asarray_chkfinite(a, dtype=None, order=None)

Parameters

a : array_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.

dtype : data-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'.

Raises

ValueError

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

Returns

out : ndarray

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.

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

See Also

asanyarray

Similar function which passes through subclasses.

asarray

Create and array.

ascontiguousarray

Convert input to a contiguous array.

asfarray

Convert input to a floating point ndarray.

asfortranarray

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

fromfunction

Construct an array by executing a function on grid positions.

fromiter

Create an array from an iterator.

Examples

Convert a list into an array. If all elements are finite 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

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

numpy.asarray numpy.asanyarray

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