Outer Product

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∘.

Outer Product (∘.), or Table is a monadic operator, which will produce a dyadic function when applied with a dyadic function. Outer product applies the operand function on each element of the left array with each element of the right array. It can be described as a shortcut for constructing nested for loops.

Syntax

Outer Product differs from all other monadic operators, which are written as a single glyph, with the operand on the left. For historical reasons, the outer product operator is a bi-glyph denoted as ∘., and its appears on the right.

This syntactical inconsistency is resolved in J and BQN, where the outer product operator, called Table, and denoted / and ⌜ respectively, have the usual operator syntax.

Examples

      x ← 1 2 3
      y ← 4 5 6
      x ∘., y ⍝ visualizing outer product
┌───┬───┬───┐
│1 4│1 5│1 6│
├───┼───┼───┤
│2 4│2 5│2 6│
├───┼───┼───┤
│3 4│3 5│3 6│
└───┴───┴───┘

      ⍝ works for multi-dimensional arrays as well
      y←2 3 ⍴ 'abcdef'
      x←2 2 ⍴ ⍳4
      x∘.,y 
┌───┬───┬───┐
│1 a│1 b│1 c│
├───┼───┼───┤
│1 d│1 e│1 f│
└───┴───┴───┘
┌───┬───┬───┐
│2 a│2 b│2 c│
├───┼───┼───┤
│2 d│2 e│2 f│
└───┴───┴───┘
             
┌───┬───┬───┐
│3 a│3 b│3 c│
├───┼───┼───┤
│3 d│3 e│3 f│
└───┴───┴───┘
┌───┬───┬───┐
│4 a│4 b│4 c│
├───┼───┼───┤
│4 d│4 e│4 f│
└───┴───┴───┘

Applications

Outer product is useful for solving problems that intuitively require a polynomial time algorithm. This may also indicate that such an algorithm is not the fastest solution.

For example, suppose we want to find duplicated elements in an non-nested array. Intuitively speaking, the easiest way to solve this problem is to compare each element of the array with all other elements, which is exactly what an outer product does. 

      x ← 1 2 3 2
      ⎕ ← matrix ← x∘.=x ⍝ compare elements with each other using equal
1 0 0 0
0 1 0 1
0 0 1 0
0 1 0 1
      ⎕ ← count ← +/matrix ⍝ get the number of occurence of each element
1 2 1 2
      ⎕ ← indices ← count ≥ 2 ⍝ get the indices of elements which occured more than once
0 1 0 1
      ⎕ ← duplicated ← ∪ indices/x 
2

      ∪((+/x∘.=x)≥2)/x ⍝ everything above in one line
2
      (⊢∪⍤/⍨2≤(+/∘.=⍨)) x ⍝ point-free/tacit version
2

Using similar techniques, we can define a function that generates prime numbers by using an outer product of Residue. 

     primes ← {x←1↓⍳⍵ ⋄ (2>+⌿0=x∘.|x)/x}
     primes 10
2 3 5 7
      primes 20
2 3 5 7 11 13 17 19

Here there are faster solutions such as the Sieve of Eratosthenes.

External links

Documentation


APL built-ins [edit]
Primitives (Timeline) Functions
Scalar
Monadic Conjugate ∙ Negate ∙ Signum ∙ Reciprocal ∙ Magnitude ∙ Exponential ∙ Natural Logarithm ∙ Floor ∙ Ceiling ∙ Factorial ∙ Not ∙ Pi Times ∙ Roll ∙ Type ∙ Imaginary ∙ Square Root ∙ Round
Dyadic Add ∙ Subtract ∙ Times ∙ Divide ∙ Residue ∙ Power ∙ Logarithm ∙ Minimum ∙ Maximum ∙ Binomial ∙ Comparison functions ∙ Boolean functions (And, Or, Nand, Nor) ∙ GCD ∙ LCM ∙ Circular ∙ Complex ∙ Root
Non-Scalar
Structural Shape ∙ Reshape ∙ Tally ∙ Depth ∙ Ravel ∙ Enlist ∙ Table ∙ Catenate ∙ Reverse ∙ Rotate ∙ Transpose ∙ Raze ∙ Mix ∙ Split ∙ Enclose ∙ Nest ∙ Cut (K) ∙ Pair ∙ Link ∙ Partitioned Enclose ∙ Partition
Selection First ∙ Pick ∙ Take ∙ Drop ∙ Unique ∙ Identity ∙ Stop ∙ Select ∙ Replicate ∙ Expand ∙ Set functions (Intersection ∙ Union ∙ Without) ∙ Bracket indexing ∙ Index ∙ Cartesian Product ∙ Sort
Selector Index generator ∙ Grade ∙ Index Of ∙ Interval Index ∙ Indices ∙ Deal ∙ Prefix and suffix vectors
Computational Match ∙ Not Match ∙ Membership ∙ Find ∙ Nub Sieve ∙ Encode ∙ Decode ∙ Matrix Inverse ∙ Matrix Divide ∙ Format ∙ Execute ∙ Materialise ∙ Range
Operators Monadic Each ∙ Commute ∙ Constant ∙ Replicate ∙ Expand ∙ Reduce ∙ Windowed Reduce ∙ Scan ∙ Outer Product ∙ Key ∙ I-Beam ∙ Spawn ∙ Function axis ∙ Identity (Null, Ident)
Dyadic Bind ∙ Compositions (Compose, Reverse Compose, Beside, Withe, Atop, Over) ∙ Inner Product ∙ Determinant ∙ Power ∙ At ∙ Under ∙ Rank ∙ Depth ∙ Variant ∙ Stencil ∙ Cut ∙ Direct definition (operator) ∙ Identity (Lev, Dex)
Quad names Index origin ∙ Comparison tolerance ∙ Migration level ∙ Atomic vector
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