inst/doc/kodom-lines.R

In ggkodom: Visualize Individual Longitudinal Trajectories

## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.width = 7,
  fig.height = 4.2,
  out.width = "100%"
)
library(ggkodom)
library(ggplot2)

## ----data---------------------------------------------------------------------
set.seed(42)
n_subjects <- 25
n_obs_per <- sample(6:12, n_subjects, replace = TRUE)

df <- do.call(rbind, lapply(seq_len(n_subjects), function(i) {
  n <- n_obs_per[i]
  base <- rnorm(1, mean = 7.5, sd = 1.2)
  trend <- rnorm(1, mean = -0.02, sd = 0.01)
  time <- sort(runif(n, 0, 24))
  value <- base + trend * time + rnorm(n, sd = 0.4)
  data.frame(
    subject_id = sprintf("P%03d", i),
    visit_month = time,
    relative_month = time - min(time),
    hba1c = pmax(4, value),
    arm = ifelse(i <= 12, "Treatment", "Control"),
    age = sample(30:75, 1),
    stringsAsFactors = FALSE
  )
}))

## ----basic--------------------------------------------------------------------
ggplot(df, aes(x = visit_month, id = subject_id, colour = hba1c)) +
  geom_kodom_line() +
  scale_colour_kodom() +
  labs(x = "Visit (months)", y = "", colour = "HbA1c (%)") +
  theme_kodom()

## ----sort, fig.height = 5-----------------------------------------------------
# Top lanes = highest mean HbA1c, bottom = lowest
ggplot(df, aes(x = visit_month, id = subject_id, colour = hba1c)) +
  geom_kodom_line(sort_by = "mean") +
  scale_colour_kodom() +
  labs(x = "Visit (months)", y = "", title = 'sort_by = "mean"') +
  theme_kodom(legend_position = "top")

## ----transform----------------------------------------------------------------
ggplot(df, aes(x = relative_month, id = subject_id, colour = hba1c)) +
  geom_kodom_line(sort_by = "first") +
  scale_colour_kodom() +
  labs(x = "Visit (months)", y = "", title = 'sort_by = "mean"') +
  theme_kodom(legend_position = "top")

## ----n_max, fig.height = 6----------------------------------------------------
ggplot(df, aes(x = visit_month, id = subject_id, colour = hba1c)) +
  geom_kodom_line(sort_by = "mean", n_max = 12) +
  scale_colour_kodom() +
  labs(x = "Visit (months)", y = "", title = "12 randomly sampled subjects") +
  theme_kodom()

## ----points-compare, fig.height = 6-------------------------------------------
p_base <- ggplot(df, aes(x = visit_month, id = subject_id, colour = hba1c)) +
  scale_colour_kodom() +
  labs(x = "Visit (months)", y = "") +
  theme_kodom()

p_base + geom_kodom_line(show_points = TRUE) +
  labs(title = "show_points = TRUE (default)")

## ----points-off, fig.height = 6-----------------------------------------------
p_base + geom_kodom_line(show_points = FALSE) +
  labs(title = "show_points = FALSE")

## ----points-na----------------------------------------------------------------
p_base + geom_kodom_line(shape = NA) +
  labs(title = "shape = NA — same effect as show_points = FALSE")

## ----point-shapes, fig.height = 6---------------------------------------------
# shape 21 = filled circle — fill controls interior, colour controls border
ggplot(
  df,
  aes(x = visit_month, id = subject_id, colour = hba1c, fill = hba1c)
) +
  geom_kodom_line(shape = 21, size = 2.5, stroke = 0.6) +
  scale_colour_kodom() +
  scale_fill_kodom() +
  labs(x = "Visit (months)", y = "", title = "shape = 21 with fill + colour") +
  theme_kodom()

## ----point-diamonds, fig.height = 6-------------------------------------------
# shape 23 = filled diamond
ggplot(
  df,
  aes(x = visit_month, id = subject_id, colour = hba1c, fill = hba1c)
) +
  geom_kodom_line(shape = 23, size = 2.5) +
  scale_colour_kodom() +
  scale_fill_kodom() +
  labs(x = "Visit (months)", y = "", title = "shape = 23 (diamond)") +
  theme_kodom()

## ----linewidth, fig.height = 6------------------------------------------------
ggplot(df, aes(x = visit_month, id = subject_id, colour = hba1c)) +
  geom_kodom_line(linewidth = 3, alpha = 0.5) +
  scale_colour_kodom() +
  labs(x = "Visit (months)", y = "", title = "linewidth = 3, alpha = 0.5") +
  theme_kodom()

## ----discrete, fig.height = 6-------------------------------------------------
ggplot(df, aes(x = visit_month, id = subject_id, colour = hba1c)) +
  geom_kodom_line(sort_by = "mean") +
  scale_colour_kodom(
    discretize   = TRUE,
    color_breaks = c(5.7, 6.5, 8),
    name         = "HbA1c (%)"
  ) +
  labs(x = "Visit (months)", y = "", title = "Discrete clinical bands") +
  theme_kodom()

## ----size-age-----------------------------------------------------------------
ggplot(df, aes(
  x = visit_month, id = subject_id,
  colour = hba1c, size = age
)) +
  geom_kodom_line(sort_by = "mean", linewidth = 0.4) +
  scale_colour_kodom() +
  scale_size_continuous(range = c(1, 4), name = "Age") +
  labs(
    x = "Visit (months)", y = "",
    title = "Point size = patient age, path width fixed"
  ) +
  theme_kodom()

## ----alpha-age----------------------------------------------------------------
ggplot(df, aes(
  x = visit_month, id = subject_id,
  colour = hba1c, alpha = age
)) +
  geom_kodom_line(sort_by = "mean") +
  scale_colour_kodom() +
  scale_alpha_continuous(range = c(0.2, 1), name = "Age") +
  labs(
    x = "Visit (months)", y = "",
    title = "Opacity = patient age"
  ) +
  theme_kodom()

## ----size-alpha-age-----------------------------------------------------------
ggplot(df, aes(
  x = visit_month, id = subject_id,
  colour = hba1c, size = age, alpha = age
)) +
  geom_kodom_line(sort_by = "mean", linewidth = 0.3) +
  scale_colour_kodom() +
  scale_size_continuous(range = c(1, 4), name = "Age") +
  scale_alpha_continuous(range = c(0.25, 1), guide = "none") +
  labs(
    x = "Visit (months)", y = "",
    title = "Size + opacity both encode age"
  ) +
  theme_kodom()

## ----facet, fig.height = 6----------------------------------------------------
ggplot(df, aes(x = visit_month, id = subject_id, colour = hba1c)) +
  geom_kodom_line(sort_by = "mean") +
  scale_colour_kodom(color_breaks = c(5.7, 6.5, 8)) +
  facet_wrap(~arm) +
  labs(x = "Visit (months)", y = "", title = "Treatment vs. Control") +
  theme_kodom()

## ----y-labels, fig.height = 6-------------------------------------------------
# Suppress y labels for large cohorts — usually the right choice
ggplot(df, aes(x = visit_month, id = subject_id, colour = hba1c)) +
  geom_kodom_line(sort_by = "mean") +
  scale_colour_kodom() +
  labs(x = "Visit (months)", y = "") +
  theme_kodom() +
  theme(axis.text.y = element_blank())

## ----palette, fig.height = 4--------------------------------------------------
# View the three anchor colors and any interpolated expansion
scales::show_col(kodom_colors(7))