Fix for #213

spotpy/analyser.py

@@ -596,46 +596,35 @@ def plot_objectivefunction(results,evaluation,limit=None,sort=True, fig_name = '
         plt.plot(bestlike)
     plt.savefig(fig_name)
 
-def plot_parametertrace_algorithms(results,algorithmnames=None,parameternames=None, fig_name='parametertrace_algorithms.png'):
+def plot_parametertrace_algorithms(result_lists, algorithmnames, spot_setup, 
+                                   fig_name='parametertrace_algorithms.png'):
     """Example Plot as seen in the SPOTPY Documentation"""
     import matplotlib.pyplot as plt
     font = {'family' : 'calibri',
         'weight' : 'normal',
         'size'   : 20}
     plt.rc('font', **font)
     fig=plt.figure(figsize=(17,5))
-    subplots=len(results)
-    rows=2
+    subplots=len(result_lists)
+    parameter = spotpy.parameter.get_parameters_array(spot_setup)
+    rows=len(parameter['name'])
     for j in range(rows):
         for i in range(subplots):
             ax  = plt.subplot(rows,subplots,i+1+j*subplots)
-            if j==0:
-                if parameternames:
-                    data=results[i]['par'+parameternames[0]]
-                else:
-                    data=results[i]['par0']
-            if j==1:
-                if parameternames:
-                    data=results[i]['par'+parameternames[1]]
-                else:
-                    data=results[i]['par1']
-                ax.set_xlabel(algorithmnames[i-subplots])
-
+            data=result_lists[i]['par'+parameter['name'][j]]
             ax.plot(data,'b-')
-            ax.set_ylim(-50,50)
-            if i==0 and j==0:
-                ax.set_ylabel('x')
-                ax.yaxis.set_ticks([-50,0,50])
+            if i==0:
+                ax.set_ylabel(parameter['name'][j])
                 rep = len(data)
-            if i==0 and j==1:
-                ax.set_ylabel('y')
-                ax.yaxis.set_ticks([-50,0,50])
-            if j==0:
-                ax.xaxis.set_ticks([])
             if i>0:
                 ax.yaxis.set_ticks([])
+            if j==rows-1:
+                ax.set_xlabel(algorithmnames[i-subplots])
+            else:
+                ax.xaxis.set_ticks([])
             ax.plot([1]*rep,'r--')
             ax.set_xlim(0,rep)
+            ax.set_ylim(parameter['minbound'][j],parameter['maxbound'][j])
 
     #plt.tight_layout()
     fig.savefig(fig_name, bbox_inches='tight')

spotpy/examples/spot_setup_rosenbrock.py

@@ -12,7 +12,7 @@
 import numpy as np
 
 from spotpy.parameter import Uniform
-from spotpy.objectivefunctions import rmse
+from spotpy.objectivefunctions import rmse, log_p
 
 class spot_setup(object):
     """
@@ -23,7 +23,8 @@ class spot_setup(object):
     x = Uniform(-10, 10, 1.5, 3.0, -10, 10, doc='x value of Rosenbrock function')
     y = Uniform(-10, 10, 1.5, 3.0, -10, 10, doc='y value of Rosenbrock function')
     z = Uniform(-10, 10, 1.5, 3.0, -10, 10, doc='z value of Rosenbrock function')
-
+    def __init__(self,used_algorithm='default'):
+        self.used_algorithm =used_algorithm
     def simulation(self, vector):
         x=np.array(vector)
         simulations= [sum(100.0 * (x[1:] - x[:-1] ** 2.0) ** 2.0 + (1 - x[:-1]) ** 2.0)]
@@ -34,5 +35,10 @@ def evaluation(self):
         return observations
 
     def objectivefunction(self, simulation, evaluation):
-        objectivefunction = rmse(evaluation=evaluation, simulation=simulation)
+        if self.used_algorithm == 'sceua':
+            objectivefunction = rmse(evaluation=evaluation, simulation=simulation)
+        elif self.used_algorithm == 'dream' or self.used_algorithm == 'demcz' or self.used_algorithm == 'mcmc':
+            objectivefunction = log_p(evaluation=evaluation, simulation=simulation)
+        elif self.used_algorithm == 'default':
+            objectivefunction = - rmse(evaluation=evaluation, simulation=simulation)
         return objectivefunction