脆皮边缘与topojson？ [英] Crispy edges with topojson?

问题描述

Mike Bostock分享了一系列世界范围的topojson文件。

由于我想要更多的数据和更高的质量，我现在从自然地球生成自己的高质量topojson文件。为了简单，我的makefile /命令是这样的：

  admin_0：crop 
 ../node_modules/topojson/ bin / topojson \ 
 --id-property name \ 
 -p name = name \ 
 -q 1e4 \ 
 --filter = small \ 
 -o admin_0.topo.json \ 
  -  admin_0 =。/ natural_earth_vector / 10m_cultural / ne_10m_admin_0_countries.shp 
  

但我的 3MB 在优雅方面令人惊讶。不完美，但很好，他确实有对角线（！）和他的线使用的各种角度。

我尝试将量化减少到 -q 1e3



从命令行API ，我注意到并阅读尽可能多的：

• -q， - 量化， - 无量化沿任一维度的可微分点的最大数量


• -s，--simplify用于Visvalingam简化的精度阈值


• - 简化比例以保持Visvalingam简化的点数


• - 宽度缩放并进行翻译以适合视口

$ b b p>这可能都有帮助我。我做了一些测试，主要学习了平衡简化是棘手的。我想请经验丰富的用户如何处理和平衡他们的topojson简化。

你采取什么方法？因此...
我应该使用哪些topojson参数来使我的topojson更好？（没有酥脆的楼梯 - 步骤边缘，正确的忠诚的形状）

解决方案

-q VS -s

有关 Topojson：quantization VS simplification 。

您的几何的总大小由两个因素控制：
的数字位数每个坐标和点数
。

c $ c> -q 减少每个坐标的位数。最初，地理位置具有非常高的精度，例如

  ...，[ -  90.07231180399987,29.501753271000098]，[ -  90.06635619599979,29.499494248000133]，... 
  

量化 -q 1e4 strong>其中 1e4 = 10000创建一个10,000×10,000网格，整数值介于0和9999之间，例如 [ - 6700,1030] 。根据坐标的字符从〜40减少到 12 ，减少了〜75％，最大值为 4 个数字。其次，quatization使得在输入shapefile中不同的地理点现在共享相同的坐标，例如 [24,62]，[24,62]，[24,62] ... 。这些重复项被合并。最终结果是由网格上的点定义的形状。 如果您只使用量化，则您的形状将采用从网格点到网格点的垂直+水平线。

简化通过删除点删除信息。 TopoJSON使用的Visvalingam方法消除了最不引人注意的点，这一原则在 Line Simplification article 。要有许多精细的三角形精细删除，首先使用更高的量化，然后简化：

  #world 
 topojson -q 1e6 -s 7e-5 -o world-110m.json  -  NaturalEarth-110m.shp 
  

这是通过删除一些角点在基于topojson的形状中创建对角线的简化。

-s

有关Google群组的问题，M. Bostock 提议的一些聪明的提示。

4. 对于美国，请使用 -s 7e-7 。 e表示指数，以球面坐标的球面度测量。 7e-8 小十倍，这是更多的细节！




最近，我开始预投射TopoJSON。这允许您在屏幕像素（ - cartesian --width 960 -s 1 对于一个正方形像素，例如）中指定直观的简化阈值，

演示

href =http://bl.ocks.org/mbostock/6320825 =nofollow>现场使用和其他类似的：

 ＃projection（从输入shapefile大时给出节点额外的内存）
 us-albers.json：County_2010Census_DP1.shp 
 node --max_old_space_size = 8192 node_modules / .bin / topojson \ 
 -q 1e5 \ 
 -s 1 \ 
 --projection'd3.geo.albersUsa（）'\ 
 --id-property = GEOID10 \ 
 -p name = NAMELSAD10，pop = + DP0010001 \ 
 -o $ @ \ 
 --counties = County_2010Census_DP1.shp 
 
＃预计（本示例不使用，但包括供参考）
 topojson --max_old_space_size = 8192 \ 
 -q 1e6 \ 
 -s 7e-5 \ 
  - o world-110m.json \ 
  -  NaturalEarth-110m.shp 
 #USA 
 topojson \ 
 -q 1e5 \ 
 -s 7e-7 \ 
 --id-property = GEOID10 \ 
 -p name = NAMELSAD10，pop = + DP0010001 \ 
 -o $ @ \ 
  -  counties = County_2010Census_DP1 .shp 
  

如果未投影，则映射区域的尺寸缩小10倍内华达州）， 7e-7 应移至较小的值，例如 7e-8 。

笛卡尔

http://bost.ocks.org/mike/simplify/

Mike Bostock shared a range of world wide topojson files.

As I wanted more data and higher quality, I now generate my own high quality topojson files from Natural Earth. To make it simple, my makefile / command is such:

admin_0: crop
    ../node_modules/topojson/bin/topojson \
        --id-property name \
        -p name=name \
        -q 1e4 \
        --filter=small \
        -o admin_0.topo.json \
        -- admin_0=./natural_earth_vector/10m_cultural/ne_10m_admin_0_countries.shp

But my 3MB .topojson is crispy, nasty, graphically messy. Take a look at the coastline, you will see the most annoying thing : lines looking like "stairs" : horizontal, vertical, horizontal, vertical,...

On his side, M. Bostock's 90kb .topojson does surprisingly fine in term of elegance. Not perfect, but nice, and he does have diagonals (!) and various angles used by his lines.

I tried reducing the quantization to -q 1e3, but it keeps crispy, and it's even more ugly: the stair's steps are even bigger.

From the command line API, I noticed and read as much as I could on :

• -q, --quantization, --no-quantization maximum number of differentiable points along either dimension
• -s, --simplify precision threshold for Visvalingam simplification
• --simplify-proportion proportion of points to retain for Visvalingam simplification
• --width scale and translate to fit a viewport of the specified width
• --height scale and translate to fit a viewport of the specified height

which may all help me. I made some test to mainly learn that balancing simplification is tricky. I would like to ask for experienced users how then handle and balance their topojson simplification.

What approach do you take yourself ? and so... What topojson parameters should I use to make my topojson nicer ? (no crispy stairs-steps edge, correct loyalty the the shape)

解决方案

-q VS -s

More details on Topojson: quantization VS simplification .

The total size of your geometry is controlled by two factors: the number of digits (the precision) of each coordinate and the number of points.

The quantization -q reduce the number of digits for each coordinate. Initially, geopoints have very high precision such

…,[-90.07231180399987,29.501753271000098],[-90.06635619599979,29.499494248000133],…

Quantization -q 1e4 where 1e4=10000 creates a 10,000×10,000 grid with integer values between 0 and 9999 such [-6700,1030]. Characters by coordinate is reduced from ~40 to 12, a ~75% reduction, with a maximum of 4 digits by value. Secondly, quatization makes geopoints which where distinct in the input shapefile to now share the same coordinates, such [24,62],[24,62],[24,62]…. These duplicates are merged. The end result are shapes defined by points on the grids. If you ONLY use the quantization your shapes will be made of vertical + horizontal lines from grid-point to grid-point.

In contrast, simplification removes information by removing points. The Visvalingam method used by the TopoJSON removes the least-noticeable points, the principle is wittily illustrated in Line Simplification article. To have many fine triangles to delicately removes, first use a higher quantization, then a simplification :

 #world
 topojson -q 1e6 -s 7e-5 -o world-110m.json -- NaturalEarth-110m.shp

It's the simplification which by removing some corner points create diagonals lines in topojson-based shapes.

-s

Asked on google group, M. Bostock proposed some smart tips.

4. For the USA, use -s 7e-7. "e" stands for exponent, measured in steradians for spherical coordinates. 7e-8 is ten times smaller, which is a lot more detail! 7e-5 is one hundred times less details.

Lately, I’ve started pre-projecting the TopoJSON. This allows you to specify an intuitive simplification threshold in screen pixels (--cartesian --width 960 -s 1 for one square pixel, e.g.) and makes rendering very fast on the client since the TopoJSON is already projected.

Demos

Two live use and an other are such :

# projected (giving node extra memory since input shapefile is big)
us-albers.json: County_2010Census_DP1.shp
    node --max_old_space_size=8192 node_modules/.bin/topojson \
        -q 1e5 \
        -s 1 \
        --projection 'd3.geo.albersUsa()' \
        --id-property=GEOID10 \
        -p name=NAMELSAD10,pop=+DP0010001 \
        -o $@ \
        -- counties=County_2010Census_DP1.shp

# non-projected (not used by this example, but included for reference)
  topojson --max_old_space_size=8192 \
     -q 1e6 \
     -s 7e-5 \
     -o world-110m.json \
     -- NaturalEarth-110m.shp
#USA
  topojson \
    -q 1e5 \
    -s 7e-7 \
    --id-property=GEOID10 \
    -p name=NAMELSAD10,pop=+DP0010001 \
    -o $@ \
    -- counties=County_2010Census_DP1.shp

With unprojected, as your mapped area's dimensions get 10 times smaller (i.e. Nevada), the 7e-7 should move to smaller values such 7e-8.

Cartesian

http://bost.ocks.org/mike/simplify/

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