---- As before, the inputs ----
The polygons that I will be using are shown to the right.
Each part is labelled at the labelpoint rather than the centroid, hence each part gets labelled.
---- An Alternate Geometry Reconstructor ---- |
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---- Arrays to Poly* Features ---- Never use <null> in a table. To many posts on the forum on how to trap them, find them, replace them. Always put in a value to represent all conditions. Too many people use None <null> as the catchall category. In reality all observations need to be classified exactly, there really is no such thing as <null>. You either made and observation or you didn't. If you didn't, your classification scheme should provide a key indicating that. If an observation was made but the phenomenon/parameter/whatever was actually not there, there should be a key for that. Similar, for 'I forgot', 'Wasn't my job' or whatever other excuses exist.
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Making none/null/real nothingnessYou can add to, or remove from, the list below. These are some that I use. I will draw your attention to the NumPy incarnations for integers. Equivalent values exist for floats. Any value that ensures that you will take a second look if a calculation looks weird is good. However if your table contains <nulls> even after my lecture above, this will help mitigate your... stupidity is such a harsh word... but you get my drift
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My favorite way of getting just the attributesSuch nice functions, FeatureClassToNumPyArray, TableToNumPyArray, and back the other way. I am sure many of you have explored where it all comes from only to find it all buried in a *.pyd file
No bother, since you can pull out data for the attributes nicely accounting for <null> records.
The explorers amongst us, may have discovered a few searchcursor shortcuts
Sadly, the integer fields with <nulls> bring the whole shortcut down. The searchcursor actually has enough information in it to create a structured/recarray. If you have a clean table with no nulls, the actual calls to _dtype and fields show that you can clearly link cursors and NumPy arrays. Too bad, the whole integer fix isn't incorporated, but _as_narray and FeatureClassToNumPyArray and TableToNumPyArray yield the same results on a 'clean' dataset.
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Geometry ... ArcPy and NumPy... # 2
/blogs/dan_patterson/2019/04/10/geometry-deconstructing-poly-features-3
/blogs/dan_patterson/2019/04/17/geometry-reconstructing-poly-features-4
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