NumPy - How to broadcast arrays of different shapes











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I have a 200 x 200 array of vectors. Its shape is (200, 200, 3).



I also have an array of 22 vectors. Its shape is (22,3).



I want to subtract all 22 vectors in the second array from each vector in the first array. The output should have shape (200, 200, 22, 3).



I'd like to perform an operation like



first - second


But I get the error



*** ValueError: operands could not be broadcast together with shapes (200,200,3) (22,3)


I think I need to pad the first array somehow in order to allow NumPy to broadcast the arrays together. How do I tell NumPy how to perform the broadcast?










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  • Doesn't subtracting 3D vectors produce another 3D vector? How is the output shape (200, 200, 22)? Shoudn't it be (200, 200, 22, 3)?
    – eozd
    Nov 19 at 21:22












  • You're right, fixed.
    – bcattle
    Nov 19 at 21:23






  • 3




    first[:,:,None,:] - second; or to be a bit more explicit first[:,:,None,:] - second[None,None,:,:]. In other words imagine where the two arrays have to be expanded to fit in the target (200,200,22,3) array.
    – hpaulj
    Nov 19 at 21:24












  • Works beautifully, thanks
    – bcattle
    Nov 19 at 21:28















up vote
0
down vote

favorite












I have a 200 x 200 array of vectors. Its shape is (200, 200, 3).



I also have an array of 22 vectors. Its shape is (22,3).



I want to subtract all 22 vectors in the second array from each vector in the first array. The output should have shape (200, 200, 22, 3).



I'd like to perform an operation like



first - second


But I get the error



*** ValueError: operands could not be broadcast together with shapes (200,200,3) (22,3)


I think I need to pad the first array somehow in order to allow NumPy to broadcast the arrays together. How do I tell NumPy how to perform the broadcast?










share|improve this question
























  • Doesn't subtracting 3D vectors produce another 3D vector? How is the output shape (200, 200, 22)? Shoudn't it be (200, 200, 22, 3)?
    – eozd
    Nov 19 at 21:22












  • You're right, fixed.
    – bcattle
    Nov 19 at 21:23






  • 3




    first[:,:,None,:] - second; or to be a bit more explicit first[:,:,None,:] - second[None,None,:,:]. In other words imagine where the two arrays have to be expanded to fit in the target (200,200,22,3) array.
    – hpaulj
    Nov 19 at 21:24












  • Works beautifully, thanks
    – bcattle
    Nov 19 at 21:28













up vote
0
down vote

favorite









up vote
0
down vote

favorite











I have a 200 x 200 array of vectors. Its shape is (200, 200, 3).



I also have an array of 22 vectors. Its shape is (22,3).



I want to subtract all 22 vectors in the second array from each vector in the first array. The output should have shape (200, 200, 22, 3).



I'd like to perform an operation like



first - second


But I get the error



*** ValueError: operands could not be broadcast together with shapes (200,200,3) (22,3)


I think I need to pad the first array somehow in order to allow NumPy to broadcast the arrays together. How do I tell NumPy how to perform the broadcast?










share|improve this question















I have a 200 x 200 array of vectors. Its shape is (200, 200, 3).



I also have an array of 22 vectors. Its shape is (22,3).



I want to subtract all 22 vectors in the second array from each vector in the first array. The output should have shape (200, 200, 22, 3).



I'd like to perform an operation like



first - second


But I get the error



*** ValueError: operands could not be broadcast together with shapes (200,200,3) (22,3)


I think I need to pad the first array somehow in order to allow NumPy to broadcast the arrays together. How do I tell NumPy how to perform the broadcast?







numpy numpy-broadcasting numpy-ndarray






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share|improve this question













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edited Nov 19 at 21:23

























asked Nov 19 at 21:15









bcattle

5,94443559




5,94443559












  • Doesn't subtracting 3D vectors produce another 3D vector? How is the output shape (200, 200, 22)? Shoudn't it be (200, 200, 22, 3)?
    – eozd
    Nov 19 at 21:22












  • You're right, fixed.
    – bcattle
    Nov 19 at 21:23






  • 3




    first[:,:,None,:] - second; or to be a bit more explicit first[:,:,None,:] - second[None,None,:,:]. In other words imagine where the two arrays have to be expanded to fit in the target (200,200,22,3) array.
    – hpaulj
    Nov 19 at 21:24












  • Works beautifully, thanks
    – bcattle
    Nov 19 at 21:28


















  • Doesn't subtracting 3D vectors produce another 3D vector? How is the output shape (200, 200, 22)? Shoudn't it be (200, 200, 22, 3)?
    – eozd
    Nov 19 at 21:22












  • You're right, fixed.
    – bcattle
    Nov 19 at 21:23






  • 3




    first[:,:,None,:] - second; or to be a bit more explicit first[:,:,None,:] - second[None,None,:,:]. In other words imagine where the two arrays have to be expanded to fit in the target (200,200,22,3) array.
    – hpaulj
    Nov 19 at 21:24












  • Works beautifully, thanks
    – bcattle
    Nov 19 at 21:28
















Doesn't subtracting 3D vectors produce another 3D vector? How is the output shape (200, 200, 22)? Shoudn't it be (200, 200, 22, 3)?
– eozd
Nov 19 at 21:22






Doesn't subtracting 3D vectors produce another 3D vector? How is the output shape (200, 200, 22)? Shoudn't it be (200, 200, 22, 3)?
– eozd
Nov 19 at 21:22














You're right, fixed.
– bcattle
Nov 19 at 21:23




You're right, fixed.
– bcattle
Nov 19 at 21:23




3




3




first[:,:,None,:] - second; or to be a bit more explicit first[:,:,None,:] - second[None,None,:,:]. In other words imagine where the two arrays have to be expanded to fit in the target (200,200,22,3) array.
– hpaulj
Nov 19 at 21:24






first[:,:,None,:] - second; or to be a bit more explicit first[:,:,None,:] - second[None,None,:,:]. In other words imagine where the two arrays have to be expanded to fit in the target (200,200,22,3) array.
– hpaulj
Nov 19 at 21:24














Works beautifully, thanks
– bcattle
Nov 19 at 21:28




Works beautifully, thanks
– bcattle
Nov 19 at 21:28

















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