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Fixed warnings, minor updates
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dev-requirements.txt

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# Allows documentation
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sphinx>=7.3.7
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sphinxawesome_theme>=5.2.0
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sphinx_collapse>=0.1.3

docs/conf.py

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# https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information
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project = 'ArrayFire'
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copyright = '2024, Michael Egwuatu'
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author = 'Michael Egwuatu'
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release = '6/11/2024'
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copyright = '2024, ArrayFire'
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author = 'ArrayFire'
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release = ''
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# -- General configuration ---------------------------------------------------
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# https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration
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html_static_path = ['_static']
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html_permalinks = False
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# -- Suppress specific warnings --------------------------------------------
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suppress_warnings = [
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'ref.include_missing',
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]

docs/examples.rst

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========
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Introduction
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------------
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This is the introductory section of File 1.
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Modules
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-------
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Here is some content for the first section.
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Mod
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~~~
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This is a subsection under Section 1.
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Mod1
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~~~~
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More content for the second section.
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Mod2
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~~~~
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This concludes the content of File 1.
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Mod3
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~~~~
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Mod4
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~~~~
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TO DO
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-----
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ADD LIST OF EXAMPLES

docs/functions/device.rst

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- Getting the Current Device: Retrieve the index of the currently selected device.
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- Setting the Current Device: Select a specific device for computations.
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- Querying Device Properties: Obtain information about the current device.
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This functionality is important for applications that need to explicitly choose between multiple GPUs or check device capabilities.
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Function Documentation

docs/functions/fft.rst

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- Signal Processing: Analyzing the frequency components of a signal.
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- Image Processing: Transforming images to the frequency domain for various processing tasks.
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- Numerical Analysis: Solving differential equations and other problems where Fourier methods are applicable.
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The function supports:
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- 1D FFT: Transforming 1D arrays (vectors).
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- 2D FFT: Transforming 2D arrays (matrices).
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- 3D FFT: Transforming 3D arrays (volumes).
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- Multi-dimensional FFTs: Transforming arrays of higher dimensions.
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The FFT can be computed along specified dimensions or all dimensions of the input array.
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Function Documentation

docs/functions/index.rst

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.. toctree::
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:maxdepth: 2
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:caption: Functions:
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transpose
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array
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ones
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zeros
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sum
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subtract
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sttdev
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randu
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randn
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det
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device
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divide
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dot
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eig
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fft
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get
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get_device
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inv
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join
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matmul
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max
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mean
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median
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min
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multiply
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prod
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reorder
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set_device
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slice
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sqrt
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add
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exp
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log
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ifft
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reshape

docs/functions/join.rst

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.. sidebar:: af.join()
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Syntax:
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af.join(dim, *arrays)
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af.join(dim, \*arrays)
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Parameters:
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'dim': The dimension along which the arrays will be concatenated. This is an integer indicating the axis along which the join operation will take place.
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'*arrays': The arrays to be concatenated. These can be 1D, 2D, or higher-dimensional arrays, and they must be compatible in all dimensions except the specified dimension.
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'\*arrays': The arrays to be concatenated. These can be 1D, 2D, or higher-dimensional arrays, and they must be compatible in all dimensions except the specified dimension.
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Returns:
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An ArrayFire array that is the result of concatenating the input arrays along the specified dimension.

docs/functions/reorder.rst

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.. sidebar:: af.reorder()
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Syntax:
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af.reorder(array, *order)
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af.reorder(array, \*order)
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Parameters:
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'array': The ArrayFire array whose dimensions are to be reordered.
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'*order': The new order of dimensions specified as a sequence of integers. Each integer represents the index of the dimension in the new order.
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'\*order': The new order of dimensions specified as a sequence of integers. Each integer represents the index of the dimension in the new order.
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Returns:
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An ArrayFire array with the dimensions reordered according to the specified order.

docs/functions/reshape.rst

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.. sidebar:: af.reshape()
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Syntax:
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af.reshape(array,*new_shape)
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af.reshape(array,\*new_shape)
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Parameters:
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'array': The ArrayFire array to be reshaped.
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'*new_shape': The new shape for the array, specified as a sequence of integers. The product of these dimensions must equal the total number of elements in the original array.
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'\*new_shape': The new shape for the array, specified as a sequence of integers. The product of these dimensions must equal the total number of elements in the original array.
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Returns:
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An ArrayFire array with the specified new shape.

docs/functions/slice.rst

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.. sidebar:: af.slice()
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Syntax:
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af.slice(array, *start_indices, *end_indices)
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af.slice(array, \*start_indices, \*end_indices)
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Parameters:
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'array': The ArrayFire array from which the subarray will be extracted.
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'*start_indices': A sequence of integers specifying the starting indices for each dimension.
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'*end_indices': A sequence of integers specifying the ending indices for each dimension.
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'\*start_indices': A sequence of integers specifying the starting indices for each dimension.
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'\*end_indices': A sequence of integers specifying the ending indices for each dimension.
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Returns:
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An ArrayFire array containing the extracted subarray.

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