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numpy.ma.outerproduct(a, b)[source] -
Compute the outer product of two vectors.
Given two vectors,
a = [a0, a1, ..., aM]andb = [b0, b1, ..., bN], the outer product [R51] is:1234[[a0*b0 a0*b1 ... a0*bN ][a1*b0 .[ ... .[aM*b0 aM*bN ]]Parameters: a : (M,) array_like
First input vector. Input is flattened if not already 1-dimensional.
b : (N,) array_like
Second input vector. Input is flattened if not already 1-dimensional.
out : (M, N) ndarray, optional
A location where the result is stored
New in version 1.9.0.
Returns: out : (M, N) ndarray
out[i, j] = a[i] * b[j]See also
inner,einsumNotes
Masked values are replaced by 0.
References
[R51] (1, 2) : G. H. Golub and C. F. van Loan, Matrix Computations, 3rd ed., Baltimore, MD, Johns Hopkins University Press, 1996, pg. 8. Examples
Make a (very coarse) grid for computing a Mandelbrot set:
123456789101112131415161718192021>>> rl=np.outer(np.ones((5,)), np.linspace(-2,2,5))>>> rlarray([[-2.,-1.,0.,1.,2.],[-2.,-1.,0.,1.,2.],[-2.,-1.,0.,1.,2.],[-2.,-1.,0.,1.,2.],[-2.,-1.,0.,1.,2.]])>>> im=np.outer(1j*np.linspace(2,-2,5), np.ones((5,)))>>> imarray([[0.+2.j,0.+2.j,0.+2.j,0.+2.j,0.+2.j],[0.+1.j,0.+1.j,0.+1.j,0.+1.j,0.+1.j],[0.+0.j,0.+0.j,0.+0.j,0.+0.j,0.+0.j],[0.-1.j,0.-1.j,0.-1.j,0.-1.j,0.-1.j],[0.-2.j,0.-2.j,0.-2.j,0.-2.j,0.-2.j]])>>> grid=rl+im>>> gridarray([[-2.+2.j,-1.+2.j,0.+2.j,1.+2.j,2.+2.j],[-2.+1.j,-1.+1.j,0.+1.j,1.+1.j,2.+1.j],[-2.+0.j,-1.+0.j,0.+0.j,1.+0.j,2.+0.j],[-2.-1.j,-1.-1.j,0.-1.j,1.-1.j,2.-1.j],[-2.-2.j,-1.-2.j,0.-2.j,1.-2.j,2.-2.j]])An example using a ?vector? of letters:
12345>>> x=np.array(['a','b','c'], dtype=object)>>> np.outer(x, [1,2,3])array([[a, aa, aaa],[b, bb, bbb],[c, cc, ccc]], dtype=object)
numpy.ma.outerproduct()
2025-01-10 15:47:30
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