ah sorry ! this line gives me the error
h= IMP.atom.Hierarchy.get_children(cs)
thanks
josh
On 2 July 2014 17:45, imp-users-request@salilab.org wrote:
> Send IMP-users mailing list submissions to > imp-users@salilab.org > > To subscribe or unsubscribe via the World Wide Web, visit > https://salilab.org/mailman/listinfo/imp-users > or, via email, send a message with subject or body 'help' to > imp-users-request@salilab.org > > You can reach the person managing the list at > imp-users-owner@salilab.org > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of IMP-users digest..." > > > Today's Topics: > > 1. Re: Sampling and writing to pym/rmf (Barak Raveh) (Barak Raveh) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Wed, 2 Jul 2014 09:45:30 -0700 > From: Barak Raveh barak.raveh@gmail.com > To: Help and discussion for users of IMP imp-users@salilab.org > Subject: Re: [IMP-users] Sampling and writing to pym/rmf (Barak Raveh) > Message-ID: > <CAHp+_Uo19VasJDJYi+2CoUUu= > u_6duKCraVetU4dW45+oDhTAw@mail.gmail.com> > Content-Type: text/plain; charset="utf-8" > > Which lines throws the error? > > > On Wed, Jul 2, 2014 at 4:56 AM, Josh Bullock jma.bullock@gmail.com > wrote: > > > Hi Barek, > > > > So I'm not giving hierarchy.get_children the correct input: > > > > TypeError: unbound method get_children() must be called with Hierarchy > > instance as first argument (got ConfigurationSet instance instead) > > > > I'm not sure which argument is the hierarchy instance. > > > > Thanks, > > > > Josh > > > > ------------------------------------------------- > > > > cs= get_conformations(m) > > > > for i in range(0, cs.get_number_of_configurations()): > > JOSH = cs.load_configuration(i) > > S= IMP.atom.Selection > > h= IMP.atom.Hierarchy.get_children(cs) > > tfn = IMP.create_temporary_file_name("josh%d"%i, ".rmf") > > rh = RMF.create_rmf_file(tfn) > > > > On 1 July 2014 17:31, imp-users-request@salilab.org wrote: > > > >> Send IMP-users mailing list submissions to > >> imp-users@salilab.org > >> > >> To subscribe or unsubscribe via the World Wide Web, visit > >> https://salilab.org/mailman/listinfo/imp-users > >> or, via email, send a message with subject or body 'help' to > >> imp-users-request@salilab.org > >> > >> You can reach the person managing the list at > >> imp-users-owner@salilab.org > >> > >> When replying, please edit your Subject line so it is more specific > >> than "Re: Contents of IMP-users digest..." > >> > >> > >> Today's Topics: > >> > >> 1. Re: Sampling and writing to pym/rmf (Barak Raveh) > >> > >> > >> ---------------------------------------------------------------------- > >> > >> Message: 1 > >> Date: Tue, 1 Jul 2014 09:31:33 -0700 > >> From: Barak Raveh barak.raveh@gmail.com > >> To: Help and discussion for users of IMP imp-users@salilab.org > >> Subject: Re: [IMP-users] Sampling and writing to pym/rmf > >> Message-ID: > >> <CAHp+_UowiBwJozbwOfi8yFEVt7Z8o2tEZ= > >> LvYPnJh-LjpC2cSA@mail.gmail.com> > >> Content-Type: text/plain; charset="utf-8" > >> > >> Hi Josh, from a very superficial look, your code to write the RMF files > >> seems fine - do you get an output RMF file? Could you load it in > Chimera? > >> > >> > >> On Tue, Jul 1, 2014 at 2:40 AM, Josh Bullock jma.bullock@gmail.com > >> wrote: > >> > >> > Hello, > >> > > >> > I'm relatively new to all this so please let me know if i'm making any > >> > obvious errors ... > >> > > >> > Essentially all i'm trying to do is generate an ensemble of models > made > >> > from four subunits - constrained by MS connectivity restraints. The > >> models > >> > get scored but nothing seems to write to the pymol file. Ideally i'd > >> like > >> > to write to an .rmf but i haven't worked that one out either ... > >> > > >> > Is this a reasonable way to go about my problem ? > >> > > >> > Many thanks, > >> > > >> > Josh > >> > > >> > ------------------------------------------- > >> > > >> > import IMP > >> > import IMP.atom > >> > import IMP.rmf > >> > import inspect > >> > import IMP.container > >> > import IMP.display > >> > import IMP.statistics > >> > #import IMP.example > >> > import sys, math, os, optparse > >> > import RMF > >> > > >> > from optparse import OptionParser > >> > > >> > > >> > # Convert the arguments into strings and number > >> > Firstpdb = str(sys.argv[1]) > >> > Secondpdb = str(sys.argv[2]) > >> > Thirdpdb = str(sys.argv[3]) > >> > Fourthpdb = str(sys.argv[4]) > >> > models = float(sys.argv[5]) > >> > > >> > #***************************************** > >> > > >> > # the spring constant to use, it doesnt really matter > >> > k=100 > >> > # the target resolution for the representation, this is used to > specify > >> > how detailed > >> > # the representation used should be > >> > resolution=300 > >> > # the box to perform everything > >> > bb=IMP.algebra.BoundingBox3D(IMP.algebra.Vector3D(0,0,0), > >> > IMP.algebra.Vector3D(300, 300, 300)) > >> > > >> > > >> > # this function creates the molecular hierarchies for the various > >> involved > >> > proteins > >> > def create_representation(): > >> > m= IMP.Model() > >> > all=IMP.atom.Hierarchy.setup_particle(IMP.Particle(m)) > >> > all.set_name("the universe") > >> > # create a protein, represented as a set of connected balls of > >> > appropriate > >> > # radii and number, chose by the resolution parameter and the > >> number of > >> > # amino acids. > >> > > >> > def create_protein_from_pdbs(name, files): > >> > > >> > def create_from_pdb(file): > >> > sls=IMP.SetLogState(IMP.NONE) > >> > datadir = os.getcwd() > >> > print datadir > >> > t=IMP.atom.read_pdb( datadir+'/' + file, m, > >> > IMP.atom.ATOMPDBSelector()) > >> > del sls > >> > #IMP.atom.show_molecular_hierarchy(t) > >> > c=IMP.atom.Chain(IMP.atom.get_by_type(t, > >> > IMP.atom.CHAIN_TYPE)[0]) > >> > if c.get_number_of_children()==0: > >> > IMP.atom.show_molecular_hierarchy(t) > >> > # there is no reason to use all atoms, just approximate > the > >> > pdb shape instead > >> > s=IMP.atom.create_simplified_along_backbone(c, > >> > > >> resolution/300.0) > >> > IMP.atom.destroy(t) > >> > # make the simplified structure rigid > >> > rb=IMP.atom.create_rigid_body(s) > >> > # rb=IMP.atom.create_rigid_body(c) > >> > rb.set_coordinates_are_optimized(True) > >> > return s > >> > # return c > >> > > >> > h= create_from_pdb(files[0]) > >> > h.set_name(name) > >> > all.add_child(h) > >> > > >> > create_protein_from_pdbs("A", [Firstpdb]) > >> > create_protein_from_pdbs("B", [Secondpdb]) > >> > create_protein_from_pdbs("C", [Thirdpdb]) > >> > create_protein_from_pdbs("D", [Fourthpdb]) > >> > #create_protein_from_pdbs("C", ["rpt3_imp.pdb"]) > >> > return (m, all) > >> > > >> > # create the needed restraints and add them to the model > >> > > >> > def create_restraints(m, all): > >> > def add_connectivity_restraint(s): > >> > > >> > tr= IMP.core.TableRefiner() > >> > rps=[] > >> > for sc in s: > >> > ps= sc.get_selected_particles() > >> > rps.append(ps[0]) > >> > tr.add_particle(ps[0], ps) > >> > > >> > # duplicate the IMP.atom.create_connectivity_restraint > >> > functionality > >> > > >> > score= > >> > > >> > IMP.core.KClosePairsPairScore(IMP.core.HarmonicSphereDistancePairScore(0,1),tr) > >> > > >> > r= IMP.core.MSConnectivityRestraint(m,score) > >> > > >> > iA = r.add_type([rps[0]]) > >> > iB = r.add_type([rps[1]]) > >> > iC = r.add_type([rps[2]]) > >> > iD = r.add_type([rps[3]]) > >> > n1 = r.add_composite([iA, iB, iC, iD]) > >> > n2 = r.add_composite([iA, iB], n1) > >> > n3 = r.add_composite([iC, iD], n1) > >> > n4 = r.add_composite([iB, iC, iD], n1) > >> > > >> > m.add_restraint(r) > >> > > >> > evr=IMP.atom.create_excluded_volume_restraint([all]) > >> > m.add_restraint(evr) > >> > # a Selection allows for natural specification of what the > >> restraints > >> > act on > >> > S= IMP.atom.Selection > >> > sA=S(hierarchy=all, molecule="A") > >> > sB=S(hierarchy=all, molecule="B") > >> > sC=S(hierarchy=all, molecule="C") > >> > sD=S(hierarchy=all, molecule="D") > >> > add_connectivity_restraint([sA, sB, sC, sD]) > >> > > >> > > >> > # find acceptable conformations of the model > >> > def get_conformations(m): > >> > sampler= IMP.core.MCCGSampler(m) > >> > sampler.set_bounding_box(bb) > >> > # magic numbers, experiment with them and make them large enough > for > >> > things to work > >> > sampler.set_number_of_conjugate_gradient_steps(100) > >> > sampler.set_number_of_monte_carlo_steps(20) > >> > sampler.set_number_of_attempts(models) > >> > # We don't care to see the output from the sampler > >> > sampler.set_log_level(IMP.SILENT) > >> > # return the IMP.ConfigurationSet storing all the found > >> configurations > >> > that > >> > # meet the various restraint maximum scores. > >> > cs= sampler.create_sample() > >> > return cs > >> > > >> > > >> > # cluster the conformations and write them to a file > >> > def analyze_conformations(cs, all, gs): > >> > # we want to cluster the configurations to make them easier to > >> > understand > >> > # in the case, the clustering is pretty meaningless > >> > embed= IMP.statistics.ConfigurationSetXYZEmbedding(cs, > >> > > >> > IMP.container.ListSingletonContainer(IMP.atom.get_leaves(all)), True) > >> > cluster= IMP.statistics.create_lloyds_kmeans(embed, 10, 10000) > >> > # dump each cluster center to a file so it can be viewed. > >> > for i in range(cluster.get_number_of_clusters()): > >> > center= cluster.get_cluster_center(i) > >> > cs.load_configuration(i) > >> > w= IMP.display.PymolWriter("cluster.%d.pym"%i) > >> > for g in gs: > >> > w.add_geometry(g) > >> > > >> > > >> > > >> > > >> > #****************************************************************************************** > >> > # now do the actual work > >> > > >> > (m,all)= create_representation() > >> > IMP.atom.show_molecular_hierarchy(all) > >> > create_restraints(m, all) > >> > > >> > # in order to display the results, we need something that maps the > >> > particles onto > >> > # geometric objets. The IMP.display.Geometry objects do this mapping. > >> > # IMP.display.XYZRGeometry map an IMP.core.XYZR particle onto a sphere > >> > gs=[] > >> > for i in range(all.get_number_of_children()): > >> > color= IMP.display.get_display_color(i) > >> > n= all.get_child(i) > >> > name= n.get_name() > >> > g= IMP.atom.HierarchyGeometry(n) > >> > g.set_color(color) > >> > gs.append(g) > >> > > >> > cs= get_conformations(m) > >> > > >> > print "found", cs.get_number_of_configurations(), "solutions" > >> > > >> > ListScores = [] > >> > for i in range(0, cs.get_number_of_configurations()): > >> > cs.load_configuration(i) > >> > # print the configuration > >> > print "solution number: ",i,"scored :", m.evaluate(False) > >> > ListScores.append(m.evaluate(False)) > >> > > >> > f1 = open("out_scores.csv", "w") > >> > f1.write("\n".join(map(lambda x: str(x), ListScores))) > >> > f1.close() > >> > > >> > # for each of the configuration, dump it to a file to view in pymol > >> > for i in range(0, cs.get_number_of_configurations()): > >> > JOSH = cs.load_configuration(i) > >> > S= IMP.atom.Selection > >> > h= IMP.atom.Hierarchy.get_children(cs) > >> > tfn = IMP.create_temporary_file_name("josh%d"%i, ".rmf") > >> > rh = RMF.create_rmf_file(tfn) > >> > > >> > # add the hierarchy to the file > >> > IMP.rmf.add_hierarchies(rh, h) > >> > > >> > # add the current configuration to the file as frame 0 > >> > IMP.rmf.save_frame(rh) > >> > > >> > for g in gs: > >> > w.add_geometry(g) > >> > > >> > analyze_conformations(cs, all, gs) > >> > > >> > > >> > _______________________________________________ > >> > IMP-users mailing list > >> > IMP-users@salilab.org > >> > https://salilab.org/mailman/listinfo/imp-users > >> > > >> > > >> > >> > >> -- > >> Barak > >>