介绍
rayrender 是一个R语言编写的开源包，用于创建光线跟踪场景。这个包为用 C++ 构建的光线追踪器提供了一个整洁的 R API，以渲染由一组基元构建的场景。 rayrender 使用可管道化的迭代界面构建场景，并支持漫反射、金属、电介质（玻璃）、发光材料，以及程序和用户指定的图像纹理和 HDR 环境照明。 rayrender 包括通过 RcppThread 的多核支持（带有进度条）、通过 PCG RNG 的随机数生成以及通过 TinyObrjLoader 的 .obj 文件支持。
官网链接
Build and Raytrace 3D Scenes • rayrender
数据源
NASA社会数据应用中心的世界格网人口数据V4版本,2010年30km级别数据
可视化过程
安装R语言环境
安装rayrender,rayshader,rgdal,magick等包
运行脚本
利用Python脚本拼接单独生成的PNG格式的图片为GIF格式的图片
可视化脚本
library(rayshader)
library(rayrender)
popdata = raster::raster("gpw_v4_basic_demographic_characteristics_rev11_atotpopbt_2010_dens_15_min.tif")
population_mat = rayshader:::flipud(raster_to_matrix(popdata))
above1 = population_mat > 1
above5 = population_mat > 5
above10 = population_mat > 10
above50 = population_mat > 50
above100 = population_mat > 100
above500 = population_mat > 500
above1000 = population_mat > 1000
above1[is.na(above1)] = 0
above5[is.na(above5)] = 0
above10[is.na(above10)] = 0
above50[is.na(above50)] = 0
above100[is.na(above100)] = 0
above500[is.na(above500)] = 0
above1000[is.na(above1000)] = 0
turbocols = viridis::turbo(7)
wc = 0.4
chart_items =
xy_rect(x=-1,y=-1.4,z=1,xwidth=wc,ywidth=0.2,
material=diffuse(color="grey30")) %>%
add_object(text3d(label = "0", x=-1,y=-1.4,z=1.01, text_height = 0.1,
material=diffuse(color="black"))) %>%
add_object(xy_rect(x=-0.6,y=-1.4,z=1,xwidth=wc,ywidth=0.2,
material=diffuse(color=turbocols[1]))) %>%
add_object(text3d(label = "1>", x=-0.6,y=-1.4,z=1.01, text_height = 0.1,
material=diffuse(color="black"))) %>%
add_object(xy_rect(x=-0.2,y=-1.4,z=1,xwidth=wc,ywidth=0.2,
material=diffuse(color=turbocols[2]))) %>%
add_object(text3d(label = "5>", x=-0.2,y=-1.4,z=1.01, text_height = 0.1,
material=diffuse(color="black"))) %>%
add_object(xy_rect(x=0.2,y=-1.4,z=1,xwidth=wc,ywidth=0.2,
material=diffuse(color=turbocols[3]))) %>%
add_object(text3d(label = "10>", x=0.2,y=-1.4,z=1.01, text_height = 0.1,
material=diffuse(color="black"))) %>%
add_object(xy_rect(x=0.6,y=-1.4,z=1,xwidth=wc,ywidth=0.2,
material=diffuse(color=turbocols[4]))) %>%
add_object(text3d(label = "50>", x=0.6,y=-1.4,z=1.01, text_height = 0.1,
material=diffuse(color="black"))) %>%
add_object(xy_rect(x=1.0,y=-1.4,z=1,xwidth=wc,ywidth=0.2,
material=diffuse(color=turbocols[5]))) %>%
add_object(text3d(label = "100>", x=1.0,y=-1.4,z=1.01, text_height = 0.1,
material=diffuse(color="black"))) %>%
add_object(xy_rect(x=1.4,y=-1.4,z=1,xwidth=wc,ywidth=0.2,
material=diffuse(color=turbocols[6]))) %>%
add_object(text3d(label = "500>", x=1.4,y=-1.4,z=1.01, text_height = 0.1,
material=diffuse(color="black"))) %>%
add_object(xy_rect(x=1.8,y=-1.4,z=1,xwidth=wc,ywidth=0.2,
material=diffuse(color=turbocols[7]))) %>%
add_object(text3d(label = "1000>", x=1.8,y=-1.4,z=1.01, text_height = 0.1,
material=diffuse(color="black"))) %>%
add_object(text3d(label = "People per 30km^2", x=-0.55,y=-1.2,z=1.01, text_height = 0.15,
material=diffuse(color="white"))) %>%
group_objects(group_translate = c(-0.4,0,0),group_scale=c(0.85,0.85,0.85))
radm = 1.2
for(i in 1:720) {
chart_items %>%
add_object(group_objects(
sphere(radius=0.99*radm,material=diffuse(color="grey20")) %>%
add_object(sphere(radius=1.0*radm,material= diffuse(color=turbocols[1],alpha_texture = above1))) %>%
add_object(sphere(radius=1.02*radm,material=diffuse(color=turbocols[2],alpha_texture = above5))) %>%
add_object(sphere(radius=1.03*radm,material=diffuse(color=turbocols[3],alpha_texture = above10))) %>%
add_object(sphere(radius=1.04*radm,material=diffuse(color=turbocols[4],alpha_texture = above50))) %>%
add_object(sphere(radius=1.05*radm,material=diffuse(color=turbocols[5],alpha_texture = above100))) %>%
add_object(sphere(radius=1.06*radm,material=diffuse(color=turbocols[6],alpha_texture = above500))) %>%
add_object(sphere(radius=1.07*radm,material=diffuse(color=turbocols[7],alpha_texture = above1000))),
group_angle = c(0,-i/2,0))) %>%
add_object(sphere(y=10,z=5,radius=3,material=light(intensity = 20))) %>%
add_object(sphere(y=0,z=20,radius=3,material=light(intensity = 20))) %>%
render_scene(width=1000,height=1000,samples=128,rotate_env = 180,clamp_value = 10,
aperture=0,
filename=sprintf("worldpopfocus%i.png",i), lookat=c(0,-0.2,0))
}
单帧生成的结果图
worldpopfocus1.png
利用Python脚本拼接多张PNG图像
import imageio
def create_gif(image_list, gif_name):
frames = []
for image_name in image_list:
frames.append(imageio.imread(image_name))
imageio.mimsave(gif_name, frames, 'GIF', duration=0.1)
return
def main():
image_list = ["rayrender\worldpopfocus" +
str(x)+".png" for x in range(1, 200)]
gif_name = 'rayrender\created_gif.gif'
create_gif(image_list, gif_name)
if __name__ == "__main__":
main()
动态可视化结果
部分地区人口密度动态图.gif
总结
rayrender提供了非常方便简洁的调用方式，即可实现很强的光线渲染效果。在GIS领域，如何实现好的光线渲染效果是一个比较热门的研究方向，而rayrender的渲染结果就非常出色，可以用于数字地形渲染、动态制图等方向。
