diff --git a/pom.xml b/pom.xml
index bd2e0bf..5563467 100644
--- a/pom.xml
+++ b/pom.xml
@@ -369,17 +369,35 @@
<groupId>com.aspose</groupId>
<artifactId>aspose-words</artifactId>
<version>18.10</version>
+ <scope>system</scope>
+ <systemPath>${project.basedir}/src/main/resources/lib/aspose-words-18.10-jdk16.jar</systemPath>
</dependency>
<dependency>
<groupId>com.aspose</groupId>
<artifactId>aspose-pdf</artifactId>
<version>18.2</version>
+ <scope>system</scope>
+ <systemPath>${project.basedir}/src/main/resources/lib/aspose-pdf-18.2.jar</systemPath>
</dependency>
<dependency>
<groupId>com.aspose</groupId>
<artifactId>aspose-cells</artifactId>
<version>20.7</version>
+ <scope>system</scope>
+ <systemPath>${project.basedir}/src/main/resources/lib/aspose-cells-20.7-crack.jar</systemPath>
</dependency>
+ <dependency>
+ <groupId>org.springframework</groupId>
+ <artifactId>spring-web</artifactId>
+ </dependency>
+
+
+ <!-- <dependency>-->
+<!-- <groupId>com.aspose</groupId>-->
+<!-- <artifactId>aspose-words</artifactId>-->
+<!-- <version>18.10</version>-->
+<!-- <scope>compile</scope>-->
+<!-- </dependency>-->
</dependencies>
diff --git a/src/main/java/com/sztzjy/marketing/config/ThreadPoolConfig.java b/src/main/java/com/sztzjy/marketing/config/ThreadPoolConfig.java
index a50da6b..379ed41 100644
--- a/src/main/java/com/sztzjy/marketing/config/ThreadPoolConfig.java
+++ b/src/main/java/com/sztzjy/marketing/config/ThreadPoolConfig.java
@@ -2,11 +2,8 @@ package com.sztzjy.marketing.config;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
-import org.springframework.scheduling.annotation.AsyncConfigurer;
-import org.springframework.scheduling.annotation.EnableAsync;
import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor;
-import java.util.concurrent.Executor;
import java.util.concurrent.ThreadPoolExecutor;
@Configuration
@@ -34,11 +31,11 @@ public class ThreadPoolConfig {
threadPool.setCorePoolSize(corePoolSize);
threadPool.setMaxPoolSize(maxPoolSize);
threadPool.setQueueCapacity(queueSize);
- threadPool.setThreadNamePrefix("testThreadPool-");
+ threadPool.setThreadNamePrefix("selfThreadPool-");
threadPool.setKeepAliveSeconds(keepAliveSeconds);
threadPool.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
//如果@Bean 就不需手动，会自动InitializingBean的afterPropertiesSet来调initialize
- // threadPool.initialize();
+ //threadPool.initialize();
return threadPool;
}
diff --git a/src/main/java/com/sztzjy/marketing/controller/stu/StuPythonController.java b/src/main/java/com/sztzjy/marketing/controller/stu/StuPythonController.java
index b33edc4..9818e35 100644
--- a/src/main/java/com/sztzjy/marketing/controller/stu/StuPythonController.java
+++ b/src/main/java/com/sztzjy/marketing/controller/stu/StuPythonController.java
@@ -2,15 +2,15 @@ package com.sztzjy.marketing.controller.stu;
import cn.hutool.core.util.IdUtil;
import com.alibaba.fastjson.JSON;
-import com.alibaba.fastjson.JSONArray;
import com.alibaba.fastjson.JSONObject;
import com.sztzjy.marketing.annotation.AnonymousAccess;
import com.sztzjy.marketing.entity.dto.CommentDTO;
+import com.sztzjy.marketing.entity.dto.NewDescriptiveStatisticsDTO;
import com.sztzjy.marketing.entity.dto.SentimentAnalyDTO;
-import com.sztzjy.marketing.qianfan.util.Json;
import com.sztzjy.marketing.util.ResultEntity;
import io.swagger.annotations.Api;
import io.swagger.annotations.ApiOperation;
+import io.swagger.annotations.ApiParam;
import org.springframework.http.HttpStatus;
import org.springframework.web.bind.annotation.PostMapping;
import org.springframework.web.bind.annotation.RequestBody;
@@ -18,7 +18,10 @@ import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;
import java.io.*;
-import java.util.*;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.List;
+import java.util.Map;
@RestController
@@ -371,5 +374,198 @@ public class StuPythonController {
return new ResultEntity<>(HttpStatus.INTERNAL_SERVER_ERROR);
}
}
+ @PostMapping("/descriptiveStatistics")
+ @ApiOperation("描述性统计分析")
+ @AnonymousAccess
+ public ResultEntity descriptiveStatistics(@ApiParam("分析的数据") @RequestBody JSONObject data, @ApiParam("计算量") @RequestBody JSONObject compute) {
+ // System.out.println(text);
+ String analyzedData = data.getString("data");
+ String computational = data.getString("compute");
+ String code = "# -*- coding: utf-8 -*-\n" +
+ "import pandas as pd\n" +
+ "import numpy as np\n" +
+ "from scipy import stats\n" +
+ "\n" +
+ "# 生成一些示例数据，故意在某些位置插入 NaN\n" +
+ "data = {\n" +
+ " 'age': [25, 32, None, 51, 23, 34, 36, 42, None, 40]\n" +
+ "}\n" +
+ "\n" +
+ "# 创建 DataFrame\n" +
+ "df = pd.DataFrame(data)\n" +
+ "\n" +
+ "\n" +
+ "# 计算描述性统计的函数\n" +
+ "def descriptive_statistics(valid_data, stats_to_compute):\n" +
+ " stats_summary = {}\n" +
+ "\n" +
+ " if '平均数' in stats_to_compute:\n" +
+ " stats_summary['平均数'] = round(valid_data.mean(), 1)\n" +
+ "\n" +
+ " if '中位数' in stats_to_compute:\n" +
+ " stats_summary['中位数'] = round(valid_data.median(), 1)\n" +
+ "\n" +
+ " if '众数' in stats_to_compute:\n" +
+ " stats_summary['众数'] = round(valid_data.mode()[0], 1) # 取众数的第一个值\n" +
+ "\n" +
+ " if '标准差' in stats_to_compute:\n" +
+ " stats_summary['标准差'] = round(valid_data.std(ddof=0), 1)\n" +
+ "\n" +
+ " if '方差' in stats_to_compute:\n" +
+ " stats_summary['方差'] = round(valid_data.var(ddof=0), 1)\n" +
+ "\n" +
+ " if '标准误差' in stats_to_compute:\n" +
+ " stats_summary['标准误差'] = round(valid_data.std(ddof=0) / np.sqrt(len(valid_data)), 1)\n" +
+ "\n" +
+ " if '峰度' in stats_to_compute:\n" +
+ " stats_summary['峰度'] = round(stats.kurtosis(valid_data, fisher=True), 1)\n" +
+ "\n" +
+ " if '偏度' in stats_to_compute:\n" +
+ " stats_summary['偏度'] = round(stats.skew(valid_data), 1)\n" +
+ "\n" +
+ " if '最大值' in stats_to_compute:\n" +
+ " stats_summary['最大值'] = round(valid_data.max(), 1)\n" +
+ "\n" +
+ " if '最小值' in stats_to_compute:\n" +
+ " stats_summary['最小值'] = round(valid_data.min(), 1)\n" +
+ "\n" +
+ " if '求和' in stats_to_compute:\n" +
+ " stats_summary['求和'] = round(valid_data.sum(), 1)\n" +
+ "\n" +
+ " # 仅在请求时计算观测数\n" +
+ " if '观测数' in stats_to_compute:\n" +
+ " stats_summary['观测数'] = valid_data.count() # 观测数不需要四舍五入\n" +
+ "\n" +
+ " return stats_summary\n" +
+ "\n" +
+ "\n" +
+ "# 根据传入的列和需要计算的统计量进行描述性统计分析\n" +
+ "def analyze_columns(df, stats_to_compute):\n" +
+ " for column in df.columns: # 直接遍历 DataFrame 中的所有列\n" +
+ " valid_data = df[column].dropna() # 去掉空值\n" +
+ " if len(valid_data) == 0:\n" +
+ " print(f\"{column} 列没有有效数据，跳过该列的描述性统计分析。\\n\")\n" +
+ " else:\n" +
+ " print(f\"{column} 的描述性统计:\")\n" +
+ " stats_summary = descriptive_statistics(valid_data, stats_to_compute) # 计算有效数据的描述性统计\n" +
+ " for stat_name, value in stats_summary.items():\n" +
+ " print(f\"{stat_name}: {value}\")\n" +
+ " print(\"\\n\")\n" +
+ "\n" +
+ "\n" +
+ "# 计算的统计量\n" +
+ "stats_to_compute = ['平均数', '中位数', '观测数'] # 可以根据需要修改要计算的统计量\n" +
+ "analyze_columns(df, stats_to_compute)";
+
+ // 替换代码中的 data和compute 为实际的 analyzedData和computational
+ String updatedCode = code.replace(" 'age': [25, 32, None, 51, 23, 34, 36, 42, None, 40]", "'" + analyzedData + "'")
+ .replace("'平均数', '中位数', '观测数'",computational);
+
+
+ //System.out.println(updatedCode);
+ try {
+ String s = IdUtil.simpleUUID();
+ String tempPythonFile = "/usr/local/tianzeProject/digitalMarketing/cnsenti/cnsenti/" + s + ".py";
+
+ File file1 = new File(tempPythonFile);
+
+ // 确保父目录存在
+ File parentDir = file1.getParentFile();
+ if (!parentDir.exists()) {
+ System.out.println("Parent directory does not exist. Creating it.");
+ if (!parentDir.mkdirs()) {
+ System.out.println("Failed to create directories.");
+ return new ResultEntity<>(HttpStatus.INTERNAL_SERVER_ERROR);
+ }
+ }
+
+ // 创建文件并写入内容
+ if (!file1.exists()) {
+ try {
+ boolean fileCreated = file1.createNewFile();
+ if (fileCreated) {
+ System.out.println("File created successfully: " + tempPythonFile);
+ } else {
+ System.out.println("File already exists: " + tempPythonFile);
+ }
+ } catch (IOException e) {
+ e.printStackTrace();
+ return new ResultEntity<>(HttpStatus.INTERNAL_SERVER_ERROR);
+ }
+ }
+
+ try (PrintWriter out = new PrintWriter(file1)) {
+ out.println(updatedCode);
+ }
+
+
+ // 确认 Docker 命令
+ String[] command = {"docker", "exec", "pyexe", "python", tempPythonFile};
+
+ Process process = Runtime.getRuntime().exec(command);
+
+ // 获取进程的输入流
+ BufferedReader inputStream = new BufferedReader(new InputStreamReader(process.getInputStream()));
+ BufferedReader errorStream = new BufferedReader(new InputStreamReader(process.getErrorStream()));
+
+ // 读取 Python 代码的输出
+ StringBuilder output = new StringBuilder();
+ String line;
+ while ((line = inputStream.readLine()) != null) {
+ output.append(line).append("\n");
+ }
+
+ // 读取 Python 代码的错误信息
+ StringBuilder errors = new StringBuilder();
+ while ((line = errorStream.readLine()) != null) {
+ errors.append(line).append("\n");
+ }
+
+ // 等待进程执行完成
+ int exitCode = process.waitFor();
+ if (exitCode == 0) {
+ String outputStr = output.toString().trim();
+ // 解析 JSON 输出
+ Map<String, Map<String, Object>> jsonResults = JSON.parseObject(outputStr, Map.class);
+
+ List<NewDescriptiveStatisticsDTO> list=new ArrayList<>();
+ // 创建并填充 NewDescriptiveStatisticsDTO 对象
+ for (Map.Entry<String, Map<String, Object>> entry : jsonResults.entrySet()) {
+ NewDescriptiveStatisticsDTO statisticsDTO = new NewDescriptiveStatisticsDTO();
+
+ Map<String, Object> stats = entry.getValue();
+ statisticsDTO.setAverage(((Number) stats.get("平均数")).doubleValue());
+ statisticsDTO.setMedian(((Number) stats.get("中位数")).doubleValue());
+ statisticsDTO.setMode(((Number) stats.get("众数")).doubleValue());
+ statisticsDTO.setStandardDeviation(((Number) stats.get("标准差")).doubleValue());
+ statisticsDTO.setVariance(((Number) stats.get("方差")).doubleValue());
+ statisticsDTO.setStandardError(((Number) stats.get("标准误差")).doubleValue());
+ statisticsDTO.setKurtosis(((Number) stats.get("峰度")).doubleValue());
+ statisticsDTO.setSkewness(((Number) stats.get("偏度")).doubleValue());
+ statisticsDTO.setMax(((Number) stats.get("最大值")).doubleValue());
+ statisticsDTO.setMin(((Number) stats.get("最小值")).doubleValue());
+ statisticsDTO.setSummation(((Number) stats.get("求和")).doubleValue());
+ statisticsDTO.setObservations(((Number) stats.get("观测数")).intValue());
+
+ // 输出或者处理 statisticsDTO 对象
+ System.out.println("Column: " + entry.getKey());
+ System.out.println(statisticsDTO);
+
+ list.add(statisticsDTO);
+ }
+
+ // System.out.println("Python code output:\n" + output.toString());
+ return new ResultEntity(HttpStatus.OK,list);
+
+
+ } else {
+ // System.err.println("Error executing Python code:\n" + errors.toString());
+ return new ResultEntity(HttpStatus.INTERNAL_SERVER_ERROR, errors.toString());
+ }
+ } catch (IOException | InterruptedException e) {
+ e.printStackTrace();
+ return new ResultEntity<>(HttpStatus.INTERNAL_SERVER_ERROR);
+ }
+ }
}
diff --git a/src/main/java/com/sztzjy/marketing/entity/dto/NewDescriptiveStatisticsDTO.java b/src/main/java/com/sztzjy/marketing/entity/dto/NewDescriptiveStatisticsDTO.java
new file mode 100644
index 0000000..74f630a
--- /dev/null
+++ b/src/main/java/com/sztzjy/marketing/entity/dto/NewDescriptiveStatisticsDTO.java
@@ -0,0 +1,48 @@
+package com.sztzjy.marketing.entity.dto;
+
+import io.swagger.annotations.ApiModelProperty;
+import lombok.Data;
+
+/**
+ * @author tz
+ * @date 2024/11/26 13:42
+ */
+//新版描述性统计分析返回数据格式
+@Data
+public class NewDescriptiveStatisticsDTO {
+ @ApiModelProperty("平均数")
+ private double average;
+
+ @ApiModelProperty("中位数")
+ private double median;
+
+ @ApiModelProperty("众数")
+ private double mode;
+
+ @ApiModelProperty("标准差")
+ private double standardDeviation;
+
+ @ApiModelProperty("方差")
+ private double variance;
+
+ @ApiModelProperty("标准误差")
+ private double standardError;
+
+ @ApiModelProperty("峰度")
+ private double kurtosis;
+
+ @ApiModelProperty("偏度")
+ private double skewness;
+
+ @ApiModelProperty("最大值")
+ private double max;
+
+ @ApiModelProperty("最小值")
+ private double min;
+
+ @ApiModelProperty("求和")
+ private double summation;
+
+ @ApiModelProperty("观测数")
+ private Integer observations;
+}
diff --git a/src/main/java/com/sztzjy/marketing/util/convertPDF/PDFConvertUtil.java b/src/main/java/com/sztzjy/marketing/util/convertPDF/PDFConvertUtil.java
index 5e64927..2e0330e 100644
--- a/src/main/java/com/sztzjy/marketing/util/convertPDF/PDFConvertUtil.java
+++ b/src/main/java/com/sztzjy/marketing/util/convertPDF/PDFConvertUtil.java
@@ -1,5 +1,6 @@
package com.sztzjy.marketing.util.convertPDF;
+
import com.aspose.words.FontSettings;
import com.aspose.words.License;
import com.aspose.words.SaveFormat;
diff --git a/src/main/resources/application.yml b/src/main/resources/application.yml
index bc9d045..f292896 100644
--- a/src/main/resources/application.yml
+++ b/src/main/resources/application.yml
@@ -83,7 +83,7 @@ mybatis:
swagger:
- enable: true
+ enable: false
tokenHeader: Authorization
title: 天择区块链金融 • 接口文档
description: 天择区块链金融WebAPI接口文档
diff --git a/src/main/resources/generatorConfig.xml b/src/main/resources/generatorConfig.xml
index b6eb666..43c9924 100644
--- a/src/main/resources/generatorConfig.xml
+++ b/src/main/resources/generatorConfig.xml
@@ -44,7 +44,7 @@
<!-- 需要生成的表 -->
- <table tableName="tch_module_weith" domainObjectName="TchModuleWeith" />
+ <table tableName="stu_machine_learning" domainObjectName="StuMachineLearning" />
</context>
diff --git a/src/main/resources/lib/aspose-cells-20.7-crack.jar b/src/main/resources/lib/aspose-cells-20.7-crack.jar
new file mode 100644
index 0000000..9676f04
Binary files /dev/null and b/src/main/resources/lib/aspose-cells-20.7-crack.jar differ
diff --git a/src/main/resources/lib/aspose-pdf-18.2.jar b/src/main/resources/lib/aspose-pdf-18.2.jar
new file mode 100644
index 0000000..833df4f
Binary files /dev/null and b/src/main/resources/lib/aspose-pdf-18.2.jar differ
diff --git a/src/main/resources/lib/aspose-words-18.10-jdk16.jar b/src/main/resources/lib/aspose-words-18.10-jdk16.jar
new file mode 100644
index 0000000..33057f9
Binary files /dev/null and b/src/main/resources/lib/aspose-words-18.10-jdk16.jar differ