceInfoService;
+import net.hzvtc.system.service.SysRoleService;
+import net.hzvtc.system.service.SysUserService;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.security.core.userdetails.UserDetails;
+import org.springframework.security.core.userdetails.UserDetailsService;
+import org.springframework.security.core.userdetails.UsernameNotFoundException;
+import org.springframework.stereotype.Service;
+
+import java.util.List;
+
+/**
+ * 用户验证处理
+ *
+ * @author admin
+ */
+@Service
+public class UserDetailsServiceImpl implements UserDetailsService {
+    private static final Logger log = LoggerFactory.getLogger(UserDetailsServiceImpl.class);
+
+    @Autowired
+    private SysUserService userService;
+
+    @Autowired
+    private SysPermissionService permissionService;
+
+    @Autowired
+    private SysRoleService sysRoleService;
+
+    @Autowired
+    private ProtectedAreaService protectedAreaService;
+
+    @Autowired
+    private DeviceInfoService deviceInfoService;
+
+    @Override
+    public UserDetails loadUserByUsername(String username) throws UsernameNotFoundException {
+        SysUser user = userService.selectUserByUserName(username);
+        if (StringUtils.isNull(user)) {
+            log.info("登录用户：{} 不存在.", username);
+            throw new ServiceException("登录用户：" + username + " 不存在");
+        } else if (UserStatus.DELETED.getCode().equals(user.getDelFlag())) {
+            log.info("登录用户：{} 已被删除.", username);
+            throw new ServiceException("对不起，您的账号：" + username + " 已被删除");
+        } else if (UserStatus.DISABLE.getCode().equals(user.getStatus())) {
+            log.info("登录用户：{} 已被停用.", username);
+            throw new ServiceException("对不起，您的账号：" + username + " 已停用");
+        }
+        return createLoginUser(user);
+    }
+
+    public UserDetails createLoginUser(SysUser user) {
+//        List<JSONObject> areaList = protectedAreaService.getAreaListByUserId(user.getUserId());
+//        Long userId = null;
+//        if(user.getDeptId()==1L){
+//            userId = 0L;
+//        }else{
+//            userId = user.getUserId();
+//        }
+//        List<JSONObject> deviceList = deviceInfoService.getDeviceInfoListByUserId(userId);
+        return new LoginUser(user.getUserId(), user.getDeptId(), user, permissionService.getMenuPermission(user),
+                user.getWebLogin(), user.getPortalLogin());
+    }
+}