Edward,
Thanks. I had to recreate a minfx-1.0.3.zip archive from
the contents of the svn and reuse the missing setup.py file
from the minfx-1.0.2.zip archive in order to build an updated
minfx-py26 package. Building the relax 1.3 branch under fink
(using the attached fink packaging files), I get the following
results on powerpc-apple-darwin9.8.0 (which contain one new
failure for this platform compared to the relax-1.2.0 release
in the System/Functional tests). I'll check the results on
i386 and x86_64 fink later tonight.
Jack
ps I noticed that minfx for both 1.0.2 and 1.0.3 doesn't report
a version despite each installation having the version field
set in setup.py. Is there a fix for this? Also, shouldn't the
scons installation have a dependency check for the 1.0.3 release
of minfx before it proceeds?
relax --info
relax repository checkout
Molecular dynamics by NMR data analysis
Copyright (C) 2001-2006 Edward d'Auvergne
Copyright (C) 2006-2010 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.
Hardware information:
Machine: Power Macintosh
Processor: powerpc
System information:
System: Darwin
Release: 9.8.0
Version: Darwin Kernel Version 9.8.0: Wed Jul 15 16:57:01
PDT 2009; root:xnu-1228.15.4~1/RELEASE_PPC
Mac version: 10.5.8 (, , ) PowerPC
Distribution:
Full platform string: Darwin-9.8.0-Power_Macintosh-powerpc-32bit
Software information:
Architecture: 32bit
Python version: 2.6.4
Python branch: tags/r264
Python build: r264:75706, Feb 24 2010 14:23:45
Python compiler: GCC 4.0.1 (Apple Inc. build 5493)
Python implementation: CPython
Python revision: 75706
Numpy version: 1.3.0
Libc version:
Python packages (most are optional):
Package Installed Version Path
minfx True Unknown
/sw/lib/python2.6/site-packages/minfx
bmrblib False
numpy True 1.3.0
/sw/lib/python2.6/site-packages/numpy
ScientificPython True 2.8
/sw/lib/python2.6/site-packages/Scientific
wxPython False
mpi4py False
epydoc False
optparse True 1.5.3
/sw/lib/python2.6/optparse.pyc
Numeric True 24.2
/sw/lib/python2.6/site-packages/Numeric/Numeric.pyc
readline True
/sw/lib/python2.6/lib-dynload/readline.so
profile True
/sw/lib/python2.6/profile.pyc
bz2 True
/sw/lib/python2.6/lib-dynload/bz2.so
gzip True
/sw/lib/python2.6/gzip.pyc
os.devnull True /sw/lib/python2.6/os.pyc
Compiled relax C modules:
Relaxation curve fitting: True
relax --test-suite
Echoing of user function calls has been enabled.
#############################
# System / functional tests #
#############################
..............F....................................................................................................
======================================================================
FAIL: Test the 'rigid' model for randomly rotated tensors with no motion.
----------------------------------------------------------------------
relax> pipe.create(pipe_name='test', pipe_type='frame order')
relax repository checkout
Molecular dynamics by NMR data analysis
Copyright (C) 2001-2006 Edward d'Auvergne
Copyright (C) 2006-2010 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> pipe.create(pipe_name='rigid', pipe_type='frame order')
relax>
script(file='/sw/lib/relax-py26/test_suite/system_tests/scripts/frame_order/tensors_rigid_rand_rot.py',
quit=False)
script =
'/sw/lib/relax-py26/test_suite/system_tests/scripts/frame_order/tensors_rigid_rand_rot.py'
----------------------------------------------------------------------------------------------------
# Random rotation matrix:
# [[ 0.33282568, -0.83581125, 0.43663098],
# [-0.92326661, -0.19462612, 0.33120905],
# [-0.19184846, -0.51336169, -0.83645319]]
# Euler angles:
# alpha: 5.0700283197712777
# beta: 2.5615753919522359
# gamma: 0.64895449611163691
# The error value.
error = 1.4741121114678945e-05
# Load tensor 0.
align_tensor.init(tensor='a 0', params=(0.00014221982216882766,
-0.00014454300156652134, -0.00070779621164871397, -0.00060161949408277324,
0.00020200800707295083), param_types=0)
align_tensor.init(tensor='b 0', params=(-1.3288330878574132e-05,
0.00020354043164217626, -0.00046409902800134087, 0.0002493202418302213,
-0.00077964218698160488), param_types=0)
align_tensor.init(tensor='a 0', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.init(tensor='b 0', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.set_domain(tensor='a 0', domain='a')
align_tensor.set_domain(tensor='b 0', domain='b')
# Load tensor 1.
align_tensor.init(tensor='a 1', params=(-0.00014307694949297205,
-0.00039671919293883539, -0.00024724524395487659, 0.00031948292975139144,
0.00018868359624777637), param_types=0)
align_tensor.init(tensor='b 1', params=(-9.738292410013338e-05,
-0.00038634774864149617, -0.00027912458757344276, -0.00038171766743202567,
-0.00011588335825493787), param_types=0)
align_tensor.init(tensor='a 1', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.init(tensor='b 1', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.set_domain(tensor='a 1', domain='a')
align_tensor.set_domain(tensor='b 1', domain='b')
# Load tensor 2.
align_tensor.init(tensor='a 2', params=(-0.00022967898444150887,
-0.00027171643813494106, -0.00021961563147411279, 0.00010337393266477703,
0.00029030226175831515), param_types=0)
align_tensor.init(tensor='b 2', params=(-0.00017932499024246612,
-0.00033064833984871618, -0.00019167049464976276, -0.00018228662361670689,
-0.00024786515322241842), param_types=0)
align_tensor.init(tensor='a 2', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.init(tensor='b 2', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.set_domain(tensor='a 2', domain='a')
align_tensor.set_domain(tensor='b 2', domain='b')
# Load tensor 3.
align_tensor.init(tensor='a 3', params=(0.00043690692358615301,
-0.00034379559287467062, -0.00019359695171683388, 0.00030194133983804048,
-6.314162250164486e-05), param_types=0)
align_tensor.init(tensor='b 3', params=(3.2029991098699158e-05,
0.0001030927713217096, -0.00040609134800855906, -0.00027871118513542376,
0.00018429705265751148), param_types=0)
align_tensor.init(tensor='a 3', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.init(tensor='b 3', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.set_domain(tensor='a 3', domain='a')
align_tensor.set_domain(tensor='b 3', domain='b')
# Load tensor 4.
align_tensor.init(tensor='a 4', params=(-0.00026249527958822807,
0.00073561736796410628, 6.3975419225898133e-05, 6.2788017118057252e-05,
0.00020119758245770023), param_types=0)
align_tensor.init(tensor='b 4', params=(0.00023041655343338213,
-0.00028914097123516663, 8.5942868106736884e-05, 0.00057733961469646491,
0.00023383246814246303), param_types=0)
align_tensor.init(tensor='a 4', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.init(tensor='b 4', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.set_domain(tensor='a 4', domain='a')
align_tensor.set_domain(tensor='b 4', domain='b')
# Load tensor 5.
align_tensor.init(tensor='a 5', params=(0.00048180707211229368,
-0.00033930112217225942, 0.00011094068795736053, 0.00070350646902989675,
0.00037537667271407197), param_types=0)
align_tensor.init(tensor='b 5', params=(-0.00034205987160777676,
-5.6563966889313711e-05, -0.00048729767346789097, -0.00020195965056872761,
0.00064352392049120096), param_types=0)
align_tensor.init(tensor='a 5', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.init(tensor='b 5', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.set_domain(tensor='a 5', domain='a')
align_tensor.set_domain(tensor='b 5', domain='b')
# Load tensor 6.
align_tensor.init(tensor='a 6', params=(0.00035672066304092451,
-0.00026838578790208884, -0.00016936140664230585, 0.00017187371551506447,
-0.00030579015509609098), param_types=0)
align_tensor.init(tensor='b 6', params=(0.00020255575866227554,
0.00015766165657592193, -0.00022547338964377635, -0.00031137881231040781,
9.8269840241030186e-05), param_types=0)
align_tensor.init(tensor='a 6', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.init(tensor='b 6', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.set_domain(tensor='a 6', domain='a')
align_tensor.set_domain(tensor='b 6', domain='b')
# Load tensor 7.
align_tensor.init(tensor='a 7', params=(0.00017061308478202151,
-0.00076455273118810501, -0.00052048809712606505, 0.00049258369866413392,
-0.00013905141064073534), param_types=0)
align_tensor.init(tensor='b 7', params=(0.00013226613079678079,
-0.00028875805425577231, -0.00055280116463899331, -0.00079483102252618661,
-0.00012673098706816532), param_types=0)
align_tensor.init(tensor='a 7', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.init(tensor='b 7', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.set_domain(tensor='a 7', domain='a')
align_tensor.set_domain(tensor='b 7', domain='b')
# Load tensor 8.
align_tensor.init(tensor='a 8', params=(-0.00022193220790426714,
-0.00090073235703922686, 0.00050867766236886724, 0.00028215012727179065,
0.0002562167583736733), param_types=0)
align_tensor.init(tensor='b 8', params=(-0.00082779604132576475,
-0.0001229250183977039, 0.00026827297822125086, -0.00076816617763492308,
1.787549543771558e-05), param_types=0)
align_tensor.init(tensor='a 8', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.init(tensor='b 8', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.set_domain(tensor='a 8', domain='a')
align_tensor.set_domain(tensor='b 8', domain='b')
# Load tensor 9.
align_tensor.init(tensor='a 9', params=(0.00037091020965736575,
-0.00012230875848954012, -0.00016247713611487416, -0.00042725170061841107,
9.0103851318397519e-05), param_types=0)
align_tensor.init(tensor='b 9', params=(-0.00019129846420341554,
0.00047556140822968502, -0.0001921404751338773, 0.00021386940177866865,
-0.00026418197641736997), param_types=0)
align_tensor.init(tensor='a 9', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.init(tensor='b 9', params=(error, error, error, error, error),
param_types=0, errors=True)
align_tensor.set_domain(tensor='a 9', domain='a')
align_tensor.set_domain(tensor='b 9', domain='b')
----------------------------------------------------------------------------------------------------
relax> align_tensor.init(tensor='a 0', params=(0.00014221982216882766,
-0.00014454300156652134, -0.00070779621164871397, -0.00060161949408277324,
0.00020200800707295083), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='b 0', params=(-1.3288330878574132e-05,
0.00020354043164217626, -0.00046409902800134087, 0.0002493202418302213,
-0.00077964218698160488), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='a 0', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.init(tensor='b 0', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.set_domain(tensor='a 0', domain='a')
relax> align_tensor.set_domain(tensor='b 0', domain='b')
relax> align_tensor.init(tensor='a 1', params=(-0.00014307694949297205,
-0.00039671919293883539, -0.00024724524395487659, 0.00031948292975139144,
0.00018868359624777637), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='b 1', params=(-9.738292410013338e-05,
-0.00038634774864149617, -0.00027912458757344276, -0.00038171766743202567,
-0.00011588335825493787), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='a 1', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.init(tensor='b 1', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.set_domain(tensor='a 1', domain='a')
relax> align_tensor.set_domain(tensor='b 1', domain='b')
relax> align_tensor.init(tensor='a 2', params=(-0.00022967898444150887,
-0.00027171643813494106, -0.00021961563147411279, 0.00010337393266477703,
0.00029030226175831515), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='b 2', params=(-0.00017932499024246612,
-0.00033064833984871618, -0.00019167049464976276, -0.00018228662361670689,
-0.00024786515322241842), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='a 2', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.init(tensor='b 2', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.set_domain(tensor='a 2', domain='a')
relax> align_tensor.set_domain(tensor='b 2', domain='b')
relax> align_tensor.init(tensor='a 3', params=(0.00043690692358615301,
-0.00034379559287467062, -0.00019359695171683388, 0.00030194133983804048,
-6.314162250164486e-05), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='b 3', params=(3.2029991098699158e-05,
0.0001030927713217096, -0.00040609134800855906, -0.00027871118513542376,
0.00018429705265751148), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='a 3', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.init(tensor='b 3', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.set_domain(tensor='a 3', domain='a')
relax> align_tensor.set_domain(tensor='b 3', domain='b')
relax> align_tensor.init(tensor='a 4', params=(-0.00026249527958822807,
0.00073561736796410628, 6.3975419225898133e-05, 6.2788017118057252e-05,
0.00020119758245770023), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='b 4', params=(0.00023041655343338213,
-0.00028914097123516663, 8.5942868106736884e-05, 0.00057733961469646491,
0.00023383246814246303), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='a 4', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.init(tensor='b 4', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.set_domain(tensor='a 4', domain='a')
relax> align_tensor.set_domain(tensor='b 4', domain='b')
relax> align_tensor.init(tensor='a 5', params=(0.00048180707211229368,
-0.00033930112217225942, 0.00011094068795736053, 0.00070350646902989675,
0.00037537667271407197), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='b 5', params=(-0.00034205987160777676,
-5.6563966889313711e-05, -0.00048729767346789097, -0.00020195965056872761,
0.00064352392049120096), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='a 5', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.init(tensor='b 5', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.set_domain(tensor='a 5', domain='a')
relax> align_tensor.set_domain(tensor='b 5', domain='b')
relax> align_tensor.init(tensor='a 6', params=(0.00035672066304092451,
-0.00026838578790208884, -0.00016936140664230585, 0.00017187371551506447,
-0.00030579015509609098), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='b 6', params=(0.00020255575866227554,
0.00015766165657592193, -0.00022547338964377635, -0.00031137881231040781,
9.8269840241030186e-05), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='a 6', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.init(tensor='b 6', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.set_domain(tensor='a 6', domain='a')
relax> align_tensor.set_domain(tensor='b 6', domain='b')
relax> align_tensor.init(tensor='a 7', params=(0.00017061308478202151,
-0.00076455273118810501, -0.00052048809712606505, 0.00049258369866413392,
-0.00013905141064073534), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='b 7', params=(0.00013226613079678079,
-0.00028875805425577231, -0.00055280116463899331, -0.00079483102252618661,
-0.00012673098706816532), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='a 7', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.init(tensor='b 7', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.set_domain(tensor='a 7', domain='a')
relax> align_tensor.set_domain(tensor='b 7', domain='b')
relax> align_tensor.init(tensor='a 8', params=(-0.00022193220790426714,
-0.00090073235703922686, 0.00050867766236886724, 0.00028215012727179065,
0.0002562167583736733), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='b 8', params=(-0.00082779604132576475,
-0.0001229250183977039, 0.00026827297822125086, -0.00076816617763492308,
1.787549543771558e-05), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='a 8', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.init(tensor='b 8', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.set_domain(tensor='a 8', domain='a')
relax> align_tensor.set_domain(tensor='b 8', domain='b')
relax> align_tensor.init(tensor='a 9', params=(0.00037091020965736575,
-0.00012230875848954012, -0.00016247713611487416, -0.00042725170061841107,
9.0103851318397519e-05), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='b 9', params=(-0.00019129846420341554,
0.00047556140822968502, -0.0001921404751338773, 0.00021386940177866865,
-0.00026418197641736997), scale=1.0, angle_units='deg', param_types=0,
errors=False)
relax> align_tensor.init(tensor='a 9', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.init(tensor='b 9', params=(1.4741121114678945e-05,
1.4741121114678945e-05, 1.4741121114678945e-05, 1.4741121114678945e-05,
1.4741121114678945e-05), scale=1.0, angle_units='deg', param_types=0,
errors=True)
relax> align_tensor.set_domain(tensor='a 9', domain='a')
relax> align_tensor.set_domain(tensor='b 9', domain='b')
relax> align_tensor.reduction(full_tensor='a 0', red_tensor='b 0')
relax> align_tensor.reduction(full_tensor='a 1', red_tensor='b 1')
relax> align_tensor.reduction(full_tensor='a 2', red_tensor='b 2')
relax> align_tensor.reduction(full_tensor='a 3', red_tensor='b 3')
relax> align_tensor.reduction(full_tensor='a 4', red_tensor='b 4')
relax> align_tensor.reduction(full_tensor='a 5', red_tensor='b 5')
relax> align_tensor.reduction(full_tensor='a 6', red_tensor='b 6')
relax> align_tensor.reduction(full_tensor='a 7', red_tensor='b 7')
relax> align_tensor.reduction(full_tensor='a 8', red_tensor='b 8')
relax> align_tensor.reduction(full_tensor='a 9', red_tensor='b 9')
relax> frame_order.select_model(model='rigid')
relax> frame_order.ref_domain(ref='a')
relax> grid_search(lower=None, upper=None, inc=6, constraints=True,
verbosity=1)
RelaxWarning: Constraints are as of yet not implemented - turning this option
off.
Grid search
~~~~~~~~~~
Searching through 108 grid nodes.
k: 0 xk: [ 0, 0, 0] fk: 60402.7971133
k: 1 xk: [ 1.0472, 0, 0] fk: 54077.0686203
k: 2 xk: [ 2.0944, 0, 0] fk: 39503.3552589
k: 3 xk: [ 3.1416, 0, 0] fk: 37578.7102679
k: 35 xk: [ 5.236, 1.9106, 1.0472] fk: 27129.433648
relax> minimise(*args=('simplex',), func_tol=1e-25, max_iterations=10000000,
constraints=False, scaling=True, verbosity=1)
Simplex minimisation
~~~~~~~~~~~~~~~~~~~
k: 0 xk: [ 5.236, 2.0062, 1.0472] fk: 22040.0462168
k: 100 xk: [ 5.07, 2.5616, 0.64895] fk:
5.30640418091e-10
k: 200 xk: [ 5.07, 2.5616, 0.64895] fk:
6.44793137198e-26
Parameter values: [5.0700283197689195, 2.561575400736614, 0.64895449611163547]
Function value: 6.4479313719786626e-26
Iterations: 201
Function calls: 368
Gradient calls: 0
Hessian calls: 0
Warning: None
relax> results.write(file='devnull', dir=None, compress_type=1, force=True)
Opening the null device file for writing.
Traceback (most recent call last):
File "/sw/lib/relax-py26/test_suite/system_tests/frame_order.py", line 147,
in test_opt_rigid_rand_rot
self.assertEqual(cdp.iter, 204, msg=self.mesg)
AssertionError: Optimisation failure.
System: Darwin
Release: 9.8.0
Version: Darwin Kernel Version 9.8.0: Wed Jul 15 16:57:01 PDT 2009;
root:xnu-1228.15.4~1/RELEASE_PPC
Win32 version:
Distribution:
Architecture: 32bit
Machine: Power Macintosh
Processor: powerpc
Python version: 2.6.4
Numpy version: 1.3.0
Libc version:
alpha: 5.0700283197689195
beta: 2.561575400736614
gamma: 0.64895449611163547
chi2: 6.4479313719786626e-26
iter: 201
f_count: 368
g_count: 0
h_count: 0
warning: None
----------------------------------------------------------------------
Ran 115 tests in 315.229s
FAILED (failures=1)
##############
# Unit tests #
##############
testing units...
----------------
/sw/lib/relax-py26/test_suite/unit_tests
...........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................
----------------------------------------------------------------------
Ran 1195 tests in 26.669s
OK
###################################
# Summary of the relax test suite #
###################################
System/functional tests
............................................................. [ Failed ]
Unit tests
.......................................................................... [
OK ]
Synopsis
............................................................................
[ Failed ]
On Thu, Feb 25, 2010 at 08:29:59AM +0100, Edward d'Auvergne wrote:
Hi,
These errors correspond in changes in the minfx package. In the
future I think I will try to package minfx,
http://gna.org/projects/minfx/ (and bmrblib,
http://gna.org/projects/bmrblib/) with relax. I don't know how this
could be done with fink though. To have a local install of minfx
within the relax source tree, just go to the base relax directory and
type:
svn co http://svn.gna.org/svn/minfx/trunk/minfx
Then if you run the test suite, most of the problems should be gone.
Cheers,
Edward
Info2: <<
Package: relax-py%type_pkg[python]
Version: 1.3.5
Revision: 0
Distribution: (%type_pkg[python] = 24) 10.4, (%type_pkg[python] = 24) 10.5
Type: python (2.4 2.5 2.6)
Source: http://download.gna.org/relax/relax-%v.src.tar.bz2
Source-MD5: 3eaf6052a6058aaec0ffa10e40429225
SourceDirectory: relax-%v
Depends: python%type_pkg[python], scipy-core-py%type_pkg[python],
scientificpython-py%type_pkg[python], minfx-py%type_pkg[python] (>= 1.0.2)
BuildDepends: python%type_pkg[python], scons, scipy-core-py%type_pkg[python],
scientificpython-py%type_pkg[python], minfx-py%type_pkg[python] (>= 1.0.2),
fink (>= 0.24.12)
Conflicts: relax-py24, relax-py25, relax-py26
Replaces: relax-py24, relax-py25, relax-py26
PatchFile: relax-py.patch
PatchFile-MD5: 36a3bbc5c1818babb92cfaaab03e4f74
PatchScript: <<
#!/bin/sh -ev
sed 's|python2.X|python%type_raw[python]|g' < %{PatchFile} | sed
's|FINK_INSTALL_DIR|%i|g' | sed 's|relax-py2X|relax-py%type_pkg[python]|g' |
patch -p1
if [ "%m" == "x86_64" ] ; then
perl -pi -e "s|cflags = '-I'|cflags = '-m64 -I'|g" ./sconstruct
perl -pi -e "s|'-bundle',|'-m64', '-bundle',|g" ./sconstruct
else
perl -pi -e "s|cflags = '-I'|cflags = '-m32 -I'|g" ./sconstruct
perl -pi -e "s|'-bundle',|'-m32', '-bundle',|g" ./sconstruct
fi
<<
CompileScript: <<
%p/bin/python%type_raw[python] %p/bin/scons
<<
InstallScript: <<
mkdir -p %i/lib
mkdir -p %i/bin
%p/bin/python%type_raw[python] %p/bin/scons install
rm -f %i/lib/relax-py%type_pkg[python]/version.pyc
rm -f %i/lib/relax-py%type_pkg[python]/scons/*.pyc
rm %i/bin/relax
<<
PostInstScript: <<
update-alternatives --install %p/bin/relax relax
%p/lib/relax-py%type_pkg[python]/relax %type_pkg[python]
cd %p/lib/relax-py%type_pkg[python]
perl -pi -e 's|%i|%p|g' ./sconstruct
relax --test
<<
PreRmScript: <<
if [ $1 != "upgrade" ]; then
update-alternatives --remove relax %p/lib/relax-py%type_pkg[python]/relax
fi
/usr/bin/find %p/lib/relax-py%type_pkg[python] -name '*.pyc' -delete
<<
Description: Protein dynamics by NMR relax. data analysis
License: GPL
Homepage: http://www.nmr-relax.com/
Maintainer: None <fink-devel@xxxxxxxxxxxxxxxxxxxxx>
<<
diff -uNr relax-1.3.5/relax relax-1.3.5.patched/relax
--- relax-1.3.5/relax 2010-02-25 08:58:20.000000000 -0500
+++ relax-1.3.5.patched/relax 2010-02-25 09:01:26.000000000 -0500
@@ -1,4 +1,4 @@
-#! /usr/bin/env python
+#! /usr/bin/env python2.X
###############################################################################
#
#
diff -uNr relax-1.3.5/scons/install.py relax-1.3.5.patched/scons/install.py
--- relax-1.3.5/scons/install.py 2010-02-25 08:57:57.000000000 -0500
+++ relax-1.3.5.patched/scons/install.py 2010-02-25 09:02:35.000000000
-0500
@@ -112,8 +112,8 @@
###############
# Run relax to create the *.pyc files.
- print("\nRunning relax to create the byte-compiled *.pyc files.")
- system(env['SYMLINK'] + " --test")
+ #print("\nRunning relax to create the byte-compiled *.pyc files.")
+ #system(env['SYMLINK'] + " --test")
# Final print out.
print("\n\n\n")
diff -uNr relax-1.3.5/sconstruct relax-1.3.5.patched/sconstruct
--- relax-1.3.5/sconstruct 2010-02-25 08:58:20.000000000 -0500
+++ relax-1.3.5.patched/sconstruct 2010-02-25 09:01:26.000000000 -0500
@@ -98,7 +98,7 @@
SYS = SYSTEM
# Mac OS X installation path.
- INSTALL_PATH = sys.prefix + sep + 'local'
+ INSTALL_PATH = 'FINK_INSTALL_DIR' + sep + 'lib'
# All other operating systems.
@@ -115,16 +115,15 @@
###############
# Relax installation directory.
-RELAX_PATH = INSTALL_PATH + sep + 'relax'
+RELAX_PATH = INSTALL_PATH + sep + 'relax-py2X'
# Installation path for binaries.
-BIN_PATH = INSTALL_PATH + sep + 'bin'
+BIN_PATH = 'FINK_INSTALL_DIR' + sep + 'bin'
# Symbolic link installation path.
SYMLINK = BIN_PATH + sep + 'relax'
-
# The distribution files.
#########################
Info2: <<
Package: minfx-py%type_pkg[python]
Version: 1.0.3
Revision: 0
Distribution: (%type_pkg[python] = 24) 10.4, (%type_pkg[python] = 24) 10.5
Type: python (2.4 2.5 2.6)
Maintainer: None <fink-devel@xxxxxxxxxxxxxxxxxxxxx>
Depends: python%type_pkg[python]
BuildDepends: python%type_pkg[python]
Source: http://download.gna.org/minfx/minfx-%v.zip
Source-MD5: c60d37fa11406e0cc2079ce975389549
CompileScript: <<
<<
InstallScript: <<
%p/bin/python%type_raw[python] setup.py install --root %d
<<
License: GPL
#DocFiles: COPYING
Description: The minfx optimisation library
DescDetail: <<
The minfx project is a python package for numerical optimisation,
being a large collection of standard minimisation algorithms. The
name minfx is simply a shortening of the mathematical expression min f(x).
<<
Homepage: https://gna.org/projects/minfx/
<<
Re: relax on Mac with fink