library(tidyplots)
# Create a data frame
df <- tibble::tibble(
x = c(1, 2, 3, 3.5),
y = rep(1, times = 4)
)
df
# Set several fixed locations/constants for efficient adjustment
text_up_dn <- 0.1 # vertical distance (tailored) to line
text_x <- df$x[1:3] # x axis locations (center) of texts
text_y <- df$y[1:3] - text_up_dn
rectangle_half_width <- 0.4 # half length (tailored) of rectangle behind text
rectangle_half_height <- 0.05
line_yend <- text_y + rectangle_half_height
labels <- c(
"# Experiment design \n# Group blinding \n# Reagent preparation\n# Reagent blinding",
"# Experiment performing\n# Collecting data ",
"# Unblinding")
person_a <- "images/person_a.png" |>
magick::image_read() |>
grid::rasterGrob()
person_b <- "images/person_b.png" |>
magick::image_read() |>
grid::rasterGrob()
person_c <- "images/person_c.png" |>
magick::image_read() |>
grid::rasterGrob()
# Plot
df |> tidyplot(x = x, y = y, color = y) |>
add_line(
arrow = grid::arrow(length = grid::unit(0.25, "cm")),
color = "#3d4f6a",
linewidth = 1
) |>
add_annotation_rectangle(
xmin = text_x - rectangle_half_width,
xmax = text_x + rectangle_half_width,
ymin = text_y + rectangle_half_height,
ymax = text_y - rectangle_half_height,
fill = c(c("#eecc66", "#ee99aa", "#6699cc")),
alpha = 1
) |>
add_annotation_text(
text = labels,
x = text_x,
y = text_y,
fontface = "bold"
) |>
add_annotation_line(
x = text_x,
xend = text_x,
y = 1.10,
yend = line_yend,
arrow = grid::arrow(length = grid::unit(0.15, "cm")),
color = c("#eecc66", "#ee99aa", "#6699cc")
) |>
add(ggplot2::annotation_custom(person_a, xmin = 0.8, xmax = 1.2, ymin = 1.05, ymax = 1.15)) |>
add(ggplot2::annotation_custom(person_b, xmin = 1.8, xmax = 2.2, ymin = 1.05, ymax = 1.15)) |>
add(ggplot2::annotation_custom(person_c, xmin = 2.8, xmax = 3.2, ymin = 1.05, ymax = 1.15)) |>
add_data_points(
data = filter_rows(x <= 3),
size = 4,
white_border = TRUE,
color = c("#eecc66", "#ee99aa", "#6699cc")) |>
adjust_title(
title = "A reliable way of experiment performing?",
fontsize = 14,
color = "#bb5566") |>
add_caption(caption = "Images are from <https://bioart.niaid.nih.gov/>\nImages do not represent genders.") |>
adjust_size(width = 150) |>
adjust_x_axis(limits = c(0.5, 3.6)) |>
adjust_y_axis(limits = c(0.85, 1.15)) |>
remove_x_axis() |>
remove_y_axis() |>
save_plot("images/2026-05-13_experiment-performing.png",
view_plot = FALSE)9 A reliable way of experiment performing?
For the purpose of authenticity
耿同学讲故事最近很流行，其主要是发现文章的造假等等。
这里列一个实验的执行策略，目的是为了得到客观的实验结果，省得给以后的自己挖坑。
假如一个项目可拆解为100个实验，其中有多少个实验需要采用这个策略？
以下是生成如上图片的代码。