.. currentmodule:: dpnp
The N-dimensional array (:class:`ndarray <ndarray>`)
:class:`ndarray` is the DPNP counterpart of NumPy :class:`numpy.ndarray`.
For the basic concept of ndarrays, please refer to the NumPy documentation.
.. autosummary:: :toctree: generated/ :nosignatures: ndarray dpnp_array.dpnp_array
New arrays can be constructed using the routines detailed in :ref:`Array Creation Routines <routines.array-creation>`, and also by using the low-level :class:`ndarray` constructor:
.. autosummary:: :toctree: generated/ :nosignatures: ndarray
Arrays can be indexed using an extended Python slicing syntax,
array[selection].
.. seealso:: :ref:`Indexing routines <routines.indexing>`.
Array attributes reflect information that is intrinsic to the array itself. Generally, accessing an array through its attributes allows you to get and sometimes set intrinsic properties of the array without creating a new array. The exposed attributes are the core parts of an array and only some of them can be reset meaningfully without creating a new array. Information on each attribute is given below.
The following attributes contain information about the memory layout of the array:
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.flags ndarray.shape ndarray.strides ndarray.ndim ndarray.data ndarray.size ndarray.itemsize ndarray.nbytes ndarray.device ndarray.sycl_context ndarray.sycl_device ndarray.sycl_queue ndarray.usm_type
.. seealso:: :ref:`Available array data types <Data types>`
The data type object associated with the array can be found in the :attr:`dtype <ndarray.dtype>` attribute:
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.dtype
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.T ndarray.mT ndarray.real ndarray.imag ndarray.flat
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.__sycl_usm_array_interface__ ndarray.__usm_ndarray__
An :class:`ndarray` object has many methods which operate on or with the array in some fashion, typically returning an array result. These methods are briefly explained below. (Each method's docstring has a more complete description.)
For the following methods there are also corresponding functions in :mod:`dpnp`: :func:`all <all>`, :func:`any <any>`, :func:`argmax <argmax>`, :func:`argmin <argmin>`, :func:`argpartition <argpartition>`, :func:`argsort <argsort>`, :func:`choose <choose>`, :func:`clip <clip>`, :func:`compress <compress>`, :func:`copy <copy>`, :func:`cumprod <cumprod>`, :func:`cumsum <cumsum>`, :func:`diagonal <diagonal>`, :func:`imag <imag>`, :func:`max <max>`, :func:`mean <mean>`, :func:`min <min>`, :func:`nonzero <nonzero>`, :func:`partition <partition>`, :func:`prod <prod>`, :func:`put <put>`, :func:`ravel <ravel>`, :func:`real <real>`, :func:`repeat <repeat>`, :func:`reshape <reshape>`, :func:`round <around>`, :func:`searchsorted <searchsorted>`, :func:`sort <sort>`, :func:`squeeze <squeeze>`, :func:`std <std>`, :func:`sum <sum>`, :func:`swapaxes <swapaxes>`, :func:`take <take>`, :func:`trace <trace>`, :func:`transpose <transpose>`, :func:`var <var>`.
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.item ndarray.tolist ndarray.tobytes ndarray.tofile ndarray.dump ndarray.dumps ndarray.astype ndarray.byteswap ndarray.copy ndarray.view ndarray.getfield ndarray.setflags ndarray.fill ndarray.get_array
For reshape, resize, and transpose, the single tuple argument may be
replaced with n integers which will be interpreted as an n-tuple.
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.reshape ndarray.resize ndarray.transpose ndarray.swapaxes ndarray.flatten ndarray.ravel ndarray.squeeze
For array methods that take an axis keyword, it defaults to None. If axis is None, then the array is treated as a 1-D array. Any other value for axis represents the dimension along which the operation should proceed.
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.take ndarray.put ndarray.repeat ndarray.choose ndarray.sort ndarray.argsort ndarray.partition ndarray.argpartition ndarray.searchsorted ndarray.nonzero ndarray.compress ndarray.diagonal
Many of these methods take an argument named axis. In such cases,
- If axis is None (the default), the array is treated as a 1-D array and the operation is performed over the entire array. This behavior is also the default if self is a 0-dimensional array.
- If axis is an integer, then the operation is done over the given axis (for each 1-D subarray that can be created along the given axis).
The parameter dtype specifies the data type over which a reduction operation (like summing) should take place. The default reduce data type is the same as the data type of self. To avoid overflow, it can be useful to perform the reduction using a larger data type.
For several methods, an optional out argument can also be provided and the result will be placed into the output array given. The out argument must be an :class:`ndarray` and have the same number of elements as the result array. It can have a different data type in which case casting will be performed.
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.max ndarray.argmax ndarray.min ndarray.argmin ndarray.clip ndarray.conj ndarray.conjugate ndarray.round ndarray.trace ndarray.sum ndarray.cumsum ndarray.mean ndarray.var ndarray.std ndarray.prod ndarray.cumprod ndarray.all ndarray.any
Arithmetic and comparison operations on :class:`ndarrays <ndarray>` are defined as element-wise operations, and generally yield :class:`ndarray` objects as results.
Each of the arithmetic operations (+, -, *, /, //, %,
divmod(), ** or pow(), <<, >>, &, ^, |, ~)
and the comparisons (==, <, >, <=, >=, !=) is
equivalent to the corresponding universal function (or :term:`ufunc` for short)
in DPNP. For more information, see the section on :ref:`Universal Functions
<ufuncs>`.
Comparison operators:
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.__lt__ ndarray.__le__ ndarray.__gt__ ndarray.__ge__ ndarray.__eq__ ndarray.__ne__
Truth value of an array (:class:`bool() <bool>`):
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.__bool__
Note
Truth-value testing of an array invokes
:meth:`ndarray.__bool__`, which raises an error if the number of
elements in the array is not 1, because the truth value
of such arrays is ambiguous. Use :meth:`.any() <ndarray.any>` and
:meth:`.all() <ndarray.all>` instead to be clear about what is meant
in such cases. (If you wish to check for whether an array is empty,
use for example .size > 0.)
Unary operations:
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.__neg__ ndarray.__pos__ ndarray.__abs__ ndarray.__invert__
Arithmetic:
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.__add__ ndarray.__sub__ ndarray.__mul__ ndarray.__truediv__ ndarray.__floordiv__ ndarray.__mod__ ndarray.__divmod__ ndarray.__pow__ ndarray.__lshift__ ndarray.__rshift__ ndarray.__and__ ndarray.__or__ ndarray.__xor__
Arithmetic, reflected:
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.__radd__ ndarray.__rsub__ ndarray.__rmul__ ndarray.__rtruediv__ ndarray.__rfloordiv__ ndarray.__rmod__ ndarray.__rdivmod__ ndarray.__rpow__ ndarray.__rlshift__ ndarray.__rrshift__ ndarray.__rand__ ndarray.__ror__ ndarray.__rxor__
Arithmetic, in-place:
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.__iadd__ ndarray.__isub__ ndarray.__imul__ ndarray.__itruediv__ ndarray.__ifloordiv__ ndarray.__imod__ ndarray.__ipow__ ndarray.__ilshift__ ndarray.__irshift__ ndarray.__iand__ ndarray.__ior__ ndarray.__ixor__
Matrix Multiplication:
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.__matmul__ ndarray.__rmatmul__ ndarray.__imatmul__
For standard library functions:
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.__copy__ ndarray.__deepcopy__ .. ndarray.__reduce__ ndarray.__setstate__
Basic customization:
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.__new__ ndarray.__array__ ndarray.__array_namespace__ ndarray.__array_wrap__ ndarray.__dlpack__ ndarray.__dlpack_device__
Container customization: (see :ref:`Indexing <routines.indexing>`)
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.__len__ ndarray.__iter__ ndarray.__getitem__ ndarray.__setitem__ ndarray.__contains__
Conversion; the operations :class:`int() <int>`, :class:`float() <float>`, :class:`complex() <complex>` and :func:`operator.index() <operator.index>`. They work only on arrays that have one element in them and return the appropriate scalar.
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.__bytes__ ndarray.__index__ ndarray.__int__ ndarray.__float__ ndarray.__complex__
String representations:
.. autosummary:: :toctree: generated/ :nosignatures: ndarray.__str__ ndarray.__repr__ ndarray.__format__