From d0aa69b442e8942f03962ba97f53d551096e9d03 Mon Sep 17 00:00:00 2001 From: MingYang Date: Mon, 16 Jun 2025 09:27:34 +0800 Subject: [PATCH] Upload files to "/" --- analyticsRecord06132025.R | 1632 +++++++++++++++++++++++++++++++++++++ 1 file changed, 1632 insertions(+) create mode 100644 analyticsRecord06132025.R diff --git a/analyticsRecord06132025.R b/analyticsRecord06132025.R new file mode 100644 index 0000000..27b3de7 --- /dev/null +++ b/analyticsRecord06132025.R @@ -0,0 +1,1632 @@ +library(readr) +#library(data.table) +library(Cairo) +library(ggplot2) +library(stringi) +library(stringr) +library(datetime) +library(dplyr) +library(ggthemes) + +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 +} + +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) + 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.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$仪器序列号=="781be43bb68f05bb",] + +cname0<-c("仪器编号" , "仪器序列号" , + "SIM卡号" , "发货时间" , "仪器类型" , + "总测试量" , "最后一次开机时间" ,"时间差" , +"开机地点" , "网络类型" , "ip地址" , + "用户" , "用户CRM" , "返利表序号" , + "申请日期" , "区域" , "客户编码" , + "代理商名称" , "用户名称" , "规格" , + "状态") +write.csv(仪器编号和序列号all[,cname0],file="仪器编号和序列号all.csv") +write.csv(仪器编号和序列号[,cname0],file="仪器编号和序列号.csv") +} + +仪器编号和序列号all<-read.csv("仪器编号和序列号all.csv",encoding = "UTF-8",fill = TRUE) +仪器编号和序列号<-read.csv("仪器编号和序列号.csv",encoding = "UTF-8",fill = TRUE) + + +df2 <- read.csv("history06092025.csv",encoding = "UTF-8",fill = TRUE) +df2<-distinct(df2) + +df2$省编号<-(df2$省市编号 %/% 10000)*10000 +df2$省名<-str_sub(df2$详细地址,1,3) +df2$省名[str_length(df2$省名)<3]<-NA + +Numberof项目号<-length(unique(df2$项目号)) +Numberof批次号<-length(unique(df2$批次号)) +Numberof样品编号<-length(unique(df2$样品编号)) +Numberof项目名称<-length(unique(df2$项目名称)) +Numberof批次名称<-length(unique(df2$批次名称)) +Numberof省编号<-length(unique(df2$省编号)) +Numberof省名<-length(unique(df2$省名)) +Numberof省市编号<-length(unique(df2$省市编号)) +Numberof仪器序列号<-length(unique(df2$仪器序列号)) +Numberof详细地址<-length(unique(df2$详细地址)) +Numberof仪器备注名称<-length(unique(df2$仪器备注名称)) +Numberof仪器投放区域<-length(unique(df2$仪器投放区域)) +Numberof样本类型<-length(unique(df2$样本类型)) + +省编号and省名<-cbind(df2$省编号,df2$省名) +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(df2)), + "\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样本类型: ",as.character(Numberof样本类型)," \n",sep="") + + + +summary(df2$结论) +summary(df2$是否阳性) +summary(df2$是否有效) + +#df2$仪器序列号_批次名称<-str_c(df2$仪器序列号,'_',df2$批次名称) + + +colnames(df2) +#colnames(df00) +#df200<-df20 +summary(df2$仪器序列号) +summary(df2$批次名称) + + +df20<-df2 #[,c(1:11,16,17,20)] +df20$省编号<-str_c("省编号: ",df20$省编号) +df20<-df20[complete.cases(df20$测试时间), ] + +colnames(df20) + +df20$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<=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) + + + +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)), + 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(dfByDay$testDay),] +#dfByDay<-dfByDay[lastDay-dfByDay$testDay<=21,] + +write.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)), + 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$testMonth),] +dfByMonth <- dfByMonth[nrow(dfByMonth):1,] + +write.csv(dfByMonth,file="按月统计0.csv") + +dfBy项目 <- df2000 %>% group_by(项目名称) %>% summarise( + 仪器数=length(unique(仪器序列号)), + 批次数=length(unique(批次名称)), + 样本数=length(unique(样本类型)), + 省数=length(unique(省编号)), + 市数=length(unique(省市编号)), + 测试数 = n(), + 阳性数=sum(结论,na.rm = TRUE), + 有效数=sum(是否有效,na.rm = TRUE), + 测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2), + 测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2) +) +dfBy项目$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.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)), + 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$测试数),] +write.csv(dfBy样本,file="按样本统计0.csv") + +dfBy区域 <- df2000 %>% group_by(省编号) %>% summarise( + 仪器数=length(unique(仪器序列号)), + 批次数=length(unique(批次名称)), + 样本数=length(unique(样本类型)), + 项目数=length(unique(项目名称)), + 市数=length(unique(省市编号)), + 测试数 = n(), + 阳性数=sum(结论,na.rm = TRUE), + 有效数=sum(是否有效,na.rm = TRUE), + 测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2), + 测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2) +) +dfBy区域$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.csv(dfBy区域,file="按区域统计0.csv") + +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)), + 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$测试数),] +write.csv(dfBy批次,file="按批次统计0.csv") + +df20001<-cbind(df2000,IDIndex=1:nrow(df2000)) +dfBy仪器 <- df20001 %>% group_by(仪器序列号) %>% summarise( + 批次数=length(unique(批次名称)), + 测试数 = n(), + 样本数=length(unique(样本类型)), + 项目数=length(unique(项目名称)), + 阳性数=sum(结论,na.rm = TRUE), + 有效数=sum(是否有效,na.rm = TRUE), + earliestIndex=min(IDIndex), + medianIndex=median(IDIndex), + latestIndex=max(IDIndex), + 最早测试=min(testDay,na.rm = TRUE), + 最近测试=max(testDay,na.rm = TRUE), + 测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2), + 测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2) +) +dfBy仪器$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$测试数),] +write.csv(dfBy仪器,file="按仪器统计0.csv") + +cname0<-c( "仪器序列号" ,"仪器编号" ,"最早测试地点","中期测试地点", "最后测试地点", + "开机地点" , "批次数" , "测试数" , "样本数" , "项目数" , + "阳性数", "有效数" , "最早测试" , "最近测试" , "测试开始" , + "测试截止", "阳性率" , "有效率", + "SIM卡号" , "发货时间" , "仪器类型" , + "总测试量" , "最后一次开机时间" ,"时间差" , + "网络类型" , "ip地址" , + "用户" , "用户CRM" , "返利表序号" , + "申请日期" , "区域" , "客户编码" , + "代理商名称" , "用户名称" , "规格" , + "状态") +colnames(dfBy仪器) +dfBy仪器andInf<-merge(dfBy仪器,仪器编号和序列号,by="仪器序列号",all.x=TRUE,all.y=FALSE) +dfBy仪器andInf <- dfBy仪器andInf[order(-dfBy仪器andInf$测试截止),][,cname0] +write.csv(dfBy仪器andInf,file="仪器统计andInf.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)), + 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$testDay),] + +dfByMonthAndLocation <- df20 %>% group_by(testMonth,省编号) %>% summarise( + 测试数 = n(), + 阳性数=sum(结论,na.rm = TRUE), + 有效数=sum(是否有效,na.rm = TRUE), + 样本数=length(unique(样本类型)), + 项目数=length(unique(项目名称)), + 仪器数=length(unique(仪器序列号)), + 批次数=length(unique(批次名称)), + 市数=length(unique(省市编号)) +) +dfByMonthAndLocation$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),] + +cairo_pdf(paste("和迈dataAnalytics06132025",".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$testDay<42,] +plotfunction(dfData=dfByDay1,independentVariableName="testDay", + dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值","")) +plotfunction(dfData=dfByDay1,independentVariableName="testDay", + dependentVariableNames=c("有效率","阳性率"),titleNames=c("最后六周按日测试统计","测试时间","统计数值","")) +plotfunction(dfData=dfByDay1,independentVariableName="testDay", + dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值","")) +plotfunction(dfData=dfByDay1,independentVariableName="testDay", + dependentVariableNames=c("样本数","市数","省数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值","")) + +dfByDayAndLocation1<-dfByDayAndLocation[lastDay-dfByDayAndLocation$testDay<42,] + +panelPlotByDayAndLocation(dfData=dfByDayAndLocation1,choosenList=dfBy区域$省编号[1:6],independentVariableName="testDay",panelName="省编号", + dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值","")) +panelPlotByDayAndLocation(dfData=dfByDayAndLocation1,choosenList=dfBy区域$省编号[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=dfBy区域$省编号[1:6],independentVariableName="testDay",panelName="省编号", + dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("最后六周按日测试统计","测试时间","统计数值","")) +panelPlotByDayAndLocation(dfData=dfByDayAndLocation1,choosenList=dfBy区域$省编号[1:6],independentVariableName="testDay",panelName="省编号", + dependentVariableNames=c("样本数","市数","省数"),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"),titleNames=c("按月测试统计","测试时间","统计数值","")) + +panelPlotByMonthAndLocation(dfData=dfByMonthAndLocation,choosenList=dfBy区域$省编号[1:6],independentVariableName="testMonth",panelName="省编号", + dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按月分省测试统计","测试时间","统计数值","")) +panelPlotByMonthAndLocation(dfData=dfByMonthAndLocation,choosenList=dfBy区域$省编号[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=dfBy区域$省编号[1:6],independentVariableName="testMonth",panelName="省编号", + dependentVariableNames=c("项目数","仪器数","批次数"),titleNames=c("按月分省测试统计","测试时间","统计数值","")) +panelPlotByMonthAndLocation(dfData=dfByMonthAndLocation,choosenList=dfBy区域$省编号[1:6],independentVariableName="testMonth",panelName="省编号", + dependentVariableNames=c("样本数","市数"),titleNames=c("按月分省测试统计","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"),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","")) + +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$仪器序列号,levels = 仪器号List[,1]) + + plotfunctionVector仪器序列号(ik=1,independentVariableList=仪器号List,dfData=dfBy仪器,independentVariableName="仪器序列号", + dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按仪器测试统计","仪器序列号","统计数值","")) + plotfunctionVector仪器序列号(ik=1,independentVariableList=仪器号List,dfData=dfBy仪器,independentVariableName="仪器序列号", + dependentVariableNames=c("项目数","样本数","批次数"),titleNames=c("按仪器测试统计","仪器序列号","统计数值","")) + plotfunctionVector仪器序列号(ik=1,independentVariableList=仪器号List,dfData=dfBy仪器,independentVariableName="仪器序列号", + dependentVariableNames=c("有效率","阳性率"),titleNames=c("按仪器测试统计","仪器序列号","统计数值","")) + plotfunctionVector仪器序列号Log(ik=1,independentVariableList=仪器号List,dfData=dfBy仪器,independentVariableName="仪器序列号", + dependentVariableNames=c("测试开始","测试截止"),titleNames=c("按仪器测试统计","仪器序列号","多少天之前","")) + + + if(FALSE) { +dfBy仪器00 <- df2000 %>% group_by(仪器序列号,省市编号,详细地址,仪器备注名称,仪器投放区域) %>% summarise( + 批次数=length(unique(批次名称)), + 测试数 = n(), + 样本数=length(unique(样本类型)), + 项目数=length(unique(项目名称)), + 阳性数=sum(结论,na.rm = TRUE), + 有效数=sum(是否有效,na.rm = TRUE), + earliestIndex=min(IDIndex), + medianIndex=median(IDIndex), + latestIndex=max(IDIndex), + 最早测试=min(testDay,na.rm = TRUE), + 最近测试=max(testDay,na.rm = TRUE), + 测试开始 = round(max(testTimeFromeToday,na.rm = TRUE),2), + 测试截止 = round(min(testTimeFromeToday,na.rm = TRUE),2) +) +dfBy仪器00$阳性率<-dfBy仪器00$阳性数/dfBy仪器00$有效数 +dfBy仪器00$有效率<-dfBy仪器00$有效数/dfBy仪器00$测试数 +dfBy仪器00$阳性数<-as.integer(dfBy仪器00$阳性数) +dfBy仪器00$测试数<-as.integer(dfBy仪器00$测试数) +dfBy仪器00$有效数<-as.integer(dfBy仪器00$有效数) + + + +dfBy仪器1<-merge(dfBy仪器00[,1:5],dfBy仪器,by="仪器序列号",all=FALSE) +write.csv(dfBy仪器1,file="仪器统计1.csv") +#仪器号MissedFromTwoYearsAgo<-仪器号[!(仪器号 %in% 仪器号00)] + } + +#样本号List<-unique(dfBy样本$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"),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$批次名称,levels = 批次号List[,1]) + +plotfunctionVector批次名称(ik=1,independentVariableList=批次号List,dfData=dfBy批次,independentVariableName="批次名称", + dependentVariableNames=c("测试数","有效数","阳性数"),titleNames=c("按批次测试统计","批次名称","统计数值","")) +plotfunctionVector批次名称(ik=1,independentVariableList=批次号List,dfData=dfBy批次,independentVariableName="批次名称", + dependentVariableNames=c("项目数","样本数","省数"),titleNames=c("按试剂批次测试统计","批次名称","统计数值","")) +plotfunctionVector批次名称(ik=1,independentVariableList=批次号List,dfData=dfBy批次,independentVariableName="批次名称", + dependentVariableNames=c("有效率","阳性率"),titleNames=c("按试剂批次测试统计","批次名称","统计数值","")) +plotfunctionVector批次名称Log(ik=1,independentVariableList=批次号List,dfData=dfBy批次,independentVariableName="批次名称", + dependentVariableNames=c("测试开始","测试截止"),titleNames=c("按试剂批次测试统计","批次名称","多少天之前","")) + +项目号List0<-cbind(dfBy项目,GroupID=rep00[1:length(dfBy项目$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"),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$testTimeFromeToday) +colnames(df20) + +#df201<-df20 + +# for(i in 1:5){ + + cairo_pdf(paste("和迈dataAnalyticsForRandD","_a06132025.pdf",sep=""), width = 8, height = 6,family = "SimHei" ) + + plotSummaryTable + +# df20<-df201[(df201$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() + +