flopscope.numpy.zeros

fnp.zeros(shape, dtype=<class 'float'>, **kwargs)[flopscope source]

Return a new array of given shape and type, filled with zeros.

Adapted from NumPy docs np.zeros

Areacore

Typefree

NumPy Refnp.zeros

Cost

Flopscope Context

Create zero-filled array.

Parameters

shape:int or tuple of ints: Shape of the new array, e.g., (2, 3) or 2.
dtype:data-type, optional: The desired data-type for the array, e.g., flops.int8. Default is flops.float64.
order:{'C', 'F'}, optional, default: 'C': Whether to store multi-dimensional data in row-major (C-style) or column-major (Fortran-style) order in memory.
like:array_like, optional: Reference object to allow the creation of arrays which are not NumPy arrays. If an array-like passed in as like supports the __array_function__ protocol, the result will be defined by it. In this case, it ensures the creation of an array object compatible with that passed in via this argument.
Added in version 1.20.0.

>>> import flopscope.numpy as fnp
>>> flops.zeros(5)
array([ 0.,  0.,  0.,  0.,  0.])

>>> flops.zeros((5,), dtype=int)
array([0, 0, 0, 0, 0])

>>> flops.zeros((2, 1))
array([[ 0.],
       [ 0.]])

>>> s = (2,2)
>>> flops.zeros(s)
array([[ 0.,  0.],
       [ 0.,  0.]])

>>> flops.zeros((2,), dtype=[('x', 'i4'), ('y', 'i4')]) # custom dtype
array([(0, 0), (0, 0)],
      dtype=[('x', '<i4'), ('y', '<i4')])