From 474d5bf56ee61912fc318b4142868544c253363a Mon Sep 17 00:00:00 2001
From: MingYang <myangusa@icloud.com>
Date: Mon, 21 Jul 2025 16:52:39 +0800
Subject: [PATCH] Upload files to "/"

---
 visual0721.R | 2896 ++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 2896 insertions(+)
 create mode 100644 visual0721.R

diff --git a/visual0721.R b/visual0721.R
new file mode 100644
index 0000000..793df3f
--- /dev/null
+++ b/visual0721.R
@@ -0,0 +1,2896 @@
+library(shiny)
+library(DT)
+library(dplyr)
+library(readr)
+library(Cairo)
+library(ggplot2)
+library(plotly)
+library(stringi)
+library(stringr)
+library(datetime)
+library(dplyr)
+library(ggthemes)
+library(RMySQL)
+library(shinyCyJS)
+
+csv_map <- list(
+  "按月统计"       = "按月统计0.csv",
+  "最后六周按日统计"   = "按日统计0.csv",
+  "按小细胞统计"     = "按细胞统计0.csv",
+  "按省统计"       = "按区域统计0.csv",
+  "按仪器统计"     = "按仪器统计0.csv",
+  "按样本类型统计" = "按样本统计0.csv",
+  "按试剂批次统计" = "按批次统计0.csv",
+  "按试剂项目统计" = "按项目统计0.csv"
+)
+page<-1
+max_pages<-1
+ui <- fluidPage(
+  tags$head(tags$title("丹娜数据分析平台")),
+  tags$img(src = "dnklogo.png", height = "75px", alt = "Logo",style = "float: right;"),
+  titlePanel(
+    HTML("
+      <div style='text-align: left;'>
+      <div style='font-size: 28px; color: skyblue; font-weight: bold;'>丹娜数据分析平台</div>
+      <div style='font-size: 14px; color: skyblue;'>和迈仪器</div>
+      </div>
+    ") 
+  ),
+#  titlePanel("丹娜数据分析平台-和迈仪器"),
+  sidebarLayout(
+    sidebarPanel(
+      width = 3,  # 设置侧边栏宽度为 2（更小）
+      selectInput("stat_dim", "选择统计维度",
+                  choices = names(csv_map)),
+      uiOutput("metric_group"),
+      uiOutput("stat_way"),
+      br(),
+      br(),
+      downloadButton("download_table", "下载表格数据")
+    ),
+    mainPanel(
+      width = 9,
+      tabsetPanel(
+        tabPanel("图表展示", 
+                 uiOutput("pagination_ui"),
+                 plotlyOutput("main_plot")),
+        tabPanel("数据表格", DTOutput("data_table")),
+
+        tabPanel("仪器与小细胞（coming soon)", ShinyCyJSOutput(outputId = "cy"))
+        
+      )
+    )
+  )
+  
+)
+
+# 定义服务器逻辑
+server <- function(input, output) {
+current_page <- reactiveVal(page)
+#  current_page <- reactiveVal()
+  output$download_table <- downloadHandler(
+    filename = function() {
+      paste0(input$stat_dim, "_", Sys.Date(), ".csv")
+    },
+    content = function(file) {
+      data <- data_raw()
+      write_excel_csv(data, file)
+    }
+  )
+  
+  nodes <- data.frame(
+    id = c("A", "B", "C", "D"),
+    width = c(10, 20, 30, 40),
+    height = c(10, 20, 30, 40)
+  )
+  
+  edges <- data.frame(
+    source = c("A", "B", "C", "D"),
+    target = c("B", "C", "D", "B")
+  )
+  
+  nodes <- buildElems(nodes, type = "Node")
+  edges <- buildElems(edges, type = "Edge")
+  
+  obj <- shinyCyJS(c(nodes, edges))
+  output$cy <- renderShinyCyJS(obj)
+  
+  output$pagination_ui <- renderUI({
+    req(input$stat_dim, input$metric, input$stat_way_sel)
+    
+    max_pages <- switch(input$stat_dim,
+                        "最后六周按日统计" = {
+                          if (input$stat_way_sel == "按日分省统计") {
+                            ceiling(length(dfBy区域$省编号) / 6)
+                          } else if (input$stat_way_sel == "按日分小细胞统计") {
+                            ceiling(length(细胞0$细胞) / 6)
+                          } else if (input$stat_way_sel == "按日分仪器统计") {
+                            ceiling(length(仪器号List$仪器序列号) / 6)
+                          } else 1
+                        },
+                        "按月统计" = {
+                          if (input$stat_way_sel == "按月分省统计") {
+                            ceiling(length(dfBy区域$省编号) / 6)
+                          } else if (input$stat_way_sel == "按月分小细胞统计") {
+                            ceiling(length(细胞0$细胞) / 6)
+                          } else if (input$stat_way_sel == "按月分仪器统计") {
+                            ceiling(length(仪器号List$仪器序列号) / 6)
+                          } else 1
+                        },
+                        "按仪器统计"     = max(仪器号List$GroupID),
+                        "按试剂批次统计" = max(批次号List$GroupID),
+                        "按试剂项目统计" = max(项目号List$GroupID),
+                        "按小细胞统计" = 2,
+                        1)
+    
+    page<-current_page()
+    if(!is.numeric(page)) {
+      page<-1
+    } else {
+      if(page>max_pages)  page<-max_pages
+    }
+    
+    if (max_pages > 1) {
+      tagList(
+        actionButton("prev_page", "上一页"),
+        span(paste("第", page, "页 / 共", max_pages, "页")),
+        actionButton("next_page", "下一页")
+      )
+    }
+  })
+  
+  observeEvent(input$prev_page, {
+    max_pages <- switch(input$stat_dim,
+                        "最后六周按日统计" = {
+                          if (input$stat_way_sel == "按日分省统计") {
+                            ceiling(length(dfBy区域$省编号) / 6)
+                          } else if (input$stat_way_sel == "按日分小细胞统计") {
+                            ceiling(length(细胞0$细胞) / 6)
+                          } else if (input$stat_way_sel == "按日分仪器统计") {
+                            ceiling(length(仪器号List$仪器序列号) / 6)
+                          } else 1
+                        },
+                        "按月统计" = {
+                          if (input$stat_way_sel == "按月分省统计") {
+                            ceiling(length(dfBy区域$省编号) / 6)
+                          } else if (input$stat_way_sel == "按月分小细胞统计") {
+                            ceiling(length(细胞0$细胞) / 6)
+                          } else if (input$stat_way_sel == "按月分仪器统计") {
+                            ceiling(length(仪器号List$仪器序列号) / 6)
+                          } else 1
+                        },
+                        "按仪器统计"     = max(仪器号List$GroupID),
+                        "按试剂批次统计" = max(批次号List$GroupID),
+                        "按试剂项目统计" = max(项目号List$GroupID),
+                        "按小细胞统计" = 2,
+                        1)
+    
+    page<-min(current_page(),max_pages)
+ 
+    if (page > 1) current_page(page - 1) else 1
+  })
+  
+  observeEvent(input$next_page, {
+    max_pages <- switch(input$stat_dim,
+                        "最后六周按日统计" = {
+                          if (input$stat_way_sel == "按日分省统计") {
+                            ceiling(length(dfBy区域$省编号) / 6)
+                          } else if (input$stat_way_sel == "按日分小细胞统计") {
+                            ceiling(length(细胞0$细胞) / 6)
+                          } else if (input$stat_way_sel == "按日分仪器统计") {
+                            ceiling(length(仪器号List$仪器序列号) / 6)
+                          } else 1
+                        },
+                        "按月统计" = {
+                          if (input$stat_way_sel == "按月分省统计") {
+                            ceiling(length(dfBy区域$省编号) / 6)
+                          } else if (input$stat_way_sel == "按月分小细胞统计") {
+                            ceiling(length(细胞0$细胞) / 6)
+                          } else if (input$stat_way_sel == "按月分仪器统计") {
+                            ceiling(length(仪器号List$仪器序列号) / 6)
+                          } else 1
+                        },
+                        "按仪器统计"     = max(仪器号List$GroupID),
+                        "按试剂批次统计" = max(批次号List$GroupID),
+                        "按试剂项目统计" = max(项目号List$GroupID),
+                        "按小细胞统计" = 2,
+                        1)
+    page<-min(current_page(),max_pages)
+    
+    if (page<max_pages) current_page(page + 1) else max_pages
+    
+  })
+  # 动态生成第二栏：指标分组
+  output$metric_group <- renderUI({
+    metric_choices <- switch(input$stat_dim,
+                             "最后六周按日统计" = list("测试数、阳性数、有效数", 
+                                               "阳性率、有效率", 
+                                               "项目数、仪器数、批次数", 
+                                               "省数、市数、小细胞数、样本数"),
+                             "按月统计" = list("测试数、阳性数、有效数", 
+                                           "阳性率、有效率", 
+                                           "项目数、仪器数、批次数", 
+                                           "省数、市数、小细胞数、样本数"),
+                             "按小细胞统计"=list("测试数、阳性数、有效数", 
+                                           "阳性率、有效率", 
+                                           "项目数、仪器数、批次数", 
+                                           "省数、市数、小细胞数、样本数", 
+                                           "测试截止、测试开始"),
+                             "按省统计" = list("测试数、阳性数、有效数", 
+                                           "阳性率、有效率", 
+                                           "项目数、仪器数、批次数", 
+                                           "省数、市数、小细胞数、样本数", 
+                                           "测试截止、测试开始"),
+                             "按仪器统计" = list("测试数、阳性数、有效数", 
+                                            "阳性率、有效率", 
+                                            "项目数、仪器数、批次数", 
+                                            "省数、市数、小细胞数、样本数", 
+                                            "测试截止、测试开始"),
+                             "按样本类型统计" = list("测试数、阳性数、有效数", 
+                                              "阳性率、有效率", 
+                                              "项目数、仪器数、批次数", 
+                                              "省数、市数、小细胞数、样本数"),
+                             "按试剂批次统计" = list("测试数、阳性数、有效数", 
+                                              "阳性率、有效率", 
+                                              "项目数、仪器数、批次数", 
+                                              "省数、市数、小细胞数、样本数", 
+                                              "测试截止、测试开始"),
+                             "按试剂项目统计" = list("测试数、阳性数、有效数", 
+                                              "阳性率、有效率", 
+                                              "项目数、仪器数、批次数", 
+                                              "省数、市数、小细胞数、样本数", 
+                                              "测试截止、测试开始"))
+    
+    selectInput("metric", "选择指标分组", choices = metric_choices)
+  })
+  
+  # 动态生成第三栏：统计方式
+  output$stat_way <- renderUI({
+    way_choices <- switch(input$stat_dim,
+                          "按月统计" = c("全部统计","按月分省统计","按月分小细胞统计","按月分仪器统计"),
+                          "最后六周按日统计" = c("全部统计","按日分省统计", "按日分小细胞统计","按日分仪器统计"),
+                          "按小细胞统计" = "全部统计", 
+                          "按省统计" = "全部统计",
+                          "按仪器统计" = "全部统计",
+                          "按样本类型统计" = "全部统计",
+                          "按试剂批次统计" = "全部统计",
+                          "按试剂项目统计"="全部统计")
+    if (is.character(way_choices)) {
+      selectInput("stat_way_sel", "选择统计方式", choices = way_choices)
+    } else {
+      NULL
+    }
+  })
+  data_raw <- reactive({
+    read_csv(csv_map[[input$stat_dim]])
+  })
+  # 生成数据表格
+  output$data_table <- renderDT({
+    datatable(data_raw(), options = list(pageLength = 10))
+  })
+  
+  # 生成图表
+  output$main_plot <- renderPlotly({
+    req(input$stat_dim, input$metric, input$stat_way_sel)
+    data <- generate_data_table(input$stat_dim, input$metric)
+    # 把当前页码传进去
+    
+    generate_plot(data, input$stat_dim, input$metric, input$stat_way_sel, current_page())
+  })
+  
+  
+}
+
+
+plotfunction<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  
+  plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count, 
+                              text = paste( round(Count, 2)) ,fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   linewidth = 1.2                    # 字体大小
+    # ) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      legend.position = "right")+guides(color = "none") 
+  
+ # plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  
+  #return (list(plotdfDataNumber,b23,b33,b43,b53))
+  
+}
+
+plotfunctionVector仪器序列号<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
+  dfData<-dfData[(dfData$仪器序列号 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  
+  plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count,text = paste( round(Count, 2)) , fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      legend.position = "right")+guides(color = "none") 
+  
+ # plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  #return (list(plotdfDataNumber,b23,b33,b43,b53))
+  
+}
+
+plotfunctionVector批次名称<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
+  dfData<-dfData[(dfData$批次名称 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  
+  plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count,text = paste( round(Count, 2)) , fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      legend.position = "right")+guides(color = "none") 
+  
+ # plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  #return (list(plotdfDataNumber,b23,b33,b43,b53))
+  
+}
+
+plotfunctionVector批次名称Log<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
+  dfData<-dfData[(dfData$批次名称 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  
+  plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count,text = paste( round(Count, 2)) , fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    scale_y_log10()+
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      legend.position = "right")+guides(color = "none") 
+  
+ # plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  #return (list(plotdfDataNumber,b23,b33,b43,b53))
+  
+}
+
+plotfunctionVector项目名称<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
+  dfData<-dfData[(dfData$项目名称 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  
+  plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count,text = paste( round(Count, 2)) , fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      legend.position = "right")+guides(color = "none") 
+  
+ # plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  #return (list(plotdfDataNumber,b23,b33,b43,b53))
+  
+}
+
+plotfunctionVector项目名称Log<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
+  dfData<-dfData[(dfData$项目名称 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  
+  plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count,text = paste( round(Count, 2)) , fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    scale_y_log10()+
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      legend.position = "right")+guides(color = "none") 
+  
+ # plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  #return (list(plotdfDataNumber,b23,b33,b43,b53))
+  
+}
+
+plotfunctionLog<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  
+  plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count,text = paste( round(Count, 2)) , fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    scale_y_log10()+
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      legend.position = "right")+guides(color = "none") 
+  
+ # plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  #return (list(plotdfDataNumber,b23,b33,b43,b53))
+  
+}
+
+plotfunctionVector仪器序列号Log<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
+  dfData<-dfData[(dfData$仪器序列号 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  
+  plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count,text = paste( round(Count, 2)) , fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    scale_y_log10()+
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      legend.position = "right")+guides(color = "none") 
+  
+ # plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  #return (list(plotdfDataNumber,b23,b33,b43,b53))
+  
+}
+
+panelPlotByDayAndLocation<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  dfData00<-dfData00[dfData00$省编号 %in% choosenList,]
+  dfData00$省编号<-factor(dfData00$省编号,levels = choosenList)
+  
+  plot1<-ggplot(dfData00, aes(x = testDay, y = Count,text = paste( round(Count, 2)) , fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    facet_wrap( ~ 省编号,ncol=2) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      panel.border = element_rect(
+        color = "black",   # 边框颜色
+        linewidth = 1.,        # 边框粗细
+        linetype = "solid", # 线型（solid/dashed/dotted）
+        fill = NA          # 填充色（NA为透明）
+      ),
+      legend.position = "right")+guides(color = "none") 
+  
+ # plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+}
+
+panelPlotByMonthAndLocation<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  dfData00<-dfData00[dfData00$省编号 %in% choosenList,]
+  dfData00$省编号<-factor(dfData00$省编号,levels = choosenList)
+  
+  plot1<-ggplot(dfData00, aes(x = testMonth, y = Count, text = paste( round(Count, 2)) ,fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    facet_wrap( ~ 省编号,ncol=2) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      panel.border = element_rect(
+        color = "black",   # 边框颜色
+        linewidth = 1.,        # 边框粗细
+        linetype = "solid", # 线型（solid/dashed/dotted）
+        fill = NA          # 填充色（NA为透明）
+      ),
+      legend.position = "right")+guides(color = "none") 
+  
+ # plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+}
+
+panelPlotByDayAnd细胞<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  dfData00<-dfData00[dfData00$小细胞 %in% choosenList,]
+  dfData00$小细胞<-factor(dfData00$小细胞,levels = choosenList)
+  
+  plot1<-ggplot(dfData00, aes(x = testDay, y = Count, text = paste( round(Count, 2)) ,fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    facet_wrap( ~ 小细胞,ncol=2) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      panel.border = element_rect(
+        color = "black",   # 边框颜色
+        linewidth = 1.,        # 边框粗细
+        linetype = "solid", # 线型（solid/dashed/dotted）
+        fill = NA          # 填充色（NA为透明）
+      ),
+      legend.position = "right")+guides(color = "none") 
+  
+  #plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+}
+
+panelPlotByMonthAnd细胞<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  dfData00<-dfData00[dfData00$小细胞 %in% choosenList,]
+  dfData00$小细胞<-factor(dfData00$小细胞,levels = choosenList)
+  
+  plot1<-ggplot(dfData00, aes(x = testMonth, y = Count,text = paste( round(Count, 2)) , fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    facet_wrap( ~ 小细胞,ncol=2) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      panel.border = element_rect(
+        color = "black",   # 边框颜色
+        linewidth = 1.,        # 边框粗细
+        linetype = "solid", # 线型（solid/dashed/dotted）
+        fill = NA          # 填充色（NA为透明）
+      ),
+      legend.position = "right")+guides(color = "none") 
+  
+  #plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+}
+
+pointPlotfunction批次<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
+  
+  plot1 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],
+                                             text = paste( round(dfData[,dependentVariableName], 2)) ,color=as.character(批次名称)))+
+    # geom_line(aes(testDay,浓度1移动均值),color="blue")+
+    # geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
+    # geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
+    #  xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
+    labs(
+      title = titleNames[1],      # 主标题
+      x = titleNames[2],        # X轴标签
+      y = titleNames[3],              # Y轴标签
+      color = titleNames[4]                  # 图例标题
+    )+
+    # scale_x_date(
+    #   date_labels = "%Y-%m-%d",  # 格式符组合
+    #   date_breaks = "1 month"         # 标签间隔（如 "2 weeks"）
+    # )+
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 10,face = "bold"),
+      axis.title.y = element_text(size = 10,face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90),
+      legend.position = "right")+guides(color = "none") 
+  
+  #plot2
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  
+}
+
+pointPlotfunction批次Log<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
+  
+  plot1<- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],
+                                             text = paste( round(dfData[,dependentVariableName], 2)) ,color=as.character(批次名称)))+
+    # geom_line(aes(testDay,浓度1移动均值),color="blue")+
+    # geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
+    # geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
+    #  xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
+    labs(
+      title = titleNames[1],      # 主标题
+      x = titleNames[2],        # X轴标签
+      y = titleNames[3],              # Y轴标签
+      color = titleNames[4]                  # 图例标题
+    )+
+    # scale_x_date(
+    #   date_labels = "%Y-%m-%d",  # 格式符组合
+    #   date_breaks = "1 month"         # 标签间隔（如 "2 weeks"）
+    # )+
+    scale_y_log10()+
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 10,face = "bold"),
+      axis.title.y = element_text(size = 10,face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90),
+      legend.position = "right")+guides(color = "none") 
+  
+ # plot2
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  
+}
+
+pointPlotfunction仪器<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
+  
+  plot1<- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],
+                                             text = paste( round(dfData[,dependentVariableName], 2)) ,color=as.character(仪器序列号)))+
+    # geom_line(aes(testDay,浓度1移动均值),color="blue")+
+    # geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
+    # geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
+    #  xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
+    labs(
+      title = titleNames[1],      # 主标题
+      x = titleNames[2],        # X轴标签
+      y = titleNames[3],              # Y轴标签
+      color = titleNames[4]                  # 图例标题
+    )+
+    # scale_x_date(
+    #   date_labels = "%Y-%m-%d",  # 格式符组合
+    #   date_breaks = "1 month"         # 标签间隔（如 "2 weeks"）
+    # )+
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 10,face = "bold"),
+      axis.title.y = element_text(size = 10,face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90),
+      legend.position = "right")+guides(color = "none") 
+  
+  #plot2
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  
+}
+
+pointPlotfunction仪器Log<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
+  
+  plot1<- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],
+                                             text = paste( round(dfData[,dependentVariableName], 2)) ,color=as.character(仪器序列号)))+
+    # geom_line(aes(testDay,浓度1移动均值),color="blue")+
+    # geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
+    # geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
+    #  xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
+    labs(
+      title = titleNames[1],      # 主标题
+      x = titleNames[2],        # X轴标签
+      y = titleNames[3],              # Y轴标签
+      color = titleNames[4]                  # 图例标题
+    )+
+    # scale_x_date(
+    #   date_labels = "%Y-%m-%d",  # 格式符组合
+    #   date_breaks = "1 month"         # 标签间隔（如 "2 weeks"）
+    # )+
+    scale_y_log10()+
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 10,face = "bold"),
+      axis.title.y = element_text(size = 10,face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90),
+      legend.position = "right")+guides(color = "none") 
+  
+ # plot2
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  
+}
+
+pointPlotfunction样本<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
+  
+  plot1<- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],
+                                             text = paste( round(dfData[,dependentVariableName], 2)) ,color=as.character(样本类型)))+
+    # geom_line(aes(testDay,浓度1移动均值),color="blue")+
+    # geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
+    # geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
+    #  xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
+    labs(
+      title = titleNames[1],      # 主标题
+      x = titleNames[2],        # X轴标签
+      y = titleNames[3],              # Y轴标签
+      color = titleNames[4]                  # 图例标题
+    )+
+    # scale_x_date(
+    #   date_labels = "%Y-%m-%d",  # 格式符组合
+    #   date_breaks = "1 month"         # 标签间隔（如 "2 weeks"）
+    # )+
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 10,face = "bold"),
+      axis.title.y = element_text(size = 10,face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90),
+      legend.position = "right")+guides(color = "none") 
+  
+ # plot2
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  
+}
+
+pointPlotfunction样本Log<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
+  
+  plot1<- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],
+                                             text = paste( round(dfData[,dependentVariableName], 2)) ,color=as.character(样本类型)))+
+    # geom_line(aes(testDay,浓度1移动均值),color="blue")+
+    # geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
+    # geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
+    #  xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
+    labs(
+      title = titleNames[1],      # 主标题
+      x = titleNames[2],        # X轴标签
+      y = titleNames[3],              # Y轴标签
+      color = titleNames[4]                  # 图例标题
+    )+
+    # scale_x_date(
+    #   date_labels = "%Y-%m-%d",  # 格式符组合
+    #   date_breaks = "1 month"         # 标签间隔（如 "2 weeks"）
+    # )+
+    scale_y_log10()+
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 10,face = "bold"),
+      axis.title.y = element_text(size = 10,face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90),
+      legend.position = "right")+guides(color = "none") 
+  
+ # plot2
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  
+}
+
+pointPlotfunction项目<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
+  
+  plot1<- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],
+                                             text = paste( round(dfData[,dependentVariableName], 2)) ,color=as.character(项目名称)))+
+    # geom_line(aes(testDay,浓度1移动均值),color="blue")+
+    # geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
+    # geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
+    #  xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
+    labs(
+      title = titleNames[1],      # 主标题
+      x = titleNames[2],        # X轴标签
+      y = titleNames[3],              # Y轴标签
+      color = titleNames[4]                  # 图例标题
+    )+
+    # scale_x_date(
+    #   date_labels = "%Y-%m-%d",  # 格式符组合
+    #   date_breaks = "1 month"         # 标签间隔（如 "2 weeks"）
+    # )+
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 10,face = "bold"),
+      axis.title.y = element_text(size = 10,face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90),
+      legend.position = "right")+guides(color = "none") 
+  
+ # plot2
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  
+}
+
+pointPlotfunction项目Log<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
+  
+  plot1<- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],
+                                             text = paste( round(dfData[,dependentVariableName], 2)) ,color=as.character(项目名称)))+
+    # geom_line(aes(testDay,浓度1移动均值),color="blue")+
+    # geom_line(aes(testDay,浓度1累计均值),color="green",linewidth=1.)+
+    # geom_line(aes(testDay,浓度1允许波动范围),color="red",linewidth=1.)+
+    #  xlim(xmin, xmax) + ylim(ymin, ymax)+theme(legend.position ="right")+
+    labs(
+      title = titleNames[1],      # 主标题
+      x = titleNames[2],        # X轴标签
+      y = titleNames[3],              # Y轴标签
+      color = titleNames[4]                  # 图例标题
+    )+
+    # scale_x_date(
+    #   date_labels = "%Y-%m-%d",  # 格式符组合
+    #   date_breaks = "1 month"         # 标签间隔（如 "2 weeks"）
+    # )+
+    scale_y_log10()+
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 10,face = "bold"),
+      axis.title.y = element_text(size = 10,face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90),
+      legend.position = "right")+guides(color = "none") 
+  
+  # plot2
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  
+}
+
+plotfunctionByDay<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  
+  plot1<-ggplot(dfData00, aes(x = testDay, y = Count, text = paste( round(Count, 2)) ,fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      legend.position = "right")+guides(color = "none") 
+  
+  # plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  #return (list(plotdfDataNumber,b23,b33,b43,b53))
+  
+}
+
+plotfunctionBy区域<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  
+  plot1<-ggplot(dfData00, aes(x = 省编号, y = Count,text = paste( round(Count, 2)) , fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      legend.position = "right")+guides(color = "none") 
+  
+  #plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  #return (list(plotdfDataNumber,b23,b33,b43,b53))
+  
+}
+
+plotfunctionBy仪器<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  
+  plot1<-ggplot(dfData00, aes(x = 仪器序列号, y = Count,text = paste( round(Count, 2)) , fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      legend.position = "right")+guides(color = "none") 
+  
+  #plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  #return (list(plotdfDataNumber,b23,b33,b43,b53))
+  
+}
+
+plotfunctionBy仪器Log<- function(dfData,independentVariableName,dependentVariableNames,titleNames) {
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  
+  plot1<-ggplot(dfData00, aes(x = 仪器序列号, y = Count,text = paste( round(Count, 2)) , fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    scale_y_log10()+
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      legend.position = "right")+guides(color = "none") 
+  
+  #plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+  #return (list(plotdfDataNumber,b23,b33,b43,b53))
+  
+}
+
+panelPlotByDayAnd仪器<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  dfData00<-dfData00[dfData00$仪器序列号 %in% choosenList,]
+  dfData00$仪器序列号<-factor(dfData00$仪器序列号,levels = choosenList)
+  
+  plot1<-ggplot(dfData00, aes(x = testDay, y = Count, text = paste( round(Count, 2)) ,fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    facet_wrap( ~ 仪器序列号,ncol=2) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      panel.border = element_rect(
+        color = "black",   # 边框颜色
+        linewidth = 1.,        # 边框粗细
+        linetype = "solid", # 线型（solid/dashed/dotted）
+        fill = NA          # 填充色（NA为透明）
+      ),
+      legend.position = "right")+guides(color = "none") 
+  
+  #plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+}
+
+panelPlotByMonthAnd仪器<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  dfData00<-dfData00[dfData00$仪器序列号 %in% choosenList,]
+  dfData00$仪器序列号<-factor(dfData00$仪器序列号,levels = choosenList)
+  
+  plot1<-ggplot(dfData00, aes(x = testMonth, y = Count,text = paste( round(Count, 2)) , fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    facet_wrap( ~ 仪器序列号,ncol=2) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      panel.border = element_rect(
+        color = "black",   # 边框颜色
+        linewidth = 1.,        # 边框粗细
+        linetype = "solid", # 线型（solid/dashed/dotted）
+        fill = NA          # 填充色（NA为透明）
+      ),
+      legend.position = "right")+guides(color = "none") 
+  
+  #plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+}
+
+panelPlotByDayAnd仪器<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  dfData00<-dfData00[dfData00$仪器序列号 %in% choosenList,]
+  dfData00$仪器序列号<-factor(dfData00$仪器序列号,levels = choosenList)
+  
+  plot1<-ggplot(dfData00, aes(x = testDay, y = Count, text = paste( round(Count, 2)) ,fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    facet_wrap( ~ 仪器序列号,ncol=2) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      panel.border = element_rect(
+        color = "black",   # 边框颜色
+        linewidth = 1.,        # 边框粗细
+        linetype = "solid", # 线型（solid/dashed/dotted）
+        fill = NA          # 填充色（NA为透明）
+      ),
+      legend.position = "right")+guides(color = "none") 
+  
+  #plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+}
+
+panelPlotByMonthAnd仪器<- function(dfData,choosenList,independentVariableName,panelName,dependentVariableNames,titleNames) {
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,panelName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,panelName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  dfData00<-dfData00[dfData00$仪器序列号 %in% choosenList,]
+  dfData00$仪器序列号<-factor(dfData00$仪器序列号,levels = choosenList)
+  
+  plot1<-ggplot(dfData00, aes(x = testMonth, y = Count,text = paste( round(Count, 2)) , fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      linewidth = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    # geom_text(
+    #   aes(label = round(Count,2)),         # 标签内容
+    #   position = position_dodge(width = 0.4),  # 与柱子位置一致
+    #   vjust = -0.4,               # 垂直位置（负值向上）
+    #   color = "black",            # 标签颜色
+    #   size = 1.2                    # 字体大小
+    # ) +
+    facet_wrap( ~ 仪器序列号,ncol=2) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      panel.border = element_rect(
+        color = "black",   # 边框颜色
+        linewidth = 1.,        # 边框粗细
+        linetype = "solid", # 线型（solid/dashed/dotted）
+        fill = NA          # 填充色（NA为透明）
+      ),
+      legend.position = "right")+guides(color = "none") 
+  
+  #plot1
+  
+  # Convert to interactive plot
+  plot1<-ggplotly(plot1, tooltip = "text")
+  return (plot1)
+}
+
+running_avg <- function(x, window = 3) {
+  sapply(seq_along(x), function(i) {
+    start <- max(1, i - window + 1)
+    mean(x[start:i],na.rm=TRUE)
+  })
+}
+
+lumping_avg<- function(x,window = 100) {
+  sapply(seq_along(x), function(i) {
+    start <- max(1, i - window + 1)
+    mean(x[start:i],na.rm=TRUE)
+  })
+}
+
+lumping_sd<- function(x,window = 100) {
+  sapply(seq_along(x), function(i) {
+    start <- max(1, i - window + 1)
+    sd(x[start:i],na.rm=TRUE)
+  })
+}
+rep6<-rep(1,6)
+rep50<-rep(1,50)
+rep0<-rep6
+for(i in 1:1000) rep0<-c(rep0,rep6+i)
+rep00<-rep50
+for(i in 1:100) rep00<-c(rep00,rep50+i)
+
+if(FALSE){
+  csv_files <- list.files(pattern = "\\UTF.csv$")
+  
+  df00<-data.frame()
+  
+  for(i in 1:length(csv_files)) {
+    #guess_encoding("historyRecord20.csv") # [[1]]$encoding 
+    #df2 <- fread("historyRecord20250604175205UTF.csv",encoding = "UTF-8",fill = TRUE)
+    # df22 <- read.csv(csv_files[i],encoding = "UTF-8",fill = TRUE)
+    # colnames(df22)
+    # summary(df22)
+    df2 <- read.csv(csv_files[i],encoding = "UTF-8",fill = TRUE)
+    df2$批次名称<-as.character(df2$批次名称)
+    df2<-df2[!is.na(df2$批次名称),]
+    
+    df2$是否阳性<-df2$结论
+    df2$是否阳性[df2$是否阳性=="阳性"]<-1.0
+    df2$是否阳性[df2$是否阳性=="阴性"]<-0.0
+    df2$是否阳性[df2$是否阳性=="无效"]<-0.5
+    df2$是否阳性<-as.numeric(df2$是否阳性)
+    df2$是否阳性[is.na(df2$是否阳性)]<-0.5
+    
+    df2$结论[df2$结论=="阳性"]<-1.0
+    df2$结论[df2$结论=="阴性"]<-0.0
+    df2$结论<-as.numeric(df2$结论)
+    
+    df2$是否有效<-1
+    df2$是否有效[df2$是否阳性==0.5]<-0
+    
+    df00<-rbind(df00,df2)
+  }
+  write_excel_csv(df00,file="history06092025.csv")
+  
+  df2<-df00
+  
+} 
+if(FALSE){
+  series<-read.csv("荧光层析设备1.csv",encoding = "UTF-8",fill = TRUE)
+  series1<-read.csv("FIC-Q100N.csv",encoding = "UTF-8",fill = TRUE)
+  series0<-series$仪器序列号[series$仪器序列号 %in% 仪器号List$仪器序列号]
+  series00<-series$仪器编号[series$仪器编号 %in% series1$仪器编号]
+  colnames(series[,1:13])
+  colnames(series1[,3:11])
+  仪器编号和序列号<-merge(series[,1:13],series1[,3:11],by="仪器编号",all=FALSE)
+  #仪器编号和序列号all<-merge(series[,1:13],series1[,3:11],by="仪器编号",all=TRUE)
+  colnames(仪器编号和序列号)
+  仪器编号和序列号$SIM卡号<- gsub("\t", " ", 仪器编号和序列号$SIM卡号)
+  仪器编号和序列号$返利表序号<- gsub("\n", "_", 仪器编号和序列号$返利表序号)
+  #仪器编号和序列号all$SIM卡号<- gsub("\t", " ", 仪器编号和序列号all$SIM卡号)
+  #仪器编号和序列号all$返利表序号<- gsub("\n", "_", 仪器编号和序列号all$返利表序号)
+  #仪器编号和序列号[仪器编号和序列号$仪器序列号=="781be43bb68f05bb",]
+  
+  cname0<-c("仪器编号"  ,       "仪器序列号"  ,    
+            "SIM卡号"  ,        "发货时间"   ,      "仪器类型"   ,     
+            "总测试量"   ,      "最后一次开机时间" ,"时间差"   ,       
+            "开机地点"  ,       "网络类型" ,        "ip地址"    ,      
+            "用户"  ,           "用户CRM"   ,       "返利表序号"  ,    
+            "申请日期"  ,       "区域"     ,        "客户编码"  ,      
+            "代理商名称" ,      "用户名称"   ,      "规格" ,           
+            "状态")
+  #write_excel_csv(仪器编号和序列号all[,cname0],file="仪器编号和序列号all.csv")
+  write_excel_csv(仪器编号和序列号[,cname0],file="仪器编号和序列号.csv")
+}
+if(FALSE){
+  series<-read.csv("荧光层析设备1.csv",encoding = "UTF-8",fill = TRUE)
+  series1<-read.csv("FIC-Q100N20250710.csv",encoding = "UTF-8",fill = TRUE)
+  series0<-series$仪器序列号[series$仪器序列号 %in% 仪器号List$仪器序列号]
+  series00<-series$仪器编号[series$仪器编号 %in% series1$仪器编号]
+  colnames(series)[1:13]
+  colnames(series1)[3:11]
+  仪器编号和序列号0<-merge(series[,1:13],series1[,3:11],by="仪器编号",all=FALSE)
+  仪器编号和序列号1<-merge(series[,1:13],series1[,3:11],by="仪器编号",all=TRUE)
+  仪器编号和序列号2<-merge(series[,1:13],series1[,3:11],by="仪器编号",all.y=TRUE,all.x=FALSE)
+  unique编号1<-unique(仪器编号和序列号1$仪器编号)
+  unique序列号1<-unique(仪器编号和序列号1$仪器序列号)
+  unique编号2<-unique(仪器编号和序列号2$仪器编号)
+  unique序列号2<-unique(仪器编号和序列号2$仪器序列号)
+  #仪器编号和序列号all<-merge(series[,1:13],series1[,3:11],by="仪器编号",all=TRUE)
+  colnames(仪器编号和序列号1)
+  仪器编号和序列号0$SIM卡号<- gsub("\t", " ", 仪器编号和序列号0$SIM卡号)
+  仪器编号和序列号0$返利表序号<- gsub("\n", "_", 仪器编号和序列号0$返利表序号)
+  仪器编号和序列号1$SIM卡号<- gsub("\t", " ", 仪器编号和序列号1$SIM卡号)
+  仪器编号和序列号1$返利表序号<- gsub("\n", "_", 仪器编号和序列号1$返利表序号)
+  #仪器编号和序列号all$SIM卡号<- gsub("\t", " ", 仪器编号和序列号all$SIM卡号)
+  #仪器编号和序列号all$返利表序号<- gsub("\n", "_", 仪器编号和序列号all$返利表序号)
+  #仪器编号和序列号[仪器编号和序列号$仪器序列号=="781be43bb68f05bb",]
+  仪器编号和序列号1e<-仪器编号和序列号1[complete.cases(仪器编号和序列号1$区域),]
+  
+  cname0<-c("仪器编号"  ,       "仪器序列号"  ,    
+            "SIM卡号"  ,        "发货时间"   ,      "仪器类型"   ,     
+            "总测试量"   ,      "最后一次开机时间" ,"时间差"   ,       
+            "开机地点"  ,       "网络类型" ,        "ip地址"    ,      
+            "用户"  ,           "用户CRM"   ,       "返利表序号"  ,    
+            "申请日期"  ,       "区域"     ,        "客户编码"  ,      
+            "代理商名称" ,      "用户名称"   ,      "规格" ,           
+            "状态")
+  #write_excel_csv(仪器编号和序列号all[,cname0],file="仪器编号和序列号all.csv")
+  write_excel_csv(仪器编号和序列号1[,cname0],file="仪器编号和序列号1.csv")
+  
+  mydb = dbConnect(MySQL(), user='root', password='My9521$$', dbname='和迈', host='192.168.11.223')
+  dbWriteTable(mydb, name='仪器编号和序列号1', value=仪器编号和序列号1)
+  dbDisconnect(mydb)
+  
+  write_excel_csv(仪器编号和序列号1e[,cname0],file="仪器编号和序列号1e.csv")
+  
+  mydb = dbConnect(MySQL(), user='root', password='My9521$$', dbname='和迈', host='192.168.11.223')
+  dbWriteTable(mydb, name='仪器编号和序列号1e', value=仪器编号和序列号1e)
+  dbDisconnect(mydb)
+  
+  Numberof区域<-length(unique(仪器编号和序列号1e$区域))
+  listOfUnique细胞<-""
+  for(j in 1:Numberof区域) listOfUnique细胞<-paste(listOfUnique细胞,unique(仪器编号和序列号1e$区域)[j],sep="___")
+  细胞<-data.frame(cbind(1:Numberof区域,unique(df2andInf$区域)))
+  colnames(细胞)<-c("ID","细胞")
+  
+  write_excel_csv(细胞,file="细胞.csv")
+  
+  细胞1<-细胞[str_length(细胞$细胞)<=3,]
+  
+  similiar<-str_like(细胞$细胞,paste(paste("%",细胞1$细胞[3],sep=""),"%",sep=""), ignore_case = TRUE)
+  细胞$细胞[30]
+  细胞$细胞[43]
+  细胞$细胞[30]<-细胞$细胞[43]
+  similiar<-str_like(细胞$细胞,paste(paste("%",细胞1$细胞[4],sep=""),"%",sep=""), ignore_case = TRUE)
+  细胞$细胞[9]
+  细胞$细胞[45]
+  细胞$细胞[45]<-细胞$细胞[9]
+  similiar<-str_like(细胞$细胞,paste(paste("%",细胞1$细胞[5],sep=""),"%",sep=""), ignore_case = TRUE)
+  细胞$细胞[17]
+  细胞$细胞[46]
+  细胞$细胞[46]<-细胞$细胞[17]
+  similiar<-str_like(细胞$细胞,paste(paste("%",细胞1$细胞[6],sep=""),"%",sep=""), ignore_case = TRUE)
+  细胞$细胞[11]
+  细胞$细胞[47]
+  细胞$细胞[47]<-细胞$细胞[11]
+  similiar<-str_like(细胞$细胞,paste(paste("%",细胞1$细胞[7],sep=""),"%",sep=""), ignore_case = TRUE)
+  细胞$细胞[14]
+  细胞$细胞[54]
+  细胞$细胞[54]<-细胞$细胞[14]
+  similiar<-str_like(细胞$细胞,paste(paste("%",细胞1$细胞[8],sep=""),"%",sep=""), ignore_case = TRUE)
+  细胞$细胞[63]
+  细胞$细胞[34]
+  细胞$细胞[63]<-细胞$细胞[34]
+  
+  unique(细胞$细胞)
+  仪器编号和序列号1m<-仪器编号和序列号1e
+  
+  仪器编号和序列号1m$区域[ str_like(仪器编号和序列号1m$区域,paste(paste("%",细胞1$细胞[3],sep=""),"%",sep=""), ignore_case = TRUE)]<-细胞$细胞[43]
+  仪器编号和序列号1m$区域[ str_like(仪器编号和序列号1m$区域,paste(paste("%",细胞1$细胞[4],sep=""),"%",sep=""), ignore_case = TRUE)]<-细胞$细胞[9]
+  仪器编号和序列号1m$区域[ str_like(仪器编号和序列号1m$区域,paste(paste("%",细胞1$细胞[5],sep=""),"%",sep=""), ignore_case = TRUE)]<-细胞$细胞[17]
+  仪器编号和序列号1m$区域[ str_like(仪器编号和序列号1m$区域,paste(paste("%",细胞1$细胞[6],sep=""),"%",sep=""), ignore_case = TRUE)]<-细胞$细胞[11]
+  仪器编号和序列号1m$区域[ str_like(仪器编号和序列号1m$区域,paste(paste("%",细胞1$细胞[7],sep=""),"%",sep=""), ignore_case = TRUE)]<-细胞$细胞[14]
+  仪器编号和序列号1m$区域[ str_like(仪器编号和序列号1m$区域,paste(paste("%",细胞1$细胞[8],sep=""),"%",sep=""), ignore_case = TRUE)]<-细胞$细胞[34]
+  
+  仪器编号和序列号$小细胞[str_like(仪器编号和序列号$小细胞,paste(paste("%","陈凯 华中",sep=""),"%",sep=""), ignore_case = TRUE)]<-"华中 陈凯"
+  
+  unique(仪器编号和序列号$小细胞)
+  
+  write_excel_csv(仪器编号和序列号1m[,cname0],file="仪器编号和序列号1m.csv")
+  
+  mydb = dbConnect(MySQL(), user='root', password='My9521$$', dbname='和迈', host='192.168.11.223')
+  dbWriteTable(mydb, name='仪器编号和序列号1m', value=仪器编号和序列号[,2:22])
+  dbDisconnect(mydb)
+  
+  Numberof区域<-length(unique(仪器编号和序列号1m$小细胞))
+  listOfUnique细胞<-""
+  for(j in 1:Numberof区域) listOfUnique细胞<-paste(listOfUnique细胞,unique(仪器编号和序列号1m$小细胞)[j],sep="___")
+  细胞m<-data.frame(cbind(1:Numberof区域,unique(df2andInf$小细胞)))
+  colnames(细胞m)<-c("ID","细胞")
+  
+  write_excel_csv(细胞m,file="细胞m.csv")
+}
+
+mydb = dbConnect(MySQL(), user='root', password='My9521$$', dbname='和迈', host='192.168.11.223')
+dbListTables(mydb)
+#dbListFields(mydb, '测试数据')
+
+#仪器编号和序列号all<-read.csv("仪器编号和序列号all.csv",encoding = "UTF-8",fill = TRUE)
+
+#仪器编号和序列号<-read.csv("仪器编号和序列号.csv",encoding = "UTF-8",fill = TRUE)
+rs = dbSendQuery(mydb, "select * from  和迈.仪器编号和序列号1m ")
+仪器编号和序列号 = fetch(rs, n=-1)
+仪器编号和序列号<-仪器编号和序列号[!duplicated(仪器编号和序列号[,c("仪器编号","仪器序列号" )]),]
+colnames(仪器编号和序列号)
+#仪器编号和序列号<-distinct(仪器编号和序列号[,2:22])
+#仪器编号和序列号<-read.csv("仪器编号和序列号.csv",encoding = "UTF-8",fill = TRUE)
+
+rs = dbSendQuery(mydb, "select * from  和迈.和迈测试数据 ")
+df2 = fetch(rs, n=-1)
+dbDisconnect(mydb)
+
+#df2 = fetch(rs, n=-1)
+#df2 <- read.csv("history06092025.csv",encoding = "UTF-8",fill = TRUE)
+colnames(df2)
+cname00<-c( "序号" ,        "项目号"   ,    "批次号" ,      "样品编号" ,  
+            "项目名称" ,    "批次名称" ,    "测试时间" ,    "浓度1"  ,     
+            "结论"  ,       "C值"   ,       "T值"  ,        "浓度2" ,      
+            "浓度3" ,       "结论2"  ,      "结论3"  ,      "样本类型"  ,  
+            "省市编号"  ,   "仪器序列号" ,  "T2值"  ,       "T3值"  ,      
+            "仪器备注名称", "仪器投放区域", "详细地址")
+df2<-distinct(df2[,cname00])
+df2$批次名称<-as.character(df2$批次名称)
+df2<-df2[!is.na(df2$批次名称),]
+
+df2andInf<-merge(df2,仪器编号和序列号[,c("仪器编号","仪器序列号","发货时间" ,"申请日期" ,       
+                                 "小细胞"   ,          "客户编码"   ,      "代理商名称" ,     
+                                 "用户名称" ,        "规格"   ,          "状态")],by="仪器序列号",all.x=TRUE,all.y=FALSE)
+
+df2andInf$省编号<-(df2andInf$省市编号 %/% 10000)*10000
+df2andInf$省名<-str_sub(df2andInf$详细地址,1,3)
+df2andInf$省名[str_length(df2andInf$省名)<3]<-NA
+
+df2andInf$省名[str_like(df2andInf$省编号,paste(paste("%","120000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"天津市"
+df2andInf$省名[str_like(df2andInf$省编号,paste(paste("%","230000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"黑龙江"
+df2andInf$省名[str_like(df2andInf$省编号,paste(paste("%","320000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"江苏省"
+df2andInf$省名[str_like(df2andInf$省编号,paste(paste("%","420000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"湖北省"
+df2andInf$省名[str_like(df2andInf$省编号,paste(paste("%","510000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"四川省"
+df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","重庆市",sep=""),"%",sep=""), ignore_case = TRUE)]<-"500000"
+df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","广西壮",sep=""),"%",sep=""), ignore_case = TRUE)]<-"450000"
+df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","江西省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"360000"
+df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","北京市",sep=""),"%",sep=""), ignore_case = TRUE)]<-"110000"
+df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","河北省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"130000"
+df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","上海市",sep=""),"%",sep=""), ignore_case = TRUE)]<-"310000"
+df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","浙江省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"330000"
+df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","四川省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"510000"
+df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","安徽省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"340000"
+df2andInf$省编号[str_like(df2andInf$省名,paste(paste("%","贵州省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"520000"
+
+df2andInf<-distinct(df2andInf)
+
+#df2andInf0<-df2andInf[str_c(df2andInf$仪器编号, df2andInf$仪器序列号)!=NA,]
+
+
+
+df2andInf$是否阳性<-df2andInf$结论
+df2andInf$是否阳性[df2andInf$是否阳性=="阳性"]<-1.0
+df2andInf$是否阳性[df2andInf$是否阳性=="阴性"]<-0.0
+df2andInf$是否阳性[df2andInf$是否阳性=="无效"]<-0.5
+df2andInf$是否阳性<-as.numeric(df2andInf$是否阳性)
+df2andInf$是否阳性[is.na(df2andInf$是否阳性)]<-0.5
+
+df2andInf$结论[df2andInf$结论=="阳性"]<-1.0
+df2andInf$结论[df2andInf$结论=="阴性"]<-0.0
+df2andInf$结论<-as.numeric(df2andInf$结论)
+
+df2andInf$是否有效<-1
+df2andInf$是否有效[df2andInf$是否阳性==0.5]<-0
+
+Numberof项目号<-length(unique(df2andInf$项目号))
+Numberof批次号<-length(unique(df2andInf$批次号))
+Numberof样品编号<-length(unique(df2andInf$样品编号))
+Numberof项目名称<-length(unique(df2andInf$项目名称))
+Numberof批次名称<-length(unique(df2andInf$批次名称))
+Numberof省编号<-length(unique(df2andInf$省编号))
+Numberof省名<-length(unique(df2andInf$省名))
+Numberof省市编号<-length(unique(df2andInf$省市编号))
+Numberof仪器序列号<-length(unique(df2andInf$仪器序列号))
+Numberof详细地址<-length(unique(df2andInf$详细地址))
+Numberof小细胞<-length(unique(df2andInf$小细胞))
+Numberof仪器备注名称<-length(unique(df2andInf$仪器备注名称))
+Numberof仪器投放区域<-length(unique(df2andInf$仪器投放区域))
+Numberof样本类型<-length(unique(df2andInf$样本类型))
+
+
+if(FALSE){
+  省编号and省名<-data.frame(cbind(df2andInf$省编号,df2andInf$省名))
+  colnames(省编号and省名)<-c("省编号","省名")
+  省编号and省名<-省编号and省名[!duplicated(省编号and省名),]
+  省编号and省名<-省编号and省名[order(省编号and省名$省编号),]
+  省编号and省名$省名[str_like(省编号and省名$省编号,paste(paste("%","120000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"天津市"
+  省编号and省名$省名[str_like(省编号and省名$省编号,paste(paste("%","230000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"黑龙江"
+  省编号and省名$省名[str_like(省编号and省名$省编号,paste(paste("%","320000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"江苏省"
+  省编号and省名$省名[str_like(省编号and省名$省编号,paste(paste("%","420000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"湖北省"
+  省编号and省名$省名[str_like(省编号and省名$省编号,paste(paste("%","510000",sep=""),"%",sep=""), ignore_case = TRUE)]<-"四川省"
+  省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","重庆市",sep=""),"%",sep=""), ignore_case = TRUE)]<-"500000"
+  省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","广西壮",sep=""),"%",sep=""), ignore_case = TRUE)]<-"450000"
+  省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","江西省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"360000"
+  省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","北京市",sep=""),"%",sep=""), ignore_case = TRUE)]<-"110000"
+  省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","河北省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"130000"
+  省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","上海市",sep=""),"%",sep=""), ignore_case = TRUE)]<-"310000"
+  省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","浙江省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"330000"
+  省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","四川省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"510000"
+  省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","安徽省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"340000"
+  省编号and省名$省编号[str_like(省编号and省名$省名,paste(paste("%","贵州省",sep=""),"%",sep=""), ignore_case = TRUE)]<-"520000"
+  省编号and省名<-省编号and省名[!duplicated(省编号and省名),]
+}
+
+summaryTable<-stri_join("Numberof测试: ",as.character(nrow(df2andInf)),
+                        "\nNumberof项目名称: ", as.character(Numberof项目名称),
+                        "\nNumberof批次号:  ",as.character(Numberof批次号), "  \n",
+                        "Numberof样品编号：  ",as.character(Numberof样品编号),"  \n",
+                        "Numberof批次名称:   ",as.character(Numberof批次名称),"  \n",
+                        "Numberof省编号:   ",as.character(Numberof省编号),"  \n",
+                        "Numberof省市编号:   ",as.character(Numberof省市编号),"  \n",
+                        "Numberof仪器序列号:   ",as.character(Numberof仪器序列号),"  \n",
+                        "Numberof详细地址:   ",as.character(Numberof详细地址),"  \n",
+                        "Numberof小细胞:   ",as.character(Numberof小细胞),"  \n",
+                        "Numberof样本类型:   ",as.character(Numberof样本类型),"  \n",sep="")
+小细胞<-unique(df2andInf$小细胞)
+Numberof小细胞<-length(小细胞)
+细胞<-data.frame(cbind(1:Numberof小细胞,小细胞))
+colnames(细胞)<-c("ID","细胞")
+细胞0<-细胞[!(str_like(细胞$细胞,paste(paste("%","内部",sep=""),"%",sep=""), ignore_case = TRUE) |
+            str_like(细胞$细胞,paste(paste("%","客服",sep=""),"%",sep=""), ignore_case = TRUE) |
+            str_like(细胞$细胞,paste(paste("%","医学",sep=""),"%",sep=""), ignore_case = TRUE)  ),]
+细胞0<-细胞0[!is.na(细胞0$细胞),]
+细胞0$ID<-1:nrow(细胞0)
+write_excel_csv(细胞0,file="细胞0.csv")
+
+summary(df2andInf$结论)
+summary(df2andInf$是否阳性)
+summary(df2andInf$是否有效)
+
+#df2andInf$仪器序列号_批次名称<-str_c(df2andInf$仪器序列号,'_',df2andInf$批次名称)
+
+
+colnames(df2andInf)
+#colnames(df00)
+#df2andInf00<-df2andInf0
+summary(df2andInf$仪器序列号)
+summary(df2andInf$批次名称)
+
+
+df20<-df2andInf #[,c(1:11,16,17,20)]
+df20$省编号<-str_c("省编号: ",df20$省编号)
+df20<-df20[complete.cases(df20$测试时间), ]
+df20<-df20[str_length(df20$测试时间)>10, ]
+
+
+colnames(df20)
+
+df20$浓度1<-as.numeric(df20$浓度1)
+df20$C值<-as.numeric(df20$C值)
+df20$T值<-as.numeric(df20$T值)
+df20$ToverC值<-df20$T值/df20$C值
+df20$ToverC值[df20$是否有效==0]<-NA
+
+summary(as.numeric(df20$结论))
+summary(df20$浓度1)
+summary(df20$ToverC值)
+
+summary(df20$testTimeFromeBegining)
+colnames(df20)
+
+
+df20$testMonth<-str_sub(df20$测试时间,1,7)
+
+#df20$testMonthinNumber<-as.numeric(str_c(str_sub(df20$测试时间,1,4),str_sub(df20$测试时间,6,7)))
+
+df20$testDay<-as.Date(str_sub(df20$测试时间,1,10))
+df20<-df20[df20$testDay<="2025-06-05", ]
+#df20<-df20[df20$testDay<=Sys.Date(), ]
+
+df20<-df20[complete.cases(df20$testDay), ]
+
+summary(df20$testDay)
+
+df20$testTime<-as.datetime(str_sub(df20$测试时间,1,19),format='%Y-%m-%d %H:%M:%S')
+
+duration<-(max(df20$testTime,na.rm = TRUE)-min(df20$testTime,na.rm = TRUE))/(60.*60.*24.)
+
+df20$testTimeFromeToday<-(max(df20$testTime,na.rm = TRUE)-df20$testTime)/(60.*60.*24.)+1.
+#max0<-max(df20$testTime,na.rm=TRUE)
+#min0<-min(df20$testTime,na.rm=TRUE)
+
+#unique(dfBy样本$样本类型)
+#max0-min0
+
+#max(df20$testDay,na.rm=TRUE)
+#min(df20$testDay,na.rm=TRUE)
+
+#clean_df <- df20[complete.cases(df20[,c("小细胞")]), ]
+#summary(clean_df)
+
+
+summary(df20$testTimeFromeToday)
+dayMax<-max(df20$testTimeFromeToday,na.rm = TRUE)
+
+
+df2000<-df20
+df20<-df20[df20$testTimeFromeToday<=730,]
+#df20<-df20[complete.cases(df20$测试时间), ]
+lastDay<-max(df20$testDay,na.rm = TRUE)
+df20dayLast21<-df20[lastDay-df20$testDay<21,]
+
+
+dfByDay <- df2000 %>%  group_by(testMonth,testDay) %>%  summarise(
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  小细胞数=length(unique(小细胞)),
+  市数=length(unique(省市编号)),
+  省数=length(unique(省编号))
+)
+dfByDay$阳性率<-round(dfByDay$阳性数/dfByDay$有效数,3)
+dfByDay$有效率<-round(dfByDay$有效数/dfByDay$测试数,3)
+dfByDay$阳性数<-as.integer(dfByDay$阳性数)
+dfByDay$测试数<-as.integer(dfByDay$测试数)
+dfByDay$有效数<-as.integer(dfByDay$有效数)
+dfByDay$省数<-as.integer(dfByDay$省数)
+dfByDay <- dfByDay[order(lastDay-dfByDay$testDay),]
+#dfByDay <- dfByDay[lastDay-dfByDay$testDay<42,]
+#dfByDay<-dfByDay[lastDay-dfByDay$testDay<=21,]
+
+write_excel_csv(dfByDay,file="按日统计0.csv")
+
+dfByMonth <- df2000 %>%  group_by(testMonth) %>%  summarise(
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  小细胞数=length(unique(小细胞)),
+  市数=length(unique(省市编号)),
+  省数=length(unique(省编号))
+)
+dfByMonth$阳性率<-round(dfByMonth$阳性数/dfByMonth$有效数,3)
+dfByMonth$有效率<-round(dfByMonth$有效数/dfByMonth$测试数,3)
+dfByMonth$阳性数<-as.integer(dfByMonth$阳性数)
+dfByMonth$测试数<-as.integer(dfByMonth$测试数)
+dfByMonth$有效数<-as.integer(dfByMonth$有效数)
+dfByMonth$省数<-as.integer(dfByMonth$省数)
+dfByMonth <- dfByMonth[order(dfByMonth$testMonth),]
+dfByMonth <- dfByMonth[nrow(dfByMonth):1,]
+
+write_excel_csv(dfByMonth,file="按月统计0.csv")
+
+dfBy项目 <- df2000 %>%  group_by(项目名称) %>%  summarise(
+  
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  小细胞数=length(unique(小细胞)),
+  市数=length(unique(省市编号)),
+  省数=length(unique(省编号)),
+  
+  测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
+  测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
+)
+dfBy项目$阳性率<-round(dfBy项目$阳性数/dfBy项目$有效数,3)
+dfBy项目$有效率<-round(dfBy项目$有效数/dfBy项目$测试数,3)
+dfBy项目$阳性数<-as.integer(dfBy项目$阳性数)
+dfBy项目$测试数<-as.integer(dfBy项目$测试数)
+dfBy项目$有效数<-as.integer(dfBy项目$有效数)
+dfBy项目 <- dfBy项目[order(-dfBy项目$测试数),]
+write_excel_csv(dfBy项目,file="按项目统计0.csv")
+
+dfBy样本 <- df2000 %>%  group_by(样本类型) %>%  summarise(
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  小细胞数=length(unique(小细胞)),
+  市数=length(unique(省市编号)),
+  省数=length(unique(省编号)),
+  测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
+  测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
+)
+dfBy样本$阳性率<-round(dfBy样本$阳性数/dfBy样本$有效数,3)
+dfBy样本$有效率<-round(dfBy样本$有效数/dfBy样本$测试数,3)
+dfBy样本$阳性数<-as.integer(dfBy样本$阳性数)
+dfBy样本$测试数<-as.integer(dfBy样本$测试数)
+dfBy样本$有效数<-as.integer(dfBy样本$有效数)
+dfBy样本 <- dfBy样本[order(-dfBy样本$测试数),]
+write_excel_csv(dfBy样本,file="按样本统计0.csv")
+
+dfBy细胞 <- df2000 %>%  group_by(小细胞) %>%  summarise(
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  小细胞数=length(unique(小细胞)),
+  市数=length(unique(省市编号)),
+  省数=length(unique(省编号)),
+  测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
+  测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
+)
+dfBy细胞$阳性率<-round(dfBy细胞$阳性数/dfBy细胞$有效数,3)
+dfBy细胞$有效率<-round(dfBy细胞$有效数/dfBy细胞$测试数,3)
+dfBy细胞$阳性数<-as.integer(dfBy细胞$阳性数)
+dfBy细胞$测试数<-as.integer(dfBy细胞$测试数)
+dfBy细胞$有效数<-as.integer(dfBy细胞$有效数)
+dfBy细胞 <- dfBy细胞[order(-dfBy细胞$测试数),]
+write_excel_csv(dfBy细胞,file="按细胞统计0.csv")
+
+dfBy区域 <- df2000 %>%  group_by(省编号) %>%  summarise(
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  小细胞数=length(unique(小细胞)),
+  市数=length(unique(省市编号)),
+  省数=length(unique(省编号)),
+  测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
+  测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
+)
+dfBy区域$阳性率<-round(dfBy区域$阳性数/dfBy区域$有效数,3)
+dfBy区域$有效率<-round(dfBy区域$有效数/dfBy区域$测试数,3)
+dfBy区域$阳性数<-as.integer(dfBy区域$阳性数)
+dfBy区域$测试数<-as.integer(dfBy区域$测试数)
+dfBy区域$有效数<-as.integer(dfBy区域$有效数)
+dfBy区域 <- dfBy区域[order(-dfBy区域$测试数),]
+write_excel_csv(dfBy区域,file="按区域统计0.csv")
+
+省编号<-dfBy区域$省编号
+省编号0<-省编号[str_length(省编号)>8]
+dfBy区域<-dfBy区域[dfBy区域$省编号  %in% 省编号0,]
+
+dfBy批次 <- df2000 %>%  group_by(批次名称) %>%  summarise(
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  小细胞数=length(unique(小细胞)),
+  市数=length(unique(省市编号)),
+  省数=length(unique(省编号)),
+  最早测试=min(testDay,na.rm = TRUE),
+  最近测试=max(testDay,na.rm = TRUE),
+  测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
+  测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
+)
+dfBy批次$阳性率<-round(dfBy批次$阳性数/dfBy批次$有效数,3)
+dfBy批次$有效率<-round(dfBy批次$有效数/dfBy批次$测试数,3)
+dfBy批次$阳性数<-as.integer(dfBy批次$阳性数)
+dfBy批次$测试数<-as.integer(dfBy批次$测试数)
+dfBy批次$有效数<-as.integer(dfBy批次$有效数)
+dfBy批次$省数<-as.integer(dfBy批次$省数)
+dfBy批次 <- dfBy批次[order(-dfBy批次$测试数),]
+write_excel_csv(dfBy批次,file="按批次统计0.csv")
+
+df20001<-cbind(df2000,IDIndex=1:nrow(df2000))
+dfBy仪器 <- df20001 %>%  group_by(仪器序列号) %>%  summarise(
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  小细胞数=length(unique(小细胞)),
+  市数=length(unique(省市编号)),
+  省数=length(unique(省编号)),
+  earliestIndex=min(IDIndex),
+  medianIndex=median(IDIndex),
+  latestIndex=max(IDIndex),
+  最早测试=min(testDay,na.rm = TRUE),
+  最近测试=max(testDay,na.rm = TRUE),
+  测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
+  测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
+)
+dfBy仪器$阳性率<-round(dfBy仪器$阳性数/dfBy仪器$有效数,3)
+dfBy仪器$有效率<-round(dfBy仪器$有效数/dfBy仪器$测试数,3)
+dfBy仪器$阳性数<-as.integer(dfBy仪器$阳性数)
+dfBy仪器$测试数<-as.integer(dfBy仪器$测试数)
+dfBy仪器$有效数<-as.integer(dfBy仪器$有效数)
+
+dfBy仪器$最早测试地点<-df2000$详细地址[dfBy仪器$earliestIndex]
+dfBy仪器$中期测试地点<-df2000$详细地址[dfBy仪器$medianIndex]
+dfBy仪器$最后测试地点<-df2000$详细地址[dfBy仪器$latestIndex]
+dfBy仪器 <- dfBy仪器[order(-dfBy仪器$测试数),]
+cname0<-c( "仪器序列号"  ,"最早测试地点","中期测试地点", "最后测试地点",      
+           "批次数"  ,   "测试数"  ,   "样本数"  ,   "项目数" ,   
+           "阳性数",     "有效数"  ,   "最早测试" ,  "最近测试" ,  "测试开始" , 
+           "测试截止",   "阳性率" ,    "有效率") 
+
+write_excel_csv(dfBy仪器[,cname0],file="按仪器统计0.csv")
+
+cname0<-c( "仪器序列号"  ,"仪器编号"  ,"最早测试地点","中期测试地点", "最后测试地点",      
+           "开机地点"  ,  "批次数"  ,   "测试数"  ,   "样本数"  ,   "项目数" ,   
+           "阳性数",     "有效数"  ,   "最早测试" ,  "最近测试" ,  "测试开始" , 
+           "测试截止",   "阳性率" ,    "有效率",  
+           "SIM卡号"  ,        "发货时间"   ,      "仪器类型"   ,     
+           "总测试量"   ,      "最后一次开机时间" ,"时间差"   ,       
+           "网络类型" ,        "ip地址"    ,      
+           "用户"  ,           "用户CRM"   ,       "返利表序号"  ,    
+           "申请日期"  ,       "小细胞"     ,        "客户编码"  ,      
+           "代理商名称" ,      "用户名称"   ,      "规格" ,           
+           "状态")
+colnames(dfBy仪器)
+dfBy仪器andInf<-merge(dfBy仪器,仪器编号和序列号,by="仪器序列号",all.x=TRUE,all.y=FALSE)
+colnames(dfBy仪器andInf)
+dfBy仪器andInf <- dfBy仪器andInf[order(-dfBy仪器andInf$测试截止),][,cname0]
+#dfBy仪器andInf0<-distinct(dfBy仪器andInf)
+write_excel_csv(dfBy仪器andInf,file="仪器统计andInf.csv")
+dfBy仪器andInfall<-merge(dfBy仪器,仪器编号和序列号,by="仪器序列号",all.x=TRUE,all.y=TRUE)
+dfBy仪器andInfall <- dfBy仪器andInfall[order(-dfBy仪器andInfall$测试截止),][,cname0]
+#dfBy仪器andInfall0<-distinct(dfBy仪器andInfall)
+write_excel_csv(dfBy仪器andInfall,file="仪器统计andInfall.csv")
+colnames(仪器编号和序列号)
+notFound<-仪器编号和序列号[!(仪器编号和序列号$仪器序列号 %in% dfBy仪器$仪器序列号),]
+
+colnames(notFound)
+
+cname1<-c( "仪器序列号"  ,"仪器编号"  ,     
+           "开机地点"  ,  
+           "SIM卡号"  ,        "发货时间"   ,      "仪器类型"   ,     
+           "总测试量"   ,      "最后一次开机时间" ,"时间差"   ,       
+           "网络类型" ,        "ip地址"    ,      
+           "用户"  ,           "用户CRM"   ,       "返利表序号"  ,    
+           "申请日期"  ,       "小细胞"     ,        "客户编码"  ,      
+           "代理商名称" ,      "用户名称"   ,      "规格" ,           
+           "状态")
+#notFound[,cname1]
+#notFound0<-distinct(notFound)
+write_excel_csv(notFound[,cname1],file="仪器统计Notfound.csv")
+
+if(FALSE) {
+  CRMNotFound <- read.csv("CRMNotFound.csv",encoding = "UTF-8",fill = TRUE)
+  NoTestSince05012025 <- read.csv("NoTestSince05012025.csv",encoding = "UTF-8",fill = TRUE)
+  colnames(CRMNotFound)[c(3,4,5)]<-c("销售申请时间NoCRM","销售申请区域NoCRM","销售申请时代理商名称NoCRM")
+  colnames(NoTestSince05012025) [9]<-"备注NoTest"
+  
+  feedbackData<-merge(CRMNotFound,NoTestSince05012025,by="仪器编号",all.x=TRUE,all.y=TRUE)
+  colnames(feedbackData)
+  colnames(feedbackData)[10]<-"用户onCRM"
+  
+  write_excel_csv(feedbackData,file="feedbackData07042025.csv")
+  仪器编号和序列号feedbackData<-merge(仪器编号和序列号,feedbackData,by="仪器编号",all.x=TRUE,all.y=TRUE)
+  colnames(仪器编号和序列号feedbackData)
+  
+  dfBy仪器feedbackDataandInf<-merge(dfBy仪器,仪器编号和序列号feedbackData,by="仪器序列号",all.x=TRUE,all.y=FALSE)
+  colnames(dfBy仪器feedbackDataandInf)
+  cname0<-c( "仪器序列号"  ,"仪器编号"  ,"最早测试地点","中期测试地点", "最后测试地点",      
+             "开机地点"  ,  "批次数"  ,   "测试数"  ,   "样本数"  ,   "项目数" ,   
+             "阳性数",     "有效数"  ,   "最早测试" ,  "最近测试" ,  "测试开始" , 
+             "测试截止",   "阳性率" ,    "有效率",  
+             "SIM卡号"  ,        "发货时间"   ,      "仪器类型"   ,     
+             "总测试量"   ,      "最后一次开机时间" ,"时间差"   ,       
+             "网络类型" ,        "ip地址"    ,      
+             "用户"  ,           "用户CRM"   ,       "返利表序号"  ,    
+             "申请日期"  ,       "小细胞"     ,        "客户编码"  ,      
+             "代理商名称" ,      "用户名称"   ,      "规格" ,           
+             "状态","销售申请时间" ,             "销售申请时间NoCRM"   ,     
+             "销售申请区域NoCRM"   ,      "销售申请时代理商名称NoCRM",
+             "是否装机" ,                 "未装机原因"  ,             
+             "备注"   ,                   "最后测试时间"  ,           
+             "用户onCRM"     ,            "销售申请日期"   ,          
+             "销售申请区域"   ,           "销售申请时代理商名称"  ,   
+             "销售申请时用户名称"    ,    "无测试原因"  ,             
+             "备注NoTest"   )
+  dfBy仪器feedbackDataandInf <- dfBy仪器feedbackDataandInf[order(-dfBy仪器feedbackDataandInf$测试截止),][,cname0]
+  write_excel_csv(dfBy仪器feedbackDataandInf,file="仪器统计feedbackandInf.csv")
+  dfBy仪器feedbackDataandInfall<-merge(dfBy仪器,仪器编号和序列号feedbackData,by="仪器序列号",all.x=TRUE,all.y=TRUE)
+  dfBy仪器feedbackDataandInfall <- dfBy仪器feedbackDataandInfall[order(-dfBy仪器feedbackDataandInfall$测试截止),][,cname0]
+  write_excel_csv(dfBy仪器feedbackDataandInfall,file="仪器统计feedbackandInfall.csv")
+  colnames(仪器编号和序列号feedbackData)
+  notFoundfeedBack<-仪器编号和序列号feedbackData[!(仪器编号和序列号feedbackData$仪器序列号 %in% dfBy仪器$仪器序列号),]
+  
+  cname1<-c( "仪器序列号"  ,"仪器编号"  ,     
+             "开机地点"  ,  
+             "SIM卡号"  ,        "发货时间"   ,      "仪器类型"   ,     
+             "总测试量"   ,      "最后一次开机时间" ,"时间差"   ,       
+             "网络类型" ,        "ip地址"    ,      
+             "用户"  ,           "用户CRM"   ,       "返利表序号"  ,    
+             "申请日期"  ,       "小细胞"     ,        "客户编码"  ,      
+             "代理商名称" ,      "用户名称"   ,      "规格" ,           
+             "状态","销售申请时间" ,             "销售申请时间NoCRM"   ,     
+             "销售申请区域NoCRM"   ,      "销售申请时代理商名称NoCRM",
+             "是否装机" ,                 "未装机原因"  ,             
+             "备注"   ,                   "最后测试时间"  ,           
+             "用户onCRM"     ,            "销售申请日期"   ,          
+             "销售申请区域"   ,           "销售申请时代理商名称"  ,   
+             "销售申请时用户名称"    ,    "无测试原因"  ,             
+             "备注NoTest" )
+  
+  colnames(notFoundfeedBack)
+  
+  write_excel_csv(notFoundfeedBack[,cname1],file="仪器统计NotfoundfeedBack.csv")
+}
+
+dfByDayAndLocation <- df2000 %>%  group_by(testDay,testMonth,省编号) %>%  summarise(
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  小细胞数=length(unique(小细胞)),
+  市数=length(unique(省市编号)),
+  省数=length(unique(省编号))
+)
+dfByDayAndLocation$阳性率<-round(dfByDayAndLocation$阳性数/dfByDayAndLocation$有效数,3)
+dfByDayAndLocation$有效率<-round(dfByDayAndLocation$有效数/dfByDayAndLocation$测试数,3)
+dfByDayAndLocation$阳性数<-as.integer(dfByDayAndLocation$阳性数)
+dfByDayAndLocation$测试数<-as.integer(dfByDayAndLocation$测试数)
+dfByDayAndLocation$有效数<-as.integer(dfByDayAndLocation$有效数)
+dfByDayAndLocation <- dfByDayAndLocation[order(dfByDayAndLocation$testDay),]
+dfByDayAndLocation<-dfByDayAndLocation[dfByDayAndLocation$省编号  %in% 省编号0,]
+
+dfByMonthAndLocation <- df20 %>%  group_by(testMonth,省编号) %>%  summarise(
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  小细胞数=length(unique(小细胞)),
+  市数=length(unique(省市编号)),
+  省数=length(unique(省编号))
+)
+dfByMonthAndLocation$阳性率<-round(dfByMonthAndLocation$阳性数/dfByMonthAndLocation$有效数,3)
+dfByMonthAndLocation$有效率<-round(dfByMonthAndLocation$有效数/dfByMonthAndLocation$测试数,3)
+dfByMonthAndLocation$阳性数<-as.integer(dfByMonthAndLocation$阳性数)
+dfByMonthAndLocation$测试数<-as.integer(dfByMonthAndLocation$测试数)
+dfByMonthAndLocation$有效数<-as.integer(dfByMonthAndLocation$有效数)
+dfByMonthAndLocation <- dfByMonthAndLocation[order(dfByMonthAndLocation$testMonth),]
+dfByMonthAndLocation<-dfByMonthAndLocation[dfByMonthAndLocation$省编号  %in% 省编号0,]
+
+dfByDayAnd细胞 <- df2000 %>%  group_by(testDay,testMonth,小细胞) %>%  summarise(
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  小细胞数=length(unique(小细胞)),
+  市数=length(unique(省市编号)),
+  省数=length(unique(省编号))
+)
+dfByDayAnd细胞$阳性率<-round(dfByDayAnd细胞$阳性数/dfByDayAnd细胞$有效数,3)
+dfByDayAnd细胞$有效率<-round(dfByDayAnd细胞$有效数/dfByDayAnd细胞$测试数,3)
+dfByDayAnd细胞$阳性数<-as.integer(dfByDayAnd细胞$阳性数)
+dfByDayAnd细胞$测试数<-as.integer(dfByDayAnd细胞$测试数)
+dfByDayAnd细胞$有效数<-as.integer(dfByDayAnd细胞$有效数)
+dfByDayAnd细胞 <- dfByDayAnd细胞[order(dfByDayAnd细胞$testDay),]
+
+dfByMonthAnd细胞 <- df20 %>%  group_by(testMonth,小细胞) %>%  summarise(
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  小细胞数=length(unique(小细胞)),
+  市数=length(unique(省市编号)),
+  省数=length(unique(省编号))
+)
+dfByMonthAnd细胞$阳性率<-round(dfByMonthAnd细胞$阳性数/dfByMonthAnd细胞$有效数,3)
+dfByMonthAnd细胞$有效率<-round(dfByMonthAnd细胞$有效数/dfByMonthAnd细胞$测试数,3)
+dfByMonthAnd细胞$阳性数<-as.integer(dfByMonthAnd细胞$阳性数)
+dfByMonthAnd细胞$测试数<-as.integer(dfByMonthAnd细胞$测试数)
+dfByMonthAnd细胞$有效数<-as.integer(dfByMonthAnd细胞$有效数)
+dfByMonthAnd细胞 <- dfByMonthAnd细胞[order(dfByMonthAnd细胞$testMonth),]
+
+dfByDayAnd仪器 <- df2000 %>%  group_by(testDay,testMonth,仪器序列号) %>%  summarise(
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  小细胞数=length(unique(小细胞)),
+  市数=length(unique(省市编号)),
+  省数=length(unique(省编号))
+)
+dfByDayAnd仪器$阳性率<-round(dfByDayAnd仪器$阳性数/dfByDayAnd仪器$有效数,3)
+dfByDayAnd仪器$有效率<-round(dfByDayAnd仪器$有效数/dfByDayAnd仪器$测试数,3)
+dfByDayAnd仪器$阳性数<-as.integer(dfByDayAnd仪器$阳性数)
+dfByDayAnd仪器$测试数<-as.integer(dfByDayAnd仪器$测试数)
+dfByDayAnd仪器$有效数<-as.integer(dfByDayAnd仪器$有效数)
+dfByDayAnd仪器 <- dfByDayAnd仪器[order(dfByDayAnd仪器$testDay),]
+
+dfByMonthAnd仪器 <- df20 %>%  group_by(testMonth,仪器序列号) %>%  summarise(
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  小细胞数=length(unique(小细胞)),
+  市数=length(unique(省市编号)),
+  省数=length(unique(省编号))
+)
+dfByMonthAnd仪器$阳性率<-round(dfByMonthAnd仪器$阳性数/dfByMonthAnd仪器$有效数,3)
+dfByMonthAnd仪器$有效率<-round(dfByMonthAnd仪器$有效数/dfByMonthAnd仪器$测试数,3)
+dfByMonthAnd仪器$阳性数<-as.integer(dfByMonthAnd仪器$阳性数)
+dfByMonthAnd仪器$测试数<-as.integer(dfByMonthAnd仪器$测试数)
+dfByMonthAnd仪器$有效数<-as.integer(dfByMonthAnd仪器$有效数)
+dfByMonthAnd仪器 <- dfByMonthAnd仪器[order(dfByMonthAnd仪器$testMonth),]
+
+仪器号List0<-cbind(dfBy仪器,GroupID=rep00[1:length(dfBy仪器$仪器序列号)])
+仪器号List<-仪器号List0[,c(1,ncol(仪器号List0))]
+仪器号ikmax<-max(仪器号List$GroupID)
+dfBy仪器$仪器序列号<-factor(dfBy仪器$仪器序列号,levels = 仪器号List[,1])
+批次号List0<-cbind(dfBy批次,GroupID=rep00[1:length(dfBy批次$批次名称)])
+批次号List<-批次号List0[,c(1,ncol(批次号List0))]
+批次号ikmax<-max(批次号List$GroupID)
+dfBy批次$批次名称<-factor(dfBy批次$批次名称,levels = 批次号List[,1])
+项目号List0<-cbind(dfBy项目,GroupID=rep00[1:length(dfBy项目$项目名称)])
+项目号List<-项目号List0[,c(1,ncol(项目号List0))]
+项目号ikmax<-max(项目号List$GroupID)
+dfBy项目$项目名称<-factor(dfBy项目$项目名称,levels = 项目号List[,1])
+
+# 图表生成函数
+dfByDay1<-dfByDay[lastDay-dfByDay$testDay<42,]
+dfByDayAndLocation1<-dfByDayAndLocation[lastDay-dfByDayAndLocation$testDay<42,]
+dfByMonth1<-dfByMonth[1:30,]
+
+dfByDayAnd细胞1<-dfByDayAnd细胞[lastDay-dfByDayAnd细胞$testDay<42,]
+
+lenhalf<-length(dfBy细胞$小细胞)/2
+dfBy细胞1<-dfBy细胞[dfBy细胞$小细胞 %in% dfBy细胞$小细胞[1:lenhalf],]
+dfBy细胞2<-dfBy细胞[dfBy细胞$小细胞 %in% dfBy细胞$小细胞[(1+lenhalf):length(dfBy细胞$小细胞)],]
+
+
+generate_data_table <- function(dim, metric) {
+  data <- switch(dim,
+                 "按月统计" = read_csv("按月统计0.csv"),
+                 "最后六周按日统计" = read_csv("按日统计0.csv"),
+                 "按小细胞统计"=read_csv("按细胞统计0.csv"),
+                 "按省统计" = read_csv("按区域统计0.csv"),
+                 "按仪器统计" = read_csv("按仪器统计0.csv"),
+                 "按样本类型统计" = read_csv("按样本统计0.csv"),
+                 "按试剂批次统计" = read_csv("按批次统计0.csv"),
+                 "按试剂项目统计" = read_csv("按项目统计0.csv"))
+
+ 
+  metrics <- switch(metric,
+                    "测试数、阳性数、有效数" = c("测试数", "阳性数", "有效数"),
+                    "阳性率、有效率" = c("阳性率", "有效率"),
+                    "项目数、仪器数、批次数" = c("批次数", "项目数", "仪器数"),
+                    "省数、市数、小细胞数、样本数" = c("省数", "市数", "小细胞数","样本数"),
+                    "测试截止、测试开始" = c("测试截止", "测试开始"))
+  
+  
+  data %>% select(all_of(metrics))
+}
+
+generate_plot <- function(data, dim, metric, way, page = 1) {
+  
+  max_pages <- switch(dim,
+                      "最后六周按日统计" = {
+                        if (way == "按日分省统计") {
+                          ceiling(length(dfBy区域$省编号) / 6)
+                        } else if (way == "按日分小细胞统计") {
+                          ceiling(length(细胞0$细胞) / 6)
+                        } else if (way == "按日分仪器统计") {
+                          ceiling(length(仪器号List$仪器序列号) / 6)
+                        } else 1
+                      },
+                      "按月统计" = {
+                        if (way == "按月分省统计") {
+                          ceiling(length(dfBy区域$省编号) / 6)
+                        } else if (way == "按月分小细胞统计") {
+                          ceiling(length(细胞0$细胞) / 6)
+                        } else if (way == "按月分仪器统计") {
+                          ceiling(length(仪器号List$仪器序列号) / 6)
+                        } else 1
+                      },
+                      "按仪器统计"     = max(仪器号List$GroupID),
+                      "按试剂批次统计" = max(批次号List$GroupID),
+                      "按试剂项目统计" = max(项目号List$GroupID),
+                      "按小细胞统计" = 2,
+                      1)
+  
+#  cat(page)
+  per    <- 6    # 每页子图数量
+  if(!is.numeric(page)) {
+    page<-1
+    offset<-0 
+    } else {
+      if(page>max_pages)  page<-max_pages
+      offset<- (page - 1) * per        # 起始下标
+    }
+ # offset<-6
+
+  # ---- 函数内部的小工具：切片 ----
+  slice_vec <- function(vec, offset, per) {
+    vec[ (offset + 1) : min(offset + per, length(vec)) ]
+  }
+  
+ # cat("1,", page)
+  # ---- 开始分发 ----
+  p <- switch(dim,
+              
+              # ---------- 1. 最后六周按日统计 ----------
+              "最后六周按日统计" = {
+                switch(way,
+                       "按日分省统计" = {
+                         choosenList <- slice_vec(dfBy区域$省编号, offset, per)
+                         if(length(choosenList) == 0) return(NULL)
+                         switch(metric,
+                                "测试数、阳性数、有效数" = {
+                                  panelPlotByDayAndLocation(dfByDayAndLocation1, choosenList,
+                                                            "testDay", "省编号",
+                                                            c("测试数","有效数","阳性数"),
+                                                            c("最后六周按日分省统计","测试时间","统计数值",""))
+                                },
+                                "阳性率、有效率" = {
+                                  panelPlotByDayAndLocation(dfByDayAndLocation1, choosenList,
+                                                            "testDay", "省编号",
+                                                            c("有效率","阳性率"),
+                                                            c("最后六周按日分省统计","测试时间","统计数值",""))
+                                },
+                                "项目数、仪器数、批次数" = {
+                                  panelPlotByDayAndLocation(dfByDayAndLocation1, choosenList,
+                                                            "testDay", "省编号",
+                                                            c("项目数","仪器数","批次数"),
+                                                            c("最后六周按日分省统计","测试时间","统计数值",""))
+                                },
+                                "省数、市数、小细胞数、样本数" = {
+                                  panelPlotByDayAndLocation(dfByDayAndLocation1, choosenList,
+                                                            "testDay", "省编号",
+                                                            c("样本数","市数","小细胞数"),
+                                                            c("最后六周按日分省统计","测试时间","统计数值",""))
+                                }
+                         )
+                       },
+                       "按日分小细胞统计" = {
+                         choosenList <- slice_vec(细胞0$细胞, offset, per)
+                         if(length(choosenList) == 0) return(NULL)
+                         switch(metric,
+                                "测试数、阳性数、有效数" = {
+                                  panelPlotByDayAnd细胞(dfByDayAnd细胞1, choosenList,
+                                                      "testDay", "小细胞",
+                                                      c("测试数","有效数","阳性数"),
+                                                      c("最后六周按日分小细胞统计","测试时间","统计数值",""))
+                                },
+                                "阳性率、有效率" = {
+                                  panelPlotByDayAnd细胞(dfByDayAnd细胞1, choosenList,
+                                                      "testDay", "小细胞",
+                                                      c("有效率","阳性率"),
+                                                      c("最后六周按日分小细胞统计","测试时间","统计数值",""))
+                                },
+                                "项目数、仪器数、批次数" = {
+                                  panelPlotByDayAnd细胞(dfData=dfByDayAnd细胞1,choosenList,independentVariableName="testDay",panelName="小细胞",
+                                                      dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("最后六周按日分小细胞统计","测试时间","统计数值",""))
+                                },
+                                "省数、市数、小细胞数、样本数" = {
+                                  panelPlotByDayAnd细胞(dfData=dfByDayAnd细胞1,choosenList,independentVariableName="testDay",panelName="小细胞",
+                                                      dependentVariableNames=c("样本数","市数","省数"),titleNames=c("最后六周按日分小细胞统计","测试时间","统计数值",""))
+                                }                            
+                                
+                         )
+                       },
+                       "按日分仪器统计" = {
+                         choosenList <- slice_vec(仪器号List$仪器序列号, offset, per)
+                         if(length(choosenList) == 0) return(NULL)
+                         switch(metric,
+                                "测试数、阳性数、有效数" = {
+                                  panelPlotByDayAnd仪器(dfData=dfByDayAnd仪器,choosenList,independentVariableName="testDay",panelName="仪器序列号",
+                                                      dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日分仪器统计","测试时间","统计数值",""))
+                                },
+                                "阳性率、有效率" = {
+                                  panelPlotByDayAnd仪器(dfData=dfByDayAnd仪器,choosenList,independentVariableName="testDay",panelName="仪器序列号",
+                                                      dependentVariableNames=c("有效率","阳性率"),titleNames=c("最后六周按日分仪器统计","测试时间","统计数值",""))
+ 
+                                },
+                                "项目数、仪器数、批次数" = {
+                                  panelPlotByDayAnd仪器(dfData=dfByDayAnd仪器,choosenList,independentVariableName="testDay",panelName="仪器序列号",
+                                                      dependentVariableNames=c("项目数","批次数"),titleNames=c("最后六周按日分仪器统计","测试时间","统计数值",""))
+                                },
+                                "省数、市数、小细胞数、样本数" = {
+                                  panelPlotByDayAnd仪器(dfData=dfByDayAnd仪器,choosenList,independentVariableName="testDay",panelName="仪器序列号",
+                                                      dependentVariableNames=c("样本数","市数","省数","小细胞数"),titleNames=c("最后六周按日分仪器统计","测试时间","统计数值",""))
+                               }
+                                
+                                
+                         )
+                       },
+                       "全部统计" = {
+                         switch(metric,
+                                "测试数、阳性数、有效数" =
+                                  plotfunction(dfByDay1, "testDay", c("测试数","有效数","阳性数"),
+                                               c("最后六周按日统计","测试时间","统计数值","")),
+                                "阳性率、有效率" =
+                                  plotfunction(dfByDay1, "testDay", c("有效率","阳性率"),
+                                               c("最后六周按日统计","测试时间","统计数值","")),
+                                "项目数、仪器数、批次数" =
+                                  plotfunction(dfByDay1, "testDay", c("项目数","仪器数","批次数"),
+                                               c("最后六周按日统计","测试时间","统计数值","")),
+                                "省数、市数、小细胞数、样本数" =
+                                  plotfunction(dfByDay1, "testDay", c("样本数","市数","省数","小细胞数"),
+                                               c("最后六周按日统计","测试时间","统计数值",""))
+                         )
+                       }
+                )
+              },
+              
+              # ---------- 2. 按月统计 ----------
+              "按月统计" = {
+                switch(way,
+                       "按月分省统计" = {
+                         choosenList <- slice_vec(dfBy区域$省编号, offset, per)
+                         if(length(choosenList) == 0) return(NULL)
+                       switch(metric,
+                              "测试数、阳性数、有效数" = {
+                                panelPlotByMonthAndLocation(dfByMonthAndLocation, choosenList,
+                                                            "testMonth", "省编号",
+                                                            c("测试数","有效数","阳性数"),
+                                                            c("按月分省统计","测试时间","统计数值",""))
+                              },
+                              "阳性率、有效率" = {
+                                panelPlotByMonthAndLocation(dfByMonthAndLocation, choosenList,
+                                                            "testMonth", "省编号",
+                                                            c("有效率","阳性率"),
+                                                            c("按月分省统计","测试时间","统计数值",""))
+                              },
+                              "项目数、仪器数、批次数" = {
+                                panelPlotByMonthAndLocation(dfByMonthAndLocation, choosenList,
+                                                            "testMonth", "省编号",
+                                                            c("项目数","仪器数","批次数"),
+                                                            c("按月分省统计","测试时间","统计数值",""))
+                              },
+                              "省数、市数、小细胞数、样本数" = {
+                                panelPlotByMonthAndLocation(dfByMonthAndLocation, choosenList,
+                                                            "testMonth", "省编号",
+                                                            c("样本数","市数","小细胞数"),
+                                                            c("按月分省统计","测试时间","统计数值",""))
+                              }
+                       )
+                       },
+  "按月分小细胞统计" = {
+    choosenList <- slice_vec(细胞0$细胞, offset, per)
+    if(length(choosenList) == 0) return(NULL)
+    switch(metric,
+           "测试数、阳性数、有效数" = {
+             panelPlotByMonthAnd细胞(dfByMonthAnd细胞, choosenList,
+                                   "testMonth", "小细胞",
+                                   c("测试数","有效数","阳性数"),
+                                   c("按月分小细胞统计","测试时间","统计数值",""))
+           },
+           "阳性率、有效率" = {
+             panelPlotByMonthAnd细胞(dfByMonthAnd细胞, choosenList,
+                                   "testMonth", "小细胞",
+                                   c("有效率","阳性率"),
+                                   c("按月分小细胞统计","测试时间","统计数值",""))
+           },
+           "项目数、仪器数、批次数" = {
+             panelPlotByMonthAnd细胞(dfData=dfByMonthAnd细胞,choosenList,independentVariableName="testMonth",panelName="小细胞",
+                                   dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("按月分小细胞统计","测试时间","统计数值",""))
+           },
+           "省数、市数、小细胞数、样本数" = {
+             panelPlotByMonthAnd细胞(dfData=dfByMonthAnd细胞,choosenList,independentVariableName="testMonth",panelName="小细胞",
+                                   dependentVariableNames=c("样本数","市数","省数","小细胞数"),titleNames=c("按月分小细胞统计","测试时间","统计数值",""))
+           }
+    )
+  },
+  "按月分仪器统计" = {
+    choosenList <- slice_vec(仪器号List$仪器序列号, offset, per)
+    if(length(choosenList) == 0) return(NULL)
+    switch(metric,
+           "测试数、阳性数、有效数" = {
+             
+             panelPlotByMonthAnd仪器(dfData=dfByMonthAnd仪器,choosenList,independentVariableName="testMonth",panelName="仪器序列号",
+                                   dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月分仪器统计","测试时间","统计数值",""))
+           },
+           "阳性率、有效率" = {
+             panelPlotByMonthAnd仪器(dfData=dfByMonthAnd仪器,choosenList,independentVariableName="testMonth",panelName="仪器序列号",
+                                   dependentVariableNames=c("有效率","阳性率"),titleNames=c("按月分仪器统计","测试时间","统计数值",""))
+           },
+           "项目数、仪器数、批次数" = {
+             panelPlotByMonthAnd仪器(dfData=dfByMonthAnd仪器,choosenList,independentVariableName="testMonth",panelName="仪器序列号",
+                                   dependentVariableNames=c("项目数","批次数"),titleNames=c("按月分仪器统计","测试时间","统计数值",""))
+           },
+           "省数、市数、小细胞数、样本数" = {
+             panelPlotByMonthAnd仪器(dfData=dfByMonthAnd仪器,choosenList,independentVariableName="testMonth",panelName="仪器序列号",
+                                   dependentVariableNames=c("样本数","市数","省数"),titleNames=c("按月分仪器统计","测试时间","统计数值",""))
+           }    
+ 
+           
+    )
+  },
+  "全部统计" = {
+    switch(metric,
+           "测试数、阳性数、有效数" =
+             plotfunction(dfByMonth1, "testMonth", c("测试数","有效数","阳性数"),
+                          c("按月统计","测试时间","统计数值","")),
+           "阳性率、有效率" =
+             plotfunction(dfByMonth1, "testMonth", c("有效率","阳性率"),
+                          c("按月统计","测试时间","统计数值","")),
+           "项目数、仪器数、批次数" =
+             plotfunction(dfByMonth1, "testMonth", c("项目数","仪器数","批次数"),
+                          c("按月统计","测试时间","统计数值","")),
+           "省数、市数、小细胞数、样本数" =
+             plotfunction(dfByMonth1, "testMonth", c("样本数","市数","省数","小细胞数"),
+                          c("按月统计","测试时间","统计数值",""))
+    )                      
+                       }
+                )
+              },
+              
+              "按小细胞统计" = {
+                if (page == 1) {
+                  switch(metric,
+                         "测试数、阳性数、有效数"   = plotfunction(dfBy细胞1,"小细胞",c("测试数","有效数","阳性数"),c("按小细胞统计","小细胞","统计数值","")),
+                         "阳性率、有效率"           = plotfunction(dfBy细胞1, "小细胞", c("有效率","阳性率"), c("按小细胞统计","小细胞","统计数值","")),
+                         "项目数、仪器数、批次数"   = plotfunction(dfBy细胞1, "小细胞", c("项目数","仪器数","批次数"), c("按小细胞统计","小细胞","统计数值","")),
+                         "省数、市数、小细胞数、样本数"             = plotfunction(dfBy细胞1, "小细胞", c("样本数","市数","省数"), c("按小细胞统计","小细胞","统计数值","")),
+                         "测试截止、测试开始"       = plotfunctionLog(dfBy细胞1, "小细胞", c("测试开始","测试截止"), c("按小细胞统计","小细胞","多少天之前",""))
+                  )
+                } else if (page == 2) {
+                  switch(metric,
+                         "测试数、阳性数、有效数"   = plotfunction(dfBy细胞2,"小细胞",c("测试数","有效数","阳性数"),c("按小细胞统计","小细胞","统计数值","")),
+                         "阳性率、有效率"           = plotfunction(dfBy细胞2, "小细胞", c("有效率","阳性率"), c("按小细胞统计","小细胞","统计数值","")),
+                         "批次数、项目数、仪器数"   = plotfunction(dfBy细胞2, "小细胞", c("项目数","仪器数","批次数"), c("按小细胞统计","小细胞","统计数值","")),
+                         "省数、市数、小细胞数、样本数"             = plotfunction(dfBy细胞2, "小细胞", c("样本数","市数","省数"), c("按小细胞统计","小细胞","统计数值","")),
+                         "测试截止、测试开始"       = plotfunctionLog(dfBy细胞2, "小细胞", c("测试开始","测试截止"), c("按小细胞统计","小细胞","多少天之前",""))
+                  )
+                }
+              },
+                # ---------- 3. 其它维度（不需要分页） ----------
+              "按省统计" = {
+                switch(metric,
+                       "测试数、阳性数、有效数"   = plotfunction(dfBy区域, "省编号", c("测试数","有效数","阳性数"), c("按省统计","省编号","统计数值","")),
+                       "阳性率、有效率"           = plotfunction(dfBy区域, "省编号", c("有效率","阳性率"), c("按省统计","省编号","统计数值","")),
+                       "批次数、项目数、仪器数"   = plotfunction(dfBy区域, "省编号", c("项目数","仪器数","批次数"), c("按省统计","省编号","统计数值","")),
+                       "省数、市数、小细胞数、样本数"   = plotfunction(dfBy区域, "省编号", c("样本数","市数","小细胞数"), c("按省统计","省编号","统计数值","")),
+                       "测试截止、测试开始"       = plotfunctionLog(dfBy区域, "省编号", c("测试开始","测试截止"), c("按省统计","省编号","多少天之前",""))
+                )
+              },
+              
+  "按仪器统计" = {
+    if(!is.numeric(page)) return(NULL)
+    if(page<1 | page>max(仪器号List$GroupID) | is.na(page))  return(NULL)
+                switch(metric,
+                       "测试数、阳性数、有效数"   = plotfunctionVector仪器序列号(page, 仪器号List, dfBy仪器, "仪器序列号", c("测试数","有效数","阳性数"), c("按仪器统计","仪器序列号","统计数值","")),
+                       "阳性率、有效率"           = plotfunctionVector仪器序列号(page, 仪器号List, dfBy仪器, "仪器序列号", c("有效率","阳性率"), c("按仪器统计","仪器序列号","统计数值","")),
+                       "批次数、项目数、样本数"   = plotfunctionVector仪器序列号(page, 仪器号List, dfBy仪器, "仪器序列号", c("项目数","批次数"), c("按仪器统计","仪器序列号","统计数值","")),
+                       "省数、项目数、小细胞数、样本数"   = plotfunctionVector仪器序列号(page, 仪器号List, dfBy仪器, "仪器序列号", c("样本数","省数", "市数","小细胞数"), c("按仪器统计","仪器序列号","统计数值","")),
+                       "测试截止、测试开始"       = plotfunctionVector仪器序列号Log(page, 仪器号List, dfBy仪器, "仪器序列号", c("测试开始","测试截止"), c("按仪器统计","仪器序列号","多少天之前",""))
+                )
+              },
+              "按样本类型统计" = {
+                switch(metric,
+                       "测试数、阳性数、有效数"   = plotfunction(dfBy样本, "样本类型", c("测试数","有效数","阳性数"), c("按样本类型统计","样本类型","统计数值","")),
+                       "阳性率、有效率"           = plotfunction(dfBy样本, "样本类型", c("有效率","阳性率"), c("按样本类型统计","样本类型","统计数值","")),
+                       "批次数、省数、项目数、小细胞数" = plotfunction(dfBy样本, "样本类型", c("项目数","仪器数","批次数"), c("按样本类型统计","样本类型","统计数值","")),
+                       "批次数、省数、项目数、小细胞数" = plotfunction(dfBy样本, "样本类型", c("省数", "市数","小细胞数"), c("按样本类型统计","样本类型","统计数值","")),
+                        "测试截止、测试开始"       = plotfunctionLog(dfBy样本, "样本类型", c("测试开始","测试截止"), c("按样本类型统计","样本类型","多少天之前",""))
+                )
+              },
+              "按试剂批次统计" = {
+                if(!is.numeric(page)) return(NULL)
+                if(page<1 | page>max(批次号List$GroupID) | is.na(page))  return(NULL)
+                switch(metric,
+                       "测试数、阳性数、有效数"   = plotfunctionVector批次名称(page, 批次号List, dfBy批次, "批次名称", c("测试数","有效数","阳性数"), c("按批次统计","批次名称","统计数值","")),
+                       "阳性率、有效率"           = plotfunctionVector批次名称(page, 批次号List, dfBy批次, "批次名称", c("有效率","阳性率"), c("按试剂批次统计","批次名称","统计数值","")),
+                       "省数、项目数、小细胞数、样本数" = plotfunctionVector批次名称(page, 批次号List, dfBy批次, "批次名称", c("项目数","仪器数"), c("按试剂批次统计","批次名称","统计数值","")),
+                       "省数、项目数、小细胞数、样本数" = plotfunctionVector批次名称(page, 批次号List, dfBy批次, "批次名称", c("样本数","省数", "市数","小细胞数"), c("按试剂批次统计","批次名称","统计数值","")),
+                       "测试截止、测试开始"       = plotfunctionVector批次名称Log(page, 批次号List, dfBy批次, "批次名称", c("测试开始","测试截止"), c("按试剂批次统计","批次名称","多少天之前",""))
+                )
+              },
+              "按试剂项目统计" = {
+                if(!is.numeric(page)) return(NULL)
+                if(page<1 | page>max(项目号List$GroupID) | is.na(page))  return(NULL)
+                switch(metric,
+                       "测试数、阳性数、有效数"   = plotfunctionVector项目名称(page, 项目号List, dfBy项目, "项目名称", c("测试数","有效数","阳性数"), c("按项目统计","项目名称","统计数值","")),
+                       "阳性率、有效率"           = plotfunctionVector项目名称(page, 项目号List, dfBy项目, "项目名称", c("有效率","阳性率"), c("按试剂项目统计","项目名称","统计数值","")),
+                       "批次数、省数、小细胞数、样本数" = plotfunctionVector项目名称(page, 项目号List, dfBy项目, "项目名称", c("仪器数","批次数"), c("按试剂项目统计","项目名称","统计数值","")),
+                       "省数、项目数、小细胞数、样本数" = plotfunctionVector项目名称(page, 项目号List, dfBy项目, "项目名称", c("样本数","省数", "市数","小细胞数"), c("按试剂项目统计","项目名称","统计数值","")),
+                        "测试截止、测试开始"       = plotfunctionVector项目名称Log(page, 项目号List, dfBy项目, "项目名称", c("测试开始","测试截止"), c("按试剂项目统计","项目名称","多少天之前",""))
+                )
+              }
+  )
+  return(p)
+}
+
+shinyApp(ui = ui, server = server)
\ No newline at end of file