Add stats work for Ruby.

Author: skytreader

python/stat_runner.py

@@ -3,16 +3,20 @@
 import subprocess
 import sys
 
+def determine_runner(script_path):
+    dot_split = script_path.split(".")
+    return ["ruby", script_path] if dot_split[-1] == "rb" else ["python3", "-m", script_path]
+
 if __name__ == "__main__":
     if len(sys.argv) != 3:
-        print("Usage: python3 %s <script.package.path> <iters>" % __file__)
+        print("Usage: python3 %s <script.path> <iters>" % __file__)
         exit(1)
     else:
         running_sum = 0
         limit = int(sys.argv[2])
 
         for _ in range(limit):
-            out = subprocess.run(["python3", "-m", sys.argv[1]], stdout=subprocess.PIPE)
+            out = subprocess.run(determine_runner(sys.argv[1]), stdout=subprocess.PIPE)
             running_sum += float(out.stdout)
 
         print("Mean: %s" % (running_sum / limit))

python/stochastic/random_search.py

@@ -59,11 +59,11 @@ def search(search_space, max_iter, show_log=True):
 
     # algorithm configuration
     max_iter = 100
+    show_log = decide()
+    best = search(search_space, max_iter, show_log)
 
     # execute the algorithm
-    if decide():
-        best = search(search_space ,max_iter)
+    if show_log:
         print("Done. Best Solution: cost = " + str(best['cost']) + ", v = " + str(best['vector']))
     else:
-        best = search(search_space, max_iter, False)
         print(best["cost"])

src/algorithms/stochastic/random_search.rb

@@ -3,6 +3,7 @@
 # The Clever Algorithms Project: http://www.CleverAlgorithms.com
 # (c) Copyright 2010 Jason Brownlee. Some Rights Reserved. 
 # This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 2.5 Australia License.
+require_relative "../switch.rb"
 
 def objective_function(vector)
   return vector.inject(0) {|sum, x| sum + (x ** 2.0)}
@@ -14,14 +15,16 @@ def random_vector(minmax)
   end
 end
 
-def search(search_space, max_iter)
+def search(search_space, max_iter, show_log=true)
   best = nil
   max_iter.times do |iter|
     candidate = {}
     candidate[:vector] = random_vector(search_space)
     candidate[:cost] = objective_function(candidate[:vector])
     best = candidate if best.nil? or candidate[:cost] < best[:cost]
-    puts " > iteration=#{(iter+1)}, best=#{best[:cost]}"
+    if show_log
+      puts " > iteration=#{(iter+1)}, best=#{best[:cost]}"
+    end
   end
   return best
 end
@@ -32,7 +35,14 @@ def search(search_space, max_iter)
   search_space = Array.new(problem_size) {|i| [-5, +5]}
   # algorithm configuration
   max_iter = 100
+  show_log = decide()
   # execute the algorithm
-  best = search(search_space, max_iter)
-  puts "Done. Best Solution: c=#{best[:cost]}, v=#{best[:vector].inspect}"
+  best = search(search_space, max_iter, show_log)
+
+  if show_log
+    puts "Done. Best Solution: c=#{best[:cost]}, v=#{best[:vector].inspect}"
+  else
+    puts best[:cost]
+  end
+
 end