def test_ensure_completeness(self):
template = DatasetTemplate(dimensions={'X': 1})
template.variables = {
'A': {'_dimensions': ['X'], '_datatype': 'float32', '_data': [12.3]},
'B': {'_dimensions': ['X'], '_data': [12.3]},
'X': {'_dimensions': ['X'], '_data': self.values1},
'Y': {'_datatype': 'float32', '_data': None}
}
template.ensure_completeness()
self.assertEqual(['X'], template.variables['A']['_dimensions'])
self.assertEqual(np.dtype('float32'), template.variables['A']['_datatype'])
self.assertEqual([12.3], template.variables['A']['_data'])
self.assertIsInstance(template.variables['A']['_data'], np.ndarray)
self.assertEqual(np.dtype('float64'), template.variables['B']['_datatype'])
self.assertIs(self.values1.dtype, template.variables['X']['_datatype'])
self.assertEqual([], template.variables['Y']['_dimensions'])
template.variables = {'Z': {'_dimensions': [], '_data': None}}
self.assertRaisesRegexp(ValidationError, r"No data type information for variable 'Z'",
template.ensure_completeness)
template.variables = {'Z': {'_dimensions': []}}
self.assertRaisesRegexp(ValidationError, r"No data specified for variable 'Z'",
template.ensure_completeness)
def test_ensure_consistency(self):
template = DatasetTemplate()
scalar = {'_dimensions': [], '_data': np.array(1)}
template.variables = {'SCALAR': scalar}
template.ensure_consistency()
self.assertEqual({}, template.dimensions)
self.assertIs(scalar, template.variables['SCALAR'])
template = DatasetTemplate(dimensions={'TEN': 10})
var_10 = {'_dimensions': ['TEN'], '_data': self.values10}
template.variables = {'TEN': var_10}
template.ensure_consistency()
self.assertEqual({'TEN': 10}, template.dimensions)
self.assertIs(var_10, template.variables['TEN'])
template = DatasetTemplate(dimensions={'X': None})
var_12 = {'_dimensions': ['X'], '_data': np.arange(12)}
template.variables = {'X': var_12}
template.ensure_consistency()
self.assertEqual({'X': 12}, template.dimensions)
self.assertIs(var_12, template.variables['X'])
empty = {'_dimensions': ['X'], '_data': None}
template.variables['EMPTY'] = empty
template.ensure_consistency()
self.assertEqual({'X': 12}, template.dimensions)
self.assertIs(empty, template.variables['EMPTY'])
template.variables['X']['_data'] = self.values1
self.assertRaisesRegexp(
ValueError,
'inconsistent with dimension sizes defined in template', template.
ensure_consistency) # now should fail because dim X is already set
template.variables = {
'Z': {
'_dimensions': ["NOSUCHTHING"],
'_data': self.values10
}
}
self.assertRaisesRegexp(ValidationError, 'undefined dimensions',
template.ensure_consistency)
template.variables = {
'W': {
'_dimensions': ['X'],
'_data': np.arange(20).reshape((10, 2))
}
}
self.assertRaisesRegexp(
ValueError,
"Variable 'W' has 1 dimensions, but value array has 2 dimensions.",
template.ensure_consistency)