Add exmaple for loguniform use #297

src/spotpy/examples/spot_setup_hymod_python_loguniform.py

@@ -0,0 +1,76 @@
+"""
+Copyright 2015 by Tobias Houska
+This file is part of Statistical Parameter Estimation Tool (SPOTPY).
+
+:author: Tobias Houska
+
+This example implements the python version of hymod into SPOTPY.
+"""
+
+
+import os
+
+from spotpy.examples.hymod_python.hymod import hymod
+from spotpy.objectivefunctions import rmse
+from spotpy.parameter import Uniform, Loguniform
+
+
+class spot_setup(object):
+    cmax = Loguniform(low=1.0, high=500, optguess=412.33)
+    bexp = Uniform(low=0.1, high=2.0, optguess=0.1725)
+    alpha = Uniform(low=0.1, high=0.99, optguess=0.8127)
+    Ks = Uniform(low=0.001, high=0.10, optguess=0.0404)
+    Kq = Uniform(low=0.1, high=0.99, optguess=0.5592)
+    # fake1 =spotpy.parameter.Uniform(low=0.1 , high=10, optguess=0.5592)
+    # fake2 =spotpy.parameter.Uniform(low=0.1 , high=10, optguess=0.5592)
+
+    def __init__(self, obj_func=None):
+        # Just a way to keep this example flexible and applicable to various examples
+        self.obj_func = obj_func
+        # Transform [mm/day] into [l s-1], where 1.783 is the catchment area
+        self.Factor = 1.783 * 1000 * 1000 / (60 * 60 * 24)
+        # Load Observation data from file
+        self.PET, self.Precip = [], []
+        self.date, self.trueObs = [], []
+        # Find Path to Hymod on users system
+        self.owd = os.path.dirname(os.path.realpath(__file__))
+        self.hymod_path = self.owd + os.sep + "hymod_python"
+        climatefile = open(self.hymod_path + os.sep + "hymod_input.csv", "r")
+        headerline = climatefile.readline()[:-1]
+
+        # Read model forcing in working storage (this is done only ones)
+        if ";" in headerline:
+            self.delimiter = ";"
+        else:
+            self.delimiter = ","
+        self.header = headerline.split(self.delimiter)
+        for line in climatefile:
+            values = line.strip().split(self.delimiter)
+            self.date.append(str(values[0]))
+            self.Precip.append(float(values[1]))
+            self.PET.append(float(values[2]))
+            self.trueObs.append(float(values[3]))
+        climatefile.close()
+
+    def simulation(self, x):
+        # Here the model is actualy startet with one paramter combination
+        data = hymod(self.Precip, self.PET, x[0], x[1], x[2], x[3], x[4])
+        sim = []
+        for val in data:
+            sim.append(val * self.Factor)
+        # The first year of simulation data is ignored (warm-up)
+        return sim[366:]
+
+    def evaluation(self):
+        return self.trueObs[366:]
+
+    def objectivefunction(self, simulation, evaluation, params=None):
+        # SPOTPY expects to get one or multiple values back,
+        # that define the performance of the model run
+        if not self.obj_func:
+            # This is used if not overwritten by user
+            like = rmse(evaluation, simulation)
+        else:
+            # Way to ensure flexible spot setup class
+            like = self.obj_func(evaluation, simulation)
+        return like

tutorials/tutorial_sceua_hymod.py

@@ -12,7 +12,7 @@
 import numpy as np
 
 import spotpy
-from spotpy.examples.spot_setup_hymod_python import spot_setup
+from spotpy.examples.spot_setup_hymod_python_loguniform import spot_setup
 
 if __name__ == "__main__":
     parallel = "seq"  # Runs everthing in sequential mode