tensorly
.zeros
- zeros(shape, dtype=float, order='C', *, like=None)
Return a new array of given shape and type, filled with zeros.
- Parameters:
- shapeint or tuple of ints
Shape of the new array, e.g.,
(2, 3)
or2
.- dtypedata-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.
- likearray_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.New in version 1.20.0.
- Returns:
- outndarray
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')])