sklearn.utils.assert_all_finite(X, *, allow_nan=False, estimator_name=None, input_name='')[source]#

Throw a ValueError if X contains NaN or infinity.

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.


>>> 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.