The Diagonal Suite: Gentle thunking goes a long way!
I've become a big advocate for gentle thunking - using thunks to delay eager evaluation wherever possible in generalized Lambda development. The timings are quicker and the logic is cleaner. On the other hand, thunking the results of MAP, BYROW, or BYCOL - especially when it leads to rows of thunks - tends to introduce recombination overhead and complexity. I think thunking is often dismissed as “too complex,” and that’s understandable if someone’s first exposure involves unwrapping a row of thunks. When used gently thunking becomes indispensable. Typically, I introduce the thunks after the initial benchmarking to see the difference in the calculation times and the after is always quicker. To illustrate, I’ll share The Diagonal Suite - a collection of functions where thunking is used at every opportunity. Simple, clean, deferred logic. What are your thoughts on gentle thunking? Where have you found it helpful/harmful in your own Lambda development? //The Diagonal Suite - Version 1.0 - 10/27/2025 //Author: Patrick H. //Description: Directional traversal and diagonal logic for 2D arrays. // Functions: // • Traverseλ - Directional traversal engine // • ByDiagλ - Diagonal-based aggregation // • DiagMapλ - Wrapper for diagonal matrix extraction // • DiagIndexλ - Targeted diagonal extraction // • Staircaseλ - Construct diagonal staircases from a vector or 2D array //──────────────────────────────────────────────────────────── //------------------------------------------------------------------------------------------- //Traverseλ - Directional Axis Remapper //------------------------------------------------------------------------------------------- //The selected axis is remapped to the top-left traversal order. //Accepted directions: // "NE" or 1 → Northeast (↗) // "SE" or 2 → Southeast (↘) // "SW" or 3 → Southwest (↙) //Parameters: //array → 2D input array (scalars not accepted) //new_axis → Axis direction ("NE", "SE", "SW" or 1–3) Traverseλ = LAMBDA( array, new_axis, //Input validation IF(OR(ROWS(array)=1,COLUMNS(array)=1), "#2D-ARRAY!", IF(AND(ISNUMBER(new_axis),OR(new_axis<=0,new_axis>3)),"#AXIS!", LET( //Dimensions i, ROWS(array), j, COLUMNS(array), //Axis traversal indices (deferred) x_NE, LAMBDA(SEQUENCE(j,,1,0)*SEQUENCE(,i)), y_NE, LAMBDA(SEQUENCE(j,,j,-1)*SEQUENCE(,i,1,0)), x_SE, LAMBDA(SEQUENCE(i,,i,-1)*SEQUENCE(,j,1,0)), y_SE, LAMBDA(SEQUENCE(i,,j,0)+SEQUENCE(,j,0,-1)), x_SW, LAMBDA(SEQUENCE(j,,i,0)+SEQUENCE(,i,0,-1)), y_SW, LAMBDA(SEQUENCE(j,,1)*SEQUENCE(,i,1,0)), //Axis mode selection mode, IF(ISNUMBER(new_axis),new_axis, SWITCH(new_axis,"NE",1,"SE",2,"SW",3,1)), //Index selection x, CHOOSE(mode,x_NE,x_SE,x_SW), y, CHOOSE(mode,y_NE,y_SE,y_SW), //Unwrap indices and get results result, INDEX(array,x(),y()), result ) ))); //------------------------------------------------------------------------------------------- //ByDiagλ - Diagonal-based aggregation //------------------------------------------------------------------------------------------- //Apply an ETA function or Lambda to diagonals //Parameters: //array → 2D input array (scalars not accepted) //[function] → ETA function or Lambda applied to diagonals //[row_wise_stack?] → Optional: Display results as a vertical stack ByDiagλ = LAMBDA( array, [function], [row_wise_stack?], //Check array input ValidateDiagλ(array,,function,row_wise_stack?, LET( //Optional parameters No_Function, ISOMITTED(function), No_row_wise_stack,ISOMITTED(row_wise_stack?), //Dimensions i, ROWS(array), j, COLUMNS(array), //Diagonal count k, MIN(i,j), //Indices - deferred r, LAMBDA(SEQUENCE(k)*SEQUENCE(,j,1,0)), y, LAMBDA(SEQUENCE(k)+SEQUENCE(,j,0,1)), c, LAMBDA(IF(y()>j,NA(),y())), //Unwrap indices, shape, and aggregate result, IFNA(INDEX(array,r(),c()),""), shaped, IF(No_row_wise_stack,result,TRANSPOSE(result)), final, IF(No_Function,shaped, IF(No_row_wise_stack,BYCOL(shaped,function), BYROW(shaped,function))), final ))); //------------------------------------------------------------------------------------------- //DiagMapλ - Wrapper (Calls ByDiagλ) to extract diagonals as 2D matrix //------------------------------------------------------------------------------------------- //Calls ByDiagλ to extract the diagonals from a 2D array. //Parameters: *Please see ByDiagλ for descriptions.** DiagMapλ = LAMBDA( array, [row_wise_stack?], ByDiagλ(array,,row_wise_stack?) ); //------------------------------------------------------------------------------------------- //DiagIndexλ - Targeted diagonal extraction //------------------------------------------------------------------------------------------- //Extract a diagonal or anti-diagonal vector from a 2D array. //Parameters: //array → 2D input array (scalars not accepted) //col_index → Column number to start from. Negative = anti-diagonal DiagIndexλ = LAMBDA( array, col_index, //Input checks ValidateDiagλ(array,col_index,,, LET( //Dimensions i, ROWS(array), j, COLUMNS(array), //Diagonal direction: +1 = SE, –1 = SW s, SIGN(col_index), //Determine diagonal length based on bounds k, IF(s>0, MIN(i, j + 1 - col_index), MIN(i, ABS(col_index))), start, IF(s<0,ABS(col_index),col_index), //Indices - deferred x, LAMBDA(SEQUENCE(k)), y, LAMBDA(SEQUENCE(k,,start,s)), //Unwrap indices and extract vector deliver, INDEX(array,x(),y()), deliver ))); //------------------------------------------------------------------------------------------- //Staircaseλ — Construct diagonal staircases from a vector or 2D array //------------------------------------------------------------------------------------------- //Parameters: //array → Input array (flattened to vector row-wise) //block_size → Number of rows/columns per staircase block //[block_offset] → Optional padding between staircases //[IsHorizontal?] → Optional toggle for column-wise orientation //[IsAntiDiag?] → Optional toggle to display staircase anti-diagonal. Staircaseλ = LAMBDA( array, block_size, [block_offset], [IsHorizontal?], [IsAntiDiag?], //Check inputs ValidateStaircaseλ(array,block_size,block_offset, LET( //Check optional parameters no_Block_Offset, ISOMITTED(block_offset), zero_Offset, block_offset=0, col_offset, IF(No_Block_Offset,0,block_offset), IsVertical?, ISOMITTED(IsHorizontal?), Not_Anti_Diag, ISOMITTED(IsAntiDiag?), //Convert to vector and get dimensions flat, TOCOL(array), k, COUNTA(flat), seq, LAMBDA(SEQUENCE(k)), V, TOROW(EXPAND(WRAPROWS(seq(),block_size),, block_size+block_offset,0)), width, COLUMNS(V), //Anchors and indices - deferred i, LAMBDA(SEQUENCE(block_size)*SEQUENCE(,width,1,0)), col_arr, LAMBDA(IF(Not_Anti_Diag,SEQUENCE(,width), SEQUENCE(,width,width,-1))), j, LAMBDA(MOD(col_arr(),block_size+block_offset)), j_, LAMBDA(IF((no_Block_Offset)+(zero_Offset), IF(j()=0,block_size,j()),j())), idx, LAMBDA(IF(i()=j_(),V,NA())), //Obtain results, shape, and calculate result, DROP(IFNA(INDEX(flat,idx()),""),,-col_offset), final, IF(IsVertical?,TRANSPOSE(result),result), final ))); //---------------------Error Handling & Validation--------------------------- //Validates inputs for Staircaseλ. Please see Staircaseλ for parameter //descriptions. ValidateStaircaseλ = LAMBDA( array, block_size, [block_offset], [on_valid], LET( //Checks NotArray,TYPE(array)<>64, Invalid_block_size, OR(ISTEXT(block_size),block_size<=0,block_size>COUNTA(array)), Invalid_block_offset, OR(ISTEXT(block_offset),block_offset<0), //Logic gate IF(NotArray, "#NOT-ARRAY!", IF(Invalid_block_size, "#BLOCK-SIZE!", IF(Invalid_block_offset,"#BLOCK-OFFSET", on_valid)))) ); //---------------------Error Handling & Validation--------------------------- //Validate inputs for ByDiagλ, DiagMapλ, and DiagIndexλ. //*Please see those functions for parameter descriptions.* ValidateDiagλ= LAMBDA( array, [col_index], [function], [row_wise_stack?], [on_valid], LET( //---Checks--- //Array input IsArray?, TYPE(array)=64, Not_Array, NOT(IsArray?), //Col_index No_Col_Index, ISOMITTED(col_index), Col_Index_Included, NOT(No_Col_Index), Not_Valid_Col_Index?, NOT(AND(col_index<>0, ABS(col_index)<=COLUMNS(array))), //Function No_Function, ISOMITTED(function), Function_Included, NOT(No_Function), Invalid_Function?, AND(ISERROR(BYROW({1,1},function))), //Shaping input RowWiseStack?, NOT(ISOMITTED(row_wise_stack?)), //Deterine which function is being validated DiagIndex, Col_Index_Included, ByDiag, AND(No_Col_Index, Function_Included), DiagMap, AND(No_Col_Index, No_Function), //Logic gates //DiagIndexλ a, IF(Not_Array, "#NOT-ARRAY!", IF(Not_Valid_Col_Index?,"#COLUMN-INDEX!", on_valid)), //ByDiagλ b, IF(Not_Array, "#NOT-ARRAY!", IF(Invalid_Function?, "#FUNCTION!", on_valid)), //DiagMapλ c, IF(Not_Array, "#NOT-ARRAY!", on_valid), //Logic gate selection decide, IF(DiagIndex,a, IF(DiagMap,c, IF(ByDiag,b, "#UNROUTED!"))), decide )); //End of The Diagonal Suite - Version 1.0 //Author: Patrick H.Join us for a professional development session on the new AI-powered Teach module in M365 Copilot
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