def coerce_type(cls, obj, typedef=None, key_order=None, **kwargs):
r"""Coerce objects of specific types to match the data type.
Args:
obj (object): Object to be coerced.
typedef (dict, optional): Type defintion that object should be
coerced to. Defaults to None.
key_order (list, optional): Order or keys correpsonding to elements in
a provided list or tuple. Defaults to None.
**kwargs: Additional keyword arguments are metadata entries that may
aid in coercing the type.
Returns:
object: Coerced object.
Raises:
RuntimeError: If obj is a list or tuple, but key_order is not provided.
"""
from yggdrasil.serialize import pandas2dict, numpy2dict, list2dict
if isinstance(obj, pd.DataFrame):
obj = pandas2dict(obj)
elif isinstance(obj, np.ndarray) and (len(obj.dtype) > 0):
obj = numpy2dict(obj)
elif isinstance(obj, (list, tuple)) and (key_order is not None):
obj = list2dict(obj, names=key_order)
return obj
def test_numpy2dict():
r"""Test conversion of a numpy array to a dictionary and back."""
with pytest.raises(TypeError):
serialize.numpy2dict(None)
with pytest.raises(TypeError):
serialize.dict2numpy(None)
nele = 5
names = ["complex", "name", "number", "value"]
dtypes = ['c16', 'S5', 'i8', 'f8']
dtype = np.dtype([(n, f) for n, f in zip(names, dtypes)])
arr_mix = np.zeros(nele, dtype)
arr_mix['name'][0] = 'hello'
test_arrs = [arr_mix, np.zeros(0, dtype)]
np.testing.assert_array_equal(serialize.dict2numpy({}), np.array([]))
for ans in test_arrs:
d = serialize.numpy2dict(ans)
# Sorted
res = serialize.dict2numpy(d)
np.testing.assert_array_equal(ans, res)
# Provided
res = serialize.dict2numpy(d, order=ans.dtype.names)
np.testing.assert_array_equal(ans, res)