15283517039

Committed 27 May 2025 07:01PM UTC coverage: 67.799% (+0.006%) from 67.793%

Build # 15283517039

Build Type

Pull #334

github

Committed by

web-flow

Commit Message

Merge 459e2938c into 47dd43fa1

Pull Request Pull Request #334: Typo adjustments, black formatting, drop Python 3.9, support Python 3.13

Run Details

24 of 99 new or added lines in 15 files covered. (24.24%)

14 existing lines in 8 files now uncovered.

3752 of 5534 relevant lines covered (67.8%)

2.03 hits per line

Source File
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0.0

/src/spotpy/examples/spot_setup_hymod_python_pareto.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

import numpy as np

import spotpy
from spotpy.examples.hymod_python.hymod import hymod


class spot_setup(object):
    cmax = spotpy.parameter.Uniform(low=1.0, high=500, optguess=412.33)
    bexp = spotpy.parameter.Uniform(low=0.1, high=2.0, optguess=0.1725)
    alpha = spotpy.parameter.Uniform(low=0.1, high=0.99, optguess=0.8127)
    Ks = spotpy.parameter.Uniform(low=0.0, high=0.10, optguess=0.0404)
    Kq = spotpy.parameter.Uniform(low=0.1, high=0.99, optguess=0.5592)

    def __init__(self):
        # 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 = [], []
        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]

        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):
        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)
        return sim[366:]

    def evaluation(self):
        return self.trueObs[366:]

    def objectivefunction(self, simulation, evaluation, params=None):
        return [
            -abs(spotpy.objectivefunctions.bias(evaluation, simulation)),
            spotpy.objectivefunctions.rsquared(evaluation, simulation),
            spotpy.objectivefunctions.nashsutcliffe(evaluation, simulation),
        ]

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
UNCOV 10	import os	×
11
12	import numpy as np	×
13
14	import spotpy	×
15	from spotpy.examples.hymod_python.hymod import hymod	×
16
17
18	class spot_setup(object):	×
19	cmax = spotpy.parameter.Uniform(low=1.0, high=500, optguess=412.33)	×
20	bexp = spotpy.parameter.Uniform(low=0.1, high=2.0, optguess=0.1725)	×
21	alpha = spotpy.parameter.Uniform(low=0.1, high=0.99, optguess=0.8127)	×
22	Ks = spotpy.parameter.Uniform(low=0.0, high=0.10, optguess=0.0404)	×
23	Kq = spotpy.parameter.Uniform(low=0.1, high=0.99, optguess=0.5592)	×
24
25	def __init__(self):	×
26	# Transform [mm/day] into [l s-1], where 1.783 is the catchment area
27	self.Factor = 1.783 * 1000 * 1000 / (60 * 60 * 24)	×
28	# Load Observation data from file
29	self.PET, self.Precip = [], []	×
30	self.date, self.trueObs = [], []	×
31	self.owd = os.path.dirname(os.path.realpath(__file__))	×
32	self.hymod_path = self.owd + os.sep + "hymod_python"	×
33	climatefile = open(self.hymod_path + os.sep + "hymod_input.csv", "r")	×
34	headerline = climatefile.readline()[:-1]	×
35
36	if ";" in headerline:	×
37	self.delimiter = ";"	×
38	else:
39	self.delimiter = ","	×
40	self.header = headerline.split(self.delimiter)	×
41	for line in climatefile:	×
42	values = line.strip().split(self.delimiter)	×
43	self.date.append(str(values[0]))	×
44	self.Precip.append(float(values[1]))	×
45	self.PET.append(float(values[2]))	×
46	self.trueObs.append(float(values[3]))	×
47
48	climatefile.close()	×
49
50	def simulation(self, x):	×
51	data = hymod(self.Precip, self.PET, x[0], x[1], x[2], x[3], x[4])	×
52	sim = []	×
53	for val in data:	×
54	sim.append(val * self.Factor)	×
55	return sim[366:]	×
56
57	def evaluation(self):	×
58	return self.trueObs[366:]	×
59
60	def objectivefunction(self, simulation, evaluation, params=None):	×
61	return [	×
62	-abs(spotpy.objectivefunctions.bias(evaluation, simulation)),
63	spotpy.objectivefunctions.rsquared(evaluation, simulation),
64	spotpy.objectivefunctions.nashsutcliffe(evaluation, simulation),
65	]

thouska / spotpy / 15283517039

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