algorithmic modeling for Rhino
Now Tree8 has a new Component "Smart T8" with the integrated smart first-end algorithm..
There have been First-End List and First-End Item Components in Tree8..
But, with multi-dimensional data tree..
First-End List Component cannot manage branches inside every dimensions..
"Smart T8" Component is developed for managing the multi dimensional data tree with first-end algorithm.
It works with path index location..
"-1" or negative numbers mean the location of item..
"0" means the location of the last path index..
positive numbers mean the location from the back..
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Now look at this example.. a simple 3-dimensional boxes..
In the data tree.. of {0;0;i;j} (k)
"k" is the item index.. Y direction..
"j" is the last path.. X direction..
and "i" is the level.. Z direction..
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When index < 0 (i.e. "-1" or negative)
"Smart T8" performs like the First-End Item Component..
It selects first items in each list and puts them out to "F"..
and in this example.. they are boxes with same Y coordinate(=0)..
In the below image..
F(Red) M(Transparent Green) E(Blue) are classified by Y coordinates..
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When index = 0
"Smart T8" focuses on the last path index..
It selects first list of every {0; 0; i; *} set of lists.. (i.e. every levels)
In this example.. they are boxes with same X coordinate(=0)..
because the last path means X grid..
In the below image..
F(Red) M(Transparent Green) E(Blue) are classified by X coordinates..
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When index = 1
"Smart T8" focuses on the third path index.. (i.e. 1 step from the back)
It selects first list of every {0; 0; *; j} set of lists..
Actually in this case.. they are first levels of every YZ planes..
In this example.. they are boxes with same Z coordinate(=0)..
because "Smart T8" manages levels now (index=1)..
In the below image..
F(Red) M(Transparent Green) E(Blue) are classified by levels..
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When index > 1.. (if it is meaningless index or out of range..)
It performs First-End List Component..
It selects only the first and end list of all lists..
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The "Smart T8" component works with 3 or more dimensional data tree well..
Please control the focusing index and enjoy it.. :)
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