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IMP Reference Guide  2.6.0
The Integrative Modeling Platform
kernel/dependency_graph.py

When trying to understand what is going on in IMP, it can often be useful to view the dependency graph, that is, the graph showing how various entities relate to one another. In it, an arrow leads from an IMP::Container or IMP::Particle to an IMP::Restraint if the IMP::Restraint reads from that container or particle. Similarly, an arrow leads from an IMP::Container or IMP::Particle to an IMP::ScoreState if the score state reads from it, and an arrow leads from an IMP::ScoreState to an IMP::Container or IMP::Particle if the score state updates the particle.

The resulting pruned depenency graph is:

1 ## \example kernel/dependency_graph.py
2 # When trying to understand what is going on in \imp, it can often be useful to view the dependency graph, that is, the graph showing how various entities relate to one another. In it, an arrow leads from an IMP::Container or IMP::Particle to an IMP::Restraint if the IMP::Restraint reads from that container or particle. Similarly, an arrow leads from an IMP::Container or IMP::Particle to an IMP::ScoreState if the score state reads from it, and an arrow leads from an IMP::ScoreState to an IMP::Container or IMP::Particle if the score state updates the particle.
3 #
4 # The resulting pruned depenency graph is:
5 # \dotgraph{ \dot
6 # digraph pruned_dependencies {
7 # 0[label="Nup85-12"];
8 # 1[label="Fragment [213-218)"];
9 # 2[label="Nup145C-4"];
10 # 3[label="Atom k distance restraint 2"];
11 # 4[label="Nup1202-8"];
12 # 5[label="Model 0"];
13 # 6[label="Fragment [239-244)"];
14 # 7[label="Nup1332-10"];
15 # 8[label="Nup1201-12"];
16 # 9[label="Connectivity particles"];
17 # 10[label="Nup84-14"];
18 # 11[label="Atom k distance restraint 3"];
19 # 12[label="MovedSingletonContainer2"];
20 # 13[label="Nup1333-16"];
21 # 14[label="Atom k distance restraint 5"];
22 # 15[label="Atom k distance restraint 4"];
23 # 16[label="normalize rigid bodies"];
24 # 17[label="Atom k distance restraint 0"];
25 # 18[label="ListSingletonContainer2"];
26 # 19[label="Chain A rigid body"];
27 # 20[label="ConnectivityRestraint 0"];
28 # 21[label="MovedSingletonContainer1"];
29 # 22[label="ListSingletonContainer1"];
30 # 23[label="HarmonicUpperBoundSphereDistancePairScore2 and ConnectingPairContainer"];
31 # 24[label="HarmonicUpperBoundSphereDistancePairScore1 and ConnectingPairContainer"];
32 # 25[label="Sec13"];
33 # 26[label="Hierarchy EV"];
34 # 27[label="Chain A rigid body rigid body positions"];
35 # 28[label="rigid bodies list"];
36 # 29[label="Atom k distance restraint 1"];
37 # 30[label="HarmonicUpperBoundSphereDistancePairScore0 and ConnectingPairContainer"];
38 # 31[label="ConnectingPairContainer"];
39 # 32[label="ConnectingPairContainer"];
40 # 33[label="Chain A rigid body"];
41 # 34[label="ListSingletonContainer0"];
42 # 35[label="ConnectivityRestraint 1"];
43 # 36[label="MovedSingletonContainer0"];
44 # 37[label="Chain A rigid body rigid body positions"];
45 # 38[label="ConnectingPairContainer"];
46 # 39[label="Seh1"];
47 # 40[label="Hierarchy EV particles"];
48 # 16->19 ;
49 # 16->33 ;
50 # 27->6 ;
51 # 27->39 ;
52 # 37->25 ;
53 # 37->1 ;
54 # 4->3 ;
55 # 2->3 ;
56 # 11->5 ;
57 # 17->5 ;
58 # 23->5 ;
59 # 14->5 ;
60 # 35->5 ;
61 # 15->5 ;
62 # 30->5 ;
63 # 24->5 ;
64 # 29->5 ;
65 # 26->5 ;
66 # 3->5 ;
67 # 20->5 ;
68 # 13->11 ;
69 # 10->11 ;
70 # 2->12 ;
71 # 18->12 ;
72 # 25->14 ;
73 # 2->14 ;
74 # 1->14 ;
75 # 33->14 ;
76 # 0->15 ;
77 # 6->15 ;
78 # 19->15 ;
79 # 39->15 ;
80 # 28->16 ;
81 # 8->17 ;
82 # 4->17 ;
83 # 13->20 ;
84 # 7->20 ;
85 # 22->21 ;
86 # 10->21 ;
87 # 2->23 ;
88 # 38->23 ;
89 # 31->24 ;
90 # 10->24 ;
91 # 0->26 ;
92 # 13->26 ;
93 # 8->26 ;
94 # 7->26 ;
95 # 4->26 ;
96 # 2->26 ;
97 # 6->26 ;
98 # 19->26 ;
99 # 10->26 ;
100 # 40->26 ;
101 # 1->26 ;
102 # 33->26 ;
103 # 19->27 ;
104 # 0->29 ;
105 # 2->29 ;
106 # 0->30 ;
107 # 32->30 ;
108 # 21->31 ;
109 # 22->31 ;
110 # 10->31 ;
111 # 0->32 ;
112 # 36->32 ;
113 # 34->32 ;
114 # 25->35 ;
115 # 2->35 ;
116 # 10->35 ;
117 # 1->35 ;
118 # 33->35 ;
119 # 0->36 ;
120 # 34->36 ;
121 # 33->37 ;
122 # 12->38 ;
123 # 2->38 ;
124 # 18->38 ;
125 # }
126 # \enddot
127 # }
128 
129 import IMP.atom
130 import IMP.container
131 import sys
132 
133 IMP.setup_from_argv(sys.argv, "Example of dependency graphs")
134 
135 
136 def create_representation():
137  m = IMP.Model()
138  all = IMP.atom.Hierarchy.setup_particle(IMP.Particle(m))
139  all.set_name("the universe")
140  rs = []
141 
142  def create_protein(name, ds):
143  h = IMP.atom.create_protein(m, name, 10, ds)
144  leaves = IMP.atom.get_leaves(h)
145  all.add_child(h)
146  r = IMP.atom.create_connectivity_restraint([IMP.atom.Selection(c)
147  for c in h.get_children()],
148  1)
149  if r:
150  rs.append(r)
151 
152  def create_protein_from_pdbs(name, files):
153  def create_from_pdb(file):
154  with IMP.SetLogState(IMP.NONE):
155  t = IMP.atom.read_pdb(
156  IMP.get_example_path("data/" + file), m,
157  IMP.atom.ATOMPDBSelector())
158  # IMP.atom.show_molecular_hierarchy(t)
159  c = IMP.atom.Chain(IMP.atom.get_by_type(t, IMP.atom.CHAIN_TYPE)[0])
160  if c.get_number_of_children() == 0:
161  IMP.atom.show_molecular_hierarchy(t)
162  # there is no reason to use all atoms, just approximate the pdb
163  # shape instead
164  s = IMP.atom.create_simplified_along_backbone(c,
165  10.0 / 2.0)
166  IMP.atom.destroy(t)
167  # make the simplified structure rigid
168  rb = IMP.atom.create_rigid_body(s)
169  rb.set_coordinates_are_optimized(True)
170  return s
171  if len(files) > 1:
172  p = IMP.Particle(m)
173  h = IMP.atom.Hierarchy.setup_particle(p)
174  h.set_name(name)
175  for i, f in enumerate(files):
176  c = create_from_pdb(f)
177  h.add_child(c)
178  c.set_name(name + " chain " + str(i))
179  r = IMP.atom.create_connectivity_restraint([IMP.atom.Selection(c)
180  for c in h.get_children(
181  )],
182  1)
183  if r:
184  rs.append(r)
185  else:
186  h = create_from_pdb(files[0])
187  h.set_name(name)
188  all.add_child(h)
189  create_protein("Nup85", 570)
190  create_protein("Nup84", 460)
191  create_protein("Nup145C", 442)
192  create_protein("Nup120", [0, 500, 761])
193  create_protein("Nup133", [0, 450, 778, 1160])
194  create_protein_from_pdbs("Seh1", ["seh1.pdb"])
195  create_protein_from_pdbs("Sec13", ["sec13.pdb"])
196  return (m, rs, all)
197 
198 
199 def create_restraints(m, rs, all):
200  def add_connectivity_restraint(s):
201  r = IMP.atom.create_connectivity_restraint(s, 1)
202  rs.append(r)
203 
204  def add_distance_restraint(s0, s1):
205  r = IMP.atom.create_distance_restraint(s0, s1, 0, 1)
206  rs.append(r)
207  evr = IMP.atom.create_excluded_volume_restraint([all])
208  rs.append(evr)
209  s0 = IMP.atom.Selection(hierarchy=all, molecule="Nup145C",
210  residue_indexes=range(0, 423))
211  s1 = IMP.atom.Selection(hierarchy=all, molecule="Nup84")
212  s2 = IMP.atom.Selection(hierarchy=all, molecule="Sec13")
213  add_connectivity_restraint([s0, s1, s2])
214  add_distance_restraint(
215  IMP.atom.Selection(hierarchy=all, molecule="Nup145C",
216  residue_indexes=range(0, 423)),
217  IMP.atom.Selection(hierarchy=all, molecule="Nup85"))
218  add_distance_restraint(
219  IMP.atom.Selection(hierarchy=all, molecule="Nup145C",
220  residue_indexes=range(0, 423)),
221  IMP.atom.Selection(hierarchy=all, molecule="Nup120",
222  residue_indexes=range(500, 762)))
223  add_distance_restraint(IMP.atom.Selection(hierarchy=all, molecule="Nup84"),
224  IMP.atom.Selection(hierarchy=all, molecule="Nup133",
225  residue_indexes=range(778, 1160)))
226  add_distance_restraint(IMP.atom.Selection(hierarchy=all, molecule="Nup85"),
227  IMP.atom.Selection(hierarchy=all, molecule="Seh1"))
228  add_distance_restraint(
229  IMP.atom.Selection(hierarchy=all, molecule="Nup145C",
230  residue_indexes=range(0, 423)),
231  IMP.atom.Selection(hierarchy=all, molecule="Sec13"))
232 
233 # now do the actual work
234 (m, rs, all) = create_representation()
235 create_restraints(m, rs, all)
236 
237 sf = IMP.core.RestraintsScoringFunction(rs)
238 
239 # we can get the full dependency graph for the whole model with all the restraints
240 # but it is pretty complex
241 dg = IMP.get_dependency_graph(m)
242 IMP.show_graphviz(dg)
243 
244 # better thing to do is to get the "pruned" graph
245 pdg = IMP.get_pruned_dependency_graph(m)
246 
247 IMP.show_graphviz(pdg)