---
title: "Complete Example"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{example1}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r setup, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
options(rmarkdown.html_vignette.check_title = FALSE)
```
## Program
The previous examples in the **logr** documentation were intentionally
simplified to focus on the workings of a particular function. It is helpful,
however, to also view **logr** functions in the context of a complete
program. The following example shows a complete program. The example illustrates
how **logr** functions work together, and interact with **tidyverse** and
**sassy** functions to create a comprehensive log.
This example has been chosen
because it incorporates many of the functions that will log automatically.
If you want to maximize the auto-generation features of **logr**, take note of
these functions.
The data for this example has been included in the **logr** package as an
external data file. It may be accessed using the `system.file()` function
as shown below, or downloaded directly from the **logr** GitHub site
[here](https://raw.githubusercontent.com/dbosak01/logr/master/inst/extdata/DM.csv)
```{r eval=FALSE, echo=TRUE}
library(tidyverse)
library(sassy)
options("logr.autolog" = TRUE)
# Get temp location for log and report output
tmp <- tempdir()
# Open the log
lf <- log_open(file.path(tmp, "example1.log"))
# Send code to the log
log_code()
sep("Load the data")
# Get path to sample data
pkg <- system.file("extdata", package = "logr")
# Define data library
libname(sdtm, pkg, "csv")
# Prepare Data -------------------------------------------------------------
sep("Prepare the data")
# Define format for age groups
ageg <- value(condition(x > 18 & x <= 29, "18 to 29"),
condition(x >= 30 & x <= 44, "30 to 44"),
condition(x >= 45 & x <= 59, "45 to 59"),
condition(TRUE, "60+"))
# Manipulate data
final <- sdtm$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")
# Close the log
log_close()
# View Report
# file.show(res$modified_path)
# View Log
# file.show(lf)
```
## Output
Here is the report produced by the sample program:
<img src="../man/images/example1a.png"/>
<img src="../man/images/example1b.png"/>
<img src="../man/images/example1c.png"/>
## Log
The above program produces the following log:
```
=========================================================================
Log Path: C:/Users/dbosa/AppData/Local/Temp/Rtmpw1TuO2/log/example1.log
Program Path: C:/packages/Testing/LogTest24.R
Working Directory: C:/packages/Testing
User Name: dbosa
R Version: 4.4.2 (2024-10-31 ucrt)
Machine: SOCRATES x86-64
Operating System: Windows 10 x64 build 26100
Base Packages: stats graphics grDevices utils datasets methods base
Other Packages: tidylog_1.1.0 procs_1.0.7 reporter_1.4.4 libr_1.3.4 logr_1.3.9
fmtr_1.6.5 common_1.1.3 sassy_1.2.5 lubridate_1.9.3 forcats_1.0.0 stringr_1.5.1
dplyr_1.1.4 purrr_1.0.2 readr_2.1.5 tidyr_1.3.1 tibble_3.2.1 ggplot2_3.5.1
tidyverse_2.0.0
Log Start Time: 2025-03-26 12:50:40.218714
=========================================================================
> library(tidyverse)
> library(sassy)
>
> options("logr.autolog" = TRUE)
>
> # Get temp location for log and report output
> tmp <- tempdir()
>
> # Open the log
> lf <- log_open(file.path(tmp, "example1.log"))
>
> # Send code to the log
> log_code()
>
> sep("Load the data")
>
> # Get path to sample data
> pkg <- system.file("extdata", package = "logr")
>
> # Define data library
> libname(sdtm, pkg, "csv")
>
> # Prepare Data -------------------------------------------------------------
> sep("Prepare the data")
>
> # Define format for age groups
> ageg <- value(condition(x > 18 & x <= 29, "18 to 29"),
> condition(x >= 30 & x <= 44, "30 to 44"),
> condition(x >= 45 & x <= 59, "45 to 59"),
> condition(TRUE, "60+"))
>
>
> # Manipulate data
> final <- sdtm$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")
>
> # Close the log
> log_close()
>
> # View Report
> # file.show(res$modified_path)
>
> # View Log
> # file.show(lf)
>
>
>
=========================================================================
Load the data
=========================================================================
# library 'sdtm': 1 items
- attributes: csv not loaded
- path: C:/Users/dbosa/AppData/Local/R/win-library/4.4/logr/extdata
- items:
Name Extension Rows Cols Size LastModified
1 DM csv 87 24 45.8 Kb 2025-03-26 11:02:29
NOTE: Log Print Time: 2025-03-26 12:50:40.733955
NOTE: Elapsed Time: 0.511612892150879 secs
=========================================================================
Prepare the data
=========================================================================
# A user-defined format: 4 conditions
Name Type Expression Label Order
1 obj U x > 18 & x <= 29 18 to 29 NA
2 obj U x >= 30 & x <= 44 30 to 44 NA
3 obj U x >= 45 & x <= 59 45 to 59 NA
4 obj U TRUE 60+ NA
NOTE: Log Print Time: 2025-03-26 12:50:40.74675
NOTE: Elapsed Time: 0.0127952098846436 secs
select: dropped 21 variables (STUDYID, DOMAIN, SUBJID, RFSTDTC, RFENDTC, …)
NOTE: Log Print Time: 2025-03-26 12:50:40.759215
NOTE: Elapsed Time: 0.0124650001525879 secs
mutate: new variable 'AGEG' (character) with 4 unique values and 0% NA
NOTE: Log Print Time: 2025-03-26 12:50:40.779213
NOTE: Elapsed Time: 0.0199978351593018 secs
group_by: one grouping variable (AGEG)
NOTE: Log Print Time: 2025-03-26 12:50:40.79064
NOTE: Elapsed Time: 0.0114271640777588 secs
datastep: columns increased from 4 to 8
NOTE: Log Print Time: 2025-03-26 12:50:40.911893
NOTE: Elapsed Time: 0.121252775192261 secs
# A tibble: 87 × 8
# Groups: AGEG [4]
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
# ℹ 77 more rows
# ℹ Use `print(n = ...)` to see more rows
NOTE: Data frame has 87 rows and 8 columns.
NOTE: Log Print Time: 2025-03-26 12:50:40.993307
NOTE: Elapsed Time: 0.0814142227172852 secs
ungroup: no grouping variables remain
NOTE: Log Print Time: 2025-03-26 12:50:41.067702
NOTE: Elapsed Time: 0.0743949413299561 secs
# A tibble: 87 × 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
# ℹ 77 more rows
# ℹ Use `print(n = ...)` to see more rows
NOTE: Data frame has 87 rows and 8 columns.
NOTE: Log Print Time: 2025-03-26 12:50:41.219635
NOTE: Elapsed Time: 0.151932954788208 secs
# A tibble: 8 × 11
Name Column Class Label Description Format Width Justify Rows NAs MaxChar
<chr> <chr> <chr> <chr> <chr> <chr> <lgl> <chr> <int> <int> <int>
1 final USUBJID charact… Univ… <NA> <NA> NA <NA> 87 0 10
2 final BRTHDTC Date Subj… <NA> "%m %… NA <NA> 87 0 10
3 final AGE numeric Subj… <NA> <NA> NA center 87 0 2
4 final AGEG charact… Subj… <NA> <NA> NA left 87 0 8
5 final AGEM numeric Mean… <NA> "%1.2… NA <NA> 87 0 16
6 final AGEB charact… Age … <NA> <NA> NA <NA> 87 0 5
7 final SEQ numeric Subj… <NA> <NA> NA center 87 0 2
8 final AGEMC charact… Subj… <NA> "Belo… NA right 87 0 1
NOTE: Data frame has 8 rows and 11 columns.
NOTE: Log Print Time: 2025-03-26 12:50:41.40138
NOTE: Elapsed Time: 0.181745052337646 secs
=========================================================================
Create report
=========================================================================
# A report specification: 3 pages
- file_path: 'C:\Users\dbosa\AppData\Local\Temp\Rtmpw1TuO2/./output/example1.rtf'
- output_type: RTF
- units: inches
- orientation: landscape
- margins: top 0.5 bottom 0.5 left 1 right 1
- line size/count: 9/42
- 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: 2025-03-26 12:50:41.999186
NOTE: Elapsed Time: 0.597805976867676 secs
=========================================================================
Clean Up
=========================================================================
=========================================================================
Log End Time: 2025-03-26 12:50:42.151877
Log Elapsed Time: 0 00:00:01
=========================================================================
```