1 """@namespace IMP.pmi1.restraints.saxs
2 Restraints for handling small angle x-ray (SAXS) data.
5 from __future__
import print_function
19 """Basic SAXS restraint."""
21 def __init__(self, input_objects, saxs_datafile, weight=1.0,
22 ff_type=IMP.saxs.HEAVY_ATOMS, label=
None, maxq=
"standard"):
23 """Builds the restraint.
24 @param input_objects A list of hierarchies or PMI objects that the
25 SAXS restraint will be applied to. This hierarchy MUST be
26 atomic. You can pass a list of CA atom particles to evaluate
28 @param saxs_datafile the SAXS .dat file.
29 @param weight Restraint score coefficient
30 @param ff_type the form factor to use, of the following types:
31 - IMP.saxs.HEAVY_ATOMS: use form factors with implicit
33 - IMP.saxs.ALL_ATOMS: use individual form factors for all
34 atoms. Does not build missing hydrogens.
35 - IMP.saxs.CA_ATOMS: use residue based form factors
37 @param label Label for the restraint in outputs
39 @param maxq - maximum q value that the restraint will be evaluated at
40 Default values for ff_type = ALL_ATOMS : 0.5. HEAVY_ATOMS : 0.4,
41 CA_ATOMS and RESIDUES = 0.15. These values were eyeballed
42 by comparing ALL_ATOM calculated SAXS profiles to those calculated
43 with the reduced representations, so could be improved.
48 model = list(hiers)[0].get_model()
49 super(SAXSRestraint, self).
__init__(model, label=label, weight=weight)
52 if maxq ==
"standard":
53 if ff_type == IMP.saxs.CA_ATOMS
or ff_type == IMP.saxs.RESIDUES:
55 elif ff_type == IMP.saxs.HEAVY_ATOMS:
59 elif type(maxq) == float:
60 if maxq < 0.01
or maxq > 4.0:
61 raise Exception(
"SAXSRestraint: maxq must be set between 0.01 and 4.0")
62 if (ff_type == IMP.saxs.CA_ATOMS
or ff_type == IMP.saxs.RESIDUES)
and maxq > 0.15:
63 print(
"SAXSRestraint: WARNING> for residue-resolved form factors, a maxq > 0.15 is not recommended!")
65 raise Exception(
"SAXSRestraint: maxq must be set to a number between 0.01 and 4.0")
70 if ff_type == IMP.saxs.RESIDUES:
72 hiers, resolution=1).get_selected_particles()
74 elif ff_type == IMP.saxs.CA_ATOMS:
76 hiers, atom_type=IMP.atom.AT_CA).get_selected_particles()
78 elif ff_type == IMP.saxs.HEAVY_ATOMS
or ff_type == IMP.saxs.ALL_ATOMS:
80 hiers, resolution=0).get_selected_particles()
83 raise Exception(
"SAXSRestraint: Must provide an IMP.saxs atom type: RESIDUES, CA_ATOMS, HEAVY_ATOMS or ALL_ATOMS")
85 if len(self.particles) == 0:
86 raise Exception(
"SAXSRestraint: There are no selected particles")
90 self.rs.add_restraint(self.restraint)
95 """Basic SAXS restraint using ISD."""
101 print(
"Module isd2 not installed. Cannot use SAXSISDRestraint")
103 def __init__(self, representation, profile, resolution=0, weight=1,
104 ff_type=IMP.saxs.HEAVY_ATOMS, label=
None):
106 model = representation.prot.get_model()
107 super(SAXSISDRestraint, self).
__init__(model, label=label,
110 self.taumaxtrans = 0.05
115 resolution=resolution)
118 self.gamma = IMP.pmi1.tools.SetupNuisance(
119 self.model, 1., 0.,
None,
False).get_particle()
122 self.sigma = IMP.pmi1.tools.SetupNuisance(self.model, 10.0, 0.,
None,
False
126 self.tau = IMP.pmi1.tools.SetupNuisance(self.model, 1., 0.,
None,
False,
130 self.c1 = IMP.pmi1.tools.SetupNuisance(self.model, 1.0, 0.95, 1.05,
132 self.c2 = IMP.pmi1.tools.SetupNuisance(self.model, 0.0, -2., 4.,
136 self.w = IMP.pmi1.tools.SetupWeight(self.model).get_particle()
140 self.cov = [[1
if i == j
else 0
for j
in range(self.prof.size())]
141 for i
in range(self.prof.size())]
143 print(
"create saxs restraint")
144 self.saxs = IMP.isd2.SAXSRestraint(self.prof, self.sigma, self.tau,
145 self.gamma, self.w, self.c1,
147 self.saxs.add_scatterer(self.atoms, self.cov, ff_type)
149 self.rs.add_restraint(self.saxs)
154 self.rs2 = self._create_restraint_set(
'Prior')
157 self.rs2.add_restraint(j1)
159 self.rs2.add_restraint(j2)
161 self.rs2.add_restraint(j3)
164 pw.set_weights(pw.get_unit_simplex().get_barycenter())
165 pw.set_weights_are_optimized(
True)
168 """Set sigma to the value that maximizes its conditional likelihood"""
170 sigma2hat = self.saxs.get_sigmasq_scale_parameter() \
171 / (self.saxs.get_sigmasq_shape_parameter() + 1)
175 """Set gamma to the value that maximizes its conditional likelihood"""
177 gammahat = math.exp(self.saxs.get_loggamma_variance_parameter() *
178 self.saxs.get_loggamma_jOg_parameter())
181 def optimize_tau(self, ltaumin=-2, ltaumax=3, npoints=100):
185 fl = open(
'tauvals.txt',
'w')
186 for tauval
in self._logspace(ltaumin, ltaumax, npoints):
189 values.append((self.model.evaluate(
False), tauval))
192 fl.write(
'%G %G\n' % (values[-1][1], values[-1][0]))
194 ltcenter = math.log(values[0][1]) / math.log(10)
195 spacing = (ltaumax - ltaumin) / float(npoints)
197 for tauval
in self._logspace(
198 ltcenter - 2 * spacing, ltcenter + 2 * spacing,
201 values.append((self.model.evaluate(
False), tauval))
202 fl.write(
'%G %G\n' % (values[-1][1], values[-1][0]))
207 """Get value of gamma."""
208 return self.gamma.get_scale()
210 def set_taumaxtrans(self, taumaxtrans):
211 self.taumaxtrans = taumaxtrans
214 """Draw 1/sigma2 from gamma distribution."""
216 self.saxs.draw_sigma()
219 """Draw gamma from lognormal distribution."""
221 self.saxs.draw_gamma()
223 def update_covariance_matrix(self):
228 self.cov = IMP.isd2.compute_relative_covariance(self.atoms, c1, c2,
233 self.saxs.set_cov(0, self.cov)
235 def write_covariance_matrix(self, fname):
236 fl = open(fname,
'w')
237 for line
in self.cov:
243 output = super(SAXSISDRestraint, self).
get_output()
244 suffix = self._get_label_suffix()
245 output[
"SAXSISDRestraint_Sigma" +
246 suffix] = str(self.sigma.get_scale())
247 output[
"SAXSISDRestraint_Tau" + suffix] = str(self.tau.get_scale())
248 output[
"SAXSISDRestraint_Gamma" +
249 suffix] = str(self.gamma.get_scale())
253 def _logspace(a, b, num=100):
254 """Mimic numpy's logspace function"""
256 val = a + float(b - a) / float(num - 1) * i
Add weights to a particle.
def draw_gamma
Draw gamma from lognormal distribution.
def optimize_sigma
Set sigma to the value that maximizes its conditional likelihood.
Various classes to hold sets of particles.
Calculate score based on fit to SAXS profile.
void write_pdb(const Selection &mhd, TextOutput out, unsigned int model=1)
Classes to handle different kinds of restraints.
Add scale parameter to particle.
def optimize_gamma
Set gamma to the value that maximizes its conditional likelihood.
def get_output
Get outputs to write to stat files.
def __init__
Builds the restraint.
Add nuisance parameter to particle.
Base class for PMI restraints, which wrap IMP.Restraint(s).
Basic functionality that is expected to be used by a wide variety of IMP users.
General purpose algebraic and geometric methods that are expected to be used by a wide variety of IMP...
The general base class for IMP exceptions.
def draw_sigma
Draw 1/sigma2 from gamma distribution.
Functionality for loading, creating, manipulating and scoring atomic structures.
Select hierarchy particles identified by the biological name.
def get_gamma_value
Get value of gamma.
Basic SAXS restraint using ISD.
Support for small angle X-ray scattering (SAXS) data.
Inferential scoring building on methods developed as part of the Inferential Structure Determination ...