torch_ecg.utils.dicts_equal¶

torch_ecg.utils.dicts_equal(d1: dict, d2: dict, allow_array_diff_types: bool = True) → bool[source]¶

Determine if two dicts are equal.

Parameters:

d1 (dict) – The two dicts to compare equality.
d2 (dict) – The two dicts to compare equality.
allow_array_diff_types (bool, default True) – Whether allow the equality of two arrays with different types, including list, tuple, numpy.ndarray, torch.Tensor, NOT including pandas.DataFrame, pandas.Series.

Returns:

True if d1 equals d2, False otherwise.

Return type:

bool

Note

The existence of ndarray, Tensor, DataFrame and Series would probably cause errors when directly use the default __eq__ method of dict For example:

>>> {"a": np.array([1,2])} == {"a": np.array([1,2])}
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

Example

>>> d1 = {"a": pd.DataFrame([{"hehe":1,"haha":2}])[["haha","hehe"]]}
>>> d2 = {"a": pd.DataFrame([{"hehe":1,"haha":2}])[["hehe","haha"]]}
>>> dicts_equal(d1, d2)
True