Multi-dimensional arrays

.. module:: pyopencl.array

The functionality in this module provides something of a work-alike for :mod:numpy arrays, but with all operations executed on the CL compute device.

Data Types

PyOpenCL provides some amount of integration between the :mod:numpy type system, as represented by :class:numpy.dtype, and the types available in OpenCL. All the simple scalar types map straightforwardly to their CL counterparts.

.. _vector-types:

Vector Types ^^^^^^^^^^^^

.. class :: vec

All of OpenCL's supported vector types, such as `float3` and `long4` are
available as :mod:`numpy` data types within this class. These
:class:`numpy.dtype` instances have field names of `x`, `y`, `z`, and `w`
just like their OpenCL counterparts. They will work both for parameter passing
to kernels as well as for passing data back and forth between kernels and
Python code. For each type, a `make_type` function is also provided (e.g.
`make_float3(x,y,z)`).
If you want to construct a pre-initialized vector type you have three new
functions to choose from:
* `zeros_type()`
* `ones_type()`
* `filled_type(fill_value)`
.. versionadded:: 2014.1
.. versionchanged:: 2014.1
    The `make_type` functions have a default value (0) for each component.
    Relying on the default values has been deprecated. Either specify all
    components or use one of th new flavors mentioned above for constructing
    a vector.

Custom data types ^^^^^^^^^^^^^^^^^

If you would like to use your own (struct/union/whatever) data types in array operations where you supply operation source code, define those types in the preamble passed to :class:pyopencl.elementwise.ElementwiseKernel, :class:pyopencl.reduction.ReductionKernel (or similar), and let PyOpenCL know about them using this function:

.. currentmodule:: pyopencl.tools

.. autofunction:: get_or_register_dtype

.. exception:: TypeNameNotKnown

.. versionadded:: 2013.1

.. function:: register_dtype(dtype, name)

.. versionchanged:: 2013.1
    This function has been deprecated. It is recommended that you develop
    against the new interface, :func:`get_or_register_dtype`.

.. function:: dtype_to_ctype(dtype)

Returns a C name registered for *dtype*.
.. versionadded: 2013.1

This function helps with producing C/OpenCL declarations for structured :class:numpy.dtype instances:

.. autofunction:: match_dtype_to_c_struct

A more complete example of how to use custom structured types can be found in :file:examples/demo-struct-reduce.py in the PyOpenCL distribution.

.. currentmodule:: pyopencl.array

Complex Numbers ^^^^^^^^^^^^^^^

PyOpenCL’s :class:Array type supports complex numbers out of the box, by simply using the corresponding :mod:numpy types.

If you would like to use this support in your own kernels, here’s how to proceed: Since OpenCL 1.2 (and earlier) do not specify native complex number support, PyOpenCL works around that deficiency. By saying::

#include <pyopencl-complex.h>

in your kernel, you get complex types cfloat_t and cdouble_t, along with functions defined on them such as cfloat_mul(a, b) or cdouble_log(z). Elementwise kernels automatically include the header if your kernel has complex input or output. See the source file <https://github.com/inducer/pyopencl/blob/master/pyopencl/cl/pyopencl-complex.h>_ for a precise list of what’s available.

If you need double precision support, please::

#define PYOPENCL_DEFINE_CDOUBLE

before including the header, as DP support apparently cannot be reliably autodetected.

Under the hood, the complex types are struct types as defined in the header. Ideally, you should only access the structs through the provided functions, never directly.

.. versionadded:: 2012.1

.. versionchanged:: 2015.2

**[INCOMPATIBLE]** Changed PyOpenCL's complex numbers from ``float2`` and
``double2`` OpenCL vector types to custom ``struct``. This was changed
because it very easily introduced bugs where
* complex*complex
* real+complex
*look* like they may do the right thing, but silently do the wrong thing.

The :class:Array Class

.. autoclass:: Array

.. autoexception:: ArrayHasOffsetError

Constructing :class:Array Instances ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. autofunction:: to_device .. function:: empty(queue, shape, dtype, order=”C”, allocator=None, data=None)

A synonym for the :class:`Array` constructor.

.. autofunction:: zeros .. autofunction:: empty_like .. autofunction:: zeros_like .. autofunction:: arange .. autofunction:: take .. autofunction:: concatenate

Manipulating :class:Array instances ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

.. autofunction:: transpose .. autofunction:: reshape

Conditionals ^^^^^^^^^^^^

.. autofunction:: if_positive .. autofunction:: maximum .. autofunction:: minimum

.. _reductions:

Reductions ^^^^^^^^^^

.. autofunction:: sum .. autofunction:: dot .. autofunction:: vdot .. autofunction:: subset_dot .. autofunction:: max .. autofunction:: min .. autofunction:: subset_max .. autofunction:: subset_min

See also :ref:custom-reductions.

Elementwise Functions on :class:Array Instances

.. module:: pyopencl.clmath

The :mod:pyopencl.clmath module contains exposes array versions of the C functions available in the OpenCL standard. (See table 6.8 in the spec.)

.. function:: acos(array, queue=None) .. function:: acosh(array, queue=None) .. function:: acospi(array, queue=None)

.. function:: asin(array, queue=None) .. function:: asinh(array, queue=None) .. function:: asinpi(array, queue=None)

.. function:: atan(array, queue=None) .. autofunction:: atan2 .. function:: atanh(array, queue=None) .. function:: atanpi(array, queue=None) .. autofunction:: atan2pi

.. function:: cbrt(array, queue=None) .. function:: ceil(array, queue=None) .. TODO: copysign

.. function:: cos(array, queue=None) .. function:: cosh(array, queue=None) .. function:: cospi(array, queue=None)

.. function:: erfc(array, queue=None) .. function:: erf(array, queue=None) .. function:: exp(array, queue=None) .. function:: exp2(array, queue=None) .. function:: exp10(array, queue=None) .. function:: expm1(array, queue=None)

.. function:: fabs(array, queue=None) .. TODO: fdim .. function:: floor(array, queue=None) .. TODO: fma .. TODO: fmax .. TODO: fmin

.. function:: fmod(arg, mod, queue=None)

Return the floating point remainder of the division `arg/mod`,
for each element in `arg` and `mod`.

.. TODO: fract

.. function:: frexp(arg, queue=None)

Return a tuple `(significands, exponents)` such that
`arg == significand * 2**exponent`.

.. TODO: hypot

.. function:: ilogb(array, queue=None) .. function:: ldexp(significand, exponent, queue=None)

Return a new array of floating point values composed from the
entries of `significand` and `exponent`, paired together as
`result = significand * 2**exponent`.

.. function:: lgamma(array, queue=None) .. TODO: lgamma_r

.. function:: log(array, queue=None) .. function:: log2(array, queue=None) .. function:: log10(array, queue=None) .. function:: log1p(array, queue=None) .. function:: logb(array, queue=None)

.. TODO: mad .. TODO: maxmag .. TODO: minmag

.. function:: modf(arg, queue=None)

Return a tuple `(fracpart, intpart)` of arrays containing the
integer and fractional parts of `arg`.

.. function:: nan(array, queue=None)

.. TODO: nextafter .. TODO: remainder .. TODO: remquo

.. function:: rint(array, queue=None) .. TODO: rootn .. function:: round(array, queue=None)

.. function:: sin(array, queue=None) .. TODO: sincos .. function:: sinh(array, queue=None) .. function:: sinpi(array, queue=None)

.. function:: sqrt(array, queue=None)

.. function:: tan(array, queue=None) .. function:: tanh(array, queue=None) .. function:: tanpi(array, queue=None) .. function:: tgamma(array, queue=None) .. function:: trunc(array, queue=None)

Generating Arrays of Random Numbers

.. automodule:: pyopencl.clrandom