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toolvariance_editor [2017/09/13 12:24]
titterton removed
toolvariance_editor [2018/10/17 15:49] (current)
sechrest
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 ==== Trunk "​C"​ ==== ==== Trunk "​C"​ ====
-Length variance is set to 3.0 and the distribution algorithm is "​Gaussian (bell curve)." ​ Each of its 23 branches has a length between 7.0 and 13.0, chosen based on a Gaussian distribution. ​ Notice that the lengths are more closely clustered around 10.0 than in the the purely random example.+Length variance is set to 3.0 and the distribution algorithm is "​Gaussian (bell curve)." ​ Each of its 23 branches has a length between 7.0 and 13.0, chosen based on a Gaussian distribution. ​ Notice that the lengths are more closely clustered around 10.0 than in the purely random example.
  
 ==== Trunk "​D"​ ==== ==== Trunk "​D"​ ====
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 This is the amount by which the property can vary. This is the amount by which the property can vary.
 ==== Distribution ==== ==== Distribution ====
-This option controls how the amount of variance is computed per node.  "​Uniform (random)"​ chooses a random amount of variance per node.  "​Gaussian (bell curve)"​ uses a bell shaped distribution where most of the variances are small amounts.+This option controls how the amount of variance is computed per node.  "​Uniform (random)"​ chooses a random amount of variance per node.  "​Gaussian (bell curve)"​ uses a bell-shaped distribution where most of the variances are small amounts.
 ==== Cohesion ==== ==== Cohesion ====
 The elements in this group control the degree to which neighboring nodes will have similar variance values. ​ Use this option to create clusters of similar objects in your model. The elements in this group control the degree to which neighboring nodes will have similar variance values. ​ Use this option to create clusters of similar objects in your model.
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   * You need variance on at least some of the properties or "​Randomize"​ won't do anything!   * You need variance on at least some of the properties or "​Randomize"​ won't do anything!
   * Use "​Gaussian (bell curve)"​ when you want most of the values to be similar but with a few outliers.   * Use "​Gaussian (bell curve)"​ when you want most of the values to be similar but with a few outliers.
-  * Use cohesion to make very noticeable properties appear coordinated. ​ A good example is "​Season:​Descendant offset"​ on branches. ​ Adding cohesive variance to this property makes season changes in large sections of the tree appear variedbut related to where they are on the model.+  * Use cohesion to make very noticeable properties appear coordinated. ​ A good example is "​Season:​Descendant offset"​ on branches. ​ Adding cohesive variance to this property makes season changes in large sections of the tree appear varied but related to where they are on the model.