Re: Segmentation Fault on Relax - 1.3.7 -- January 28, 2011

Hi,

Strangely your system seems to be the less precise of all the machines
with test results returned.  This is nothing to be worried about, your
precision is 1e-20 versers 1e-27 for other computers, so you should
have no problem finding the correct model-free results (for reference
Art Palmer's Modelfree4 has a precision of 1e-5).  It is a little
strange though that you do not reach the precision of 1e-25 stated in
the minimise command:

relax> minimise(*args=('bfgs', 'back'), func_tol=1e-25,
max_iterations=10000000, constraints=True, scaling=True, verbosity=1)

But your computer is not the only one not to reach this.  The other
thing is that the processor or CPU type is not listed in the print
out.  Are you running in a virtual machine?  I'm just asking out of
curiosity.  I am trying to try to work out why different machines do
not give identical model-free results.  This is all being recorded in
the relax test suite for future reference and research into model-free
analysis (see 
http://svn.gna.org/viewcvs/relax/1.3/test_suite/system_tests/model_free.py?view=markup).

Cheers,

Edward





On 28 January 2011 18:03, Edward d'Auvergne <edward@xxxxxxxxxxxxx> wrote:

Hi,

This is exactly what is needed.  Cheers.  I will add this data about
your specific setup to relax, and the tests will pass in the next
version.  These 2 failures you are seeing are perfectly fine.  They
relate only to machine precision differences (your computer has an Rex
value of 0.14899999999883881 verses the real value of 0.149, so this
will make no difference in your analysis ;)  You have nothing to worry
about, everything is working perfectly!  The mf_multimodel.py or
modsel.py scripts will return the correct result.  However if you have
data at 2 field strengths, which is almost a prerequisite for a
serious publication these days, I would recommend the orders of
magnitude higher quality protocol in
sample_scripts/dauvergne_protocol.py (see the reference
http://www.nmr-relax.com/refs.html#dAuvergneGooley08b).  Or you could
install relax 1.3.9 and try out the new GUI at
http://www.nmr-relax.com/download.html (this requires wxPython to be
installed).  The GUI uses this protocol to perform an automatic
model-free analysis, and the paper for it is in press.

Regards,

Edward


On 28 January 2011 11:39, Tiago Pais <tpais@xxxxxxxxxxx> wrote:

Hi,
I have executed the scons with no problems.
The print out that I could get is at the bottom of this em-mail. I hope 
this
is what you asked.
Anyway, does this bug affect the analysis for example with a
mf_multimodel.py or modsel.py?

Regards
TiagoP

Print out:
S2_0.970_te_2048_Rex_0.149', spin_id_col=None, mol_name_col=None,
res_num_col=1, res_name_col=2, spin_num_col=None, spin_name_col=None,
data_col=3, error_col=4, sep=None, spin_id=None)
Opening the file
'/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_2048_R
ex_0.149/r1.500.out' for reading.

relax> relax_data.read(ri_label='R2', frq_label='500', frq=500000000.0,
file='r2.500.out',
dir='/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_20
48_Rex_0.149', spin_id_col=None, mol_name_col=None, res_num_col=1,
res_name_col=2, spin_num_col=None, spin_name_col=None, data_col=3,
error_col=4, sep=None, spin_id=None)
Opening the file
'/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_2048_R
ex_0.149/r2.500.out' for reading.

relax> relax_data.read(ri_label='NOE', frq_label='500', frq=500000000.0,
file='noe.500.out',
dir='/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_20
48_Rex_0.149', spin_id_col=None, mol_name_col=None, res_num_col=1,
res_name_col=2, spin_num_col=None, spin_name_col=None, data_col=3,
error_col=4, sep=None, spin_id=None)
Opening the file
'/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_2048_R
ex_0.149/noe.500.out' for reading.

relax> diffusion_tensor.init(params=1e-08, time_scale=1.0, d_scale=1.0,
angle_units='deg', param_types=0, spheroid_type=None, fixed=True)

relax> value.set(val=1.0200000000000001e-10, param='bond_length',
spin_id=None)

relax> value.set(val=-0.00015999999999999999, param='csa', spin_id=None)

relax> value.set(val='15N', param='heteronucleus', spin_id=None)

relax> value.set(val='1H', param='proton', spin_id=None)

relax> value.display(param='csa')

# mol_name res_num    res_name   spin_num   spin_name  value
error
None       1          GLY        None       None                   -0.00016
None
None       2          ALA        None       None                   -0.00016
None

relax> value.write(param='proton', file='devnull', dir=None, force=False)
Opening the null device file for writing.

relax> model_free.select_model(model='m4', spin_id=None)

relax> value.set(val=[1.0, 0.0, 0.0], param=['S2', 'te', 'Rex'],
spin_id=None)

relax> minimise(*args=('bfgs', 'back'), func_tol=1e-25,
max_iterations=10000000, constraints=True, scaling=True, verbosity=1)


Over-fit spin deselection.

RelaxWarning: The spin ':1&:GLY' has been deselected because of 
insufficient
relaxation data, 3 or more data points are required.
Only the model-free parameters for single spins will be used.


Fitting to spin ':2&:ALA'
~~~~~~~~~~~~~~~~~~~~~~~~~


Method of Multipliers
~~~~~~~~~~~~~~~~~~~~~

k: 0       xk: array([ 1.,  0.,  0.])
fk: 3.9844117908982288
Entering sub-algorithm.

       Quasi-Newton BFGS minimisation
       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
       Line search:  Backtracking line search.

       k: 0        xk: [           1,           0,           0] fk:
3.9844117909

       Parameter values: [0.90905501681906287, 74.36929554563136,
1.2231009087192337]
       Function value:   -1447.7789206950388
       Iterations:       37
       Function calls:   93
       Gradient calls:   38
       Hessian calls:    0
       Warning:          None


k: 1       xk: array([  0.90905502,  74.36929555,   1.22310091])
fk: 48.121412825285709
Entering sub-algorithm.

       Quasi-Newton BFGS minimisation
       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
       Line search:  Backtracking line search.

       k: 0        xk: [     0.90906,      74.369,      1.2231] fk:
46.0715795854

       Parameter values: [0.98956103882988777, 408.92210939854823,
0.12789912252738242]
       Function value:   1.5767185066455172
       Iterations:       36
       Function calls:   160
       Gradient calls:   37
       Hessian calls:    0
       Warning:          None


k: 2       xk: array([  9.89561039e-01,   4.08922109e+02,   
1.27899123e-01])
fk: 3.6265517464833064
Entering sub-algorithm.

       Quasi-Newton BFGS minimisation
       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
       Line search:  Backtracking line search.

       k: 0        xk: [     0.98956,      408.92,      0.1279] fk:
3.62655174648

       Parameter values: [0.97366872065557464, 847.48129324681554,
0.12587481779543874]
       Function value:   2.1499888720861113
       Iterations:       30
       Function calls:   150
       Gradient calls:   31
       Hessian calls:    0
       Warning:          None


k: 3       xk: array([  9.73668721e-01,   8.47481293e+02,   
1.25874818e-01])
fk: 2.1499888720861113
Entering sub-algorithm.

       Quasi-Newton BFGS minimisation
       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
       Line search:  Backtracking line search.

       k: 0        xk: [     0.97367,      847.48,     0.12587] fk:
2.14998887209

       Parameter values: [0.97000000000112863, 2048.0000001778708,
0.14899999998759275]
       Function value:   1.2766370598812569e-20
       Iterations:       40
       Function calls:   94
       Gradient calls:   41
       Hessian calls:    0
       Warning:          None


k: 4       xk: array([  9.70000000e-01,   2.04800000e+03,   
1.49000000e-01])
fk: 1.2766370598812569e-20
Entering sub-algorithm.

       Quasi-Newton BFGS minimisation
       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
       Line search:  Backtracking line search.

       k: 0        xk: [        0.97,        2048,       0.149] fk:
1.27663705988e-20

       Parameter values: [0.97000000000095432, 2048.0000001778708,
0.14899999998189384]
       Function value:   1.1498830911662198e-20
       Iterations:       7
       Function calls:   28
       Gradient calls:   8
       Hessian calls:    0
       Warning:          None


k: 5       xk: array([  9.70000000e-01,   2.04800000e+03,   
1.49000000e-01])
fk: 1.1498830911662198e-20
Entering sub-algorithm.

       Quasi-Newton BFGS minimisation
       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
       Line search:  Backtracking line search.

       k: 0        xk: [        0.97,        2048,       0.149] fk:
1.14988309117e-20

       Parameter values: [0.97000000000095099, 2048.0000001778708,
0.14899999998189395]
       Function value:   1.1498599057727952e-20
       Iterations:       3
       Function calls:   39
       Gradient calls:   4
       Hessian calls:    0
       Warning:          None


k: 6       xk: array([  9.70000000e-01,   2.04800000e+03,   
1.49000000e-01])
fk: 1.1498599057727952e-20
Entering sub-algorithm.

       Quasi-Newton BFGS minimisation
       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
       Line search:  Backtracking line search.

       k: 0        xk: [        0.97,        2048,       0.149] fk:
1.14985990577e-20

       Parameter values: [0.97000000000095099, 2048.0000001778708,
0.14899999998189395]
       Function value:   1.1498599057727952e-20
       Iterations:       1
       Function calls:   34
       Gradient calls:   2
       Hessian calls:    0
       Warning:          None


Parameter values: [0.97000000000095099, 2048.0000001778708,
0.14899999998189395]
Function value:   1.1498599057727952e-20
Iterations:       154
Function calls:   598
Gradient calls:   161
Hessian calls:    0
Warning:          None

Traceback (most recent call last):
 File "/usr/local/relax-1.3.8/test_suite/system_tests/model_free.py", line
803, in test_opt_constr_bfgs_back_S2_0_970_te_2048_Rex_0_149
   self.value_test(spin, select=select, s2=s2, te=te, rex=rex, chi2=chi2,
iter=iter, f_count=f_count, g_count=g_count, h_count=h_count,
warning=warning)
 File "/usr/local/relax-1.3.8/test_suite/system_tests/model_free.py", line
2498, in value_test
   self.assert_(spin.iter in iter, msg=mesg)
AssertionError: Optimisation failure.

System:           Linux
Release:          2.6.28-17-generic
Version:          #58-Ubuntu SMP Tue Dec 1 18:57:07 UTC 2009
Win32 version:
Distribution:     Ubuntu 9.04 jaunty
Architecture:     32bit ELF
Machine:          i686
Processor:
Python version:   2.6.2
Numpy version:    1.2.1
Libc version:     glibc 2.4

s2:                          0.970000000000951
te (ps):                        2048.000000178
rex:                       0.14899999998189395
chi2:                   1.1498599057727952e-20
iter:                                      154
f_count:                                   598
g_count:                                   161
h_count:                                     0
warning:                                  None


======================================================================
FAIL: Constrained BFGS opt, More and Thuente line search {S2=0.970, 
te=2048,
Rex=0.149}
----------------------------------------------------------------------

relax> pipe.create(pipe_name='mf', pipe_type='mf')



                                           relax 1.3.8

                             Molecular dynamics by NMR data analysis

                            Copyright (C) 2001-2006 Edward d'Auvergne
                        Copyright (C) 2006-2011 the relax development team

This is free software which you are welcome to modify and redistribute 
under
the conditions of the
GNU General Public License (GPL).  This program, including all modules, is
licensed under the GPL
and comes with absolutely no warranty.  For details type 'GPL' within the
relax prompt.

Assistance in using the relax prompt and scripting interface can be 
accessed
by typing 'help' within
the prompt.


relax> sequence.read(file='noe.500.out',
dir='/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_20
48_Rex_0.149', spin_id_col=None, mol_name_col=None, res_num_col=1,
res_name_col=2, spin_num_col=None, spin_name_col=None, sep=None,
spin_id=None)
Opening the file
'/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_2048_R
ex_0.149/noe.500.out' for reading.



relax> relax_data.read(ri_label='R1', frq_label='600', frq=600000000.0,
file='r1.600.out',
dir='/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_20
48_Rex_0.149', spin_id_col=None, mol_name_col=None, res_num_col=1,
res_name_col=2, spin_num_col=None, spin_name_col=None, data_col=3,
error_col=4, sep=None, spin_id=None)
Opening the file
'/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_2048_R
ex_0.149/r1.600.out' for reading.

relax> relax_data.read(ri_label='R2', frq_label='600', frq=600000000.0,
file='r2.600.out',
dir='/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_20
48_Rex_0.149', spin_id_col=None, mol_name_col=None, res_num_col=1,
res_name_col=2, spin_num_col=None, spin_name_col=None, data_col=3,
error_col=4, sep=None, spin_id=None)
Opening the file
'/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_2048_R
ex_0.149/r2.600.out' for reading.

relax> relax_data.read(ri_label='NOE', frq_label='600', frq=600000000.0,
file='noe.600.out',
dir='/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_20
48_Rex_0.149', spin_id_col=None, mol_name_col=None, res_num_col=1,
res_name_col=2, spin_num_col=None, spin_name_col=None, data_col=3,
error_col=4, sep=None, spin_id=None)
Opening the file
'/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_2048_R
ex_0.149/noe.600.out' for reading.

relax> relax_data.read(ri_label='R1', frq_label='500', frq=500000000.0,
file='r1.500.out',
dir='/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_20
48_Rex_0.149', spin_id_col=None, mol_name_col=None, res_num_col=1,
res_name_col=2, spin_num_col=None, spin_name_col=None, data_col=3,
error_col=4, sep=None, spin_id=None)
Opening the file
'/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_2048_R
ex_0.149/r1.500.out' for reading.

relax> relax_data.read(ri_label='R2', frq_label='500', frq=500000000.0,
file='r2.500.out',
dir='/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_20
48_Rex_0.149', spin_id_col=None, mol_name_col=None, res_num_col=1,
res_name_col=2, spin_num_col=None, spin_name_col=None, data_col=3,
error_col=4, sep=None, spin_id=None)
Opening the file
'/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_2048_R
ex_0.149/r2.500.out' for reading.

relax> relax_data.read(ri_label='NOE', frq_label='500', frq=500000000.0,
file='noe.500.out',
dir='/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_20
48_Rex_0.149', spin_id_col=None, mol_name_col=None, res_num_col=1,
res_name_col=2, spin_num_col=None, spin_name_col=None, data_col=3,
error_col=4, sep=None, spin_id=None)
Opening the file
'/usr/local/relax-1.3.8/test_suite/shared_data/model_free/S2_0.970_te_2048_R
ex_0.149/noe.500.out' for reading.

relax> diffusion_tensor.init(params=1e-08, time_scale=1.0, d_scale=1.0,
angle_units='deg', param_types=0, spheroid_type=None, fixed=True)

relax> value.set(val=1.0200000000000001e-10, param='bond_length',
spin_id=None)

relax> value.set(val=-0.00015999999999999999, param='csa', spin_id=None)

relax> value.set(val='15N', param='heteronucleus', spin_id=None)

relax> value.set(val='1H', param='proton', spin_id=None)

relax> value.display(param='csa')

# mol_name res_num    res_name   spin_num   spin_name  value
error
None       1          GLY        None       None                   -0.00016
None
None       2          ALA        None       None                   -0.00016
None

relax> value.write(param='proton', file='devnull', dir=None, force=False)
Opening the null device file for writing.

relax> model_free.select_model(model='m4', spin_id=None)

relax> value.set(val=[1.0, 0.0, 0.0], param=['S2', 'te', 'Rex'],
spin_id=None)

relax> minimise(*args=('bfgs', 'mt'), func_tol=1e-25,
max_iterations=10000000, constraints=True, scaling=True, verbosity=1)


Over-fit spin deselection.

RelaxWarning: The spin ':1&:GLY' has been deselected because of 
insufficient
relaxation data, 3 or more data points are required.
Only the model-free parameters for single spins will be used.


Fitting to spin ':2&:ALA'
~~~~~~~~~~~~~~~~~~~~~~~~~


Method of Multipliers
~~~~~~~~~~~~~~~~~~~~~

k: 0       xk: array([ 1.,  0.,  0.])
fk: 3.9844117908982288
Entering sub-algorithm.

       Quasi-Newton BFGS minimisation
       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
       Line search:  More and Thuente line search.

       k: 0        xk: [           1,           0,           0] fk:
3.9844117909

       Parameter values: [0.90905506221773003, 74.369430109373241,
1.2231015622343226]
       Function value:   -1447.7789206948669
       Iterations:       22
       Function calls:   50
       Gradient calls:   50
       Hessian calls:    0
       Warning:          None


k: 1       xk: array([  0.90905506,  74.36943011,   1.22310156])
fk: 48.121371716785198
Entering sub-algorithm.

       Quasi-Newton BFGS minimisation
       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
       Line search:  More and Thuente line search.

       k: 0        xk: [     0.90906,      74.369,      1.2231] fk:
46.0715179226

       Parameter values: [0.9949366307767159, 88.138505840636597,
-3.7928107170550836e-05]
       Function value:   1.9644199913790175
       Iterations:       38
       Function calls:   128
       Gradient calls:   128
       Hessian calls:    0
       Warning:          The gradient at point 0 of this line search is
positive, ie p is not a descent direction and the line search will not 
work.
(fatal minimisation error).


k: 2       xk: array([  9.94936631e-01,   8.81385058e+01,  
-3.79281072e-05])
fk: 144.63951390018761
Entering sub-algorithm.

       Quasi-Newton BFGS minimisation
       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
       Line search:  More and Thuente line search.

       k: 0        xk: [     0.99494,      88.139, -3.7928e-05] fk:
4.01470534795

       Parameter values: [0.97000000000210929, 2048.0000000116925,
0.14899999998318531]
       Function value:   -7.1927065677039468e-05
       Iterations:       56
       Function calls:   129
       Gradient calls:   129
       Hessian calls:    0
       Warning:          None


k: 3       xk: array([  9.70000000e-01,   2.04800000e+03,   
1.49000000e-01])
fk: 1.608820007827088e-20
Entering sub-algorithm.

       Quasi-Newton BFGS minimisation
       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
       Line search:  More and Thuente line search.

       k: 0        xk: [        0.97,        2048,       0.149] fk:
1.60882000783e-20

       Parameter values: [0.97000000000063913, 2048.0000000116925,
0.14899999998315802]
       Function value:   2.6640810074146136e-21
       Iterations:       1
       Function calls:   4
       Gradient calls:   4
       Hessian calls:    0
       Warning:          None


k: 4       xk: array([  9.70000000e-01,   2.04800000e+03,   
1.49000000e-01])
fk: 2.6640810074146136e-21
Entering sub-algorithm.

       Quasi-Newton BFGS minimisation
       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
       Line search:  More and Thuente line search.

       k: 0        xk: [        0.97,        2048,       0.149] fk:
2.66408100741e-21

       Parameter values: [0.97000000000006137, 2048.0000000116925,
0.14899999999883881]
       Function value:   4.9272178768519757e-23
       Iterations:       2
       Function calls:   7
       Gradient calls:   7
       Hessian calls:    0
       Warning:          None


k: 5       xk: array([  9.70000000e-01,   2.04800000e+03,   
1.49000000e-01])
fk: 4.9272178768519757e-23
Entering sub-algorithm.

       Quasi-Newton BFGS minimisation
       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
       Line search:  More and Thuente line search.

       k: 0        xk: [        0.97,        2048,       0.149] fk:
4.92721787685e-23

       Parameter values: [0.97000000000006137, 2048.0000000116925,
0.14899999999883881]
       Function value:   4.9272178768519757e-23
       Iterations:       1
       Function calls:   63
       Gradient calls:   63
       Hessian calls:    0
       Warning:          None


Parameter values: [0.97000000000006137, 2048.0000000116925,
0.14899999999883881]
Function value:   4.9272178768519757e-23
Iterations:       120
Function calls:   381
Gradient calls:   381
Hessian calls:    0
Warning:          None

Traceback (most recent call last):
 File "/usr/local/relax-1.3.8/test_suite/system_tests/model_free.py", line
965, in test_opt_constr_bfgs_mt_S2_0_970_te_2048_Rex_0_149
   self.value_test(spin, select=select, s2=s2, te=te, rex=rex, chi2=chi2,
iter=iter, f_count=f_count, g_count=g_count, h_count=h_count,
warning=warning)
 File "/usr/local/relax-1.3.8/test_suite/system_tests/model_free.py", line
2500, in value_test
   self.assert_(spin.f_count in f_count, msg=mesg)
AssertionError: Optimisation failure.

System:           Linux
Release:          2.6.28-17-generic
Version:          #58-Ubuntu SMP Tue Dec 1 18:57:07 UTC 2009
Win32 version:
Distribution:     Ubuntu 9.04 jaunty
Architecture:     32bit ELF
Machine:          i686
Processor:
Python version:   2.6.2
Numpy version:    1.2.1
Libc version:     glibc 2.4

s2:                         0.9700000000000614
te (ps):                        2048.000000012
rex:                       0.14899999999883881
chi2:                   4.9272178768519757e-23
iter:                                      120
f_count:                                   381
g_count:                                   381
h_count:                                     0
warning:                                  None


----------------------------------------------------------------------
Ran 204 tests in 732.632s

FAILED (failures=2)




##############
# Unit tests #
##############


............................................................................
............................................................................
............................................................................
............................................................................
............................................................................
............................................................................
............................................................................
............................................................................
............................................................................
............................................................................
............................................................................
............................................................................
............................................................................
............................................................................
............................................................................
............................................................................
.......................
----------------------------------------------------------------------
Ran 1239 tests in 31.194s

OK




###################################
# Summary of the relax test suite #
###################################


# Optional packages/modules
###########################

No tests skipped due to missing modules.

# Synopsis
##########

System/functional tests ......................................... [ Failed 
]
Unit tests ...................................................... [ OK ]
Synopsis ........................................................ [ Failed 
]



-----Original Message-----
From: edward.dauvergne@xxxxxxxxx [mailto:edward.dauvergne@xxxxxxxxx] On
Behalf Of Edward d'Auvergne
Sent: quinta-feira, 27 de Janeiro de 2011 16:48
To: Tiago Pais
Cc: relax-users@xxxxxxx
Subject: Re: Segmentation Fault on Relax - 1.3.7

Hi,

Thanks for testing that.  The optimisation failures are not failures
of relax, but that it is a new platform where optimisation is a tiny
bit different.  I'm collecting all the information about these, and
adding exceptions for each machine.  I might have to turn this off
though.  You'll see that the optimised pararameters will be
nevertheless very close to those in the test name
'test_opt_constr_bfgs_mt_S2_0_970_te_2048_Rex_0_149'.  If you could
email more of the information from the system test, this would be
quite useful to make this test pass.  There should be a long print out
like:

--------------------------------------
System: Darwin
Release: 9.8.0
Version: Darwin Kernel Version 9.8.0: Wed Jul 15 16:55:01 PDT 2009;
root:xnu-1228.15.4~1/RELEASE_I386
Win32 version:
Distribution:
Architecture: 64bit
Machine: i386
Processor: i386
Python version: 2.6.2
numpy version: 1.3.0

s2: 0.9699999999999785
te: 2047.9999999962433
rex: 0.14900000000039709
chi2: 5.2479491342506911e-24
iter: 162
f_count: 758
g_count: 169
h_count: 0
warning: None
--------------------------------------

before the traceback message you posted.  This is the information
needed.  But everything should be fine, just that you won't be able to
run relaxation curve-fitting for the R1 and R2 until the module is
compiled.  The python version I compiled on (2.6.5) is similar enough
to your 2.6.2 - this is not the issue.  Maybe the numpy version is the
problem - I compiled on 1.4.1 and you are using 1.2.1.  They could
have introduced an incompatibility.  If you can install the numpy
headers package and scons, you'll be able to compile without problem
by typing 'scons'.

Cheers,

Edward




On 27 January 2011 12:14, Tiago Pais <tpais@xxxxxxxxxxx> wrote:

Thank you Edward,
Renaming the relax_fit.so did the job! Nice catch!

However, when running the test suite it is falling in the

System/Functional

tests:

Traceback (most recent call last):
 File "/usr/local/relax-1.3.7/test_suite/system_tests/model_free.py", line
677, in test_opt_constr_bfgs_mt_S2_0_970_te_2048_Rex_0_149
   self.value_test(spin, select, s2, te, rex, chi2, iter, f_count,

g_count,

h_count, warning)
 File "/usr/local/relax-1.3.7/test_suite/system_tests/model_free.py", line
2051, in value_test
   self.assert_(spin.f_count in f_count, msg=mesg)
AssertionError: Optimisation failure.


And this is the output information from relax --info (v1.3.8)

Hardware information:
   Machine:                 i686
   Processor:

System information:
   System:                  Linux
   Release:                 2.6.28-17-generic
   Version:                 #58-Ubuntu SMP Tue Dec 1 18:57:07 UTC 2009
   GNU/Linux version:       Ubuntu 9.04 jaunty
   Distribution:            Ubuntu 9.04 jaunty
   Full platform string:
Linux-2.6.28-17-generic-i686-with-Ubuntu-9.04-jaunty

Software information:
   Architecture:            32bit ELF
   Python version:          2.6.2
   Python branch:           branches/release26-maint
   Python build:            release26-maint, Apr 19 2009 01:56:41
   Python compiler:         GCC 4.3.3
   Python implementation:   CPython
   Python revision:
   Numpy version:           1.2.1
   Libc version:            glibc 2.4

Python packages (most are optional):

Package              Installed       Version         Path
minfx                True            Unknown
/usr/local/relax-1.3.8/minfx
bmrblib              False
numpy                True            1.2.1
/usr/lib/python2.6/dist-packages/numpy
ScientificPython     True            2.4.11
/usr/lib/python2.6/dist-packages/Scientific
wxPython             False
mpi4py               False
epydoc               False
optparse             True            1.5.3
/usr/lib/python2.6/optparse.pyc
Numeric              True            24.2
/usr/lib/python2.6/dist-packages/Numeric/Numeric.pyc
readline             True
/usr/lib/python2.6/lib-dynload/readline.so
profile              True
/usr/lib/python2.6/profile.pyc
bz2                  True
/usr/lib/python2.6/lib-dynload/bz2.so
gzip                 True
/usr/lib/python2.6/gzip.pyc
os.devnull           True
/usr/lib/python2.6/os.pyc

Compiled relax C modules:
   Relaxation curve fitting: False

I have not tried the "scons" possibility that you suggested.

Regards,
TiagoP



-----Original Message-----
From: edward.dauvergne@xxxxxxxxx [mailto:edward.dauvergne@xxxxxxxxx] On
Behalf Of Edward d'Auvergne
Sent: quarta-feira, 26 de Janeiro de 2011 19:56
To: Tiago Pais
Cc: relax-users@xxxxxxx
Subject: Re: Segmentation Fault on Relax - 1.3.7

Hi,

This is strange!  Do the source code versions work ok?  It could be
the a strange combination of python and numpy, together with relax's C
modules.  You could possibly remove (or rename) the
maths_fns/relax_fit.so file and try again.  It would be useful to have
information about the system to work out what is happening.  You can
get all the relevant info by typing:

$ relax --info

This is assuming relax will run at all.  Another option would be if
you have 'scons', 'numpy', and 'numpy-devel' (or something like that)
installed.  You could then type:

$ scons clean_all

to remove the compiled C module, and

$ scons

to build it again.  I hope this helps!

Cheers,

Edward



On 26 January 2011 19:35, Tiago Pais <tpais@xxxxxxxxxxx> wrote:

Dear all,
Surely this should be a very silly mistake of mine but I can not manage

to

put to work any of the relax versions above 1.3.6.
I just get the message "Segmentation fault" when I type "relax"

Do I need to uninstall the previous 1.3.4 version?
For now I would like to keep the old one since I have things analyzed on
that one.

Any help would be much appreciated.
Cheers
Tiago P



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Re: Segmentation Fault on Relax - 1.3.7

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