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https://github.com/ejeanboris/MDAF.git
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96 lines
2.9 KiB
Python
96 lines
2.9 KiB
Python
import unittest
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import os
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from MDAF.MDAF import representfunc
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from MDAF.MDAF import installFalcoo
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from MDAF.MDAF import doe
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from MDAF.TestFunctions import *
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#target = __import__("MDAF.py")
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# Testing the test function representation workflow
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class Test_representfunc(unittest.TestCase):
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def testexternalfuncs(self):
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"""
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Test that the function can calculate the representation and write to the function docstring
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"""
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funcpath = 'tests/Bukin2.py'
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#funcpath_backup = 'tests/Bukin2.py.old'
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results = representfunc(funcpath, forced = True)
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with open(funcpath,"r") as file:
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content = file.read()
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reprCheck = bool(content.find('#_# Represented: 1'))
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#os.remove(funcpath)
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#os.replace(funcpath_backup, funcpath)
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self.assertTrue(reprCheck)
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self.assertIsInstance(results, dict)
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def testinternalfuncs(self):
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"""
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Test that the function can calculate the representation and write to the function docstring
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"""
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funcpath = '@Bukin2.py'
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funcverify = 'MDAF/TestFunctions/Bukin2.py'
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#funcpath_backup = 'tests/Bukin2.py.old'
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results = representfunc(funcpath, forced = True)
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with open(funcverify,"r") as file:
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content = file.read()
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reprCheck = bool(content.find('#_# Represented: 1'))
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#os.remove(funcpath)
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#os.replace(funcpath_backup, funcpath)
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self.assertTrue(reprCheck)
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self.assertIsInstance(results, dict)
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# Testing the flacco installation workflow
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class Test_flaccoInstall(unittest.TestCase):
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def testoutput(self):
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"""
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Test that the flacco packages are able to install automatically
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"""
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#installFalcoo()
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# Testing the DOE execution workflow
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class Test_DOE(unittest.TestCase):
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def testexternalfuncs(self):
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"""
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Test that it can execute a DOE and output the dictionarry of the results
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"""
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testfunctionpaths = ["tests/Bukin2.py"]
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heuristicpath = "tests/SimmulatedAnnealing.py"
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args = {"t": 1000, "p": 0.95, "objs": 0}
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data = doe (heuristicpath, testfunctionpaths, args)
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self.assertIsInstance(data, dict)
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def testinternalfuncs(self):
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"""
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Test that it can execute a DOE and output the dictionarry of the results
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"""
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testfunctionpaths = ["@Bukin2.py"]
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heuristicpath = "@SimmulatedAnnealing.py"
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args = {"t": 1000, "p": 0.95, "objs": 0}
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data = doe (heuristicpath, testfunctionpaths, args)
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print(data)
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self.assertIsInstance(data, dict)
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# Testing the surrogate modelling workflow
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class Test_surrogate(unittest.TestCase):
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def testoutput(self):
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"""
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Test that it can generate a neural network approximation of the algorithm's performance expectation
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"""
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#tbd
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if __name__ == '__main__':
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unittest.main() |