lib/mopti/scaled_conjugate_gradient.rb in mopti-0.1.0 vs lib/mopti/scaled_conjugate_gradient.rb in mopti-0.2.0

@@ -40,11 +40,11 @@
   #   #  :n_iter=>9,
   #   #  :fnc=>1.6170212789006122,
   #   #  :jcb=>1.8698188678645777e-07}
   #
   # *Reference*
-  # 1. M F. Moller, "A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning," Neural Networks, Vol. 6, pp. 525--533, 1993.
+  # 1. Moller, M F., "A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning," Neural Networks, Vol. 6, pp. 525--533, 1993.
   class ScaledConjugateGradient
     include Enumerable
 
     # Create a new optimizer with scaled conjugate gradient.
     #
@@ -54,11 +54,11 @@
     # @param x_init [Numo::NArray] Initial point.
     # @param max_iter [Integer] Maximum number of iterations.
     # @param xtol [Float] Tolerance for termination for the optimal vector norm.
     # @param ftol [Float] Tolerance for termination for the objective function value.
     # @param jtol [Float] Tolerance for termination for the gradient norm.
-    def initialize(fnc:, jcb:, args: nil, x_init:, max_iter: 200, xtol: 1e-6, ftol: 1e-8, jtol: 1e-7)
+    def initialize(fnc:, jcb:, x_init:, args: nil, max_iter: 200, xtol: 1e-6, ftol: 1e-8, jtol: 1e-7)
       @fnc = fnc
       @jcb = jcb
       @x_init = x_init
       @args = args
       @max_iter = max_iter
@@ -80,14 +80,14 @@
     # @return [Enumerator] If block is not given, this method returns Enumerator.
     def each
       return to_enum(__method__) unless block_given?
 
       x = @x_init
-      f_prev = func(x)
+      f_prev = func(x, @args)
       n_fev = 1
       f_curr = f_prev
-      j_next = jacb(x)
+      j_next = jacb(x, @args)
       n_jev = 1
 
       j_curr = j_next.dot(j_next)
       j_prev = j_next.dup
       d = -j_next
@@ -107,24 +107,27 @@
           kappa = d.dot(d)
           break if kappa < 1e-16
 
           sigma = SIGMA_INIT / Math.sqrt(kappa)
           x_plus = x + sigma * d
-          j_plus = jacb(x_plus)
+          j_plus = jacb(x_plus, @args)
           n_jev += 1
           theta = d.dot(j_plus - j_next) / sigma
         end
 
         delta = theta + beta * kappa
         if delta <= 0
           delta = beta * kappa
-          beta -= theta / kappa
+          # TODO: Investigate the cause of the type error.
+          # Cannot assign a value of type `::Complex` to a variable of type `::Float`
+          # beta -= theta / kappa
+          beta = (beta - (theta / kappa)).to_f
         end
         alpha = -mu / delta
 
         x_next = x + alpha * d
-        f_next = func(x_next)
+        f_next = func(x_next, @args)
         n_fev += 1
 
         delta = 2 * (f_next - f_prev) / (alpha * mu)
         if delta >= 0
           success = true
@@ -144,19 +147,19 @@
           break if (alpha * d).abs.max < @xtol
 
           f_prev = f_next
 
           j_prev = j_next
-          j_next = jacb(x)
+          j_next = jacb(x, @args)
           n_jev += 1
 
           j_curr = j_next.dot(j_next)
           break if j_curr <= @jtol
         end
 
-        beta = [beta * 4, BETA_MAX].min if delta < 0.25
-        beta = [beta / 4, BETA_MIN].max if delta > 0.75
+        beta = beta * 4 < BETA_MAX ? beta * 4 : BETA_MAX if delta < 0.25
+        beta = beta / 4 > BETA_MIN ? beta / 4 : BETA_MIN if delta > 0.75
 
         if n_successes == x.size
           d = -j_next
           beta = 1.0
           n_successes = 0
@@ -173,30 +176,30 @@
 
     private_constant :SIGMA_INIT, :BETA_MIN, :BETA_MAX
 
     private
 
-    def func(x)
-      if @args.is_a?(Hash)
-        @fnc.call(x, **@args)
-      elsif @args.is_a?(Array)
-        @fnc.call(x, *@args)
-      elsif @args.nil?
+    def func(x, args)
+      if args.is_a?(Hash)
+        @fnc.call(x, **args)
+      elsif args.is_a?(Array)
+        @fnc.call(x, *args)
+      elsif args.nil?
         @fnc.call(x)
       else
-        @fnc.call(x, @args)
+        @fnc.call(x, args)
       end
     end
 
-    def jacb(x)
-      if @args.is_a?(Hash)
-        @jcb.call(x, **@args)
-      elsif @args.is_a?(Array)
-        @jcb.call(x, *@args)
-      elsif @args.nil?
+    def jacb(x, args)
+      if args.is_a?(Hash)
+        @jcb.call(x, **args)
+      elsif args.is_a?(Array)
+        @jcb.call(x, *args)
+      elsif args.nil?
         @jcb.call(x)
       else
-        @jcb.call(x, @args)
+        @jcb.call(x, args)
       end
     end
   end
 end