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Support sparse #14

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Commits on Nov 15, 2019

  1. Remove unneeded copying.

    When algorithm operates by modifying the input array in place, it is
    good manners to make a copy first so that the function does not mutate
    user input. I am guessing that that was the motivation for the use of
    `copy()` here.
    
    However, as far as I can tell, this algorithm does not modify `signal`
    (or its alias `a`) in place. It reassigns the variable `a` in a loop,
    but does not actually modify the input array object.
    
    Therefore, we can remove this copying and increase the speed. Also, note
    that the call to `np.array` explicitly cast the input to a literal numpy
    array. By removing that from the code, we accept dask arrays and cupy
    arrays and allow them to flow through the algorithm via the NEP-18 numpy
    dispatch mechanism.
    danielballan committed Nov 15, 2019
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  2. Use ndim.

    danielballan committed Nov 15, 2019
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Commits on Feb 6, 2020

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Commits on Feb 7, 2020

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