numpy.asarray_chkfinite#

numpy.asarray_chkfinite(a, dtype=None, order=None)[source]#

Convert the input to an array, checking for NaNs or Infs.

Parameters:
aarray_like

Input data, in any form that can be converted to an array. This includes lists, lists of tuples, tuples, tuples of tuples, tuples of lists and ndarrays. Success requires no NaNs or Infs.

dtypedata-type, optional

By default, the data-type is inferred from the input data.

order{‘C’, ‘F’, ‘A’, ‘K’}, optional

Memory layout. ‘A’ and ‘K’ depend on the order of input array a. ‘C’ row-major (C-style), ‘F’ column-major (Fortran-style) memory representation. ‘A’ (any) means ‘F’ if a is Fortran contiguous, ‘C’ otherwise ‘K’ (keep) preserve input order Defaults to ‘C’.

Returns:
outndarray

Array interpretation of a. No copy is performed if the input is already an ndarray. If a is a subclass of ndarray, a base class ndarray is returned.

Raises:
ValueError

Raises ValueError if a contains NaN (Not a Number) or Inf (Infinity).

See also

asarray

Create and array.

asanyarray

Similar function which passes through subclasses.

ascontiguousarray

Convert input to a contiguous array.

asfortranarray

Convert input to an ndarray with column-major memory order.

fromiter

Create an array from an iterator.

fromfunction

Construct an array by executing a function on grid positions.

Examples

>>> import numpy as np

Convert a list into an array. If all elements are finite, then asarray_chkfinite is identical to asarray.

>>> a = [1, 2]
>>> np.asarray_chkfinite(a, dtype=float)
array([1., 2.])

Raises ValueError if array_like contains Nans or Infs.

>>> a = [1, 2, np.inf]
>>> try:
...     np.asarray_chkfinite(a)
... except ValueError:
...     print('ValueError')
...
ValueError