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Challenge #113: Interpolating Spatial Grid Values

Kinga
アステロイド

hi,

 

Please find my solutions: one Spatial one non-Spatial.

 

スポイラ
Kinga_0-1668617601467.png

 

ahsanaali
ボリード
スポイラ
ahsanaali_0-1670516549874.png

 

FrederikE
パルサー
スポイラ
FrederikE_0-1670709776792.png

 

rubaiyadoula
アトム

 

スポイラ
 

In the provided solution, could anyone please explain how this Batch Macro is working?

 

1. This is the U input that contains all the non-zero Pixel Values:

 

U Input with all the values that aren't 0U Input with all the values that aren't 0

 

2. The Z input with all the 0 Pixel Values:

 

Z Input with all the 0 valuesZ Input with all the 0 values

 

3. The Control Parameter with the field "Concat_Column_Row" and none group settings:

Control ParameterControl Parameter

 

4. Output of the Macro:
 macroques1.PNG

 

Based on the input, how is it calculating the missing value using the average of the known measurements from the surrounding cells only based on one column value and outputting the Smoothed Pixel Value?

kristiadiuisan
アステロイド
スポイラ
Alteryx_challenge_113_KU.png
olga_strubbe
ボリード
スポイラ
olga_strubbe_0-1677072893026.png

 

This was a neat, but definitely challenging problem, thank you!  I liked the solution by @ggruccio    I followed a similar approach.  Thank you, ggruccio!

alacoume
コメット

My solution:

CeliaC_Silje
アステロイド
スポイラ
CeliaC_Silje_0-1680143054436.png
bkclaw113
コメット

I went a different route and ignored the spatial component

スポイラ
Once you transpose the columns and get row,col, value just takes a simple batch match to average the adjacent values for the missing spots.
bkclaw113_0-1681477781054.png

 

bkclaw113_1-1681477793423.png

 

chandler-gjino
Alteryx
Alteryx

attaching my solution