migrate

README.md

@@ -1,3 +1,5 @@
+**Migrated to <https://git.sceptique.eu/Sceptique/stats>**
+
 # stats
 
 An expressive implementation of statistical distributions.
@@ -10,7 +12,7 @@ Add this to your application's `shard.yml`:
 ```yaml
 dependencies:
   stats:
-    github: Nephos/stats
+    git: https://git.sceptique.eu/Sceptique/stats
 ```
 
 
@@ -92,6 +94,8 @@ Math.factorial(4) # => 24
 
 ### Quartiles & Boxplot
 
+*Note: not big compatible yet*
+
 ```crystal
 [1, 3, 5].first_quartile  # => 2.0 (alias of lower_quartile)
 [1, 3, 5].second_quartile # => 3.0 (alias of median)
@@ -118,9 +122,16 @@ arr.upper_fence(3)    # => 47.5 (Q3 + 3 * IQR)
 arr.upper_outliers(3) # => [1337]
 ```
 
+### Frequency
+
+```crystal
+[0, 1, 2, 3].frequency_of(0) # => 0.25 (amount of X in the population, by the size of the population)
+[0, 0, 1, 2, 3].all_frequencies # => { 0 => 0.4, 1 => 0.2, 2 => 0.2, 3 => 0.2}
+```
+
 ## Development
 
-- The lib is adapted to be usable with BigInt and BigFloat values
+- The lib should take care of "big" numbers
 
 ## Contributing
 

shard.yml

@@ -1,5 +1,5 @@
 name: stats
-version: 0.2.4
+version: 0.3.0
 
 authors:
   - Arthur Poulet <arthur.poulet@mailoo.org>

spec/math/correlation.cr

@@ -1,3 +1,5 @@
+require "big"
+
 describe Math::Correlation do
   it "test basic confidence interval" do
     arr1 = [1, 2, 2.5, 3, 3.5, 3.8, 4, 4.2, 4.4, 4.5]
@@ -9,4 +11,11 @@ describe Math::Correlation do
     arr1.covariance(arr2).round(4).should eq 4.2215
     arr1.correlation_coef(arr2).round(4).should eq 0.8906
   end
+
+  it "test big" do
+    [BigInt.new(1), 2].correlation_coef([2, 3])
+    [1, 2].correlation_coef([BigInt.new(2), 3])
+    [BigInt.new(1), 2].correlation_coef([BigInt.new(2), 3])
+    [1, 2].correlation_coef([BigInt.new(2), BigInt.new(3)])
+  end
 end

spec/math/factorial.cr

@@ -10,8 +10,8 @@ describe Math do
     Math.factorial(6).should eq 720
   end
 
-  it "factorial bigint" do
-    res = (1..20).to_a.reduce(BigInt.new 1) { |e, i| e * BigInt.new(i) }
-    Math.factorial(BigInt.new 20).should eq res
+  it "factorial big" do
+    res = (1..20).to_a.reduce(BigInt.new(1)) { |e, i| e * BigInt.new(i) }
+    Math.factorial(BigInt.new(20)).should eq res
   end
 end

spec/math/frequency.cr

@@ -0,0 +1,34 @@
+FREQ_LIMIT = 100
+
+describe Math::Frequency do
+  it "test trivia" do
+    ([] of Int32).frequency_of(0).should eq 0.0
+    [0, 1, 2, 3].frequency_of(0).should eq 0.25
+    [0, 0, 1, 2, 3].frequency_of(0).should eq 0.40
+    [0, 0, 1, 2, 3].all_frequencies.should eq({0 => 0.4, 1 => 0.2, 2 => 0.2, 3 => 0.2})
+    # allfreq1 = [0, 0, 1, 2, 3].all_frequencies(2)
+    # allfreq1[1].should eq 0.4
+    # allfreq1.size.should eq 2
+    # expect_raises(Error) { [0, 0, 1, 2, 3].all_frequencies(2, true) }
+  end
+
+  it "test basic" do
+    FREQ_LIMIT.times do |modi|
+      modulo = modi + 1
+      # we should have the same or more because we don't / modulo in the freq
+      arr = FREQ_LIMIT.times.to_a.map { |e| e % modulo }
+      (arr.frequency_of(0) >= (1.0f64 / modulo)).should be_true
+
+      next if modulo <= 20
+      # make an array with less or equal amount of iterations
+      arr_less = FREQ_LIMIT.times.to_a.map { |e| e % (modulo + 5) }
+      (arr.frequency_of(0) >= arr_less.frequency_of(0)).should be_true
+
+      # make an array with more or equal amount of iterations
+      arr_more = FREQ_LIMIT.times.to_a.map { |e| e % (modulo - 5) }
+      (arr.frequency_of(0) <= arr_more.frequency_of(0)).should be_true
+    end
+
+    [0, 0, 0, 0, 1, 1, 1, 2, 2, 3].all_frequencies.should eq({0 => 0.4, 1 => 0.3, 2 => 0.2, 3 => 0.1})
+  end
+end

spec/math/macd.cr

@@ -1,5 +1,11 @@
+require "big"
+
 describe Math::MACD do
   it "test basic macd" do
     [1, 2, 3, 2, 1].macd(3).map { |e| e.round(3) }.should eq [2, 2.333, 2]
   end
+
+  it "test big basic macd" do
+    puts [BigInt.new(1), BigInt.new(2), BigInt.new(3), BigInt.new(2), 1].macd(3).map { |e| e.round(3) }.should eq [2, 2.333, 2]
+  end
 end

spec/math/mean.cr

@@ -1,3 +1,5 @@
+require "big"
+
 describe Math::Mean do
   it "test several basic mean special case" do
     arr = ([] of Int32)
@@ -17,6 +19,11 @@ describe Math::Mean do
     [1, 2, -3].mean.should eq 0.0
   end
 
+  it "test mean on big" do
+    [BigInt.new(1), 2, 3].mean.should eq 2.0
+    [BigInt.new(1), BigInt.new(2), BigFloat.new(-3)].mean.should eq 0.0
+  end
+
   it "test quadratic mean" do
     [1, 2, 3, 2].quadratic_mean.round(4).should eq(2.1213)
     [1, 2, 1, 5, 10, 9, 1, -13, 2].quadratic_mean.round(4).should eq(6.549)

spec/math/median.cr

@@ -1,6 +1,8 @@
+require "big"
+
 describe Math::Median do
   it "test trivia" do
-    arr = ([]of Int32)
+    arr = ([] of Int32)
     arr.median.should eq 0.0
   end
 
@@ -10,7 +12,12 @@ describe Math::Median do
 
     [1, 2, 5].median.should eq 2.0
     [2, 5, 1].median.should eq 2.0
-    
+
     [4, 1, 1, 1, 2].median.should eq 1.0
   end
+
+  it "test big" do
+    [BigInt.new(1.0), 2.0].median.should eq 1.5
+    [BigInt.new(1.0), BigFloat.new(2.0)].median.should eq 1.5
+  end
 end

spec/math/quartile.cr

@@ -1,3 +1,5 @@
+require "big"
+
 module Math::Quartile
   it "trivial" do
     arr = [1, 3, 5]
@@ -11,6 +13,19 @@ module Math::Quartile
     arr.iqr.should eq 2.0
   end
 
+  # TODO
+  # it "big" do
+  #   arr = [BigInt.new(1), BigFloat.new(3), 5]
+  #
+  #   arr.first_quartile.should eq 2.0
+  #   arr.second_quartile.should eq 3.0
+  #   arr.third_quartile.should eq 4.0
+  #
+  #   arr.quartiles.should eq [2.0, 3.0, 4.0]
+  #
+  #   arr.iqr.should eq 2.0
+  # end
+
   it "odd size input" do
     arr = [6, 7, 15, 36, 39, 40, 41, 42, 43, 47, 49]
 
@@ -79,6 +94,5 @@ module Math::Quartile
 
     arr.upper_fence(3).should eq 47.5
     arr.upper_outliers(3).should eq [1337]
-
   end
 end

spec/math/standard_deviation.cr

@@ -9,6 +9,16 @@ describe Math::StandardDeviation do
     arr.standard_deviation.should eq(standard_deviation)
   end
 
+  it "test big" do
+    arr = [BigInt.new(1), BigFloat.new(2), 3, 4.0, 4]
+    mean = (4 + 4 + 3 + 2 + 1) / 5.0
+    variance = ((4 - mean)**2 + (4 - mean)**2 + (3 - mean)**2 + (2 - mean)**2 + (1 - mean)**2) / 5.0
+    standard_deviation = Math.sqrt(variance)
+    arr.mean.should eq(mean)
+    arr.variance.should eq(variance)
+    arr.standard_deviation.should eq(standard_deviation)
+  end
+
   it "test standard deviation without explanations" do
     arr = [1, 5, 23, 2, 0, 0, 1]
     arr.mean.round(2).should eq 4.57

src/lib/math/frequency.cr

@@ -0,0 +1,18 @@
+module Math::Frequency(T)
+  def frequency_of(value : T) : Float64
+    return 0.0f64 if empty?
+    count { |curr| curr == value }.to_f64 / size.to_f64
+  end
+
+  def all_frequencies : Hash(T, Float64)
+    values = to_set
+    frequencies = Hash(T, Float64).new(0.0f64, values.size)
+    each { |value| frequencies[value] += 1 }
+    frequencies.each { |k, _| frequencies[k] = frequencies[k] / size }
+    frequencies
+  end
+end
+
+module Enumerable(T)
+  include Math::Frequency(T)
+end

src/lib/math/mean.cr

@@ -1,14 +1,14 @@
 module Math::Mean
   # Standard arithmetic mean
   # TODO: Handle big Float/Int
-  def mean : Float64
+  def mean
     return 0.0_f64 if empty?
     sum.to_f64 / size.to_f64
   end
 
   # The root square mean of the list.
   # TODO: Handle big Float/Int
-  def quadratic_mean : Float64
+  def quadratic_mean
     return 0.0_f64 if empty?
     Math.sqrt map { |e| e ** 2 }.mean
   end
@@ -16,14 +16,14 @@ module Math::Mean
   # The geometric mean of the list.
   # For [a, b], a/c = c/b; c**2 = a*b
   # TODO: Handle big Float/Int
-  def geometric_mean : Float64
+  def geometric_mean
     return 0.0_f64 if empty?
     reduce { |l, r| l * r } ** (1.0 / size.to_f64)
   end
 
   # The harmonic mean of the list.
   # TODO: Handle big Float/Int
-  def harmonic_mean : Float64
+  def harmonic_mean
     return 0.0_f64 if empty?
     size.to_f64 / map { |e| 1.0 / e }.sum
   end

src/lib/math/median.cr

@@ -1,9 +1,9 @@
 module Math::Median
-  def median : Float64
+  def median
     return 0.0_f64 if empty?
     sorted = sort
     size = size()
-    return sorted[(size - 1)  / 2].to_f64 if size.odd?
+    return sorted[(size - 1) / 2] / 1.0 if size.odd?
     (sorted[(size / 2) - 1] + sorted[size / 2]) / 2.0
   end
 end

src/lib/math/quartile.cr

@@ -1,5 +1,5 @@
 # There are several methods for computing the quartiles of an array.
-# 
+#
 # This library utilizes the method proposed by John Tukey
 # https://en.wikipedia.org/wiki/Quartile#Method_2
 #

src/stats/version.cr

@@ -1,3 +1,3 @@
 module Stats
-  VERSION = "0.2"
+  VERSION = "0.3"
 end