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This is an ugly problem. does the rectangle have to be axis aligned? (ie. parallel to the x/y axes) are the polygons convex or concave the 60% factor ... how fast is that requirement? do you mean 60% or more? 60% or less? what is the actual rectangle area you are interested in? is there a minimum or maximum size? If you can articulate your requirements, perhaps alternate solutions can be suggested. I suggest you do some reading on the topic: Project with visuals Largest inscribed rectangles in convex polygons  ScienceDirect [1905.13246] Largest Inscribed Rectangles in Geometric Convex Sets (arxiv.org) (PDF) Computing the Largest Inscribed Isothetic Rectangle (researchgate.net)
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Did you use the tool or using shortcuts? Enable Attachments (Data Management)—ArcGIS Pro  Documentation
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yesterday

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There is an @ArcGis_Ideas idea along those lines Add old pixel inspector to arcgis pro  GeoNet, The Esri Community
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yesterday

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Laura.... I think any shmo can... however, I have never had any problem with forward slashes. My default is "raw" encoding (using the little 'r' in scripts). In geoprocessing tools, I don't type... I navigate and select files and let arc* wizardry do its work. I would investigate further and see whether other paths fail with forward slashes. I am wondering if it just may be that particular folder, or something in the mp module (which I rarely use). Give it shot and if it is reproduceable, then file a report ... however, the first thing that will be suggested is to upgrade to the latest version (2.6.3) Good luck!
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Wednesday

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What do you get when you run these from sys? This is my default path structure minus personal ones. #  NOTE : replace C:\\arc_pro with your installation path
sys.executable
'C:\\arc_pro\\bin\\Python\\envs\\arcgispropy3\\python.exe'
sys.path
['C:\\arc_pro\\Resources\\ArcPy',
...snip...,
'C:\\arc_pro\\bin\\Python\\envs\\arcgispropy3\\DLLs',
'C:\\arc_pro\\bin\\Python\\envs\\arcgispropy3\\lib',
'C:\\arc_pro\\bin\\Python\\envs\\arcgispropy3',
'',
'C:\\arc_pro\\bin\\Python\\envs\\arcgispropy3\\lib\\sitepackages',
'C:\\arc_pro\\bin',
'C:\\arc_pro\\Resources\\ArcToolbox\\Scripts',
'C:\\arc_pro\\bin\\Python\\envs\\arcgispropy3\\lib\\sitepackages\\future0.18.2py3.7.egg',
'C:\\arc_pro\\bin\\Python\\envs\\arcgispropy3\\lib\\sitepackages\\pytz2020.1py3.7.egg',
'C:\\arc_pro\\bin\\Python\\envs\\arcgispropy3\\lib\\sitepackages\\pywin32_ctypes0.2.0py3.7.egg',
'C:\\arc_pro\\bin\\Python\\envs\\arcgispropy3\\lib\\sitepackages\\pywin32security',
'C:\\arc_pro\\bin\\Python\\envs\\arcgispropy3\\lib\\sitepackages\\sympy1.5.1py3.7.egg',
'C:\\arc_pro\\bin\\Python\\envs\\arcgispropy3\\lib\\sitepackages\\IPython\\extensions',
]
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Wednesday

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GAIT (Topographic Production)—ArcGIS Pro  Documentation required Defense mapping, but I have no clue whether the arcmap version is the same
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Wednesday

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Sophie, I will have to flag @MelitaKennedy to see if she has any comment. That kind of shift is not associated with major datum differences for sure.
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BLOG

Densification Densification of polygon boundaries or polyline segments, is a common task. In a previous incarnation, I wrote about densifying geometry based on a "factor", that is, double, triple... the number of points along a segment. Planar densification can be carried out in Editing Tools, with several options. It is not available at the Basic license level for some reason. Densify (Editing)—ArcGIS Pro  Documentation This missive concentrates on densification based on a planar distance step along the line/perimeter. It is the most common usage. It will included a couple of my toolsets (listed below). The code is illustrative of the power of numpy in geoprocessing. def _pnts_on_line_(a, spacing=1, is_percent=False): # densify by distance
"""Add points, at a fixed spacing, to an array representing a line.
Parameters

a : array
A sequence of `points`, x,y pairs, representing the bounds of a polygon
or polyline object.
spacing : number
Spacing between the points to be added to the line.
is_percent : boolean
Express the densification as a percent of the total length.
"""
a = _get_base_(a)
N = len(a)  1 # segments
dxdy = a[1:, :]  a[:1, :] # coordinate differences
leng = np.sqrt(np.einsum('ij,ij>i', dxdy, dxdy)) # segment lengths
if is_percent: # as percentage
spacing = abs(spacing)
spacing = min(spacing / 100, 1.)
steps = (sum(leng) * spacing) / leng # step distance
else:
steps = leng / spacing # step distance
deltas = dxdy / (steps.reshape(1, 1)) # coordinate steps
pnts = np.empty((N,), dtype='O') # construct an `O` array
for i in range(N): # cycle through the segments and make
num = np.arange(steps[i]) # the new points
pnts[i] = np.array((num, num)).T * deltas[i] + a[i]
a0 = a[1].reshape(1, 1) # add the final point and concatenate
return np.concatenate((*pnts, a0), axis=0) I think my favorite 2 lines are ... dxdy = a[1:, :]  a[:1, :] # coordinate differences
leng = np.sqrt(np.einsum('ij,ij>i', dxdy, dxdy)) # segment lengths Einstein was a smart dude. His notation syntax is implemented in many languages and causes brain squint until you get used to it (fodder for another blog). In short, dxdy represents the sequential differences in an array's coordinates (read polygon/polyline coordinates). None of this reading the geometry and subtracting each x and y coordinate in turn. One line and you are done. Now a[1:, :] means from the second coordinate pair onward and a[:1, :] means from the first coordinate upto but not including the last (indexing is zerobased). Head swimming? You have been using Pandas or shapely too long. Here is what a simple polygon looks like represented like an array (even an arcpy.Array ) a #  an array of x, y coordinates... first and last are the same
array([[ 0.00, 0.00],
[ 2.00, 8.00],
[ 8.00, 10.00],
[ 10.00, 10.00],
[ 10.00, 8.00],
[ 9.00, 1.00],
[ 0.00, 0.00]])
dxdy #  sequential, delta x and delta y between the pairs
array([[ 2.00, 8.00],
[ 6.00, 2.00],
[ 2.00, 0.00],
[ 0.00, 2.00],
[ 1.00, 7.00],
[ 9.00, 1.00]])
leng #  the interpoint pair distance
array([ 8.25, 6.32, 2.00, 2.00, 7.07, 9.06]) Now that the magic is done, the rest is just stuff to determine whether you want to densify based on an absolute distance or as a percentage of the total distance. The for loop section can be simplified, however, I kept it as such since it shows how each segment gets densified and the results collected and then assembled into the final result, So what does it look like? The simple polygon shown above and the densified version are as follows. Plots done in Spyder using Matplotlib. Finally, I will add this capability to my Polyline/Polygon tools and Free Tools tools shortly. Free_Tools in Tools_for_ArcGIS_Pro (github.com) PolygonLine Tools in Tools_for_ArcGIS_Pro (github.com) If you are interested in geometry, computational geometry and numpy and its interface with arcpy and arcgis pro, then my Numpy Geometry link may be of interest. It is the foundation for all the toolset in my site. numpy_geometry: A numpy geometry class and functions that work with arcpy and ESRI featureclasses That's all for now. Give me a buzz if you need something you would like added... especially if it requires and Advance license 😉 .  Previous work Densification.... sometimes being dense is a good ...  GeoNet, The Esri Community
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Wednesday

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NIM000967: Geoprocessing tools do not recognize a layer name wi.. (esri.com) but you weren't using geoprocessing tools
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Wednesday

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what is the input? (tin, raster etc) resolution of the data? accuracy of the data? Are you seeing differences in the calculations? What does PostGIS use? Too many factors to consider with a comparable comparison between the two. Surface Volume (3D Analyst)—ArcGIS Pro  Documentation
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