def submit_job(self,job):
pad = self.enter(job.directory,msg=job.internal_id)
if job.subfile==None:
self.error('submission file not specified for job')
elif not os.path.exists(job.subfile):
self.error('job submission file was not written prior to submission\n submission file: '+os.path.join(job.directory,job.subfile))
#end if
command = self.sub_launcher+' '+job.subfile
if self.generate_only:
self.log(pad+'Would have executed: '+command)
job.status = job.states.running
process = obj()
process.job = job
self.processes[job.internal_id] = process
else:
self.log(pad+'Executing: '+command)
job.status = job.states.running
process = obj()
process.job = job
out,err = Popen(command,shell=True,stdout=PIPE,stderr=PIPE,close_fds=True).communicate()
output=out+'\n'+err
pid = self.read_process_id(output)
if pid is None:
self.error('process id could not be determined from submission output\n output:\n'+output)
#end if
#pid = 'fakepid_'+str(job.internal_id)
job.system_id = pid
self.processes[pid] = process
#end if
self.leave()
def read_outcar_charge_mag(vlines,odata,token):
ion = obj(s=[],p=[],d=[],tot=[])
total = obj()
vlines.advance_token(token)
vlines.advance(4)
prev_end = False
n=0
for line in vlines.remainder():
n+=1
if prev_end:
break
#end if
if line[0]=='-':
prev_end = True
else:
vals = array(line.split()[1:],dtype=float)
ion.s.append(vals[0])
ion.p.append(vals[1])
ion.d.append(vals[2])
ion.tot.append(vals[3])
#end if
#end for
for channel,vals in ion.iteritems():
ion[channel] = array(vals,dtype=float)
#end for
vlines.advance(n)
vals = array(line.split()[1:],dtype=float)
total.s = vals[0]
total.p = vals[1]
total.d = vals[2]
total.tot = vals[3]
return ion,total
def post_process_read(self,parent):
if 'atomic_species' in parent:
keys = self.keys()
for alias,name in self.atomic_variables.iteritems():
has_var = False
avals = obj()
akeys = []
for key in keys:
if key.startswith(name):
has_hubbard_u = True
akeys.append(key)
index = int(key.replace(name,'').strip('()'))
avals[index] = self[key]
#end if
#end for
if has_var:
for key in akeys:
del self[key]
#end for
atoms = parent.atomic_species.atoms
value = obj()
for i in range(len(atoms)):
index = i+1
if index in avals:
value[atoms[i]] = avals[i+1]
#end if
#end for
self[alias] = value
def class_init(cls):
for kw_field in cls.kw_fields:
if not kw_field in cls.__dict__:
cls.__dict__[kw_field] = set()
#end if
#end for
#cls.check_consistency()
cls.scalar_keywords = set()
for scalar_field in cls.kw_scalars:
cls.scalar_keywords |= cls.__dict__[scalar_field]
#end for
cls.array_keywords = set()
for array_field in cls.kw_arrays:
cls.array_keywords |= cls.__dict__[array_field]
#end for
cls.keywords = cls.scalar_keywords | cls.array_keywords
cls.type = obj()
cls.read_value = obj()
cls.write_value = obj()
cls.assign_value = obj()
for type in cls.kw_scalars + cls.kw_arrays:
for name in cls.__dict__[type]:
cls.type[name] = type
cls.read_value[name] = read_value_functions[type]
cls.write_value[name] = write_value_functions[type]
cls.assign_value[name] = assign_value_functions[type]
def get_result(self,result_name,sim):
result = obj()
input = self.input
control = input.control
prefix = 'pwscf'
outdir = './'
if 'prefix' in control:
prefix = control.prefix
#end if
if 'outdir' in control:
outdir = control.outdir
#end if
if outdir.startswith('./'):
outdir = outdir[2:]
#end if
if result_name=='charge_density':
result.location = os.path.join(self.locdir,outdir,prefix+'.save','charge-density.dat')
elif result_name=='orbitals':
result.location = os.path.join(self.locdir,outdir,prefix+'.wfc1')
elif result_name=='structure':
pa = self.load_analyzer_image()
structs = pa.structures
pos,atoms = structs[len(structs)-1].tuple('positions','atoms')
scale = self.input.system['celldm(1)']
pos = scale*array(pos)
atoms = array(atoms)
result.structure = obj(
positions = pos,
atoms = atoms
)
else:
self.error('ability to get result '+result_name+' has not been implemented')
#end if
return result
def __init__(self):
modes = nexus_core.modes
self.persistent_modes = set([modes.submit,modes.all])
self.simulations = obj()
self.cascades = obj()
self.progressing_cascades = obj()
self.operations = []
def pot_info(self):
pot_info = obj()
if len(self.pseudos)>0:
pots = self.pseudos
elif self.filepath!=None and self.files!=None:
pots = obj()
for file in self.files:
pots.append(open(os.path.join(self.filepath,file),'r').read())
#end for
else:
pots = obj()
#end if
for i in range(len(pots)):
pot = pots[i]
n1 = pot.find('\n')
n2 = pot.find('\n',n1+1)
Zval = int(float(pot[n1:n2].strip()))
n = pot.find('VRHFIN')
n1 = pot.find('=',n+1)+1
n2 = pot.find(':',n1+1)
element = pot[n1:n2].strip()
pot_info.append(obj(Zval=Zval,element=element))
#end for
return pot_info
def get_result(self, result_name, sim):
result = obj()
input = self.input
control = input.control
prefix = "pwscf"
outdir = "./"
if "prefix" in control:
prefix = control.prefix
# end if
if "outdir" in control:
outdir = control.outdir
# end if
if outdir.startswith("./"):
outdir = outdir[2:]
# end if
if result_name == "charge_density":
result.location = os.path.join(self.locdir, outdir, prefix + ".save", "charge-density.dat")
result.spin_location = os.path.join(self.locdir, outdir, prefix + ".save", "spin-polarization.dat")
elif result_name == "orbitals":
result.location = os.path.join(self.locdir, outdir, prefix + ".wfc1")
elif result_name == "structure":
pa = self.load_analyzer_image()
structs = pa.structures
pos, atoms = structs[len(structs) - 1].tuple("positions", "atoms")
scale = self.input.system["celldm(1)"]
pos = scale * array(pos)
atoms = array(atoms)
result.structure = obj(positions=pos, atoms=atoms)
else:
self.error("ability to get result " + result_name + " has not been implemented")
# end if
return result
def readfile(self,filepath):
text = TextFile(filepath)
Zatom,Z = text.read_tokens('Atomic number and pseudo-charge',int,float)
if Zatom>len(pt.simple_elements):
self.error('element {0} is not in the periodic table')
#end if
element = pt.simple_elements[Zatom].symbol
units = text.read_tokens('Energy units',str)
if not units in self.unitmap:
self.error('units {0} unrecognized from casino PP file {1}'.format(units,filepath))
#end if
lloc = text.read_tokens('Angular momentum of local component',int)
ngrid = text.read_tokens('Number of grid points',int)
i = text.find_line('R(i)',exit=True)+1
r = empty((ngrid,),dtype=float)
for ir in xrange(ngrid):
r[ir] = float(text.lines[i])
i+=1
#end for
r=r[1:]
p = obj()
while i<len(text.lines):
line = text.lines[i]
if 'potential' in line:
eqloc = line.find('=')
if eqloc==-1:
self.error('"=" not found in potential line')
#end if
l = int(line[eqloc+1])
i+=1
if i+ngrid>len(text.lines):
self.error('potentials in file {0} are not the right length'.format(filepath))
#end if
v = empty((ngrid,),dtype=float)
for ir in xrange(ngrid):
v[ir] = float(text.lines[i])
i+=1
#end for
p[l] = v[1:]/r
#end if
#end while
for l in p.keys():
p[l] = convert(p[l],self.unitmap[units],self.energy_units)
#end for
self.set(
element = element,
type = 'Trail-Needs',
Z = Z,
r = r,
potentials = p,
pp = obj(
Zatom = Zatom,
Z = Z,
units = units,
lloc = lloc,
ngrid = ngrid
)
)
def uncontract(self,tol=1e-3):
if self.uncontracted():
return
#end if
lbasis = self.lbasis()
self.basis.clear()
for l in self.lset_full:
if l in lbasis:
exponents = []
lbas = lbasis[l]
for n in xrange(len(lbas)):
uterms = lbas[n].terms
for i in xrange(len(uterms)):
expon = uterms[i].expon
if len(exponents)==0:
exponents = array([expon],dtype=float)
elif abs(exponents-expon).min()>tol:
exponents = array(list(exponents)+[expon],dtype=float)
#end if
#end for
#end for
for expon in exponents:
cterms = obj()
cterms.append(obj(expon=expon,coeff=1.0))
bf = obj(l=l,scale=array([1.0]),terms=cterms)
self.basis.append(bf)
def morse_fit_fine(r,E,p0=None,rfine=None,both=False,jackknife=False,minimizer=least_squares,capture=None):
if rfine is None:
rfine = linspace(r.min(),r.max(),400)
#end if
auxfuncs = obj(
Efine = (morse,[None,rfine])
)
auxres = obj()
res = morse_fit(r,E,p0,jackknife,minimizer,auxfuncs,auxres,capture)
if not jackknife:
pf = res
else:
pf,pmean,perror = res
#end if
Efine = morse(pf,rfine)
if not jackknife:
if not both:
return Efine
else:
return pf,Efine
#end if
else:
Emean,Eerror = auxres.Efine
if not both:
return Efine,Emean,Eerror
else:
return pf,pmean,perror,Efine,Emean,Eerror
def __init__(self, arg0=None, prefix=None, analyze=False, exit=False, **outfilenames):
self.info = obj(exit=exit, path=None, input=None, prefix=None, files=obj(), initialized=False)
infile = None
if isinstance(arg0, Simulation):
sim = arg0
infile = os.path.join(sim.locdir, sim.infile)
else:
infile = arg0
# end if
if infile != None:
info = self.info
info.path = os.path.dirname(infile)
info.input = GamessInput(infile)
infilename = os.path.split(infile)[1]
if prefix is None:
prefix = infilename.rsplit(".", 1)[0]
# end if
info.prefix = prefix
files = info.files
for file, unit in GamessInput.file_units.iteritems():
files[file.lower()] = "{0}.F{1}".format(prefix, str(unit).zfill(2))
# end for
files.input = infilename
files.output = "{0}.out".format(prefix)
for name, filename in outfilenames:
if name in files:
files[name] = filename
else:
self.error("unknown GAMESS file: {0}".format(name))
# end if
# end for
info.initialized = True
if analyze:
self.analyze()
def __init__(self):
# variables determined by self
modes = self.modes
self.persistent_modes = set([modes.submit, modes.all])
self.simulations = obj()
self.cascades = obj()
self.progressing_cascades = obj()
self.operations = []
def from_list_rep(self,list_rep):
self.local = list_rep[0][0]
if len(list_rep)>1:
boxes = obj()
for units,rmin,rmax,depth in list_rep[2:]:
boxes.append(obj(units=units,rmin=rmin,rmax=rmax,depth=depth))
#end for
self.boxes = boxes
def plot_trace(self,quantity,style='b-',offset=0,source='scalar',mlabels=True,
mlines=True,show=True,alloff=False):
mlabels &= not alloff
mlines &= not alloff
show &= not alloff
shw = show
offset = int(offset)
id = self.info.input.get('project').id
sdata = obj()
series = sorted(self.qmc.keys())
q = []
soffset = offset
for s in series:
qmc = self.qmc[s]
method = qmc.info.method
if source=='scalar' or method=='vmc':
src = qmc.scalars.data
elif source=='dmc':
src = qmc.dmc.data
else:
self.error('invalid source: '+source)
#end if
if quantity in src:
qn = list(src[quantity])
else:
qn = len(src.LocalEnergy)*[0]
#end if
q.extend(qn)
sdata[s] = obj(
mlab = method+' '+str(s),
mloc = soffset + len(qn)/2,
line_loc = soffset + len(qn)-1
)
soffset += len(qn)
#end for
q = array(q)
qmin = q.min()
qmax = q.max()
mlabel_height = qmin + .8*(qmax-qmin)
if shw:
figure()
#end if
plot(offset+arange(len(q)),q,style,label=id)
for s in series:
sd = sdata[s]
if mlabels:
text(sd.mloc,mlabel_height,sd.mlab)
#end if
if mlines:
plot([sd.line_loc,sd.line_loc],[qmin,qmax],'k-')
#end if
#end for
if shw:
title('{0} vs series for {1}'.format(quantity,id))
xlabel('blocks')
ylabel(quantity)
legend()
show()
def correct(self,*corrections):
corrkey=''
for corr in corrections:
corrkey+=corr+'_'
#end for
corrkey=corrkey[:-1]
if set(corrections)>set(self.corrections.keys()):
self.warn('correction '+corrkey+' is unknown and cannot be applied')
return
#end if
if not 'data' in self:
self.warn('correction '+corrkey+' cannot be applied because data is not present')
return
#end if
varname = 'LocalEnergy_'+corrkey
if varname in self and varname in self.data:
return
#end if
corrvars = ['LocalEnergy']
signs = [1]
for corr in corrections:
for var,sign in self.corrections[corr].iteritems():
corrvars.append(var)
signs.append(sign)
#end for
#end for
missing = list(set(corrvars)-set(self.data.keys()))
if len(missing)>0:
self.warn('correction '+corrkey+' cannot be applied because '+str(missing)+' are missing')
return
#end if
le = self.data.LocalEnergy
E,E2 = 0*le.value,0*le.value_squared
n = len(corrvars)
for i in range(n):
ed = self.data[corrvars[i]]
e,e2 = ed.value,ed.value_squared
s = signs[i]
E += s*e
E2 += e2
for j in range(i+1,n):
eo = self.data[corrvars[j]].value
so = signs[j]
E2 += 2*s*e*so*eo
#end for
#end for
val = obj(value=E,value_squared=E2)
self.data[varname] = val
nbe = self.info.nblocks_exclude
(mean,var,error,kappa)=simstats(val.value[nbe:,...].ravel())
self[varname] = obj(
mean = mean,
variance = val.value_squared[nbe:,...].mean()-mean**2,
sample_variance = var,
error = error,
kappa = kappa
)
def __init__(self,**kwargs):
#user specified variables
self.path = None #directory where sim will be run
self.job = None #Job object for machine
self.dependencies = obj() #Simulation results on which sim serially depends
#variables determined by self
self.identifier = self.generic_identifier
self.simid = Simulation.sim_count
Simulation.sim_count+=1
self.files = set()
self.app_name = self.application
self.app_props = list(self.application_properties)
self.sim_image = self.sim_imagefile
self.input_image = self.input_imagefile
self.analyzer_image = self.analyzer_imagefile
self.image_dir = self.image_directory
self.input = self.input_type()
self.system = None
self.dependents = obj()
self.created_directories = False
self.got_dependencies = False
self.setup = False
self.sent_files = False
self.submitted = False
self.finished = False
self.failed = False
self.got_output = False
self.analyzed = False
self.subcascade_finished = False
self.dependency_ids = set()
self.wait_ids = set()
self.block = False
self.block_subcascade = False
self.skip_submit = nexus_core.skip_submit
self.force_write = False
self.loaded = False
self.ordered_dependencies = []
self.process_id = None
self.infile = None
self.outfile = None
self.errfile = None
#variables determined by derived classes
self.outputs = None #object representing output data
# accessed by dependents when calling get_dependencies
self.set(**kwargs)
self.set_directories()
self.set_files()
self.propagate_identifier()
if len(kwargs)>0:
self.init_job()
#end if
self.post_init()
if self.system!=None:
self.system.check_folded_system()
def __init__(self,*args,**kwargs):
# some args are
# graph_name = 'G'
# graph_type in ('graph','digraph')
self.graph = self.pydot_type(*args,**kwargs)
self.name = self.graph.get_name()
self.nodes = obj()
self.edges = obj()
self.subgraphs = obj()
def add_density(
self, cell, density, name="density", corner=None, grid=None, centered=False, add_ghost=False, transpose=False
):
if corner is None:
corner = zeros((3,), dtype=float)
# end if
if grid is None:
grid = density.shape
# end if
grid = array(grid, dtype=int)
corner = array(corner, dtype=float)
cell = array(cell, dtype=float)
density = array(density, dtype=float)
density.shape = tuple(grid)
if centered: # shift corner by half a grid cell to center it
dc = 0.5 / grid
dc = dot(dc, cell)
corner += dc
# end if
if add_ghost: # add ghost points to make a 'general' xsf grid
g = grid # this is an extra shell of points in PBC
d = density
grid = g + 1
density = zeros(tuple(grid), dtype=float)
density[: g[0], : g[1], : g[2]] = d[:, :, :] # volume copy
density[-1, : g[1], : g[2]] = d[0, :, :] # face copies
density[: g[0], -1, : g[2]] = d[:, 0, :]
density[: g[0], : g[1], -1] = d[:, :, 0]
density[-1, -1, : g[2]] = d[0, 0, :] # edge copies
density[-1, : g[1], -1] = d[0, :, 0]
density[: g[0], -1, -1] = d[:, 0, 0]
density[-1, -1, -1] = d[0, 0, 0] # corner copy
# end if
if transpose: # shift from row major to column major
g = grid
d = density
density = zeros((d.size,))
n = 0
for k in xrange(g[2]):
for j in xrange(g[1]):
for i in xrange(g[0]):
density[n] = d[i, j, k]
n += 1
# end for
# end for
# end for
density.shape = tuple(grid)
# end if
self.data = obj()
self.data[3] = obj()
self.data[3][name] = obj()
self.data[3][name][name] = obj(grid=grid, corner=corner, cell=cell, values=density)
def load_cascades(self):
cascades = obj()
progressing_cascades = obj()
for cid,cascade in self.cascades.iteritems():
rc = cascade.reconstruct_cascade()
cascades[rc.simid] = rc
progressing_cascades[rc.simid] = rc
#end for
self.cascades = cascades
self.progressing_cascades = progressing_cascades
def from_list_rep(self,list_rep):
self.symbol = list_rep[0][0]
self.rorbs = list_rep[1][0]
ref = obj()
n = 0
for nlm,occ,eig in list_rep[2:]:
ref[n] = obj(nlm=nlm,occ=occ,eig=eig)
n+=1
#end for
self.ref = ref
def __init__(self,fpath,verbose=False,view=False):
HDFglobals.view = view
if verbose:
print ' Initializing HDFreader'
self.fpath=fpath
if verbose:
print ' loading h5 file'
try:
self.hdf = h5py.File(fpath,'r')
except IOError:
self._success = False
self.hdf = obj(obj=obj())
else:
self._success = True
#end if
if verbose:
print ' converting h5 file to dynamic object'
#convert the hdf 'dict' into a dynamic object
self.nlevels=1
self.ilevel=0
# Set the current hdf group
self.obj = HDFgroup()
self.cur=[self.obj]
self.hcur=[self.hdf]
if self._success:
cur = self.cur[self.ilevel]
hcur = self.hcur[self.ilevel]
for kr,v in hcur.iteritems():
k=cur._escape_name(kr)
if valid_variable_name(k):
vtype = str(type(v))
if vtype in HDFreader.datasets:
self.add_dataset(cur,k,v)
elif vtype in HDFreader.groups:
self.add_group(hcur,cur,k,v)
else:
print 'hdfreader error: encountered invalid type: '+vtype
sys.exit()
#end if
else:
print 'hdfreader warning: attribute '+k+' is not a valid variable name and has been ignored'
#end if
#end for
#end if
if verbose:
print ' end HDFreader Initialization'
return
def lbasis(self):
lbasis = obj()
for n in range(len(self.basis)):
bf = self.basis[n]
l = bf.l
if l not in lbasis:
lbasis[l] = obj()
#end if
lbasis[l].append(bf)
#end for
return lbasis
def add_to_image(self, image, name, value):
if image is None:
self[name] = value
else:
if "images" not in self:
self.images = obj()
# end if
if not image in self.images:
self.images[image] = obj()
# end if
self.images[image][name] = value
def analyze_outcar(self,outcar):
if not os.path.exists(outcar):
self.error('outcar file {0} does not exist'.format(outcar))
#end if
oc = open(outcar,'r')
lines = oc.read().splitlines()
oc.close()
del oc
# gather initialization lines
init = []
n = 0
for line in lines:
if len(line)>0 and line[0]=='-' and 'Iteration' in line:
break
#end if
init.append(line)
n+=1
#end for
# gather lines for each iteration
ion_steps = obj()
for line in lines[n:]:
if len(line)>0 and line[0]=='-' and 'Iteration' in line:
iteration = []
inum,enum = line.strip(' -Iteration)').split('(')
inum = int(inum)
enum = int(enum)
if not inum in ion_steps:
ion_steps[inum] = obj()
#end if
ion_steps[inum][enum] = OutcarData(lines=iteration)
#end if
iteration.append(line)
#end for
del lines
del n
# read data from each iteration
if len(ion_steps)>0:
imax = array(ion_steps.keys(),dtype=int).max()
for inum,ion_step in ion_steps.iteritems():
ilast = inum==imax
if len(ion_step)>0:
emax = array(ion_step.keys(),dtype=int).max()
for enum,elec_step in ion_step.iteritems():
elast = enum==emax
elec_step.read(ilast,elast,all=False)
if ilast and elast:
self.transfer_from(elec_step)
#end if
#end for
#end if
#end for
#end if
self.ion_steps = ion_steps
def read_contents(self,lines):
atoms = []
masses = obj()
pseudopotentials = obj()
for l in lines:
tokens = l.split()
atom = tokens[0]
atoms.append(tokens[0])
masses[atom] = float(tokens[1])
pseudopotentials[atom] = tokens[2]
#end for
self.add(atoms=atoms,masses=masses,pseudopotentials=pseudopotentials)
def read_contents(self,lines):
tokens = lines[0].split()
self.ncontraints = int(tokens[0])
if len(tokens)>1:
self.tolerance = float(tokens[1])
#end if
self.collective_vars = obj()
for i in range(len(lines)-1):
tokens = lines[i+1].split()
collv = obj()
collv.type = tokens[0]
collv.parameters = array(tokens[1:],dtype=float64)
self.collective_vars[i] = collv
def __init__(self):
self._name=''
self._parent=None
self._elements=obj()
self._texts=obj()
self._attributes=obj()
self._element_counts=obj()
self._ntexts=0
self._escape_names=None
#self._escape_names=set(dict(getmembers(self)).keys()) | set(keyword.kwlist)
self._escape_names=set(keyword.kwlist)
return
def read_outcar_accounting(vlines,odata):
time = obj()
memory = obj()
vlines.advance_token('General timing and accounting')
vlines.advance(2)
time.cpu = float(vlines.advance_line(1).split()[-1])
time.user = float(vlines.advance_line(1).split()[-1])
time.system = float(vlines.advance_line(1).split()[-1])
time.elapsed = float(vlines.advance_line(1).split()[-1])
vlines.advance(1)
memory.maximum = float(vlines.advance_line(1).split()[-1])
memory.average = float(vlines.advance_line(1).split()[-1])
odata.time = time
odata.memory = memory
def load_cascades(self):
self.dlog("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~load cascades", n=1)
cascades = obj()
progressing_cascades = obj()
for cid, cascade in self.cascades.iteritems():
self.dlog("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~reconstruct cascade", n=1)
rc = cascade.reconstruct_cascade()
self.dlog("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~end reconstruct cascade", n=1)
cascades[rc.simid] = rc
progressing_cascades[rc.simid] = rc
# end for
self.cascades = cascades
self.progressing_cascades = progressing_cascades
self.dlog("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~end load cascades", n=1)
def get_result(self,result_name,sim):
result = obj()
input = self.input
wfn_file,ptcl_file = self.list_output_files()
if result_name=='orbitals':
result.location = os.path.join(self.locdir,wfn_file)
if self.input.hdf5==True:
orbfile = self.get_prefix()+'.orbs.h5'
result.orbfile = os.path.join(self.locdir,orbfile)
#end if
elif result_name=='particles':
result.location = os.path.join(self.locdir,ptcl_file)
else:
self.error('ability to get result '+result_name+' has not been implemented')
#end if
return result
def contracted_basis_size(self):
bcount = obj()
for bf in self.basis:
l = bf.l
if l not in bcount:
bcount[l] = 0
#end if
bcount[l] += 1
#end for
bs = ''
for l in self.lset_full:
if l in bcount:
bs += str(bcount[l]) + l
#end if
#end for
return bs
def init_job_extra(self):
# gamess seems to need lots of environment variables to run properly
# nearly all of these are names of output/work files
# setup the environment to run gamess
if not isinstance(self.ericfmt, str):
self.error(
'you must set ericfmt with settings() or Gamess.settings()')
#end if
env = obj()
for file, unit in GamessInput.file_units.iteritems():
env[file] = '{0}.F{1}'.format(self.identifier, str(unit).zfill(2))
#end for
env.INPUT = self.infile
env.ERICFMT = self.ericfmt
env.MCPPATH = self.mcppath
self.job.set_environment(**env)
def prim_expons(self):
if self.contracted():
self.error(
'cannot find primitive gaussian expons because basis is contracted'
)
#end if
lbasis = self.lbasis()
gexpon = obj()
for l, lbas in lbasis.items():
e = []
for n in range(len(lbas)):
e.append(lbas[n].terms[0].expon)
#end for
gexpon[l] = array(e, dtype=float)
#end for
return gexpon
def prim_widths(self):
if self.contracted():
self.error(
'cannot find primitive gaussian widths because basis is contracted'
)
#end if
lbasis = self.lbasis()
gwidth = obj()
for l, lbas in lbasis.items():
w = []
for n in range(len(lbas)):
w.append(1. / sqrt(2. * lbas[n].terms[0].expon))
#end for
gwidth[l] = array(w, dtype=float)
#end for
return gwidth
class SystemGroup(KeywordSpecGroup):
keywords = set(['mwords','memddi','timlim','parall','kdiag','corefl',
'baltyp','mxseq2','mxseq3','nodext','iosmp','modio' ,
'memory'])
integers = set(['mwords','memddi','kdiag','mxseq2','mxseq3','modio','memory'])
reals = set(['timlim'])
bools = set(['parall','corefl'])
strings = set(['baltyp'])
arrays = set(['nodext','iosmp'])
allowed_values = obj(
kdiag = set([0,1,2,3]),
baltyp = set(['slb','dlb','loop','nxtval']),
modio = set([1,2,4,8,15]),
)
def finalize(self):
keys = list(self.keys())
enums = obj()
for k in keys:
v = self[k]
if isinstance(k,str) and '.' in k and k.split('.',1)[1].isdigit():
name,index = k.split('.',1)
index = int(index)
if not name in enums:
enums[name] = QEXML()
#end if
enums[name][index] = v
del self[k]
continue
#end if
if isinstance(v,QEXML):
if len(set(v.keys())-self.array_keys)==0:
a = array(v._value)
if len(a)==1:
a = a[0]
elif 'columns' in v and v.size%v.columns==0:
a.shape = v.size/v.columns,v.columns
#end if
self[k] = a
else:
v.finalize()
#end if
#end if
#end for
for k,v in enums.iteritems():
self[k] = v
v.finalize()
#end for
if len(self._value)==0:
del self._value
elif not 'value' in self:
if len(self._value)==1:
self.value = self._value[0]
else:
self.value = array(self._value)
#end if
del self._value
else:
if len(self._value)==1:
self._value = self._value[0]
else:
self._value = array(self._value)
def __init__(self,structure=None,net_charge=0,net_spin=0,particles=None,**valency):
self.pseudized = False
if structure is None:
self.structure = Structure()
else:
self.structure = structure
#end if
if particles is None:
self.particles = Particles()
else:
self.particles = particles.copy()
#end if
self.folded_system = None
if self.structure.folded_structure!=None:
vratio = structure.volume()/structure.folded_structure.volume()
ncells = int(round(vratio))
if abs(vratio-ncells)>1e-4:
self.error('volume of system does not divide evenly into folded system')
#end if
if net_charge%ncells!=0:
self.error('net charge of system does not divide evenly into folded system')
#end if
if isinstance(net_spin,str):
net_spin_fold = net_spin
elif net_spin%ncells!=0:
self.error('net_spin of system does not divide evenly into folded system')
else:
net_spin_fold = net_spin/ncells
#end if
self.folded_system = PhysicalSystem(
structure = structure.folded_structure,
net_charge = net_charge/ncells,
net_spin = net_spin_fold,
particles = particles,
**valency
)
#end if
self.valency_in = obj(**valency)
self.net_charge_in = net_charge
self.net_spin_in = net_spin
self.update_particles(clear=False)
self.check_folded_system()
def get_result(self, result_name, sim):
result = obj()
analyzer = self.load_analyzer_image()
if result_name == 'orbitals':
outfiles = self.input.get_output_info(list=False)
result.set(dir=self.locdir,
h5file=outfiles.h5,
qmcfile=outfiles.qmc)
elif result_name == 'jastrow':
result.set(rcut=analyzer.find_rcut(qcut=1e-3),
B=1. / analyzer.moment(n=1))
else:
self.error('ability to get result ' + result_name +
' has not been implemented')
#end if
del analyzer
return result
def get_result(self, result_name, sim):
# optional
# only necessary if another simulation depends on this one
# e.g.
# other_sim.depends(template_simulation_sim,'orbitals') or similar
# if you don't want to implement it, uncomment the line below
#self.not_implemented()
result = obj()
input = self.input
#analyzer = self.load_analyzer_image()
# package information about a result/product in the result object
# for example, if orbitals are requested,
# the path to the orbital file might be provided:
# result.orbital_file = '/path/to/orbital/file'
return result
def get_result(self, result_name, sim):
result = obj()
analyzer = self.load_analyzer_image()
if result_name == 'jastrow':
if not 'results' in analyzer or not 'optimization' in analyzer.results:
self.error(
'analyzer did not compute results required to determine jastrow'
)
#end if
opt_file = str(analyzer.results.optimization.optimal_file)
result.opt_file = os.path.join(self.locdir, opt_file)
else:
self.error('ability to get result ' + result_name +
' has not been implemented')
#end if
del analyzer
return result
def resolve_file_collisions(self):
self.log('checking for file collisions',n=1)
entry_order = obj()
def set_entry_order(sim,entry_order):
locdir = sim.locdir
if not locdir in entry_order:
entry_order[locdir] = [sim]
else:
entry_order[locdir].append(sim)
#end if
#end def set_entry_order
self.traverse_cascades(set_entry_order,entry_order)
any_collisions = False
collpath = ''
for path,simlist in entry_order.iteritems():
if len(simlist)>1:
#raise an error if any in/out/err files will collide
filespace = dict()
for sim in simlist:
if not sim.allow_overlapping_files:
files = sim.list('infile','outfile','errfile')
for f in files:
if f not in filespace:
filespace[f] = [sim]
else:
filespace[f].append(sim)
#end if
#end for
#end if
#end for
for f,sims in filespace.iteritems():
if len(sims)>1 and f!=None:
any_collisions = True
msg = 'collision: file '+f+' is overwritten by '
for sim in sims:
msg +=str(sim.identifier)+' '+str(sim.simid)+','
#end for
self.log(msg[:-1],n=2)
collpath = path
#end if
#end for
#end if
#end for
if any_collisions:
self.error('file collisions found in directory\n '+path+'\n set a unique identifier for each simulation')
class Optinfo(Section):
variables = obj(qcuts=list, bessels=list)
def list_rep(self):
list_rep = zip(self.qcuts, self.bessels)
return list_rep
#end def list_rep
def from_list_rep(self, list_rep):
qc = []
bs = []
for q, b in list_rep:
qc.append(q)
bs.append(b)
#end for
self.qcuts = qc
self.bessels = bs
def incorporate_user_info(self, infoin):
info = obj(**infoin)
vars = set(info.keys())
invalid = vars - self.allowed_user_info
if len(invalid) > 0:
self.error(
'invalid inputs encountered in incorporate_user_info\n allowed inputs: {0}\n invalid inputs: {1}'
.format(list(self.allowed_user_info), list(invalid)))
#end if
if 'app_directories' in info:
ad = info.app_directories
if not isinstance(ad, dict) and not isinstance(ad, obj):
self.error(
'app_directories must be of type dict or obj\n you provided '
+ ad.__class__.__name__)
#end if
#end if
self.transfer_from(info)
class BasisGroup(KeywordSpecGroup):
keywords = set([
'gbasis','ngauss','ndfunc','npfunc','diffsp','diffs',
'polar' ,'split2','split3','basnam','extfil'
])
integers = set(['ngauss','ndfunc','nffunc'])
bools = set(['diffsp','diffs','extfil'])
strings = set(['gbasis','polar'])
arrays = set(['split2','split3','basname'])
allowed_values = obj(
#gbasis = set(['sto','n21','n31','n311','g3l','g3lx','mini','midi','dzv',
# 'dh','tzv','mc']) # many others
ndfunc = set([0,1,2,3]),
nffunc = set([0,1]),
polar = set(['common','popn31','popn311','dunning','huzinaga','hondo7']),
)
def __init__(self):
self.methods = set(['opt', 'vmc', 'dmc', 'rmc'])
self.data_sources = set(
['scalar', 'stat', 'dmc', 'storeconfig', 'opt', 'traces'])
self.scalars = set([
'localenergy', 'localpotential', 'kinetic', 'elecelec', 'localecp',
'nonlocalecp', 'ionion', 'localenergy_sq', 'acceptratio',
'blockcpu', 'blockweight', 'mpc', 'kecorr'
])
self.fields = set([
'energydensity', 'density', 'dm1b', 'spindensity',
'structurefactor'
])
hdf_data_sources = set(['stat', 'storeconfig', 'traces'])
if h5py_unavailable:
self.data_sources -= hdf_data_sources
#end if
self.analyzer_quantities = set(self.fields)
self.analyzers = obj(scalars_dat=ScalarsDatAnalyzer,
scalars_hdf=ScalarsHDFAnalyzer,
dmc_dat=DmcDatAnalyzer,
traces=TracesAnalyzer,
energydensity=EnergyDensityAnalyzer,
dm1b=DensityMatricesAnalyzer,
spindensity=SpinDensityAnalyzer,
structurefactor=StructureFactorAnalyzer,
density=DensityAnalyzer)
self.quantities = self.scalars | self.fields
self.ignorable_estimators = set(['LocalEnergy'])
self.quantity_aliases = dict()
for q in self.analyzer_quantities:
self.quantity_aliases[q] = q
#end for
self.future_quantities = set(
['StructureFactor', 'MomentumDistribution'])
return
def test_convert4qmc_input_generate():
from generic import obj
from qmcpack_converters import generate_convert4qmc_input
ci = generate_convert4qmc_input(
gamess='gamess.out',
hdf5=True,
)
ci_ref = obj(
add_3body_J=False,
add_cusp=False,
app_name='convert4qmc',
casino=None,
ci=None,
first=None,
gamess='gamess.out',
gamess_ascii=None,
gamess_fmo=None,
gamess_xml=None,
gaussian=None,
gridtype=None,
hdf5=True,
ion_tag=None,
last=None,
multidet=None,
natural_orbitals=None,
no_jastrow=False,
opt_det_coeffs=False,
orbitals=None,
prefix=None,
production=False,
psi_tag=None,
pyscf=None,
qp=None,
read_initial_guess=None,
size=None,
target_state=None,
threshold=None,
vsvb=None,
zero_ci=False,
)
assert (object_eq(ci.to_obj(), ci_ref))
def check_attributes(self, exit=False):
msg = ''
cls = self.__class__
a = obj()
for name in cls.toplevel_attributes:
if name in self:
a[name] = self[name]
#end if
#end for
props = cls.attribute_definitions
for name in cls.sublevel_attributes:
p = props[name]
if p.dest in self:
sub = self[p.dest]
if name in sub:
a[name] = sub[name]
#end if
#end if
#end for
present = set(a.keys())
missing = cls.required_attributes - present
if len(missing) > 0:
m = ''
for n in sorted(missing):
m += '\n ' + n
#end for
msg += 'Required attributes are missing.\nPlease provide the following attributes during initialization:{}\n'.format(
m)
#end if
for name in cls.typed_attributes:
if name in a:
p = props[name]
v = a[name]
if not isinstance(v, p.type):
msg += 'Attribute "{}" has invalid type.\n Type expected: {}\n Type present: {}\n'.format(
name, p.type.__name__, v.__class__.__name__)
#end if
#end if
#end for
valid = len(msg) == 0
if not valid and exit:
self.error(msg)
#end if
return valid
def get_result(self, result_name, sim):
result = obj()
rc = self.input.run_control
if result_name == 'orbitals':
if rc.run_type == 'save_for_qmcpack':
result.outfile = os.path.join(self.locdir, self.outfile)
elif rc.save_for_qmcpack:
result.outfile = os.path.join(
self.locdir, '{0}_savewf.out'.format(self.identifier))
else:
self.error(
"cannot get orbitals\ntracking of save_for_qmcpack is somehow corrupted\nthis is a developer error"
)
#end if
else:
self.error('ability to get result ' + result_name +
' has not been implemented')
#end if
return result
def get_result(self, result_name, sim):
result = obj()
input = self.input
if result_name == 'structure':
# OUTCAR structure is not as precise as CONTCAR structure
#pa = self.load_analyzer_image()
#elem = input.poscar.elem
#elem_count = input.poscar.elem_count
#atoms = []
#for i in range(len(elem)):
# atoms += elem_count[i]*[elem[i]]
##end for
#structure = Structure(
# units = 'A',
# axes = pa.lattice_vectors.copy(),
# elem = atoms,
# pos = pa.position.copy()
# )
# get structure from CONTCAR
ccfile = os.path.join(self.locdir, self.identifier + '.CONTCAR')
if not os.path.exists(ccfile):
self.error(
'CONTCAR file does not exist for relax simulation at ' +
self.locdir)
#end if
contcar = Poscar(ccfile)
structure = Structure()
if contcar.elem != None:
structure.read_poscar(ccfile)
else:
elem, elem_count = self.system.structure.order_by_species()
structure.read_poscar(ccfile, elem=elem)
#end if
if input.poscar.dynamic != None:
structure.freeze(input.poscar.dynamic, negate=True)
#end if
result.structure = structure
else:
self.error('ability to get result ' + result_name +
' has not been implemented')
#end if
return result
class GuessGroup(KeywordSpecGroup):
keywords = set([
'guess', 'prtmo', 'punmo', 'mix', 'norb', 'norder', 'iorder', 'jorder',
'insorb', 'purify', 'tolz', 'tole', 'symden'
])
integers = set(['norb', 'norder', 'insorb'])
reals = set(['tolz', 'tole'])
bools = set(['prtmo', 'punmo', 'mix', 'purify', 'symden'])
strings = set(['guess'])
arrays = set(['iorder', 'jorder'])
allowed_values = obj(
guess=set([
'huckel', 'hcore', 'moread', 'rdmini', 'mosaved', 'skip', 'fmo',
'hucsub', 'dmread'
]),
norder=set([0, 1]),
)
class CidrtGroup(KeywordSpecGroup):
keywords = set([
'group','fors' ,'foci' ,'soci','iexcit','intact','nfzc' ,
'ndoc' ,'naos' ,'nbos' ,'nalp','nval' ,'next' ,'nfzv' ,'stsym',
'noirr','mxnint','mxneme','nprt'
])
integers = set(['iexcit','nfzc','ndoc','naos','nbos','nalp','nval',
'next','nfzv','noirr','mxnint','mxneme','nprt'])
bools = set(['fors','foci','soci','intact'])
strings = set(['group','stsym'])
allowed_values = obj(
group = set(['c1','c2','ci','cs','c2v','c2h','d2','d2h','c4v','d4','d4h']),
stsym = set(['a','ag','au','ap','app','a','b','a1','a2','b1','b2','ag',
'bu','bg','au','a','b1','b2','b3','ag','b1g','b2g','b3g',
'au','b1u','b2u','b3u']),
nprt = set([0,1,2,3]),
)
def read_results(self, logfile):
results = obj()
if 'setup_info' in self and 'run_mode' in self.setup_info:
mode = self.setup_info.run_mode
else:
return
#end if
f = logfile
if mode == 'scf':
f.seek('final total energy', 1)
t = f.readtokens()
results.energy = float(t[-2])
results.energy_units = t[-1]
elif mode == 'band':
None
else:
self.warn(
'Results not read.\nUnrecognized run mode: {}'.format(mode))
#end if
self.results = results
def pseudize(self,**valency):
errors = False
for ion,valence_charge in valency.iteritems():
if ion in self.particles:
ionp = self.particles[ion]
if isinstance(ionp,Ion):
self.particles[ion] = ionp.pseudize(valence_charge)
else:
self.error(ion+' cannot be pseudized',exit=False)
#end if
else:
self.error(ion+' is not in the physical system',exit=False)
errors = True
#end if
#end for
if errors:
self.error('system cannot be generated')
#end if
self.valency = obj(**valency)
self.update()
def get_result(self,result_name,sim):
result = obj()
analyzer = self.load_analyzer_image()
if result_name=='jastrow' or result_name=='wavefunction':
if not 'results' in analyzer or not 'optimization' in analyzer.results:
self.error('analyzer did not compute results required to determine jastrow')
#end if
opt_file = analyzer.results.optimization.optimal_file
opt_file = str(opt_file)
result.opt_file = os.path.join(self.locdir,opt_file)
elif result_name=='cuspcorr':
result.spo_up_cusps = os.path.join(self.locdir,self.identifier+'.spo-up.cuspInfo.xml')
result.spo_dn_cusps = os.path.join(self.locdir,self.identifier+'.spo-dn.cuspInfo.xml')
result.updet_cusps = os.path.join(self.locdir,'updet.cuspInfo.xml')
result.dndet_cusps = os.path.join(self.locdir,'downdet.cuspInfo.xml')
else:
self.error('ability to get result '+result_name+' has not been implemented')
#end if
del analyzer
return result
def set_dev_instruction(cls,
situation='writing a derived class',
class_variables=None,
class_functions=None,
member_variables=None,
member_functions=None):
if class_variables is None:
class_variables = []
if class_functions is None:
class_functions = []
if member_variables is None:
member_variables = []
if member_functions is None:
member_functions = []
ins = obj()
cls.dev_instructions_data[situation] = ins
ins.class_variables = class_variables
ins.class_functions = class_functions
ins.member_variables = member_variables
ins.member_functions = member_functions
def read_states(self):
log = self.log
log.seek('state #')
nstates = 0
elem_ind = set()
elem = []
while True:
line = log.readline()
tokens = line.replace('(', ' ').replace(')', ' ').split()
if not (len(tokens) > 0 and tokens[0] == 'state'):
break
#end if
ei, e = tokens[4], tokens[5]
if ei not in elem_ind:
elem.append(e)
elem_ind.add(ei)
#end if
nstates += 1
#end while
self.states = obj(nstates=nstates, elem=elem)
class QAobject(Pobj):
_global = obj()
_global.dynamic_methods_objects = []
plotter = Plotter()
opt_methods = set(['opt', 'linear', 'cslinear'])
def __init__(self):
return
#end def __init__
@staticmethod
def condense_name(name):
return name.strip().lower().replace(' ', '_').replace('-',
'_').replace(
'__', '_')
#end def condense_name
def _register_dynamic_methods(self):
QAobject._global.dynamic_methods_objects.append(self)
return
#end def _register_dynamic_methods
def _unlink_dynamic_methods(self):
for o in QAobject._global.dynamic_methods_objects:
o._unset_dynamic_methods()
#end for
return
#end def _unlink_dynamic_methods
def _relink_dynamic_methods(self):
for o in QAobject._global.dynamic_methods_objects:
o._reset_dynamic_methods()
#end for
return
def get_result(self, result_name, sim):
result = obj()
inputpp = self.input.inputpp
prefix = 'pwscf'
outdir = './'
if 'prefix' in inputpp:
prefix = inputpp.prefix
#end if
if 'outdir' in inputpp:
outdir = inputpp.outdir
#end if
if outdir.startswith('./'):
outdir = outdir[2:]
#end if
if result_name == '':
None
else:
self.error('ability to get result ' + result_name +
' has not been implemented')
#end if
return result
def md_statistics(self, equil=None, autocorr=None):
import numpy as np
from numerics import simstats, simplestats
mds = obj()
for q, v in self.md_data.items():
if equil is not None:
v = v[equil:]
#end if
if autocorr is None:
mean, var, error, kappa = simstats(v)
else:
nv = len(v)
nb = int(np.floor(float(nv) / autocorr))
nexclude = nv - nb * autocorr
v = v[nexclude:]
v.shape = nb, autocorr
mean, error = simplestats(v.mean(axis=1))
#end if
mds[q] = mean, error
#end for
return mds