# numpy.isinf¶

numpy.isinf(x[, out])

Test element-wise for positive or negative infinity, return result as bool array.

Parameters: x : array_like Input values y : array_like, optional An array with the same shape as x to store the result. y : {ndarray, bool} For scalar input, the result is a new boolean with value True if the input is positive or negative infinity; otherwise the value is False. For array input, the result is a boolean array with the same dimensions as the input and the values are True if the corresponding element of the input is positive or negative infinity; otherwise the values are False. If a second argument is supplied the result is stored there. If the type of that array is a numeric type the result is represented as zeros and ones, if the type is boolean then as False and True. The return value y is then a reference to that array.

Notes

Numpy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754).

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

Examples

```>>> np.isinf(np.inf)
True
>>> np.isinf(np.nan)
False
>>> np.isinf(np.NINF)
True
>>> np.isinf([np.inf, -np.inf, 1.0, np.nan])
array([ True,  True, False, False], dtype=bool)
```
```>>> x = np.array([-np.inf, 0., np.inf])
>>> y = np.array([2, 2, 2])
>>> np.isinf(x, y)
array([1, 0, 1])
>>> y
array([1, 0, 1])
```

numpy.isfinite

numpy.isnan