# -*- coding: utf-8 -*-
import logging
import numpy as np
from sklearn.pipeline import Pipeline
"""
Collection of functions to work with the input and output of a scikit.base.BaseEstimator
"""
logger = logging.getLogger(__name__)
def get_model_output(model: Pipeline, X: np.ndarray) -> np.ndarray:
"""
Get the raw output from the current model given X.
Will try to `predict` and then `transform`, raising an error
if both fail.
Parameters
----------
X: np.ndarray
2d array of sample(s)
Returns
-------
np.ndarray
The raw output of the model in numpy array form.
"""
try:
return model.predict(X) # type: ignore
# Model may only be a transformer
except AttributeError:
try:
return model.transform(X) # type: ignore
except Exception as exc:
logger.error(f"Failed to predict or transform; error: {exc}")
raise
