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IMP Reference Guide  2.16.0
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 dependency graph is:

1 ## \example kernel/dependency_graph.py
2 # When trying to understand what is going on in \imp, it can often be useful
3 # to view the dependency graph, that is, the graph showing how various
4 # entities relate to one another. In it, an arrow leads from an IMP::Container
5 # or IMP::Particle to an IMP::Restraint if the IMP::Restraint reads from that
6 # container or particle. Similarly, an arrow leads from an IMP::Container or
7 # IMP::Particle to an IMP::ScoreState if the score state reads from it, and
8 # an arrow leads from an IMP::ScoreState to an IMP::Container or IMP::Particle
9 # if the score state updates the particle.
10 #
11 # The resulting pruned dependency graph is:
12 # \dotgraph{ \dot
13 # digraph pruned_dependencies {
14 # 0[label="Nup85-12"];
15 # 1[label="Fragment [213-218)"];
16 # 2[label="Nup145C-4"];
17 # 3[label="Atom k distance restraint 2"];
18 # 4[label="Nup1202-8"];
19 # 5[label="Model 0"];
20 # 6[label="Fragment [239-244)"];
21 # 7[label="Nup1332-10"];
22 # 8[label="Nup1201-12"];
23 # 9[label="Connectivity particles"];
24 # 10[label="Nup84-14"];
25 # 11[label="Atom k distance restraint 3"];
26 # 12[label="MovedSingletonContainer2"];
27 # 13[label="Nup1333-16"];
28 # 14[label="Atom k distance restraint 5"];
29 # 15[label="Atom k distance restraint 4"];
30 # 16[label="normalize rigid bodies"];
31 # 17[label="Atom k distance restraint 0"];
32 # 18[label="ListSingletonContainer2"];
33 # 19[label="Chain A rigid body"];
34 # 20[label="ConnectivityRestraint 0"];
35 # 21[label="MovedSingletonContainer1"];
36 # 22[label="ListSingletonContainer1"];
37 # 23[label="HarmonicUpperBoundSphereDistancePairScore2 and ConnectingPairContainer"];
38 # 24[label="HarmonicUpperBoundSphereDistancePairScore1 and ConnectingPairContainer"];
39 # 25[label="Sec13"];
40 # 26[label="Hierarchy EV"];
41 # 27[label="Chain A rigid body rigid body positions"];
42 # 28[label="rigid bodies list"];
43 # 29[label="Atom k distance restraint 1"];
44 # 30[label="HarmonicUpperBoundSphereDistancePairScore0 and ConnectingPairContainer"];
45 # 31[label="ConnectingPairContainer"];
46 # 32[label="ConnectingPairContainer"];
47 # 33[label="Chain A rigid body"];
48 # 34[label="ListSingletonContainer0"];
49 # 35[label="ConnectivityRestraint 1"];
50 # 36[label="MovedSingletonContainer0"];
51 # 37[label="Chain A rigid body rigid body positions"];
52 # 38[label="ConnectingPairContainer"];
53 # 39[label="Seh1"];
54 # 40[label="Hierarchy EV particles"];
55 # 16->19 ;
56 # 16->33 ;
57 # 27->6 ;
58 # 27->39 ;
59 # 37->25 ;
60 # 37->1 ;
61 # 4->3 ;
62 # 2->3 ;
63 # 11->5 ;
64 # 17->5 ;
65 # 23->5 ;
66 # 14->5 ;
67 # 35->5 ;
68 # 15->5 ;
69 # 30->5 ;
70 # 24->5 ;
71 # 29->5 ;
72 # 26->5 ;
73 # 3->5 ;
74 # 20->5 ;
75 # 13->11 ;
76 # 10->11 ;
77 # 2->12 ;
78 # 18->12 ;
79 # 25->14 ;
80 # 2->14 ;
81 # 1->14 ;
82 # 33->14 ;
83 # 0->15 ;
84 # 6->15 ;
85 # 19->15 ;
86 # 39->15 ;
87 # 28->16 ;
88 # 8->17 ;
89 # 4->17 ;
90 # 13->20 ;
91 # 7->20 ;
92 # 22->21 ;
93 # 10->21 ;
94 # 2->23 ;
95 # 38->23 ;
96 # 31->24 ;
97 # 10->24 ;
98 # 0->26 ;
99 # 13->26 ;
100 # 8->26 ;
101 # 7->26 ;
102 # 4->26 ;
103 # 2->26 ;
104 # 6->26 ;
105 # 19->26 ;
106 # 10->26 ;
107 # 40->26 ;
108 # 1->26 ;
109 # 33->26 ;
110 # 19->27 ;
111 # 0->29 ;
112 # 2->29 ;
113 # 0->30 ;
114 # 32->30 ;
115 # 21->31 ;
116 # 22->31 ;
117 # 10->31 ;
118 # 0->32 ;
119 # 36->32 ;
120 # 34->32 ;
121 # 25->35 ;
122 # 2->35 ;
123 # 10->35 ;
124 # 1->35 ;
125 # 33->35 ;
126 # 0->36 ;
127 # 34->36 ;
128 # 33->37 ;
129 # 12->38 ;
130 # 2->38 ;
131 # 18->38 ;
132 # }
133 # \enddot
134 # }
135 
136 import IMP.atom
137 import IMP.container
138 import sys
139 
140 IMP.setup_from_argv(sys.argv, "Example of dependency graphs")
141 
142 
143 def create_representation():
144  m = IMP.Model()
146  all.set_name("the universe")
147  rs = []
148 
149  def create_protein(name, ds):
150  h = IMP.atom.create_protein(m, name, 10, ds)
151  # leaves = IMP.atom.get_leaves(h)
152  all.add_child(h)
154  [IMP.atom.Selection(c) for c in h.get_children()], 1)
155  if r:
156  rs.append(r)
157 
158  def create_protein_from_pdbs(name, files):
159  def create_from_pdb(file):
160  with IMP.SetLogState(IMP.NONE):
161  t = IMP.atom.read_pdb(
162  IMP.get_example_path("data/" + file), m,
164  # IMP.atom.show_molecular_hierarchy(t)
165  c = IMP.atom.Chain(IMP.atom.get_by_type(t, IMP.atom.CHAIN_TYPE)[0])
166  if c.get_number_of_children() == 0:
168  # there is no reason to use all atoms, just approximate the pdb
169  # shape instead
171  10.0 / 2.0)
172  IMP.atom.destroy(t)
173  # make the simplified structure rigid
175  rb.set_coordinates_are_optimized(True)
176  return s
177  if len(files) > 1:
178  p = IMP.Particle(m)
180  h.set_name(name)
181  for i, f in enumerate(files):
182  c = create_from_pdb(f)
183  h.add_child(c)
184  c.set_name(name + " chain " + str(i))
186  [IMP.atom.Selection(c) for c in h.get_children()], 1)
187  if r:
188  rs.append(r)
189  else:
190  h = create_from_pdb(files[0])
191  h.set_name(name)
192  all.add_child(h)
193  create_protein("Nup85", 570)
194  create_protein("Nup84", 460)
195  create_protein("Nup145C", 442)
196  create_protein("Nup120", [0, 500, 761])
197  create_protein("Nup133", [0, 450, 778, 1160])
198  create_protein_from_pdbs("Seh1", ["seh1.pdb"])
199  create_protein_from_pdbs("Sec13", ["sec13.pdb"])
200  return (m, rs, all)
201 
202 
203 def create_restraints(m, rs, all):
204  def add_connectivity_restraint(s):
206  rs.append(r)
207 
208  def add_distance_restraint(s0, s1):
209  r = IMP.atom.create_distance_restraint(s0, s1, 0, 1)
210  rs.append(r)
212  rs.append(evr)
213  s0 = IMP.atom.Selection(hierarchy=all, molecule="Nup145C",
214  residue_indexes=range(0, 423))
215  s1 = IMP.atom.Selection(hierarchy=all, molecule="Nup84")
216  s2 = IMP.atom.Selection(hierarchy=all, molecule="Sec13")
217  add_connectivity_restraint([s0, s1, s2])
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="Nup85"))
222  add_distance_restraint(
223  IMP.atom.Selection(hierarchy=all, molecule="Nup145C",
224  residue_indexes=range(0, 423)),
225  IMP.atom.Selection(hierarchy=all, molecule="Nup120",
226  residue_indexes=range(500, 762)))
227  add_distance_restraint(IMP.atom.Selection(hierarchy=all, molecule="Nup84"),
229  hierarchy=all, molecule="Nup133",
230  residue_indexes=range(778, 1160)))
231  add_distance_restraint(IMP.atom.Selection(hierarchy=all, molecule="Nup85"),
232  IMP.atom.Selection(hierarchy=all, molecule="Seh1"))
233  add_distance_restraint(
234  IMP.atom.Selection(hierarchy=all, molecule="Nup145C",
235  residue_indexes=range(0, 423)),
236  IMP.atom.Selection(hierarchy=all, molecule="Sec13"))
237 
238 
239 # now do the actual work
240 (m, rs, all) = create_representation()
241 create_restraints(m, rs, all)
242 
244 
245 # we can get the full dependency graph for the whole model with all
246 # the restraints but it is pretty complex
249 
250 # better thing to do is to get the "pruned" graph
252