lbfgsb.rb in lbfgsb-0.2.0

- old
+ new
@@ -10,26 +10,36 @@
 
   # Minimize a function using the L-BFGS-B algorithm.
   #
   # @param fnc [Method/Proc] Method for calculating the function to be minimized.
   # @param x_init [Numo::DFloat] (shape: [n_elements]) Initial point.
-  # @param jcb [Method/Proc] Method for calculating the gradient vector.
+  # @param jcb [Method/Proc/Boolean] Method for calculating the gradient vector.
+  #   If true is given, fnc is assumed to return the function value and gardient vector as [f, g] array.
   # @param args [Object] Arguments pass to the 'fnc' and 'jcb'.
   # @param bounds [Numo::DFloat/Nil] (shape: [n_elements, 2])
   #   \[lower, upper\] bounds for each element x. If nil is given, x is unbounded.
   # @param factr [Float] The iteration will be stop when
   #
-  #   `(f^k - f^\{k+1\})/max{|f^k|,|f^\{k+1\}|,1} <= factr * Lbfgsb::DBL_EPSILON`
+  #   (f^k - f^\{k+1\})/max{|f^k|,|f^\{k+1\}|,1} <= factr * Lbfgsb::DBL_EPSILON
   #
   #   Typical values for factr: 1e12 for low accuracy; 1e7 for moderate accuracy; 1e1 for extremely high accuracy.
   # @param pgtol [Float] The iteration will be stop when
   #
-  #   `max{|pg_i| i = 1, ..., n} <= pgtol`
+  #   max{|pg_i| i = 1, ..., n} <= pgtol
   #
   #   where pg_i is the ith component of the projected gradient.
   # @param maxcor [Integer] The maximum number of variable metric corrections used to define the limited memory matrix.
   # @param maxiter [Integer] The maximum number of iterations.
   # @param verbose [Integer/Nil] If negative value or nil is given, no display output is generated.
+  # @return [Hash] Optimization results; { x:, n_fev:, n_jev:, n_iter:, fnc:, jcb:, task:, success: }
+  #   - x [Numo::DFloat] Updated vector by optimization.
+  #   - n_fev [Interger] Number of calls of the objective function.
+  #   - n_jev [Integer] Number of calls of the jacobian.
+  #   - n_iter [Integer] Number of iterations.
+  #   - fnc [Float] Value of the objective function.
+  #   - jcb [Numo::Narray] Values of the jacobian
+  #   - task [String] Description of the cause of the termination.
+  #   - success [Boolean] Whether or not the optimization exited successfully.
   def minimize(fnc:, x_init:, jcb:, args: nil, bounds: nil, factr: 1e7, pgtol: 1e-5, maxcor: 10, maxiter: 15_000, verbose: nil)
     n_elements = x_init.size
     l = Numo::DFloat.zeros(n_elements)
     u = Numo::DFloat.zeros(n_elements)
     nbd = Numo::Int64.zeros(n_elements)