def create_ragged_array(cls, data):
return NumpyUtils.create_numpy_object_array(data)
def test_ragged_array_types(self):
param_type = RaggedArrayType()
param_ctx = ParameterContext("array_type", param_type=param_type, fill_value='')
# test well-formed
scov = _make_cov(self.working_dir, ['quantity', param_ctx], nt = 0)
with self.assertRaises(ValueError):
data_dict = {
'time' : np.array([0,1], dtype='<f8'),
'array_type' : np.array([[0,0,0], [1,1,1]], dtype=np.dtype('object'))
}
data_dict = _easy_dict(data_dict)
scov.set_parameter_values(data_dict)
data_dict = {
'time' : np.array([0,1], dtype='<f8'),
'array_type' : np.array([[0,0,0], [1,1,1,1]], dtype=np.dtype('object'))
}
data_dict = _easy_dict(data_dict)
scov.set_parameter_values(data_dict)
returned_dict = scov.get_parameter_values(param_names=data_dict.keys()).get_data()
for k,v in data_dict.iteritems():
np.testing.assert_array_equal(v.get_data(), returned_dict[k])
# test one element
scov = _make_cov(self.working_dir, ['quantity', param_ctx], nt = 0)
from coverage_model.util.numpy_utils import NumpyUtils
data_dict = {
'time' : np.array([0], dtype='<f8'),
'array_type' : RaggedArrayType.create_ragged_array(np.array([[0,0,0]]))
}
data_dict = _easy_dict(data_dict)
scov.set_parameter_values(data_dict)
returned_dict = scov.get_parameter_values(param_names=data_dict.keys()).get_data()
for k,v in data_dict.iteritems():
np.testing.assert_array_equal(v.get_data(), returned_dict[k])
# test numpy array
scov = _make_cov(self.working_dir, ['quantity', param_ctx], nt = 0)
data_dict = {
'time' : np.array([0,1], dtype='<f8'),
'array_type' : NumpyUtils.create_numpy_object_array(np.array([[1,1,1], [2,2,2]], dtype='i4'))
}
data_dict = _easy_dict(data_dict)
scov.set_parameter_values(data_dict)
returned_dict = scov.get_parameter_values(param_names=data_dict.keys()).get_data()
for k,v in data_dict.iteritems():
np.testing.assert_array_equal(v.get_data(), returned_dict[k])
# test numpy array
scov = _make_cov(self.working_dir, ['quantity', param_ctx], nt = 0)
data_dict = {
'time' : np.array([0,1], dtype='<f8'),
'array_type' : NumpyUtils.create_numpy_object_array(np.array([[1,1,1], [2,2,2,2]]))
}
data_dict = _easy_dict(data_dict)
scov.set_parameter_values(data_dict)
data_dict = {
'time' : np.array([2,3], dtype='<f8'),
'array_type' : RaggedArrayType.create_ragged_array(np.array([[1,1,1], [2,2,2]]))
}
data_dict = _easy_dict(data_dict)
scov.set_parameter_values(data_dict)
returned_dict = scov.get_parameter_values(time_segment=(2,3), param_names=data_dict.keys()).get_data()
for k,v in data_dict.iteritems():
np.testing.assert_array_equal(v.get_data(), returned_dict[k])
self.assertEqual(2, returned_dict[k].size)
data_dict = {
'time' : np.array([0,1,2,3], dtype='<f8'),
'array_type' : NumpyUtils.create_numpy_object_array(np.array([[1,1,1], [2,2,2,2], [1,1,1], [2,2,2]]))
}
data_dict = _easy_dict(data_dict)
returned_dict = scov.get_parameter_values(param_names=data_dict.keys()).get_data()
for k,v in data_dict.iteritems():
np.testing.assert_array_equal(v.get_data(), returned_dict[k])
self.assertEqual(4, returned_dict[k].size)
