Raster function equivalent of Build Raster Attribute Table

[MervynLotter]

Hi there

I would like to include the output of a raster function into the Tabulate Area GP tool, but my raster function output does not have an attribute table. If it were a traditional raster, then I would have run the  Build Raster Attribute Table gp tool to create one.  Is there a raster function equivalent or is there a different approach to follow? I need to work with categorical data.

Thanks.

[DanPatterson]

what kind of raster is it?  normally a float raster has to be converted to an int raster in order to build a raster attribute table.  The only thing that I can find to do zonal crosstab (aka counts) is xarray's zonal.crosstab, it is shipped with Pro 2.9 

xrspatial.zonal.crosstab — xarray_spatial 0.3.0+g9a8909e-dirty documentation (xarray-spatial.org)

it produces a pandas df (pandas is also installed)

[DanPatterson]

Of course you can do it in numpy using RasterToNumPyArray to get a raster out to an array 

import numpy as np
a = np.random.randint(0, 4, size=100).reshape(10, 10)
b = np.random.randint(4, 8, size=100).reshape(10, 10)
ab = np.vstack((a.ravel(), b.ravel())).T
u, cnts = np.unique(ab, return_counts=True, axis=0)

a  # -- zone raster 
array([[0, 1, 0, 2, 2, 1, 2, 0, 1, 0],
       [0, 3, 0, 2, 1, 3, 0, 0, 2, 0],
       [0, 1, 2, 1, 2, 3, 1, 0, 0, 3],
       [2, 1, 1, 2, 0, 0, 1, 3, 3, 2],
       [0, 0, 2, 2, 0, 0, 0, 0, 1, 1],
       [3, 1, 2, 0, 0, 1, 2, 1, 1, 0],
       [0, 0, 3, 0, 3, 1, 2, 3, 0, 0],
       [0, 3, 3, 1, 3, 1, 3, 1, 2, 3],
       [3, 0, 0, 1, 3, 2, 2, 1, 0, 0],
       [1, 1, 0, 2, 3, 3, 1, 1, 1, 1]])

b  # -- values raster
array([[5, 6, 4, 6, 4, 7, 7, 6, 6, 4],
       [6, 4, 6, 4, 7, 6, 4, 7, 4, 6],
       [4, 4, 7, 5, 4, 7, 6, 7, 5, 4],
       [7, 6, 5, 6, 7, 4, 7, 4, 5, 5],
       [4, 7, 4, 6, 7, 5, 5, 4, 4, 7],
       [4, 6, 7, 4, 7, 6, 6, 6, 6, 4],
       [4, 6, 7, 6, 4, 7, 4, 5, 6, 4],
       [4, 6, 6, 6, 4, 4, 4, 4, 6, 5],
       [4, 7, 7, 7, 6, 5, 5, 6, 7, 5],
       [4, 4, 5, 5, 4, 6, 5, 5, 6, 6]])

u  # -- unique combinations
array([[0, 4],
       [0, 5],
       [0, 6],
       [0, 7],
       [1, 4],
       [1, 5],
       [1, 6],
       [1, 7],
       [2, 4],
       [2, 5],
       [2, 6],
       [2, 7],
       [3, 4],
       [3, 5],
       [3, 6],
       [3, 7]])

cnts  # -- counts per combination
array([12,  6,  7,  9,  6,  4, 12,  6,  6,  4,  5,  4,  9,  3,  5,  2],
      dtype=int64)

[curtvprice]

My understanding is that raster functions are on the fly animals that process at a dynamic resolution and window, so seems to me the idea of a raster table wouldn't really apply, as you need a complete dataset to calculate cell counts and a list of unique values.