How to create new numpy array by using a function on every row with no loops









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so I've got a project which asks of me to use a DFT function that I've built (on an array of size [N,1]) and use that function on an entire image of size [N,M].



I've been asked to do so using no loops and I can't figure it out.
Is there a way to use a function on each one of my rows which returns a new row and that way build a new numpy array without loops?










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  • Sounds like you're looking for numpy.apply_along_axis
    – jwil
    Nov 9 at 21:28






  • 1




    Hey, so numpy.apply_along_axis uses a for loop internally and is slow, I've already tested it and I wasn't very happy with the results.
    – edan patt
    Nov 9 at 21:30














up vote
0
down vote

favorite












so I've got a project which asks of me to use a DFT function that I've built (on an array of size [N,1]) and use that function on an entire image of size [N,M].



I've been asked to do so using no loops and I can't figure it out.
Is there a way to use a function on each one of my rows which returns a new row and that way build a new numpy array without loops?










share|improve this question





















  • Sounds like you're looking for numpy.apply_along_axis
    – jwil
    Nov 9 at 21:28






  • 1




    Hey, so numpy.apply_along_axis uses a for loop internally and is slow, I've already tested it and I wasn't very happy with the results.
    – edan patt
    Nov 9 at 21:30












up vote
0
down vote

favorite









up vote
0
down vote

favorite











so I've got a project which asks of me to use a DFT function that I've built (on an array of size [N,1]) and use that function on an entire image of size [N,M].



I've been asked to do so using no loops and I can't figure it out.
Is there a way to use a function on each one of my rows which returns a new row and that way build a new numpy array without loops?










share|improve this question













so I've got a project which asks of me to use a DFT function that I've built (on an array of size [N,1]) and use that function on an entire image of size [N,M].



I've been asked to do so using no loops and I can't figure it out.
Is there a way to use a function on each one of my rows which returns a new row and that way build a new numpy array without loops?







python-3.x image-processing computer-science






share|improve this question













share|improve this question











share|improve this question




share|improve this question










asked Nov 9 at 21:26









edan patt

1




1











  • Sounds like you're looking for numpy.apply_along_axis
    – jwil
    Nov 9 at 21:28






  • 1




    Hey, so numpy.apply_along_axis uses a for loop internally and is slow, I've already tested it and I wasn't very happy with the results.
    – edan patt
    Nov 9 at 21:30
















  • Sounds like you're looking for numpy.apply_along_axis
    – jwil
    Nov 9 at 21:28






  • 1




    Hey, so numpy.apply_along_axis uses a for loop internally and is slow, I've already tested it and I wasn't very happy with the results.
    – edan patt
    Nov 9 at 21:30















Sounds like you're looking for numpy.apply_along_axis
– jwil
Nov 9 at 21:28




Sounds like you're looking for numpy.apply_along_axis
– jwil
Nov 9 at 21:28




1




1




Hey, so numpy.apply_along_axis uses a for loop internally and is slow, I've already tested it and I wasn't very happy with the results.
– edan patt
Nov 9 at 21:30




Hey, so numpy.apply_along_axis uses a for loop internally and is slow, I've already tested it and I wasn't very happy with the results.
– edan patt
Nov 9 at 21:30

















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