fixup Fit sigs

Author: rickhull

lib/compsci/fit.rb

@@ -20,7 +20,7 @@ def self.constant xs, ys
     #
 
     def self.best xs, ys
-      vals = []
+      vals = [0.0, 0.0, 0.0, :default]
       max_r2 = 0
       [:logarithmic, :linear, :exponential, :power].each { |fn|
         a, b, r2 = Fit.send(fn, xs, ys)
@@ -45,8 +45,7 @@ def self.best xs, ys
     #   sigma([1, 2, 3]) { |n| n ** 2 } # => 1 + 4 + 9 => 14
 
     def self.sigma enum, &block
-      enum = enum.map(&block) if block
-      enum.inject { |sum, n| sum + n }
+      (block ? enum.map(&block) : enum).sum
     end
 
     ##
@@ -76,7 +75,7 @@ def self.error xys, &blk
 
     def self.logarithmic xs, ys
       n     = xs.size
-      xys   = xs.zip(ys)
+      xys   = xs.zip(ys).take(n)
       slnx2 = sigma(xys) { |x, _| Math.log(x) ** 2 }
       slnx  = sigma(xys) { |x, _| Math.log(x)      }
       sylnx = sigma(xys) { |x, y| y * Math.log(x)  }

sig/fit.rbs

@@ -1,14 +1,28 @@
 module CompSci
   module Fit
-    def self.constant: (Array[Numeric] xs, Array[Numeric] ys) ->
-      Array[Numeric]
-    def self.best: (Array[Numeric] xs, Array[Numeric] ys) -> Array[untyped]
-    def self.sigma: (Enumerable enum) ?{ (?) -> Numeric } -> Numeric
-    def self.error: (untyped xys) { (untyped) -> untyped } -> untyped
-    def self.logarithmic: (untyped xs, untyped ys) -> ::Array[untyped]
-    def self.linear: (untyped xs, untyped ys) -> ::Array[untyped]
-    def self.exponential: (untyped xs, untyped ys) -> ::Array[untyped]
-    def self.power: (untyped xs, untyped ys) -> ::Array[untyped]
-    def self.predict: (untyped model, untyped a, untyped b, untyped x) -> untyped
+    def self.constant: (Array[Float | Integer] xs,
+                        Array[Float | Integer] ys) -> [Float, (Float | Integer)]
+    def self.best: (Array[Float | Integer] xs,
+                    Array[Float | Integer] ys) -> Array[Float | Symbol]
+
+    def self.sigma: (Array[Float | Integer] enum) ?{ (untyped) -> untyped } -> Float
+                  | (Array[[Float | Integer, Float | Integer]] enum) ?{ (untyped) -> untyped } -> Float
+		  | (Array[Array[Float | Integer]] enum) ?{ (untyped) -> untyped } -> Float
+		  | (Array[untyped] enum) ?{ (untyped) -> untyped } -> Float
+
+    def self.error: (Array[Float | Integer] xys) { (untyped) -> untyped } -> Float
+                  | (Array[[Float | Integer, Float | Integer]] xys) { (untyped) -> untyped } -> Float
+                  | (Array[Array[Float | Integer]] xys) { (untyped) -> untyped } -> Float
+                  | (Array[untyped] xys) { (untyped) -> untyped } -> Float
+
+    def self.logarithmic: (Array[Float | Integer] xs, Array[Float | Integer] ys) -> [Float, Float, Float]
+
+    def self.linear: (Array[Float | Integer] xs, Array[Float | Integer] ys) -> [Float, Float, Float]
+
+    def self.exponential: (Array[Float | Integer] xs, Array[Float | Integer] ys) -> [Float, Float, Float]
+
+    def self.power: (Array[Float | Integer] xs, Array[Float | Integer] ys) -> [Float, Float, Float]
+
+    def self.predict: (Symbol model, Float a, Float b, (Float | Integer) x) -> Float
   end
 end