Added mean algorithms :)

Yonaba · Yonaba · commit b69fc8967e05 · 2014-04-24T09:55:56.000Z
diff --git a/Average/Lua/Yonaba/average.lua b/Average/Lua/Yonaba/average.lua
@@ -0,0 +1,91 @@
+-- Various average (means) algorithms implementation
+-- See: http://en.wikipedia.org/wiki/Average
+
+-- Returns the sum of a sequence of values
+local function sum(x)
+  local s = 0
+  for _, v in ipairs(x) do s = s + v end
+  return s
+end
+
+-- Calculates the arithmetic mean of a set of values
+-- x       : an array of values
+-- returns : the arithmetic mean
+local function arithmetic_mean(x)
+  return (sum(x) / #x)
+end
+
+-- Calculates the geometric mean of a set of values
+-- x       : an array of values
+-- returns : the geometric mean
+local function geometric_mean(x)
+  local prod = 1
+  for _, v in ipairs(x) do prod = prod * v end
+  return (prod ^ (1 / #x))
+end
+
+-- Calculates the harmonic mean of a set of values
+-- x       : an array of values
+-- returns : the harmonic mean
+local function harmonic_mean(x)
+  local s = 0
+  for _, v in ipairs(x) do s = s + (1 / v) end
+  return (#x / s)
+end
+
+-- Calculates the quadratic mean of a set of values
+-- x       : an array of values
+-- returns : the quadratic mean
+local function quadratic_mean(x)
+  local ssquares = 0
+  for _, v in ipairs(x) do ssquares = ssquares + (v * v) end
+  return math.sqrt((1 / #x) * ssquares)
+end
+
+-- Calculates the generalized mean (to a specified power p) of a set of values
+-- x       : an array of values
+-- p       : a power
+-- returns : the generalized mean
+local function generalized_mean(x, p)
+  local sump = 0
+  for _, v in ipairs(x) do sump = sump + (v ^ p) end
+  return ((1 / #x) * sump) ^ (1 / p)
+end
+
+-- Calculates the weighted mean of a set of values
+-- x       : an array of values
+-- w       : an array of weights for each value in x
+-- returns : the weighted mean
+local function weighted_mean(x, w)
+  local sump = 0
+  for i, v in ipairs (x) do sump = sump + (v * w[i]) end
+  return sump / sum(w)
+end
+
+-- Calculates the midrange mean of a set of values
+-- x       : an array of values
+-- returns : the midrange mean
+local function midrange_mean(x)
+  local sump = 0
+  return 0.5 * (math.min(unpack(x)) + math.max(unpack(x)))
+end
+
+-- Calculates the energetic mean of a set of values
+-- x       : an array of values
+-- returns : the energetic mean
+local function energetic_mean(x)
+  local s = 0
+  for _,v in ipairs(x) do s = s + (10 ^ (v / 10)) end
+  return 10 * math.log10((1 / #x) * s)
+end
+
+return {
+  arithmetic     = arithmetic_mean,
+  geometric      = geometric_mean,
+  harmonic       = harmonic_mean,
+  quadratic      = quadratic_mean,
+  generalized    = generalized_mean,
+  weighted       = weighted_mean,
+  midrange       = midrange_mean,
+  energetic = energetic_mean,
+}
diff --git a/Average/Lua/Yonaba/average_test.lua b/Average/Lua/Yonaba/average_test.lua
@@ -0,0 +1,60 @@
+-- Tests for average.lua
+local mean = require 'average'
+
+local total, pass = 0, 0
+
+local function dec(str, len)
+  return #str < len
+     and str .. (('.'):rep(len-#str))
+      or str:sub(1,len)
+end
+
+local function run(message, f)
+  total = total + 1
+  local ok, err = pcall(f)
+  if ok then pass = pass + 1 end
+  local status = ok and 'PASSED' or 'FAILED'
+  print(('%02d. %68s: %s'):format(total, dec(message,68), status))
+end
+
+local function fuzzyEqual(a, b, eps) return math.abs(a - b) < eps end
+local x = {1, 2, 3, 4, 5}  
+
+run('Arithmetic mean', function()
+  assert(mean.arithmetic(x) == 3)
+end)
+
+run('Geometric mean', function()
+  assert(fuzzyEqual(mean.geometric(x), 2.60517108,1e-8))
+end)
+
+run('Harmonic mean', function()
+  assert(fuzzyEqual(mean.harmonic(x), 2.18978102,1e-8))
+end)
+
+run('Quadratic mean', function()
+  assert(fuzzyEqual(mean.quadratic(x), 3.31662479,1e-8))
+end)
+
+run('Generalized mean', function()
+  assert(fuzzyEqual(mean.generalized(x,1), mean.arithmetic(x),1e-8))
+  assert(fuzzyEqual(mean.generalized(x,2), mean.quadratic(x),1e-8))
+  assert(fuzzyEqual(mean.generalized(x,-1), mean.harmonic(x),1e-8))
+end)
+
+run('Weighted mean', function()
+  local w = { 0.1, 0.2, 0.2, 0.3, 0.2}
+  assert(mean.weighted(x, w) == 3.3)
+end)
+
+run('Midrange mean', function()
+  assert(mean.midrange(x) == 3)
+end)
+
+run('Energetic mean', function()
+  assert(fuzzyEqual(mean.energetic(x), 3.22766781,1e-8))
+end)
+
+print(('-'):rep(80))
+print(('Total : %02d: Pass: %02d - Failed : %02d - Success: %.2f %%')
+  :format(total, pass, total-pass, (pass*100/total)))
