def setUp(self):
_data = [-2.1, 0.2, 1.9, 3.8, 6.1]
self._means = np.array([3.654, 7.789])
self._vars = np.array([2.467, 1.543])
self._cov_mat_uncor = np.array([[self._vars[0], 0.0], [0.0, self._vars[1]]])
self._cov_mat_uncor_inv = np.linalg.inv(self._cov_mat_uncor)
self._cov_mat_cor = np.array([[self._vars[0], 0.1], [0.1, self._vars[1]]])
self._cov_mat_cor_inv = np.linalg.inv(self._cov_mat_cor)
self._cov_mat_simple_a_inv = np.array([[1.0 / self._vars[0], 0.0], [0.0, 0.0]])
self._cov_mat_simple_b_inv = np.array([[0.0, 0.0], [0.0, 1.0 / self._vars[1]]])
self._data_container = IndexedContainer(data=_data)
self._data_container.add_error(err_val=1.0)
_a_test = np.linspace(start=0, stop=4, num=9, endpoint=True)
_b_test = np.linspace(start=-4, stop=0, num=9, endpoint=True)
self._test_par_values = np.zeros((4, 2, 9))
self._test_par_values[0, 0] = _a_test
self._test_par_values[1, 1] = _b_test
self._test_par_values[2, 0] = _a_test
self._test_par_values[2, 1] = _b_test
self._test_par_values[3, 0] = _a_test
self._test_par_values[3, 1] = -_b_test
self._test_par_res = self._test_par_values - self._means.reshape((1, 2, 1))
self._test_par_res = np.transpose(self._test_par_res, axes=(0, 2, 1))
self._fit_no_constraints = IndexedFit(self._data_container, model_function=self._model)
self._fit_no_constraints.do_fit()
_cost_function = self._fit_no_constraints._fitter._fcn_wrapper
self._profile_no_constraints = np.zeros((4, 9))
for _i in range(4):
for _j in range(9):
self._profile_no_constraints[_i, _j] = _cost_function(
self._test_par_values[_i, 0, _j],
self._test_par_values[_i, 1, _j])
def setUp(self):
self._ref_data = [3.3, 5.5, 2.2, 8.5, 10.2]
self.idx_cont = IndexedContainer(data=self._ref_data)
self._ref_err_abs_singlevalue = 1.2
self._ref_err_abs_valuearray = [1.2, 1.1, 1.2, 1.2, 1.1]
self._ref_err_corr_coeff = 0.23
self.idx_cont.add_error(self._ref_err_abs_valuearray,
name='MyError',
correlation=self._ref_err_corr_coeff,
relative=False)
self._ref_cov_mat = cov_mat_from_float_list(
self._ref_err_abs_valuearray,
correlation=self._ref_err_corr_coeff).mat
class TestDatastoreIndexed(unittest.TestCase):
def setUp(self):
self._ref_data = [3.3, 5.5, 2.2, 8.5, 10.2]
self.idx_cont = IndexedContainer(data=self._ref_data)
self._ref_err_abs_singlevalue = 1.2
self._ref_err_abs_valuearray = [1.2, 1.1, 1.2, 1.2, 1.1]
self._ref_err_corr_coeff = 0.23
self.idx_cont.add_error(self._ref_err_abs_valuearray,
name='MyError',
correlation=self._ref_err_corr_coeff,
relative=False)
self._ref_cov_mat = cov_mat_from_float_list(
self._ref_err_abs_valuearray,
correlation=self._ref_err_corr_coeff).mat
def test_get_matching_error_all_empty_dict(self):
_errs = self.idx_cont.get_matching_errors(matching_criteria=dict())
self.assertEqual(len(_errs), 1)
self.assertIs(self.idx_cont._error_dicts['MyError']['err'],
_errs['MyError'])
def test_get_matching_error_all_None(self):
_errs = self.idx_cont.get_matching_errors(matching_criteria=None)
self.assertEqual(len(_errs), 1)
self.assertIs(self.idx_cont._error_dicts['MyError']['err'],
_errs['MyError'])
def test_get_matching_error_name(self):
_errs = self.idx_cont.get_matching_errors(matching_criteria=dict(
name='MyError'))
self.assertEqual(len(_errs), 1)
self.assertIs(self.idx_cont._error_dicts['MyError']['err'],
_errs['MyError'])
def test_get_matching_error_type_simple(self):
_errs = self.idx_cont.get_matching_errors(matching_criteria=dict(
type='simple'))
self.assertEqual(len(_errs), 1)
self.assertIs(self.idx_cont._error_dicts['MyError']['err'],
_errs['MyError'])
def test_get_matching_error_type_matrix(self):
_errs = self.idx_cont.get_matching_errors(matching_criteria=dict(
type='matrix'))
self.assertEqual(len(_errs), 0)
def test_get_matching_error_uncorrelated(self):
_errs = self.idx_cont.get_matching_errors(matching_criteria=dict(
correlated=False))
self.assertEqual(len(_errs), 0)
def test_get_matching_error_correlated(self):
_errs = self.idx_cont.get_matching_errors(matching_criteria=dict(
correlated=True))
self.assertEqual(len(_errs), 1)
self.assertIs(self.idx_cont._error_dicts['MyError']['err'],
_errs['MyError'])
def test_compare_error_reference(self):
for _err_dict in self.idx_cont._error_dicts.values():
_err_ref_vals = _err_dict['err'].reference
self.assertTrue(np.all(_err_ref_vals == self._ref_data))
def test_compare_ref_data(self):
self.assertTrue(np.all(self.idx_cont.data == self._ref_data))
def test_compare_ref_err(self):
self.assertTrue(
np.allclose(self.idx_cont.err,
self._ref_err_abs_valuearray,
atol=1e-10))
def test_compare_ref_total_cov_mat(self):
_err = self.idx_cont.get_total_error()
_mat = _err.cov_mat
self.assertTrue(np.allclose(_mat, self._ref_cov_mat, atol=1e-5))
def test_compare_ref_total_err_for_add_err_twice(self):
self.idx_cont.add_error(self._ref_err_abs_valuearray,
name='MyNewError',
correlation=self._ref_err_corr_coeff,
relative=False)
_err = self.idx_cont.get_total_error()
_mat = _err.cov_mat
self.assertTrue(
np.allclose(_mat, self._ref_cov_mat + self._ref_cov_mat,
atol=1e-5))
def test_compare_ref_total_err_for_add_disable_new_err(self):
self.idx_cont.add_error(self._ref_err_abs_valuearray,
name='MyNewError',
correlation=self._ref_err_corr_coeff,
relative=False)
self.idx_cont.disable_error("MyNewError")
_err = self.idx_cont.get_total_error()
_mat = _err.cov_mat
self.assertTrue(np.allclose(_mat, self._ref_cov_mat, atol=1e-5))
def test_compare_ref_total_err_for_add_disable_reenable_new_err(self):
self.idx_cont.add_error(self._ref_err_abs_valuearray,
name='MyNewError',
correlation=self._ref_err_corr_coeff,
relative=False)
self.idx_cont.disable_error("MyNewError")
_err = self.idx_cont.get_total_error()
self.idx_cont.enable_error("MyNewError")
_err = self.idx_cont.get_total_error()
_mat = _err.cov_mat
self.assertTrue(
np.allclose(_mat, self._ref_cov_mat + self._ref_cov_mat,
atol=1e-5))
def test_raise_add_same_error_name_twice(self):
self.idx_cont.add_error(0.1,
name="MyNewError",
correlation=0,
relative=False)
with self.assertRaises(DataContainerException):
self.idx_cont.add_error(0.1,
name="MyNewError",
correlation=0,
relative=False)
def test_raise_get_inexistent_error(self):
with self.assertRaises(DataContainerException):
self.idx_cont.get_error("MyInexistentError")
class TestParameterConstraintInIndexedFit(unittest.TestCase):
def _expected_profile_diff(self, res, cov_mat_inv):
return res.dot(cov_mat_inv).dot(res)
def _test_consistency(self, constrained_fit, par_cov_mat_inv):
constrained_fit.do_fit()
_cost_function = constrained_fit._fitter._fcn_wrapper
for _i in range(4):
for _j in range(9):
_profile_constrained = _cost_function(self._test_par_values[_i, 0, _j], self._test_par_values[_i, 1, _j])
_diff = _profile_constrained - self._profile_no_constraints[_i, _j]
_expected_profile_diff = self._expected_profile_diff(self._test_par_res[_i, _j], par_cov_mat_inv)
self.assertTrue(np.abs(_diff - _expected_profile_diff) < 1e-12)
@staticmethod
def _model(a, b):
return a * np.arange(5) + b
def setUp(self):
_data = [-2.1, 0.2, 1.9, 3.8, 6.1]
self._means = np.array([3.654, 7.789])
self._vars = np.array([2.467, 1.543])
self._cov_mat_uncor = np.array([[self._vars[0], 0.0], [0.0, self._vars[1]]])
self._cov_mat_uncor_inv = np.linalg.inv(self._cov_mat_uncor)
self._cov_mat_cor = np.array([[self._vars[0], 0.1], [0.1, self._vars[1]]])
self._cov_mat_cor_inv = np.linalg.inv(self._cov_mat_cor)
self._cov_mat_simple_a_inv = np.array([[1.0 / self._vars[0], 0.0], [0.0, 0.0]])
self._cov_mat_simple_b_inv = np.array([[0.0, 0.0], [0.0, 1.0 / self._vars[1]]])
self._data_container = IndexedContainer(data=_data)
self._data_container.add_error(err_val=1.0)
_a_test = np.linspace(start=0, stop=4, num=9, endpoint=True)
_b_test = np.linspace(start=-4, stop=0, num=9, endpoint=True)
self._test_par_values = np.zeros((4, 2, 9))
self._test_par_values[0, 0] = _a_test
self._test_par_values[1, 1] = _b_test
self._test_par_values[2, 0] = _a_test
self._test_par_values[2, 1] = _b_test
self._test_par_values[3, 0] = _a_test
self._test_par_values[3, 1] = -_b_test
self._test_par_res = self._test_par_values - self._means.reshape((1, 2, 1))
self._test_par_res = np.transpose(self._test_par_res, axes=(0, 2, 1))
self._fit_no_constraints = IndexedFit(self._data_container, model_function=self._model)
self._fit_no_constraints.do_fit()
_cost_function = self._fit_no_constraints._fitter._fcn_wrapper
self._profile_no_constraints = np.zeros((4, 9))
for _i in range(4):
for _j in range(9):
self._profile_no_constraints[_i, _j] = _cost_function(
self._test_par_values[_i, 0, _j],
self._test_par_values[_i, 1, _j])
def test_bad_input_exception(self):
_fit_with_constraint = IndexedFit(self._data_container, model_function=self._model)
with self.assertRaises(IndexedFitException):
_fit_with_constraint.add_parameter_constraint('c', 1.0, 1.0)
with self.assertRaises(IndexedFitException):
_fit_with_constraint.add_matrix_parameter_constraint(['a', 'c'], [1.0, 2.0], [[0.2, 0.0], [0.0, 0.1]])
with self.assertRaises(IndexedFitException):
_fit_with_constraint.add_matrix_parameter_constraint(['a'], [1.0, 2.0], [[0.2, 0.0], [0.0, 0.1]])
def test_fit_profile_cov_mat_uncorrelated(self):
_fit_with_constraint = IndexedFit(self._data_container, model_function=self._model)
_fit_with_constraint.add_matrix_parameter_constraint(['a', 'b'], self._means, self._cov_mat_uncor)
self._test_consistency(_fit_with_constraint, self._cov_mat_uncor_inv)
_fit_with_constraint_alt = IndexedFit(self._data_container, model_function=self._model)
_fit_with_constraint_alt.add_parameter_constraint('a', self._means[0], np.sqrt(self._vars[0]))
_fit_with_constraint_alt.add_parameter_constraint('b', self._means[1], np.sqrt(self._vars[1]))
self._test_consistency(_fit_with_constraint_alt, self._cov_mat_uncor_inv)
def test_fit_profile_cov_mat_correlated(self):
_fit_with_constraint = IndexedFit(self._data_container, model_function=self._model)
_fit_with_constraint.add_matrix_parameter_constraint(['a', 'b'], self._means, self._cov_mat_cor)
self._test_consistency(_fit_with_constraint, self._cov_mat_cor_inv)
def test_fit_profile_simple_a(self):
_fit_with_constraint = IndexedFit(self._data_container, model_function=self._model)
_fit_with_constraint.add_parameter_constraint('a', self._means[0], np.sqrt(self._vars[0]))
self._test_consistency(_fit_with_constraint, self._cov_mat_simple_a_inv)
def test_fit_profile_simple_b(self):
_fit_with_constraint = IndexedFit(self._data_container, model_function=self._model)
_fit_with_constraint.add_parameter_constraint('b', self._means[1], np.sqrt(self._vars[1]))
self._test_consistency(_fit_with_constraint, self._cov_mat_simple_b_inv)
def setUp(self):
_data = [4, 5, 6, 2, 4, 5., 3.01e-5, 4.4e+45]
_ndat = len(_data)
self._container = IndexedContainer(data=_data)
self._container.add_error(err_val=0.1,
name="SUA",
correlation=0.0,
relative=False)
self._container.add_error(err_val=0.1,
name="SUR",
correlation=0.0,
relative=True)
self._container.add_error(err_val=0.1,
name="SCA",
correlation=1.0,
relative=False)
self._container.add_matrix_error(err_matrix=np.eye(_ndat) * 0.1,
name="MCov",
relative=False,
matrix_type='covariance')
self._container.add_matrix_error(err_matrix=np.eye(_ndat),
name="MCor",
relative=False,
matrix_type='correlation',
err_val=0.1)
# # xy
# self._container.add_simple_error(axis='x', err_val=0.1, correlation=0.0, relative=False)
# self._container.add_simple_error(axis='y', err_val=0.2, correlation=0.0, relative=False)
# self._container.add_matrix_error(axis='y', err_matrix=np.eye(8) * 0.1, relative=False, matrix_type='covariance')
# # hist
# self._container.add_simple_error(err_val=2, correlation=0.5, relative=False)
self._roundtrip_stringstream = IOStreamHandle(StringIO())
self._testfile_stringstream = IOStreamHandle(
StringIO(TEST_DATASET_INDEXED))
self._roundtrip_streamreader = DataContainerYamlReader(
self._roundtrip_stringstream)
self._roundtrip_streamwriter = DataContainerYamlWriter(
self._container, self._roundtrip_stringstream)
self._testfile_streamreader = DataContainerYamlReader(
self._testfile_stringstream)
self._ref_testfile_data = [80.429, 80.339]
self._ref_testfile_err = [0.89442719, 0.89442719]
self._ref_testfile_cov_mat = np.array([[0.8, 0.3], [0.3, 0.8]])
self._ref_testfile_error_names = {
'ErrorOne', 'ErrorTwo', 'ErrorThree', 'ErrorFour'
}
self._testfile_stringstream_missing_keyword = IOStreamHandle(
StringIO(TEST_DATASET_INDEXED_MISSING_KEYWORD))
self._testfile_stringstream_extra_keyword = IOStreamHandle(
StringIO(TEST_DATASET_INDEXED_EXTRA_KEYWORD))
self._testfile_streamreader_missing_keyword = DataContainerYamlReader(
self._testfile_stringstream_missing_keyword)
self._testfile_streamreader_extra_keyword = DataContainerYamlReader(
self._testfile_stringstream_extra_keyword)
class TestIndexedContainerYamlRepresentation(unittest.TestCase):
def setUp(self):
_data = [4, 5, 6, 2, 4, 5., 3.01e-5, 4.4e+45]
_ndat = len(_data)
self._container = IndexedContainer(data=_data)
self._container.add_error(err_val=0.1,
name="SUA",
correlation=0.0,
relative=False)
self._container.add_error(err_val=0.1,
name="SUR",
correlation=0.0,
relative=True)
self._container.add_error(err_val=0.1,
name="SCA",
correlation=1.0,
relative=False)
self._container.add_matrix_error(err_matrix=np.eye(_ndat) * 0.1,
name="MCov",
relative=False,
matrix_type='covariance')
self._container.add_matrix_error(err_matrix=np.eye(_ndat),
name="MCor",
relative=False,
matrix_type='correlation',
err_val=0.1)
# # xy
# self._container.add_simple_error(axis='x', err_val=0.1, correlation=0.0, relative=False)
# self._container.add_simple_error(axis='y', err_val=0.2, correlation=0.0, relative=False)
# self._container.add_matrix_error(axis='y', err_matrix=np.eye(8) * 0.1, relative=False, matrix_type='covariance')
# # hist
# self._container.add_simple_error(err_val=2, correlation=0.5, relative=False)
self._roundtrip_stringstream = IOStreamHandle(StringIO())
self._testfile_stringstream = IOStreamHandle(
StringIO(TEST_DATASET_INDEXED))
self._roundtrip_streamreader = DataContainerYamlReader(
self._roundtrip_stringstream)
self._roundtrip_streamwriter = DataContainerYamlWriter(
self._container, self._roundtrip_stringstream)
self._testfile_streamreader = DataContainerYamlReader(
self._testfile_stringstream)
self._ref_testfile_data = [80.429, 80.339]
self._ref_testfile_err = [0.89442719, 0.89442719]
self._ref_testfile_cov_mat = np.array([[0.8, 0.3], [0.3, 0.8]])
self._ref_testfile_error_names = {
'ErrorOne', 'ErrorTwo', 'ErrorThree', 'ErrorFour'
}
self._testfile_stringstream_missing_keyword = IOStreamHandle(
StringIO(TEST_DATASET_INDEXED_MISSING_KEYWORD))
self._testfile_stringstream_extra_keyword = IOStreamHandle(
StringIO(TEST_DATASET_INDEXED_EXTRA_KEYWORD))
self._testfile_streamreader_missing_keyword = DataContainerYamlReader(
self._testfile_stringstream_missing_keyword)
self._testfile_streamreader_extra_keyword = DataContainerYamlReader(
self._testfile_stringstream_extra_keyword)
def test_write_to_roundtrip_stringstream(self):
self._roundtrip_streamwriter.write()
def test_read_from_testfile_stream(self):
_read_container = self._testfile_streamreader.read()
self.assertTrue(isinstance(_read_container, IndexedContainer))
self.assertTrue(
np.allclose(_read_container.data, self._ref_testfile_data))
self.assertTrue(
np.allclose(_read_container.err, self._ref_testfile_err))
self.assertTrue(
np.allclose(
_read_container.cov_mat,
self._ref_testfile_cov_mat,
))
# check that the error names are the same
self.assertEqual(set(_read_container._error_dicts.keys()),
self._ref_testfile_error_names)
def test_read_from_testfile_stream_missing_keyword(self):
with self.assertRaises(YamlReaderException):
self._testfile_streamreader_missing_keyword.read()
def test_read_from_testfile_stream_extra_keyword(self):
with self.assertRaises(YamlReaderException):
self._testfile_streamreader_extra_keyword.read()
def test_round_trip_with_stringstream(self):
self._roundtrip_streamwriter.write()
self._roundtrip_stringstream.seek(0) # return to beginning
_read_container = self._roundtrip_streamreader.read()
self.assertTrue(isinstance(_read_container, IndexedContainer))
# compare data members
self.assertTrue(np.allclose(self._container.data,
_read_container.data))
# compare (total) errors and cov mats
# TODO: compare individual error components -> nontrivial because error ids change...
self.assertTrue(np.allclose(self._container.err, _read_container.err))
self.assertTrue(
np.allclose(self._container.cov_mat, _read_container.cov_mat))
# check that the error names are the same
self.assertEqual(set(self._container._error_dicts.keys()),
set(_read_container._error_dicts.keys()))