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273 discussions

Python wrapper error after IMP installation
by Adhikari, Badri (MU-Student) 10 Apr '12

10 Apr '12

Hello all, We installed IMP in one of our servers by building the source code files. I do not have root access on the servers. It looks like I need to use the atom module and so after installation, I tested the installation with the files in the test directory inside the atom module's directory. I can run the files like test_bd.py and test_charmm_atom.py run smooth, but files like test_charmm_parameters.py throw the following error. RuntimeError: Unknown error caught by Python wrapper Details of the error message is attached. Please help! Warm Regards, Badri Adhikari CS Graduate Student, University of Missouri-Columbia, Columbia, Missouri Cell: 573 639 2847 BAP54(a)mail.missouri.edu<mailto:BAP54@mail.missouri.edu>

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ImportError: No module named IMP
by Adhikari, Badri (MU-Student) 28 Mar '12

28 Mar '12

Hello everyone, I installed IMP and tried to execute a sample python script sample.py using the command: python sample.py I keep getting ImportError that looks like in the image below. [Description: cid:image001.png@01CD0D1B.B639C5D0] I do not have root access in the server and I have installed all other prerequisites (swig, boost and scons). I downloaded IMP at http://salilab.org/imp/get.php?pkg=1.0/download/imp-1.0.tar.gz Has anyone faced this error before. Please help! ---------------------------------------- Warm Regards, Badri Adhikari CS Graduate Student, University of Missouri-Columbia, Columbia, Missouri BAP54(a)mail.missouri.edu<mailto:BAP54@mail.missouri.edu>

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IMP Survey Reminder
by Charles Greenberg 12 Mar '12

12 Mar '12

Hi all, If you haven't had a chance yet, please fill out the IMP survey (link below). We will be discussing the survey results at our upcoming lab retreat, and we'd like to have as many opinions as possible. The results will help us decide future directions for IMP and improve its usability. https://docs.google.com/spreadsheet/viewform?formkey=dFZaOGlEa2hYUmE5d1N3SU… Thanks again! --Charles

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IMP Survey 2012
by Charles Greenberg 08 Mar '12

08 Mar '12

Hello IMP users, We've put together a little survey about IMP: its features, usability, documentation, etc. If you could take the time to fill it out, we'd love to get your opinions on how we can improve IMP. The survey is anonymous of course. Here is the link: https://docs.google.com/spreadsheet/viewform?formkey=dFZaOGlEa2hYUmE5d1N3SU… Thanks! Charles Greenberg Sali Lab, UCSF

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IMP cannot find Modeller 9.10 script - Regular Expression problem?
by João Rodrigues 23 Oct '11

23 Oct '11

Dear all, I tried to install IMP today in our cluster and I ran into a small problem with MODELLER. IMP could not find MODELLER, despite the directory and all the paths being perfectly fine. I double checked the modeller_test.py in scons_test/ and I found that the regular expression looking for mod9v10 instead of mod9.10. After changing the expression all went well. Maybe this changed with the last version of MODELLER. Just letting you know for future reference! An additional question, should I use the version 1.0 or the SVN? Cheers, João [...] Rodrigues http://nmr.chem.uu.nl/~joao

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does IMP.algebra.get_transformation_aligning_first_to_second minimize RMSD ?
by Benjamin SCHWARZ 20 Oct '11

20 Oct '11

Hi list, Just confronted to something that looks like a bug, either in IMP or in my reading of the IMP manual. I'd expect the alignment of two sets of particles or vectors to minimize the RMD between the two sets, but in my case it appears the alignment produces a worse RMSD. See output underneath, and sample script attached. Considering 30 3D vectors natural rmsd between v1 and v2: 209.651290894 aligning v1 on v2... with resulting rmsd 220.458206177 running IMP version kernel SVN 10177 with Boost.FileSystem

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IMP-1.0-Stable Installation Ubuntu 10.04 Help
by Martin Turk 11 Oct '11

11 Oct '11

Dear imp users and developers, I need some help with compiling the source code on Ubuntu 10.04 I tried compiling imp with: >scons prefix=/installation/folder build=debug install and the only imp binaries being generated are foxs and protein_ligand_score. the only error I get is: """ sh: Syntax error: Bad fd number """ and the graphviz, gslcblas and modeller dependencies are missing otherwise the installation finishes without errors. Since Ubuntu has system libraries in a different place than Fedora I tried compiling imp by specifying libpath and linking it to python. What is odd is that graphviz and gslcblas are not found when I specify libpath /usr/lib/graphviz/ /usr/lib/libgslcblas.so.0 >scons -j 16 libpath=/usr/lib:/usr/lib64 path=/usr/bin pythonpath=/usr/lib64/python2.6 prefix=/home/turk/imp build=debug install again I assume the installation directory is missing some content ../bin: protein_ligand_score foxs ../lib64/python2.6/site-packages: IMP _IMP_algebra.so _IMP_atom.so _IMP_benchmark.so _IMP_container.so _IMP_core.so _IMP_display.so _IMP_domino.so _IMP_em.so _IMP_example.so _IMP_gsl.so _IMP_helper.so _IMP_misc.so _IMP_restrainer.so _IMP_saxs.so _IMP.so _IMP_statistics.so after adding site-packages to the $PYTHONPATH python import imp gives me: i>>> import IMP Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/turk/imp/lib64/python2.6/site-packages/IMP/__init__.py", line 25, in <module> _IMP = swig_import_helper() File "/home/turk/imp/lib64/python2.6/site-packages/IMP/__init__.py", line 17, in swig_import_helper import _IMP ImportError: libimp.so: cannot open shared object file: No such file or directory Now I don't know what to try next and if playing with swig will bring me any further -> the email :-) All suggestions are welcome :) Martin

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How to use IMP
by 张春雷 29 Sep '11

29 Sep '11

Dear all, I am trying to use IMP as a C++ library for my modeling work: using some functions of IMP in my own code. But I get no idea how to use it. One way I tried is to put my own code in the "applications" directory and put a Sconscript file along with it. But how to compile my code? Could anyone tell my some details? Thanks a lot! -Justin

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IMP.restrainer examples
by Jascha Casadio 20 Sep '11

20 Sep '11

Hi there. I was checking the IMP.restrained examples and I have a couple of questions about it. The rigid_body_and_excluded_volume_restrain.py example shows how to get proteins from multiple PDBs and enforce upon them connectivity restraints, but doesn't give any graphical representation of the whole assembly (before/after). The basic_display.py example does show how to create Chimera logs to store optimization states, but the rigid_body_and_excluded_volume_restrain.py example doesn't do any optimization. So, how do I simply see the assembly produced in rigid_body_and_excluded_volume_restrain.py before and after the restraints have been applied (the five proteins connected without crashing into each other). I've actually tried to play with it myself, but the results are far from what I've desired. The representation and restraints XML files are exaclty those coming with the IMP examples: five proteins loaded from PDB files, not allowed to crash into each other and connected (1,2,3;4,5). I've created a display file so that each particle has its own color.  <Display> �� <Protein id="Protein1"><Color r="0.15" g="0.58" b="0.66"/></Protein> �� <Protein id="Protein2"><Color r="0.38" g="0.04" b="0.37"/></Protein> �� <Protein id="Protein3"><Color r="0.84" g="0.78" b="0.24"/></Protein> �� <Protein id="Protein4"><Color r="0.62" g="0.47" b="0.45"/></Protein> �� <Protein id="Protein5"><Color r="0.00" g="0.71" b="0.01"/></Protein> </Display> I've also modified the file rigid_body_and_excluded_volume_restraint.py so that first the display information is loaded then, once restraints are enforced, the model is optimized (I've removed the lines showing how to manipulate/rotate a rigid body). #-- File: rigid_body_and_excluded_volume_restraint.py --# import IMP import IMP.restrainer import IMP.display # Load representation rep_parser = IMP.restrainer.XMLRepresentation('input/eg2_representation.xml') representation = rep_parser.run() # Load restraints restraint_parser = IMP.restrainer.XMLRestraint('input/eg2_restraint.xml') restraint = restraint_parser.run() # Load display display_parser = IMP.restrainer.XMLDisplay('input/eg2_display.xml') display = display_parser.run() model = representation.to_model() # Write initial display in Chimera format log = display.create_log(representation, 'pdb_log_%03d.py') log.write('rigid_display_initial.py') # Place restraint into IMP model restraint.add_to_representation(representation) ###=======================================================================### #� At this point all data from XML files have been placed into the model. #� Now it is possible to perform various operations on the IMP model. ###=======================================================================### # Optimize opt = IMP.core.ConjugateGradients() opt.set_model(model) opt.add_optimizer_state(log) opt.optimize(10) # Write final display in Chimera format log.write('rigid_display_optimized.py') First, I've noticed that in the initial representation, I can only see one of the molecules. I assume this is because they don't have an initial position (unlike when I use spheres), so they can be anywhere. Using the ConjugateGradients optimization makes it crash: _IMP.UsageException: Attempting to construct a rotation from a� non-quaternion value. The coefficient vector must have a length of 1. Got: 0.377264 0.0876134 0.185363 1.48248 gives 2.38212. Using MonteCarlo or SteepestDescent optimizations (opt = IMP.core.MonteCarlo()) doesn't seem to change the model score. In the end, I end up with an optimized display which looks exactly the same as the initial one, that is to say, I can only see one (the first of the five) proteins. I guess this is caused by the fact that optimizing doesn't change the score of the final model. Nevertheless, I was simply trying to diplay the five proteins before and after the connectivity and excluded volume restraints were applied... Hope you can help. Thanks

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coarse models with MCCG sampler : biased ?
by Benjamin SCHWARZ 20 Sep '11

20 Sep '11

Hi guys, I am currently interested in the coarse modeling of a small (10 subunits) system for which I have nothing but a few interactomics data as well as some (parts of) structures to help me to assess the size and number of beads to represent some of the subunits (details on my OS as well as on the modeled system can be found below.). Thanks to the nup84 example, I was rapidly able to generate a large number of configurations and to visualize it (thanks for the MCCG sampler and the IMP.display.PymolWriter). I am however puzzled by the look of the obtained configurations : having represented my subunits as a succession of beads (I explicitly defined my restraints between successive balls), I expected my subunits to accommodate various types of shapes whereas they seem to have a tendency to adopt preferentially a straight aligned rod-like shape ( An example of a pymol file containing 1000 configurations can be downloaded for visualization at alnitak.u-strasbg.fr/~schwarz/Perso/1000-configs.pym). I am now wondering if these configurations are really random generated, or if -as I fear- I have a bias in my sampling scheme, and how I can circumvent the trouble. Here is one explanations I could find to this apparent behavior : I don't know how the excluded volume is handled by the MCCG sampler, but my guess is that the CG step helps a lot in "locally" optimizing this particular restraint. Now, if all balls are considered in the computation of derivatives (and not only those that really present a common intersection), it is intuitively quite probable that the system will ultimately push successive balls the furthest away from each other, hence favoring rod-like shapes upon epileptic-snake-like ones. Does this assumption makes any sense ? I am running IMP kernel SVN 10177 with Boost.FileSystem on Mac OS My system is composed of - 10 subunits (divided in 30 beads to represent specific domains) - 29 restraints to enforce pair connectivity between domains of a same subunits, or domains of different subunits for which a connectivity is known - 2 ambiguous connections between several domains or subunits - 1 excluded volume restraint between every 30 particles in the system. --Ben (S)

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