Geometry ... Attributes actually... the other bits # 5

DanPatterson_Retired

Part 5 ... The attributes attached to the geometry

•  target="_self">Part 5 ... The attributes attached to the geometry
• Making none/null/real nothingness
• My favorite way of getting just the attributes
• Coming soon
• Other links

---- As before, the inputs ----

The polygons that I will be using are shown to the right.

1. A square, 5 points, first and last duplicates
2. A lake on an island in a lake...
3. A multipart with a two different shaped donut holes
4. The letter 'C'
5. The letter 'V'

Each part is labelled at the labelpoint rather than the centroid, hence each part gets labelled.

 

 

 

---- An Alternate Geometry Reconstructor ----
---- 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.   For observations recorded as floating point numbers, that truly yielded 'nothing/None/nadda/zilch', I use 'nan' (np.nan) since it is a recognized number. For text/string observations, I use None since None the object translates to 'None' the text easily in most tables. For time, there is now 'not a time' (NaT), but I don't work with time, preferring to use the string incarnations of those observations For integers... sadly there is no 'Nint'.  You have to provide an actual integer value to represent no value observed, although you desperately tried.   You can use the old school -999, or even 2**8, 2**16 etcetera. For all of the above, anything that is truly doesn't represent an observation where no value was observed, you will have to provide alternatives
Making none/null/real nothingness You 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 <SPAN class="keyword token">def</SPAN> <SPAN class="token function">_make_nulls_</SPAN><SPAN class="punctuation token">(</SPAN>in_fc<SPAN class="punctuation token">,</SPAN> int_null<SPAN class="operator token">=</SPAN><SPAN class="operator token">-</SPAN><SPAN class="number token">999</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN> <SPAN class="string token">""</SPAN>"Return null values <SPAN class="keyword token">for</SPAN> a list of fields objects<SPAN class="punctuation token">,</SPAN> excluding objectid <SPAN class="operator token">and</SPAN> geometry related fields<SPAN class="punctuation token">.</SPAN> Throw <SPAN class="keyword token">in</SPAN> whatever <SPAN class="keyword token">else</SPAN> you want<SPAN class="punctuation token">.</SPAN> Parameters <SPAN class="operator token">-</SPAN><SPAN class="operator token">-</SPAN><SPAN class="operator token">-</SPAN><SPAN class="operator token">-</SPAN><SPAN class="operator token">-</SPAN><SPAN class="operator token">-</SPAN><SPAN class="operator token">-</SPAN><SPAN class="operator token">-</SPAN><SPAN class="operator token">-</SPAN><SPAN class="operator token">-</SPAN> in_flds <SPAN class="punctuation token">:</SPAN> list of field objects arcpy field objects<SPAN class="punctuation token">,</SPAN> use arcpy<SPAN class="punctuation token">.</SPAN>ListFields to get a list of featureclass fields<SPAN class="punctuation token">.</SPAN> int_null <SPAN class="punctuation token">:</SPAN> integer A default to use <SPAN class="keyword token">for</SPAN> integer nulls since there <SPAN class="keyword token">is</SPAN> no ``nan`` equivalent Other options include <SPAN class="operator token">>></SPAN><SPAN class="operator token">></SPAN> np<SPAN class="punctuation token">.</SPAN>iinfo<SPAN class="punctuation token">(</SPAN>np<SPAN class="punctuation token">.</SPAN>int32<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">.</SPAN>min <SPAN class="comment token"># -2147483648</SPAN> <SPAN class="operator token">>></SPAN><SPAN class="operator token">></SPAN> np<SPAN class="punctuation token">.</SPAN>iinfo<SPAN class="punctuation token">(</SPAN>np<SPAN class="punctuation token">.</SPAN>int16<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">.</SPAN>min <SPAN class="comment token"># -32768</SPAN> <SPAN class="operator token">>></SPAN><SPAN class="operator token">></SPAN> np<SPAN class="punctuation token">.</SPAN>iinfo<SPAN class="punctuation token">(</SPAN>np<SPAN class="punctuation token">.</SPAN>int8<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">.</SPAN>min <SPAN class="comment token"># -128</SPAN> <SPAN class="punctuation token">[</SPAN>i <SPAN class="keyword token">for</SPAN> i <SPAN class="keyword token">in</SPAN> cur<SPAN class="punctuation token">.</SPAN>__iter__<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">]</SPAN> <SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">[</SPAN>j <SPAN class="keyword token">if</SPAN> j <SPAN class="keyword token">is</SPAN> <SPAN class="operator token">not</SPAN> None <SPAN class="keyword token">else</SPAN> <SPAN class="operator token">-</SPAN><SPAN class="number token">999</SPAN> <SPAN class="keyword token">for</SPAN> j <SPAN class="keyword token">in</SPAN> i <SPAN class="punctuation token">]</SPAN> <SPAN class="keyword token">for</SPAN> i <SPAN class="keyword token">in</SPAN> cur<SPAN class="punctuation token">.</SPAN>__iter__<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">)</SPAN> <SPAN class="punctuation token">]</SPAN> <SPAN class="string token">""</SPAN>" nulls <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">{</SPAN><SPAN class="string token">'Double'</SPAN><SPAN class="punctuation token">:</SPAN> np<SPAN class="punctuation token">.</SPAN>nan<SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'Single'</SPAN><SPAN class="punctuation token">:</SPAN> np<SPAN class="punctuation token">.</SPAN>nan<SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'Float'</SPAN><SPAN class="punctuation token">:</SPAN> np<SPAN class="punctuation token">.</SPAN>nan<SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'Short'</SPAN><SPAN class="punctuation token">:</SPAN> int_null<SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'SmallInteger'</SPAN><SPAN class="punctuation token">:</SPAN> int_null<SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'Long'</SPAN><SPAN class="punctuation token">:</SPAN> int_null<SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'Integer'</SPAN><SPAN class="punctuation token">:</SPAN> int_null<SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'String'</SPAN><SPAN class="punctuation token">:</SPAN>str<SPAN class="punctuation token">(</SPAN>None<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'Text'</SPAN><SPAN class="punctuation token">:</SPAN>str<SPAN class="punctuation token">(</SPAN>None<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'Date'</SPAN><SPAN class="punctuation token">:</SPAN> np<SPAN class="punctuation token">.</SPAN>datetime64<SPAN class="punctuation token">(</SPAN><SPAN class="string token">'NaT'</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">}</SPAN> <SPAN class="comment token">#</SPAN> desc <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>da<SPAN class="punctuation token">.</SPAN>Describe<SPAN class="punctuation token">(</SPAN>in_fc<SPAN class="punctuation token">)</SPAN> <SPAN class="keyword token">if</SPAN> desc<SPAN class="punctuation token">[</SPAN><SPAN class="string token">'dataType'</SPAN><SPAN class="punctuation token">]</SPAN> <SPAN class="operator token">!=</SPAN> <SPAN class="string token">'FeatureClass'</SPAN><SPAN class="punctuation token">:</SPAN> <SPAN class="keyword token">print</SPAN><SPAN class="punctuation token">(</SPAN><SPAN class="string token">"Only Featureclasses are supported"</SPAN><SPAN class="punctuation token">)</SPAN> <SPAN class="keyword token">return</SPAN> None<SPAN class="punctuation token">,</SPAN> None in_flds <SPAN class="operator token">=</SPAN> desc<SPAN class="punctuation token">[</SPAN><SPAN class="string token">'fields'</SPAN><SPAN class="punctuation token">]</SPAN> shp <SPAN class="operator token">=</SPAN> desc<SPAN class="punctuation token">[</SPAN><SPAN class="string token">'shapeFieldName'</SPAN><SPAN class="punctuation token">]</SPAN> good <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">[</SPAN>f <SPAN class="keyword token">for</SPAN> f <SPAN class="keyword token">in</SPAN> in_flds <SPAN class="keyword token">if</SPAN> f<SPAN class="punctuation token">.</SPAN>editable <SPAN class="operator token">and</SPAN> f<SPAN class="punctuation token">.</SPAN>name <SPAN class="operator token">!=</SPAN> shp<SPAN class="punctuation token">]</SPAN> fld_dict <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">{</SPAN>f<SPAN class="punctuation token">.</SPAN>name<SPAN class="punctuation token">:</SPAN> f<SPAN class="punctuation token">.</SPAN>type <SPAN class="keyword token">for</SPAN> f <SPAN class="keyword token">in</SPAN> good<SPAN class="punctuation token">}</SPAN> fld_names <SPAN class="operator token">=</SPAN> list<SPAN class="punctuation token">(</SPAN>fld_dict<SPAN class="punctuation token">.</SPAN>keys<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">)</SPAN> null_dict <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">{</SPAN>f<SPAN class="punctuation token">:</SPAN> nulls<SPAN class="punctuation token">[</SPAN>fld_dict<SPAN class="punctuation token">[</SPAN>f<SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">]</SPAN> <SPAN class="keyword token">for</SPAN> f <SPAN class="keyword token">in</SPAN> fld_names<SPAN class="punctuation token">}</SPAN> <SPAN class="comment token"># ---- insert the OBJECTID field</SPAN> <SPAN class="keyword token">return</SPAN> null_dict<SPAN class="punctuation token">,</SPAN> fld_names‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍<SPAN class="line-numbers-rows"><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN>
My favorite way of getting just the attributes Such 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 <SPAN class="keyword token">import</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>da <SPAN class="keyword token">as</SPAN> apd apd<SPAN class="punctuation token">.</SPAN>__file__ <SPAN class="comment token"># ---- 'C:\\...install path...\\Resources\\ArcPy\\arcpy\\da.py'</SPAN> <SPAN class="comment token"># ---- which is actually just imports arcgisscripting</SPAN> <SPAN class="comment token"># ---- so import it directly</SPAN> <SPAN class="keyword token">import</SPAN> arcgisscripting <SPAN class="keyword token">as</SPAN> ags ags<SPAN class="punctuation token">.</SPAN>__file__ <SPAN class="comment token"># ---- 'C:\\...install path...\\bin\\Python\\envs\\arcgispro-py3\\lib\\</SPAN> <SPAN class="comment token"># site-packages\\arcgisscripting.pyd'‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍</SPAN><SPAN class="line-numbers-rows"><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN> No bother, since you can pull out data for the attributes nicely accounting for <null> records. <SPAN class="keyword token">def</SPAN> <SPAN class="token function">fc_data</SPAN><SPAN class="punctuation token">(</SPAN>in_fc<SPAN class="punctuation token">,</SPAN> verbose<SPAN class="operator token">=</SPAN><SPAN class="token boolean">False</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN> <SPAN class="string token">"""Pull all editable attributes from a featureclass tables. During the process, <null> values are changed to an appropriate type. Parameters ---------- in_fc : text Path to the input featureclass verbose : boolean Requires ``'prn_rec' in locals().keys()`` in order to set to ``True``. ``prn_rec`` is imported from arraytools.frmts """</SPAN> flds <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">[</SPAN><SPAN class="string token">'OID@'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'SHAPE@X'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'SHAPE@Y'</SPAN><SPAN class="punctuation token">]</SPAN> null_dict<SPAN class="punctuation token">,</SPAN> fld_names <SPAN class="operator token">=</SPAN> _make_nulls_<SPAN class="punctuation token">(</SPAN>in_fc<SPAN class="punctuation token">,</SPAN> int_null<SPAN class="operator token">=</SPAN><SPAN class="operator token">-</SPAN><SPAN class="number token">999</SPAN><SPAN class="punctuation token">)</SPAN> fld_names <SPAN class="operator token">=</SPAN> flds <SPAN class="operator token">+</SPAN> fld_names new_names <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">[</SPAN><SPAN class="string token">'OID_orig'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'X_centroid'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'Y_centroid'</SPAN><SPAN class="punctuation token">]</SPAN> a <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>da<SPAN class="punctuation token">.</SPAN>FeatureClassToNumPyArray<SPAN class="punctuation token">(</SPAN>in_fc<SPAN class="punctuation token">,</SPAN> fld_names<SPAN class="punctuation token">,</SPAN> skip_nulls<SPAN class="operator token">=</SPAN><SPAN class="token boolean">False</SPAN><SPAN class="punctuation token">,</SPAN> null_value<SPAN class="operator token">=</SPAN>null_dict<SPAN class="punctuation token">)</SPAN> a<SPAN class="punctuation token">.</SPAN>dtype<SPAN class="punctuation token">.</SPAN>names <SPAN class="operator token">=</SPAN> new_names <SPAN class="operator token">+</SPAN> fld_names<SPAN class="punctuation token">[</SPAN><SPAN class="number token">3</SPAN><SPAN class="punctuation token">:</SPAN><SPAN class="punctuation token">]</SPAN> <SPAN class="keyword token">if</SPAN> verbose<SPAN class="punctuation token">:</SPAN> <SPAN class="keyword token">try</SPAN><SPAN class="punctuation token">:</SPAN> prn_rec<SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">)</SPAN> <SPAN class="comment token"># ** prn_rec imported from arraytools.frmts</SPAN> <SPAN class="keyword token">except</SPAN><SPAN class="punctuation token">:</SPAN> <SPAN class="keyword token">print</SPAN><SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">)</SPAN> <SPAN class="keyword token">return</SPAN> np<SPAN class="punctuation token">.</SPAN>asarray<SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">)</SPAN>‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍ The explorers amongst us, may have discovered a few searchcursor shortcuts fld_names <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">[</SPAN><SPAN class="string token">'OBJECTID'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'Long_1'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'Short_1'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'Float_1'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'Double_1'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'Text_1'</SPAN><SPAN class="punctuation token">]</SPAN> cur <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>da<SPAN class="punctuation token">.</SPAN>SearchCursor<SPAN class="punctuation token">(</SPAN>in_fc<SPAN class="punctuation token">,</SPAN> fld_names<SPAN class="punctuation token">,</SPAN> explode_to_points<SPAN class="operator token">=</SPAN><SPAN class="token boolean">False</SPAN><SPAN class="punctuation token">)</SPAN> z <SPAN class="operator token">=</SPAN> cur<SPAN class="punctuation token">.</SPAN>_as_narray<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">)</SPAN> Traceback <SPAN class="punctuation token">(</SPAN>most recent call last<SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">:</SPAN> File <SPAN class="string token">"<ipython-input-220-b4e724f0982b>"</SPAN><SPAN class="punctuation token">,</SPAN> line <SPAN class="number token">1</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="keyword token">in</SPAN> <SPAN class="operator token"><</SPAN>module<SPAN class="operator token">></SPAN> z <SPAN class="operator token">=</SPAN> cur<SPAN class="punctuation token">.</SPAN>_as_narray<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">)</SPAN>‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍<SPAN class="line-numbers-rows"><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN> 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. dir<SPAN class="punctuation token">(</SPAN>cur<SPAN class="punctuation token">)</SPAN> <SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">.</SPAN><SPAN class="punctuation token">.</SPAN><SPAN class="punctuation token">.</SPAN>snip<SPAN class="punctuation token">.</SPAN><SPAN class="punctuation token">.</SPAN><SPAN class="punctuation token">.</SPAN> <SPAN class="string token">'_as_narray'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'_dtype'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'fields'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'next'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'reset'</SPAN><SPAN class="punctuation token">]</SPAN>‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍<SPAN class="line-numbers-rows"><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN>

 

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Coming soon

• Work with the geometry... and/or … work with the attributes, then put it all back together.

 

Other links

Geometry in NumPy... # 1 

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