knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) options(rmarkdown.html_vignette.check_title = FALSE)
The previous examples in the logr documentation were intentionally simplified to focus on the workings of a particular function. It is helpful, however, to also view logr functions in the context of a complete program. The following example shows a complete program. The example illustrates how logr functions work together, and interact with tidyverse and sassy functions to create a comprehensive log.
This example has been chosen because it incorporates many of the functions that will log automatically. If you want to maximize the auto-generation features of logr, take note of these functions.
The data for this example has been included in the logr package as an
external data file. It may be accessed using the system.file()
function
as shown below, or downloaded directly from the logr GitHub site
here
library(tidyverse) library(sassy) options("logr.autolog" = TRUE) # Get temp location for log and report output tmp <- tempdir() # Open the log lf <- log_open(file.path(tmp, "example1.log")) # Send code to the log log_code() sep("Load the data") # Get path to sample data pkg <- system.file("extdata", package = "logr") # Define data library libname(sdtm, pkg, "csv") # Load the library into memory lib_load(sdtm) # Prepare Data ------------------------------------------------------------- sep("Prepare the data") # Define format for age groups ageg <- value(condition(x > 18 & x <= 29, "18 to 29"), condition(x >= 30 & x <= 44, "30 to 44"), condition(x >= 45 & x <= 59, "45 to 59"), condition(TRUE, "60+")) # Manipulate data final <- sdtm.DM %>% select(USUBJID, BRTHDTC, AGE) %>% mutate(AGEG = fapply(AGE, ageg)) %>% arrange(AGEG, AGE) %>% group_by(AGEG) %>% datastep(retain = list(SEQ = 0), calculate = {AGEM <- mean(AGE)}, attrib = list(USUBJID = dsattr(label = "Universal Subject ID"), BRTHDTC = dsattr(label = "Subject Birth Date", format = "%m %B %Y"), AGE = dsattr(label = "Subject Age in Years", justify = "center"), AGEG = dsattr(label = "Subject Age Group", justify = "left"), AGEB = dsattr(label = "Age Group Boundaries"), SEQ = dsattr(label = "Subject Age Group Sequence", justify = "center"), AGEM = dsattr(label = "Mean Subject Age", format = "%1.2f"), AGEMC = dsattr(label = "Subject Age Mean Category", format = c(B = "Below", A = "Above"), justify = "right")), { # Start and end of Age Groups if (first. & last.) AGEB <- "Start - End" else if (first.) AGEB <- "Start" else if (last.) AGEB <- "End" else AGEB <- "-" # Sequence within Age Groups if (first.) SEQ <- 1 else SEQ <- SEQ + 1 # Above or Below the mean age if (AGE > AGEM) AGEMC <- "A" else AGEMC <- "B" }) %>% ungroup() %>% put() # Put dictionary to log dictionary(final) %>% put() # Create Report ------------------------------------------------------------ sep("Create report") # Create table tbl <- create_table(final) # Create report rpt <- create_report(file.path(tmp, "./output/example1.rtf"), output_type = "RTF", font = "Arial") %>% titles("Our first SASSY report", bold = TRUE) %>% add_content(tbl) # write out the report res <- write_report(rpt) # Clean Up ----------------------------------------------------------------- sep("Clean Up") # Unload libname lib_unload(sdtm) # Close the log log_close() # View log writeLines(readLines(lf, encoding = "UTF-8")) # View Report # file.show(res$modified_path)
Here is the report produced by the sample program:
The above program produces the following log:
========================================================================= Log Path: C:/Users/dbosa/AppData/Local/Temp/Rtmp6DW7BF/log/example1.log Program Path: C:\packages\logr\vignettes\logr-example1.Rmd Working Directory: C:/packages/logr 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_1.5.3 sassy_1.0.5 forcats_0.5.1 stringr_1.4.0 purrr_0.3.4 readr_2.0.2 tidyr_1.1.4 tibble_3.1.5 ggplot2_3.3.5 tidyverse_1.3.1 logr_1.2.7 dplyr_1.0.7 Log Start Time: 2021-11-16 08:40:18 ========================================================================= > library(tidyverse) > library(sassy) > > options("logr.autolog" = TRUE) > > # Open the log > lf <- log_open() > > # Send code to the log > log_code() > > sep("Load the data") > > # Get path to sample data > pkg <- system.file("extdata", package = "logr") > > # Define data library > libname(sdtm, pkg, "csv") > > # Load the library into memory > lib_load(sdtm) > > > # Prepare Data ------------------------------------------------------------- > sep("Prepare the data") > > # Define format for age groups > ageg <- value(condition(x > 18 & x <= 29, "18 to 29"), > condition(x >= 30 & x <= 44, "30 to 44"), > condition(x >= 45 & x <= 59, "45 to 59"), > condition(TRUE, "60+")) > > > # Manipulate data > final <- sdtm.DM %>% > select(USUBJID, BRTHDTC, AGE) %>% > mutate(AGEG = fapply(AGE, ageg)) %>% > arrange(AGEG, AGE) %>% > group_by(AGEG) %>% > datastep(retain = list(SEQ = 0), > calculate = {AGEM <- mean(AGE)}, > attrib = list(USUBJID = dsattr(label = "Universal Subject ID"), > BRTHDTC = dsattr(label = "Subject Birth Date", > format = "%m %B %Y"), > AGE = dsattr(label = "Subject Age in Years", > justify = "center"), > AGEG = dsattr(label = "Subject Age Group", > justify = "left"), > AGEB = dsattr(label = "Age Group Boundaries"), > SEQ = dsattr(label = "Subject Age Group Sequence", > justify = "center"), > AGEM = dsattr(label = "Mean Subject Age", > format = "%1.2f"), > AGEMC = dsattr(label = "Subject Age Mean Category", > format = c(B = "Below", A = "Above"), > justify = "right")), > { > > # Start and end of Age Groups > if (first. & last.) > AGEB <- "Start - End" > else if (first.) > AGEB <- "Start" > else if (last.) > AGEB <- "End" > else > AGEB <- "-" > > # Sequence within Age Groups > if (first.) > SEQ <- 1 > else > SEQ <- SEQ + 1 > > # Above or Below the mean age > if (AGE > AGEM) > AGEMC <- "A" > else > AGEMC <- "B" > > }) %>% > ungroup() %>% > put() > > # Put dictionary to log > dictionary(final) %>% put() > > # Create Report ------------------------------------------------------------ > sep("Create report") > > > # Create table > tbl <- create_table(final) > > # Create report > rpt <- create_report("./output/example1.rtf", > output_type = "RTF", font = "Arial") %>% > titles("Our first SASSY report", bold = TRUE) %>% > add_content(tbl) > > # write out the report > res <- write_report(rpt) > > > # Clean Up ----------------------------------------------------------------- > sep("Clean Up") > > # Unload libname > lib_unload(sdtm) > > # Close the log > log_close() > > # View log > writeLines(readLines(lf, encoding = "UTF-8")) > > # View Report > # file.show(res$modified_path) ========================================================================= Load the data ========================================================================= # library 'sdtm': 8 items - attributes: csv not loaded - path: C:/Users/dbosa/Documents/R/win-library/4.1/logr/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 NOTE: Log Print Time: 2021-11-16 08:40:54 NOTE: Elapsed Time in seconds: 35.2692317962646 lib_load: library 'sdtm' loaded NOTE: Log Print Time: 2021-11-16 08:41:00 NOTE: Elapsed Time in seconds: 5.96066999435425 ========================================================================= Prepare the data ========================================================================= select: dropped 21 variables (STUDYID, DOMAIN, SUBJID, RFSTDTC, RFENDTC, <U+0085>) NOTE: Log Print Time: 2021-11-16 08:41:09 NOTE: Elapsed Time in seconds: 9.39324498176575 mutate: new variable 'AGEG' (character) with 4 unique values and 0% NA NOTE: Log Print Time: 2021-11-16 08:41:09 NOTE: Elapsed Time in seconds: 0.0129940509796143 group_by: one grouping variable (AGEG) NOTE: Log Print Time: 2021-11-16 08:41:09 NOTE: Elapsed Time in seconds: 0.0119409561157227 datastep: columns increased from 4 to 8 NOTE: Log Print Time: 2021-11-16 08:41:09 NOTE: Elapsed Time in seconds: 0.0947761535644531 ungroup: no grouping variables NOTE: Log Print Time: 2021-11-16 08:41:09 NOTE: Elapsed Time in seconds: 0.0029609203338623 # A tibble: 87 x 8 USUBJID BRTHDTC AGE AGEG AGEM AGEB SEQ AGEMC <chr> <date> <dbl> <chr> <dbl> <chr> <dbl> <chr> 1 ABC-04-128 1987-05-24 19 18 to 29 49.4 Start 1 B 2 ABC-07-011 1985-01-18 21 18 to 29 49.4 - 2 B 3 ABC-09-139 1985-11-13 21 18 to 29 49.4 - 3 B 4 ABC-09-018 1984-08-29 22 18 to 29 49.4 - 4 B 5 ABC-04-074 1983-03-28 23 18 to 29 49.4 - 5 B 6 ABC-01-053 1980-04-07 26 18 to 29 49.4 - 6 B 7 ABC-06-070 1980-02-01 26 18 to 29 49.4 End 7 B 8 ABC-02-112 1976-11-01 30 30 to 44 49.4 Start 1 B 9 ABC-01-056 1975-05-02 31 30 to 44 49.4 - 2 B 10 ABC-03-089 1975-10-02 31 30 to 44 49.4 - 3 B # ... with 77 more rows NOTE: Data frame has 87 rows and 8 columns. NOTE: Log Print Time: 2021-11-16 08:41:09 NOTE: Elapsed Time in seconds: 0.0398931503295898 # A tibble: 8 x 10 Name Column Class Label Description Format Width Justify Rows NAs <chr> <chr> <chr> <chr> <chr> <chr> <int> <chr> <int> <int> 1 final USUBJID character Universa~ <NA> <NA> 10 <NA> 87 0 2 final BRTHDTC Date Subject ~ <NA> "%m %B~ NA <NA> 87 0 3 final AGE numeric Subject ~ <NA> <NA> NA center 87 0 4 final AGEG character Subject ~ <NA> <NA> 8 left 87 0 5 final AGEM numeric Mean Sub~ <NA> "%1.2f" NA <NA> 87 0 6 final AGEB character Age Grou~ <NA> <NA> 5 <NA> 87 0 7 final SEQ numeric Subject ~ <NA> <NA> NA center 87 0 8 final AGEMC character Subject ~ <NA> "Below~ 1 right 87 0 NOTE: Data frame has 8 rows and 10 columns. NOTE: Log Print Time: 2021-11-16 08:41:11 NOTE: Elapsed Time in seconds: 2.2303478717804 ========================================================================= Create report ========================================================================= # A report specification: 3 pages - file_path: 'C:\Users\dbosa\AppData\Local\Temp\Rtmp6DW7BF/./output/example1.rtf' - output_type: RTF - units: inches - orientation: landscape - margins: top 0.5 bottom 0.5 left 1 right 1 - line size/count: 9/46 - title 1: 'Our first SASSY report' - content: # A table specification: - data: tibble 'final' 87 rows 8 cols - show_cols: all - use_attributes: all NOTE: Log Print Time: 2021-11-16 08:41:16 NOTE: Elapsed Time in seconds: 4.57250308990479 ========================================================================= Clean Up ========================================================================= lib_sync: synchronized data in library 'sdtm' NOTE: Log Print Time: 2021-11-16 08:41:17 NOTE: Elapsed Time in seconds: 1.38584780693054 lib_unload: library 'sdtm' unloaded NOTE: Log Print Time: 2021-11-16 08:41:17 NOTE: Elapsed Time in seconds: 0.00399112701416016 ========================================================================= Log End Time: 2021-11-16 08:41:19 Log Elapsed Time: 0 00:00:01 =========================================================================
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