Merge pull request #185 from suavecode/feature-optimizers_from_MF

Mulfi-fidelity Optimizers

trunk/SUAVE/Methods/Utilities/latin_hypercube_sampling.py

@@ -1,7 +1,7 @@
 # latin_hypercube_sampling.py
 #
 # Created:  Jul 2016, R. Fenrich (outside of SUAVE code)
-# Modified: Mar 2017, T. MacDonald
+# Modified: Apr 2017, T. MacDonald
 
 
 # ----------------------------------------------------------------------
@@ -18,7 +18,7 @@
 #   Latin Hypercube Sampling
 # ----------------------------------------------------------------------
 
-def latin_hypercube_sampling(num_dimensions,num_samples,criterion='random'):
+def latin_hypercube_sampling(num_dimensions,num_samples,bounds=None,criterion='random'):
 
     n = num_dimensions
     samples = num_samples
@@ -43,6 +43,11 @@ def latin_hypercube_sampling(num_dimensions,num_samples,criterion='random'):
 
     ## Map samples to the standard normal distribution (if needed for future functionality)
     #lhd = norm(loc=0,scale=1).ppf(lhd)
+
+    if bounds != None:
+        lower_bounds = bounds[0]
+        upper_bounds = bounds[1]
+        lhd = lhd*(upper_bounds-lower_bounds) + lower_bounds
 
     return lhd
 

trunk/SUAVE/Optimization/Nexus.py

@@ -1,7 +1,8 @@
 # Nexus.py
 # 
 # Created:  Jul 2015, E. Botero 
-# Modified: Feb 2015, M. Vegh
+# Modified: Feb 2016, M. Vegh
+#           Apr 2017, T. MacDonald
 
 # ----------------------------------------------------------------------
 #  Imports
@@ -29,14 +30,18 @@ def __defaults__(self):
         self.results                = SUAVE.Analyses.Results()
         self.summary                = Data()
         self.optimization_problem   = None
+        self.fidelity_level         = 1
         self.last_inputs            = None
+        self.last_fidelity          = None
         self.evaluation_count       = 0
 
     def evaluate(self,x = None):
 
         self.unpack_inputs(x)
-        # This function calls really_evaluate
-        if np.all(self.optimization_problem.inputs==self.last_inputs):
+
+        # Check if last call was the same
+        if np.all(self.optimization_problem.inputs==self.last_inputs) \
+           and self.last_fidelity == self.fidelity_level:
             pass
         else:
             self._really_evaluate()
@@ -56,7 +61,8 @@ def _really_evaluate(self):
             self = nexus
 
         # Store to cache
-        self.last_inputs = deepcopy(self.optimization_problem.inputs)
+        self.last_inputs   = deepcopy(self.optimization_problem.inputs)
+        self.last_fidelity = self.fidelity_level
 
 
     def objective(self,x = None):
@@ -155,7 +161,7 @@ def unpack_inputs(self,x = None):
     def constraints_individual(self,x = None):
         pass     
 
-    def finite_difference(self,x):
+    def finite_difference(self,x,diff_interval=1e-8):
 
         obj = self.objective(x)
         con = self.all_constraints(x)
@@ -173,14 +179,14 @@ def finite_difference(self,x):
 
         for ii in xrange(0,inplen):
             newx     = np.asarray(x)*1.0
-            newx[ii] = newx[ii]+ 1e-8
+            newx[ii] = newx[ii] + diff_interval
 
             grad_obj[ii]  = self.objective(newx)
             jac_con[ii,:] = self.all_constraints(newx)
 
-        grad_obj = (grad_obj - obj)/(1e-8)
+        grad_obj = (grad_obj - obj)/diff_interval
 
-        jac_con = (jac_con - con2).T/(1e-8)
+        jac_con = (jac_con - con2).T/diff_interval
 
         grad_obj = grad_obj.astype(float)
         jac_con  = jac_con.astype(float)

trunk/SUAVE/Optimization/Package_Setups/TRMM/TRMM_setup.py

@@ -0,0 +1,31 @@
+# TRMM_setup.py
+#
+# Created:  Apr 2017, T. MacDonald
+# Modified: 
+
+# ----------------------------------------------------------------------
+#  Imports
+# ----------------------------------------------------------------------
+
+# suave imports
+import numpy as np
+from SUAVE.Optimization import helper_functions as help_fun
+from SUAVE.Optimization.Package_Setups.TRMM import Trust_Region_Optimization as tro
+from SUAVE.Optimization.Package_Setups.TRMM.Trust_Region import Trust_Region
+
+# ----------------------------------------------------------------------
+#  TRMM_Solve
+# ----------------------------------------------------------------------
+
+def TRMM_Solve(problem,tr=None,tr_opt=None,print_output=False):
+
+    if tr == None:
+        tr = Trust_Region()
+    problem.trust_region = tr
+    if tr_opt == None:
+        TRM_opt = tro.Trust_Region_Optimization()
+    else:
+        TRM_opt = tr_opt
+    TRM_opt.optimize(problem,print_output=print_output)
+
+    return

trunk/SUAVE/Optimization/Package_Setups/TRMM/Trust_Region.py

@@ -0,0 +1,32 @@
+# Trust_Region.py
+#
+# Created:  Apr 2017, T. MacDonald
+# Modified: Jun 2017, T. MacDonald
+
+# ----------------------------------------------------------------------
+#  Imports
+# ----------------------------------------------------------------------
+
+import SUAVE
+from SUAVE.Core import Data
+
+# ----------------------------------------------------------------------
+#  Trust Region Class
+# ----------------------------------------------------------------------
+
+class Trust_Region(Data):
+
+    def __defaults__(self):
+
+        self.initial_size       = 0.05
+        self.size               = 0.05
+        self.minimum_size       = 1e-15
+        self.contract_threshold = 0.25
+        self.expand_threshold   = 0.75
+        self.contraction_factor = 0.25
+        self.expansion_factor   = 1.5
+
+
+    def evaluate_function(self,f,gviol):
+        phi = f + gviol**2
+        return phi