Status Quo
library(tidyverse)
library(ggswim)
library(ggplot2)
p1 <- ggplot() +
geom_swim_lane(
data = patient_data,
mapping = aes(
x = start_time, y = pt_id, xend = end_time,
colour = disease_assessment
))
p1
# Construct arrow_data for arrow display later
arrow_data <- patient_data |>
dplyr::left_join(
end_study_events |>
dplyr::select(pt_id, label),
by = "pt_id"
) |>
dplyr::select(pt_id, end_time, label) |>
dplyr::filter(.by = pt_id, end_time == max(end_time)) |>
dplyr::filter(is.na(label)) |>
unique()
p2 <- ggplot() +
geom_swim_arrow(
data = arrow_data,
mapping = aes(xend = end_time, y = pt_id)
) +
scale_colour_brewer(
name = "Disease Assessments",
palette = "Set1"
)
p2
all_events <- dplyr::bind_rows(
infusion_events,
end_study_events
)
head(all_events)
## # A tibble: 6 × 5
## pt_id time_from_initial_infusion label glyph colour
## <chr> <dbl> <chr> <chr> <chr>
## 1 01 1 First Reinfusion ⬤ #999999
## 2 02 0 First Reinfusion ⬤ #999999
## 3 03 2 First Reinfusion ⬤ #999999
## 4 03 3 Second Reinfusion ⬤ #f57dc1
## 5 04 5 First Reinfusion ⬤ #999999
## 6 05 2 First Reinfusion ⬤ #999999
p3 <- ggplot() +
geom_swim_marker(
data = all_events,
aes(x = time_from_initial_infusion, y = pt_id, marker = label),
size = 5
)
p3
library(patchwork)
p1 / p2 / p3
all_events %>%
distinct(glyph, colour, label) ->
marker_dictionary
marker_dictionary
## # A tibble: 5 × 3
## glyph colour label
## <chr> <chr> <chr>
## 1 ⬤ #999999 First Reinfusion
## 2 ⬤ #f57dc1 Second Reinfusion
## 3 ⚠️ <NA> Other End Study Reason
## 4 ❌ <NA> Deceased
## 5 ✅ <NA> Completed Study Follow-Up
p4 <- p3 +
scale_marker_discrete(
glyphs = marker_dictionary$glyph,
colours = marker_dictionary$colour,
limits = marker_dictionary$label,
name = "Study Events"
)
p4
library(ggplot2)
library(ggswim)
geom_marker <- geom_swim_marker
mtcars |>
ggplot() +
aes(x = wt, y = mpg, marker = factor(am)) +
geom_marker(size = 8) +
scale_marker_discrete(
limits = 0:1,
colours = c("orange", "midnightblue")
)
## Warning in scale_marker_discrete(limits = 0:1, colours = c("orange", "midnightblue")): Continuous limits supplied to discrete scale.
## ℹ Did you mean `limits = factor(...)` or `scale_*_continuous()`?
# scale_marker_discrete(
# limits = c("First Reinfusion",
# "Second Reinfusion",
# "Other End Study Reason",
# "Deceased",
# "Completed Study Follow-Up"),
# glyphs = c( "⬤" , "⬤" ,"⚠️" , "❌" ,"✅"),
# colours = c("#999999", "#f57dc1", NA, NA, NA),
# name = "Study Events"
# )