Advertisement
Not a member of Pastebin yet?
Sign Up,
it unlocks many cool features!
- sol0 = minimize(objective, x0, args=mock_df, method='trust-constr',
- bounds=bnds, constraints=cons,
- options={'maxiter': 250, 'verbose': 3})
- | niter |f evals|CG iter| obj func |tr radius | opt | c viol | penalty |barrier param|CG stop|
- |-------|-------|-------|-------------|----------|----------|----------|----------|-------------|-------|
- C:ProgramDataAnaconda3libsite-packagesscipyoptimize_trustregion_constrprojections.py:182: UserWarning: Singular Jacobian matrix. Using SVD decomposition to perform the factorizations.
- warn('Singular Jacobian matrix. Using SVD decomposition to ' +
- | 1 | 31 | 0 | -4.4450e+02 | 1.00e+00 | 7.61e+02 | 5.00e-01 | 1.00e+00 | 1.00e-01 | 0 |
- C:ProgramDataAnaconda3libsite-packagesscipyoptimize_hessian_update_strategy.py:187: UserWarning: delta_grad == 0.0. Check if the approximated function is linear. If the function is linear better results can be obtained by defining the Hessian as zero instead of using quasi-Newton approximations.
- 'approximations.', UserWarning)
- | 2 | 62 | 1 | -2.2830e+03 | 6.99e+00 | 3.64e+02 | 7.28e-01 | 1.00e+00 | 1.00e-01 | 2 |
- | 3 | 93 | 2 | -9.7651e+03 | 3.42e+01 | 5.52e+01 | 5.33e+00 | 1.00e+00 | 1.00e-01 | 2 |
- | 4 | 124 | 26 | -4.9999e+03 | 3.42e+01 | 8.23e+01 | 9.29e-01 | 3.48e+16 | 1.00e-01 | 1 |
- | 5 | 155 | 50 | -4.1486e+03 | 3.42e+01 | 5.04e+01 | 2.08e-01 | 3.48e+16 | 1.00e-01 | 1 |
- ...
- | 56 | 1674 | 1127 | -1.6146e+03 | 1.77e-08 | 4.49e+00 | 3.55e-15 | 3.66e+33 | 1.00e-01 | 1 |
- | 57 | 1705 | 1151 | -1.6146e+03 | 1.77e-09 | 4.49e+00 | 3.55e-15 | 3.66e+33 | 1.00e-01 | 1 |
- | 58 | 1736 | 1151 | -1.6146e+03 | 1.00e+00 | 4.42e+00 | 3.55e-15 | 1.00e+00 | 2.00e-02 | 0 |
- | 59 | 1767 | 1175 | -1.6146e+03 | 1.00e-01 | 4.42e+00 | 3.55e-15 | 1.00e+00 | 2.00e-02 | 1 |
- | 60 | 1798 | 1199 | -1.6146e+03 | 1.00e-02 | 4.42e+00 | 3.55e-15 | 1.00e+00 | 2.00e-02 | 1 |
- ...
- | 66 | 1984 | 1343 | -1.6146e+03 | 1.00e-08 | 4.42e+00 | 3.55e-15 | 1.00e+00 | 2.00e-02 | 1 |
- | 67 | 2015 | 1367 | -1.6146e+03 | 1.00e-09 | 4.42e+00 | 3.55e-15 | 1.00e+00 | 2.00e-02 | 1 |
- | 68 | 2046 | 1367 | -1.6146e+03 | 1.00e+00 | 4.36e+00 | 3.55e-15 | 1.00e+00 | 4.00e-03 | 0 |
- | 69 | 2077 | 1391 | -1.6146e+03 | 1.00e-01 | 4.36e+00 | 3.55e-15 | 1.00e+00 | 4.00e-03 | 1 |
- ...
- | 77 | 2325 | 1583 | -1.6146e+03 | 1.00e-09 | 4.36e+00 | 3.55e-15 | 1.00e+00 | 4.00e-03 | 1 |
- | 78 | 2356 | 1583 | -1.6146e+03 | 1.00e+00 | 4.35e+00 | 3.55e-15 | 1.00e+00 | 8.00e-04 | 0 |
- | 79 | 2387 | 1607 | -1.6146e+03 | 1.00e-01 | 4.35e+00 | 3.55e-15 | 1.00e+00 | 8.00e-04 | 1 |
- ...
- | 87 | 2635 | 1799 | -1.6146e+03 | 1.00e-09 | 4.35e+00 | 3.55e-15 | 1.00e+00 | 8.00e-04 | 1 |
- | 88 | 2666 | 1799 | -1.6146e+03 | 1.00e+00 | 4.34e+00 | 3.55e-15 | 1.00e+00 | 1.60e-04 | 0 |
- | 89 | 2697 | 1823 | -1.6146e+03 | 1.00e-01 | 4.34e+00 | 3.55e-15 | 1.00e+00 | 1.60e-04 | 1 |
- ...
- | 97 | 2945 | 2015 | -1.6146e+03 | 1.00e-09 | 4.34e+00 | 3.55e-15 | 1.00e+00 | 1.60e-04 | 1 |
- | 98 | 2976 | 2015 | -1.6146e+03 | 1.00e+00 | 4.34e+00 | 3.55e-15 | 1.00e+00 | 3.20e-05 | 0 |
- | 99 | 3007 | 2039 | -1.6146e+03 | 1.00e-01 | 4.34e+00 | 3.55e-15 | 1.00e+00 | 3.20e-05 | 1 |
- ...
- | 167 | 5053 | 3527 | -1.6146e+03 | 1.00e-07 | 1.35e+01 | 2.12e-11 | 1.00e+00 | 2.05e-09 | 1 |
- | 168 | 5084 | 3551 | -1.6146e+03 | 1.00e-08 | 1.35e+01 | 2.12e-11 | 1.00e+00 | 2.05e-09 | 1 |
- | 169 | 5115 | 3575 | -1.6146e+03 | 1.00e-09 | 1.35e+01 | 2.12e-11 | 1.00e+00 | 2.05e-09 | 1 |
- `xtol` termination condition is satisfied.
- Number of iterations: 169, function evaluations: 5115, CG iterations: 3575, optimality: 1.35e+01, constraint violation: 2.12e-11, execution time: 3.8e+02 s.
- con0 = {'type': 'eq', 'fun': constraint0}
Advertisement
Add Comment
Please, Sign In to add comment
Advertisement