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‎arrayfire/__init__.py‎

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########################################################
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"""
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A high performance scientific computing library for CUDA, OpenCL and CPU devices.
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ArrayFire is a high performance scientific computing library with an easy to use API.
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The functionality provided by ArrayFire spans the following domains:
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1. Vector Algorithms
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2. Image Processing
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3. Signal Processing
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4. Computer Vision
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5. Linear Algebra
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6. Statistics
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>>> # Monte Carlo estimation of pi
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>>> def calc_pi_device(samples):
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# Simple, array based API
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# Generate uniformly distributed random numers
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x = af.randu(samples)
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y = af.randu(samples)
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# Supports Just In Time Compilation
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# The following line generates a single kernel
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within_unit_circle = (x * x + y * y) < 1
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# Intuitive function names
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return 4 * af.count(within_unit_circle) / samples
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Programs written using ArrayFire are portable across CUDA, OpenCL and CPU devices
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Programs written using ArrayFire are portable across CUDA, OpenCL and CPU devices.
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The default backend is chosen in the following order of preference based on the available libraries:
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>>> af.backend.set(name)
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where name is one of 'cuda', 'opencl' or 'cpu'
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where name is one of 'cuda', 'opencl' or 'cpu'.
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The functionality provided by ArrayFire spans the following domains:
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1. Vector Algorithms
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2. Image Processing
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3. Signal Processing
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4. Computer Vision
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5. Linear Algebra
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6. Statistics
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"""
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‎arrayfire/algorithm.py‎

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########################################################
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"""
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Vector algorithms for ArrayFire
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Vector algorithms (sum, min, sort, etc).
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"""
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from .library import *
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def accum(a, dim=0):
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"""
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Cumulative sum of an array along a specified dimension.
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Cumulative sum of an array along a specified dimension
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Parameters
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----------

‎arrayfire/arith.py‎

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########################################################
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"""
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Math functions for ArrayFire
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Math functions (sin, sqrt, exp, etc).
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"""
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from .library import *

‎arrayfire/array.py‎

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"""
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arrayfire.Array class and helper functions.
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Array class and helper functions.
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"""
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import inspect
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Return the device pointer exclusively held by the array.
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Returns
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------
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--------
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ptr : int
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Contains location of the device pointer
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Return the device pointer held by the array.
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Returns
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--------
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ptr : int
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Contains location of the device pointer
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Return the offset, of the first element relative to the raw pointer.
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Returns
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--------
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offset : int
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The offset in number of elements
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"""
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Return the distance in bytes between consecutive elements for each dimension.
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Returns
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--------
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strides : tuple
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The strides for each dimension
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"""
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Return the data as a ctype C array after copying to host memory
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Parameters
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---------
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-----------
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row_major: optional: bool. default: False.
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Specifies if a transpose needs to occur before copying to host memory.
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Return the data as array.array
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Parameters
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-----------
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row_major: optional: bool. default: False.
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Specifies if a transpose needs to occur before copying to host memory.
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Return the data as list
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-----------
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row_major: optional: bool. default: False.
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Specifies if a transpose needs to occur before copying to host memory.

‎arrayfire/blas.py‎

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"""
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BLAS functions for arrayfire.
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BLAS functions (matmul, dot, etc)
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"""
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from .library import *

‎arrayfire/data.py‎

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An array containing the input arrays joined along the specified dimension.
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Examples
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-------
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>>> import arrayfire as af
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>>> a = af.randu(2, 3)
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An array containing the input after tiling the the specified number of times.
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>>> import arrayfire as af
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The output after flipping `a` along `dim`.
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Examples
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>>> import arrayfire as af
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>>> a = af.randu(3, 3)

‎arrayfire/device.py‎

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Change the active device to the specified id.
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num: int.
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id of the desired device.
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"""
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Check if double precision is supported on specified device.
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id of the desired device.
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Block until all the functions on the device have completed execution.
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device: optional: int. default: None.
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id of the desired device.
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"""

‎arrayfire/features.py‎

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# http://arrayfire.com/licenses/BSD-3-Clause
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########################################################
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"""
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arrayfire.Features class
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Features class used for Computer Vision algorithms.
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"""
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from .library import *
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from .array import *

‎arrayfire/graphics.py‎

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"""
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graphics functions for arrayfire
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Graphics functions (plot, image, etc).
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"""
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from .library import *

‎arrayfire/image.py‎

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"""
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Image processing functions for arrayfire.
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Image processing functions.
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"""
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from .library import *

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