numpy.asarray_chkfinite(a, dtype=None, order=None)
Convert the input to an array, checking for NaNs or Infs.
Parameters:aarray_likeInput 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, optionalBy default, the data-type is inferred from the input data.
order{‘C’, ‘F’, ‘A’, ‘K’}, optionalThe memory layout of the output. ‘C’ gives a row-major layout (C-style), ‘F’ gives a column-major layout (Fortran-style). ‘C’ and ‘F’ will copy if needed to ensure the output format. ‘A’ (any) is equivalent to ‘F’ if input a is non-contiguous or Fortran-contiguous, otherwise, it is equivalent to ‘C’. Unlike ‘C’ or ‘F’, ‘A’ does not ensure that the result is contiguous. ‘K’ (keep) preserves the input order for the output. ‘C’ is the default.
Returns:outndarrayArray 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:ValueErrorRaises ValueError if a contains NaN (Not a Number) or Inf (Infinity).
Examples
>>> importnumpyasnpConvert 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=np.float64)array([1., 2.])Raises ValueError if array_like contains Nans or Infs.
>>> a=[1,2,np.inf]>>> try:... np.asarray_chkfinite(a)... exceptValueError:... print('ValueError')...ValueError