nums.numpy.isinf
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nums.numpy.isinf(x, out=None, where=True, **kwargs)[source] Test element-wise for positive or negative infinity.
This docstring was copied from numpy.isinf.
Some inconsistencies with the NumS version may exist.
Returns a boolean array of the same shape as x, True where
x == +/-inf, otherwise False.- Parameters
x (BlockArray) – Input values
out (BlockArray, None, or optional) – A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.
where (BlockArray, optional) – This condition is broadcast over the input. At locations where the condition is True, the out array will be set to the ufunc result. Elsewhere, the out array will retain its original value. Note that if an uninitialized out array is created via the default
out=None, locations within it where the condition is False will remain uninitialized.**kwargs – For other keyword-only arguments, see the ufunc docs.
- Returns
y – True where
xis positive or negative infinity, false otherwise.- Return type
boolean BlockArray
Notes
NumPy uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754).
Errors result if the second argument is supplied when the first argument is a scalar, or if the first and second arguments have different shapes.
Examples
The doctests shown below are copied from NumPy. They won’t show the correct result until you operate
get().>>> nps.isinf(nps.array(nps.inf)).get() array(True) >>> nps.isinf(nps.array(nps.nan)).get() array(False) >>> nps.isinf(nps.array(nps.NINF)).get() array(True) >>> nps.isinf(nps.array([nps.inf, -nps.inf, 1.0, nps.nan])).get() array([ True, True, False, False])
>>> x = nps.array([-nps.inf, 0., nps.inf]) >>> y = nps.array([2, 2, 2]) >>> nps.isinf(x, y).get() array([1, 0, 1]) >>> y.get() array([1, 0, 1])