Fixed thouska#175 and thouska#166 with extensive check to preserve th…

…e constants

in sceua and developed a number of tests to ensure the constants stays
constant in all samplers.

spotpy/algorithms/sceua.py

@@ -125,7 +125,7 @@ def simulate(self, id_params_tuple):
                 lcs.sort()
 
                 # Construct the simplex:
-                s = np.zeros((self.nps, self.nopt))
+
                 s = cx[lcs, :]
                 sf = cf[lcs]
 
@@ -188,7 +188,7 @@ def sample(self, repetitions, ngs=20, kstop=100, pcento=0.0000001, peps=0.000000
         self.bl, self.bu = self.parameter()['minbound'], self.parameter()[
             'maxbound']
         bound = self.bu - self.bl  # np.array
-        stochastic_parameters = bound != 0
+        self.stochastic_parameters = bound != 0
         if self.breakpoint == 'read' or self.breakpoint == 'readandwrite':
             data_frombreak = self.read_breakdata(self.dbname)
             icall = data_frombreak[0]
@@ -250,7 +250,7 @@ def sample(self, repetitions, ngs=20, kstop=100, pcento=0.0000001, peps=0.000000
 
         # Computes the normalized geometric range of the parameters
         gnrng = np.exp(
-            np.mean(np.log((np.max(x, axis=0) - np.min(x, axis=0)) / bound)))
+            np.mean(np.log((np.max(x[:, self.stochastic_parameters], axis=0) - np.min(x[:, self.stochastic_parameters], axis=0)) / bound[self.stochastic_parameters])))
 
         # Check for convergency;
         if icall >= repetitions:
@@ -294,7 +294,7 @@ def sample(self, repetitions, ngs=20, kstop=100, pcento=0.0000001, peps=0.000000
                                for rep in range(int(self.ngs)))
             for igs, likes, pars, sims, cx, cf, k1, k2 in self.repeat(param_generator):
                 icall += len(likes)
-                x[k2, stochastic_parameters] = cx[k1, stochastic_parameters]
+                x[k2, :] = cx[k1, :]
                 xf[k2] = cf[k1]
                 #print(len(likes))
                 for i in range(len(likes)):
@@ -336,7 +336,7 @@ def sample(self, repetitions, ngs=20, kstop=100, pcento=0.0000001, peps=0.000000
 
             # Computes the normalized geometric range of the parameters
             gnrng = np.exp(
-                np.mean(np.log((np.max(x, axis=0) - np.min(x, axis=0)) / bound)))
+                np.mean(np.log((np.max(x[:, self.stochastic_parameters], axis=0) - np.min(x[:, self.stochastic_parameters], axis=0)) / bound[self.stochastic_parameters])))
 
             # Check for convergency;
             if icall >= repetitions:
@@ -397,7 +397,7 @@ def _cceua(self, s, sf, icall):
             #   iviol = flag indicating if constraints are violated
             #         = 1 , yes
             #         = 0 , no
-
+        constant_parameters = np.invert(self.stochastic_parameters)
         self.nps, self.nopt = s.shape
         alpha = 1.0
         beta = 0.5
@@ -411,7 +411,7 @@ def _cceua(self, s, sf, icall):
 
         # Attempt a reflection point
         snew = ce + alpha * (ce - sw)
-
+        snew[constant_parameters] = sw[constant_parameters]
         # Check if is outside the bounds:
         ibound = 0
         s1 = snew - self.bl
@@ -440,6 +440,8 @@ def _cceua(self, s, sf, icall):
         # Reflection failed; now attempt a contraction point:
         if fnew > fw:
             snew = sw + beta * (ce - sw)
+            snew[constant_parameters] = sw[constant_parameters]
+
             simulations = self.model(snew)
             like = self.postprocessing(icall, snew, simulations, save=False)
 #            like = self.objectivefunction(

spotpy/unittests/test_list_and_constant_parameters_with_samplers.py

@@ -59,7 +59,7 @@ class RosenbrockWithList(Rosenbrock):
     x = parameter.Uniform(-10, 10, 1.5, 3.0, -10, 10, doc='x value of Rosenbrock function')
     y = parameter.Uniform(-10, 10, 1.5, 3.0, -10, 10, doc='y value of Rosenbrock function')
     z = parameter.Uniform(-10, 10, 1.5, 3.0, -10, 10, doc='z value of Rosenbrock function')
-    l = parameter.List(range(10), repeat=True)
+    l = parameter.List(np.arange(0, 10), repeat=True, doc='list parameter for testing')
 
 
 def get_all_samplers():
@@ -80,8 +80,7 @@ def sampler_with_constant(self, sampler_class):
         sampler_name = sampler_class.__name__
         print(sampler_name)
         sampler = sampler_class(self.setup, dbformat='ram', save_sim=False)
-        sampler.sample(100)
-        print(sampler.datawriter.ram[-1])
+        sampler.sample(1000)
         print('-' * 50)
         self.assertTrue(all(line[-2] == 0 for line in sampler.datawriter.ram),
                         msg='Parameter c == 0 not true in all lines')
@@ -126,7 +125,6 @@ def setUp(self):
         self.setup = RosenbrockWithList()
         print(spotpy.describe.setup(self.setup))
 
-
     def test_list_parameter(self):
 
         for sampler_name, sampler_class in get_all_samplers():