dpnp.ogrid

dpnp.ogrid = <dpnp.dpnp_iface_arraycreation.OGridClass object>

Construct an open multi-dimensional "meshgrid".

For full documentation refer to numpy.ogrid.

Parameters:

device ({None, string, SyclDevice, SyclQueue}, optional) -- An array API concept of device where the output array is created. The device can be None (the default), an OneAPI filter selector string, an instance of dpctl.SyclDevice corresponding to a non-partitioned SYCL device, an instance of dpctl.SyclQueue, or a Device object returned by dpnp.dpnp_array.dpnp_array.device property.
usm_type ({None, "device", "shared", "host"}, optional) -- The type of SYCL USM allocation for the output array. Default: "device".
sycl_queue ({None, SyclQueue}, optional) -- A SYCL queue to use for output array allocation and copying. The sycl_queue can be passed as None (the default), which means to get the SYCL queue from device keyword if present or to use a default queue. Default: None.

Returns:

out -- Returns a tuple of arrays, with grid[i].shape = (1, ..., 1, dimensions[i], 1, ..., 1) with dimensions[i] in the i-th place.

Return type:

one dpnp.ndarray or tuple of dpnp.ndarray

Examples

>>> import dpnp as np
>>> np.ogrid[0:5, 0:5]
[array([[0],
        [1],
        [2],
        [3],
        [4]]), array([[0, 1, 2, 3, 4]])]

Creating an array on a different device or with a specified usm_type

>>> x = np.ogrid[-1:1:5j] # default case
>>> x, x.device, x.usm_type
(array([-1. , -0.5,  0. ,  0.5,  1. ]), Device(level_zero:gpu:0), 'device')

>>> y = np.ogrid(device="cpu")[-1:1:5j]
>>> y, y.device, y.usm_type
(array([-1. , -0.5,  0. ,  0.5,  1. ]), Device(opencl:cpu:0), 'device')

>>> z = np.ogrid(usm_type="host")[-1:1:5j]
>>> z, z.device, z.usm_type
(array([-1. , -0.5,  0. ,  0.5,  1. ]), Device(level_zero:gpu:0), 'host')