本文分享基于R绘制圣诞树~~~
一个成成品~~~
# load packages
library(tidyverse)
library(rlang)
# source grow_tree.R script (assuming it is in the /R subdirectory of the working directory)
source('C:/Users/xx/R/grow_tree.R')#主函数
# define simple angle, length and survival functions
angle_fun1 <- function(angle) angle + c(-0.1 * pi, 0.1 * pi)
# angle: parent angle +- 0.1pi
length_fun1 <- function(length) 0.85 * length
# length: 85% of parent length
surv_fun1 <- function() 0.9
# survival probability: 90% for both children
# define random seed (for reproducibility)
set.seed(12345)
# grow your first tree (using 15 iterations)
tree1 <- grow_tree(n_iter = 10,
angle_fun = angle_fun1(angle),
length_fun = length_fun1(length),
surv_fun = surv_fun1(),
verbose = FALSE) # do not print progress
# plot with the plot_tree function
# (ony_living = TRUE excludes all dead segments from the plot)
plot_tree(tree1, only_living = TRUE)#绘制枝干 
# angle defined as a function of generation and parent angle;
# symmetric bifurcation with increasing average angle and variability in
# angles higher up in the canopy
angle_fun2 <- function(angle, generation){
# weights that get bigger which each generation
w <- 1 - 1 / generation
# get absolute deviations from parent segment angle
a0 <- rnorm(1, 0.12 * w * pi, 0.05 * w * pi)
# return new angles with randomized order
angle + sample(c(-a0, a0))
}
# length as a function of parent length, decreasing on average by 10 percent
# with stochastic variation
length_fun2 <- function(length) rnorm(2, 0.9, 0.05) * length
# survival function as a function of generation and number of iterations -
# one of the branches survives with a probability of 95%, the 'survival'
# probability of the other branch increases with tree age (looks more
# realistic because it seems like broken off branches)
surv_fun2 <- function(generation, n_iter) c(.75 - (n_iter - generation[1]) / (2 * n_iter), .95)
# set random seed
set.seed(999)
# grow tree for 25 iterations
tree2 <- grow_tree(n_iter = 25,
angle_fun2(angle, generation),
length_fun2(length),
surv_fun2(generation, 25), # note that n_iter has to be
# specified explicitly because it
# is not in the treetab
verbose = FALSE)
# plot tree
plot_tree(tree2)#长上叶子
# clean the second tree，#结上果子
tree2_clean <- clean_tree(tree2)
# set random seed
set.seed(13579)
# extract 30 random basal ends of the terminal branches
baubles <- filter(tree2_clean,
generation == 25,
pos == 0) %>%
sample_n(30)
# add baubles to the tree
p1 +
# red baubles with black outlines
geom_point(data = baubles, aes(x = x, y = y),
fill = "#AA1243", col = 1, pch = 21, size = 5) +
# white transparent shine (with a small offset to avoid the center)
geom_point(data = baubles, aes(x = x, y = y),
col = "white", alpha = 0.3, size = 1,
position = position_nudge(x = -0.08, y = 0.08)
)