22064487714

Committed 16 Feb 2026 01:24PM UTC coverage: 66.773% (-1.0%) from 67.817%

Build # 22064487714

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thouska

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/src/spotpy/examples/spot_setup_hymod_python.py

"""
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
import datetime as dt


class spot_setup(object):
    cmax = Uniform(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(dt.datetime.strptime(str(values[0]), '%d.%m.%Y'))
            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

1	"""
2	Copyright 2015 by Tobias Houska
3	This file is part of Statistical Parameter Estimation Tool (SPOTPY).
4
5	:author: Tobias Houska
6
7	This example implements the python version of hymod into SPOTPY.
8	"""
9
10	import os	3✔
11
12	from spotpy.examples.hymod_python.hymod import hymod	3✔
13	from spotpy.objectivefunctions import rmse	3✔
14	from spotpy.parameter import Uniform	3✔
15	import datetime as dt	3✔
16
17
18	class spot_setup(object):	3✔
19	cmax = Uniform(low=1.0, high=500, optguess=412.33)	3✔
20	bexp = Uniform(low=0.1, high=2.0, optguess=0.1725)	3✔
21	alpha = Uniform(low=0.1, high=0.99, optguess=0.8127)	3✔
22	Ks = Uniform(low=0.001, high=0.10, optguess=0.0404)	3✔
23	Kq = Uniform(low=0.1, high=0.99, optguess=0.5592)	3✔
24	# fake1 =spotpy.parameter.Uniform(low=0.1 , high=10, optguess=0.5592)
25	# fake2 =spotpy.parameter.Uniform(low=0.1 , high=10, optguess=0.5592)
26
27	def __init__(self, obj_func=None):	3✔
28	# Just a way to keep this example flexible and applicable to various examples
29	self.obj_func = obj_func	3✔
30	# Transform [mm/day] into [l s-1], where 1.783 is the catchment area
31	self.Factor = 1.783 * 1000 * 1000 / (60 * 60 * 24)	3✔
32	# Load Observation data from file
33	self.PET, self.Precip = [], []	3✔
34	self.date, self.trueObs = [], []	3✔
35	# Find Path to Hymod on users system
36	self.owd = os.path.dirname(os.path.realpath(__file__))	3✔
37	self.hymod_path = self.owd + os.sep + "hymod_python"	3✔
38	climatefile = open(self.hymod_path + os.sep + "hymod_input.csv", "r")	3✔
39	headerline = climatefile.readline()[:-1]	3✔
40
41	# Read model forcing in working storage (this is done only ones)
42	if ";" in headerline:	3✔
43	self.delimiter = ";"	3✔
44	else:
45	self.delimiter = ","	×
46	self.header = headerline.split(self.delimiter)	3✔
47	for line in climatefile:	3✔
48	values = line.strip().split(self.delimiter)	3✔
49	self.date.append(dt.datetime.strptime(str(values[0]), '%d.%m.%Y'))	3✔
50	self.Precip.append(float(values[1]))	3✔
51	self.PET.append(float(values[2]))	3✔
52	self.trueObs.append(float(values[3]))	3✔
53	climatefile.close()	3✔
54
55	def simulation(self, x):	3✔
56	# Here the model is actualy startet with one paramter combination
57	data = hymod(self.Precip, self.PET, x[0], x[1], x[2], x[3], x[4])	3✔
58	sim = []	3✔
59	for val in data:	3✔
60	sim.append(val * self.Factor)	3✔
61	# The first year of simulation data is ignored (warm-up)
62	return sim[366:]	3✔
63
64	def evaluation(self):	3✔
65	return self.trueObs[366:]	3✔
66
67	def objectivefunction(self, simulation, evaluation, params=None):	3✔
68	# SPOTPY expects to get one or multiple values back,
69	# that define the performance of the model run
70	if not self.obj_func:	3✔
71	# This is used if not overwritten by user
72	like = rmse(evaluation, simulation)	3✔
73	else:
74	# Way to ensure flexible spot setup class
75	like = self.obj_func(evaluation, simulation)	3✔
76	return like	3✔

thouska / spotpy / 22064487714

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