flopscope.numpy.asarray_chkfinite
fnp.asarray_chkfinite(a, dtype=None, order=None)[flopscope source][numpy source]
Convert the input to an array, checking for NaNs or Infs.
Adapted from NumPy docs np.asarray_chkfinite
Convert to array, raising if NaN or inf. Cost: numel(input).
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
ais Fortran contiguous, 'C' otherwise 'K' (keep) preserve input order Defaults to 'C'.
Returns
- out:ndarray
Array interpretation of
a. No copy is performed if the input is already an ndarray. Ifais a subclass of ndarray, a base class ndarray is returned.
Raises
- :ValueError
Raises ValueError if
acontains NaN (Not a Number) or Inf (Infinity).
See also
- we.flops.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.
- we.flops.fromiter Create an array from an iterator.
- we.flops.fromfunction Construct an array by executing a function on grid positions.
Examples
>>> import flopscope.numpy as fnpConvert a list into an array. If all elements are finite, then asarray_chkfinite is identical to asarray.
>>> a = [1, 2]
>>> flops.asarray_chkfinite(a, dtype=float)
array([1., 2.])Raises ValueError if array_like contains Nans or Infs.
>>> a = [1, 2, flops.inf]
>>> try:
... flops.asarray_chkfinite(a)
... except ValueError:
... print('ValueError')
...
ValueError