fix parameter running out of bounds causes by wrong index

spotpy/algorithms/dds.py

@@ -396,9 +396,9 @@ def calculate_next_s_test(self, previous_x_curr, rep, rep_limit, r):
                 new_x_curr[j] = new_value  # change relevant dec var value in x_curr
 
         if dvn_count == 0:  # no DVs selected at random, so select ONE
-            dec_var = np.int(np.ceil(amount_params * self.np_random.rand()))
-            new_value = self.dds_generator.neigh_value_mixed(previous_x_curr, r, dec_var - 1, self.min_bound[j],self.max_bound[j])
-
-            new_x_curr[dec_var - 1] = new_value  # change relevant decision variable value in s_test
+            dec_var = np.int(np.ceil(amount_params * self.np_random.rand())) - 1
+            new_value = self.dds_generator.neigh_value_mixed(previous_x_curr, r, dec_var, self.min_bound[dec_var],
+                                                             self.max_bound[dec_var])
+            new_x_curr[dec_var] = new_value  # change relevant decision variable value in s_test
 
         return new_x_curr

spotpy/algorithms/padds.py

@@ -305,11 +305,10 @@ def calculate_next_s_test(self, previous_x_curr, rep, rep_limit, r):
                 new_x_curr[j] = new_value  # change relevant dec var value in x_curr
 
         if dvn_count == 0:  # no DVs selected at random, so select ONE
-            dec_var = np.int(np.ceil(amount_params * self.np_random.rand()))
-            new_value = self.dds_generator.neigh_value_mixed(previous_x_curr, r, dec_var - 1,  self.min_bound[j],self.max_bound[j])
-
-            new_x_curr[dec_var - 1] = new_value  # change relevant decision variable value in s_test
-
+            dec_var = np.int(np.ceil(amount_params * self.np_random.rand())) - 1
+            new_value = self.dds_generator.neigh_value_mixed(previous_x_curr, r, dec_var, self.min_bound[dec_var],
+                                                             self.max_bound[dec_var])
+            new_x_curr[dec_var] = new_value  # change relevant decision variable value in s_test
         return new_x_curr
 
 

spotpy/examples/spot_setup_dds.py

@@ -53,6 +53,21 @@ def _objfunc_switcher(self, name):
                            for j in range(2)] + [Uniform('c' + str(j), -500, 700, 1.5, 3.0, -500, 700,
                                                          doc=str(j) + 'continuous parameter within a boundary')
                                                  for j in range(8)]
+        elif name == "cmf_style":
+            self.objfunc = ackley10
+            self.params = [Uniform(.5, 5., optguess=1.5, doc='saturated depth at beginning'),
+                           Uniform(.001, .8, optguess=.1, doc='porosity of matrix [m3 Pores / m3 Soil]'),
+                           Uniform(1., 240., optguess=10.,
+                                   doc='ssaturated conductivity of macropores [m/day]'),
+                           Uniform(.0001, .5, optguess=.05, doc='macropore fraction [m3/m3]'),
+                           Uniform(.005, 1., optguess=.05,
+                                   doc='mean distance between the macropores [m]'),
+                           Uniform(0., 1., optguess=0.,
+                                   doc='water content when matric potential pointing towards -infinity'),
+                           Uniform(.5, 1., optguess=.99,
+                                   doc='wetness above which the parabolic extrapolation is used instead of VGM'),
+                           Uniform(0., 50, optguess=.1,
+                                   doc='exchange rate [1/day] for macropore-matrix-exchange')]
 
     def parameters(self):
         if self.params is None:

spotpy/examples/tutorial_padds.py

@@ -1,6 +1,7 @@
 # -*- coding: utf-8 -*-
 import numpy as np
 import sys
+from spotpy.parameter import Uniform
 try:
     import spotpy
 except ModuleNotFoundError:
@@ -48,10 +49,27 @@ def ZDT1(x):
 
 
 class padds_spot_setup(object):
-    def __init__(self):
+    def __init__(self, default=True):
         self.params = []
-        for i in range(30):
-            self.params.append(spotpy.parameter.Uniform(str(i+1), 0, 1, 0, 0, 0, 1,doc="param no " + str(i+1)))
+        if default:
+            for i in range(30):
+                self.params.append(spotpy.parameter.Uniform(str(i+1), 0, 1, 0, 0, 0, 1,doc="param no " + str(i+1)))
+        else:
+            self.params = [Uniform(.5, 5., optguess=1.5, doc='saturated depth at beginning'),
+                           Uniform(.001, .8, optguess=.1, doc='porosity of matrix [m3 Pores / m3 Soil]'),
+                           Uniform(1., 240., optguess=10.,
+                                   doc='ssaturated conductivity of macropores [m/day]'),
+                           Uniform(.0001, .5, optguess=.05, doc='macropore fraction [m3/m3]'),
+                           Uniform(.005, 1., optguess=.05,
+                                   doc='mean distance between the macropores [m]'),
+                           Uniform(0., 1., optguess=0.,
+                                   doc='water content when matric potential pointing towards -infinity'),
+                           Uniform(.5, 1., optguess=.99,
+                                   doc='wetness above which the parabolic extrapolation is used instead of VGM'),
+                           Uniform(0., 50, optguess=.1,
+                                   doc='exchange rate [1/day] for macropore-matrix-exchange')]
+            for i in range(8,30):
+                self.params.append(Uniform(str(i+1), 0, 1, 0, 0, 0, 1,doc="param no " + str(i+1)))
 
     def parameters(self):
 

tests/test_dds.py

@@ -126,6 +126,24 @@ def test_run_own_initial_1(self):
     def test_run_own_initial_2(self):
         self.run_a_dds("own_input_2")
 
+    def outside_bound(self, x_curr, min_bound, max_bound):
+        out_left = min_bound > x_curr  # [x<x_curr self.min_bound, self.max_bound
+        out_right = max_bound < x_curr
+
+        self.assertNotIn(True, out_right)
+        self.assertNotIn(True, out_left)
+
+    def test_bounds(self):
+        self.spot_setup._objfunc_switcher("cmf_style")
+        sampler = spotpy.algorithms.dds(self.spot_setup, parallel="seq", dbname='test_DDS', dbformat="csv",
+                                        sim_timeout=self.timeout)
+        sampler._set_np_random(self.f_random)
+
+        results = sampler.sample(1000,1)
+        print("results",results[0]['sbest'])
+        print(sampler.min_bound, sampler.max_bound)
+        self.outside_bound(results[0]['sbest'], sampler.min_bound, sampler.max_bound)
+
     def run_a_dds(self, run):
         original_result = self.json_helper(run)
 

tests/test_padds.py

@@ -61,6 +61,22 @@ def test_run_8(self):
     def test_run_9(self):
         self.run_a_dds(9)
 
+    def outside_bound(self, x_curr, min_bound, max_bound):
+        out_left = min_bound > x_curr  # [x<x_curr self.min_bound, self.max_bound
+        out_right = max_bound < x_curr
+
+        self.assertNotIn(True, out_right)
+        self.assertNotIn(True, out_left)
+
+    def test_bounds(self):
+        self.spot_setup = padds_spot_setup(False)
+        sampler = spotpy.algorithms.padds(self.spot_setup, parallel="seq", dbname='test_DDS', dbformat="csv",
+                                        sim_timeout=self.timeout)
+        sampler._set_np_random(self.f_random)
+        results = sampler.sample(100, 1)
+
+        self.outside_bound(results[0]['sbest'], sampler.min_bound, sampler.max_bound)
+
     def test_chc(self):
         self.assertArrayEqual([0.01851852, 0. , 0.01851852, 0.01851852, 0.,0.01851852],
                               chc([[1,10], [2,9.8],[3,5] ,[4, 4], [8,2], [10,1]]))