ArrayMath.coffee

radians = (n) ->
  n * (Math.PI / 180)

# Operates similarly to Ruby's `Enumerable.invoke`
invoke = (a, f) ->
  for n in a
    memo = f memo, n
  memo

# Returns the sum of an array of numeric items
sum = (a) ->
  invoke a, (memo, n) ->
    memo ?= 0
    memo += n

# Returns the difference of an array of numeric items
difference = (a) ->
  start = a.slice(0, 1)
  invoke a.slice(1), (memo, n) ->
    memo ?= start
    memo -= n

# Returns the product of an array of numeric items
product = (a) ->
  invoke a, (memo, n) ->
    memo ?= 0
    memo *= n

# Returns the quotient of an array of numeric items
quotient = (a) ->
  start = a.slice(0, 1)
  invoke a.slice(1), (memo, n) ->
    memo ?= start
    memo /= n

# Returns the dot product of two arrays of numeric items
dotProduct = (a, b) ->
  if a.length isnt b.length
    throw 'Argument `a` is not the same length as `b`.'
  else
    products = for v_a, i in a
      v_b = b[i]
      if v_a.length isnt v_b.length
        throw 'Item `a`[#{i}] does not have the same dimmension as `b`[#{i}].'
      else
        v_a * v_b
    sum products

matrix = (a, r, c) ->
  {
    rows: r,
    columns: c,
    data: a
  }

identity = (d) ->
  a = []
  a.push (x is d - y) + 0 for x in [1..d] for y in [d-1..0]
  matrix(a, d, d)

transform = (a, b) ->
  n = []
  for r in [0...a.rows]
    a_r = a.data.slice r * a.columns, r * a.columns + a.columns
    for c in [0...b.columns]
      b_c = (v for v, i in b.data when i % b.columns is c)
      n.push dotProduct a_r, b_c
  matrix n, r, c