--- title: "Complete Example 1" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{example1} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r setup, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) options(rmarkdown.html_vignette.check_title = FALSE) ``` ## Program The previous examples in the **libr** documentation were intentionally simplified to focus on the workings of a particular function. It is helpful, however, to also view **libr** functions in the context of a complete program. The following example shows a complete program. The example illustrates how **libr** functions work together, and interact with **tidyverse** and **sassy** functions to create a report. The data for this example has been included in the **libr** package as an external data file. It may be accessed using the `system.file()` function as shown below, or downloaded directly from the **libr** GitHub site [here](https://raw.githubusercontent.com/dbosak01/libr/master/inst/extdata/DM.csv) ```{r eval=FALSE, echo=TRUE} library(tidyverse) library(sassy) # Prepare Log ------------------------------------------------------------- options("logr.autolog" = TRUE, "logr.notes" = FALSE) # Get temp location for log and report output tmp <- tempdir() # Open log lf <- log_open(file.path(tmp, "example1.log")) # Load and Prepare Data --------------------------------------------------- sep("Prepare Data") # Get path to sample data pkg <- system.file("extdata", package = "libr") # Define data library libname(sdtm, pkg, "csv", quiet = TRUE) # Prepare data dm_mod <- sdtm$DM |> select(USUBJID, SEX, AGE, ARM) |> filter(ARM != "SCREEN FAILURE") |> datastep({ if (AGE >= 18 & AGE <= 24) AGECAT = "18 to 24" else if (AGE >= 25 & AGE <= 44) AGECAT = "25 to 44" else if (AGE >= 45 & AGE <= 64) AGECAT <- "45 to 64" else if (AGE >= 65) AGECAT <- ">= 65" }) |> put() put("Get population counts") arm_pop <- count(dm_mod, ARM) |> put() sex_pop <- count(dm_mod, SEX) |> put() agecat_pop <- count(dm_mod, AGECAT) |> put() # Convert agecat to factor so rows will sort correctly agecat_pop$AGECAT <- factor(agecat_pop$AGECAT, levels = c("18 to 24", "25 to 44", "45 to 64", ">= 65")) # Sort agecat agecat_pop <- agecat_pop |> arrange(AGECAT) # Create Plots ------------------------------------------------------------ plt1 <- ggplot(data = arm_pop, aes(x = ARM, y = n)) + geom_col(fill = "#0000A0") + geom_text(aes(label = n), vjust = 1.5, colour = "white") + labs(x = "Treatment Group", y = "Number of Subjects (n)") plt2 <- ggplot(data = sex_pop, aes(x = SEX, y = n)) + geom_col(fill = "#00A000") + geom_text(aes(label = n), vjust = 1.5, colour = "white") + labs(x = "Biological Sex", y = "Number of Subjects (n)") plt3 <- ggplot(data = agecat_pop, aes(x = AGECAT, y = n)) + geom_col(fill = "#A00000") + geom_text(aes(label = n), vjust = 1.5, colour = "white") + labs(x = "Age Categories", y = "Number of Subjects (n)") # Report ------------------------------------------------------------------ sep("Create and print report") page1 <- create_plot(plt1, 4.5, 7) |> titles("Figure 1.1", "Distribution of Subjects by Treatment Group") page2 <- create_plot(plt2, 4.5, 7) |> titles("Figure 1.2", "Distribution of Subjects by Biological Sex") page3 <- create_plot(plt3, 4.5, 7) |> titles("Figure 1.2", "Distribution of Subjects by Age Category") rpt <- create_report(file.path(tmp, "./output/example1.rtf"), output_type = "RTF", font = "Arial") |> set_margins(top = 1, bottom = 1) |> page_header("Sponsor: Company", "Study: ABC") |> add_content(page1) |> add_content(page2) |> add_content(page3) |> footnotes("Program: DM_Figure.R") |> page_footer(paste0("Date Produced: ", fapply(Sys.time(), "%d%b%y %H:%M")), right = "Page [pg] of [tpg]") res <- write_report(rpt) # Clean Up ---------------------------------------------------------------- sep("Clean Up") # Close log log_close() # View log # file.show(lf) # View report # file.show(res$file_path) ``` ## Log Here is the log from the above program: ``` ========================================================================= Log Path: C:/Users/dbosa/AppData/Local/Temp/RtmpwLpEIV/log/example1.log Program Path: C:\packages\Testing\libr_example1.R Working Directory: C:/packages/Testing User Name: dbosa R Version: 4.1.2 (2021-11-01) Machine: SOCRATES x86-64 Operating System: Windows 10 x64 build 19041 Base Packages: stats graphics grDevices utils datasets methods base Other Packages: tidylog_1.0.2 reporter_1.2.6 libr_1.2.1 fmtr_1.5.4 logr_1.2.7 sassy_1.0.5 forcats_0.5.1 stringr_1.4.0 dplyr_1.0.7 purrr_0.3.4 readr_2.0.2 tidyr_1.1.4 tibble_3.1.5 ggplot2_3.3.5 tidyverse_1.3.1 Log Start Time: 2021-11-20 23:06:50 ========================================================================= ========================================================================= Prepare Data ========================================================================= # library 'sdtm': 8 items - attributes: csv not loaded - path: C:/Users/dbosa/Documents/R/win-library/4.1/libr/extdata - items: Name Extension Rows Cols Size LastModified 1 AE csv 150 27 88.3 Kb 2021-10-08 15:02:15 2 DA csv 3587 18 528.1 Kb 2021-10-08 15:02:15 3 DM csv 87 24 45.4 Kb 2021-10-08 15:02:15 4 DS csv 174 9 33.9 Kb 2021-10-08 15:02:15 5 EX csv 84 11 26.2 Kb 2021-10-08 15:02:15 6 IE csv 2 14 13.2 Kb 2021-10-08 15:02:15 7 SV csv 685 10 70.2 Kb 2021-10-08 15:02:15 8 VS csv 3358 17 467.3 Kb 2021-10-08 15:02:15 lib_load: library 'sdtm' loaded select: dropped 20 variables (STUDYID, DOMAIN, SUBJID, RFSTDTC, RFENDTC, ) filter: removed 2 rows (2%), 85 rows remaining datastep: columns increased from 4 to 5 # A tibble: 85 x 5 USUBJID SEX AGE ARM AGECAT 1 ABC-01-049 M 39 ARM D 25 to 44 2 ABC-01-050 M 47 ARM B 45 to 64 3 ABC-01-051 M 34 ARM A 25 to 44 4 ABC-01-052 F 45 ARM C 45 to 64 5 ABC-01-053 F 26 ARM B 25 to 44 6 ABC-01-054 M 44 ARM D 25 to 44 7 ABC-01-055 F 47 ARM C 45 to 64 8 ABC-01-056 M 31 ARM A 25 to 44 9 ABC-01-113 M 74 ARM D >= 65 10 ABC-01-114 F 72 ARM B >= 65 # ... with 75 more rows Get population counts count: now 4 rows and 2 columns, ungrouped # A tibble: 4 x 2 ARM n 1 ARM A 20 2 ARM B 21 3 ARM C 21 4 ARM D 23 count: now 2 rows and 2 columns, ungrouped # A tibble: 2 x 2 SEX n 1 F 32 2 M 53 count: now 4 rows and 2 columns, ungrouped # A tibble: 4 x 2 AGECAT n 1 >= 65 13 2 18 to 24 5 3 25 to 44 23 4 45 to 64 44 ========================================================================= Create and print report ========================================================================= # A report specification: 3 pages - file_path: 'C:\Users\dbosa\AppData\Local\Temp\RtmpwLpEIV/./output/example1.rtf' - output_type: RTF - units: inches - orientation: landscape - margins: top 1 bottom 1 left 1 right 1 - line size/count: 9/40 - page_header: left=Sponsor: Company right=Study: ABC - footnote 1: 'Program: DM_Figure.R' - page_footer: left=Date Produced: 20Nov21 23:06 center= right=Page [pg] of [tpg] - content: # A plot specification: - data: 4 rows, 2 cols - layers: 2 - height: 4.5 - width: 7 - title 1: 'Figure 1.1' - title 2: 'Distribution of Subjects by Treatment Group' # A plot specification: - data: 2 rows, 2 cols - layers: 2 - height: 4.5 - width: 7 - title 1: 'Figure 1.2' - title 2: 'Distribution of Subjects by Biological Sex' # A plot specification: - data: 4 rows, 2 cols - layers: 2 - height: 4.5 - width: 7 - title 1: 'Figure 1.2' - title 2: 'Distribution of Subjects by Age Category' ========================================================================= Clean Up ========================================================================= lib_sync: synchronized data in library 'sdtm' lib_unload: library 'sdtm' unloaded ========================================================================= Log End Time: 2021-11-20 23:06:57 Log Elapsed Time: 0 00:00:07 ========================================================================= ``` ## Output And here is the output: Example 1 page 1 Example 1 page 2 Example 1 page 3 Next: [Complete Example 2](libr-example2.html)