I have a previously reclassified raster file which I run a simple process on and then need to generate a very basic report about the percentages of each class. I'm able to calculate the total count for each raster value/class using summary stats and was wondering if there's a way to skip summary stats and accomplish this with NumPy instead? Here's a sample code: import arcpy import pandas as pd InRaster = "SomeSingleBandRaster" ##This raster was reclassified to have 4 classes## OutGDB = arcpy . env . scratchGDB SlopeReport = OutGDB + '/' + "SlopeReport" StatsTable = OutGDB + '/' + "StatsTable" #Generate Summary Statistics# arcpy . analysis . Statistics ( InRaster , StatsTable , "Value SUM" , "Count" ) #Create array and calculate percentate of each class array = arcpy . da . TableToNumPyArray ( StatsTable , [ 'Count' , 'SUM_Value' ] ) df = pd . DataFrame ( array ) df [ 'perc' ] = df [ "Count" ] / df [ "Count" ] . sum ( ) * 100 print ( df ) This will generate the following output: Count SUM_Value perc 0 5.0 4.0 0.198255 1 274.0 3.0 10.864393 2 1057.0 1.0 41.911182 3 1186.0 2.0 47.026170 This works but I'm always eager to cut out unnecessary steps (while hopefully learning something in the process!) Thanks! InRaster.zip

Lesson 2... *tif file in … info out. First the verbose code that produces the outcome, followed by explanations fn = "c:/Temp/InRaster/InRaster.tif" import arcpy a = arcpy . RasterToNumPyArray ( fn ) uniq , cnts = np . unique ( a , return_counts = True ) per = cnts [ : - 1 ] / np . sum ( cnts [ : - 1 ] ) * 100 . dt = [ ( 'Value' , ' ) , ( 'Count' , ' ) , ( 'Percent' , ' ) ] sze = cnts [ : - 1 ] . size out = np . zeros ( sze , dtype = dt ) out [ 'Value' ] = uniq [ : - 1 ] out [ 'Count' ] = cnts [ : - 1 ] out [ 'Percent' ] = per We don't need to know the coordinates of the lower left, the number of rows and columns or the nodata value, since we can get that when we read in the raster. RasterToNumPyArray—ArcPy Functions | ArcGIS Desktop RasterToNumPyArray (in_raster, {lower_left_corner}, {ncols}, {nrows}, {nodata_to_value}) Basic information on the array shape and data type a . shape # ---- number of rows and columns ( 84 , 55 ) a . dtype # ---- data type of the array, unsigned 16bit integer dtype ( 'uint16' ) # ---- the nodata value is 65535, which is the maximum integer value for uint16 # ---- get this infor from `uniq` uniq array ( [ 1 , 2 , 3 , 4 , 65535 ] , dtype = uint16 ) # ---- counts return a 64bit integer, the 2098 is the nodata cell count cnts array ( [ 1057 , 1186 , 274 , 5 , 2098 ] , dtype = int64 ) # ---- At this stage we want to remove our nodata values from the counts and % calculations Line 5 in the first code block per = cnts [ : - 1 ] / np . sum ( cnts [ : - 1 ] ) * 100 . basically means " use all the cnts up to but no including the last value, divide it by their sum and multiply by 100%. cnts[:-1] ... is a slice, the : means everything up to but excluding... Read up on array slicing... This is only a 2D array, but it can be head melting for arrays beyond 4D. You will notice that I did slicing in lines 10 and 11 to exclude the no data values, but I didn't need to do if for the 'per' line because I sliced already. Of course, the above can be put into a 'def' (aka function) if you need to do it all the time, and the code can be simplified greatly... Just to show you how working with basic arrays is easy. When you want to work with things like area... then it becomes important to know the cell size of each array element. That is where 'human-ware' comes into play (ie, take notes) and sometimes exporting rasters to old-school ASCII rasters is useful since the cell size information goes out with it. RasterToNumPyArray, doesn't... you have to remember.. So you want to save stuff? I use numpy as well. out_fn = "C:/temp/InRaster/in_raster.npy" np . save ( out_fn , a ) Hmmm maybe I should look at it again, just in case a_gain = np . load ( "C:/temp/InRaster/in_raster.npy" ) np . all ( a == a_gain ) True All is good!

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Use NumPy to calculate summary statistics?

ZacharyHart

I have a previously reclassified raster file which I run a simple process on and then need to generate a very basic report about the percentages of each class.

I'm able to calculate the total count for each raster value/class using summary stats and was wondering if there's a way to skip summary stats and accomplish this with NumPy instead?

Here's a sample code:

<SPAN class="keyword token">import</SPAN> arcpy
<SPAN class="keyword token">import</SPAN> pandas <SPAN class="keyword token">as</SPAN> pd

InRaster <SPAN class="operator token">=</SPAN> <SPAN class="string token">"SomeSingleBandRaster"</SPAN> <SPAN class="comment token">##This raster was reclassified to have 4 classes##</SPAN>
OutGDB <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>env<SPAN class="punctuation token">.</SPAN>scratchGDB
SlopeReport <SPAN class="operator token">=</SPAN> OutGDB <SPAN class="operator token">+</SPAN> <SPAN class="string token">'/'</SPAN> <SPAN class="operator token">+</SPAN> <SPAN class="string token">"SlopeReport"</SPAN>
StatsTable <SPAN class="operator token">=</SPAN> OutGDB <SPAN class="operator token">+</SPAN> <SPAN class="string token">'/'</SPAN> <SPAN class="operator token">+</SPAN> <SPAN class="string token">"StatsTable"</SPAN>


<SPAN class="comment token">#Generate Summary Statistics#</SPAN>
arcpy<SPAN class="punctuation token">.</SPAN>analysis<SPAN class="punctuation token">.</SPAN>Statistics<SPAN class="punctuation token">(</SPAN>InRaster<SPAN class="punctuation token">,</SPAN> StatsTable<SPAN class="punctuation token">,</SPAN> <SPAN class="string token">"Value SUM"</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">"Count"</SPAN><SPAN class="punctuation token">)</SPAN>

<SPAN class="comment token">#Create array and calculate percentate of each class</SPAN>
array <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>da<SPAN class="punctuation token">.</SPAN>TableToNumPyArray<SPAN class="punctuation token">(</SPAN>StatsTable<SPAN class="punctuation token">,</SPAN> <SPAN class="punctuation token">[</SPAN><SPAN class="string token">'Count'</SPAN><SPAN class="punctuation token">,</SPAN><SPAN class="string token">'SUM_Value'</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">)</SPAN>
df <SPAN class="operator token">=</SPAN> pd<SPAN class="punctuation token">.</SPAN>DataFrame<SPAN class="punctuation token">(</SPAN>array<SPAN class="punctuation token">)</SPAN>
df<SPAN class="punctuation token">[</SPAN><SPAN class="string token">'perc'</SPAN><SPAN class="punctuation token">]</SPAN> <SPAN class="operator token">=</SPAN> df<SPAN class="punctuation token">[</SPAN><SPAN class="string token">"Count"</SPAN><SPAN class="punctuation token">]</SPAN> <SPAN class="operator token">/</SPAN> df<SPAN class="punctuation token">[</SPAN><SPAN class="string token">"Count"</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">.</SPAN>sum<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">)</SPAN> <SPAN class="operator token">*</SPAN> <SPAN class="number token">100</SPAN>
<SPAN class="keyword token">print</SPAN><SPAN class="punctuation token">(</SPAN>df<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>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN>

This will generate the following output:

    Count  SUM_Value       perc
<SPAN class="number token">0</SPAN>     <SPAN class="number token">5.0</SPAN>        <SPAN class="number token">4.0</SPAN>   <SPAN class="number token">0.198255</SPAN>
<SPAN class="number token">1</SPAN>   <SPAN class="number token">274.0</SPAN>        <SPAN class="number token">3.0</SPAN>  <SPAN class="number token">10.864393</SPAN>
<SPAN class="number token">2</SPAN>  <SPAN class="number token">1057.0</SPAN>        <SPAN class="number token">1.0</SPAN>  <SPAN class="number token">41.911182</SPAN>
<SPAN class="number token">3</SPAN>  <SPAN class="number token">1186.0</SPAN>        <SPAN class="number token">2.0</SPAN>  <SPAN class="number token">47.026170</SPAN>‍‍‍‍‍<SPAN class="line-numbers-rows"><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN>

This works but I'm always eager to cut out unnecessary steps (while hopefully learning something in the process!)

Thanks!

InRaster.zip

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DanPatterson_Retired

Lesson 2... *tif file in … info out.

First the verbose code that produces the outcome, followed by explanations

fn <SPAN class="operator token">=</SPAN> <SPAN class="string token">"c:/Temp/InRaster/InRaster.tif"</SPAN>
<SPAN class="keyword token">import</SPAN> arcpy
a <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>RasterToNumPyArray<SPAN class="punctuation token">(</SPAN>fn<SPAN class="punctuation token">)</SPAN>
uniq<SPAN class="punctuation token">,</SPAN> cnts <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>unique<SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">,</SPAN> return_counts<SPAN class="operator token">=</SPAN><SPAN class="token boolean">True</SPAN><SPAN class="punctuation token">)</SPAN>
per <SPAN class="operator token">=</SPAN> cnts<SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">:</SPAN><SPAN class="operator token">-</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="operator token">/</SPAN>np<SPAN class="punctuation token">.</SPAN>sum<SPAN class="punctuation token">(</SPAN>cnts<SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">:</SPAN><SPAN class="operator token">-</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">)</SPAN> <SPAN class="operator token">*</SPAN><SPAN class="number token">100</SPAN><SPAN class="punctuation token">.</SPAN>

dt <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">(</SPAN><SPAN class="string token">'Value'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'<i4'</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="punctuation token">(</SPAN><SPAN class="string token">'Count'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'<i4'</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="punctuation token">(</SPAN><SPAN class="string token">'Percent'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'<f8'</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">]</SPAN>
sze <SPAN class="operator token">=</SPAN> cnts<SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">:</SPAN><SPAN class="operator token">-</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">.</SPAN>size
out <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>zeros<SPAN class="punctuation token">(</SPAN>sze<SPAN class="punctuation token">,</SPAN> dtype<SPAN class="operator token">=</SPAN>dt<SPAN class="punctuation token">)</SPAN>
out<SPAN class="punctuation token">[</SPAN><SPAN class="string token">'Value'</SPAN><SPAN class="punctuation token">]</SPAN> <SPAN class="operator token">=</SPAN> uniq<SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">:</SPAN><SPAN class="operator token">-</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN>
out<SPAN class="punctuation token">[</SPAN><SPAN class="string token">'Count'</SPAN><SPAN class="punctuation token">]</SPAN> <SPAN class="operator token">=</SPAN> cnts<SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">:</SPAN><SPAN class="operator token">-</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN>
out<SPAN class="punctuation token">[</SPAN><SPAN class="string token">'Percent'</SPAN><SPAN class="punctuation token">]</SPAN> <SPAN class="operator token">=</SPAN> per<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>

We don't need to know the coordinates of the lower left, the number of rows and columns or the nodata value, since we can get that when we read in the raster.

RasterToNumPyArray—ArcPy Functions | ArcGIS Desktop

RasterToNumPyArray (in_raster, {lower_left_corner}, {ncols}, {nrows}, {nodata_to_value})

Basic information on the array shape and data type

a<SPAN class="punctuation token">.</SPAN>shape  <SPAN class="comment token"># ---- number of rows and columns</SPAN>
<SPAN class="punctuation token">(</SPAN><SPAN class="number token">84</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">55</SPAN><SPAN class="punctuation token">)</SPAN>

a<SPAN class="punctuation token">.</SPAN>dtype  <SPAN class="comment token"># ---- data type of the array, unsigned 16bit integer</SPAN>
dtype<SPAN class="punctuation token">(</SPAN><SPAN class="string token">'uint16'</SPAN><SPAN class="punctuation token">)</SPAN>

<SPAN class="comment token"># ---- the nodata value is 65535, which is the maximum integer value for uint16</SPAN>
<SPAN class="comment token"># ---- get this infor from `uniq`</SPAN>
uniq
array<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">[</SPAN>    <SPAN class="number token">1</SPAN><SPAN class="punctuation token">,</SPAN>     <SPAN class="number token">2</SPAN><SPAN class="punctuation token">,</SPAN>     <SPAN class="number token">3</SPAN><SPAN class="punctuation token">,</SPAN>     <SPAN class="number token">4</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">65535</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">,</SPAN> dtype<SPAN class="operator token">=</SPAN>uint16<SPAN class="punctuation token">)</SPAN>

<SPAN class="comment token"># ---- counts return a 64bit integer, the 2098 is the nodata cell count</SPAN>
cnts
array<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">[</SPAN><SPAN class="number token">1057</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">1186</SPAN><SPAN class="punctuation token">,</SPAN>  <SPAN class="number token">274</SPAN><SPAN class="punctuation token">,</SPAN>    <SPAN class="number token">5</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">2098</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">,</SPAN> dtype<SPAN class="operator token">=</SPAN>int64<SPAN class="punctuation token">)</SPAN>

<SPAN class="comment token"># ---- At this stage we want to remove our nodata values from the counts and % calculations‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍</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>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN>

Line 5 in the first code block

per <SPAN class="operator token">=</SPAN> cnts<SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">:</SPAN><SPAN class="operator token">-</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="operator token">/</SPAN>np<SPAN class="punctuation token">.</SPAN>sum<SPAN class="punctuation token">(</SPAN>cnts<SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">:</SPAN><SPAN class="operator token">-</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">)</SPAN> <SPAN class="operator token">*</SPAN><SPAN class="number token">100</SPAN><SPAN class="punctuation token">.</SPAN><SPAN class="line-numbers-rows"><SPAN>‍</SPAN></SPAN>

basically means " use all the cnts up to but no including the last value, divide it by their sum and multiply by 100%.

cnts[:-1] ... is a slice, the : means everything up to but excluding... Read up on array slicing... This is only a 2D array, but it can be head melting for arrays beyond 4D.

You will notice that I did slicing in lines 10 and 11 to exclude the no data values, but I didn't need to do if for the 'per' line because I sliced already.

Of course, the above can be put into a 'def' (aka function) if you need to do it all the time, and the code can be simplified greatly... Just to show you how working with basic arrays is easy.

When you want to work with things like area... then it becomes important to know the cell size of each array element. That is where 'human-ware' comes into play (ie, take notes) and sometimes exporting rasters to old-school ASCII rasters is useful since the cell size information goes out with it. RasterToNumPyArray, doesn't... you have to remember..

So you want to save stuff? I use numpy as well.

out_fn <SPAN class="operator token">=</SPAN> <SPAN class="string token">"C:/temp/InRaster/in_raster.npy"</SPAN>
np<SPAN class="punctuation token">.</SPAN>save<SPAN class="punctuation token">(</SPAN>out_fn<SPAN class="punctuation token">,</SPAN> a<SPAN class="punctuation token">)</SPAN><SPAN class="line-numbers-rows"><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN>

Hmmm maybe I should look at it again, just in case

a_gain <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>load<SPAN class="punctuation token">(</SPAN><SPAN class="string token">"C:/temp/InRaster/in_raster.npy"</SPAN><SPAN class="punctuation token">)</SPAN>

np<SPAN class="punctuation token">.</SPAN>all<SPAN class="punctuation token">(</SPAN>a <SPAN class="operator token">==</SPAN> a_gain<SPAN class="punctuation token">)</SPAN>
<SPAN class="token boolean">True</SPAN><SPAN class="line-numbers-rows"><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN>

All is good!

All comments

DanPatterson_Retired

Let me know if you are having any troubles or if there is something you use often in your workflow...there is always lesson 3

ZacharyHart

Dan,

I can't thank you enough for taking the time to do this! I marked this as correct and am looking forward to using NumPy even more.

Thanks so much!

DanPatterson_Retired

Lesson 2... *tif file in … info out.

First the verbose code that produces the outcome, followed by explanations

fn <SPAN class="operator token">=</SPAN> <SPAN class="string token">"c:/Temp/InRaster/InRaster.tif"</SPAN>
<SPAN class="keyword token">import</SPAN> arcpy
a <SPAN class="operator token">=</SPAN> arcpy<SPAN class="punctuation token">.</SPAN>RasterToNumPyArray<SPAN class="punctuation token">(</SPAN>fn<SPAN class="punctuation token">)</SPAN>
uniq<SPAN class="punctuation token">,</SPAN> cnts <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>unique<SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">,</SPAN> return_counts<SPAN class="operator token">=</SPAN><SPAN class="token boolean">True</SPAN><SPAN class="punctuation token">)</SPAN>
per <SPAN class="operator token">=</SPAN> cnts<SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">:</SPAN><SPAN class="operator token">-</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="operator token">/</SPAN>np<SPAN class="punctuation token">.</SPAN>sum<SPAN class="punctuation token">(</SPAN>cnts<SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">:</SPAN><SPAN class="operator token">-</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">)</SPAN> <SPAN class="operator token">*</SPAN><SPAN class="number token">100</SPAN><SPAN class="punctuation token">.</SPAN>

dt <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">(</SPAN><SPAN class="string token">'Value'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'<i4'</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="punctuation token">(</SPAN><SPAN class="string token">'Count'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'<i4'</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="punctuation token">(</SPAN><SPAN class="string token">'Percent'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'<f8'</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">]</SPAN>
sze <SPAN class="operator token">=</SPAN> cnts<SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">:</SPAN><SPAN class="operator token">-</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">.</SPAN>size
out <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>zeros<SPAN class="punctuation token">(</SPAN>sze<SPAN class="punctuation token">,</SPAN> dtype<SPAN class="operator token">=</SPAN>dt<SPAN class="punctuation token">)</SPAN>
out<SPAN class="punctuation token">[</SPAN><SPAN class="string token">'Value'</SPAN><SPAN class="punctuation token">]</SPAN> <SPAN class="operator token">=</SPAN> uniq<SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">:</SPAN><SPAN class="operator token">-</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN>
out<SPAN class="punctuation token">[</SPAN><SPAN class="string token">'Count'</SPAN><SPAN class="punctuation token">]</SPAN> <SPAN class="operator token">=</SPAN> cnts<SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">:</SPAN><SPAN class="operator token">-</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN>
out<SPAN class="punctuation token">[</SPAN><SPAN class="string token">'Percent'</SPAN><SPAN class="punctuation token">]</SPAN> <SPAN class="operator token">=</SPAN> per<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>

We don't need to know the coordinates of the lower left, the number of rows and columns or the nodata value, since we can get that when we read in the raster.

RasterToNumPyArray—ArcPy Functions | ArcGIS Desktop

RasterToNumPyArray (in_raster, {lower_left_corner}, {ncols}, {nrows}, {nodata_to_value})

Basic information on the array shape and data type

a<SPAN class="punctuation token">.</SPAN>shape  <SPAN class="comment token"># ---- number of rows and columns</SPAN>
<SPAN class="punctuation token">(</SPAN><SPAN class="number token">84</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">55</SPAN><SPAN class="punctuation token">)</SPAN>

a<SPAN class="punctuation token">.</SPAN>dtype  <SPAN class="comment token"># ---- data type of the array, unsigned 16bit integer</SPAN>
dtype<SPAN class="punctuation token">(</SPAN><SPAN class="string token">'uint16'</SPAN><SPAN class="punctuation token">)</SPAN>

<SPAN class="comment token"># ---- the nodata value is 65535, which is the maximum integer value for uint16</SPAN>
<SPAN class="comment token"># ---- get this infor from `uniq`</SPAN>
uniq
array<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">[</SPAN>    <SPAN class="number token">1</SPAN><SPAN class="punctuation token">,</SPAN>     <SPAN class="number token">2</SPAN><SPAN class="punctuation token">,</SPAN>     <SPAN class="number token">3</SPAN><SPAN class="punctuation token">,</SPAN>     <SPAN class="number token">4</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">65535</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">,</SPAN> dtype<SPAN class="operator token">=</SPAN>uint16<SPAN class="punctuation token">)</SPAN>

<SPAN class="comment token"># ---- counts return a 64bit integer, the 2098 is the nodata cell count</SPAN>
cnts
array<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">[</SPAN><SPAN class="number token">1057</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">1186</SPAN><SPAN class="punctuation token">,</SPAN>  <SPAN class="number token">274</SPAN><SPAN class="punctuation token">,</SPAN>    <SPAN class="number token">5</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">2098</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">,</SPAN> dtype<SPAN class="operator token">=</SPAN>int64<SPAN class="punctuation token">)</SPAN>

<SPAN class="comment token"># ---- At this stage we want to remove our nodata values from the counts and % calculations‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍</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>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN>

Line 5 in the first code block

per <SPAN class="operator token">=</SPAN> cnts<SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">:</SPAN><SPAN class="operator token">-</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="operator token">/</SPAN>np<SPAN class="punctuation token">.</SPAN>sum<SPAN class="punctuation token">(</SPAN>cnts<SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">:</SPAN><SPAN class="operator token">-</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">)</SPAN> <SPAN class="operator token">*</SPAN><SPAN class="number token">100</SPAN><SPAN class="punctuation token">.</SPAN><SPAN class="line-numbers-rows"><SPAN>‍</SPAN></SPAN>

basically means " use all the cnts up to but no including the last value, divide it by their sum and multiply by 100%.

cnts[:-1] ... is a slice, the : means everything up to but excluding... Read up on array slicing... This is only a 2D array, but it can be head melting for arrays beyond 4D.

You will notice that I did slicing in lines 10 and 11 to exclude the no data values, but I didn't need to do if for the 'per' line because I sliced already.

Of course, the above can be put into a 'def' (aka function) if you need to do it all the time, and the code can be simplified greatly... Just to show you how working with basic arrays is easy.

So you want to save stuff? I use numpy as well.

out_fn <SPAN class="operator token">=</SPAN> <SPAN class="string token">"C:/temp/InRaster/in_raster.npy"</SPAN>
np<SPAN class="punctuation token">.</SPAN>save<SPAN class="punctuation token">(</SPAN>out_fn<SPAN class="punctuation token">,</SPAN> a<SPAN class="punctuation token">)</SPAN><SPAN class="line-numbers-rows"><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN>

Hmmm maybe I should look at it again, just in case

a_gain <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>load<SPAN class="punctuation token">(</SPAN><SPAN class="string token">"C:/temp/InRaster/in_raster.npy"</SPAN><SPAN class="punctuation token">)</SPAN>

np<SPAN class="punctuation token">.</SPAN>all<SPAN class="punctuation token">(</SPAN>a <SPAN class="operator token">==</SPAN> a_gain<SPAN class="punctuation token">)</SPAN>
<SPAN class="token boolean">True</SPAN><SPAN class="line-numbers-rows"><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN>

All is good!

ZacharyHart

yay!

DanPatterson_Retired

I can check when I get back, there are a few tricks when moving from structured to non-structured not covered in my example.... lesson 2 coming soon

ZacharyHart

what a treasure trove!

ZacharyHart

Dan, this is great! And now i'm learning about NumPy Data type objects.

One thing: I'm getting an error which I'm guessing is a result of something specific with the raster I'm using.

out<SPAN class="punctuation token">[</SPAN><SPAN class="string token">'Value'</SPAN><SPAN class="punctuation token">]</SPAN> <SPAN class="operator token">=</SPAN> uniq
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">"<string>"</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>
ValueError<SPAN class="punctuation token">:</SPAN> Can't cast <SPAN class="keyword token">from</SPAN> structure to non<SPAN class="operator token">-</SPAN>structure<SPAN class="punctuation token">,</SPAN> <SPAN class="keyword token">except</SPAN> <SPAN class="keyword token">if</SPAN> the structure only has a single field<SPAN class="punctuation token">.</SPAN>‍‍‍‍<SPAN class="line-numbers-rows"><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN><SPAN>‍</SPAN></SPAN>

Conceptually, I understand what you're doing with your example. Thanks!

EDIT: I uploaded some sample raster data to my original post.

DanPatterson_Retired

Zachary... I also have loads of quasi-organized code on my GitHub site

Dan-Patterson (Dan Patterson) · GitHub

arraytools and tools for pro might have some useful stuff

PS, if you have nodata areas, then all the stats stuff has 'nan' equivalents... ie np.sum there is np.nansum which just sums all the nodata values.

numpy and scipy are both very powerful tools and you would be amazed at how much their functionality is used with the esri code base. Many of the spatial analyst tools have a direct numpy equivalent/replacement

DanPatterson_Retired

Love a lesson... this is going to be verbose and I will leave out all the shortcuts and helper functions.

Assume you have your 'array'... I will generate a small array, so you can ignore the first two lines and begin with

array 'a'

np<SPAN class="punctuation token">.</SPAN>random<SPAN class="punctuation token">.</SPAN>RandomState<SPAN class="punctuation token">(</SPAN><SPAN class="number token">123</SPAN><SPAN class="punctuation token">)</SPAN>
a <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>random<SPAN class="punctuation token">.</SPAN>randint<SPAN class="punctuation token">(</SPAN><SPAN class="number token">0</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">5</SPAN><SPAN class="punctuation token">,</SPAN> size<SPAN class="operator token">=</SPAN><SPAN class="punctuation token">(</SPAN><SPAN class="number token">10</SPAN><SPAN class="punctuation token">,</SPAN><SPAN class="number token">10</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">)</SPAN>

uniq<SPAN class="punctuation token">,</SPAN> cnts <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>unique<SPAN class="punctuation token">(</SPAN>a<SPAN class="punctuation token">,</SPAN> return_counts<SPAN class="operator token">=</SPAN><SPAN class="token boolean">True</SPAN><SPAN class="punctuation token">)</SPAN>  <SPAN class="comment token"># ---- get the unique values and their count</SPAN>
per <SPAN class="operator token">=</SPAN> cnts<SPAN class="operator token">/</SPAN>cnts<SPAN class="punctuation token">.</SPAN>sum<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">)</SPAN> <SPAN class="operator token">*</SPAN><SPAN class="number token">100</SPAN><SPAN class="punctuation token">.</SPAN>   <SPAN class="comment token"># ---- the percentage, old school</SPAN>
dt <SPAN class="operator token">=</SPAN> <SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">(</SPAN><SPAN class="string token">'Value'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'<i4'</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="punctuation token">(</SPAN><SPAN class="string token">'Count'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'<i4'</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="punctuation token">(</SPAN><SPAN class="string token">'Percent'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'<f8'</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">]</SPAN>  <SPAN class="comment token"># --- data type for output</SPAN>
out <SPAN class="operator token">=</SPAN> np<SPAN class="punctuation token">.</SPAN>zeros<SPAN class="punctuation token">(</SPAN>uniq<SPAN class="punctuation token">.</SPAN>size<SPAN class="punctuation token">,</SPAN> dtype<SPAN class="operator token">=</SPAN>dt<SPAN class="punctuation token">)</SPAN>  <SPAN class="comment token"># ---- make a 'container' to store the results</SPAN>
out<SPAN class="punctuation token">[</SPAN><SPAN class="string token">'Value'</SPAN><SPAN class="punctuation token">]</SPAN> <SPAN class="operator token">=</SPAN> uniq  <SPAN class="comment token"># ---- fill the container</SPAN>
out<SPAN class="punctuation token">[</SPAN><SPAN class="string token">'Count'</SPAN><SPAN class="punctuation token">]</SPAN> <SPAN class="operator token">=</SPAN> cnts  <SPAN class="comment token"># ----</SPAN>
out<SPAN class="punctuation token">[</SPAN><SPAN class="string token">'Percent'</SPAN><SPAN class="punctuation token">]</SPAN> <SPAN class="operator token">=</SPAN> per <SPAN class="comment token"># ----</SPAN>

<SPAN class="comment token"># ---- Result</SPAN>
out

array<SPAN class="punctuation token">(</SPAN><SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">(</SPAN><SPAN class="number token">0</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">22</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">22</SPAN><SPAN class="punctuation token">.</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="punctuation token">(</SPAN><SPAN class="number token">1</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">16</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">16</SPAN><SPAN class="punctuation token">.</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="punctuation token">(</SPAN><SPAN class="number token">2</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">19</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">19</SPAN><SPAN class="punctuation token">.</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="punctuation token">(</SPAN><SPAN class="number token">3</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">23</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">23</SPAN><SPAN class="punctuation token">.</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="punctuation token">(</SPAN><SPAN class="number token">4</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">20</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="number token">20</SPAN><SPAN class="punctuation token">.</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">,</SPAN>
      dtype<SPAN class="operator token">=</SPAN><SPAN class="punctuation token">[</SPAN><SPAN class="punctuation token">(</SPAN><SPAN class="string token">'Value'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'<i4'</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="punctuation token">(</SPAN><SPAN class="string token">'Count'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'<i4'</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="punctuation token">(</SPAN><SPAN class="string token">'Percent'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'<f8'</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">]</SPAN><SPAN class="punctuation token">)</SPAN>

<SPAN class="comment token"># ---- Oooooo I don't like that look ---- time for a 'helper' function (written by me)</SPAN>

Array info<SPAN class="punctuation token">.</SPAN><SPAN class="punctuation token">.</SPAN><SPAN class="punctuation token">.</SPAN>
shape<SPAN class="punctuation token">.</SPAN><SPAN class="punctuation token">.</SPAN><SPAN class="punctuation token">.</SPAN> <SPAN class="punctuation token">(</SPAN><SPAN class="number token">5</SPAN><SPAN class="punctuation token">,</SPAN><SPAN class="punctuation token">)</SPAN>  ndim<SPAN class="punctuation token">.</SPAN><SPAN class="punctuation token">.</SPAN><SPAN class="punctuation token">.</SPAN> <SPAN class="number token">1</SPAN>  dtype<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><SPAN class="string token">'Value'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'<i4'</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="punctuation token">(</SPAN><SPAN class="string token">'Count'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'<i4'</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="punctuation token">(</SPAN><SPAN class="string token">'Percent'</SPAN><SPAN class="punctuation token">,</SPAN> <SPAN class="string token">'<f8'</SPAN><SPAN class="punctuation token">)</SPAN><SPAN class="punctuation token">]</SPAN> 
╔═ 
║ ╔═ 
<SPAN class="number token">5</SPAN>  

 id  Value   Count   Percent  
<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><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><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>
 <SPAN class="number token">000</SPAN>       <SPAN class="number token">0</SPAN>      <SPAN class="number token">22</SPAN>     <SPAN class="number token">22.00</SPAN>
 <SPAN class="number token">001</SPAN>       <SPAN class="number token">1</SPAN>      <SPAN class="number token">16</SPAN>     <SPAN class="number token">16.00</SPAN>
 <SPAN class="number token">002</SPAN>       <SPAN class="number token">2</SPAN>      <SPAN class="number token">19</SPAN>     <SPAN class="number token">19.00</SPAN>
 <SPAN class="number token">003</SPAN>       <SPAN class="number token">3</SPAN>      <SPAN class="number token">23</SPAN>     <SPAN class="number token">23.00</SPAN>
 <SPAN class="number token">004</SPAN>       <SPAN class="number token">4</SPAN>      <SPAN class="number token">20</SPAN>     <SPAN class="number token">20.00</SPAN>

<SPAN class="comment token"># ----- digest, I have lots of examples on my blog</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>‍</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>

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