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    <p><strong>EDIT</strong> The following code does allow to perform a convolution based check of equality. It maps <code>True</code> to <code>1</code> and <code>False</code> to <code>-1</code>. It also reverses <code>b</code>, which is needed for it to work properly:</p> <pre><code>def search(a, b) : return np.where(np.round(fftconvolve(a * 2 - 1, (b * 2 - 1)[::-1], mode='valid') - len(b)) == 0)[0] </code></pre> <p>I have checked that it gives the same output as the <code>as_strided</code> method for a variety of random inputs, which it does. I have also timed both approached, and convolution only starts paying off with largish search tokens of around 256 items.</p> <hr> <p>It seems like a little overkill, but with boolean data you can use (abuse?) convolution:</p> <pre><code>In [8]: np.where(np.convolve(may_a, may_b.astype(int), ...: mode='valid') == may_b.sum())[0] Out[8]: array([2, 7]) </code></pre> <p>For larger datasets it may be faster to go with <code>scipy.signal.fftconvolve</code>:</p> <pre><code>In [13]: np.where(scipy.signal.fftconvolve(may_a, may_b, ....: mode='valid') == may_b.sum())[0] Out[13]: array([2, 7]) </code></pre> <p>You have to be careful though, because the output now is floating point, and rounding may spoil the equality check:</p> <pre><code>In [14]: scipy.signal.fftconvolve(may_a, may_b, mode='valid') Out[14]: array([ 1., 1., 2., 1., 1., 1., 1., 2.]) </code></pre> <p>So you may be better off with something along the lines of:</p> <pre><code>In [15]: np.where(np.round(scipy.signal.fftconvolve(may_a, may_b, mode='valid') - ....: may_b.sum()) == 0)[0] Out[15]: array([2, 7]) </code></pre>
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    1. COWith This convolution you'll match anything that is `[*, True, True, *]` where `*` is a wildcard.
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    2. CO@BiRico Oops, you are absolutely right! There may be a chance to salvage the method, by mapping the `True`'s and the `False`'s to some integer value, possibly `+1` and `-1`.
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    3. CO@Jaime `>>> may_a = np.array([True,True,True,True]) >>> out_ind = np.where(np.convolve(may_a, may_b.astype(int),mode='valid') == may_b.sum())[0] >>> out_ind -> array([0])` it is incorrect(
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