def _md_problems(problem_dir):
global _md
_md = ModelDict()
_md.directory = problem_dir
_md.load(ModelBase)
lst = []
for k, m in sorted(_md._models.items()):
lst.append({'key': k, 'solved': m.solved})
return lst
def _md_problems(problem_dir):
global _md
_md = ModelDict()
_md.directory = problem_dir
_md.load(ModelBase)
lst = []
for k, m in sorted(_md._models.items()):
lst.append({ 'key' : k, 'solved' : m.solved })
return lst
def __init__(self, parameters, functionals, model_class):
self._parameters = None
self.parameters = parameters
self._functionals = None
self.functionals = functionals
self.model_dict = ModelDict()
self.model_class = model_class
def test_parameteric_study(self):
mg = ModelGenerator()
n = 50
k = 2
mg.add_parameter('x', np.linspace(-10, 10, n))
mg.add_parameter('y', np.linspace(-10, 10, n))
mg.combination()
cwd = '{0}/models'.format(pythonlab.tempname())
mg.save(cwd)
md = ModelDict()
md.directory = cwd
md.load(booths_function.BoothsFunction)
md.solve()
self.assertEqual(len(md.solved_models), n**k)
def setUp(self):
md = ModelDict()
variants = [1e-3, 1e-2, 1e2, 1e-4, 1e-1,
1e-5, 1e-8, 1e3, 1e6, 1e-8]
for x in variants:
model = quadratic_function.QuadraticFunction()
model.parameters['x'] = x
GeneticInfo.set_population_from(model, 0)
GeneticInfo.set_population_to(model, 0)
md.add_model(model)
md.solve(save=False)
self.functionals = Functionals(Functional('F', 'min'))
self.selector = SingleCriteriaSelector(self.functionals)
self.selector.recomended_population_size = len(variants)
self.population = md.models
def setUp(self):
self.md = ModelDict()
self.md.directory = '{0}/models'.format(pythonlab.tempname())
class TestModelDict(Agros2DTestCase):
def setUp(self):
self.md = ModelDict()
self.md.directory = '{0}/models'.format(pythonlab.tempname())
"""
def test_set_directory(self):
model = ModelBase()
self.md.add_model(model)
with self.assertRaises(RuntimeError):
self.md.directory = '{0}/models'.format(pythonlab.tempname())
"""
def test_set_wrong_directory(self):
with self.assertRaises(IOError):
self.md.directory = '/models'
def test_add_model(self):
model = ModelBase()
self.md.add_model(model)
self.assertTrue(len(self.md.models))
"""
def test_add_model_with_existing_name(self):
model = ModelBase()
self.md.add_model(model, 'model')
self.md.save()
self.md.clear()
with self.assertRaises(KeyError):
self.md.add_model(model, 'model')
"""
"""
def test_add_model_with_automatic_name(self):
model = ModelBase()
indexes = [0, 1, 3]
for index in indexes:
self.md.add_model(model, name='model_{0:06d}'.format(index))
self.md.save()
self.md.add_model(model)
self.md.save()
self.md.clear()
self.md.load(ModelBase)
self.assertEqual(len(indexes)+1, len(self.md.models))
self.md.load(ModelBase, mask='model_000002.pickle')
self.assertEqual(len(indexes)+1, len(self.md.models))
"""
def test_save_and_load(self):
model = ModelBase()
N = 10
for i in range(N):
self.md.add_model(model)
self.md.save()
self.md.clear()
self.md.load(ModelBase)
self.assertEqual(N, len(self.md.models))
def test_load_files_with_wrong_directory(self):
model = ModelBase()
self.md.add_model(model)
with self.assertRaises(RuntimeError):
self.md.load(ModelBase,
mask='{0}/models'.format(pythonlab.tempname()))
def test_solve(self):
variants = [(1, 2), (2, 3), (3, 4)]
for a, x in variants:
model = quadratic_function.QuadraticFunction()
model.parameters['a'] = a
model.parameters['x'] = x
self.md.add_model(model)
self.md.solve()
for a, x in variants:
model = self.md.find_model_by_parameters({'a': a, 'x': x})
self.assertEqual(a * x**2, model.variables['F'])
def test_solve_models_by_mask(self):
for a, x in [(1, 2), (2, 3), (3, 4)]:
model = quadratic_function.QuadraticFunction()
model.parameters['a'] = a
model.parameters['x'] = x
self.md.add_model(model)
self.md.solve(mask='model_00000[0, 2]')
self.assertEqual(len(self.md.models), 3)
self.assertEqual(len(self.md.solved_models), 2)
for a, x in [(1, 2), (3, 4)]:
model = self.md.find_model_by_parameters({'a': a, 'x': x})
self.assertEqual(a * x**2, model.variables['F'])
def __init__(self):
self._dict = ModelDict()
self._model_class = ModelBase
self._parameters = dict()
class ModelGenerator:
def __init__(self):
self._dict = ModelDict()
self._model_class = ModelBase
self._parameters = dict()
@property
def parameters(self):
"""Parameters of the model."""
return list(self._parameters)
@property
def dict(self):
"""Models dictionary."""
return self._dict
@property
def models(self):
"""List of models in dictionary."""
return self._dict.models
def add_parameter(self, name, values):
"""Add new model parameter.
add_parameter(name, values)
Keyword arguments:
name -- parameter name
values -- list of parameter values
"""
self._parameters[name] = values
def remove_parameter(self, name):
"""Remove model parameter.
remove_parameter(name)
Keyword arguments:
name -- parameter name
"""
del self._parameters[name]
def save(self, directory):
"""Save models to directory.
save(directory)
Keyword arguments:
directory -- directory path
"""
self._dict.directory = directory
self._dict.save()
def combination(self):
"""Generate models by combination of parameters values."""
combinations = [[{key: value} for (key, value) in zip(self._parameters, values)]
for values in product(*self._parameters.values())]
for combination in combinations:
model = self._model_class()
for parameter in combination:
model.parameters.update(parameter)
self._dict.add_model(model)
def random_selection(self, count):
"""Generate models by random selection of parameters values."""
for index in range(count):
model = self._model_class()
for key, value in self._parameters.items():
model.parameters[key] = choice(value)
self._dict.add_model(model)
def __init__(self):
self._dict = ModelDict()
self._model_class = ModelBase
self._parameters = dict()
class ModelGenerator:
def __init__(self):
self._dict = ModelDict()
self._model_class = ModelBase
self._parameters = dict()
@property
def parameters(self):
"""Parameters of the model."""
return list(self._parameters)
@property
def dict(self):
"""Models dictionary."""
return self._dict
@property
def models(self):
"""List of models in dictionary."""
return self._dict.models
def add_parameter(self, name, values):
"""Add new model parameter.
add_parameter(name, values)
Keyword arguments:
name -- parameter name
values -- list of parameter values
"""
self._parameters[name] = values
def remove_parameter(self, name):
"""Remove model parameter.
remove_parameter(name)
Keyword arguments:
name -- parameter name
"""
del self._parameters[name]
def save(self, directory):
"""Save models to directory.
save(directory)
Keyword arguments:
directory -- directory path
"""
self._dict.directory = directory
self._dict.save()
def combination(self):
"""Generate models by combination of parameters values."""
combinations = [[{
key: value
} for (key, value) in zip(self._parameters, values)]
for values in product(*self._parameters.values())]
for combination in combinations:
model = self._model_class()
for parameter in combination:
model.parameters.update(parameter)
self._dict.add_model(model)
def random_selection(self, count):
"""Generate models by random selection of parameters values."""
for index in range(count):
model = self._model_class()
for key, value in self._parameters.items():
model.parameters[key] = choice(value)
self._dict.add_model(model)
def create_model_dict(directory):
md = ModelDict()
md.load(ModelBase, directory)
return md
class TestModelDict(Agros2DTestCase):
def setUp(self):
self.md = ModelDict()
self.md.directory = '{0}/models'.format(pythonlab.tempname())
"""
def test_set_directory(self):
model = ModelBase()
self.md.add_model(model)
with self.assertRaises(RuntimeError):
self.md.directory = '{0}/models'.format(pythonlab.tempname())
"""
def test_set_wrong_directory(self):
with self.assertRaises(IOError):
self.md.directory = '/models'
def test_add_model(self):
model = ModelBase()
self.md.add_model(model)
self.assertTrue(len(self.md.models))
"""
def test_add_model_with_existing_name(self):
model = ModelBase()
self.md.add_model(model, 'model')
self.md.save()
self.md.clear()
with self.assertRaises(KeyError):
self.md.add_model(model, 'model')
"""
"""
def test_add_model_with_automatic_name(self):
model = ModelBase()
indexes = [0, 1, 3]
for index in indexes:
self.md.add_model(model, name='model_{0:06d}'.format(index))
self.md.save()
self.md.add_model(model)
self.md.save()
self.md.clear()
self.md.load(ModelBase)
self.assertEqual(len(indexes)+1, len(self.md.models))
self.md.load(ModelBase, mask='model_000002.pickle')
self.assertEqual(len(indexes)+1, len(self.md.models))
"""
def test_save_and_load(self):
model = ModelBase()
N = 10
for i in range(N):
self.md.add_model(model)
self.md.save()
self.md.clear()
self.md.load(ModelBase)
self.assertEqual(N, len(self.md.models))
def test_load_files_with_wrong_directory(self):
model = ModelBase()
self.md.add_model(model)
with self.assertRaises(RuntimeError):
self.md.load(ModelBase, mask='{0}/models'.format(pythonlab.tempname()))
def test_solve(self):
variants = [(1, 2), (2, 3), (3, 4)]
for a, x in variants:
model = quadratic_function.QuadraticFunction()
model.parameters['a'] = a
model.parameters['x'] = x
self.md.add_model(model)
self.md.solve()
for a, x in variants:
model = self.md.find_model_by_parameters({'a' : a, 'x' : x})
self.assertEqual(a*x**2, model.variables['F'])
def test_solve_models_by_mask(self):
for a, x in [(1, 2), (2, 3), (3, 4)]:
model = quadratic_function.QuadraticFunction()
model.parameters['a'] = a
model.parameters['x'] = x
self.md.add_model(model)
self.md.solve(mask='model_00000[0, 2]')
self.assertEqual(len(self.md.models), 3)
self.assertEqual(len(self.md.solved_models), 2)
for a, x in [(1, 2), (3, 4)]:
model = self.md.find_model_by_parameters({'a' : a, 'x' : x})
self.assertEqual(a*x**2, model.variables['F'])
def setUp(self):
self.md = ModelDict()
self.md.directory = '{0}/models'.format(pythonlab.tempname())