Type checking of input data

[TobyBoyne]

Input data, X, is either a list object or an ndarray object. We should ensure that the handling of these objects is consistent and predictable. For example, the type hint below: encode expects a list, but we type hint this as an ndarray.

entmoot/entmoot/models/enting.py

Lines 80 to 85 in 1ae5042

	def fit(self, X: np.ndarray, y: np.ndarray) -> None:
	"""
	Performs the training of you tree model using training data and labels
	"""
	# encode categorical features
	X = self._problem_config.encode(X)

[TobyBoyne]

Similarly, the encode/decode methods return an empty list if the data is empty, otherwise an ndarray