MKL FFT
=======

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    <p>The speed-boosted variants of NumPy&#8217;s FFT operations are accessible in the
    <code class="docutils literal"><span class="pre">numpy.fft</span></code> package, and the <code class="docutils literal"><span class="pre">accelerate.mkl.fftpack</span></code> package. The following
    functions in these packages are accelerated using MKL:</p>
    <table border="1" class="docutils">
    <colgroup>
    <col width="41%" />
    <col width="59%" />
    </colgroup>
    <thead valign="bottom">
    <tr class="row-odd"><th class="head">Function</th>
    <th class="head">Description</th>
    </tr>
    </thead>
    <tbody valign="top">
    <tr class="row-even"><td><code class="docutils literal"><span class="pre">fft(a,</span> <span class="pre">n=None,</span> <span class="pre">axis=-1)</span></code></td>
    <td>1-dimensional forward transform</td>
    </tr>
    <tr class="row-odd"><td><code class="docutils literal"><span class="pre">ifft(a,</span> <span class="pre">n=None,</span> <span class="pre">axis=-1)</span></code></td>
    <td>1-dimensional inverse transform</td>
    </tr>
    <tr class="row-even"><td><code class="docutils literal"><span class="pre">rfft(a,</span> <span class="pre">n=None,</span> <span class="pre">axis=-1)</span></code></td>
    <td>1-dimensional forward transform of purely real data</td>
    </tr>
    <tr class="row-odd"><td><code class="docutils literal"><span class="pre">irfft(a,</span> <span class="pre">n=None,</span> <span class="pre">axis=-1)</span></code></td>
    <td>1-dimensional inverse transform of purely real data</td>
    </tr>
    <tr class="row-even"><td><code class="docutils literal"><span class="pre">hfft(a,</span> <span class="pre">n=None,</span> <span class="pre">axis=-1)</span></code></td>
    <td>Hermite transform</td>
    </tr>
    <tr class="row-odd"><td><code class="docutils literal"><span class="pre">ihfft(a,</span> <span class="pre">n=None,</span> <span class="pre">axis=-1)</span></code></td>
    <td>Inverse Hermite transform</td>
    </tr>
    <tr class="row-even"><td><code class="docutils literal"><span class="pre">fftn(a,</span> <span class="pre">s=None,</span> <span class="pre">axes=None)</span></code></td>
    <td>N-dimensional forward transform</td>
    </tr>
    <tr class="row-odd"><td><code class="docutils literal"><span class="pre">ifftn(a,</span> <span class="pre">s=None,</span> <span class="pre">axes=None)</span></code></td>
    <td>N-dimensional inverse transform</td>
    </tr>
    <tr class="row-even"><td><code class="docutils literal"><span class="pre">fft2(a,</span> <span class="pre">s=None,</span> <span class="pre">axes=(-2,</span> <span class="pre">-1))</span></code></td>
    <td>2-dimensional forward transform</td>
    </tr>
    <tr class="row-odd"><td><code class="docutils literal"><span class="pre">ifft2(a,</span> <span class="pre">s=None,</span> <span class="pre">axes=(-2,</span> <span class="pre">-1))</span></code></td>
    <td>2-dimensional inverse transform</td>
    </tr>
    <tr class="row-even"><td><code class="docutils literal"><span class="pre">rfftn(a,</span> <span class="pre">s=None,</span> <span class="pre">axes=None)</span></code></td>
    <td>N-dimensional forward transform of purely real data</td>
    </tr>
    <tr class="row-odd"><td><code class="docutils literal"><span class="pre">rfft2(a,</span> <span class="pre">s=None,</span> <span class="pre">axes=(-2,</span> <span class="pre">-1))</span></code></td>
    <td>2-dimensional forward transform of purely real data</td>
    </tr>
    <tr class="row-even"><td><code class="docutils literal"><span class="pre">irfftn(a,</span> <span class="pre">s=None,</span> <span class="pre">axes=None)</span></code></td>
    <td>N-dimensional inverse transform of purely real data</td>
    </tr>
    <tr class="row-odd"><td><code class="docutils literal"><span class="pre">irfft2(a,</span> <span class="pre">s=None,</span> <span class="pre">axes=(-2,</span> <span class="pre">-1))</span></code></td>
    <td>2-dimensional inverse transform of purely real data</td>
    </tr>
    </tbody>
    </table>
    <p>For further information on these functions, please refer to the Numpy
    documentation: <code class="xref py py-mod docutils literal"><span class="pre">numpy.fft</span></code>.</p>

