Outer product in CVXPY
I have an objective function that depends on a sum of outer products. If I could use Numpy functions, I would write this as:
A = np.ones(m, n)
U = Variable(m, n)
objective = np.trace(sum([np.outer(A[i,:], U[i,:]) for i in range(m)]))
Of course np.outer doesn't work when U is a variable. Is there a cvxpy affine function that would implement this?
python numpy cvxpy
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I have an objective function that depends on a sum of outer products. If I could use Numpy functions, I would write this as:
A = np.ones(m, n)
U = Variable(m, n)
objective = np.trace(sum([np.outer(A[i,:], U[i,:]) for i in range(m)]))
Of course np.outer doesn't work when U is a variable. Is there a cvxpy affine function that would implement this?
python numpy cvxpy
add a comment |
I have an objective function that depends on a sum of outer products. If I could use Numpy functions, I would write this as:
A = np.ones(m, n)
U = Variable(m, n)
objective = np.trace(sum([np.outer(A[i,:], U[i,:]) for i in range(m)]))
Of course np.outer doesn't work when U is a variable. Is there a cvxpy affine function that would implement this?
python numpy cvxpy
I have an objective function that depends on a sum of outer products. If I could use Numpy functions, I would write this as:
A = np.ones(m, n)
U = Variable(m, n)
objective = np.trace(sum([np.outer(A[i,:], U[i,:]) for i in range(m)]))
Of course np.outer doesn't work when U is a variable. Is there a cvxpy affine function that would implement this?
python numpy cvxpy
python numpy cvxpy
asked Nov 24 '18 at 7:37
geoffn91geoffn91
10413
10413
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cvxpy has a kron function that works. Since it only works on 2d Variables and 2d-arrays, you have to reshape the vectors to (n, 1) vectors first:
cvx.trace(sum([cvx.kron(A[i, :].reshape(n,1), cvx.reshape(U[i,:], (n,1))
for i in range(m)]))
add a comment |
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1 Answer
1
active
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votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
cvxpy has a kron function that works. Since it only works on 2d Variables and 2d-arrays, you have to reshape the vectors to (n, 1) vectors first:
cvx.trace(sum([cvx.kron(A[i, :].reshape(n,1), cvx.reshape(U[i,:], (n,1))
for i in range(m)]))
add a comment |
cvxpy has a kron function that works. Since it only works on 2d Variables and 2d-arrays, you have to reshape the vectors to (n, 1) vectors first:
cvx.trace(sum([cvx.kron(A[i, :].reshape(n,1), cvx.reshape(U[i,:], (n,1))
for i in range(m)]))
add a comment |
cvxpy has a kron function that works. Since it only works on 2d Variables and 2d-arrays, you have to reshape the vectors to (n, 1) vectors first:
cvx.trace(sum([cvx.kron(A[i, :].reshape(n,1), cvx.reshape(U[i,:], (n,1))
for i in range(m)]))
cvxpy has a kron function that works. Since it only works on 2d Variables and 2d-arrays, you have to reshape the vectors to (n, 1) vectors first:
cvx.trace(sum([cvx.kron(A[i, :].reshape(n,1), cvx.reshape(U[i,:], (n,1))
for i in range(m)]))
answered Nov 24 '18 at 7:37
geoffn91geoffn91
10413
10413
add a comment |
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