def __init__(self,options,tgt_opts,forcefield):
super(BindingEnergy,self).__init__(options,tgt_opts,forcefield)
self.set_option(None, None, 'inter_txt', os.path.join(self.tgtdir,tgt_opts['inter_txt']))
self.global_opts, self.sys_opts, self.inter_opts = parse_interactions(self.inter_txt)
# If the global option doesn't exist in the system / interaction, then it is copied over.
for opt in self.global_opts:
for sys in self.sys_opts:
if opt not in self.sys_opts[sys]:
self.sys_opts[sys][opt] = self.global_opts[opt]
for inter in self.inter_opts:
if opt not in self.inter_opts[inter]:
self.inter_opts[inter][opt] = self.global_opts[opt]
for inter in self.inter_opts:
if 'energy_unit' in self.inter_opts[inter] and self.inter_opts[inter]['energy_unit'].lower() not in ['kilocalorie_per_mole', 'kilocalories_per_mole']:
logger.error('Usage of physical units is has been removed, please provide all binding energies in kcal/mole\n')
raise RuntimeError
self.inter_opts[inter]['reference_physical'] = self.inter_opts[inter]['energy']
if tgt_opts['energy_denom'] == 0.0:
self.set_option(None, None, 'energy_denom', val=np.std(np.array([val['reference_physical'] for val in self.inter_opts.values()])))
else:
self.set_option(None, None, 'energy_denom', val=tgt_opts['energy_denom'])
self.set_option(None, None, 'rmsd_denom', val=tgt_opts['rmsd_denom'])
self.set_option(tgt_opts,'cauchy')
self.set_option(tgt_opts,'attenuate')
## LPW 2018-02-11: This is set to True if the target calculates
## a single-point property over several existing snapshots.
self.loop_over_snapshots = False
logger.info("The energy denominator is: %s\n" % str(self.energy_denom))
logger.info("The RMSD denominator is: %s\n" % str(self.rmsd_denom))
if self.cauchy:
logger.info("Each contribution to the interaction energy objective function will be scaled by 1.0 / ( denom**2 + reference**2 )\n")
if self.attenuate:
logger.error('attenuate and cauchy are mutually exclusive\n')
raise RuntimeError
elif self.attenuate:
logger.info("Repulsive interactions beyond energy_denom will be scaled by 1.0 / ( denom**2 + (reference-denom)**2 )\n")
## Build keyword dictionaries to pass to engine.
engine_args = OrderedDict(list(self.OptionDict.items()) + list(options.items()))
del engine_args['name']
## Create engine objects.
self.engines = OrderedDict()
for sysname,sysopt in self.sys_opts.items():
M = Molecule(os.path.join(self.root, self.tgtdir, sysopt['geometry']))
if 'select' in sysopt:
atomselect = np.array(uncommadash(sysopt['select']))
M = M.atom_select(atomselect)
if self.FF.rigid_water: M.rigid_water()
self.engines[sysname] = self.engine_(target=self, mol=M, name=sysname, tinker_key=os.path.join(sysopt['keyfile']), **engine_args)
def prepare_temp_directory(self, options, tgt_opts):
abstempdir = os.path.join(self.root,self.tempdir)
if self.FF.rigid_water:
self.optprog = "optrigid"
#LinkFile(os.path.join(self.root,self.tgtdir,"rigid.key"),os.path.join(abstempdir,"rigid.key"))
else:
self.optprog = "optimize"
# Link the necessary programs into the temporary directory
LinkFile(os.path.join(options['tinkerpath'],"analyze"),os.path.join(abstempdir,"analyze"))
LinkFile(os.path.join(options['tinkerpath'],self.optprog),os.path.join(abstempdir,self.optprog))
LinkFile(os.path.join(options['tinkerpath'],"superpose"),os.path.join(abstempdir,"superpose"))
# Link the run parameter file
# The master file might be unneeded??
for sysname,sysopt in self.sys_opts.items():
if self.FF.rigid_water:
# Make every water molecule rigid
# WARNING: Hard coded values here!
M = Molecule(os.path.join(self.root, self.tgtdir, sysopt['geometry']),ftype="tinker")
for a in range(0, len(M.xyzs[0]), 3):
flex = M.xyzs[0]
wat = flex[a:a+3]
com = wat.mean(0)
wat -= com
o = wat[0]
h1 = wat[1]
h2 = wat[2]
r1 = h1 - o
r2 = h2 - o
r1 /= Np.linalg.norm(r1)
r2 /= Np.linalg.norm(r2)
# Obtain unit vectors.
ex = r1 + r2
ey = r1 - r2
ex /= Np.linalg.norm(ex)
ey /= Np.linalg.norm(ey)
Bond = 0.9572
Ang = Np.pi * 104.52 / 2 / 180
cosx = Np.cos(Ang)
cosy = Np.sin(Ang)
h1 = o + Bond*ex*cosx + Bond*ey*cosy
h2 = o + Bond*ex*cosx - Bond*ey*cosy
rig = Np.array([o, h1, h2]) + com
M.xyzs[0][a:a+3] = rig
M.write(os.path.join(abstempdir,sysopt['geometry']),ftype="tinker")
else:
M = Molecule(os.path.join(self.root, self.tgtdir, sysopt['geometry']),ftype="tinker")
if 'select' in sysopt:
atomselect = Np.array(uncommadash(sysopt['select']))
#atomselect = eval("Np.arange(M.na)"+sysopt['select'])
M = M.atom_select(atomselect)
M.write(os.path.join(abstempdir,sysname+".xyz"),ftype="tinker")
write_key_with_prm(os.path.join(self.root,self.tgtdir,sysopt['keyfile']),os.path.join(abstempdir,sysname+".key"),ffobj=self.FF)
def __init__(self,options,tgt_opts,forcefield):
super(BindingEnergy,self).__init__(options,tgt_opts,forcefield)
self.set_option(None, None, 'inter_txt', os.path.join(self.tgtdir,tgt_opts['inter_txt']))
self.global_opts, self.sys_opts, self.inter_opts = parse_interactions(self.inter_txt)
# If the global option doesn't exist in the system / interaction, then it is copied over.
for opt in self.global_opts:
for sys in self.sys_opts:
if opt not in self.sys_opts[sys]:
self.sys_opts[sys][opt] = self.global_opts[opt]
for inter in self.inter_opts:
if opt not in self.inter_opts[inter]:
self.inter_opts[inter][opt] = self.global_opts[opt]
for inter in self.inter_opts:
if 'energy_unit' in self.inter_opts[inter] and self.inter_opts[inter]['energy_unit'].lower() not in ['kilocalorie_per_mole', 'kilocalories_per_mole']:
logger.error('Usage of physical units is has been removed, please provide all binding energies in kcal/mole\n')
raise RuntimeError
self.inter_opts[inter]['reference_physical'] = self.inter_opts[inter]['energy']
if tgt_opts['energy_denom'] == 0.0:
self.set_option(None, None, 'energy_denom', val=np.std(np.array([val['reference_physical'] for val in self.inter_opts.values()])))
else:
self.set_option(None, None, 'energy_denom', val=tgt_opts['energy_denom'])
self.set_option(None, None, 'rmsd_denom', val=tgt_opts['rmsd_denom'])
self.set_option(tgt_opts,'cauchy')
self.set_option(tgt_opts,'attenuate')
logger.info("The energy denominator is: %s\n" % str(self.energy_denom))
logger.info("The RMSD denominator is: %s\n" % str(self.rmsd_denom))
if self.cauchy:
logger.info("Each contribution to the interaction energy objective function will be scaled by 1.0 / ( denom**2 + reference**2 )\n")
if self.attenuate:
logger.error('attenuate and cauchy are mutually exclusive\n')
raise RuntimeError
elif self.attenuate:
logger.info("Repulsive interactions beyond energy_denom will be scaled by 1.0 / ( denom**2 + (reference-denom)**2 )\n")
## Build keyword dictionaries to pass to engine.
engine_args = OrderedDict(self.OptionDict.items() + options.items())
del engine_args['name']
## Create engine objects.
self.engines = OrderedDict()
for sysname,sysopt in self.sys_opts.items():
M = Molecule(os.path.join(self.root, self.tgtdir, sysopt['geometry']))
if 'select' in sysopt:
atomselect = np.array(uncommadash(sysopt['select']))
M = M.atom_select(atomselect)
if self.FF.rigid_water: M.rigid_water()
self.engines[sysname] = self.engine_(target=self, mol=M, name=sysname, tinker_key=os.path.join(sysopt['keyfile']), **engine_args)
def __init__(self,options,tgt_opts,forcefield):
super(BindingEnergy,self).__init__(options,tgt_opts,forcefield)
self.set_option(None, None, 'inter_txt', os.path.join(self.tgtdir,tgt_opts['inter_txt']))
self.global_opts, self.sys_opts, self.inter_opts = parse_interactions(self.inter_txt)
# If the global option doesn't exist in the system / interaction, then it is copied over.
for opt in self.global_opts:
for sys in self.sys_opts:
if opt not in self.sys_opts[sys]:
self.sys_opts[sys][opt] = self.global_opts[opt]
for inter in self.inter_opts:
if opt not in self.inter_opts[inter]:
self.inter_opts[inter][opt] = self.global_opts[opt]
for inter in self.inter_opts:
if 'energy_unit' in self.inter_opts[inter] and self.inter_opts[inter]['energy_unit'].lower() not in ['kilocalorie_per_mole', 'kilocalories_per_mole']:
logger.error('Usage of physical units is has been removed, please provide all binding energies in kcal/mole\n')
raise RuntimeError
self.inter_opts[inter]['reference_physical'] = self.inter_opts[inter]['energy']
if tgt_opts['energy_denom'] == 0.0:
self.set_option(None, None, 'energy_denom', val=np.std(np.array([val['reference_physical'] for val in self.inter_opts.values()])))
else:
self.set_option(None, None, 'energy_denom', val=tgt_opts['energy_denom'])
self.set_option(None, None, 'rmsd_denom', val=tgt_opts['rmsd_denom'])
self.set_option(tgt_opts,'attenuate')
## LPW 2018-02-11: This is set to True if the target calculates
## a single-point property over several existing snapshots.
self.loop_over_snapshots = False
logger.info("The energy denominator is: %s\n" % str(self.energy_denom))
logger.info("The RMSD denominator is: %s\n" % str(self.rmsd_denom))
if self.attenuate:
denom = self.energy_denom
logger.info("Interaction energies more positive than %.1f will have reduced weight going as: 1.0 / (%.1f^2 + (energy-%.1f)^2)\n" % (denom, denom, denom))
## Build keyword dictionaries to pass to engine.
engine_args = OrderedDict(list(self.OptionDict.items()) + list(options.items()))
engine_args.pop('name', None)
## Create engine objects.
self.engines = OrderedDict()
for sysname,sysopt in self.sys_opts.items():
M = Molecule(os.path.join(self.root, self.tgtdir, sysopt['geometry']))
if 'select' in sysopt:
atomselect = np.array(uncommadash(sysopt['select']))
M = M.atom_select(atomselect)
if self.FF.rigid_water: M.rigid_water()
self.engines[sysname] = self.engine_(target=self, mol=M, name=sysname, tinker_key=os.path.join(sysopt['keyfile']), **engine_args)
class AMBER(Engine):
""" Engine for carrying out general purpose AMBER calculations. """
def __init__(self, name="amber", **kwargs):
## Keyword args that aren't in this list are filtered out.
self.valkwd = ['amberhome', 'pdb', 'mol2', 'frcmod', 'leapcmd']
super(AMBER,self).__init__(name=name, **kwargs)
def setopts(self, **kwargs):
""" Called by __init__ ; Set AMBER-specific options. """
## The directory containing TINKER executables (e.g. dynamic)
if 'amberhome' in kwargs:
self.amberhome = kwargs['amberhome']
if not os.path.exists(os.path.join(self.amberhome,"sander")):
warn_press_key("The 'sander' executable indicated by %s doesn't exist! (Check amberhome)" \
% os.path.join(self.amberhome,"sander"))
else:
warn_once("The 'amberhome' option was not specified; using default.")
if which('sander') == '':
warn_press_key("Please add AMBER executables to the PATH or specify amberhome.")
self.amberhome = os.path.split(which('sander'))[0]
with wopen('.quit.leap') as f:
print >> f, 'quit'
# AMBER search path
self.spath = []
for line in self.callamber('tleap -f .quit.leap'):
if 'Adding' in line and 'to search path' in line:
self.spath.append(line.split('Adding')[1].split()[0])
os.remove('.quit.leap')
def readsrc(self, **kwargs):
""" Called by __init__ ; read files from the source directory. """
self.leapcmd = onefile(kwargs.get('leapcmd'), 'leap', err=True)
self.absleap = os.path.abspath(self.leapcmd)
# Name of the molecule, currently just call it a default name.
self.mname = 'molecule'
if 'mol' in kwargs:
self.mol = kwargs['mol']
elif 'coords' in kwargs:
crdfile = onefile(kwargs.get('coords'), None, err=True)
self.mol = Molecule(crdfile, build_topology=False)
# AMBER has certain PDB requirements, so we will absolutely require one.
needpdb = True
# if hasattr(self, 'mol') and all([i in self.mol.Data.keys() for i in ["chain", "atomname", "resid", "resname", "elem"]]):
# needpdb = False
# Determine the PDB file name.
# If 'pdb' is provided to Engine initialization, it will be used to
# copy over topology information (chain, atomname etc.). If mol/coords
# is not provided, then it will also provide the coordinates.
pdbfnm = onefile(kwargs.get('pdb'), 'pdb' if needpdb else None, err=needpdb)
if pdbfnm != None:
mpdb = Molecule(pdbfnm, build_topology=False)
if hasattr(self, 'mol'):
for i in ["chain", "atomname", "resid", "resname", "elem"]:
self.mol.Data[i] = mpdb.Data[i]
else:
self.mol = copy.deepcopy(mpdb)
self.abspdb = os.path.abspath(pdbfnm)
# Write the PDB that AMBER is going to read in.
# This may or may not be identical to the one used to initialize the engine.
# self.mol.write('%s.pdb' % self.name)
# self.abspdb = os.path.abspath('%s.pdb' % self.name)
def callamber(self, command, stdin=None, print_to_screen=False, print_command=False, **kwargs):
""" Call TINKER; prepend the amberhome to calling the TINKER program. """
csplit = command.split()
# Sometimes the engine changes dirs and the inpcrd/prmtop go missing, so we link it.
# Prepend the AMBER path to the program call.
prog = os.path.join(self.amberhome, "bin", csplit[0])
csplit[0] = prog
# No need to catch exceptions since failed AMBER calculations will return nonzero exit status.
o = _exec(' '.join(csplit), stdin=stdin, print_to_screen=print_to_screen, print_command=print_command, rbytes=1024, **kwargs)
return o
def leap(self, name=None, delcheck=False):
if not os.path.exists(self.leapcmd):
LinkFile(self.absleap, self.leapcmd)
pdb = os.path.basename(self.abspdb)
if not os.path.exists(pdb):
LinkFile(self.abspdb, pdb)
if name == None: name = self.name
write_leap(self.leapcmd, mol2=self.mol2, frcmod=self.frcmod, pdb=pdb, prefix=name, spath=self.spath, delcheck=delcheck)
self.callamber("tleap -f %s_" % self.leapcmd)
def prepare(self, pbc=False, **kwargs):
""" Called by __init__ ; prepare the temp directory and figure out the topology. """
if hasattr(self,'FF'):
if not (os.path.exists(self.FF.amber_frcmod) and os.path.exists(self.FF.amber_mol2)):
# If the parameter files don't already exist, create them for the purpose of
# preparing the engine, but then delete them afterward.
prmtmp = True
self.FF.make(np.zeros(self.FF.np))
# Currently force field object only allows one mol2 and frcmod file although this can be lifted.
self.mol2 = [self.FF.amber_mol2]
self.frcmod = [self.FF.amber_frcmod]
if 'mol2' in kwargs:
logger.error("FF object is provided, which overrides mol2 keyword argument")
raise RuntimeError
if 'frcmod' in kwargs:
logger.error("FF object is provided, which overrides frcmod keyword argument")
raise RuntimeError
else:
prmtmp = False
self.mol2 = listfiles(kwargs.get('mol2'), 'mol2', err=True)
self.frcmod = listfiles(kwargs.get('frcmod'), 'frcmod', err=True)
# Figure out the topology information.
self.leap()
o = self.callamber("rdparm %s.prmtop" % self.name,
stdin="printAtoms\nprintBonds\nexit\n",
persist=True, print_error=False)
# Once we do this, we don't need the prmtop and inpcrd anymore
os.unlink("%s.inpcrd" % self.name)
os.unlink("%s.prmtop" % self.name)
os.unlink("leap.log")
mode = 'None'
self.AtomLists = defaultdict(list)
G = nx.Graph()
for line in o:
s = line.split()
if 'Atom' in line:
mode = 'Atom'
elif 'Bond' in line:
mode = 'Bond'
elif 'RDPARM MENU' in line:
continue
elif 'EXITING' in line:
break
elif len(s) == 0:
continue
elif mode == 'Atom':
# Based on parsing lines like these:
"""
327: HA -0.01462 1.0 ( 23:HIP ) H1 E
328: CB -0.33212 12.0 ( 23:HIP ) CT 3
329: HB2 0.10773 1.0 ( 23:HIP ) HC E
330: HB3 0.10773 1.0 ( 23:HIP ) HC E
331: CG 0.18240 12.0 ( 23:HIP ) CC B
"""
# Based on variable width fields.
atom_number = int(line.split(':')[0])
atom_name = line.split()[1]
atom_charge = float(line.split()[2])
atom_mass = float(line.split()[3])
rnn = line.split('(')[1].split(')')[0].split(':')
residue_number = int(rnn[0])
residue_name = rnn[1]
atom_type = line.split(')')[1].split()[0]
self.AtomLists['Name'].append(atom_name)
self.AtomLists['Charge'].append(atom_charge)
self.AtomLists['Mass'].append(atom_mass)
self.AtomLists['ResidueNumber'].append(residue_number)
self.AtomLists['ResidueName'].append(residue_name)
# Not sure if this works
G.add_node(atom_number)
elif mode == 'Bond':
a, b = (int(i) for i in (line.split('(')[1].split(')')[0].split(',')))
G.add_edge(a, b)
self.AtomMask = [a == 'A' for a in self.AtomLists['ParticleType']]
# Use networkx to figure out a list of molecule numbers.
# gs = nx.connected_component_subgraphs(G)
# tmols = [gs[i] for i in np.argsort(np.array([min(g.nodes()) for g in gs]))]
# mnodes = [m.nodes() for m in tmols]
# self.AtomLists['MoleculeNumber'] = [[i+1 in m for m in mnodes].index(1) for i in range(self.mol.na)]
## Write out the trajectory coordinates to a .mdcrd file.
# I also need to write the trajectory
if 'boxes' in self.mol.Data.keys():
warn_press_key("Writing %s-all.crd file with no periodic box information" % self.name)
del self.mol.Data['boxes']
if hasattr(self, 'target') and hasattr(self.target,'shots'):
self.qmatoms = target.qmatoms
self.mol.write("%s-all.crd" % self.name, select=range(self.target.shots), ftype="mdcrd")
else:
self.qmatoms = self.mol.na
self.mol.write("%s-all.crd" % self.name, ftype="mdcrd")
if prmtmp:
for f in self.FF.fnms:
os.unlink(f)
def evaluate_(self, crdin, force=False):
"""
Utility function for computing energy and forces using AMBER.
Inputs:
crdin: AMBER .mdcrd file name.
force: Switch for parsing the force. (Currently it always calculates the forces.)
Outputs:
Result: Dictionary containing energies (and optionally) forces.
"""
force_mdin="""Loop over conformations and compute energy and force (use ioutfnm=1 for netcdf, ntb=0 for no box)
&cntrl
imin = 5, ntb = 0, cut=9, nstlim = 0, nsnb = 0
/
&debugf
do_debugf = 1, dumpfrc = 1
/
"""
with wopen("%s-force.mdin" % self.name) as f:
print >> f, force_mdin
## This line actually runs AMBER.
self.leap(delcheck=True)
self.callamber("sander -i %s-force.mdin -o %s-force.mdout -p %s.prmtop -c %s.inpcrd -y %s -O" %
(self.name, self.name, self.name, self.name, crdin))
ParseMode = 0
Result = {}
Energies = []
Forces = []
Force = []
for line in open('forcedump.dat'):
line = line.strip()
sline = line.split()
if ParseMode == 1:
if len(sline) == 1 and isfloat(sline[0]):
Energies.append(float(sline[0]) * 4.184)
ParseMode = 0
if ParseMode == 2:
if len(sline) == 3 and all(isfloat(sline[i]) for i in range(3)):
Force += [float(sline[i]) * 4.184 * 10 for i in range(3)]
if len(Force) == 3*self.qmatoms:
Forces.append(np.array(Force))
Force = []
ParseMode = 0
if line == '0 START of Energies':
ParseMode = 1
elif line == '1 Total Force':
ParseMode = 2
Result["Energy"] = np.array(Energies[1:])
Result["Force"] = np.array(Forces[1:])
return Result
def energy_force_one(self, shot):
""" Computes the energy and force using TINKER for one snapshot. """
self.mol[shot].write("%s.xyz" % self.name, ftype="tinker")
Result = self.evaluate_("%s.xyz" % self.name, force=True)
return np.hstack((Result["Energy"].reshape(-1,1), Result["Force"]))
def energy(self):
""" Computes the energy using TINKER over a trajectory. """
if hasattr(self, 'md_trajectory') :
x = self.md_trajectory
else:
x = "%s-all.crd" % self.name
self.mol.write(x, ftype="tinker")
return self.evaluate_(x)["Energy"]
def energy_force(self):
""" Computes the energy and force using AMBER over a trajectory. """
if hasattr(self, 'md_trajectory') :
x = self.md_trajectory
else:
x = "%s-all.crd" % self.name
Result = self.evaluate_(x, force=True)
return np.hstack((Result["Energy"].reshape(-1,1), Result["Force"]))
def energy_dipole(self):
""" Computes the energy and dipole using TINKER over a trajectory. """
logger.error('Dipole moments are not yet implemented in AMBER interface')
raise NotImplementedError
if hasattr(self, 'md_trajectory') :
x = self.md_trajectory
else:
x = "%s.xyz" % self.name
self.mol.write(x, ftype="tinker")
Result = self.evaluate_(x, dipole=True)
return np.hstack((Result["Energy"].reshape(-1,1), Result["Dipole"]))
def optimize(self, shot=0, method="newton", crit=1e-4):
""" Optimize the geometry and align the optimized geometry to the starting geometry. """
logger.error('Geometry optimizations are not yet implemented in AMBER interface')
raise NotImplementedError
# Code from tinkerio.py
if os.path.exists('%s.xyz_2' % self.name):
os.unlink('%s.xyz_2' % self.name)
self.mol[shot].write('%s.xyz' % self.name, ftype="tinker")
if method == "newton":
if self.rigid: optprog = "optrigid"
else: optprog = "optimize"
elif method == "bfgs":
if self.rigid: optprog = "minrigid"
else: optprog = "minimize"
o = self.calltinker("%s %s.xyz %f" % (optprog, self.name, crit))
# Silently align the optimized geometry.
M12 = Molecule("%s.xyz" % self.name, ftype="tinker") + Molecule("%s.xyz_2" % self.name, ftype="tinker")
if not self.pbc:
M12.align(center=False)
M12[1].write("%s.xyz_2" % self.name, ftype="tinker")
rmsd = M12.ref_rmsd(0)[1]
cnvgd = 0
mode = 0
for line in o:
s = line.split()
if len(s) == 0: continue
if "Optimally Conditioned Variable Metric Optimization" in line: mode = 1
if "Limited Memory BFGS Quasi-Newton Optimization" in line: mode = 1
if mode == 1 and isint(s[0]): mode = 2
if mode == 2:
if isint(s[0]): E = float(s[1])
else: mode = 0
if "Normal Termination" in line:
cnvgd = 1
if not cnvgd:
for line in o:
logger.info(str(line) + '\n')
logger.info("The minimization did not converge in the geometry optimization - printout is above.\n")
return E, rmsd
def normal_modes(self, shot=0, optimize=True):
logger.error('Normal modes are not yet implemented in AMBER interface')
raise NotImplementedError
# Copied from tinkerio.py
if optimize:
self.optimize(shot, crit=1e-6)
o = self.calltinker("vibrate %s.xyz_2 a" % (self.name))
else:
warn_once("Asking for normal modes without geometry optimization?")
self.mol[shot].write('%s.xyz' % self.name, ftype="tinker")
o = self.calltinker("vibrate %s.xyz a" % (self.name))
# Read the TINKER output. The vibrational frequencies are ordered.
# The six modes with frequencies closest to zero are ignored
readev = False
calc_eigvals = []
calc_eigvecs = []
for line in o:
s = line.split()
if "Vibrational Normal Mode" in line:
freq = float(s[-2])
readev = False
calc_eigvals.append(freq)
calc_eigvecs.append([])
elif "Atom" in line and "Delta X" in line:
readev = True
elif readev and len(s) == 4 and all([isint(s[0]), isfloat(s[1]), isfloat(s[2]), isfloat(s[3])]):
calc_eigvecs[-1].append([float(i) for i in s[1:]])
calc_eigvals = np.array(calc_eigvals)
calc_eigvecs = np.array(calc_eigvecs)
# Sort by frequency absolute value and discard the six that are closest to zero
calc_eigvecs = calc_eigvecs[np.argsort(np.abs(calc_eigvals))][6:]
calc_eigvals = calc_eigvals[np.argsort(np.abs(calc_eigvals))][6:]
# Sort again by frequency
calc_eigvecs = calc_eigvecs[np.argsort(calc_eigvals)]
calc_eigvals = calc_eigvals[np.argsort(calc_eigvals)]
os.system("rm -rf *.xyz_* *.[0-9][0-9][0-9]")
return calc_eigvals, calc_eigvecs
def multipole_moments(self, shot=0, optimize=True, polarizability=False):
logger.error('Multipole moments are not yet implemented in AMBER interface')
raise NotImplementedError
""" Return the multipole moments of the 1st snapshot in Debye and Buckingham units. """
# This line actually runs TINKER
if optimize:
self.optimize(shot, crit=1e-6)
o = self.calltinker("analyze %s.xyz_2 M" % (self.name))
else:
self.mol[shot].write('%s.xyz' % self.name, ftype="tinker")
o = self.calltinker("analyze %s.xyz M" % (self.name))
# Read the TINKER output.
qn = -1
ln = 0
for line in o:
s = line.split()
if "Dipole X,Y,Z-Components" in line:
dipole_dict = OrderedDict(zip(['x','y','z'], [float(i) for i in s[-3:]]))
elif "Quadrupole Moment Tensor" in line:
qn = ln
quadrupole_dict = OrderedDict([('xx',float(s[-3]))])
elif qn > 0 and ln == qn + 1:
quadrupole_dict['xy'] = float(s[-3])
quadrupole_dict['yy'] = float(s[-2])
elif qn > 0 and ln == qn + 2:
quadrupole_dict['xz'] = float(s[-3])
quadrupole_dict['yz'] = float(s[-2])
quadrupole_dict['zz'] = float(s[-1])
ln += 1
calc_moments = OrderedDict([('dipole', dipole_dict), ('quadrupole', quadrupole_dict)])
if polarizability:
if optimize:
o = self.calltinker("polarize %s.xyz_2" % (self.name))
else:
o = self.calltinker("polarize %s.xyz" % (self.name))
# Read the TINKER output.
pn = -1
ln = 0
polarizability_dict = OrderedDict()
for line in o:
s = line.split()
if "Total Polarizability Tensor" in line:
pn = ln
elif pn > 0 and ln == pn + 2:
polarizability_dict['xx'] = float(s[-3])
polarizability_dict['yx'] = float(s[-2])
polarizability_dict['zx'] = float(s[-1])
elif pn > 0 and ln == pn + 3:
polarizability_dict['xy'] = float(s[-3])
polarizability_dict['yy'] = float(s[-2])
polarizability_dict['zy'] = float(s[-1])
elif pn > 0 and ln == pn + 4:
polarizability_dict['xz'] = float(s[-3])
polarizability_dict['yz'] = float(s[-2])
polarizability_dict['zz'] = float(s[-1])
ln += 1
calc_moments['polarizability'] = polarizability_dict
os.system("rm -rf *.xyz_* *.[0-9][0-9][0-9]")
return calc_moments
def energy_rmsd(self, shot=0, optimize=True):
""" Calculate energy of the selected structure (optionally minimize and return the minimized energy and RMSD). In kcal/mol. """
logger.error('Geometry optimization is not yet implemented in AMBER interface')
raise NotImplementedError
rmsd = 0.0
# This line actually runs TINKER
# xyzfnm = sysname+".xyz"
if optimize:
E_, rmsd = self.optimize(shot)
o = self.calltinker("analyze %s.xyz_2 E" % self.name)
#----
# Two equivalent ways to get the RMSD, here for reference.
#----
# M1 = Molecule("%s.xyz" % self.name, ftype="tinker")
# M2 = Molecule("%s.xyz_2" % self.name, ftype="tinker")
# M1 += M2
# rmsd = M1.ref_rmsd(0)[1]
#----
# oo = self.calltinker("superpose %s.xyz %s.xyz_2 1 y u n 0" % (self.name, self.name))
# for line in oo:
# if "Root Mean Square Distance" in line:
# rmsd = float(line.split()[-1])
#----
os.system("rm %s.xyz_2" % self.name)
else:
o = self.calltinker("analyze %s.xyz E" % self.name)
# Read the TINKER output.
E = None
for line in o:
if "Total Potential Energy" in line:
E = float(line.split()[-2].replace('D','e'))
if E == None:
logger.error("Total potential energy wasn't encountered when calling analyze!\n")
raise RuntimeError
if optimize and abs(E-E_) > 0.1:
warn_press_key("Energy from optimize and analyze aren't the same (%.3f vs. %.3f)" % (E, E_))
return E, rmsd
def interaction_energy(self, fraga, fragb):
""" Calculate the interaction energy for two fragments. """
logger.error('Interaction energy is not yet implemented in AMBER interface')
raise NotImplementedError
self.A = TINKER(name="A", mol=self.mol.atom_select(fraga), tinker_key="%s.key" % self.name, tinkerpath=self.tinkerpath)
self.B = TINKER(name="B", mol=self.mol.atom_select(fragb), tinker_key="%s.key" % self.name, tinkerpath=self.tinkerpath)
# Interaction energy needs to be in kcal/mol.
return (self.energy() - self.A.energy() - self.B.energy()) / 4.184
def molecular_dynamics(self, nsteps, timestep, temperature=None, pressure=None, nequil=0, nsave=1000, minimize=True, anisotropic=False, threads=1, verbose=False, **kwargs):
"""
Method for running a molecular dynamics simulation.
Required arguments:
nsteps = (int) Number of total time steps
timestep = (float) Time step in FEMTOSECONDS
temperature = (float) Temperature control (Kelvin)
pressure = (float) Pressure control (atmospheres)
nequil = (int) Number of additional time steps at the beginning for equilibration
nsave = (int) Step interval for saving and printing data
minimize = (bool) Perform an energy minimization prior to dynamics
threads = (int) Specify how many OpenMP threads to use
Returns simulation data:
Rhos = (array) Density in kilogram m^-3
Potentials = (array) Potential energies
Kinetics = (array) Kinetic energies
Volumes = (array) Box volumes
Dips = (3xN array) Dipole moments
EComps = (dict) Energy components
"""
logger.error('Molecular dynamics not yet implemented in AMBER interface')
raise NotImplementedError
md_defs = OrderedDict()
md_opts = OrderedDict()
# Print out averages only at the end.
md_opts["printout"] = nsave
md_opts["openmp-threads"] = threads
# Langevin dynamics for temperature control.
if temperature != None:
md_defs["integrator"] = "stochastic"
else:
md_defs["integrator"] = "beeman"
md_opts["thermostat"] = None
# Periodic boundary conditions.
if self.pbc:
md_opts["vdw-correction"] = ''
if temperature != None and pressure != None:
md_defs["integrator"] = "beeman"
md_defs["thermostat"] = "bussi"
md_defs["barostat"] = "montecarlo"
if anisotropic:
md_opts["aniso-pressure"] = ''
elif pressure != None:
warn_once("Pressure is ignored because temperature is turned off.")
else:
if pressure != None:
warn_once("Pressure is ignored because pbc is set to False.")
# Use stochastic dynamics for the gas phase molecule.
# If we use the regular integrators it may miss
# six degrees of freedom in calculating the kinetic energy.
md_opts["barostat"] = None
eq_opts = deepcopy(md_opts)
if self.pbc and temperature != None and pressure != None:
eq_opts["integrator"] = "beeman"
eq_opts["thermostat"] = "bussi"
eq_opts["barostat"] = "berendsen"
if minimize:
if verbose: logger.info("Minimizing the energy...")
self.optimize(method="bfgs", crit=1)
os.system("mv %s.xyz_2 %s.xyz" % (self.name, self.name))
if verbose: logger.info("Done\n")
# Run equilibration.
if nequil > 0:
write_key("%s-eq.key" % self.name, eq_opts, "%s.key" % self.name, md_defs)
if verbose: printcool("Running equilibration dynamics", color=0)
if self.pbc and pressure != None:
self.calltinker("dynamic %s -k %s-eq %i %f %f 4 %f %f" % (self.name, self.name, nequil, timestep, float(nsave*timestep)/1000,
temperature, pressure), print_to_screen=verbose)
else:
self.calltinker("dynamic %s -k %s-eq %i %f %f 2 %f" % (self.name, self.name, nequil, timestep, float(nsave*timestep)/1000,
temperature), print_to_screen=verbose)
os.system("rm -f %s.arc" % (self.name))
# Run production.
if verbose: printcool("Running production dynamics", color=0)
write_key("%s-md.key" % self.name, md_opts, "%s.key" % self.name, md_defs)
if self.pbc and pressure != None:
odyn = self.calltinker("dynamic %s -k %s-md %i %f %f 4 %f %f" % (self.name, self.name, nsteps, timestep, float(nsave*timestep/1000),
temperature, pressure), print_to_screen=verbose)
else:
odyn = self.calltinker("dynamic %s -k %s-md %i %f %f 2 %f" % (self.name, self.name, nsteps, timestep, float(nsave*timestep/1000),
temperature), print_to_screen=verbose)
# Gather information.
os.system("mv %s.arc %s-md.arc" % (self.name, self.name))
self.md_trajectory = "%s-md.arc" % self.name
edyn = []
kdyn = []
temps = []
for line in odyn:
s = line.split()
if 'Current Potential' in line:
edyn.append(float(s[2]))
if 'Current Kinetic' in line:
kdyn.append(float(s[2]))
if len(s) > 0 and s[0] == 'Temperature' and s[2] == 'Kelvin':
temps.append(float(s[1]))
# Potential and kinetic energies converted to kJ/mol.
edyn = np.array(edyn) * 4.184
kdyn = np.array(kdyn) * 4.184
temps = np.array(temps)
if verbose: logger.info("Post-processing to get the dipole moments\n")
oanl = self.calltinker("analyze %s-md.arc" % self.name, stdin="G,E,M", print_to_screen=False)
# Read potential energy and dipole from file.
eanl = []
dip = []
mass = 0.0
ecomp = OrderedDict()
havekeys = set()
first_shot = True
for ln, line in enumerate(oanl):
strip = line.strip()
s = line.split()
if 'Total System Mass' in line:
mass = float(s[-1])
if 'Total Potential Energy : ' in line:
eanl.append(float(s[4]))
if 'Dipole X,Y,Z-Components :' in line:
dip.append([float(s[i]) for i in range(-3,0)])
if first_shot:
for key in eckeys:
if strip.startswith(key):
if key in ecomp:
ecomp[key].append(float(s[-2])*4.184)
else:
ecomp[key] = [float(s[-2])*4.184]
if key in havekeys:
first_shot = False
havekeys.add(key)
else:
for key in havekeys:
if strip.startswith(key):
if key in ecomp:
ecomp[key].append(float(s[-2])*4.184)
else:
ecomp[key] = [float(s[-2])*4.184]
for key in ecomp:
ecomp[key] = np.array(ecomp[key])
ecomp["Potential Energy"] = edyn
ecomp["Kinetic Energy"] = kdyn
ecomp["Temperature"] = temps
ecomp["Total Energy"] = edyn+kdyn
# Energies in kilojoules per mole
eanl = np.array(eanl) * 4.184
# Dipole moments in debye
dip = np.array(dip)
# Volume of simulation boxes in cubic nanometers
# Conversion factor derived from the following:
# In [22]: 1.0 * gram / mole / (1.0 * nanometer)**3 / AVOGADRO_CONSTANT_NA / (kilogram/meter**3)
# Out[22]: 1.6605387831627252
conv = 1.6605387831627252
if self.pbc:
vol = np.array([BuildLatticeFromLengthsAngles(*[float(j) for j in line.split()]).V \
for line in open("%s-md.arc" % self.name).readlines() \
if (len(line.split()) == 6 and isfloat(line.split()[1]) \
and all([isfloat(i) for i in line.split()[:6]]))]) / 1000
rho = conv * mass / vol
else:
vol = None
rho = None
prop_return = OrderedDict()
prop_return.update({'Rhos': rho, 'Potentials': edyn, 'Kinetics': kdyn, 'Volumes': vol, 'Dips': dip, 'Ecomps': ecomp})
return prop_return
class TINKER(Engine):
""" Engine for carrying out general purpose TINKER calculations. """
def __init__(self, name="tinker", **kwargs):
## Keyword args that aren't in this list are filtered out.
self.valkwd = ['tinker_key', 'tinkerpath', 'tinker_prm']
self.warn_vn = False
super(TINKER,self).__init__(name=name, **kwargs)
def setopts(self, **kwargs):
""" Called by __init__ ; Set TINKER-specific options. """
## The directory containing TINKER executables (e.g. dynamic)
if 'tinkerpath' in kwargs:
self.tinkerpath = kwargs['tinkerpath']
if not os.path.exists(os.path.join(self.tinkerpath,"dynamic")):
warn_press_key("The 'dynamic' executable indicated by %s doesn't exist! (Check tinkerpath)" \
% os.path.join(self.tinkerpath,"dynamic"))
else:
warn_once("The 'tinkerpath' option was not specified; using default.")
if which('mdrun') == '':
warn_press_key("Please add TINKER executables to the PATH or specify tinkerpath.")
self.tinkerpath = which('dynamic')
def readsrc(self, **kwargs):
""" Called by __init__ ; read files from the source directory. """
self.key = onefile(kwargs.get('tinker_key'), 'key')
self.prm = onefile(kwargs.get('tinker_prm'), 'prm')
if 'mol' in kwargs:
self.mol = kwargs['mol']
else:
crdfile = onefile(kwargs.get('coords'), 'arc', err=True)
self.mol = Molecule(crdfile)
def calltinker(self, command, stdin=None, print_to_screen=False, print_command=False, **kwargs):
""" Call TINKER; prepend the tinkerpath to calling the TINKER program. """
csplit = command.split()
# Sometimes the engine changes dirs and the key goes missing, so we link it.
if "%s.key" % self.name in csplit and not os.path.exists("%s.key" % self.name):
LinkFile(self.abskey, "%s.key" % self.name)
prog = os.path.join(self.tinkerpath, csplit[0])
csplit[0] = prog
o = _exec(' '.join(csplit), stdin=stdin, print_to_screen=print_to_screen, print_command=print_command, rbytes=1024, **kwargs)
# Determine the TINKER version number.
for line in o[:10]:
if "Version" in line:
vw = line.split()[2]
if len(vw.split('.')) <= 2:
vn = float(vw)
else:
vn = float(vw.split('.')[:2])
vn_need = 6.3
try:
if vn < vn_need:
if self.warn_vn:
warn_press_key("ForceBalance requires TINKER %.1f - unexpected behavior with older versions!" % vn_need)
self.warn_vn = True
except:
logger.error("Unable to determine TINKER version number!\n")
raise RuntimeError
for line in o[-10:]:
# Catch exceptions since TINKER does not have exit status.
if "TINKER is Unable to Continue" in line:
for l in o:
logger.error("%s\n" % l)
time.sleep(1)
logger.error("TINKER may have crashed! (See above output)\nThe command was: %s\nThe directory was: %s\n" % (' '.join(csplit), os.getcwd()))
raise RuntimeError
break
for line in o:
if 'D+' in line:
logger.info(line+'\n')
warn_press_key("TINKER returned a very large floating point number! (See above line; will give error on parse)")
return o
def prepare(self, pbc=False, **kwargs):
""" Called by __init__ ; prepare the temp directory and figure out the topology. """
# Call TINKER but do nothing to figure out the version number.
o = self.calltinker("dynamic", persist=1, print_error=False)
self.rigid = False
## Attempt to set some TINKER options.
tk_chk = []
tk_opts = OrderedDict([("digits", "10"), ("archive", "")])
tk_defs = OrderedDict()
prmtmp = False
if hasattr(self,'FF'):
if not os.path.exists(self.FF.tinkerprm):
# If the parameter files don't already exist, create them for the purpose of
# preparing the engine, but then delete them afterward.
prmtmp = True
self.FF.make(np.zeros(self.FF.np))
if self.FF.rigid_water:
tk_opts["rattle"] = "water"
self.rigid = True
if self.FF.amoeba_pol == 'mutual':
tk_opts['polarization'] = 'mutual'
if self.FF.amoeba_eps != None:
tk_opts['polar-eps'] = str(self.FF.amoeba_eps)
else:
tk_defs['polar-eps'] = '1e-6'
elif self.FF.amoeba_pol == 'direct':
tk_opts['polarization'] = 'direct'
else:
warn_press_key("Using TINKER without explicitly specifying AMOEBA settings. Are you sure?")
self.prm = self.FF.tinkerprm
prmfnm = self.FF.tinkerprm
elif self.prm:
prmfnm = self.prm
else:
prmfnm = None
# Periodic boundary conditions may come from the TINKER .key file.
keypbc = False
minbox = 1e10
if self.key:
for line in open(os.path.join(self.srcdir, self.key)).readlines():
s = line.split()
if len(s) > 0 and s[0].lower() == 'a-axis':
keypbc = True
minbox = float(s[1])
if len(s) > 0 and s[0].lower() == 'b-axis' and float(s[1]) < minbox:
minbox = float(s[1])
if len(s) > 0 and s[0].lower() == 'c-axis' and float(s[1]) < minbox:
minbox = float(s[1])
if keypbc and (not pbc):
warn_once("Deleting PBC options from the .key file.")
tk_opts['a-axis'] = None
tk_opts['b-axis'] = None
tk_opts['c-axis'] = None
tk_opts['alpha'] = None
tk_opts['beta'] = None
tk_opts['gamma'] = None
if pbc:
if (not keypbc) and 'boxes' not in self.mol.Data:
logger.error("Periodic boundary conditions require either (1) a-axis to be in the .key file or (b) boxes to be in the coordinate file.\n")
raise RuntimeError
self.pbc = pbc
if pbc:
tk_opts['ewald'] = ''
if minbox <= 10:
warn_press_key("Periodic box is set to less than 10 Angstroms across")
# TINKER likes to use up to 7.0 Angstrom for PME cutoffs
rpme = 0.05*(float(int(minbox - 1))) if minbox <= 15 else 7.0
tk_defs['ewald-cutoff'] = "%f" % rpme
# TINKER likes to use up to 9.0 Angstrom for vdW cutoffs
rvdw = 0.05*(float(int(minbox - 1))) if minbox <= 19 else 9.0
tk_defs['vdw-cutoff'] = "%f" % rvdw
if (minbox*0.5 - rpme) > 2.5 and (minbox*0.5 - rvdw) > 2.5:
tk_defs['neighbor-list'] = ''
elif (minbox*0.5 - rpme) > 2.5:
tk_defs['mpole-list'] = ''
else:
tk_opts['ewald'] = None
tk_opts['ewald-cutoff'] = None
tk_opts['vdw-cutoff'] = None
# This seems to have no effect on the kinetic energy.
# tk_opts['remove-inertia'] = '0'
write_key("%s.key" % self.name, tk_opts, os.path.join(self.srcdir, self.key) if self.key else None, tk_defs, verbose=False, prmfnm=prmfnm)
self.abskey = os.path.abspath("%s.key")
self.mol[0].write(os.path.join("%s.xyz" % self.name), ftype="tinker")
## If the coordinates do not come with TINKER suffixes then throw an error.
self.mol.require('tinkersuf')
## Call analyze to read information needed to build the atom lists.
o = self.calltinker("analyze %s.xyz P,C" % (self.name), stdin="ALL")
## Parse the output of analyze.
mode = 0
self.AtomMask = []
self.AtomLists = defaultdict(list)
ptype_dict = {'atom': 'A', 'vsite': 'D'}
G = nx.Graph()
for line in o:
s = line.split()
if len(s) == 0: continue
if "Atom Type Definition Parameters" in line:
mode = 1
if mode == 1:
if isint(s[0]): mode = 2
if mode == 2:
if isint(s[0]):
mass = float(s[5])
self.AtomLists['Mass'].append(mass)
if mass < 1.0:
# Particles with mass less than one count as virtual sites.
self.AtomLists['ParticleType'].append('D')
else:
self.AtomLists['ParticleType'].append('A')
self.AtomMask.append(mass >= 1.0)
else:
mode = 0
if "List of 1-2 Connected Atomic Interactions" in line:
mode = 3
if mode == 3:
if isint(s[0]): mode = 4
if mode == 4:
if isint(s[0]):
a = int(s[0])
b = int(s[1])
G.add_node(a)
G.add_node(b)
G.add_edge(a, b)
else: mode = 0
# Use networkx to figure out a list of molecule numbers.
if len(G.nodes()) > 0:
# The following code only works in TINKER 6.2
gs = nx.connected_component_subgraphs(G)
tmols = [gs[i] for i in np.argsort(np.array([min(g.nodes()) for g in gs]))]
mnodes = [m.nodes() for m in tmols]
self.AtomLists['MoleculeNumber'] = [[i+1 in m for m in mnodes].index(1) for i in range(self.mol.na)]
else:
grouped = [i.L() for i in self.mol.molecules]
self.AtomLists['MoleculeNumber'] = [[i in g for g in grouped].index(1) for i in range(self.mol.na)]
if prmtmp:
for f in self.FF.fnms:
os.unlink(f)
def optimize(self, shot=0, method="newton", crit=1e-4):
""" Optimize the geometry and align the optimized geometry to the starting geometry. """
if os.path.exists('%s.xyz_2' % self.name):
os.unlink('%s.xyz_2' % self.name)
self.mol[shot].write('%s.xyz' % self.name, ftype="tinker")
if method == "newton":
if self.rigid: optprog = "optrigid"
else: optprog = "optimize"
elif method == "bfgs":
if self.rigid: optprog = "minrigid"
else: optprog = "minimize"
o = self.calltinker("%s %s.xyz %f" % (optprog, self.name, crit))
# Silently align the optimized geometry.
M12 = Molecule("%s.xyz" % self.name, ftype="tinker") + Molecule("%s.xyz_2" % self.name, ftype="tinker")
if not self.pbc:
M12.align(center=False)
M12[1].write("%s.xyz_2" % self.name, ftype="tinker")
rmsd = M12.ref_rmsd(0)[1]
cnvgd = 0
mode = 0
for line in o:
s = line.split()
if len(s) == 0: continue
if "Optimally Conditioned Variable Metric Optimization" in line: mode = 1
if "Limited Memory BFGS Quasi-Newton Optimization" in line: mode = 1
if mode == 1 and isint(s[0]): mode = 2
if mode == 2:
if isint(s[0]): E = float(s[1])
else: mode = 0
if "Normal Termination" in line:
cnvgd = 1
if not cnvgd:
for line in o:
logger.info(str(line) + '\n')
logger.info("The minimization did not converge in the geometry optimization - printout is above.\n")
return E, rmsd
def evaluate_(self, xyzin, force=False, dipole=False):
"""
Utility function for computing energy, and (optionally) forces and dipoles using TINKER.
Inputs:
xyzin: TINKER .xyz file name.
force: Switch for calculating the force.
dipole: Switch for calculating the dipole.
Outputs:
Result: Dictionary containing energies, forces and/or dipoles.
"""
Result = OrderedDict()
# If we want the dipoles (or just energies), analyze is the way to go.
if dipole or (not force):
oanl = self.calltinker("analyze %s -k %s" % (xyzin, self.name), stdin="G,E,M", print_to_screen=False)
# Read potential energy and dipole from file.
eanl = []
dip = []
for line in oanl:
s = line.split()
if 'Total Potential Energy : ' in line:
eanl.append(float(s[4]) * 4.184)
if dipole:
if 'Dipole X,Y,Z-Components :' in line:
dip.append([float(s[i]) for i in range(-3,0)])
Result["Energy"] = np.array(eanl)
Result["Dipole"] = np.array(dip)
# If we want forces, then we need to call testgrad.
if force:
E = []
F = []
Fi = []
o = self.calltinker("testgrad %s -k %s y n n" % (xyzin, self.name))
i = 0
ReadFrc = 0
for line in o:
s = line.split()
if "Total Potential Energy" in line:
E.append(float(s[4]) * 4.184)
if "Cartesian Gradient Breakdown over Individual Atoms" in line:
ReadFrc = 1
if ReadFrc and len(s) == 6 and all([s[0] == 'Anlyt',isint(s[1]),isfloat(s[2]),isfloat(s[3]),isfloat(s[4]),isfloat(s[5])]):
ReadFrc = 2
if self.AtomMask[i]:
Fi += [-1 * float(j) * 4.184 * 10 for j in s[2:5]]
i += 1
if ReadFrc == 2 and len(s) < 6:
ReadFrc = 0
F.append(Fi)
Fi = []
i = 0
Result["Energy"] = np.array(E)
Result["Force"] = np.array(F)
return Result
def energy_force_one(self, shot):
""" Computes the energy and force using TINKER for one snapshot. """
self.mol[shot].write("%s.xyz" % self.name, ftype="tinker")
Result = self.evaluate_("%s.xyz" % self.name, force=True)
return np.hstack((Result["Energy"].reshape(-1,1), Result["Force"]))
def energy(self):
""" Computes the energy using TINKER over a trajectory. """
if hasattr(self, 'md_trajectory') :
x = self.md_trajectory
else:
x = "%s.xyz" % self.name
self.mol.write(x, ftype="tinker")
return self.evaluate_(x)["Energy"]
def energy_force(self):
""" Computes the energy and force using TINKER over a trajectory. """
if hasattr(self, 'md_trajectory') :
x = self.md_trajectory
else:
x = "%s.xyz" % self.name
self.mol.write(x, ftype="tinker")
Result = self.evaluate_(x, force=True)
return np.hstack((Result["Energy"].reshape(-1,1), Result["Force"]))
def energy_dipole(self):
""" Computes the energy and dipole using TINKER over a trajectory. """
if hasattr(self, 'md_trajectory') :
x = self.md_trajectory
else:
x = "%s.xyz" % self.name
self.mol.write(x, ftype="tinker")
Result = self.evaluate_(x, dipole=True)
return np.hstack((Result["Energy"].reshape(-1,1), Result["Dipole"]))
def normal_modes(self, shot=0, optimize=True):
# This line actually runs TINKER
if optimize:
self.optimize(shot, crit=1e-6)
o = self.calltinker("vibrate %s.xyz_2 a" % (self.name))
else:
warn_once("Asking for normal modes without geometry optimization?")
self.mol[shot].write('%s.xyz' % self.name, ftype="tinker")
o = self.calltinker("vibrate %s.xyz a" % (self.name))
# Read the TINKER output. The vibrational frequencies are ordered.
# The six modes with frequencies closest to zero are ignored
readev = False
calc_eigvals = []
calc_eigvecs = []
for line in o:
s = line.split()
if "Vibrational Normal Mode" in line:
freq = float(s[-2])
readev = False
calc_eigvals.append(freq)
calc_eigvecs.append([])
elif "Atom" in line and "Delta X" in line:
readev = True
elif readev and len(s) == 4 and all([isint(s[0]), isfloat(s[1]), isfloat(s[2]), isfloat(s[3])]):
calc_eigvecs[-1].append([float(i) for i in s[1:]])
calc_eigvals = np.array(calc_eigvals)
calc_eigvecs = np.array(calc_eigvecs)
# Sort by frequency absolute value and discard the six that are closest to zero
calc_eigvecs = calc_eigvecs[np.argsort(np.abs(calc_eigvals))][6:]
calc_eigvals = calc_eigvals[np.argsort(np.abs(calc_eigvals))][6:]
# Sort again by frequency
calc_eigvecs = calc_eigvecs[np.argsort(calc_eigvals)]
calc_eigvals = calc_eigvals[np.argsort(calc_eigvals)]
os.system("rm -rf *.xyz_* *.[0-9][0-9][0-9]")
return calc_eigvals, calc_eigvecs
def multipole_moments(self, shot=0, optimize=True, polarizability=False):
""" Return the multipole moments of the 1st snapshot in Debye and Buckingham units. """
# This line actually runs TINKER
if optimize:
self.optimize(shot, crit=1e-6)
o = self.calltinker("analyze %s.xyz_2 M" % (self.name))
else:
self.mol[shot].write('%s.xyz' % self.name, ftype="tinker")
o = self.calltinker("analyze %s.xyz M" % (self.name))
# Read the TINKER output.
qn = -1
ln = 0
for line in o:
s = line.split()
if "Dipole X,Y,Z-Components" in line:
dipole_dict = OrderedDict(zip(['x','y','z'], [float(i) for i in s[-3:]]))
elif "Quadrupole Moment Tensor" in line:
qn = ln
quadrupole_dict = OrderedDict([('xx',float(s[-3]))])
elif qn > 0 and ln == qn + 1:
quadrupole_dict['xy'] = float(s[-3])
quadrupole_dict['yy'] = float(s[-2])
elif qn > 0 and ln == qn + 2:
quadrupole_dict['xz'] = float(s[-3])
quadrupole_dict['yz'] = float(s[-2])
quadrupole_dict['zz'] = float(s[-1])
ln += 1
calc_moments = OrderedDict([('dipole', dipole_dict), ('quadrupole', quadrupole_dict)])
if polarizability:
if optimize:
o = self.calltinker("polarize %s.xyz_2" % (self.name))
else:
o = self.calltinker("polarize %s.xyz" % (self.name))
# Read the TINKER output.
pn = -1
ln = 0
polarizability_dict = OrderedDict()
for line in o:
s = line.split()
if "Molecular Polarizability Tensor" in line:
pn = ln
elif pn > 0 and ln == pn + 2:
polarizability_dict['xx'] = float(s[-3])
polarizability_dict['yx'] = float(s[-2])
polarizability_dict['zx'] = float(s[-1])
elif pn > 0 and ln == pn + 3:
polarizability_dict['xy'] = float(s[-3])
polarizability_dict['yy'] = float(s[-2])
polarizability_dict['zy'] = float(s[-1])
elif pn > 0 and ln == pn + 4:
polarizability_dict['xz'] = float(s[-3])
polarizability_dict['yz'] = float(s[-2])
polarizability_dict['zz'] = float(s[-1])
ln += 1
calc_moments['polarizability'] = polarizability_dict
os.system("rm -rf *.xyz_* *.[0-9][0-9][0-9]")
print polarizability
print calc_moments
return calc_moments
def energy_rmsd(self, shot=0, optimize=True):
""" Calculate energy of the selected structure (optionally minimize and return the minimized energy and RMSD). In kcal/mol. """
rmsd = 0.0
# This line actually runs TINKER
# xyzfnm = sysname+".xyz"
if optimize:
E_, rmsd = self.optimize(shot)
o = self.calltinker("analyze %s.xyz_2 E" % self.name)
#----
# Two equivalent ways to get the RMSD, here for reference.
#----
# M1 = Molecule("%s.xyz" % self.name, ftype="tinker")
# M2 = Molecule("%s.xyz_2" % self.name, ftype="tinker")
# M1 += M2
# rmsd = M1.ref_rmsd(0)[1]
#----
# oo = self.calltinker("superpose %s.xyz %s.xyz_2 1 y u n 0" % (self.name, self.name))
# for line in oo:
# if "Root Mean Square Distance" in line:
# rmsd = float(line.split()[-1])
#----
os.system("rm %s.xyz_2" % self.name)
else:
o = self.calltinker("analyze %s.xyz E" % self.name)
# Read the TINKER output.
E = None
for line in o:
if "Total Potential Energy" in line:
E = float(line.split()[-2].replace('D','e'))
if E == None:
logger.error("Total potential energy wasn't encountered when calling analyze!\n")
raise RuntimeError
if optimize and abs(E-E_) > 0.1:
warn_press_key("Energy from optimize and analyze aren't the same (%.3f vs. %.3f)" % (E, E_))
return E, rmsd
def interaction_energy(self, fraga, fragb):
""" Calculate the interaction energy for two fragments. """
self.A = TINKER(name="A", mol=self.mol.atom_select(fraga), tinker_key="%s.key" % self.name, tinkerpath=self.tinkerpath)
self.B = TINKER(name="B", mol=self.mol.atom_select(fragb), tinker_key="%s.key" % self.name, tinkerpath=self.tinkerpath)
# Interaction energy needs to be in kcal/mol.
return (self.energy() - self.A.energy() - self.B.energy()) / 4.184
def molecular_dynamics(self, nsteps, timestep, temperature=None, pressure=None, nequil=0, nsave=1000, minimize=True, anisotropic=False, threads=1, verbose=False, **kwargs):
"""
Method for running a molecular dynamics simulation.
Required arguments:
nsteps = (int) Number of total time steps
timestep = (float) Time step in FEMTOSECONDS
temperature = (float) Temperature control (Kelvin)
pressure = (float) Pressure control (atmospheres)
nequil = (int) Number of additional time steps at the beginning for equilibration
nsave = (int) Step interval for saving and printing data
minimize = (bool) Perform an energy minimization prior to dynamics
threads = (int) Specify how many OpenMP threads to use
Returns simulation data:
Rhos = (array) Density in kilogram m^-3
Potentials = (array) Potential energies
Kinetics = (array) Kinetic energies
Volumes = (array) Box volumes
Dips = (3xN array) Dipole moments
EComps = (dict) Energy components
"""
md_defs = OrderedDict()
md_opts = OrderedDict()
# Print out averages only at the end.
md_opts["printout"] = nsave
md_opts["openmp-threads"] = threads
# Langevin dynamics for temperature control.
if temperature != None:
md_defs["integrator"] = "stochastic"
else:
md_defs["integrator"] = "beeman"
md_opts["thermostat"] = None
# Periodic boundary conditions.
if self.pbc:
md_opts["vdw-correction"] = ''
if temperature != None and pressure != None:
md_defs["integrator"] = "beeman"
md_defs["thermostat"] = "bussi"
md_defs["barostat"] = "montecarlo"
if anisotropic:
md_opts["aniso-pressure"] = ''
elif pressure != None:
warn_once("Pressure is ignored because temperature is turned off.")
else:
if pressure != None:
warn_once("Pressure is ignored because pbc is set to False.")
# Use stochastic dynamics for the gas phase molecule.
# If we use the regular integrators it may miss
# six degrees of freedom in calculating the kinetic energy.
md_opts["barostat"] = None
eq_opts = deepcopy(md_opts)
if self.pbc and temperature != None and pressure != None:
eq_opts["integrator"] = "beeman"
eq_opts["thermostat"] = "bussi"
eq_opts["barostat"] = "berendsen"
if minimize:
if verbose: logger.info("Minimizing the energy...")
self.optimize(method="bfgs", crit=1)
os.system("mv %s.xyz_2 %s.xyz" % (self.name, self.name))
if verbose: logger.info("Done\n")
# Run equilibration.
if nequil > 0:
write_key("%s-eq.key" % self.name, eq_opts, "%s.key" % self.name, md_defs)
if verbose: printcool("Running equilibration dynamics", color=0)
if self.pbc and pressure != None:
self.calltinker("dynamic %s -k %s-eq %i %f %f 4 %f %f" % (self.name, self.name, nequil, timestep, float(nsave*timestep)/1000,
temperature, pressure), print_to_screen=verbose)
else:
self.calltinker("dynamic %s -k %s-eq %i %f %f 2 %f" % (self.name, self.name, nequil, timestep, float(nsave*timestep)/1000,
temperature), print_to_screen=verbose)
os.system("rm -f %s.arc" % (self.name))
# Run production.
if verbose: printcool("Running production dynamics", color=0)
write_key("%s-md.key" % self.name, md_opts, "%s.key" % self.name, md_defs)
if self.pbc and pressure != None:
odyn = self.calltinker("dynamic %s -k %s-md %i %f %f 4 %f %f" % (self.name, self.name, nsteps, timestep, float(nsave*timestep/1000),
temperature, pressure), print_to_screen=verbose)
else:
odyn = self.calltinker("dynamic %s -k %s-md %i %f %f 2 %f" % (self.name, self.name, nsteps, timestep, float(nsave*timestep/1000),
temperature), print_to_screen=verbose)
# Gather information.
os.system("mv %s.arc %s-md.arc" % (self.name, self.name))
self.md_trajectory = "%s-md.arc" % self.name
edyn = []
kdyn = []
temps = []
for line in odyn:
s = line.split()
if 'Current Potential' in line:
edyn.append(float(s[2]))
if 'Current Kinetic' in line:
kdyn.append(float(s[2]))
if len(s) > 0 and s[0] == 'Temperature' and s[2] == 'Kelvin':
temps.append(float(s[1]))
# Potential and kinetic energies converted to kJ/mol.
edyn = np.array(edyn) * 4.184
kdyn = np.array(kdyn) * 4.184
temps = np.array(temps)
if verbose: logger.info("Post-processing to get the dipole moments\n")
oanl = self.calltinker("analyze %s-md.arc" % self.name, stdin="G,E,M", print_to_screen=False)
# Read potential energy and dipole from file.
eanl = []
dip = []
mass = 0.0
ecomp = OrderedDict()
havekeys = set()
first_shot = True
for ln, line in enumerate(oanl):
strip = line.strip()
s = line.split()
if 'Total System Mass' in line:
mass = float(s[-1])
if 'Total Potential Energy : ' in line:
eanl.append(float(s[4]))
if 'Dipole X,Y,Z-Components :' in line:
dip.append([float(s[i]) for i in range(-3,0)])
if first_shot:
for key in eckeys:
if strip.startswith(key):
if key in ecomp:
ecomp[key].append(float(s[-2])*4.184)
else:
ecomp[key] = [float(s[-2])*4.184]
if key in havekeys:
first_shot = False
havekeys.add(key)
else:
for key in havekeys:
if strip.startswith(key):
if key in ecomp:
ecomp[key].append(float(s[-2])*4.184)
else:
ecomp[key] = [float(s[-2])*4.184]
for key in ecomp:
ecomp[key] = np.array(ecomp[key])
ecomp["Potential Energy"] = edyn
ecomp["Kinetic Energy"] = kdyn
ecomp["Temperature"] = temps
ecomp["Total Energy"] = edyn+kdyn
# Energies in kilojoules per mole
eanl = np.array(eanl) * 4.184
# Dipole moments in debye
dip = np.array(dip)
# Volume of simulation boxes in cubic nanometers
# Conversion factor derived from the following:
# In [22]: 1.0 * gram / mole / (1.0 * nanometer)**3 / AVOGADRO_CONSTANT_NA / (kilogram/meter**3)
# Out[22]: 1.6605387831627252
conv = 1.6605387831627252
if self.pbc:
vol = np.array([BuildLatticeFromLengthsAngles(*[float(j) for j in line.split()]).V \
for line in open("%s-md.arc" % self.name).readlines() \
if (len(line.split()) == 6 and isfloat(line.split()[1]) \
and all([isfloat(i) for i in line.split()[:6]]))]) / 1000
rho = conv * mass / vol
else:
vol = None
rho = None
prop_return = OrderedDict()
prop_return.update({'Rhos': rho, 'Potentials': edyn, 'Kinetics': kdyn, 'Volumes': vol, 'Dips': dip, 'Ecomps': ecomp})
return prop_return
class AMBER(Engine):
""" Engine for carrying out general purpose AMBER calculations. """
def __init__(self, name="amber", **kwargs):
## Keyword args that aren't in this list are filtered out.
self.valkwd = ['amberhome', 'pdb', 'mol2', 'frcmod', 'leapcmd']
super(AMBER, self).__init__(name=name, **kwargs)
def setopts(self, **kwargs):
""" Called by __init__ ; Set AMBER-specific options. """
## The directory containing TINKER executables (e.g. dynamic)
if 'amberhome' in kwargs:
self.amberhome = kwargs['amberhome']
if not os.path.exists(os.path.join(self.amberhome, "sander")):
warn_press_key("The 'sander' executable indicated by %s doesn't exist! (Check amberhome)" \
% os.path.join(self.amberhome,"sander"))
else:
warn_once(
"The 'amberhome' option was not specified; using default.")
if which('sander') == '':
warn_press_key(
"Please add AMBER executables to the PATH or specify amberhome."
)
self.amberhome = os.path.split(which('sander'))[0]
with wopen('.quit.leap') as f:
print >> f, 'quit'
# AMBER search path
self.spath = []
for line in self.callamber('tleap -f .quit.leap'):
if 'Adding' in line and 'to search path' in line:
self.spath.append(line.split('Adding')[1].split()[0])
os.remove('.quit.leap')
def readsrc(self, **kwargs):
""" Called by __init__ ; read files from the source directory. """
self.leapcmd = onefile(kwargs.get('leapcmd'), 'leap', err=True)
self.absleap = os.path.abspath(self.leapcmd)
# Name of the molecule, currently just call it a default name.
self.mname = 'molecule'
if 'mol' in kwargs:
self.mol = kwargs['mol']
elif 'coords' in kwargs:
crdfile = onefile(kwargs.get('coords'), None, err=True)
self.mol = Molecule(crdfile, build_topology=False)
# AMBER has certain PDB requirements, so we will absolutely require one.
needpdb = True
# if hasattr(self, 'mol') and all([i in self.mol.Data.keys() for i in ["chain", "atomname", "resid", "resname", "elem"]]):
# needpdb = False
# Determine the PDB file name.
# If 'pdb' is provided to Engine initialization, it will be used to
# copy over topology information (chain, atomname etc.). If mol/coords
# is not provided, then it will also provide the coordinates.
pdbfnm = onefile(kwargs.get('pdb'),
'pdb' if needpdb else None,
err=needpdb)
if pdbfnm != None:
mpdb = Molecule(pdbfnm, build_topology=False)
if hasattr(self, 'mol'):
for i in ["chain", "atomname", "resid", "resname", "elem"]:
self.mol.Data[i] = mpdb.Data[i]
else:
self.mol = copy.deepcopy(mpdb)
self.abspdb = os.path.abspath(pdbfnm)
# Write the PDB that AMBER is going to read in.
# This may or may not be identical to the one used to initialize the engine.
# self.mol.write('%s.pdb' % self.name)
# self.abspdb = os.path.abspath('%s.pdb' % self.name)
def callamber(self,
command,
stdin=None,
print_to_screen=False,
print_command=False,
**kwargs):
""" Call TINKER; prepend the amberhome to calling the TINKER program. """
csplit = command.split()
# Sometimes the engine changes dirs and the inpcrd/prmtop go missing, so we link it.
# Prepend the AMBER path to the program call.
prog = os.path.join(self.amberhome, "bin", csplit[0])
csplit[0] = prog
# No need to catch exceptions since failed AMBER calculations will return nonzero exit status.
o = _exec(' '.join(csplit),
stdin=stdin,
print_to_screen=print_to_screen,
print_command=print_command,
rbytes=1024,
**kwargs)
return o
def leap(self, name=None, delcheck=False):
if not os.path.exists(self.leapcmd):
LinkFile(self.absleap, self.leapcmd)
pdb = os.path.basename(self.abspdb)
if not os.path.exists(pdb):
LinkFile(self.abspdb, pdb)
if name == None: name = self.name
write_leap(self.leapcmd,
mol2=self.mol2,
frcmod=self.frcmod,
pdb=pdb,
prefix=name,
spath=self.spath,
delcheck=delcheck)
self.callamber("tleap -f %s_" % self.leapcmd)
def prepare(self, pbc=False, **kwargs):
""" Called by __init__ ; prepare the temp directory and figure out the topology. """
if hasattr(self, 'FF'):
if not (os.path.exists(self.FF.amber_frcmod)
and os.path.exists(self.FF.amber_mol2)):
# If the parameter files don't already exist, create them for the purpose of
# preparing the engine, but then delete them afterward.
prmtmp = True
self.FF.make(np.zeros(self.FF.np))
# Currently force field object only allows one mol2 and frcmod file although this can be lifted.
self.mol2 = [self.FF.amber_mol2]
self.frcmod = [self.FF.amber_frcmod]
if 'mol2' in kwargs:
logger.error(
"FF object is provided, which overrides mol2 keyword argument"
)
raise RuntimeError
if 'frcmod' in kwargs:
logger.error(
"FF object is provided, which overrides frcmod keyword argument"
)
raise RuntimeError
else:
prmtmp = False
self.mol2 = listfiles(kwargs.get('mol2'), 'mol2', err=True)
self.frcmod = listfiles(kwargs.get('frcmod'), 'frcmod', err=True)
# Figure out the topology information.
self.leap()
o = self.callamber("rdparm %s.prmtop" % self.name,
stdin="printAtoms\nprintBonds\nexit\n",
persist=True,
print_error=False)
# Once we do this, we don't need the prmtop and inpcrd anymore
os.unlink("%s.inpcrd" % self.name)
os.unlink("%s.prmtop" % self.name)
os.unlink("leap.log")
mode = 'None'
self.AtomLists = defaultdict(list)
G = nx.Graph()
for line in o:
s = line.split()
if 'Atom' in line:
mode = 'Atom'
elif 'Bond' in line:
mode = 'Bond'
elif 'RDPARM MENU' in line:
continue
elif 'EXITING' in line:
break
elif len(s) == 0:
continue
elif mode == 'Atom':
# Based on parsing lines like these:
"""
327: HA -0.01462 1.0 ( 23:HIP ) H1 E
328: CB -0.33212 12.0 ( 23:HIP ) CT 3
329: HB2 0.10773 1.0 ( 23:HIP ) HC E
330: HB3 0.10773 1.0 ( 23:HIP ) HC E
331: CG 0.18240 12.0 ( 23:HIP ) CC B
"""
# Based on variable width fields.
atom_number = int(line.split(':')[0])
atom_name = line.split()[1]
atom_charge = float(line.split()[2])
atom_mass = float(line.split()[3])
rnn = line.split('(')[1].split(')')[0].split(':')
residue_number = int(rnn[0])
residue_name = rnn[1]
atom_type = line.split(')')[1].split()[0]
self.AtomLists['Name'].append(atom_name)
self.AtomLists['Charge'].append(atom_charge)
self.AtomLists['Mass'].append(atom_mass)
self.AtomLists['ResidueNumber'].append(residue_number)
self.AtomLists['ResidueName'].append(residue_name)
# Not sure if this works
G.add_node(atom_number)
elif mode == 'Bond':
a, b = (int(i)
for i in (line.split('(')[1].split(')')[0].split(',')))
G.add_edge(a, b)
self.AtomMask = [a == 'A' for a in self.AtomLists['ParticleType']]
# Use networkx to figure out a list of molecule numbers.
# gs = nx.connected_component_subgraphs(G)
# tmols = [gs[i] for i in np.argsort(np.array([min(g.nodes()) for g in gs]))]
# mnodes = [m.nodes() for m in tmols]
# self.AtomLists['MoleculeNumber'] = [[i+1 in m for m in mnodes].index(1) for i in range(self.mol.na)]
## Write out the trajectory coordinates to a .mdcrd file.
# I also need to write the trajectory
if 'boxes' in self.mol.Data.keys():
warn_press_key(
"Writing %s-all.crd file with no periodic box information" %
self.name)
del self.mol.Data['boxes']
if hasattr(self, 'target') and hasattr(self.target, 'shots'):
self.qmatoms = target.qmatoms
self.mol.write("%s-all.crd" % self.name,
select=range(self.target.shots),
ftype="mdcrd")
else:
self.qmatoms = self.mol.na
self.mol.write("%s-all.crd" % self.name, ftype="mdcrd")
if prmtmp:
for f in self.FF.fnms:
os.unlink(f)
def evaluate_(self, crdin, force=False):
"""
Utility function for computing energy and forces using AMBER.
Inputs:
crdin: AMBER .mdcrd file name.
force: Switch for parsing the force. (Currently it always calculates the forces.)
Outputs:
Result: Dictionary containing energies (and optionally) forces.
"""
force_mdin = """Loop over conformations and compute energy and force (use ioutfnm=1 for netcdf, ntb=0 for no box)
&cntrl
imin = 5, ntb = 0, cut=9, nstlim = 0, nsnb = 0
/
&debugf
do_debugf = 1, dumpfrc = 1
/
"""
with wopen("%s-force.mdin" % self.name) as f:
print >> f, force_mdin
## This line actually runs AMBER.
self.leap(delcheck=True)
self.callamber(
"sander -i %s-force.mdin -o %s-force.mdout -p %s.prmtop -c %s.inpcrd -y %s -O"
% (self.name, self.name, self.name, self.name, crdin))
ParseMode = 0
Result = {}
Energies = []
Forces = []
Force = []
for line in open('forcedump.dat'):
line = line.strip()
sline = line.split()
if ParseMode == 1:
if len(sline) == 1 and isfloat(sline[0]):
Energies.append(float(sline[0]) * 4.184)
ParseMode = 0
if ParseMode == 2:
if len(sline) == 3 and all(
isfloat(sline[i]) for i in range(3)):
Force += [float(sline[i]) * 4.184 * 10 for i in range(3)]
if len(Force) == 3 * self.qmatoms:
Forces.append(np.array(Force))
Force = []
ParseMode = 0
if line == '0 START of Energies':
ParseMode = 1
elif line == '1 Total Force':
ParseMode = 2
Result["Energy"] = np.array(Energies[1:])
Result["Force"] = np.array(Forces[1:])
return Result
def energy_force_one(self, shot):
""" Computes the energy and force using TINKER for one snapshot. """
self.mol[shot].write("%s.xyz" % self.name, ftype="tinker")
Result = self.evaluate_("%s.xyz" % self.name, force=True)
return np.hstack((Result["Energy"].reshape(-1, 1), Result["Force"]))
def energy(self):
""" Computes the energy using TINKER over a trajectory. """
if hasattr(self, 'md_trajectory'):
x = self.md_trajectory
else:
x = "%s-all.crd" % self.name
self.mol.write(x, ftype="tinker")
return self.evaluate_(x)["Energy"]
def energy_force(self):
""" Computes the energy and force using AMBER over a trajectory. """
if hasattr(self, 'md_trajectory'):
x = self.md_trajectory
else:
x = "%s-all.crd" % self.name
Result = self.evaluate_(x, force=True)
return np.hstack((Result["Energy"].reshape(-1, 1), Result["Force"]))
def energy_dipole(self):
""" Computes the energy and dipole using TINKER over a trajectory. """
logger.error(
'Dipole moments are not yet implemented in AMBER interface')
raise NotImplementedError
if hasattr(self, 'md_trajectory'):
x = self.md_trajectory
else:
x = "%s.xyz" % self.name
self.mol.write(x, ftype="tinker")
Result = self.evaluate_(x, dipole=True)
return np.hstack((Result["Energy"].reshape(-1, 1), Result["Dipole"]))
def optimize(self, shot=0, method="newton", crit=1e-4):
""" Optimize the geometry and align the optimized geometry to the starting geometry. """
logger.error(
'Geometry optimizations are not yet implemented in AMBER interface'
)
raise NotImplementedError
# Code from tinkerio.py
if os.path.exists('%s.xyz_2' % self.name):
os.unlink('%s.xyz_2' % self.name)
self.mol[shot].write('%s.xyz' % self.name, ftype="tinker")
if method == "newton":
if self.rigid: optprog = "optrigid"
else: optprog = "optimize"
elif method == "bfgs":
if self.rigid: optprog = "minrigid"
else: optprog = "minimize"
o = self.calltinker("%s %s.xyz %f" % (optprog, self.name, crit))
# Silently align the optimized geometry.
M12 = Molecule("%s.xyz" % self.name, ftype="tinker") + Molecule(
"%s.xyz_2" % self.name, ftype="tinker")
if not self.pbc:
M12.align(center=False)
M12[1].write("%s.xyz_2" % self.name, ftype="tinker")
rmsd = M12.ref_rmsd(0)[1]
cnvgd = 0
mode = 0
for line in o:
s = line.split()
if len(s) == 0: continue
if "Optimally Conditioned Variable Metric Optimization" in line:
mode = 1
if "Limited Memory BFGS Quasi-Newton Optimization" in line:
mode = 1
if mode == 1 and isint(s[0]): mode = 2
if mode == 2:
if isint(s[0]): E = float(s[1])
else: mode = 0
if "Normal Termination" in line:
cnvgd = 1
if not cnvgd:
for line in o:
logger.info(str(line) + '\n')
logger.info(
"The minimization did not converge in the geometry optimization - printout is above.\n"
)
return E, rmsd
def normal_modes(self, shot=0, optimize=True):
logger.error('Normal modes are not yet implemented in AMBER interface')
raise NotImplementedError
# Copied from tinkerio.py
if optimize:
self.optimize(shot, crit=1e-6)
o = self.calltinker("vibrate %s.xyz_2 a" % (self.name))
else:
warn_once("Asking for normal modes without geometry optimization?")
self.mol[shot].write('%s.xyz' % self.name, ftype="tinker")
o = self.calltinker("vibrate %s.xyz a" % (self.name))
# Read the TINKER output. The vibrational frequencies are ordered.
# The six modes with frequencies closest to zero are ignored
readev = False
calc_eigvals = []
calc_eigvecs = []
for line in o:
s = line.split()
if "Vibrational Normal Mode" in line:
freq = float(s[-2])
readev = False
calc_eigvals.append(freq)
calc_eigvecs.append([])
elif "Atom" in line and "Delta X" in line:
readev = True
elif readev and len(s) == 4 and all(
[isint(s[0]),
isfloat(s[1]),
isfloat(s[2]),
isfloat(s[3])]):
calc_eigvecs[-1].append([float(i) for i in s[1:]])
calc_eigvals = np.array(calc_eigvals)
calc_eigvecs = np.array(calc_eigvecs)
# Sort by frequency absolute value and discard the six that are closest to zero
calc_eigvecs = calc_eigvecs[np.argsort(np.abs(calc_eigvals))][6:]
calc_eigvals = calc_eigvals[np.argsort(np.abs(calc_eigvals))][6:]
# Sort again by frequency
calc_eigvecs = calc_eigvecs[np.argsort(calc_eigvals)]
calc_eigvals = calc_eigvals[np.argsort(calc_eigvals)]
os.system("rm -rf *.xyz_* *.[0-9][0-9][0-9]")
return calc_eigvals, calc_eigvecs
def multipole_moments(self, shot=0, optimize=True, polarizability=False):
logger.error(
'Multipole moments are not yet implemented in AMBER interface')
raise NotImplementedError
""" Return the multipole moments of the 1st snapshot in Debye and Buckingham units. """
# This line actually runs TINKER
if optimize:
self.optimize(shot, crit=1e-6)
o = self.calltinker("analyze %s.xyz_2 M" % (self.name))
else:
self.mol[shot].write('%s.xyz' % self.name, ftype="tinker")
o = self.calltinker("analyze %s.xyz M" % (self.name))
# Read the TINKER output.
qn = -1
ln = 0
for line in o:
s = line.split()
if "Dipole X,Y,Z-Components" in line:
dipole_dict = OrderedDict(
zip(['x', 'y', 'z'], [float(i) for i in s[-3:]]))
elif "Quadrupole Moment Tensor" in line:
qn = ln
quadrupole_dict = OrderedDict([('xx', float(s[-3]))])
elif qn > 0 and ln == qn + 1:
quadrupole_dict['xy'] = float(s[-3])
quadrupole_dict['yy'] = float(s[-2])
elif qn > 0 and ln == qn + 2:
quadrupole_dict['xz'] = float(s[-3])
quadrupole_dict['yz'] = float(s[-2])
quadrupole_dict['zz'] = float(s[-1])
ln += 1
calc_moments = OrderedDict([('dipole', dipole_dict),
('quadrupole', quadrupole_dict)])
if polarizability:
if optimize:
o = self.calltinker("polarize %s.xyz_2" % (self.name))
else:
o = self.calltinker("polarize %s.xyz" % (self.name))
# Read the TINKER output.
pn = -1
ln = 0
polarizability_dict = OrderedDict()
for line in o:
s = line.split()
if "Total Polarizability Tensor" in line:
pn = ln
elif pn > 0 and ln == pn + 2:
polarizability_dict['xx'] = float(s[-3])
polarizability_dict['yx'] = float(s[-2])
polarizability_dict['zx'] = float(s[-1])
elif pn > 0 and ln == pn + 3:
polarizability_dict['xy'] = float(s[-3])
polarizability_dict['yy'] = float(s[-2])
polarizability_dict['zy'] = float(s[-1])
elif pn > 0 and ln == pn + 4:
polarizability_dict['xz'] = float(s[-3])
polarizability_dict['yz'] = float(s[-2])
polarizability_dict['zz'] = float(s[-1])
ln += 1
calc_moments['polarizability'] = polarizability_dict
os.system("rm -rf *.xyz_* *.[0-9][0-9][0-9]")
return calc_moments
def energy_rmsd(self, shot=0, optimize=True):
""" Calculate energy of the selected structure (optionally minimize and return the minimized energy and RMSD). In kcal/mol. """
logger.error(
'Geometry optimization is not yet implemented in AMBER interface')
raise NotImplementedError
rmsd = 0.0
# This line actually runs TINKER
# xyzfnm = sysname+".xyz"
if optimize:
E_, rmsd = self.optimize(shot)
o = self.calltinker("analyze %s.xyz_2 E" % self.name)
#----
# Two equivalent ways to get the RMSD, here for reference.
#----
# M1 = Molecule("%s.xyz" % self.name, ftype="tinker")
# M2 = Molecule("%s.xyz_2" % self.name, ftype="tinker")
# M1 += M2
# rmsd = M1.ref_rmsd(0)[1]
#----
# oo = self.calltinker("superpose %s.xyz %s.xyz_2 1 y u n 0" % (self.name, self.name))
# for line in oo:
# if "Root Mean Square Distance" in line:
# rmsd = float(line.split()[-1])
#----
os.system("rm %s.xyz_2" % self.name)
else:
o = self.calltinker("analyze %s.xyz E" % self.name)
# Read the TINKER output.
E = None
for line in o:
if "Total Potential Energy" in line:
E = float(line.split()[-2].replace('D', 'e'))
if E == None:
logger.error(
"Total potential energy wasn't encountered when calling analyze!\n"
)
raise RuntimeError
if optimize and abs(E - E_) > 0.1:
warn_press_key(
"Energy from optimize and analyze aren't the same (%.3f vs. %.3f)"
% (E, E_))
return E, rmsd
def interaction_energy(self, fraga, fragb):
""" Calculate the interaction energy for two fragments. """
logger.error(
'Interaction energy is not yet implemented in AMBER interface')
raise NotImplementedError
self.A = TINKER(name="A",
mol=self.mol.atom_select(fraga),
tinker_key="%s.key" % self.name,
tinkerpath=self.tinkerpath)
self.B = TINKER(name="B",
mol=self.mol.atom_select(fragb),
tinker_key="%s.key" % self.name,
tinkerpath=self.tinkerpath)
# Interaction energy needs to be in kcal/mol.
return (self.energy() - self.A.energy() - self.B.energy()) / 4.184
def molecular_dynamics(self,
nsteps,
timestep,
temperature=None,
pressure=None,
nequil=0,
nsave=1000,
minimize=True,
anisotropic=False,
threads=1,
verbose=False,
**kwargs):
"""
Method for running a molecular dynamics simulation.
Required arguments:
nsteps = (int) Number of total time steps
timestep = (float) Time step in FEMTOSECONDS
temperature = (float) Temperature control (Kelvin)
pressure = (float) Pressure control (atmospheres)
nequil = (int) Number of additional time steps at the beginning for equilibration
nsave = (int) Step interval for saving and printing data
minimize = (bool) Perform an energy minimization prior to dynamics
threads = (int) Specify how many OpenMP threads to use
Returns simulation data:
Rhos = (array) Density in kilogram m^-3
Potentials = (array) Potential energies
Kinetics = (array) Kinetic energies
Volumes = (array) Box volumes
Dips = (3xN array) Dipole moments
EComps = (dict) Energy components
"""
logger.error(
'Molecular dynamics not yet implemented in AMBER interface')
raise NotImplementedError
md_defs = OrderedDict()
md_opts = OrderedDict()
# Print out averages only at the end.
md_opts["printout"] = nsave
md_opts["openmp-threads"] = threads
# Langevin dynamics for temperature control.
if temperature != None:
md_defs["integrator"] = "stochastic"
else:
md_defs["integrator"] = "beeman"
md_opts["thermostat"] = None
# Periodic boundary conditions.
if self.pbc:
md_opts["vdw-correction"] = ''
if temperature != None and pressure != None:
md_defs["integrator"] = "beeman"
md_defs["thermostat"] = "bussi"
md_defs["barostat"] = "montecarlo"
if anisotropic:
md_opts["aniso-pressure"] = ''
elif pressure != None:
warn_once(
"Pressure is ignored because temperature is turned off.")
else:
if pressure != None:
warn_once("Pressure is ignored because pbc is set to False.")
# Use stochastic dynamics for the gas phase molecule.
# If we use the regular integrators it may miss
# six degrees of freedom in calculating the kinetic energy.
md_opts["barostat"] = None
eq_opts = deepcopy(md_opts)
if self.pbc and temperature != None and pressure != None:
eq_opts["integrator"] = "beeman"
eq_opts["thermostat"] = "bussi"
eq_opts["barostat"] = "berendsen"
if minimize:
if verbose: logger.info("Minimizing the energy...")
self.optimize(method="bfgs", crit=1)
os.system("mv %s.xyz_2 %s.xyz" % (self.name, self.name))
if verbose: logger.info("Done\n")
# Run equilibration.
if nequil > 0:
write_key("%s-eq.key" % self.name, eq_opts, "%s.key" % self.name,
md_defs)
if verbose: printcool("Running equilibration dynamics", color=0)
if self.pbc and pressure != None:
self.calltinker(
"dynamic %s -k %s-eq %i %f %f 4 %f %f" %
(self.name, self.name, nequil, timestep,
float(nsave * timestep) / 1000, temperature, pressure),
print_to_screen=verbose)
else:
self.calltinker("dynamic %s -k %s-eq %i %f %f 2 %f" %
(self.name, self.name, nequil, timestep,
float(nsave * timestep) / 1000, temperature),
print_to_screen=verbose)
os.system("rm -f %s.arc" % (self.name))
# Run production.
if verbose: printcool("Running production dynamics", color=0)
write_key("%s-md.key" % self.name, md_opts, "%s.key" % self.name,
md_defs)
if self.pbc and pressure != None:
odyn = self.calltinker(
"dynamic %s -k %s-md %i %f %f 4 %f %f" %
(self.name, self.name, nsteps, timestep,
float(nsave * timestep / 1000), temperature, pressure),
print_to_screen=verbose)
else:
odyn = self.calltinker(
"dynamic %s -k %s-md %i %f %f 2 %f" %
(self.name, self.name, nsteps, timestep,
float(nsave * timestep / 1000), temperature),
print_to_screen=verbose)
# Gather information.
os.system("mv %s.arc %s-md.arc" % (self.name, self.name))
self.md_trajectory = "%s-md.arc" % self.name
edyn = []
kdyn = []
temps = []
for line in odyn:
s = line.split()
if 'Current Potential' in line:
edyn.append(float(s[2]))
if 'Current Kinetic' in line:
kdyn.append(float(s[2]))
if len(s) > 0 and s[0] == 'Temperature' and s[2] == 'Kelvin':
temps.append(float(s[1]))
# Potential and kinetic energies converted to kJ/mol.
edyn = np.array(edyn) * 4.184
kdyn = np.array(kdyn) * 4.184
temps = np.array(temps)
if verbose: logger.info("Post-processing to get the dipole moments\n")
oanl = self.calltinker("analyze %s-md.arc" % self.name,
stdin="G,E,M",
print_to_screen=False)
# Read potential energy and dipole from file.
eanl = []
dip = []
mass = 0.0
ecomp = OrderedDict()
havekeys = set()
first_shot = True
for ln, line in enumerate(oanl):
strip = line.strip()
s = line.split()
if 'Total System Mass' in line:
mass = float(s[-1])
if 'Total Potential Energy : ' in line:
eanl.append(float(s[4]))
if 'Dipole X,Y,Z-Components :' in line:
dip.append([float(s[i]) for i in range(-3, 0)])
if first_shot:
for key in eckeys:
if strip.startswith(key):
if key in ecomp:
ecomp[key].append(float(s[-2]) * 4.184)
else:
ecomp[key] = [float(s[-2]) * 4.184]
if key in havekeys:
first_shot = False
havekeys.add(key)
else:
for key in havekeys:
if strip.startswith(key):
if key in ecomp:
ecomp[key].append(float(s[-2]) * 4.184)
else:
ecomp[key] = [float(s[-2]) * 4.184]
for key in ecomp:
ecomp[key] = np.array(ecomp[key])
ecomp["Potential Energy"] = edyn
ecomp["Kinetic Energy"] = kdyn
ecomp["Temperature"] = temps
ecomp["Total Energy"] = edyn + kdyn
# Energies in kilojoules per mole
eanl = np.array(eanl) * 4.184
# Dipole moments in debye
dip = np.array(dip)
# Volume of simulation boxes in cubic nanometers
# Conversion factor derived from the following:
# In [22]: 1.0 * gram / mole / (1.0 * nanometer)**3 / AVOGADRO_CONSTANT_NA / (kilogram/meter**3)
# Out[22]: 1.6605387831627252
conv = 1.6605387831627252
if self.pbc:
vol = np.array([BuildLatticeFromLengthsAngles(*[float(j) for j in line.split()]).V \
for line in open("%s-md.arc" % self.name).readlines() \
if (len(line.split()) == 6 and isfloat(line.split()[1]) \
and all([isfloat(i) for i in line.split()[:6]]))]) / 1000
rho = conv * mass / vol
else:
vol = None
rho = None
prop_return = OrderedDict()
prop_return.update({
'Rhos': rho,
'Potentials': edyn,
'Kinetics': kdyn,
'Volumes': vol,
'Dips': dip,
'Ecomps': ecomp
})
return prop_return
