diff --git a/analyticsRecord07152025.R b/analyticsRecord07152025.R
new file mode 100644
index 0000000..eb54f24
--- /dev/null
+++ b/analyticsRecord07152025.R
@@ -0,0 +1,2178 @@
+library(readr)
+#library(data.table)
+library(Cairo)
+library(ggplot2)
+library(stringi)
+library(stringr)
+library(datetime)
+library(dplyr)
+library(ggthemes)
+library(RMySQL)
+
+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, 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),
+      size = 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")
+  
+  plot1
+  #return (list(plotdfDataNumber,b23,b33,b43,b53))
+  
+}
+
+plotfunctionVector仪器序列号<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
+  dfData<-dfData[(dfData$仪器序列号 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  
+  plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count, fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      size = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    geom_text(
+      aes(label = round(Count,2)),         # 标签内容
+      position = position_dodge(width = 0.4),  # 与柱子位置一致
+      vjust = -0.4,               # 垂直位置（负值向上）
+      color = "black",            # 标签颜色
+      size = 1.2                    # 字体大小
+    ) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      legend.position = "right")
+  
+  plot1
+  #return (list(plotdfDataNumber,b23,b33,b43,b53))
+  
+}
+
+plotfunctionVector批次名称<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
+  dfData<-dfData[(dfData$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, 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),
+      size = 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")
+  
+  plot1
+  #return (list(plotdfDataNumber,b23,b33,b43,b53))
+  
+}
+
+plotfunctionVector批次名称Log<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
+  dfData<-dfData[(dfData$批次名称 %in% c(independentVariableList[independentVariableList[,2]==ik,][,1])),]
+  lth1<-length(dependentVariableNames)
+  dfData00<-data.frame()
+  for(i in 1:lth1){
+    dfData0<-cbind(dependentVariableNames[i],dfData[,c(independentVariableName,dependentVariableNames[i])])
+    colnames(dfData0)<-c("Group",c(independentVariableName,"Count"))
+    dfData00<-rbind(dfData00,dfData0)
+  }
+  
+  plot1<-ggplot(dfData00, aes(x = dfData00[,2], y = Count, fill = Group)) +
+    geom_col(
+      position = position_dodge(width = 0.4),  # 控制条间距
+      width = 0.7  # 条宽度
+    ) +
+    geom_line(
+      aes(group = Group, color = Group),
+      position = position_dodge(width = 0.4),
+      size = 1,
+      linetype="dashed",
+      show.legend=FALSE,
+      alpha = 1.0
+    ) +  
+    scale_color_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    geom_text(
+      aes(label = round(Count,2)),         # 标签内容
+      position = position_dodge(width = 0.4),  # 与柱子位置一致
+      vjust = -0.4,               # 垂直位置（负值向上）
+      color = "black",            # 标签颜色
+      size = 1.2                    # 字体大小
+    ) +
+    labs(
+      title = titleNames[1],
+      x = titleNames[2],
+      y = titleNames[3],
+      fill = titleNames[4]
+    ) +
+    scale_fill_manual(values = c("red", "blue","green","yellow")) +  # 自定义颜色
+    scale_y_log10()+
+    theme_minimal() + theme(
+      plot.title = element_text(size = 14, face = "bold", hjust = 0.5),
+      axis.title.x = element_text(size = 12, face = "bold"),
+      axis.title.y = element_text(size = 12, face = "bold"),
+      axis.text.x = element_text(size = 8, face = "bold",angle=90) ,
+      legend.position = "right")
+  
+  plot1
+  #return (list(plotdfDataNumber,b23,b33,b43,b53))
+  
+}
+
+plotfunctionVector项目名称<- function(ik,independentVariableList,dfData,independentVariableName,dependentVariableNames,titleNames) {
+  dfData<-dfData[(dfData$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, 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),
+      size = 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")
+  
+  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, 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),
+      size = 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")
+  
+  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, 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),
+      size = 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")
+  
+  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, 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),
+      size = 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")
+  
+  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, 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),
+      size = 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
+        size = 1.,        # 边框粗细
+        linetype = "solid", # 线型（solid/dashed/dotted）
+        fill = NA          # 填充色（NA为透明）
+      ),
+      legend.position = "right")
+  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, 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),
+      size = 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
+        size = 1.,        # 边框粗细
+        linetype = "solid", # 线型（solid/dashed/dotted）
+        fill = NA          # 填充色（NA为透明）
+      ),
+      legend.position = "right")
+  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, 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),
+      size = 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
+        size = 1.,        # 边框粗细
+        linetype = "solid", # 线型（solid/dashed/dotted）
+        fill = NA          # 填充色（NA为透明）
+      ),
+      legend.position = "right")
+  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, 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),
+      size = 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
+        size = 1.,        # 边框粗细
+        linetype = "solid", # 线型（solid/dashed/dotted）
+        fill = NA          # 填充色（NA为透明）
+      ),
+      legend.position = "right")
+  plot1
+}
+
+pointPlotfunction批次<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
+  
+  plot2 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],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")
+  
+  plot2
+  
+}
+
+pointPlotfunction批次Log<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
+  
+  plot2 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],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")
+  
+  plot2
+  
+}
+
+pointPlotfunction仪器<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
+  
+  plot2 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],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")
+  
+  plot2
+  
+}
+
+pointPlotfunction仪器Log<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
+  
+  plot2 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],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")
+  
+  plot2
+  
+}
+
+pointPlotfunction样本<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
+  
+  plot2 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],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")
+  
+  plot2
+  
+}
+
+pointPlotfunction样本Log<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
+  
+  plot2 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],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")
+  
+  plot2
+  
+}
+
+pointPlotfunction项目<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
+  
+  plot2 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],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")
+  
+  plot2
+  
+}
+
+pointPlotfunction项目Log<- function(dfData,independentVariableName,dependentVariableName,titleNames) {
+  
+  plot2 <- ggplot(df20Ploted)+geom_point(aes(dfData[,independentVariableName], dfData[,dependentVariableName],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")
+  
+  plot2
+  
+}
+
+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, 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),
+      size = 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")
+  
+  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, 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),
+      size = 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")
+  
+  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, 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),
+      size = 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")
+  
+  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, 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),
+      size = 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")
+  
+  plot1
+  #return (list(plotdfDataNumber,b23,b33,b43,b53))
+  
+}
+
+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<-dfByDay$阳性数/dfByDay$有效数
+dfByDay$有效率<-dfByDay$有效数/dfByDay$测试数
+dfByDay$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$阳性率<-dfByMonth$阳性数/dfByMonth$有效数
+dfByMonth$有效率<-dfByMonth$有效数/dfByMonth$测试数
+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$testMonth),]
+dfByMonth <- dfByMonth[nrow(dfByMonth):1,]
+
+write_excel_csv(dfByMonth,file="按月统计0.csv")
+
+dfBy项目 <- df2000 %>%  group_by(项目名称) %>%  summarise(
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  样本数=length(unique(样本类型)),
+  省数=length(unique(省编号)),
+  市数=length(unique(省市编号)),
+  小细胞数=length(unique(小细胞)),
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
+  测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
+)
+dfBy项目$阳性率<-dfBy项目$阳性数/dfBy项目$有效数
+dfBy项目$有效率<-dfBy项目$有效数/dfBy项目$测试数
+dfBy项目$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(
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  项目数=length(unique(项目名称)),
+  省数=length(unique(省编号)),
+  市数=length(unique(省市编号)),
+  小细胞数=length(unique(小细胞)),
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,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样本$阳性率<-dfBy样本$阳性数/dfBy样本$有效数
+dfBy样本$有效率<-dfBy样本$有效数/dfBy样本$测试数
+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$测试数),]
+write_excel_csv(dfBy样本,file="按样本统计0.csv")
+
+dfBy细胞 <- df2000 %>%  group_by(小细胞) %>%  summarise(
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  市数=length(unique(省市编号)),
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
+  测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
+)
+dfBy细胞$阳性率<-dfBy细胞$阳性数/dfBy细胞$有效数
+dfBy细胞$有效率<-dfBy细胞$有效数/dfBy细胞$测试数
+dfBy细胞$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(
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称)),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  市数=length(unique(省市编号)),
+  小细胞数=length(unique(小细胞)),
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,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区域$阳性率<-dfBy区域$阳性数/dfBy区域$有效数
+dfBy区域$有效率<-dfBy区域$有效数/dfBy区域$测试数
+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$省编号  %in% 省编号0,]
+
+dfBy批次 <- df2000 %>%  group_by(批次名称) %>%  summarise(
+  仪器数=length(unique(仪器序列号)),
+  测试数 = n(),
+  省数=length(unique(省编号)),
+  市数=length(unique(省市编号)),
+  小细胞数=length(unique(小细胞)),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  最早测试=min(testDay,na.rm = TRUE),
+  最近测试=max(testDay,na.rm = TRUE),
+  测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2),
+  测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2)
+)
+dfBy批次$阳性率<-dfBy批次$阳性数/dfBy批次$有效数
+dfBy批次$有效率<-dfBy批次$有效数/dfBy批次$测试数
+dfBy批次$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(
+  批次数=length(unique(批次名称)),
+  测试数 = n(),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  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$阳性率<-dfBy仪器$阳性数/dfBy仪器$有效数
+dfBy仪器$有效率<-dfBy仪器$有效数/dfBy仪器$测试数
+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$阳性率<-dfByDayAndLocation$阳性数/dfByDayAndLocation$有效数
+dfByDayAndLocation$有效率<-dfByDayAndLocation$有效数/dfByDayAndLocation$测试数
+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))
+)
+dfByMonthAndLocation$阳性率<-dfByMonthAndLocation$阳性数/dfByMonthAndLocation$有效数
+dfByMonthAndLocation$有效率<-dfByMonthAndLocation$有效数/dfByMonthAndLocation$测试数
+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))
+)
+dfByDayAnd细胞$阳性率<-dfByDayAnd细胞$阳性数/dfByDayAnd细胞$有效数
+dfByDayAnd细胞$有效率<-dfByDayAnd细胞$有效数/dfByDayAnd细胞$测试数
+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$testDay),]
+
+dfByMonthAnd细胞 <- df20 %>%  group_by(testMonth,小细胞) %>%  summarise(
+  测试数 = n(),
+  阳性数=sum(结论,na.rm = TRUE),
+  有效数=sum(是否有效,na.rm = TRUE),
+  样本数=length(unique(样本类型)),
+  项目数=length(unique(项目名称)),
+  仪器数=length(unique(仪器序列号)),
+  批次数=length(unique(批次名称))
+)
+dfByMonthAnd细胞$阳性率<-dfByMonthAnd细胞$阳性数/dfByMonthAnd细胞$有效数
+dfByMonthAnd细胞$有效率<-dfByMonthAnd细胞$有效数/dfByMonthAnd细胞$测试数
+dfByMonthAnd细胞$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),]
+
+cairo_pdf(paste("和迈dataAnalytics07152025",".pdf",sep=""), width = 8, height = 6,family = "SimHei" )
+
+plotSummaryTable<-ggplot() +geom_text(aes(x = 100, y = 40,
+                                          label = summaryTable),
+                                      stat = "unique",
+                                      fontface = "bold",
+                                      color = "black",            # 标签颜色
+                                      size = 5.0  )+                 # 字体大小
+  xlim(0,200)+ylim(0,100)+
+  theme_minimal() + theme(axis.text = element_blank(),
+                          axis.ticks = element_blank(),
+                          axis.title = element_blank())
+
+plotSummaryTable
+
+dfByDay1<-dfByDay[lastDay-dfByDay$testDay<42,]
+plotfunction(dfData=dfByDay1,independentVariableName="testDay",
+                  dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+plotfunction(dfData=dfByDay1,independentVariableName="testDay",
+                  dependentVariableNames=c("有效率","阳性率"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+plotfunction(dfData=dfByDay1,independentVariableName="testDay",
+                  dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+plotfunction(dfData=dfByDay1,independentVariableName="testDay",
+             dependentVariableNames=c("样本数","市数","省数","小细胞数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+
+dfByDayAndLocation1<-dfByDayAndLocation[lastDay-dfByDayAndLocation$testDay<42,]
+
+panelPlotByDayAndLocation(dfData=dfByDayAndLocation1,choosenList=省编号0[1:6],independentVariableName="testDay",panelName="省编号",
+                          dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+panelPlotByDayAndLocation(dfData=dfByDayAndLocation1,choosenList=省编号0[7:12],independentVariableName="testDay",panelName="省编号",
+                          dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+panelPlotByDayAndLocation(dfData=dfByDayAndLocation1,choosenList=省编号0[13:18],independentVariableName="testDay",panelName="省编号",
+                          dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+panelPlotByDayAndLocation(dfData=dfByDayAndLocation1,choosenList=省编号0[c(19:24)],independentVariableName="testDay",panelName="省编号",
+                          dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+panelPlotByDayAndLocation(dfData=dfByDayAndLocation1,choosenList=省编号0[c(25:length(省编号0))],independentVariableName="testDay",panelName="省编号",
+                          dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+
+panelPlotByDayAndLocation(dfData=dfByDayAndLocation1,choosenList=省编号0[1:6],independentVariableName="testDay",panelName="省编号",
+                          dependentVariableNames=c("有效率","阳性率"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+panelPlotByDayAndLocation(dfData=dfByDayAndLocation1,choosenList=省编号0[1:6],independentVariableName="testDay",panelName="省编号",
+                          dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+panelPlotByDayAndLocation(dfData=dfByDayAndLocation1,choosenList=省编号0[1:6],independentVariableName="testDay",panelName="省编号",
+                          dependentVariableNames=c("样本数","市数","省数","小细胞数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+
+dfByDayAnd细胞1<-dfByDayAnd细胞[lastDay-dfByDayAnd细胞$testDay<42,]
+
+panelPlotByDayAnd细胞(dfData=dfByDayAnd细胞1,choosenList=细胞0$细胞[1:6],independentVariableName="testDay",panelName="小细胞",
+                    dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+panelPlotByDayAnd细胞(dfData=dfByDayAnd细胞1,choosenList=细胞0$细胞[7:12],independentVariableName="testDay",panelName="小细胞",
+                    dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+panelPlotByDayAnd细胞(dfData=dfByDayAnd细胞1,choosenList=细胞0$细胞[13:18],independentVariableName="testDay",panelName="小细胞",
+                    dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+panelPlotByDayAnd细胞(dfData=dfByDayAnd细胞1,choosenList=细胞0$细胞[19:24],independentVariableName="testDay",panelName="小细胞",
+                    dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+panelPlotByDayAnd细胞(dfData=dfByDayAnd细胞1,choosenList=细胞0$细胞[25:30],independentVariableName="testDay",panelName="小细胞",
+                    dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+panelPlotByDayAnd细胞(dfData=dfByDayAnd细胞1,choosenList=细胞0$细胞[31:36],independentVariableName="testDay",panelName="小细胞",
+                    dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+panelPlotByDayAnd细胞(dfData=dfByDayAnd细胞1,choosenList=细胞0$细胞[37:42],independentVariableName="testDay",panelName="小细胞",
+                    dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+panelPlotByDayAnd细胞(dfData=dfByDayAnd细胞1,choosenList=dfBy细胞$小细胞[43:nrow(细胞0)],independentVariableName="testDay",panelName="小细胞",
+                    dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+
+panelPlotByDayAnd细胞(dfData=dfByDayAnd细胞1,choosenList=细胞0$细胞[1:6],independentVariableName="testDay",panelName="小细胞",
+                    dependentVariableNames=c("有效率","阳性率"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+panelPlotByDayAnd细胞(dfData=dfByDayAnd细胞1,choosenList=细胞0$细胞[1:6],independentVariableName="testDay",panelName="小细胞",
+                    dependentVariableNames=c("项目数","仪器数","批次数","样本数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+#panelPlotByDayAnd细胞(dfData=dfByDayAnd细胞1,choosenList=细胞0$细胞[1:6],independentVariableName="testDay",panelName="小细胞",
+#                    dependentVariableNames=c("样本数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值",""))
+
+dfByMonth1<-dfByMonth[1:30,]
+
+plotfunction(dfData=dfByMonth1,independentVariableName="testMonth",
+                    dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月测试统计","测试时间","统计数值",""))
+plotfunction(dfData=dfByMonth1,independentVariableName="testMonth",
+                    dependentVariableNames=c("有效率","阳性率"),titleNames=c("按月测试统计","测试时间","统计数值",""))
+plotfunction(dfData=dfByMonth1,independentVariableName="testMonth",
+                    dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("按月测试统计","测试时间","统计数值",""))
+plotfunction(dfData=dfByMonth1,independentVariableName="testMonth",
+                    dependentVariableNames=c("样本数","市数","省数","小细胞数"),titleNames=c("按月测试统计","测试时间","统计数值",""))
+
+panelPlotByMonthAndLocation(dfData=dfByMonthAndLocation,choosenList=省编号0[1:6],independentVariableName="testMonth",panelName="省编号",
+                            dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月分省测试统计","测试时间","统计数值",""))
+panelPlotByMonthAndLocation(dfData=dfByMonthAndLocation,choosenList=省编号0[7:12],independentVariableName="testMonth",panelName="省编号",
+                            dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月分省测试统计","测试时间","统计数值",""))
+panelPlotByMonthAndLocation(dfData=dfByMonthAndLocation,choosenList=省编号0[13:18],independentVariableName="testMonth",panelName="省编号",
+                            dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月分省测试统计","测试时间","统计数值",""))
+panelPlotByMonthAndLocation(dfData=dfByMonthAndLocation,choosenList=省编号0[c(19:24)],independentVariableName="testMonth",panelName="省编号",
+                            dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月分省测试统计","测试时间","统计数值",""))
+panelPlotByMonthAndLocation(dfData=dfByMonthAndLocation,choosenList=省编号0[c(25:length(省编号0))],independentVariableName="testMonth",panelName="省编号",
+                            dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月分省测试统计","测试时间","统计数值",""))
+
+panelPlotByMonthAndLocation(dfData=dfByMonthAndLocation,choosenList=省编号0[1:6],independentVariableName="testMonth",panelName="省编号",
+                            dependentVariableNames=c("有效率","阳性率"),titleNames=c("按月分省测试统计","测试时间","统计数值",""))
+panelPlotByMonthAndLocation(dfData=dfByMonthAndLocation,choosenList=省编号0[1:6],independentVariableName="testMonth",panelName="省编号",
+                            dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("按月分省测试统计","测试时间","统计数值",""))
+panelPlotByMonthAndLocation(dfData=dfByMonthAndLocation,choosenList=省编号0[1:6],independentVariableName="testMonth",panelName="省编号",
+                            dependentVariableNames=c("样本数","市数","小细胞数"),titleNames=c("按月分省测试统计","测试时间","统计数值",""))
+
+panelPlotByMonthAnd细胞(dfData=dfByMonthAnd细胞,choosenList=细胞0$细胞[1:6],independentVariableName="testMonth",panelName="小细胞",
+                      dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月分细胞测试统计","测试时间","统计数值",""))
+panelPlotByMonthAnd细胞(dfData=dfByMonthAnd细胞,choosenList=细胞0$细胞[7:12],independentVariableName="testMonth",panelName="小细胞",
+                      dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月分细胞测试统计","测试时间","统计数值",""))
+panelPlotByMonthAnd细胞(dfData=dfByMonthAnd细胞,choosenList=细胞0$细胞[13:18],independentVariableName="testMonth",panelName="小细胞",
+                      dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月分细胞测试统计","测试时间","统计数值",""))
+panelPlotByMonthAnd细胞(dfData=dfByMonthAnd细胞,choosenList=细胞0$细胞[19:24],independentVariableName="testMonth",panelName="小细胞",
+                      dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月分细胞测试统计","测试时间","统计数值",""))
+panelPlotByMonthAnd细胞(dfData=dfByMonthAnd细胞,choosenList=细胞0$细胞[25:30],independentVariableName="testMonth",panelName="小细胞",
+                      dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月分细胞测试统计","测试时间","统计数值",""))
+panelPlotByMonthAnd细胞(dfData=dfByMonthAnd细胞,choosenList=细胞0$细胞[31:36],independentVariableName="testMonth",panelName="小细胞",
+                      dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月分细胞测试统计","测试时间","统计数值",""))
+panelPlotByMonthAnd细胞(dfData=dfByMonthAnd细胞,choosenList=细胞0$细胞[37:42],independentVariableName="testMonth",panelName="小细胞",
+                      dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月分细胞测试统计","测试时间","统计数值",""))
+panelPlotByMonthAnd细胞(dfData=dfByMonthAnd细胞,choosenList=细胞0$细胞[43:nrow(细胞0)],independentVariableName="testMonth",panelName="小细胞",
+                      dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月分细胞测试统计","测试时间","统计数值",""))
+
+panelPlotByMonthAnd细胞(dfData=dfByMonthAnd细胞,choosenList=细胞0$细胞[1:6],independentVariableName="testMonth",panelName="小细胞",
+                      dependentVariableNames=c("有效率","阳性率"),titleNames=c("按月分细胞测试统计","测试时间","统计数值",""))
+panelPlotByMonthAnd细胞(dfData=dfByMonthAnd细胞,choosenList=细胞0$细胞[1:6],independentVariableName="testMonth",panelName="小细胞",
+                      dependentVariableNames=c("项目数","仪器数","批次数","样本数"),titleNames=c("按月分细胞测试统计","测试时间","统计数值",""))
+#panelPlotByMonthAnd细胞(dfData=dfByMonthAnd细胞,choosenList=细胞0$细胞[1:6],independentVariableName="testMonth",panelName="小细胞",
+#                      dependentVariableNames=c("样本数"),titleNames=c("按月分细胞测试统计","测试时间","统计数值",""))
+
+plotfunction(dfData=dfBy区域,independentVariableName="省编号",
+                 dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按省测试统计","省编号","统计数值",""))
+plotfunction(dfData=dfBy区域,independentVariableName="省编号",
+                 dependentVariableNames=c("有效率","阳性率"),titleNames=c("按省测试统计","省编号","统计数值",""))
+plotfunction(dfData=dfBy区域,independentVariableName="省编号",
+                 dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("按省测试统计","省编号","统计数值",""))
+plotfunction(dfData=dfBy区域,independentVariableName="省编号",
+                 dependentVariableNames=c("样本数","市数","小细胞数"),titleNames=c("按省测试统计","省编号","统计数值",""))
+plotfunctionLog(dfData=dfBy区域,independentVariableName="省编号",
+                 dependentVariableNames=c("测试开始","测试截止"),titleNames=c("按省测试统计","省编号","多少天之前",""))
+
+lenhalf<-length(dfBy细胞$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$小细胞)],]
+plotfunction(dfData=dfBy细胞1,independentVariableName="小细胞",
+             dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按细胞测试统计","细胞","统计数值",""))
+plotfunction(dfData=dfBy细胞2,independentVariableName="小细胞",
+             dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按细胞测试统计","细胞","统计数值",""))
+plotfunction(dfData=dfBy细胞1,independentVariableName="小细胞",
+             dependentVariableNames=c("有效率","阳性率"),titleNames=c("按细胞测试统计","细胞","统计数值",""))
+plotfunction(dfData=dfBy细胞2,independentVariableName="小细胞",
+             dependentVariableNames=c("有效率","阳性率"),titleNames=c("按细胞测试统计","细胞","统计数值",""))
+plotfunction(dfData=dfBy细胞1,independentVariableName="小细胞",
+             dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("按细胞测试统计","细胞","统计数值",""))
+plotfunction(dfData=dfBy细胞2,independentVariableName="小细胞",
+             dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("按细胞测试统计","细胞","统计数值",""))
+plotfunction(dfData=dfBy细胞1,independentVariableName="小细胞",
+             dependentVariableNames=c("样本数","市数"),titleNames=c("按细胞测试统计","细胞","统计数值",""))
+plotfunction(dfData=dfBy细胞2,independentVariableName="小细胞",
+             dependentVariableNames=c("样本数","市数"),titleNames=c("按细胞测试统计","细胞","统计数值",""))
+plotfunctionLog(dfData=dfBy细胞1,independentVariableName="小细胞",
+                dependentVariableNames=c("测试开始","测试截止"),titleNames=c("按细胞测试统计","细胞","多少天之前",""))
+plotfunctionLog(dfData=dfBy细胞2,independentVariableName="小细胞",
+                dependentVariableNames=c("测试开始","测试截止"),titleNames=c("按细胞测试统计","细胞","多少天之前",""))
+
+仪器号List0<-cbind(dfBy仪器,GroupID=rep00[1:length(dfBy仪器$仪器序列号)])
+仪器号List<-仪器号List0[,c(1,ncol(仪器号List0))]
+dfBy仪器$仪器序列号<-factor(dfBy仪器$仪器序列号,levels = 仪器号List[,1])
+
+  plotfunctionVector仪器序列号(ik=1,independentVariableList=仪器号List,dfData=dfBy仪器,independentVariableName="仪器序列号",
+                   dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按仪器测试统计","仪器序列号","统计数值",""))
+  plotfunctionVector仪器序列号(ik=1,independentVariableList=仪器号List,dfData=dfBy仪器,independentVariableName="仪器序列号",
+                   dependentVariableNames=c("项目数","样本数","批次数"),titleNames=c("按仪器测试统计","仪器序列号","统计数值",""))
+  plotfunctionVector仪器序列号(ik=1,independentVariableList=仪器号List,dfData=dfBy仪器,independentVariableName="仪器序列号",
+                   dependentVariableNames=c("有效率","阳性率"),titleNames=c("按仪器测试统计","仪器序列号","统计数值",""))
+  plotfunctionVector仪器序列号Log(ik=1,independentVariableList=仪器号List,dfData=dfBy仪器,independentVariableName="仪器序列号",
+                      dependentVariableNames=c("测试开始","测试截止"),titleNames=c("按仪器测试统计","仪器序列号","多少天之前",""))
+
+
+#样本号List<-unique(dfBy样本$样本类型)
+plotfunction(dfData=dfBy样本,independentVariableName="样本类型",
+             dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按样本类型测试统计","样本类型","统计数值",""))
+plotfunction(dfData=dfBy样本,independentVariableName="样本类型",
+             dependentVariableNames=c("项目数","批次数","省数","小细胞数"),titleNames=c("按样本类型测试统计","样本类型","统计数值",""))
+plotfunction(dfData=dfBy样本,independentVariableName="样本类型",
+             dependentVariableNames=c("有效率","阳性率"),titleNames=c("按样本类型测试统计","样本类型","统计数值",""))
+plotfunctionLog(dfData=dfBy样本,independentVariableName="样本类型",
+                dependentVariableNames=c("测试开始","测试截止"),titleNames=c("按样本类型测试统计","样本类型","多少天之前",""))
+
+
+批次号List0<-cbind(dfBy批次,GroupID=rep00[1:length(dfBy批次$批次名称)])
+批次号List<-批次号List0[,c(1,ncol(批次号List0))]
+dfBy批次$批次名称<-factor(dfBy批次$批次名称,levels = 批次号List[,1])
+
+plotfunctionVector批次名称(ik=1,independentVariableList=批次号List,dfData=dfBy批次,independentVariableName="批次名称",
+                        dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按批次测试统计","批次名称","统计数值",""))
+plotfunctionVector批次名称(ik=1,independentVariableList=批次号List,dfData=dfBy批次,independentVariableName="批次名称",
+             dependentVariableNames=c("项目数","样本数","省数","小细胞数"),titleNames=c("按试剂批次测试统计","批次名称","统计数值",""))
+plotfunctionVector批次名称(ik=1,independentVariableList=批次号List,dfData=dfBy批次,independentVariableName="批次名称",
+             dependentVariableNames=c("有效率","阳性率"),titleNames=c("按试剂批次测试统计","批次名称","统计数值",""))
+plotfunctionVector批次名称Log(ik=1,independentVariableList=批次号List,dfData=dfBy批次,independentVariableName="批次名称",
+                dependentVariableNames=c("测试开始","测试截止"),titleNames=c("按试剂批次测试统计","批次名称","多少天之前",""))
+
+项目号List0<-cbind(dfBy项目,GroupID=rep00[1:length(dfBy项目$项目名称)])
+项目号List<-项目号List0[,c(1,ncol(项目号List0))]
+dfBy项目$项目名称<-factor(dfBy项目$项目名称,levels = 项目号List[,1])
+
+plotfunctionVector项目名称(ik=1,independentVariableList=项目号List,dfData=dfBy项目,independentVariableName="项目名称",
+                       dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按项目测试统计","项目名称","统计数值",""))
+plotfunctionVector项目名称(ik=1,independentVariableList=项目号List,dfData=dfBy项目,independentVariableName="项目名称",
+                       dependentVariableNames=c("批次数","样本数","省数","小细胞数"),titleNames=c("按试剂项目测试统计","项目名称","统计数值",""))
+plotfunctionVector项目名称(ik=1,independentVariableList=项目号List,dfData=dfBy项目,independentVariableName="项目名称",
+                       dependentVariableNames=c("有效率","阳性率"),titleNames=c("按试剂项目测试统计","项目名称","统计数值",""))
+plotfunctionVector项目名称Log(ik=1,independentVariableList=项目号List,dfData=dfBy项目,independentVariableName="项目名称",
+                          dependentVariableNames=c("测试开始","测试截止"),titleNames=c("按试剂项目测试统计","项目名称","多少天之前",""))
+
+
+dev.off()
+
+df20$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$ToverC值)
+
+summary(df20$testTimeFromeToday)
+colnames(df20)
+
+#df201<-df20
+
+# for(i in 1:5){
+  
+  cairo_pdf(paste("和迈dataAnalyticsForRandD","_07152025.pdf",sep=""), width = 8, height = 6,family = "SimHei" )
+  
+  plotSummaryTable
+  
+#  df20<-df201[(df201$项目名称 %in% dfBy项目top4[i]),]
+  # plot项目名称Title<-ggplot() +geom_text(aes(x = 100, y = 60,
+  #                                        label = paste("项目名称： ",dfBy项目名称top5[i],sep="")),
+  #                                    stat = "unique",
+  #                                    fontface = "bold",
+  #                                    color = "black",            # 标签颜色
+  #                                    size = 8.0  )+                 # 字体大小
+  #   xlim(0,200)+ylim(0,100)+
+  #   theme_minimal() + theme(axis.text = element_blank(),
+  #                           axis.ticks = element_blank(),
+  #                           axis.title = element_blank())
+  # 
+  # plot项目名称Title
+  
+  df20 <- df20[order(-df20$testTimeFromeToday),]
+
+df20 <- df20 %>%  group_by(批次名称) %>%  transform(
+  浓度1移动均值 = running_avg(浓度1,20),
+  C值移动均值 = running_avg(C值,20),
+  T值移动均值 = running_avg(T值,20),
+  ToverC值移动均值 = running_avg(ToverC值,20),
+  结论移动均值 = running_avg(结论,20)
+)
+
+# df20$浓度1移动均值<-running_avg(df20$浓度1, 20)
+# df20$C值移动均值<-running_avg(df20$C值, 20)
+# df20$T值移动均值<-running_avg(df20$T值, 20)
+# df20$ToverC值移动均值<-running_avg(df20$ToverC值, 20)
+# df20$结论移动均值<-running_avg(df20$结论, 20)
+
+df20$浓度1累计均值<-lumping_avg(df20$浓度1)
+df20$C值累计均值<-lumping_avg(df20$C值)
+df20$T值累计均值<-lumping_avg(df20$T值)
+df20$ToverC值累计均值<-lumping_avg(df20$ToverC值)
+df20$结论累计均值<-lumping_avg(df20$结论)
+
+# df20$浓度1累计标差<-lumping_sd(df20$浓度1)
+# df20$C值累计标差<-lumping_sd(df20$C值)
+# df20$T值累计标差<-lumping_sd(df20$T值)
+# df20$ToverC值累计标差<-lumping_sd(df20$ToverC值)
+# df20$结论累计标差<-lumping_sd(df20$结论移动均值)
+
+df20$浓度1累计标差<-lumping_sd(df20$浓度1移动均值)
+df20$C值累计标差<-lumping_sd(df20$C值移动均值)
+df20$T值累计标差<-lumping_sd(df20$T值移动均值)
+df20$ToverC值累计标差<-lumping_sd(df20$ToverC值移动均值)
+df20$结论累计标差<-lumping_sd(df20$结论移动均值)
+
+df20$浓度1允许波动范围<-df20$浓度1累计均值+2*df20$浓度1累计标差
+df20$C值允许波动范围<-df20$C值累计均值+2*df20$C值累计标差
+df20$T值允许波动范围<-df20$T值累计均值+2*df20$T值累计标差
+df20$ToverC值允许波动范围<-df20$ToverC值累计均值+2*df20$ToverC值累计标差
+df20$结论允许波动范围<-df20$结论累计均值+2*df20$结论累计标差
+
+summary(df20$浓度1移动均值)
+summary(df20$running_avg)
+summary(df20$浓度1累计均值)
+summary(df20$浓度1累计标差)
+summary(df20$结论累计均值)
+df200<-df20
+df20<-df200[df200$项目名称 %in% 项目号List[1,1], ]
+#df20Ploted<-df20[df20$批次名称 %in% 批次号List$批次名称[批次号List[,2]==1],]
+df20Ploted<-df20[df20$批次名称 %in% 批次号List$批次名称[1:5],]
+
+pointPlotfunction批次(dfData=df20Ploted,independentVariableName="testDay",
+                    dependentVariableName="浓度1",titleNames=c("浓度","测试日期","浓度1",""))
+pointPlotfunction批次Log(dfData=df20Ploted,independentVariableName="testDay",
+                       dependentVariableName="C值",titleNames=c("C值","测试日期","C值",""))
+pointPlotfunction批次Log(dfData=df20Ploted,independentVariableName="testDay",
+                       dependentVariableName="T值",titleNames=c("T值","测试日期","T值",""))
+pointPlotfunction批次(dfData=df20Ploted,independentVariableName="testDay",
+                    dependentVariableName="ToverC值",titleNames=c("T/C值","测试日期","T/C值",""))
+pointPlotfunction批次(dfData=df20Ploted,independentVariableName="testDay",
+                    dependentVariableName="结论移动均值",titleNames=c("结论/阳性率","测试日期","结论/阳性率",""))
+
+df20Ploted<-df20[df20$仪器序列号 %in% 仪器号List$仪器序列号[1:5],]
+
+pointPlotfunction仪器(dfData=df20Ploted,independentVariableName="testDay",
+                    dependentVariableName="浓度1",titleNames=c("浓度","测试日期","浓度1",""))
+pointPlotfunction仪器Log(dfData=df20Ploted,independentVariableName="testDay",
+                       dependentVariableName="C值",titleNames=c("C值","测试日期","C值",""))
+pointPlotfunction仪器Log(dfData=df20Ploted,independentVariableName="testDay",
+                       dependentVariableName="T值",titleNames=c("T值","测试日期","T值",""))
+pointPlotfunction仪器(dfData=df20Ploted,independentVariableName="testDay",
+                    dependentVariableName="ToverC值",titleNames=c("T/C值","测试日期","T/C值",""))
+pointPlotfunction仪器(dfData=df20Ploted,independentVariableName="testDay",
+                    dependentVariableName="结论移动均值",titleNames=c("结论/阳性率","测试日期","结论/阳性率",""))
+
+
+df20Ploted<-df20[df20$样本类型 %in% unique(df20$样本类型)[1:2],]
+
+pointPlotfunction样本(dfData=df20Ploted,independentVariableName="testDay",
+                    dependentVariableName="浓度1",titleNames=c("浓度","测试日期","浓度1",""))
+pointPlotfunction样本Log(dfData=df20Ploted,independentVariableName="testDay",
+                       dependentVariableName="C值",titleNames=c("C值","测试日期","C值",""))
+pointPlotfunction样本Log(dfData=df20Ploted,independentVariableName="testDay",
+                       dependentVariableName="T值",titleNames=c("T值","测试日期","T值",""))
+pointPlotfunction样本(dfData=df20Ploted,independentVariableName="testDay",
+                    dependentVariableName="ToverC值",titleNames=c("T/C值","测试日期","T/C值",""))
+pointPlotfunction样本(dfData=df20Ploted,independentVariableName="testDay",
+                    dependentVariableName="结论移动均值",titleNames=c("结论/阳性率","测试日期","结论/阳性率",""))
+
+
+dev.off()
+
+