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Today's Topics:
 Â1. Re: Sampling and writing to pym/rmf (Barak Raveh)
----------------------------------------------------------------------
Message: 1
Date: Wed, 2 Jul 2014 15:03:19 -0700
From: Barak Raveh <">>
To: Help and discussion for users of IMP <">>
Subject: Re: [IMP-users] Sampling and writing to pym/rmf
Message-ID:
    <CAHp+_UqO8rXRMsUSndbg-c0jyDxnswDe9aFKvW889gGMU=">>
Content-Type: text/plain; charset="utf-8"
* I meant
h = IMP.atom.Hierarchy(p)
c = p.get_children(h)
this assumes that particle p was already decorated as Hierarchy (let me
know if you are not familiar with decorators, Hierarchy, or Particle).
On Wed, Jul 2, 2014 at 3:02 PM, Barak Raveh <">> wrote:
> Hi Josh,
>
> I think get_children() is only a member function of Hierarchy, so you
> should do something like
>
> IMP.atom.Hierarchy(p)
> c = p.get_children()
>
> 'cs' seems to be a ConfigurationSet object - are you sure that you expect
> it to have children?
>
> What do you want to do?
>
> Cheers,
> Barak
>
> On Wed, Jul 2, 2014 at 1:42 PM, Josh Bullock <">>
> wrote:
>
>> ah sorry ! this line gives me the error
>>
>> h= IMP.atom.Hierarchy.get_children(cs)
>>
>> thanks
>>
>> josh
>>
>> On 2 July 2014 17:45, <">> wrote:
>>
>>> Send IMP-users mailing list submissions to
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>>> Today's Topics:
>>>
>>> Â Â1. 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 <">>
>>> To: Help and discussion for users of IMP <">>
>>> Subject: Re: [IMP-users] Sampling and writing to pym/rmf (Barak Raveh)
>>> Message-ID:
>>> Â Â Â Â <CAHp+_Uo19VasJDJYi+2CoUUu=
>>> ">u_6duKCraVetU4dW45+>
>>> Content-Type: text/plain; charset="utf-8"
>>>
>>> Which lines throws the error?
>>>
>>>
>>> On Wed, Jul 2, 2014 at 4:56 AM, Josh Bullock <">>
>>> 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()):
>>> > Â Â JOSH = cs.load_configuration(i)
>>> > Â Â S= IMP.atom.Selection
>>> > Â Â h= IMP.atom.Hierarchy.get_children(cs)
>>> > Â Â tfn = IMP.create_temporary_file_name("josh%d"%i, ".rmf")
>>> > Â Â rh = RMF.create_rmf_file(tfn)
>>> >
>>> > On 1 July 2014 17:31, <">> wrote:
>>> >
>>> >> Send IMP-users mailing list submissions to
>>> >> Â Â Â Â ">
>>> >>
>>> >> To subscribe or unsubscribe via the World Wide Web, visit
>>> >> Â Â Â Â https://salilab.org/mailman/listinfo/imp-users
>>> >> or, via email, send a message with subject or body 'help' to
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>>> >>
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>>> >>
>>> >> When replying, please edit your Subject line so it is more specific
>>> >> than "Re: Contents of IMP-users digest..."
>>> >>
>>> >>
>>> >> Today's Topics:
>>> >>
>>> >> Â Â1. Re: Sampling and writing to pym/rmf (Barak Raveh)
>>> >>
>>> >>
>>> >> ----------------------------------------------------------------------
>>> >>
>>> >> Message: 1
>>> >> Date: Tue, 1 Jul 2014 09:31:33 -0700
>>> >> From: Barak Raveh <">>
>>> >> To: Help and discussion for users of IMP <">>
>>> >> Subject: Re: [IMP-users] Sampling and writing to pym/rmf
>>> >> Message-ID:
>>> >> Â Â Â Â <CAHp+_UowiBwJozbwOfi8yFEVt7Z8o2tEZ=
>>> >> ">>
>>> >> 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 <">>
>>> >> 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),
>>> >> > Â Â Â Â Â Â Â Â Â Â Â Â Â Â ÂIMP.algebra.Vector3D(300, 300, 300))
>>> >> >
>>> >> >
>>> >> > # this function creates the molecular hierarchies for the various
>>> >> involved
>>> >> > proteins
>>> >> > def create_representation():
>>> >> > Â Â m= IMP.Model()
>>> >> > Â Â all=IMP.atom.Hierarchy.setup_particle(IMP.Particle(m))
>>> >> > Â Â all.set_name("the universe")
>>> >> > Â Â # create a protein, represented as a set of connected balls of
>>> >> > appropriate
>>> >> > Â Â # radii and number, chose by the resolution parameter and the
>>> >> number of
>>> >> > Â Â # amino acids.
>>> >> >
>>> >> > Â Â def create_protein_from_pdbs(name, files):
>>> >> >
>>> >> > Â Â Â Â def create_from_pdb(file):
>>> >> > Â Â Â Â Â Â sls=IMP.SetLogState(IMP.NONE)
>>> >> > Â Â Â Â Â Â datadir = os.getcwd()
>>> >> > Â Â Â Â Â Â print datadir
>>> >> > Â Â t=IMP.atom.read_pdb( datadir+'/' + file, m,
>>> >> > Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â ÂIMP.atom.ATOMPDBSelector())
>>> >> > Â Â Â Â Â Â del sls
>>> >> > Â Â Â Â Â Â #IMP.atom.show_molecular_hierarchy(t)
>>> >> > Â Â Â Â Â Â c=IMP.atom.Chain(IMP.atom.get_by_type(t,
>>> >> > IMP.atom.CHAIN_TYPE)[0])
>>> >> > Â Â Â Â Â Â if c.get_number_of_children()==0:
>>> >> > Â Â Â Â Â Â Â Â IMP.atom.show_molecular_hierarchy(t)
>>> >> > Â Â Â Â Â Â # there is no reason to use all atoms, just approximate
>>> the
>>> >> > pdb shape instead
>>> >> > Â Â Â Â Â Â s=IMP.atom.create_simplified_along_backbone(c,
>>> >> >
>>> >> resolution/300.0)
>>> >> > Â Â Â Â Â Â IMP.atom.destroy(t)
>>> >> > Â Â Â Â Â Â # make the simplified structure rigid
>>> >> > Â Â Â Â Â Â rb=IMP.atom.create_rigid_body(s)
>>> >> > # Â Â Â Â Â Ârb=IMP.atom.create_rigid_body(c)
>>> >> > Â Â Â Â Â Â rb.set_coordinates_are_optimized(True)
>>> >> > Â Â Â Â Â Â return s
>>> >> > # Â Â Â Â Â Âreturn c
>>> >> >
>>> >> > Â Â Â Â h= create_from_pdb(files[0])
>>> >> > Â Â Â Â h.set_name(name)
>>> >> > Â Â Â Â all.add_child(h)
>>> >> >
>>> >> > Â Â create_protein_from_pdbs("A", [Firstpdb])
>>> >> > Â Â create_protein_from_pdbs("B", [Secondpdb])
>>> >> > Â Â create_protein_from_pdbs("C", [Thirdpdb])
>>> >> > Â Â create_protein_from_pdbs("D", [Fourthpdb])
>>> >> > Â Â #create_protein_from_pdbs("C", ["rpt3_imp.pdb"])
>>> >> > Â Â return (m, all)
>>> >> >
>>> >> > # create the needed restraints and add them to the model
>>> >> >
>>> >> > def create_restraints(m, all):
>>> >> > Â Â def add_connectivity_restraint(s):
>>> >> >
>>> >> > Â Â Â Â tr= IMP.core.TableRefiner()
>>> >> > Â Â Â Â rps=[]
>>> >> > Â Â Â Â for sc in s:
>>> >> > Â Â Â Â Â Â ps= sc.get_selected_particles()
>>> >> > Â Â Â Â Â Â rps.append(ps[0])
>>> >> > Â Â Â Â Â Â tr.add_particle(ps[0], ps)
>>> >> >
>>> >> > Â Â Â Â # duplicate the IMP.atom.create_connectivity_restraint
>>> >> > functionality
>>> >> >
>>> >> > Â Â Â Â score=
>>> >> >
>>> >>
>>> IMP.core.KClosePairsPairScore(IMP.core.HarmonicSphereDistancePairScore(0,1),tr)
>>> >> >
>>> >> > Â Â Â Â r= IMP.core.MSConnectivityRestraint(m,score)
>>> >> >
>>> >> > Â Â Â Â iA = r.add_type([rps[0]])
>>> >> > Â Â Â Â iB = r.add_type([rps[1]])
>>> >> > Â Â Â Â iC = r.add_type([rps[2]])
>>> >> > Â Â Â Â iD = r.add_type([rps[3]])
>>> >> > Â Â Â Â n1 = r.add_composite([iA, iB, iC, iD])
>>> >> > Â Â Â Â n2 = r.add_composite([iA, iB], n1)
>>> >> > Â Â Â Â n3 = r.add_composite([iC, iD], n1)
>>> >> > Â Â Â Â n4 = r.add_composite([iB, iC, iD], n1)
>>> >> >
>>> >> > Â Â Â Â m.add_restraint(r)
>>> >> >
>>> >> > Â Â evr=IMP.atom.create_excluded_volume_restraint([all])
>>> >> > Â Â m.add_restraint(evr)
>>> >> > Â Â # a Selection allows for natural specification of what the
>>> >> restraints
>>> >> > act on
>>> >> > Â Â S= IMP.atom.Selection
>>> >> > Â Â sA=S(hierarchy=all, molecule="A")
>>> >> > Â Â sB=S(hierarchy=all, molecule="B")
>>> >> > Â Â sC=S(hierarchy=all, molecule="C")
>>> >> > Â Â sD=S(hierarchy=all, molecule="D")
>>> >> > Â Â add_connectivity_restraint([sA, sB, sC, sD])
>>> >> >
>>> >> >
>>> >> > # find acceptable conformations of the model
>>> >> > def get_conformations(m):
>>> >> > Â Â sampler= IMP.core.MCCGSampler(m)
>>> >> > Â Â sampler.set_bounding_box(bb)
>>> >> > Â Â # magic numbers, experiment with them and make them large
>>> enough for
>>> >> > things to work
>>> >> > Â Â sampler.set_number_of_conjugate_gradient_steps(100)
>>> >> > Â Â sampler.set_number_of_monte_carlo_steps(20)
>>> >> > Â Â sampler.set_number_of_attempts(models)
>>> >> > Â Â # We don't care to see the output from the sampler
>>> >> > Â Â sampler.set_log_level(IMP.SILENT)
>>> >> > Â Â # return the IMP.ConfigurationSet storing all the found
>>> >> configurations
>>> >> > that
>>> >> > Â Â # meet the various restraint maximum scores.
>>> >> > Â Â cs= sampler.create_sample()
>>> >> > Â Â return cs
>>> >> >
>>> >> >
>>> >> > # cluster the conformations and write them to a file
>>> >> > def analyze_conformations(cs, all, gs):
>>> >> > Â Â # we want to cluster the configurations to make them easier to
>>> >> > understand
>>> >> > Â Â # in the case, the clustering is pretty meaningless
>>> >> > Â Â embed= IMP.statistics.ConfigurationSetXYZEmbedding(cs,
>>> >> >
>>> >> > ÂIMP.container.ListSingletonContainer(IMP.atom.get_leaves(all)),
>>> True)
>>> >> > Â Â cluster= IMP.statistics.create_lloyds_kmeans(embed, 10, 10000)
>>> >> > Â Â # dump each cluster center to a file so it can be viewed.
>>> >> > Â Â for i in range(cluster.get_number_of_clusters()):
>>> >> > Â Â Â Â center= cluster.get_cluster_center(i)
>>> >> > Â Â Â Â cs.load_configuration(i)
>>> >> > Â Â Â Â w= IMP.display.PymolWriter("cluster.%d.pym"%i)
>>> >> > Â Â Â Â for g in gs:
>>> >> > Â Â Â Â Â Â 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()):
>>> >> > Â Â color= IMP.display.get_display_color(i)
>>> >> > Â Â n= all.get_child(i)
>>> >> > Â Â name= n.get_name()
>>> >> > Â Â g= IMP.atom.HierarchyGeometry(n)
>>> >> > Â Â g.set_color(color)
>>> >> > Â Â 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()):
>>> >> > Â Â Â Â cs.load_configuration(i)
>>> >> > Â Â Â Â # print the configuration
>>> >> > Â Â Â Â print "solution number: ",i,"scored :", m.evaluate(False)
>>> >> > Â Â Â Â 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()):
>>> >> > Â Â JOSH = cs.load_configuration(i)
>>> >> > Â Â S= IMP.atom.Selection
>>> >> > Â Â h= IMP.atom.Hierarchy.get_children(cs)
>>> >> > Â Â tfn = IMP.create_temporary_file_name("josh%d"%i, ".rmf")
>>> >> > Â Â rh = RMF.create_rmf_file(tfn)
>>> >> >
>>> >> > Â Â # add the hierarchy to the file
>>> >> > Â Â IMP.rmf.add_hierarchies(rh, h)
>>> >> >
>>> >> > Â Â # add the current configuration to the file as frame 0
>>> >> > Â Â IMP.rmf.save_frame(rh)
>>> >> >
>>> >> > Â Â for g in gs:
>>> >> > Â Â Â Â w.add_geometry(g)
>>> >> >
>>> >> > analyze_conformations(cs, all, gs)
>>> >> >
>>> >> >
>>> >> > _______________________________________________
>>> >> > IMP-users mailing list
>>> >> > ">
>>> >> > https://salilab.org/mailman/listinfo/imp-users
>>> >> >
>>> >> >
>>> >>
>>> >>
>>> >> --
>>> >> Barak
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>>> >> ------------------------------
>>>
>>> >>
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>>>
>>> >>
>>> >
>>> >
>>> > _______________________________________________
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>>>
>>>
>>> --
>>> Barak
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>>
>>
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>
>
> --
> Barak
>
--
Barak
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