numpy.ceil

numpy.ceil(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'ceil'>

Return the ceiling of the input, element-wise.

The ceil of the scalar x is the smallest integer i, such that i >= x. It is often denoted as $\lceil x \rceil$ .

Parameters:

Parameters:	`x : array_like` Input data. `out : ndarray, None, or tuple of ndarray and None, 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 : array_like, optional` Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. **kwargs For other keyword-only arguments, see the ufunc docs.
Returns:	`y : ndarray or scalar` The ceiling of each element in `x`, with `float` dtype. This is a scalar if `x` is a scalar.

x : array_like: Input data.
out : ndarray, None, or tuple of ndarray and None, 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 : array_like, optional: Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone.
**kwargs: For other keyword-only arguments, see the ufunc docs.

Returns:

y : ndarray or scalar: The ceiling of each element in x, with float dtype. This is a scalar if x is a scalar.

>>> a = np.array([-1.7, -1.5, -0.2, 0.2, 1.5, 1.7, 2.0])
>>> np.ceil(a)
array([-1., -1., -0.,  1.,  2.,  2.,  2.])