| Issue 5: | undefined symbol: dsyev_ | |
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What steps will reproduce the problem? 1. Install Ipopt from source. svn co https://projects.coin-or.org/svn/Ipopt/trunk CoinIpopt ./configure make make test make install 2. Install pyipopt from source. svn checkout http://pyipopt.googlecode.com/svn/trunk/ pyipopt-read-only make pyipopt make install 3. Run the test example shipped with pyipopt. python -i example.py Traceback (most recent call last): File "example.py", line 6, in <module> import pyipopt ImportError: /home/nwagner/svn/CoinIpopt/lib/libipopt.so.0: undefined symbol: dsyev_ nm /home/nwagner/svn/CoinIpopt/lib/libipopt.so.0 | grep dsyev U dsyev_ If I add -llapack -lblas to the line LDFLAGS = -L/home/nwagner/svn/CoinIpopt/lib -lipopt -llapack -lblas -lgfortran -lm in the makefile it works fine for me. What is the expected output? python -i example.py [PyIPOPT] Ipopt will use Hessian approximation. [PyIPOPT] nele_hess is 10 example.py:110: DeprecationWarning: PyArray_FromDims: use PyArray_SimpleNew. x, zl, zu, obj = nlp.solve(x0) example.py:110: DeprecationWarning: PyArray_FromDimsAndDataAndDescr: use PyArray_NewFromDescr. x, zl, zu, obj = nlp.solve(x0) ****************************************************************************** This program contains Ipopt, a library for large-scale nonlinear optimization. Ipopt is released as open source code under the Common Public License (CPL). For more information visit http://projects.coin-or.org/Ipopt ****************************************************************************** NOTE: You are using Ipopt by default with the MUMPS linear solver. Other linear solvers might be more efficient (see Ipopt documentation). This is Ipopt version 3.5trunk, running with linear solver mumps. Number of nonzeros in equality constraint Jacobian...: 4 Number of nonzeros in inequality constraint Jacobian.: 4 Number of nonzeros in Lagrangian Hessian.............: 0 Total number of variables............................: 4 variables with only lower bounds: 0 variables with lower and upper bounds: 4 variables with only upper bounds: 0 Total number of equality constraints.................: 1 Total number of inequality constraints...............: 1 inequality constraints with only lower bounds: 1 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 1.6109693e+01 1.12e+01 5.28e-01 0.0 0.00e+00 - 0.00e+00 0.00e+00 0 1 1.7420709e+01 8.40e-01 2.40e+01 -0.3 8.13e-01 - 3.20e-01 1.00e+00f 1 2 1.7120453e+01 2.14e-01 2.00e-01 -0.6 1.02e+00 - 9.97e-01 1.00e+00h 1 3 1.6979032e+01 2.15e-01 8.49e-02 -1.6 1.18e-01 - 9.72e-01 1.00e+00h 1 4 1.6972554e+01 7.81e-02 1.20e-02 -3.2 8.01e-02 - 1.00e+00 1.00e+00h 1 5 1.7013661e+01 6.94e-04 9.50e-03 -4.9 1.00e-02 - 1.00e+00 1.00e+00h 1 6 1.7014018e+01 1.96e-06 3.49e-04 -6.1 1.09e-03 - 1.00e+00 1.00e+00h 1 7 1.7014017e+01 1.47e-09 2.15e-07 -8.2 3.02e-05 - 1.00e+00 1.00e+00h 1 8 1.7014017e+01 0.00e+00 1.69e-09 -11.0 1.17e-08 - 1.00e+00 1.00e+00h 1 Number of Iterations....: 8 (scaled) (unscaled) Objective...............: 1.7014017140224176e+01 1.7014017140224176e+01 Dual infeasibility......: 1.6853158598871439e-09 1.6853158598871439e-09 Constraint violation....: 0.0000000000000000e+00 0.0000000000000000e+00 Complementarity.........: 1.0002952000760553e-11 1.0002952000760553e-11 Overall NLP error.......: 1.6853158598871439e-09 1.6853158598871439e-09 Number of objective function evaluations = 9 Number of objective gradient evaluations = 9 Number of equality constraint evaluations = 9 Number of inequality constraint evaluations = 9 Number of equality constraint Jacobian evaluations = 9 Number of inequality constraint Jacobian evaluations = 9 Number of Lagrangian Hessian evaluations = 0 Total CPU secs in IPOPT (w/o function evaluations) = 0.008 Total CPU secs in NLP function evaluations = 0.004 EXIT: Optimal Solution Found. Problem solved Solution of the primal variables, x [ 1. 4.74299964 3.82114998 1.37940829] Solution of the bound multipliers, z_L and z_U [ 1.08787121e+00 2.67165388e-12 3.54465533e-12 2.63564701e-11] [ 2.49999763e-12 3.89104702e-11 8.48283408e-12 2.76198339e-12] Objective value f(x*) = 17.0140171402 What do you see instead? What version of the product are you using? On what operating system? svn versions on opensuse11.1 x86_64. Please provide any additional information below. How can I switch from MUMPS to another linear solver ?
May 1, 2009
Project Member
#1
xu.mathena
Aug 25, 2009
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