sklearn.utils
.assert_all_finite¶
- sklearn.utils.assert_all_finite(X, *, allow_nan=False, estimator_name=None, input_name='')[source]¶
Throw a ValueError if X contains NaN or infinity.
- Parameters:
- X{ndarray, sparse matrix}
The input data.
- allow_nanbool, default=False
If True, do not throw error when
X
contains NaN.- estimator_namestr, default=None
The estimator name, used to construct the error message.
- input_namestr, default=””
The data name used to construct the error message. In particular if
input_name
is “X” and the data has NaN values and allow_nan is False, the error message will link to the imputer documentation.
Examples
>>> from sklearn.utils import assert_all_finite >>> import numpy as np >>> array = np.array([1, np.inf, np.nan, 4]) >>> try: ... assert_all_finite(array) ... print("Test passed: Array contains only finite values.") ... except ValueError: ... print("Test failed: Array contains non-finite values.") Test failed: Array contains non-finite values.