knitr::opts_chunk$set(results = 'asis', echo = FALSE, warning = FALSE)
cat("**Filename:** ", inFile$name, "\n\n", sep = "")
# use results before trimmed L1:6 df_plot <- df_lev_flags alpha_rect <- 0.25 plot_mean <- mean(df_plot$Primary_Therm) p1 <- ggplot2::ggplot(df_plot, ggplot2::aes(x = Primary_Therm)) + ggplot2::geom_histogram(bins = 50) + ggplot2::annotate("rect" , xmin = 5.5 , xmax = 6.25 , ymin = -Inf , ymax = Inf , alpha = alpha_rect , fill = "red") + ggplot2::annotate("rect" , xmin = 4.5 , xmax = 5.5 , ymin = -Inf , ymax = Inf , alpha = alpha_rect , fill = "dark orange") + ggplot2::annotate("rect" , xmin = 3.5 , xmax = 4.5 , ymin = -Inf , ymax = Inf , alpha = alpha_rect , fill = "yellow") + ggplot2::annotate("rect" , xmin = 2.5 , xmax = 3.5 , ymin = -Inf , ymax = Inf , alpha = alpha_rect , fill = "gray") + ggplot2::annotate("rect" , xmin = 1.5 , xmax = 2.5 , ymin = -Inf , ymax = Inf , alpha = alpha_rect , fill = "green") + ggplot2::annotate("rect" , xmin = 1.25 , xmax = 1.5 , ymin = -Inf , ymax = Inf , alpha = alpha_rect , fill = "blue") + ggplot2::geom_histogram(bins = 50) + ggplot2::geom_vline( ggplot2::aes(xintercept = plot_mean) , color = "black" , linetype = "dashed") + ggplot2::labs(caption = paste0("mean (black dashed line) = " , round(plot_mean, 2)) , x = "Primary Thermal") + ggplot2::theme_light() # plotly::ggplotly(p1) p1
cap_flags <- "Flag summary." knitr::kable(table(df_flags[, "CHECKNAME"] , df_flags[, "FLAG"] , useNA = "ifany") , caption = cap_flags)
# Data df_plot2 <- df_flags_wide # Munge ## SampleID to row names row.names(df_plot2) <- df_plot2[, "SAMPLEID"] ## Remove columns df_plot2 <- df_plot2[, -c(1:2)] ## Change terminology; NA/flag to 0/1 df_plot2[!is.na(df_plot2)] <- 1 df_plot2[is.na(df_plot2)] <- 0 ## Convert character to numeric col2fix <- 1:ncol(df_plot2) df_plot2[, col2fix] <- apply(df_plot2[, col2fix] , 2 , function(x) as.numeric(as.character(x))) # plot p2 <- ComplexUpset::upset(df_plot2 , intersect = names(df_plot2) , name = "Flags") p2
cap_data <- "Summary results." DT::datatable(df_lev_flags , filter = "top" , caption = cap_data , options = list(scrollX = TRUE , lengthMenu = c(5, 10, 25, 50, 100, 1000) , autoWidth = TRUE ))
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