numpy.isfinite

numpy.isfinite(x[, out])

Returns True for each element that is a finite number.

Shows which elements of the input are finite (not infinity or not Not a Number).

Parameters:

x : array_like

Input values.

y : array_like, optional

A boolean array with the same shape and type as x to store the result.

Returns:

y : ndarray, bool

For scalar input data, the result is a new numpy boolean with value True if the input data is finite; otherwise the value is False (input is either positive infinity, negative infinity or Not a Number).

For array input data, the result is an numpy boolean array with the same dimensions as the input and the values are True if the corresponding element of the input is finite; otherwise the values are False (element is either positive infinity, negative infinity or Not a Number). If the second argument is supplied then an numpy integer array is returned with values 0 or 1 corresponding to False and True, respectively.

See also

isinf
Shows which elements are negative or negative infinity.
isneginf
Shows which elements are negative infinity.
isposinf
Shows which elements are positive infinity.
isnan
Shows which elements are Not a Number (NaN).

Notes

Not a Number, positive infinity and negative infinity are considered to be non-finite.

Numpy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. Also that positive infinity is not equivalent to negative infinity. But infinity is equivalent to positive infinity.

Errors result if second argument is also supplied with scalar input or if first and second arguments have different shapes.

Examples

>>> np.isfinite(1)
True
>>> np.isfinite(0)
True
>>> np.isfinite(np.nan)
False
>>> np.isfinite(np.inf)
False
>>> np.isfinite(np.NINF)
False
>>> np.isfinite([np.log(-1.),1.,np.log(0)])
array([False,  True, False], dtype=bool)
>>> x=np.array([-np.inf, 0., np.inf])
>>> y=np.array([2,2,2])
>>> np.isfinite(x,y)
array([0, 1, 0])
>>> y
array([0, 1, 0])

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