nparray.zeros (function)


def zeros(shape, unit=None)

This is an nparray wrapper around the numpy function. The numpy documentation is included below. Currently most kwargs should be accepted with the exception of 'dtype'. The returned object should act exactly like the numpy array itself, but with several extra helpful methods and attributes. Call help on the resulting object for more information.

If you have astropy installed, units are supported by passing unit=astropy.unit to the instantiation functions or by multiplying an array with a unit object.

See also:

Arguments

  • shape (int or sequence of ints): Shape of the new array, e.g., (2, 3) or 2.
  • unit (astropy unit or string, optional, default=None): unit corresponding to the passed values.

Returns

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numpy documentation for underlying function:

zeros(shape, dtype=float, order='C')

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

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., `numpy.int8`.  Default is
    `numpy.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.

Returns
-------
out : ndarray
    Array of zeros with the given shape, dtype, and order.

See Also
--------
zeros_like : Return an array of zeros with shape and type of input.
empty : Return a new uninitialized array.
ones : Return a new array setting values to one.
full : Return a new array of given shape filled with value.

Examples
--------
>>> np.zeros(5)
array([ 0.,  0.,  0.,  0.,  0.])

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

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

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

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