Example 3: Figures"
In sassy: Makes 'R' Easier for Everyone

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

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
=========================================================================

Next: Example 4: Adverse Events Table