Example 3: Figures
The sassy system of functions also supports reports with graphics. Plots from the popular ggplot2 package can be added to a report. The following example illustrates such a report.
Program
Note the following about this example:
- The plots are created using ggplot2 and the
create_plot()function. - The plots are added to the report with the
add_content()function, just like the tables in the previous examples. - The reporter package allows you to add multiple pieces of content to the same report.
- Titles, footnotes, and other report enhancements are added to the figure just like previous examples.
library(ggplot2)
library(sassy)
# Prepare Log -------------------------------------------------------------
options("logr.autolog" = TRUE,
"logr.notes" = FALSE)
# Get path to temp directory
tmp <- tempdir()
# Get sample data directory
dir <- system.file("extdata", package = "sassy")
# Open log
lgpth <- log_open(file.path(tmp, "example3.log"))
# Load and Prepare Data ---------------------------------------------------
sep("Prepare Data")
# Define data library
libname(sdtm, dir, "csv")
put("Prepare format")
agefmt <- value(condition(x >= 18 & x <= 24, "18 to 24"),
condition(x >= 25 & x <= 44, "25 to 44"),
condition(x >= 45 & x <= 64, "45 to 64"),
condition(x >= 65, ">= 65"))
put("Prepare data")
datastep(sdtm$DM, keep = v(USUBJID, SEX, AGE, ARM, AGECAT),
where = expression(ARM != "SCREEN FAILURE"),
{
AGECAT <- fapply(AGE, agefmt)
}) -> dm_mod
put("Get population counts")
proc_freq(dm_mod, tables = ARM,
options = v(nonobs, nopercent)) -> arm_pop
proc_freq(dm_mod, tables = SEX,
options = v(nonobs, nopercent)) -> sex_pop
proc_freq(dm_mod, tables = AGECAT,
options = v(nonobs, nopercent)) -> agecat_pop
put("Convert agecat to factor so rows will sort correctly")
agecat_pop$CAT <- factor(agecat_pop$CAT, levels = levels(agefmt))
put("Sort agecat")
agecat_pop <- proc_sort(agecat_pop, by = CAT)
# Create Plots ------------------------------------------------------------
plt1 <- ggplot(data = arm_pop, aes(x = CAT, y = CNT)) +
geom_col(fill = "#0000A0") +
geom_text(aes(label = CNT), vjust = 1.5, colour = "white") +
labs(x = "Treatment Group", y = "Number of Subjects (n)")
plt2 <- ggplot(data = sex_pop, aes(x = CAT, y = CNT)) +
geom_col(fill = "#00A000") +
geom_text(aes(label = CNT), vjust = 1.5, colour = "white") +
labs(x = "Biological Sex", y = "Number of Subjects (n)")
plt3 <- ggplot(data = agecat_pop, aes(x = CAT, y = CNT)) +
geom_col(fill = "#A00000") +
geom_text(aes(label = CNT), vjust = 1.5, colour = "white") +
labs(x = "Age Categories", y = "Number of Subjects (n)")
# Report ------------------------------------------------------------------
sep("Create and print report")
pth <- file.path(tmp, "output/example3.rtf")
page1 <- create_plot(plt1, 4.5, 7) |>
titles("Figure 1.1", "Distribution of Subjects by Treatment Group",
bold = TRUE, font_size = 11)
page2 <- create_plot(plt2, 4.5, 7) |>
titles("Figure 1.2", "Distribution of Subjects by Biological Sex",
bold = TRUE, font_size = 11)
page3 <- create_plot(plt3, 4.5, 7) |>
titles("Figure 1.2", "Distribution of Subjects by Age Category",
bold = TRUE, font_size = 11)
rpt <- create_report(pth, 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]")
write_report(rpt)
# Clean Up ----------------------------------------------------------------
# Close log
log_close()
# View files
# file.show(pth)
# file.show(lgpth)Output
Here are the three pages of the report:
Log
Here is the log for the above program:
=========================================================================
Log Path: C:/Users/dbosa/AppData/Local/Temp/Rtmpo1naKK/log/example3.log
Program Path: C:/packages/Testing/procs/ProcsFigs.R
Working Directory: C:/packages/Testing/procs
User Name: dbosa
R Version: 4.3.1 (2023-06-16 ucrt)
Machine: SOCRATES x86-64
Operating System: Windows 10 x64 build 22621
Base Packages: stats graphics grDevices utils datasets methods base Other
Packages: tidylog_1.0.2 ggplot2_3.4.2 procs_1.0.3 reporter_1.4.1 libr_1.2.8
fmtr_1.5.9 logr_1.3.4 common_1.0.8 sassy_1.1.0
Log Start Time: 2023-09-06 18:32:28.438427
=========================================================================
=========================================================================
Prepare Data
=========================================================================
# library 'sdtm': 7 items
- attributes: csv not loaded
- path: C:/Users/dbosa/AppData/Local/R/win-library/4.3/sassy/extdata
- items:
Name Extension Rows Cols Size LastModified
1 AE csv 150 27 88.5 Kb 2023-08-07 17:51:40
2 DM csv 87 24 45.5 Kb 2023-08-07 17:51:40
3 DS csv 174 9 34.1 Kb 2023-08-07 17:51:40
4 EX csv 84 11 26.4 Kb 2023-08-07 17:51:40
5 IE csv 2 14 13.4 Kb 2023-08-07 17:51:40
6 SV csv 685 10 70.3 Kb 2023-08-07 17:51:40
7 VS csv 3358 17 467.4 Kb 2023-08-07 17:51:40
Prepare format
# A user-defined format: 4 conditions
Name Type Expression Label Order
1 obj U x >= 18 & x <= 24 18 to 24 NA
2 obj U x >= 25 & x <= 44 25 to 44 NA
3 obj U x >= 45 & x <= 64 45 to 64 NA
4 obj U x >= 65 >= 65 NA
Prepare data
datastep: columns decreased from 24 to 5
# A tibble: 85 × 5
USUBJID SEX AGE ARM AGECAT
<chr> <chr> <dbl> <chr> <chr>
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
# ℹ 75 more rows
# ℹ Use `print(n = ...)` to see more rows
Get population counts
proc_freq: input data set 85 rows and 5 columns
tables: ARM
view: TRUE
output: 1 datasets
# A tibble: 4 × 3
VAR CAT CNT
<chr> <chr> <dbl>
1 ARM ARM A 20
2 ARM ARM B 21
3 ARM ARM C 21
4 ARM ARM D 23
proc_freq: input data set 85 rows and 5 columns
tables: SEX
view: TRUE
output: 1 datasets
# A tibble: 2 × 3
VAR CAT CNT
<chr> <chr> <dbl>
1 SEX F 32
2 SEX M 53
proc_freq: input data set 85 rows and 5 columns
tables: AGECAT
view: TRUE
output: 1 datasets
# A tibble: 4 × 3
VAR CAT CNT
<chr> <chr> <dbl>
1 AGECAT >= 65 13
2 AGECAT 18 to 24 5
3 AGECAT 25 to 44 23
4 AGECAT 45 to 64 44
Convert agecat to factor so rows will sort correctly
Sort agecat
proc_sort: input data set 4 rows and 3 columns
by: CAT
keep: VAR CAT CNT
order: a
output data set 4 rows and 3 columns
# A tibble: 4 × 3
VAR CAT CNT
<chr> <fct> <dbl>
1 AGECAT 18 to 24 5
2 AGECAT 25 to 44 23
3 AGECAT 45 to 64 44
4 AGECAT >= 65 13
=========================================================================
Create and print report
=========================================================================
# A report specification: 3 pages
- file_path: 'C:\Users\dbosa\AppData\Local\Temp\Rtmpo1naKK/output/example3.rtf'
- output_type: RTF
- units: inches
- orientation: landscape
- margins: top 1 bottom 1 left 1 right 1
- line size/count: 9/36
- page_header: left=Sponsor: Company right=Study: ABC
- footnote 1: 'Program: DM_Figure.R'
- page_footer: left=Date Produced: 06Sep23 18:32 center= right=Page [pg] of [tpg]
- content:
# A plot specification:
- data: 4 rows, 3 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, 3 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, 3 cols
- layers: 2
- height: 4.5
- width: 7
- title 1: 'Figure 1.2'
- title 2: 'Distribution of Subjects by Age Category'
lib_sync: synchronized data in library 'sdtm'
=========================================================================
Log End Time: 2023-09-06 18:32:32.220485
Log Elapsed Time: 0 00:00:03
=========================================================================