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In the APL [[array model]] and [[leading axis theory]], a '''major cell''' is a [[cell]] of an array which has [[rank]] one smaller than the rank of the array, or equal to it if the array is a [[scalar]]. The number of major cells in an array is its [[Tally]], and a function can be called on the major cells of an array individually by applying it with rank <source lang=apl inline>¯1</source> using the [[Rank operator]]. Functions designed to follow leading axis theory often manipulate the major cells of an array. For example, [[Reverse First]] (<source lang=apl inline>⊖</source>) is considered the primary form of [[Reverse]] in leading-axis languages because it can be interpreted as reversing the major cells of its argument; [[J]] removes last-axis Reverse entirely.
In the APL [[array model]] and [[leading axis theory]], a '''major cell''', or '''item''', is a [[cell]] of an array which has [[rank]] one smaller than the rank of the array, or equal to it if the array is a [[scalar]]. The number of major cells in an array is its [[Tally]], and a function can be called on the major cells of an array individually by applying it with rank <syntaxhighlight lang=apl inline>¯1</syntaxhighlight> using the [[Rank operator]]. Functions designed to follow leading axis theory often manipulate the major cells of an array. For example, [[Reverse First]] (<syntaxhighlight lang=apl inline>⊖</syntaxhighlight>) is considered the primary form of [[Reverse]] in leading-axis languages because it can be interpreted as reversing the major cells of its argument; [[J]] removes last-axis Reverse entirely.


== Examples ==
== Examples ==


<source lang=apl inline>A</source> is an array with [[shape]] <source lang=apl inline>3 4</source>. Using [[Tally]] we see that the number of major cells in <source lang=apl inline>A</source> is the first element of the shape, <source lang=apl inline>3</source>:
<syntaxhighlight lang=apl inline>A</syntaxhighlight> is an array with [[shape]] <syntaxhighlight lang=apl inline>3 4</syntaxhighlight>. Using [[Tally]] we see that the number of major cells in <syntaxhighlight lang=apl inline>A</syntaxhighlight> is the first element of the shape, <syntaxhighlight lang=apl inline>3</syntaxhighlight>:
<source lang=apl>
<syntaxhighlight lang=apl>
       ⊢A ← 5 3 1 ∘.∧ 2 3 4 5
       ⎕←A ← 5 3 1 ∘.∧ 2 3 4 5
10 15 20  5
10 15 20  5
  6  3 12 15
  6  3 12 15
Line 11: Line 11:
       ≢A
       ≢A
3
3
</source>
</syntaxhighlight>
We can separate <source lang=apl inline>A</source>'s major cells using [[Enclose]] with [[Rank operator|rank]] <source lang=apl inline>¯1</source>:
We can separate <syntaxhighlight lang=apl inline>A</syntaxhighlight>'s major cells using [[Enclose]] with [[Rank operator|rank]] <syntaxhighlight lang=apl inline>¯1</syntaxhighlight>:
<source lang=apl>
<syntaxhighlight lang=apl>
       ⊂⍤¯1 ⊢A
       ⊂⍤¯1 ⊢A
┌──────────┬─────────┬───────┐
┌──────────┬─────────┬───────┐
│10 15 20 5│6 3 12 15│2 3 4 5│
│10 15 20 5│6 3 12 15│2 3 4 5│
└──────────┴─────────┴───────┘
└──────────┴─────────┴───────┘
</source>
</syntaxhighlight>
Given another array <source lang=apl inline>B</source> we can search for cells of <source lang=apl inline>B</source> which [[match]] major cells of <source lang=apl inline>B</source>. [[High rank set functions|High-rank]] [[Index-of]] always searches for right argument cells whose rank matches the rank of a left argument major cell: if the right argument is a [[vector]] and not a [[matrix]] then it searches for the entire vector rather than its major cells (which are [[scalar]]s).
Given another array <syntaxhighlight lang=apl inline>B</syntaxhighlight> we can search for cells of <syntaxhighlight lang=apl inline>B</syntaxhighlight> which [[match]] major cells of <syntaxhighlight lang=apl inline>B</syntaxhighlight>. [[Major cell search|High-rank]] [[Index-of]] always searches for right argument cells whose rank matches the rank of a left argument major cell: if the right argument is a [[vector]] and not a [[matrix]] then it searches for the entire vector rather than its major cells (which are [[scalar]]s).
<source lang=apl>
<syntaxhighlight lang=apl>
       ⊢B ← ↑ 4,/⍳6
       ⎕←B ← ↑ 4,/⍳6
1 2 3 4
1 2 3 4
2 3 4 5
2 3 4 5
Line 29: Line 29:
       A ⍳ 2 3 4 5
       A ⍳ 2 3 4 5
3
3
</source>
</syntaxhighlight>


{{APL programming language}}
{{APL features}}[[Category:Array relationships]]

Latest revision as of 23:27, 10 March 2024

In the APL array model and leading axis theory, a major cell, or item, is a cell of an array which has rank one smaller than the rank of the array, or equal to it if the array is a scalar. The number of major cells in an array is its Tally, and a function can be called on the major cells of an array individually by applying it with rank ¯1 using the Rank operator. Functions designed to follow leading axis theory often manipulate the major cells of an array. For example, Reverse First () is considered the primary form of Reverse in leading-axis languages because it can be interpreted as reversing the major cells of its argument; J removes last-axis Reverse entirely.

Examples

A is an array with shape 3 4. Using Tally we see that the number of major cells in A is the first element of the shape, 3:

      ⎕←A ← 5 3 1 ∘.∧ 2 3 4 5
10 15 20  5
 6  3 12 15
 2  3  4  5
      ≢A
3

We can separate A's major cells using Enclose with rank ¯1:

      ⊂⍤¯1 ⊢A
┌──────────┬─────────┬───────┐
│10 15 20 5│6 3 12 15│2 3 4 5│
└──────────┴─────────┴───────┘

Given another array B we can search for cells of B which match major cells of B. High-rank Index-of always searches for right argument cells whose rank matches the rank of a left argument major cell: if the right argument is a vector and not a matrix then it searches for the entire vector rather than its major cells (which are scalars).

      ⎕←B ← ↑ 4,/⍳6
1 2 3 4
2 3 4 5
3 4 5 6
      A ⍳ B
4 3 4
      A ⍳ 2 3 4 5
3


APL features [edit]
Built-ins Primitives (functions, operators) ∙ Quad name
Array model ShapeRankDepthBoundIndex (Indexing) ∙ AxisRavelRavel orderElementScalarVectorMatrixSimple scalarSimple arrayNested arrayCellMajor cellSubarrayEmpty arrayPrototype
Data types Number (Boolean, Complex number) ∙ Character (String) ∙ BoxNamespaceFunction array
Concepts and paradigms Conformability (Scalar extension, Leading axis agreement) ∙ Scalar function (Pervasion) ∙ Identity elementComplex floorArray ordering (Total) ∙ Tacit programming (Function composition, Close composition) ∙ GlyphLeading axis theoryMajor cell searchFirst-class function
Errors LIMIT ERRORRANK ERRORSYNTAX ERRORDOMAIN ERRORLENGTH ERRORINDEX ERRORVALUE ERROREVOLUTION ERROR