Source code for wrappers

"""Module with functions that call the four main :py:mod:`driver`
functions: :py:mod:`driver.energy`, :py:mod:`driver.optimize`,
:py:mod:`driver.response`, and :py:mod:`driver.frequency`.

"""
import PsiMod
import re
import os
import math
import warnings
import pickle
import copy
import physconst
from driver import *
from molutil import *
from text import *
from collections import defaultdict
from procutil import *
# never import aliases into this file


# Function to make calls among wrappers(), energy(), optimize(), etc.
[docs]def call_function_in_1st_argument(funcarg, **largs): r"""Function to make primary function call to energy(), opt(), etc. with options dictionary *largs*. Useful when *funcarg* to call is stored in variable. """ return funcarg(**largs)
[docs]def convert(p, symbol): if symbol[p] == 'H': d = 1.001 if symbol[p] == 'He': d = 1.012 if symbol[p] == 'Li': d = 0.825 if symbol[p] == 'Be': d = 1.408 if symbol[p] == 'B': d = 1.485 if symbol[p] == 'C': d = 1.452 if symbol[p] == 'N': d = 1.397 if symbol[p] == 'O': d = 1.342 if symbol[p] == 'F': d = 1.287 if symbol[p] == 'Ne': d = 1.243 if symbol[p] == 'Na': d = 1.144 if symbol[p] == 'Mg': d = 1.364 if symbol[p] == 'Al': d = 1.639 if symbol[p] == 'Si': d = 1.716 if symbol[p] == 'P': d = 1.705 if symbol[p] == 'S': d = 1.683 if symbol[p] == 'Cl': d = 1.639 if symbol[p] == 'Ar': d = 1.595 return d / 1.5 #Automatically detect fragments and build a new molecule for fragment #needing methods (SAPT0, etc...)
[docs]def auto_fragments(name, **kwargs): r""" Detects fragments if the user does not supply them. Currently only used for the WebMO implementation of SAPT usage: auto_fragments('') """ if 'molecule' in kwargs: activate(kwargs['molecule']) del kwargs['molecule'] molecule = PsiMod.get_active_molecule() molecule.update_geometry() geom = molecule.save_string_xyz() numatoms = molecule.natom() VdW = [1.2, 1.7, 1.5, 1.55, 1.52, 1.9, 1.85, 1.8] symbol = range(numatoms) X = [0.0] * numatoms Y = [0.0] * numatoms Z = [0.0] * numatoms Queue = [] White = [] Black = [] F = geom.split('\n') for f in range(0, numatoms): A = F[f+1].split() symbol[f] = A[0] X[f] = float(A[1]) Y[f] = float(A[2]) Z[f] = float(A[3]) White.append(f) Fragment = [[] for i in range(numatoms)] # stores fragments start = 0 # starts with the first atom in the list Queue.append(start) White.remove(start) frag = 0 while((len(White) > 0) or (len(Queue) > 0)): # Iterates to the next fragment while(len(Queue) > 0): # BFS within a fragment for u in Queue: # find all nearest Neighbors # (still coloured white) to vertex u for i in White: Distance = math.sqrt((X[i] - X[u]) * (X[i] - X[u]) + (Y[i] - Y[u]) * (Y[i] - Y[u]) + (Z[i] - Z[u]) * (Z[i] - Z[u])) if Distance < convert(u,symbol) + convert(i,symbol): Queue.append(i) # if you find you, put it in the que White.remove(i) # and remove it from the untouched list Queue.remove(u) # remove focus from Queue Black.append(u) Fragment[frag].append(int(u + 1)) # add to group (adding 1 to start # list at one instead of zero) if(len(White) != 0): # cant move White->Queue if no more exist Queue.append(White[0]) White.remove(White[0]) frag += 1 new_geom = """\n0 1\n""" for i in Fragment[0]: new_geom = new_geom + F[i].lstrip() + """\n""" new_geom = new_geom + """--\n0 1\n""" for j in Fragment[1]: new_geom = new_geom + F[j].lstrip() + """\n""" new_geom = new_geom + """units angstrom\n""" new_mol = geometry(new_geom) new_mol.print_out() PsiMod.print_out("Exiting auto_fragments\n") ####################### ## Start of n_body ## #######################
[docs]def n_body(name, **kwargs): lowername = name.lower() kwargs = kwargs_lower(kwargs) # Wrap any positional arguments into kwargs (for intercalls among wrappers) if not('name' in kwargs) and name: kwargs['name'] = name.lower() # Establish function to call if not('n_body_func' in kwargs): if ('func' in kwargs): kwargs['n_body_func'] = kwargs['func'] del kwargs['func'] else: kwargs['n_body_func'] = energy func = kwargs['n_body_func'] if not func: raise ValidationError('Function \'%s\' does not exist to be called by wrapper n_body.' % (func.__name__)) if (func is db): raise ValidationError('Wrapper n_body is unhappy to be calling function \'%s\'.' % (func.__name__)) # Make sure the molecule the user provided is the active one if 'molecule' in kwargs: activate(kwargs['molecule']) del kwargs['molecule'] molecule = PsiMod.get_active_molecule() molecule.update_geometry() PsiMod.set_global_option("BASIS", PsiMod.get_global_option("BASIS")) # N-body run configuration bsse = 'on' if 'bsse' in kwargs: bsse = kwargs['bsse'] max_n_body = molecule.nfragments() if 'max_n_body' in kwargs: max_n_body = kwargs['max_n_body'] do_total = False if 'do_total' in kwargs: do_total = kwargs['do_total'] external = None external_indices = [] if 'external' in kwargs: external = kwargs['external'] external_indices = [molecule.nfragments()] if 'external_monomers' in kwargs: external_indices = kwargs['external_monomers'] # Check input args if not bsse == 'off' and not bsse == 'on' and not bsse == 'both': raise ValidationError('n_body: bsse argument is one of on, off, or both') if max_n_body < 1: raise ValidationError('n_body: max_n_body must be at least 1') if max_n_body > molecule.nfragments(): raise ValidationError('n_body: max_n_body must be <= to the number of fragments in the molecule') # Set to save RI integrals for repeated full-basis computations ri_ints_io = PsiMod.get_global_option('DF_INTS_IO') # inquire if above at all applies to dfmp2 or just scf PsiMod.set_global_option('DF_INTS_IO', 'SAVE') psioh = PsiMod.IOManager.shared_object() psioh.set_specific_retention(97, True) # Tell 'em what you're gonna tell 'em has_external = 'No' if (external): has_external = 'Yes' PsiMod.print_out('\n') PsiMod.print_out(' ==> N-Body Interaction Energy Analysis <==\n\n') PsiMod.print_out(' BSSE Treatment: %s\n' % (bsse)) PsiMod.print_out(' Maximum N-Body Interactions: %d\n' % (max_n_body)) PsiMod.print_out(' Compute Total Energy: %s\n' % (do_total)) PsiMod.print_out(' External Field: %s\n' % (has_external)) if (external): PsiMod.print_out(' External Field Monomers: ') for k in external_indices: PsiMod.print_out('%-3d ' % (k)) PsiMod.print_out('\n') PsiMod.print_out('\n') # Run the total molecule, if required energies_full = {} energies_mon = {} N = molecule.nfragments() Etotal = 0.0 if do_total or max_n_body == molecule.nfragments(): PsiMod.print_out(' => Total Cluster Energy <=\n') # Full cluster always gets the external field if (external): PsiMod.set_global_option_python("EXTERN", external) Etotal = call_function_in_1st_argument(func, **kwargs) if (external): PsiMod.set_global_option_python("EXTERN", None) energies_full[N] = [] energies_full[N].append(Etotal) energies_mon[N] = [] energies_mon[N].append(Etotal) PsiMod.set_global_option('DF_INTS_IO', 'LOAD') PsiMod.clean() max_effective = max_n_body if (max_effective == N): max_effective = N - 1 # Build the combos for indexing purposes Ns = [] if (max_n_body == N or do_total): Ns.append(N) for n in range(max_effective, 0, -1): Ns.append(n) combos = {} for n in Ns: combos[n] = [] # Loop through combinations in lexical order # # initialize the reals list reals = [] #setup first combination [3,2,1] lexical ordering #fragments indexing is 1's based, bloody hell for index in range(n, 0, -1): reals.append(index) #start loop through lexical promotion counter = 0 while True: counter = counter + 1 # Append the current combo combos[n].append(copy.deepcopy(reals)) #reset rank rank = 0 #look for lexical promotion opportunity #i.e.: [4 2 1] has a promotion opportunity at # index 1 to produce [4 3 1] for k in range(n - 2, -1, -1): if (reals[k] != reals[k + 1] + 1): rank = k + 1 break #do the promotion reals[rank] = reals[rank] + 1 #demote the right portion of the register val = 1 for k in range(n - 1, rank, -1): reals[k] = val val = val + 1 #boundary condition is promotion into #[nfrag+1 nfrag-1 ...] if (reals[0] > N): break # Hack for external externNone = PsiMod.ExternalPotential() # Run the clusters in the full basis if bsse == 'on' or bsse == 'both': for n in range(max_effective, 0, -1): energies_full[n] = [] clusters = extract_clusters(molecule, True, n) for k in range(len(clusters)): activate(clusters[k]) # Do the external field for this cluster or not? if (external): do_extern = False for mon in combos[n][k]: if (mon in external_indices): do_extern = True break if do_extern: PsiMod.set_global_option_python("EXTERN", external) PsiMod.print_out('\n => Cluster (N-Body %4d, Combination %4d) Energy (Full Basis) <=\n' % (n, k + 1)) energies_full[n].append(call_function_in_1st_argument(func, **kwargs)) # Turn the external field off if (external): PsiMod.set_global_option_python("EXTERN", externNone) PsiMod.set_global_option('DF_INTS_IO', 'LOAD') PsiMod.clean() # Run the clusters in the minimal cluster bases PsiMod.set_global_option('DF_INTS_IO', 'NONE') if bsse == 'off' or bsse == 'both': for n in range(max_effective, 0, -1): energies_mon[n] = [] clusters = extract_clusters(molecule, False, n) for k in range(len(clusters)): activate(clusters[k]) # Do the external field for this cluster or not? if (external): do_extern = False for mon in combos[n][k]: if (mon in external_indices): do_extern = True break if do_extern: PsiMod.set_global_option_python("EXTERN", external) PsiMod.print_out('\n => Cluster (N-Body %4d, Combination %4d) Energy (Cluster Basis) <=\n' % (n, k + 1)) energies_mon[n].append(call_function_in_1st_argument(func, **kwargs)) # Turn the external field off if (external): PsiMod.set_global_option_python("EXTERN", externNone) PsiMod.clean() # Report the energies PsiMod.print_out('\n ==> N-Body Interaction Energy Analysis: Combination Definitions <==\n\n') PsiMod.print_out(' %6s %6s | %-24s\n' % ("N-Body", "Combo", "Monomers")) for n in Ns: for k in range(len(combos[n])): PsiMod.print_out(' %6d %6d | ' % (n, k + 1)) for l in combos[n][k]: PsiMod.print_out('%-3d ' % (l)) PsiMod.print_out('\n') PsiMod.print_out('\n') PsiMod.print_out(' ==> N-Body Interaction Energy Analysis: Total Energies <==\n\n') if bsse == 'on' or bsse == 'both': PsiMod.print_out(' => Full Basis Set Results <=\n\n') PsiMod.print_out(' %6s %6s %24s %24s\n' % ("N-Body", "Combo", "E [H]", "E [kcal mol^-1]")) for n in Ns: for k in range(len(energies_full[n])): PsiMod.print_out(' %6d %6d %24.16E %24.16E\n' % (n, k + 1, energies_full[n][k], physconst.psi_hartree2kcalmol * energies_full[n][k])) PsiMod.print_out('\n') if bsse == 'off' or bsse == 'both': PsiMod.print_out(' => Cluster Basis Set Results <=\n\n') PsiMod.print_out(' %6s %6s %24s %24s\n' % ("N-Body", "Combo", "E [H]", "E [kcal mol^-1]")) for n in Ns: for k in range(len(energies_mon[n])): PsiMod.print_out(' %6d %6d %24.16E %24.16E\n' % (n, k + 1, energies_mon[n][k], physconst.psi_hartree2kcalmol * energies_mon[n][k])) PsiMod.print_out('\n') if bsse == 'both': PsiMod.print_out(' => BSSE Results <=\n\n') PsiMod.print_out(' %6s %6s %24s %24s\n' % ("N-Body", "Combo", "Delta E [H]", "Delta E [kcal mol^-1]")) for n in Ns: for k in range(len(energies_mon[n])): PsiMod.print_out(' %6d %6d %24.16E %24.16E\n' % (n, k + 1, energies_full[n][k] - energies_mon[n][k], physconst.psi_hartree2kcalmol * (energies_full[n][k] - energies_mon[n][k]))) PsiMod.print_out('\n') PsiMod.print_out(' ==> N-Body Interaction Energy Analysis: N-Body Energies <==\n\n') if bsse == 'on' or bsse == 'both': PsiMod.print_out(' => Full Basis Set Results <=\n\n') PsiMod.print_out(' %6s %6s %24s %24s\n' % ("N-Body", "Combo", "E [H]", "E [kcal mol^-1]")) energies_n_full = {} for n in Ns: if n == 1: continue En = 0.0 for k in range(len(energies_full[n])): E = energies_full[n][k] for l in range(len(combos[n][k])): E -= energies_full[1][combos[n][k][l] - 1] PsiMod.print_out(' %6d %6d %24.16E %24.16E\n' % (n, k + 1, E, physconst.psi_hartree2kcalmol * E)) En += E energies_n_full[n] = En for n in Ns: if n == 1: continue nn = molecule.nfragments() - 2 kk = n - 2 energies_n_full[n] /= (math.factorial(nn) / (math.factorial(kk) * math.factorial(nn - kk))) PsiMod.print_out(' %6d %6s %24.16E %24.16E\n' % (n, 'Total', energies_n_full[n], physconst.psi_hartree2kcalmol * energies_n_full[n])) PsiMod.print_out('\n') if bsse == 'off' or bsse == 'both': PsiMod.print_out(' => Cluster Basis Set Results <=\n\n') PsiMod.print_out(' %6s %6s %24s %24s\n' % ("N-Body", "Combo", "E [H]", "E [kcal mol^-1]")) energies_n_mon = {} for n in Ns: if n == 1: continue En = 0.0 for k in range(len(energies_mon[n])): E = energies_mon[n][k] for l in range(len(combos[n][k])): E -= energies_mon[1][combos[n][k][l] - 1] PsiMod.print_out(' %6d %6d %24.16E %24.16E\n' % (n, k + 1, E, physconst.psi_hartree2kcalmol * E)) En += E energies_n_mon[n] = En for n in Ns: if n == 1: continue nn = molecule.nfragments() - 2 kk = n - 2 energies_n_mon[n] /= (math.factorial(nn) / (math.factorial(kk) * math.factorial(nn - kk))) PsiMod.print_out(' %6d %6s %24.16E %24.16E\n' % (n, 'Total', energies_n_mon[n], physconst.psi_hartree2kcalmol * energies_n_mon[n])) PsiMod.print_out('\n') if bsse == 'both': PsiMod.print_out(' => BSSE Results <=\n\n') PsiMod.print_out(' %6s %6s %24s %24s\n' % ("N-Body", "Combo", "Delta E [H]", "Delta E [kcal mol^-1]")) energies_n_bsse = {} for n in Ns: if n == 1: continue En = 0.0 for k in range(len(energies_mon[n])): E = energies_full[n][k] - energies_mon[n][k] for l in range(len(combos[n][k])): E -= energies_full[1][combos[n][k][l] - 1] E += energies_mon[1][combos[n][k][l] - 1] PsiMod.print_out(' %6d %6d %24.16E %24.16E\n' % (n, k + 1, E, physconst.psi_hartree2kcalmol * E)) En += E energies_n_bsse[n] = En for n in Ns: if n == 1: continue nn = molecule.nfragments() - 2 kk = n - 2 energies_n_bsse[n] /= (math.factorial(nn) / (math.factorial(kk) * math.factorial(nn - kk))) PsiMod.print_out(' %6d %6s %24.16E %24.16E\n' % (n, 'Total', energies_n_bsse[n], physconst.psi_hartree2kcalmol * energies_n_bsse[n])) PsiMod.print_out('\n') PsiMod.print_out(' ==> N-Body Interaction Energy Analysis: Non-Additivities <==\n\n') if bsse == 'on' or bsse == 'both': energies_n_full[1] = 0.0 PsiMod.print_out(' => Full Basis Set Results <=\n\n') PsiMod.print_out(' %6s %24s %24s\n' % ("N-Body", "E [H]", "E [kcal mol^-1]")) for k in range(len(Ns)): n = Ns[k] if n == 1: continue E = energies_n_full[Ns[k]] - energies_n_full[Ns[k + 1]] PsiMod.print_out(' %6s %24.16E %24.16E\n' % (n, E, physconst.psi_hartree2kcalmol * E)) PsiMod.print_out('\n') if bsse == 'off' or bsse == 'both': energies_n_mon[1] = 0.0 PsiMod.print_out(' => Cluster Basis Set Results <=\n\n') PsiMod.print_out(' %6s %24s %24s\n' % ("N-Body", "E [H]", "E [kcal mol^-1]")) for k in range(len(Ns)): n = Ns[k] if n == 1: continue E = energies_n_mon[Ns[k]] - energies_n_mon[Ns[k + 1]] PsiMod.print_out(' %6s %24.16E %24.16E\n' % (n, E, physconst.psi_hartree2kcalmol * E)) PsiMod.print_out('\n') if bsse == 'both': energies_n_bsse[1] = 0.0 PsiMod.print_out(' => BSSE Results <=\n\n') PsiMod.print_out(' %6s %24s %24s\n' % ("N-Body", "Delta E [H]", "Delta E [kcal mol^-1]")) for k in range(len(Ns)): n = Ns[k] if n == 1: continue E = energies_n_bsse[Ns[k]] - energies_n_bsse[Ns[k + 1]] PsiMod.print_out(' %6s %24.16E %24.16E\n' % (n, E, physconst.psi_hartree2kcalmol * E)) PsiMod.print_out('\n') # Put everything back the way it was PsiMod.set_global_option('DF_INTS_IO', ri_ints_io) psioh.set_specific_retention(97, False) PsiMod.clean() activate(molecule) if bsse == 'on' or bsse == 'both': return energies_n_full[Ns[0]] else: return energies_n_mon[Ns[0]] ## Aliases ##
nbody = n_body ##################### ## End of n_body ## ##################### ################### ## Start of cp ## ###################
[docs]def cp(name, **kwargs): r"""The cp function computes counterpoise-corrected two-body interaction energies for complexes composed of arbitrary numbers of monomers. :aliases: counterpoise_correct(), counterpoise_correction() :returns: (*float*) Counterpoise-corrected interaction energy in Hartrees. :PSI variables: .. hlist:: :columns: 1 * :psivar:`CP-CORRECTED 2-BODY INTERACTION ENERGY <CP-CORRECTED2-BODYINTERACTIONENERGY>` * :psivar:`UNCP-CORRECTED 2-BODY INTERACTION ENERGY <UNCP-CORRECTED2-BODYINTERACTIONENERGY>` .. caution:: Some features are not yet implemented. Buy a developer a coffee. - No values of func besides energy have been tested. - Table print-out needs improving. Add some PSI variables. :type name: string :param name: ``'scf'`` || ``'ccsd(t)'`` || etc. First argument, usually unlabeled. Indicates the computational method to be applied to the molecule. May be any valid argument to :py:func:`~driver.energy`; however, SAPT is not appropriate. :type func: :ref:`function <op_py_function>` :param func: |dl| ``energy`` |dr| || ``optimize`` || ``cbs`` Indicates the type of calculation to be performed on the molecule and each of its monomers. The default performs a single-point ``energy('name')``, while ``optimize`` perfoms a geometry optimization on each system, and ``cbs`` performs a compound single-point energy. If a nested series of python functions is intended (see :ref:`sec:intercalls`), use keyword ``cp_func`` instead of ``func``. :type check_bsse: :ref:`boolean <op_py_boolean>` :param check_bsse: ``'on'`` || |dl| ``'off'`` |dr| Indicates whether to additionally compute un-counterpoise corrected monomers and thus obtain an estimate for the basis set superposition error. :type molecule: :ref:`molecule <op_py_molecule>` :param molecule: ``h2o`` || etc. The target molecule, if not the last molecule defined. :examples: >>> # [1] counterpoise-corrected mp2 interaction energy >>> cp('df-mp2') """ lowername = name.lower() kwargs = kwargs_lower(kwargs) # Wrap any positional arguments into kwargs (for intercalls among wrappers) if not('name' in kwargs) and name: kwargs['name'] = name.lower() # Establish function to call if not('cp_func' in kwargs): if ('func' in kwargs): kwargs['cp_func'] = kwargs['func'] del kwargs['func'] else: kwargs['cp_func'] = energy func = kwargs['cp_func'] if not func: raise ValidationError('Function \'%s\' does not exist to be called by wrapper counterpoise_correct.' % (func.__name__)) if (func is db): raise ValidationError('Wrapper counterpoise_correct is unhappy to be calling function \'%s\'.' % (func.__name__)) if 'check_bsse' in kwargs and yes.match(str(kwargs['check_bsse'])): check_bsse = True else: check_bsse = False # Make sure the molecule the user provided is the active one if 'molecule' in kwargs: activate(kwargs['molecule']) del kwargs['molecule'] molecule = PsiMod.get_active_molecule() molecule.update_geometry() PsiMod.set_global_option("BASIS", PsiMod.get_global_option("BASIS")) df_ints_io = PsiMod.get_global_option('DF_INTS_IO') # inquire if above at all applies to dfmp2 or just scf PsiMod.set_global_option('DF_INTS_IO', 'SAVE') psioh = PsiMod.IOManager.shared_object() psioh.set_specific_retention(97, True) activate(molecule) molecule.update_geometry() PsiMod.print_out("\n") banner("CP Computation: Complex.\nFull Basis Set.") PsiMod.print_out("\n") e_dimer = call_function_in_1st_argument(func, **kwargs) #e_dimer = energy(name, **kwargs) PsiMod.clean() PsiMod.set_global_option('DF_INTS_IO', 'LOAD') # All monomers with ghosts monomers = extract_clusters(molecule, True, 1) e_monomer_full = [] cluster_n = 0 for cluster in monomers: activate(cluster) PsiMod.print_out("\n") banner(("CP Computation: Monomer %d.\n Full Basis Set." % (cluster_n + 1))) PsiMod.print_out("\n") e_monomer_full.append(call_function_in_1st_argument(func, **kwargs)) #e_monomer_full.append(energy(name,**kwargs)) cluster_n = cluster_n + 1 PsiMod.clean() PsiMod.set_global_option('DF_INTS_IO', 'NONE') if (check_bsse): # All monomers without ghosts monomers = extract_clusters(molecule, False, 1) e_monomer_bsse = [] cluster_n = 0 for cluster in monomers: activate(cluster) PsiMod.print_out("\n") #cluster.print_to_output() banner(("CP Computation: Monomer %d.\n Monomer Set." % (cluster_n + 1))) PsiMod.print_out("\n") e_monomer_bsse.append(call_function_in_1st_argument(func, **kwargs)) #e_monomer_bsse.append(energy(name,**kwargs)) cluster_n = cluster_n + 1 PsiMod.set_global_option('DF_INTS_IO', df_ints_io) psioh.set_specific_retention(97, False) activate(molecule) if (check_bsse == False): cp_table = Table(rows=["System:"], cols=["Energy (full):"]) cp_table["Complex"] = [e_dimer] for cluster_n in range(0, len(monomers)): key = "Monomer %d" % (cluster_n + 1) cp_table[key] = [e_monomer_full[cluster_n]] e_full = e_dimer for cluster_n in range(0, len(monomers)): e_full = e_full - e_monomer_full[cluster_n] cp_table["Interaction"] = [e_full] PsiMod.set_variable('CP-CORRECTED 2-BODY INTERACTION ENERGY', e_full) else: cp_table = Table(rows=["System:"], cols=["Energy (full):", "Energy (monomer):", "BSSE:"]) cp_table["Complex"] = [e_dimer, 0.0, 0.0] for cluster_n in range(0, len(monomers)): key = "Monomer %d" % (cluster_n + 1) cp_table[key] = [e_monomer_full[cluster_n], e_monomer_bsse[cluster_n], \ e_monomer_full[cluster_n] - e_monomer_bsse[cluster_n]] e_full = e_dimer e_bsse = e_dimer for cluster_n in range(0, len(monomers)): e_full = e_full - e_monomer_full[cluster_n] e_bsse = e_bsse - e_monomer_bsse[cluster_n] cp_table["Totals:"] = [e_full, e_bsse, e_full - e_bsse] PsiMod.set_variable('UNCP-CORRECTED 2-BODY INTERACTION ENERGY', e_full) PsiMod.print_out("\n") banner("CP Computation: Results.") PsiMod.print_out("\n") banner("Hartree", 2) PsiMod.print_out("\n") PsiMod.print_out(str(cp_table)) PsiMod.print_out("\n") banner("kcal*mol^-1", 2) PsiMod.print_out("\n") cp_table.scale() PsiMod.print_out(str(cp_table)) return e_full ## Aliases ##
counterpoise_correct = cp counterpoise_correction = cp ################# ## End of cp ## ################# ######################### ## Start of Database ## ######################### DB_RGT = {} DB_RXN = {}
[docs]def database(name, db_name, **kwargs): r"""Function to access the molecule objects and reference energies of popular chemical databases. :aliases: db() :returns: (*float*) Mean absolute deviation of the database in kcal/mol :PSI variables: .. hlist:: :columns: 1 * :psivar:`db_name DATABASE MEAN SIGNED DEVIATION <db_nameDATABASEMEANSIGNEDDEVIATION>` * :psivar:`db_name DATABASE MEAN ABSOLUTE DEVIATION <db_nameDATABASEMEANABSOLUTEDEVIATION>` * :psivar:`db_name DATABASE ROOT-MEAN-SQUARE DEVIATION <db_nameDATABASEROOT-MEAN-SQUARESIGNEDDEVIATION>` * Python dictionaries of results accessible as ``DB_RGT`` and ``DB_RXN``. .. note:: It is very easy to make a database from a collection of xyz files using the script :source:`lib/scripts/ixyz2database.pl`. See :ref:`sec:createDatabase` for details. .. caution:: Some features are not yet implemented. Buy a developer some coffee. - In sow/reap mode, use only global options (e.g., the local option set by ``set scf scf_type df`` will not be respected). .. note:: To access a database that is not embedded in a |PSIfour| distribution, add the path to the directory containing the database to the environment variable :envvar:`PYTHONPATH`. :type name: string :param name: ``'scf'`` || ``'sapt0'`` || ``'ccsd(t)'`` || etc. First argument, usually unlabeled. Indicates the computational method to be applied to the database. May be any valid argument to :py:func:`~driver.energy`. :type db_name: string :param db_name: ``'BASIC'`` || ``'S22'`` || ``'HTBH'`` || etc. Second argument, usually unlabeled. Indicates the requested database name, matching (case insensitive) the name of a python file in ``psi4/lib/databases`` or :envvar:`PYTHONPATH`. Consult that directory for available databases and literature citations. :type func: :ref:`function <op_py_function>` :param func: |dl| ``energy`` |dr| || ``optimize`` || ``cbs`` Indicates the type of calculation to be performed on each database member. The default performs a single-point ``energy('name')``, while ``optimize`` perfoms a geometry optimization on each reagent, and ``cbs`` performs a compound single-point energy. If a nested series of python functions is intended (see :ref:`sec:intercalls`), use keyword ``db_func`` instead of ``func``. :type mode: string :param mode: |dl| ``'continuous'`` |dr| || ``'sow'`` || ``'reap'`` Indicates whether the calculations required to complete the database are to be run in one file (``'continuous'``) or are to be farmed out in an embarrassingly parallel fashion (``'sow'``/``'reap'``). For the latter, run an initial job with ``'sow'`` and follow instructions in its output file. :type cp: :ref:`boolean <op_py_boolean>` :param cp: ``'on'`` || |dl| ``'off'`` |dr| Indicates whether counterpoise correction is employed in computing interaction energies. Use this option and NOT the :py:func:`~wrappers.cp` function for BSSE correction in database(). Option available (See :ref:`sec:availableDatabases`) only for databases of bimolecular complexes. :type rlxd: :ref:`boolean <op_py_boolean>` :param rlxd: ``'on'`` || |dl| ``'off'`` |dr| Indicates whether correction for deformation energy is employed in computing interaction energies. Option available (See :ref:`sec:availableDatabases`) only for databases of bimolecular complexes with non-frozen monomers, e.g., HBC6. :type symm: :ref:`boolean <op_py_boolean>` :param symm: |dl| ``'on'`` |dr| || ``'off'`` Indicates whether the native symmetry of the database reagents is employed (``'on'``) or whether it is forced to :math:`C_1` symmetry (``'off'``). Some computational methods (e.g., SAPT) require no symmetry, and this will be set by database(). :type zpe: :ref:`boolean <op_py_boolean>` :param zpe: ``'on'`` || |dl| ``'off'`` |dr| Indicates whether zero-point-energy corrections are appended to single-point energy values. Option valid only for certain thermochemical databases. Disabled until Hessians ready. :type benchmark: string :param benchmark: |dl| ``'default'`` |dr| || ``'S22A'`` || etc. Indicates whether a non-default set of reference energies, if available (See :ref:`sec:availableDatabases`), are employed for the calculation of error statistics. :type tabulate: array of strings :param tabulate: |dl| ``[]`` |dr| || ``['scf total energy', 'natom']`` || etc. Indicates whether to form tables of variables other than the primary requested energy. Available for any PSI variable. :type subset: string or array of strings :param subset: Indicates a subset of the full database to run. This is a very flexible option and can be used in three distinct ways, outlined below. Note that two take a string and the last takes an array. See `Available Databases`_ for available values. * ``'small'`` || ``'large'`` || ``'equilibrium'`` Calls predefined subsets of the requested database, either ``'small'``, a few of the smallest database members, ``'large'``, the largest of the database members, or ``'equilibrium'``, the equilibrium geometries for a database composed of dissociation curves. * ``'BzBz_S'`` || ``'FaOOFaON'`` || ``'ArNe'`` || ``'HB'`` || etc. For databases composed of dissociation curves, or otherwise divided into subsets, individual curves and subsets can be called by name. Consult the database python files for available molecular systems (case insensitive). * ``[1,2,5]`` || ``['1','2','5']`` || ``['BzMe-3.5', 'MeMe-5.0']`` || etc. Specify a list of database members to run. Consult the database python files for available molecular systems. This is the only portion of database input that is case sensitive; choices for this keyword must match the database python file. :examples: >>> # [1] Two-stage SCF calculation on short, equilibrium, and long helium dimer >>> db('scf','RGC10',cast_up='sto-3g',subset=['HeHe-0.85','HeHe-1.0','HeHe-1.5'], tabulate=['scf total energy','natom']) >>> # [2] Counterpoise-corrected interaction energies for three complexes in S22 >>> # Error statistics computed wrt an old benchmark, S22A >>> database('df-mp2','S22',cp=1,subset=[16,17,8],benchmark='S22A') >>> # [3] SAPT0 on the neon dimer dissociation curve >>> db('sapt0',subset='NeNe',cp=0,symm=0,db_name='RGC10') >>> # [4] Optimize system 1 in database S22, producing tables of scf and mp2 energy >>> db('mp2','S22',db_func=optimize,subset=[1], tabulate=['mp2 total energy','current energy']) >>> # [5] CCSD on the smallest systems of HTBH, a hydrogen-transfer database >>> database('ccsd','HTBH',subset='small', tabulate=['ccsd total energy', 'mp2 total energy']) """ lowername = name.lower() kwargs = kwargs_lower(kwargs) # Wrap any positional arguments into kwargs (for intercalls among wrappers) if not('name' in kwargs) and name: kwargs['name'] = name.lower() if not('db_name' in kwargs) and db_name: kwargs['db_name'] = db_name # Establish function to call if not('db_func' in kwargs): if ('func' in kwargs): kwargs['db_func'] = kwargs['func'] del kwargs['func'] else: kwargs['db_func'] = energy func = kwargs['db_func'] if not func: raise ValidationError('Function \'%s\' does not exist to be called by wrapper database.' % (func.__name__)) if (func is cp): raise ValidationError('Wrapper database is unhappy to be calling function \'%s\'. Use the cp keyword within database instead.' % (func.__name__)) # Define path and load module for requested database sys.path.append('%sdatabases' % (PsiMod.Process.environment["PSIDATADIR"])) sys.path.append('%s/lib/databases' % PsiMod.psi_top_srcdir()) database = import_ignorecase(db_name) if database is None: PsiMod.print_out('\nPython module for database %s failed to load\n\n' % (db_name)) PsiMod.print_out('\nSearch path that was tried:\n') PsiMod.print_out(", ".join(map(str, sys.path))) raise ValidationError("Python module loading problem for database " + str(db_name)) else: dbse = database.dbse HRXN = database.HRXN ACTV = database.ACTV RXNM = database.RXNM BIND = database.BIND TAGL = database.TAGL GEOS = database.GEOS try: DATA = database.DATA except AttributeError: DATA = {} # Must collect (here) and set (below) basis sets after every new molecule activation user_basis = PsiMod.get_global_option('BASIS') user_df_basis_scf = PsiMod.get_global_option('DF_BASIS_SCF') user_df_basis_mp2 = PsiMod.get_global_option('DF_BASIS_MP2') user_df_basis_sapt = PsiMod.get_global_option('DF_BASIS_SAPT') user_df_basis_elst = PsiMod.get_global_option('DF_BASIS_ELST') user_writer_file_label = PsiMod.get_global_option('WRITER_FILE_LABEL') b_user_reference = PsiMod.has_global_option_changed('REFERENCE') user_reference = PsiMod.get_global_option('REFERENCE') user_memory = PsiMod.get_memory() user_molecule = PsiMod.get_active_molecule() # Configuration based upon e_name & db_name options # Force non-supramolecular if needed if re.match(r'^sapt', lowername): try: database.ACTV_SA except AttributeError: raise ValidationError('Database %s not suitable for non-supramolecular calculation.' % (db_name)) else: ACTV = database.ACTV_SA # Force open-shell if needed openshell_override = 0 if (user_reference == 'RHF') or (user_reference == 'RKS'): try: database.isOS except AttributeError: pass else: if yes.match(str(database.isOS)): openshell_override = 1 PsiMod.print_out('\nSome reagents in database %s require an open-shell reference; will be reset to UHF/UKS as needed.\n' % (db_name)) # Configuration based upon database keyword options # Option symmetry- whether symmetry treated normally or turned off (currently req'd for dfmp2 & dft) db_symm = 'yes' if 'symm' in kwargs: db_symm = kwargs['symm'] symmetry_override = 0 if no.match(str(db_symm)): symmetry_override = 1 elif yes.match(str(db_symm)): pass else: raise ValidationError('Symmetry mode \'%s\' not valid.' % (db_symm)) # Option mode of operation- whether db run in one job or files farmed out if not('db_mode' in kwargs): if ('mode' in kwargs): kwargs['db_mode'] = kwargs['mode'] del kwargs['mode'] else: kwargs['db_mode'] = 'continuous' db_mode = kwargs['db_mode'] if (db_mode.lower() == 'continuous'): pass elif (db_mode.lower() == 'sow'): pass elif (db_mode.lower() == 'reap'): if 'linkage' in kwargs: db_linkage = kwargs['linkage'] else: raise ValidationError('Database execution mode \'reap\' requires a linkage option.') else: raise ValidationError('Database execution mode \'%s\' not valid.' % (db_mode)) # Option counterpoise- whether for interaction energy databases run in bsse-corrected or not db_cp = 'no' if 'cp' in kwargs: db_cp = kwargs['cp'] if yes.match(str(db_cp)): try: database.ACTV_CP except AttributeError: raise ValidationError('Counterpoise correction mode \'yes\' invalid for database %s.' % (db_name)) else: ACTV = database.ACTV_CP elif no.match(str(db_cp)): pass else: raise ValidationError('Counterpoise correction mode \'%s\' not valid.' % (db_cp)) # Option relaxed- whether for non-frozen-monomer interaction energy databases include deformation correction or not? db_rlxd = 'no' if 'rlxd' in kwargs: db_rlxd = kwargs['rlxd'] if yes.match(str(db_rlxd)): if yes.match(str(db_cp)): try: database.ACTV_CPRLX database.RXNM_CPRLX except AttributeError: raise ValidationError('Deformation and counterpoise correction mode \'yes\' invalid for database %s.' % (db_name)) else: ACTV = database.ACTV_CPRLX RXNM = database.RXNM_CPRLX elif no.match(str(db_cp)): try: database.ACTV_RLX except AttributeError: raise ValidationError('Deformation correction mode \'yes\' invalid for database %s.' % (db_name)) else: ACTV = database.ACTV_RLX elif no.match(str(db_rlxd)): pass else: raise ValidationError('Deformation correction mode \'%s\' not valid.' % (db_rlxd)) # Option zero-point-correction- whether for thermochem databases jobs are corrected by zpe db_zpe = 'no' if 'zpe' in kwargs: db_zpe = kwargs['zpe'] if yes.match(str(db_zpe)): raise ValidationError('Zero-point-correction mode \'yes\' not yet implemented.') elif no.match(str(db_zpe)): pass else: raise ValidationError('Zero-point-correction \'mode\' %s not valid.' % (db_zpe)) # Option benchmark- whether error statistics computed wrt alternate reference energies db_benchmark = 'default' if 'benchmark' in kwargs: db_benchmark = kwargs['benchmark'] if (db_benchmark.lower() == 'default'): pass else: BIND = getattr_ignorecase(database, 'BIND_' + db_benchmark) if BIND is None: raise ValidationError('Special benchmark \'%s\' not available for database %s.' % (db_benchmark, db_name)) # Option tabulate- whether tables of variables other than primary energy method are formed db_tabulate = [] if 'tabulate' in kwargs: db_tabulate = kwargs['tabulate'] # Option subset- whether all of the database or just a portion is run db_subset = HRXN if 'subset' in kwargs: db_subset = kwargs['subset'] if isinstance(db_subset, basestring): if (db_subset.lower() == 'small'): try: database.HRXN_SM except AttributeError: raise ValidationError('Special subset \'small\' not available for database %s.' % (db_name)) else: HRXN = database.HRXN_SM elif (db_subset.lower() == 'large'): try: database.HRXN_LG except AttributeError: raise ValidationError('Special subset \'large\' not available for database %s.' % (db_name)) else: HRXN = database.HRXN_LG elif (db_subset.lower() == 'equilibrium'): try: database.HRXN_EQ except AttributeError: raise ValidationError('Special subset \'equilibrium\' not available for database %s.' % (db_name)) else: HRXN = database.HRXN_EQ else: HRXN = getattr_ignorecase(database, db_subset) if HRXN is None: HRXN = getattr_ignorecase(database, 'HRXN_' + db_subset) if HRXN is None: raise ValidationError('Special subset \'%s\' not available for database %s.' % (db_subset, db_name)) else: temp = [] for rxn in db_subset: if rxn in HRXN: temp.append(rxn) else: raise ValidationError('Subset element \'%s\' not a member of database %s.' % (str(rxn), db_name)) HRXN = temp temp = [] for rxn in HRXN: temp.append(ACTV['%s-%s' % (dbse, rxn)]) HSYS = drop_duplicates(sum(temp, [])) # Sow all the necessary reagent computations PsiMod.print_out("\n\n") banner(("Database %s Computation" % (db_name))) PsiMod.print_out("\n") # write index of calcs to output file if (db_mode.lower() == 'continuous'): instructions = """\n The database single-job procedure has been selected through mode='continuous'.\n""" instructions += """ Calculations for the reagents will proceed in the order below and will be followed\n""" instructions += """ by summary results for the database.\n\n""" for rgt in HSYS: instructions += """ %-s\n""" % (rgt) instructions += """\n Alternatively, a farming-out of the database calculations may be accessed through\n""" instructions += """ the database wrapper option mode='sow'/'reap'.\n\n""" PsiMod.print_out(instructions) # write sow/reap instructions and index of calcs to output file and reap input file if (db_mode.lower() == 'sow'): instructions = """\n The database sow/reap procedure has been selected through mode='sow'. In addition\n""" instructions += """ to this output file (which contains no quantum chemical calculations), this job\n""" instructions += """ has produced a number of input files (%s-*.in) for individual database members\n""" % (dbse) instructions += """ and a single input file (%s-master.in) with a database(mode='reap') command.\n""" % (dbse) instructions += """ The former may look very peculiar since processed and pickled python rather than\n""" instructions += """ raw input is written. Follow the instructions below to continue.\n\n""" instructions += """ (1) Run all of the %s-*.in input files on any variety of computer architecture.\n""" % (dbse) instructions += """ The output file names must be as given below.\n\n""" for rgt in HSYS: instructions += """ psi4 -i %-27s -o %-27s\n""" % (rgt + '.in', rgt + '.out') instructions += """\n (2) Gather all the resulting output files in a directory. Place input file\n""" instructions += """ %s-master.in into that directory and run it. The job will be trivial in\n""" % (dbse) instructions += """ length and give summary results for the database in its output file.\n\n""" instructions += """ psi4 -i %-27s -o %-27s\n\n""" % (dbse + '-master.in', dbse + '-master.out') instructions += """ Alternatively, a single-job execution of the database may be accessed through\n""" instructions += """ the database wrapper option mode='continuous'.\n\n""" PsiMod.print_out(instructions) fmaster = open('%s-master.in' % (dbse), 'w') fmaster.write('# This is a psi4 input file auto-generated from the database() wrapper.\n\n') fmaster.write("database('%s', '%s', mode='reap', cp='%s', rlxd='%s', zpe='%s', benchmark='%s', linkage=%d, subset=%s, tabulate=%s)\n\n" % (name, db_name, db_cp, db_rlxd, db_zpe, db_benchmark, os.getpid(), HRXN, db_tabulate)) fmaster.close() # Loop through chemical systems ERGT = {} ERXN = {} VRGT = {} VRXN = {} for rgt in HSYS: VRGT[rgt] = {} # extra definition of molecule so that logic in building commands string has something to act on exec(format_molecule_for_input(GEOS[rgt])) molecule = PsiMod.get_active_molecule() # build string of title banner banners = '' banners += """PsiMod.print_out('\\n')\n""" banners += """banner(' Database %s Computation: Reagent %s \\n %s')\n""" % (db_name, rgt, TAGL[rgt]) banners += """PsiMod.print_out('\\n')\n\n""" # build string of lines that defines contribution of rgt to each rxn actives = '' actives += """PsiMod.print_out(' Database Contributions Map:\\n %s\\n')\n""" % ('-' * 75) for rxn in HRXN: db_rxn = dbse + '-' + str(rxn) if rgt in ACTV[db_rxn]: actives += """PsiMod.print_out(' reagent %s contributes by %.4f to reaction %s\\n')\n""" \ % (rgt, RXNM[db_rxn][rgt], db_rxn) actives += """PsiMod.print_out('\\n')\n\n""" # build string of commands for options from the input file TODO: handle local options too commands = '' commands += """\nPsiMod.set_memory(%s)\n\n""" % (user_memory) for chgdopt in PsiMod.get_global_option_list(): if PsiMod.has_global_option_changed(chgdopt): chgdoptval = PsiMod.get_global_option(chgdopt) #chgdoptval = PsiMod.get_option(chgdopt) if isinstance(chgdoptval, basestring): commands += """PsiMod.set_global_option('%s', '%s')\n""" % (chgdopt, chgdoptval) elif isinstance(chgdoptval, int) or isinstance(chgdoptval, float): commands += """PsiMod.set_global_option('%s', %s)\n""" % (chgdopt, chgdoptval) else: raise ValidationError('Option \'%s\' is not of a type (string, int, float, bool) that can be processed by database wrapper.' % (chgdopt)) # build string of molecule and commands that are dependent on the database commands += '\n' commands += """PsiMod.set_global_option('BASIS', '%s')\n""" % (user_basis) if not((user_df_basis_scf == "") or (user_df_basis_scf == 'NONE')): commands += """PsiMod.set_global_option('DF_BASIS_SCF', '%s')\n""" % (user_df_basis_scf) if not((user_df_basis_mp2 == "") or (user_df_basis_mp2 == 'NONE')): commands += """PsiMod.set_global_option('DF_BASIS_MP2', '%s')\n""" % (user_df_basis_mp2) if not((user_df_basis_sapt == "") or (user_df_basis_sapt == 'NONE')): commands += """PsiMod.set_global_option('DF_BASIS_SAPT', '%s')\n""" % (user_df_basis_sapt) if not((user_df_basis_elst == "") or (user_df_basis_elst == 'NONE')): commands += """PsiMod.set_global_option('DF_BASIS_ELST', '%s')\n""" % (user_df_basis_elst) commands += """molecule = PsiMod.get_active_molecule()\n""" commands += """molecule.update_geometry()\n""" if symmetry_override: commands += """molecule.reset_point_group('c1')\n""" commands += """molecule.fix_orientation(1)\n""" commands += """molecule.update_geometry()\n""" if (openshell_override) and (molecule.multiplicity() != 1): if user_reference == 'RHF': commands += """PsiMod.set_global_option('REFERENCE', 'UHF')\n""" elif user_reference == 'RKS': commands += """PsiMod.set_global_option('REFERENCE', 'UKS')\n""" commands += """PsiMod.set_global_option('WRITER_FILE_LABEL', '%s')\n""" % \ (user_writer_file_label + ('' if user_writer_file_label == '' else '-') + rgt) # all modes need to step through the reagents but all for different purposes # continuous: defines necessary commands, executes energy(method) call, and collects results into dictionary # sow: opens individual reagent input file, writes the necessary commands, and writes energy(method) call # reap: opens individual reagent output file, collects results into a dictionary if (db_mode.lower() == 'continuous'): exec(banners) exec(format_molecule_for_input(GEOS[rgt])) exec(commands) #print 'MOLECULE LIVES %23s %8s %4d %4d %4s' % (rgt, PsiMod.get_global_option('REFERENCE'), # molecule.molecular_charge(), molecule.multiplicity(), molecule.schoenflies_symbol()) PsiMod.set_variable('NATOM', molecule.natom()) PsiMod.set_variable('NUCLEAR REPULSION ENERGY', molecule.nuclear_repulsion_energy()) if re.match(r'^verify', lowername): compare_values(DATA['NUCLEAR REPULSION ENERGY'][rgt], PsiMod.get_variable('NUCLEAR REPULSION ENERGY'), 4, '%s %.4f' % (rgt, PsiMod.get_variable('NUCLEAR REPULSION ENERGY'))) ERGT[rgt] = 7.0 else: ERGT[rgt] = call_function_in_1st_argument(func, **kwargs) #print ERGT[rgt] PsiMod.print_variables() exec(actives) for envv in db_tabulate: VRGT[rgt][envv.upper()] = PsiMod.get_variable(envv) PsiMod.set_global_option("REFERENCE", user_reference) PsiMod.clean() elif (db_mode.lower() == 'sow'): freagent = open('%s.in' % (rgt), 'w') freagent.write('# This is a psi4 input file auto-generated from the database() wrapper.\n\n') freagent.write(banners) freagent.write(format_molecule_for_input(GEOS[rgt])) freagent.write(commands) freagent.write('''\npickle_kw = ("""''') pickle.dump(kwargs, freagent) freagent.write('''""")\n''') freagent.write("""\nkwargs = pickle.loads(pickle_kw)\n""") freagent.write("""electronic_energy = %s(**kwargs)\n\n""" % (func.__name__)) freagent.write("""PsiMod.print_variables()\n""") freagent.write("""PsiMod.print_out('\\nDATABASE RESULT: computation %d for reagent %s """ % (os.getpid(), rgt)) freagent.write("""yields electronic energy %20.12f\\n' % (electronic_energy))\n\n""") freagent.write("""PsiMod.set_variable('NATOM', molecule.natom())\n""") for envv in db_tabulate: freagent.write("""PsiMod.print_out('DATABASE RESULT: computation %d for reagent %s """ % (os.getpid(), rgt)) freagent.write("""yields variable value %20.12f for variable %s\\n' % (PsiMod.get_variable(""") freagent.write("""'%s'), '%s'))\n""" % (envv.upper(), envv.upper())) freagent.close() elif (db_mode.lower() == 'reap'): ERGT[rgt] = 0.0 for envv in db_tabulate: VRGT[rgt][envv.upper()] = 0.0 exec(banners) exec(actives) try: freagent = open('%s.out' % (rgt), 'r') except IOError: PsiMod.print_out('Warning: Output file \'%s.out\' not found.\n' % (rgt)) PsiMod.print_out(' Database summary will have 0.0 and **** in its place.\n') else: while 1: line = freagent.readline() if not line: if ERGT[rgt] == 0.0: PsiMod.print_out('Warning: Output file \'%s.out\' has no DATABASE RESULT line.\n' % (rgt)) PsiMod.print_out(' Database summary will have 0.0 and **** in its place.\n') break s = line.split() if (len(s) != 0) and (s[0:3] == ['DATABASE', 'RESULT:', 'computation']): if int(s[3]) != db_linkage: raise ValidationError('Output file \'%s.out\' has linkage %s incompatible with master.in linkage %s.' % (rgt, str(s[3]), str(db_linkage))) if s[6] != rgt: raise ValidationError('Output file \'%s.out\' has nominal affiliation %s incompatible with reagent %s.' % (rgt, s[6], rgt)) if (s[8:10] == ['electronic', 'energy']): ERGT[rgt] = float(s[10]) PsiMod.print_out('DATABASE RESULT: electronic energy = %20.12f\n' % (ERGT[rgt])) elif (s[8:10] == ['variable', 'value']): for envv in db_tabulate: envv = envv.upper() if (s[13:] == envv.split()): VRGT[rgt][envv] = float(s[10]) PsiMod.print_out('DATABASE RESULT: variable %s value = %20.12f\n' % (envv, VRGT[rgt][envv])) freagent.close() # end sow after writing files if (db_mode.lower() == 'sow'): return 0.0 # Reap all the necessary reaction computations PsiMod.print_out("\n") banner(("Database %s Results" % (db_name))) PsiMod.print_out("\n") maxactv = [] for rxn in HRXN: maxactv.append(len(ACTV[dbse + '-' + str(rxn)])) maxrgt = max(maxactv) table_delimit = '-' * (54 + 20 * maxrgt) tables = '' # find any reactions that are incomplete FAIL = defaultdict(int) for rxn in HRXN: db_rxn = dbse + '-' + str(rxn) for i in range(len(ACTV[db_rxn])): if abs(ERGT[ACTV[db_rxn][i]]) < 1.0e-12: FAIL[rxn] = 1 # tabulate requested process::environment variables tables += """ For each VARIABLE requested by tabulate, a 'Reaction Value' will be formed from\n""" tables += """ 'Reagent' values according to weightings 'Wt', as for the REQUESTED ENERGY below.\n""" tables += """ Depending on the nature of the variable, this may or may not make any physical sense.\n""" for rxn in HRXN: db_rxn = dbse + '-' + str(rxn) VRXN[db_rxn] = {} for envv in db_tabulate: envv = envv.upper() tables += """\n ==> %s <==\n\n""" % (envv.title()) tables += tblhead(maxrgt, table_delimit, 2) for rxn in HRXN: db_rxn = dbse + '-' + str(rxn) if FAIL[rxn]: tables += """\n%23s %8s %8s %8s""" % (db_rxn, '', '****', '') for i in range(len(ACTV[db_rxn])): tables += """ %16.8f %2.0f""" % (VRGT[ACTV[db_rxn][i]][envv], RXNM[db_rxn][ACTV[db_rxn][i]]) else: VRXN[db_rxn][envv] = 0.0 for i in range(len(ACTV[db_rxn])): VRXN[db_rxn][envv] += VRGT[ACTV[db_rxn][i]][envv] * RXNM[db_rxn][ACTV[db_rxn][i]] tables += """\n%23s %16.8f """ % (db_rxn, VRXN[db_rxn][envv]) for i in range(len(ACTV[db_rxn])): tables += """ %16.8f %2.0f""" % (VRGT[ACTV[db_rxn][i]][envv], RXNM[db_rxn][ACTV[db_rxn][i]]) tables += """\n %s\n""" % (table_delimit) # tabulate primary requested energy variable with statistics count_rxn = 0 minDerror = 100000.0 maxDerror = 0.0 MSDerror = 0.0 MADerror = 0.0 RMSDerror = 0.0 tables += """\n ==> %s <==\n\n""" % ('Requested Energy') tables += tblhead(maxrgt, table_delimit, 1) for rxn in HRXN: db_rxn = dbse + '-' + str(rxn) if FAIL[rxn]: tables += """\n%23s %8.4f %8s %8s""" % (db_rxn, BIND[db_rxn], '****', '****') for i in range(len(ACTV[db_rxn])): tables += """ %16.8f %2.0f""" % (ERGT[ACTV[db_rxn][i]], RXNM[db_rxn][ACTV[db_rxn][i]]) else: ERXN[db_rxn] = 0.0 for i in range(len(ACTV[db_rxn])): ERXN[db_rxn] += ERGT[ACTV[db_rxn][i]] * RXNM[db_rxn][ACTV[db_rxn][i]] error = physconst.psi_hartree2kcalmol * ERXN[db_rxn] - BIND[db_rxn] tables += """\n%23s %8.4f %8.4f %8.4f""" % (db_rxn, BIND[db_rxn], physconst.psi_hartree2kcalmol * ERXN[db_rxn], error) for i in range(len(ACTV[db_rxn])): tables += """ %16.8f %2.0f""" % (ERGT[ACTV[db_rxn][i]], RXNM[db_rxn][ACTV[db_rxn][i]]) if abs(error) < abs(minDerror): minDerror = error if abs(error) > abs(maxDerror): maxDerror = error MSDerror += error MADerror += abs(error) RMSDerror += error * error count_rxn += 1 tables += """\n %s\n""" % (table_delimit) if count_rxn: MSDerror /= float(count_rxn) MADerror /= float(count_rxn) RMSDerror = math.sqrt(RMSDerror / float(count_rxn)) tables += """%23s %19s %8.4f\n""" % ('Minimal Dev', '', minDerror) tables += """%23s %19s %8.4f\n""" % ('Maximal Dev', '', maxDerror) tables += """%23s %19s %8.4f\n""" % ('Mean Signed Dev', '', MSDerror) tables += """%23s %19s %8.4f\n""" % ('Mean Absolute Dev', '', MADerror) tables += """%23s %19s %8.4f\n""" % ('RMS Dev', '', RMSDerror) tables += """ %s\n""" % (table_delimit) PsiMod.set_variable('%s DATABASE MEAN SIGNED DEVIATION' % (db_name), MSDerror) PsiMod.set_variable('%s DATABASE MEAN ABSOLUTE DEVIATION' % (db_name), MADerror) PsiMod.set_variable('%s DATABASE ROOT-MEAN-SQUARE DEVIATION' % (db_name), RMSDerror) #print tables PsiMod.print_out(tables) finalenergy = MADerror else: finalenergy = 0.0 # restore molecule and options activate(user_molecule) user_molecule.update_geometry() PsiMod.set_global_option("BASIS", user_basis) PsiMod.set_global_option("REFERENCE", user_reference) if not b_user_reference: PsiMod.revoke_global_option_changed('REFERENCE') PsiMod.set_global_option('WRITER_FILE_LABEL', user_writer_file_label) DB_RGT.clear() DB_RGT.update(VRGT) DB_RXN.clear() DB_RXN.update(VRXN) return finalenergy
[docs]def tblhead(tbl_maxrgt, tbl_delimit, ttype): r"""Function that prints the header for the changable-width results tables in db(). *tbl_maxrgt* is the number of reagent columns the table must plan for. *tbl_delimit* is a string of dashes of the correct length to set off the table. *ttype* is 1 for tables comparing the computed values to the reference or 2 for simple tabulation and sum of the computed values. """ tbl_str = '' tbl_str += """ %s""" % (tbl_delimit) if ttype == 1: tbl_str += """\n%23s %19s %8s""" % ('Reaction', 'Reaction Energy', 'Error') elif ttype == 2: tbl_str += """\n%23s %19s %6s""" % ('Reaction', 'Reaction Value', '') for i in range(tbl_maxrgt): tbl_str += """%20s""" % ('Reagent ' + str(i + 1)) if ttype == 1: tbl_str += """\n%23s %8s %8s %8s""" % ('', 'Ref', 'Calc', '[kcal/mol]') elif ttype == 2: tbl_str += """\n%54s""" % ('') for i in range(tbl_maxrgt): if ttype == 1: tbl_str += """%20s""" % ('[H] Wt') elif ttype == 2: tbl_str += """%20s""" % ('Value Wt') tbl_str += """\n %s""" % (tbl_delimit) return tbl_str ## Aliases ##
db = database ####################### ## End of Database ## ####################### ################################### ## Start of Complete Basis Set ## ###################################
[docs]def complete_basis_set(name, **kwargs): r"""Function to define a multistage energy method from combinations of basis set extrapolations and delta corrections and condense the components into a minimum number of calculations. :aliases: cbs() :returns: (*float*) -- Total electronic energy in Hartrees :PSI variables: .. hlist:: :columns: 1 * :psivar:`CBS TOTAL ENERGY <CBSTOTALENERGY>` * :psivar:`CBS REFERENCE ENERGY <CBSREFERENCEENERGY>` * :psivar:`CBS CORRELATION ENERGY <CBSCORRELATIONENERGY>` * :psivar:`CURRENT ENERGY <CURRENTENERGY>` * :psivar:`CURRENT REFERENCE ENERGY <CURRENTREFERENCEENERGY>` * :psivar:`CURRENT CORRELATION ENERGY <CURRENTCORRELATIONENERGY>` .. caution:: Some features are not yet implemented. Buy a developer a coffee. - Not all methods hooked in through PSI variables, configuration interaction and arbitrary order MP in particular. - No scheme defaults for given basis zeta number, so scheme must be specified explicitly. - No way to tell function to boost fitting basis size for all calculations. - No way to extrapolate def2 family basis sets - Need to add more extrapolation schemes As represented in the equation below, a CBS energy method is defined in four sequential stages (scf, corl, delta, delta2) covering treatment of the reference total energy, the correlation energy, a delta correction to the correlation energy, and a second delta correction. Each is activated by its stage_wfn keyword and is only allowed if all preceding stages are active. .. include:: cbs_eqn.rst * Energy Methods The presence of a stage_wfn keyword is the indicator to incorporate (and check for stage_basis and stage_scheme keywords) and compute that stage in defining the CBS energy. The cbs() function requires, at a minimum, ``name='scf'`` and ``scf_basis`` keywords to be specified for reference-step only jobs and ``name`` and ``corl_basis`` keywords for correlated jobs. The following energy methods have been set up for cbs(). .. hlist:: :columns: 5 * scf * mp2 * mp2.5 * mp3 * mp4(sdq) * mp4 * omp2 * omp3 * ocepa * cepa0 * cepa(0) * cepa(1) * cepa(3) * acpf * aqcc * qcisd * cc2 * ccsd * fno-df-ccsd * bccd * cc3 * qcisd(t) * ccsd(t) * fno-df-ccsd(t) * bccd(t) * cisd * cisdt * cisdtq * ci\ *n* * fci :type name: string :param name: ``'scf'`` || ``'ccsd'`` || etc. First argument, usually unlabeled. Indicates the computational method for the correlation energy, unless only reference step to be performed, in which case should be ``'scf'``. Overruled if stage_wfn keywords supplied. :type corl_wfn: string :param corl_wfn: ``'mp2'`` || ``'ccsd(t)'`` || etc. Indicates the energy method for which the correlation energy is to be obtained. Can also be specified with ``name`` or as the unlabeled first argument to the function. :type delta_wfn: string :param delta_wfn: ``'ccsd'`` || ``'ccsd(t)'`` || etc. Indicates the (superior) energy method for which a delta correction to the correlation energy is to be obtained. :type delta_wfn_lesser: string :param delta_wfn_lesser: |dl| ``'mp2'`` |dr| || ``'ccsd'`` || etc. Indicates the inferior energy method for which a delta correction to the correlation energy is to be obtained. :type delta2_wfn: string :param delta2_wfn: ``'ccsd'`` || ``'ccsd(t)'`` || etc. Indicates the (superior) energy method for which a second delta correction to the correlation energy is to be obtained. :type delta2_wfn_lesser: string :param delta2_wfn_lesser: |dl| ``'mp2'`` |dr| || ``'ccsd(t)'`` || etc. Indicates the inferior energy method for which a second delta correction to the correlation energy is to be obtained. * Basis Sets Currently, the basis set set through ``set`` commands have no influence on a cbs calculation. :type scf_basis: :ref:`basis string <apdx:basisElement>` :param scf_basis: |dl| ``corl_basis`` |dr| || ``'cc-pV[TQ]Z'`` || ``'jun-cc-pv[tq5]z'`` || ``'6-31G*'`` || etc. Indicates the sequence of basis sets employed for the reference energy. If any correlation method is specified, ``scf_basis`` can default to ``corl_basis``. :type corl_basis: :ref:`basis string <apdx:basisElement>` :param corl_basis: ``'cc-pV[TQ]Z'`` || ``'jun-cc-pv[tq5]z'`` || ``'6-31G*'`` || etc. Indicates the sequence of basis sets employed for the correlation energy. :type delta_basis: :ref:`basis string <apdx:basisElement>` :param delta_basis: ``'cc-pV[TQ]Z'`` || ``'jun-cc-pv[tq5]z'`` || ``'6-31G*'`` || etc. Indicates the sequence of basis sets employed for the delta correction to the correlation energy. :type delta2_basis: :ref:`basis string <apdx:basisElement>` :param delta2_basis: ``'cc-pV[TQ]Z'`` || ``'jun-cc-pv[tq5]z'`` || ``'6-31G*'`` || etc. Indicates the sequence of basis sets employed for the second delta correction to the correlation energy. * Schemes Transformations of the energy through basis set extrapolation for each stage of the CBS definition. A complaint is generated if number of basis sets in stage_basis does not exactly satisfy requirements of stage_scheme. An exception is the default, ``'highest_1'``, which uses the best basis set available. See `Extrapolation Schemes`_ for all available schemes. :type scf_scheme: function :param scf_scheme: |dl| ``highest_1`` |dr| || ``scf_xtpl_helgaker_3`` || etc. Indicates the basis set extrapolation scheme to be applied to the reference energy. :type corl_scheme: function :param corl_scheme: |dl| ``highest_1`` |dr| || ``corl_xtpl_helgaker_2`` || etc. Indicates the basis set extrapolation scheme to be applied to the correlation energy. :type delta_scheme: function :param delta_scheme: |dl| ``highest_1`` |dr| || ``corl_xtpl_helgaker_2`` || etc. Indicates the basis set extrapolation scheme to be applied to the delta correction to the correlation energy. :type delta2_scheme: function :param delta2_scheme: |dl| ``highest_1`` |dr| || ``corl_xtpl_helgaker_2`` || etc. Indicates the basis set extrapolation scheme to be applied to the second delta correction to the correlation energy. :type molecule: :ref:`molecule <op_py_molecule>` :param molecule: ``h2o`` || etc. The target molecule, if not the last molecule defined. :examples: >>> # [1] replicates with cbs() the simple model chemistry scf/cc-pVDZ: set basis cc-pVDZ energy('scf') >>> cbs('scf', scf_basis='cc-pVDZ') >>> # [2] replicates with cbs() the simple model chemistry mp2/jun-cc-pVDZ: set basis jun-cc-pVDZ energy('mp2') >>> cbs('mp2', corl_basis='jun-cc-pVDZ') >>> # [3] DTQ-zeta extrapolated scf reference energy >>> cbs('scf', scf_basis='cc-pV[DTQ]Z', scf_scheme=scf_xtpl_helgaker_3) >>> # [4] DT-zeta extrapolated mp2 correlation energy atop a T-zeta reference >>> cbs('mp2', corl_basis='cc-pv[dt]z', corl_scheme=corl_xtpl_helgaker_2) >>> # [5] a DT-zeta extrapolated coupled-cluster correction atop a TQ-zeta extrapolated mp2 correlation energy atop a Q-zeta reference >>> cbs('mp2', corl_basis='aug-cc-pv[tq]z', corl_scheme=corl_xtpl_helgaker_2, delta_wfn='ccsd(t)', delta_basis='aug-cc-pv[dt]z', delta_scheme=corl_xtpl_helgaker_2) >>> # [6] a D-zeta ccsd(t) correction atop a DT-zeta extrapolated ccsd cluster correction atop a TQ-zeta extrapolated mp2 correlation energy atop a Q-zeta reference >>> cbs('mp2', corl_basis='aug-cc-pv[tq]z', corl_scheme=corl_xtpl_helgaker_2, delta_wfn='ccsd', delta_basis='aug-cc-pv[dt]z', delta_scheme=corl_xtpl_helgaker_2, delta2_wfn='ccsd(t)', delta2_wfn_lesser='ccsd', delta2_basis='aug-cc-pvdz') >>> # [7] cbs() coupled with database() >>> database('mp2', 'BASIC', subset=['h2o','nh3'], symm='on', func=cbs, corl_basis='cc-pV[tq]z', corl_scheme=corl_xtpl_helgaker_2, delta_wfn='ccsd(t)', delta_basis='sto-3g') """ lowername = name.lower() kwargs = kwargs_lower(kwargs) # Wrap any positional arguments into kwargs (for intercalls among wrappers) if not('name' in kwargs) and name: kwargs['name'] = name.lower() # Establish function to call (only energy makes sense for cbs) if not('cbs_func' in kwargs): if ('func' in kwargs): kwargs['cbs_func'] = kwargs['func'] del kwargs['func'] else: kwargs['cbs_func'] = energy func = kwargs['cbs_func'] if not func: raise ValidationError('Function \'%s\' does not exist to be called by wrapper complete_basis_set.' % (func.__name__)) if not(func is energy): raise ValidationError('Wrapper complete_basis_set is unhappy to be calling function \'%s\' instead of \'energy\'.' % (func.__name__)) # Define some quantum chemical knowledge, namely what methods are subsumed in others VARH = {} VARH['scf'] = { 'scftot': 'SCF TOTAL ENERGY'} VARH['mp2'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY'} VARH['mp2.5'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'mp2.5corl': 'MP2.5 CORRELATION ENERGY', 'mp3corl': 'MP3 CORRELATION ENERGY'} VARH['mp3'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'mp2.5corl': 'MP2.5 CORRELATION ENERGY', 'mp3corl': 'MP3 CORRELATION ENERGY'} VARH['mp4(sdq)'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'mp2.5corl': 'MP2.5 CORRELATION ENERGY', 'mp3corl': 'MP3 CORRELATION ENERGY', 'mp4(sdq)corl': 'MP4(SDQ) CORRELATION ENERGY'} VARH['mp4'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'mp2.5corl': 'MP2.5 CORRELATION ENERGY', 'mp3corl': 'MP3 CORRELATION ENERGY', 'mp4(sdq)corl': 'MP4(SDQ) CORRELATION ENERGY', 'mp4corl': 'MP4(SDTQ) CORRELATION ENERGY'} VARH['omp2'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'omp2corl': 'OMP2 CORRELATION ENERGY'} VARH['omp3'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'mp3corl': 'MP3 CORRELATION ENERGY', 'omp3corl': 'OMP3 CORRELATION ENERGY'} VARH['ocepa'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'ocepacorl': 'OCEPA(0) CORRELATION ENERGY'} VARH['cepa0'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'cepa0corl': 'CEPA(0) CORRELATION ENERGY'} VARH['cepa(0)'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'cepa(0)corl': 'CEPA(0) CORRELATION ENERGY'} VARH['cepa(1)'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'cepa(1)corl': 'CEPA(1) CORRELATION ENERGY'} VARH['cepa(3)'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'cepa(3)corl': 'CEPA(3) CORRELATION ENERGY'} VARH['acpf'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'acpfcorl': 'ACPF CORRELATION ENERGY'} VARH['aqcc'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'aqcccorl': 'AQCC CORRELATION ENERGY'} VARH['qcisd'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'mp2.5corl': 'MP2.5 CORRELATION ENERGY', 'mp3corl': 'MP3 CORRELATION ENERGY', 'mp4(sdq)corl': 'MP4(SDQ) CORRELATION ENERGY', 'qcisdcorl': 'QCISD CORRELATION ENERGY'} VARH['cc2'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'cc2corl': 'CC2 CORRELATION ENERGY'} VARH['ccsd'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'ccsdcorl': 'CCSD CORRELATION ENERGY'} VARH['bccd'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'bccdcorl': 'CCSD CORRELATION ENERGY'} VARH['cc3'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'cc3corl': 'CC3 CORRELATION ENERGY'} VARH['fno-df-ccsd'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'fno-df-ccsdcorl': 'CCSD CORRELATION ENERGY'} VARH['fno-df-ccsd(t)'] = {'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'ccsdcorl': 'CCSD CORRELATION ENERGY', 'fno-df-ccsd(t)corl': 'CCSD(T) CORRELATION ENERGY'} VARH['qcisd(t)'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'mp2.5corl': 'MP2.5 CORRELATION ENERGY', 'mp3corl': 'MP3 CORRELATION ENERGY', 'mp4(sdq)corl': 'MP4(SDQ) CORRELATION ENERGY', 'qcisdcorl': 'QCISD CORRELATION ENERGY', 'qcisd(t)corl': 'QCISD(T) CORRELATION ENERGY'} VARH['ccsd(t)'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'ccsdcorl': 'CCSD CORRELATION ENERGY', 'ccsd(t)corl': 'CCSD(T) CORRELATION ENERGY'} VARH['bccd(t)'] = { 'scftot': 'SCF TOTAL ENERGY', 'mp2corl': 'MP2 CORRELATION ENERGY', 'ccsdcorl': 'CCSD CORRELATION ENERGY', 'bccd(t)corl': 'CCSD(T) CORRELATION ENERGY'} VARH['cisd'] = { 'scftot': 'SCF TOTAL ENERGY', 'cisdcorl': 'CISD CORRELATION ENERGY'} VARH['cisdt'] = { 'scftot': 'SCF TOTAL ENERGY', 'cisdtcorl': 'CISDT CORRELATION ENERGY'} VARH['cisdtq'] = { 'scftot': 'SCF TOTAL ENERGY', 'cisdtqcorl': 'CISDTQ CORRELATION ENERGY'} VARH['fci'] = { 'scftot': 'SCF TOTAL ENERGY', 'fcicorl': 'FCI CORRELATION ENERGY'} for cilevel in range(2, 99): VARH['ci%s' % (str(cilevel))] = { 'scftot': 'SCF TOTAL ENERGY', 'ci%scorl' % (str(cilevel)): 'CI CORRELATION ENERGY'} finalenergy = 0.0 do_scf = 1 do_corl = 0 do_delta = 0 do_delta2 = 0 # Must collect (here) and set (below) basis sets after every new molecule activation b_user_basis = PsiMod.has_global_option_changed('BASIS') user_basis = PsiMod.get_global_option('BASIS') #user_df_basis_scf = PsiMod.get_option('DF_BASIS_SCF') #user_df_basis_mp2 = PsiMod.get_option('DF_BASIS_MP2') #user_df_basis_cc = PsiMod.get_option('DF_BASIS_CC') #user_df_basis_sapt = PsiMod.get_option('DF_BASIS_SAPT') #user_df_basis_elst = PsiMod.get_option('DF_BASIS_ELST') b_user_wfn = PsiMod.has_global_option_changed('WFN') user_wfn = PsiMod.get_global_option('WFN') user_writer_file_label = PsiMod.get_global_option('WRITER_FILE_LABEL') # Make sure the molecule the user provided is the active one if 'molecule' in kwargs: activate(kwargs['molecule']) del kwargs['molecule'] molecule = PsiMod.get_active_molecule() molecule.update_geometry() PsiMod.set_global_option("BASIS", PsiMod.get_global_option("BASIS")) # Establish method for correlation energy if 'name' in kwargs: if (lowername == 'scf') or (lowername == 'df-scf'): pass else: do_corl = 1 cbs_corl_wfn = kwargs['name'].lower() if 'corl_wfn' in kwargs: do_corl = 1 cbs_corl_wfn = kwargs['corl_wfn'].lower() if do_corl: if not (cbs_corl_wfn in VARH.keys()): raise ValidationError('Requested CORL method \'%s\' is not recognized. Add it to VARH in wrapper.py to proceed.' % (cbs_corl_wfn)) # Establish method for delta correction energy if 'delta_wfn' in kwargs: do_delta = 1 cbs_delta_wfn = kwargs['delta_wfn'].lower() if not (cbs_delta_wfn in VARH.keys()): raise ValidationError('Requested DELTA method \'%s\' is not recognized. Add it to VARH in wrapper.py to proceed.' % (cbs_delta_wfn)) if 'delta_wfn_lesser' in kwargs: cbs_delta_wfn_lesser = kwargs['delta_wfn_lesser'].lower() else: cbs_delta_wfn_lesser = 'mp2' if not (cbs_delta_wfn_lesser in VARH.keys()): raise ValidationError('Requested DELTA method lesser \'%s\' is not recognized. Add it to VARH in wrapper.py to proceed.' % (cbs_delta_wfn_lesser)) # Establish method for second delta correction energy if 'delta2_wfn' in kwargs: do_delta2 = 1 cbs_delta2_wfn = kwargs['delta2_wfn'].lower() if not (cbs_delta2_wfn in VARH.keys()): raise ValidationError('Requested DELTA2 method \'%s\' is not recognized. Add it to VARH in wrapper.py to proceed.' % (cbs_delta2_wfn)) if 'delta2_wfn_lesser' in kwargs: cbs_delta2_wfn_lesser = kwargs['delta2_wfn_lesser'].lower() else: cbs_delta2_wfn_lesser = 'mp2' if not (cbs_delta2_wfn_lesser in VARH.keys()): raise ValidationError('Requested DELTA2 method lesser \'%s\' is not recognized. Add it to VARH in wrapper.py to proceed.' % (cbs_delta2_wfn_lesser)) # Check that user isn't skipping steps in scf + corl + delta + delta2 sequence if do_scf and not do_corl and not do_delta and not do_delta2: pass elif do_scf and do_corl and not do_delta and not do_delta2: pass elif do_scf and do_corl and do_delta and not do_delta2: pass elif do_scf and do_corl and do_delta and do_delta2: pass else: raise ValidationError('Requested scf (%s) + corl (%s) + delta (%s) + delta2 (%s) not valid. These steps are cummulative.' % (do_scf, do_corl, do_delta, do_delta2)) # Establish list of valid basis sets for correlation energy if do_corl: if 'corl_basis' in kwargs: BSTC, ZETC = validate_bracketed_basis(kwargs['corl_basis'].lower()) else: raise ValidationError('CORL basis sets through keyword \'%s\' are required.' % ('corl_basis')) # Establish list of valid basis sets for scf energy if 'scf_basis' in kwargs: BSTR, ZETR = validate_bracketed_basis(kwargs['scf_basis'].lower()) else: if do_corl: BSTR = BSTC[:] ZETR = ZETC[:] else: raise ValidationError('SCF basis sets through keyword \'%s\' are required. Or perhaps you forgot the \'%s\'.' % ('scf_basis', 'corl_wfn')) # Establish list of valid basis sets for delta correction energy if do_delta: if 'delta_basis' in kwargs: BSTD, ZETD = validate_bracketed_basis(kwargs['delta_basis'].lower()) else: raise ValidationError('DELTA basis sets through keyword \'%s\' are required.' % ('delta_basis')) # Establish list of valid basis sets for second delta correction energy if do_delta2: if 'delta2_basis' in kwargs: BSTD2, ZETD2 = validate_bracketed_basis(kwargs['delta2_basis'].lower()) else: raise ValidationError('DELTA2 basis sets through keyword \'%s\' are required.' % ('delta2_basis')) # Establish treatment for scf energy (validity check useless since python will catch it long before here) cbs_scf_scheme = highest_1 if 'scf_scheme' in kwargs: cbs_scf_scheme = kwargs['scf_scheme'] # Establish treatment for correlation energy cbs_corl_scheme = highest_1 if 'corl_scheme' in kwargs: cbs_corl_scheme = kwargs['corl_scheme'] # Establish treatment for delta correction energy cbs_delta_scheme = highest_1 if 'delta_scheme' in kwargs: cbs_delta_scheme = kwargs['delta_scheme'] # Establish treatment for delta2 correction energy cbs_delta2_scheme = highest_1 if 'delta2_scheme' in kwargs: cbs_delta2_scheme = kwargs['delta2_scheme'] # Build string of title banner cbsbanners = '' cbsbanners += """PsiMod.print_out('\\n')\n""" cbsbanners += """banner(' CBS Setup ')\n""" cbsbanners += """PsiMod.print_out('\\n')\n\n""" exec(cbsbanners) # Call schemes for each portion of total energy to 'place orders' for calculations needed d_fields = ['d_stage', 'd_scheme', 'd_basis', 'd_wfn', 'd_need', 'd_coef', 'd_energy'] f_fields = ['f_wfn', 'f_portion', 'f_basis', 'f_zeta', 'f_energy'] GRAND_NEED = [] MODELCHEM = [] bstring = '' if do_scf: NEED = call_function_in_1st_argument(cbs_scf_scheme, mode='requisition', basisname=BSTR, basiszeta=ZETR, wfnname='scf') GRAND_NEED.append(dict(zip(d_fields, ['scf', cbs_scf_scheme, reconstitute_bracketed_basis(NEED), 'scf', NEED, +1, 0.0]))) if do_corl: NEED = call_function_in_1st_argument(cbs_corl_scheme, mode='requisition', basisname=BSTC, basiszeta=ZETC, wfnname=cbs_corl_wfn) GRAND_NEED.append(dict(zip(d_fields, ['corl', cbs_corl_scheme, reconstitute_bracketed_basis(NEED), cbs_corl_wfn, NEED, +1, 0.0]))) if do_delta: NEED = call_function_in_1st_argument(cbs_delta_scheme, mode='requisition', basisname=BSTD, basiszeta=ZETD, wfnname=cbs_delta_wfn) GRAND_NEED.append(dict(zip(d_fields, ['delta', cbs_delta_scheme, reconstitute_bracketed_basis(NEED), cbs_delta_wfn, NEED, +1, 0.0]))) NEED = call_function_in_1st_argument(cbs_delta_scheme, mode='requisition', basisname=BSTD, basiszeta=ZETD, wfnname=cbs_delta_wfn_lesser) GRAND_NEED.append(dict(zip(d_fields, ['delta', cbs_delta_scheme, reconstitute_bracketed_basis(NEED), cbs_delta_wfn_lesser, NEED, -1, 0.0]))) if do_delta2: NEED = call_function_in_1st_argument(cbs_delta2_scheme, mode='requisition', basisname=BSTD2, basiszeta=ZETD2, wfnname=cbs_delta2_wfn) GRAND_NEED.append(dict(zip(d_fields, ['delta2', cbs_delta2_scheme, reconstitute_bracketed_basis(NEED), cbs_delta2_wfn, NEED, +1, 0.0]))) NEED = call_function_in_1st_argument(cbs_delta2_scheme, mode='requisition', basisname=BSTD2, basiszeta=ZETD2, wfnname=cbs_delta2_wfn_lesser) GRAND_NEED.append(dict(zip(d_fields, ['delta2', cbs_delta2_scheme, reconstitute_bracketed_basis(NEED), cbs_delta2_wfn_lesser, NEED, -1, 0.0]))) for stage in GRAND_NEED: for lvl in stage['d_need'].items(): MODELCHEM.append(lvl[1]) # Apply chemical reasoning to choose the minimum computations to run JOBS = MODELCHEM[:] instructions = '' instructions += """ Naive listing of computations required.\n""" for mc in JOBS: instructions += """ %12s / %-24s for %s\n""" % (mc['f_wfn'], mc['f_basis'], VARH[mc['f_wfn']][mc['f_wfn'] + mc['f_portion']]) # Remove duplicate modelchem portion listings for indx_mc, mc in enumerate(MODELCHEM): dups = -1 for indx_job, job in enumerate(JOBS): if (job['f_wfn'] == mc['f_wfn']) and (job['f_basis'] == mc['f_basis']): dups += 1 if (dups >= 1): del JOBS[indx_job] # Remove chemically subsumed modelchem portion listings for indx_mc, mc in enumerate(MODELCHEM): for menial in VARH[mc['f_wfn']]: for indx_job, job in enumerate(JOBS): if (menial == job['f_wfn'] + job['f_portion']) and (mc['f_basis'] == job['f_basis']) and not (mc['f_wfn'] == job['f_wfn']): del JOBS[indx_job] instructions += """\n Enlightened listing of computations required.\n""" for mc in JOBS: instructions += """ %12s / %-24s for %s\n""" % (mc['f_wfn'], mc['f_basis'], VARH[mc['f_wfn']][mc['f_wfn'] + mc['f_portion']]) # Expand listings to all that will be obtained JOBS_EXT = [] for indx_job, job in enumerate(JOBS): for menial in VARH[job['f_wfn']]: temp_wfn, temp_portion = split_menial(menial) JOBS_EXT.append(dict(zip(f_fields, [temp_wfn, temp_portion, job['f_basis'], job['f_zeta'], 0.0]))) #instructions += """\n Full listing of computations to be obtained (required and bonus).\n""" #for mc in JOBS_EXT: # instructions += """ %12s / %-24s for %s\n""" % (mc['f_wfn'], mc['f_basis'], VARH[mc['f_wfn']][mc['f_wfn']+mc['f_portion']]) PsiMod.print_out(instructions) psioh = PsiMod.IOManager.shared_object() psioh.set_specific_retention(PSIF_SCF_MOS, True) # Run necessary computations for mc in JOBS: kwargs['name'] = mc['f_wfn'] # Build string of title banner cbsbanners = '' cbsbanners += """PsiMod.print_out('\\n')\n""" cbsbanners += """banner(' CBS Computation: %s / %s ')\n""" % (mc['f_wfn'].upper(), mc['f_basis'].upper()) cbsbanners += """PsiMod.print_out('\\n')\n\n""" exec(cbsbanners) # Build string of molecule and commands that are dependent on the database commands = '\n' commands += """\nPsiMod.set_global_option('BASIS', '%s')\n""" % (mc['f_basis']) commands += """PsiMod.set_global_option('WRITER_FILE_LABEL', '%s')\n""" % \ (user_writer_file_label + ('' if user_writer_file_label == '' else '-') + mc['f_wfn'].lower() + '-' + mc['f_basis'].lower()) exec(commands) # Make energy() call mc['f_energy'] = call_function_in_1st_argument(func, **kwargs) # Fill in energies for subsumed methods for menial in VARH[mc['f_wfn']]: temp_wfn, temp_portion = split_menial(menial) for job in JOBS_EXT: if (temp_wfn == job['f_wfn']) and (temp_portion == job['f_portion']) and (mc['f_basis'] == job['f_basis']): job['f_energy'] = PsiMod.get_variable(VARH[temp_wfn][menial]) PsiMod.clean() psioh.set_specific_retention(PSIF_SCF_MOS, False) # Build string of title banner cbsbanners = '' cbsbanners += """PsiMod.print_out('\\n')\n""" cbsbanners += """banner(' CBS Results ')\n""" cbsbanners += """PsiMod.print_out('\\n')\n\n""" exec(cbsbanners) # Insert obtained energies into the array that stores the cbs stages for stage in GRAND_NEED: for lvl in stage['d_need'].items(): MODELCHEM.append(lvl[1]) for job in JOBS_EXT: if ((lvl[1]['f_wfn'] == job['f_wfn']) and (lvl[1]['f_portion'] == job['f_portion']) and (lvl[1]['f_basis'] == job['f_basis'])): lvl[1]['f_energy'] = job['f_energy'] for stage in GRAND_NEED: stage['d_energy'] = call_function_in_1st_argument(stage['d_scheme'], needname=stage['d_need'], mode='evaluate') finalenergy += stage['d_energy'] * stage['d_coef'] # Build string of results table table_delimit = ' ' + '-' * 105 + '\n' tables = '' tables += """\n ==> %s <==\n\n""" % ('Components') tables += table_delimit tables += """ %6s %20s %1s %-26s %3s %16s %-s\n""" % ('', 'Method', '/', 'Basis', 'Rqd', 'Energy [H]', 'Variable') tables += table_delimit for job in JOBS_EXT: star = '' for mc in MODELCHEM: if (job['f_wfn'] == mc['f_wfn']) and (job['f_basis'] == mc['f_basis']): star = '*' tables += """ %6s %20s %1s %-27s %2s %16.8f %-s\n""" % ('', job['f_wfn'], '/', job['f_basis'], star, job['f_energy'], VARH[job['f_wfn']][job['f_wfn'] + job['f_portion']]) tables += table_delimit tables += """\n ==> %s <==\n\n""" % ('Stages') tables += table_delimit tables += """ %6s %20s %1s %-27s %2s %16s %-s\n""" % ('Stage', 'Method', '/', 'Basis', 'Wt', 'Energy [H]', 'Scheme') tables += table_delimit for stage in GRAND_NEED: tables += """ %6s %20s %1s %-27s %2d %16.8f %-s\n""" % (stage['d_stage'], stage['d_wfn'], '/', stage['d_basis'], stage['d_coef'], stage['d_energy'], stage['d_scheme'].__name__) tables += table_delimit tables += """\n ==> %s <==\n\n""" % ('CBS') tables += table_delimit tables += """ %6s %20s %1s %-27s %2s %16s %-s\n""" % ('Stage', 'Method', '/', 'Basis', '', 'Energy [H]', 'Scheme') tables += table_delimit if do_scf: tables += """ %6s %20s %1s %-27s %2s %16.8f %-s\n""" % (GRAND_NEED[0]['d_stage'], GRAND_NEED[0]['d_wfn'], '/', GRAND_NEED[0]['d_basis'], '', GRAND_NEED[0]['d_energy'], GRAND_NEED[0]['d_scheme'].__name__) if do_corl: tables += """ %6s %20s %1s %-27s %2s %16.8f %-s\n""" % (GRAND_NEED[1]['d_stage'], GRAND_NEED[1]['d_wfn'], '/', GRAND_NEED[1]['d_basis'], '', GRAND_NEED[1]['d_energy'], GRAND_NEED[1]['d_scheme'].__name__) if do_delta: tables += """ %6s %20s %1s %-27s %2s %16.8f %-s\n""" % (GRAND_NEED[2]['d_stage'], GRAND_NEED[2]['d_wfn'] + ' - ' + GRAND_NEED[3]['d_wfn'], '/', GRAND_NEED[2]['d_basis'], '', GRAND_NEED[2]['d_energy'] - GRAND_NEED[3]['d_energy'], GRAND_NEED[2]['d_scheme'].__name__) if do_delta2: tables += """ %6s %20s %1s %-27s %2s %16.8f %-s\n""" % (GRAND_NEED[4]['d_stage'], GRAND_NEED[4]['d_wfn'] + ' - ' + GRAND_NEED[5]['d_wfn'], '/', GRAND_NEED[4]['d_basis'], '', GRAND_NEED[4]['d_energy'] - GRAND_NEED[5]['d_energy'], GRAND_NEED[4]['d_scheme'].__name__) tables += """ %6s %20s %1s %-27s %2s %16.8f %-s\n""" % ('total', 'CBS', '', '', '', finalenergy, '') tables += table_delimit #print tables PsiMod.print_out(tables) # Restore molecule and options #PsiMod.set_local_option('SCF', "WFN", user_wfn) # TODO refuses to set global option WFN - rejects SCF as option PsiMod.set_global_option('BASIS', user_basis) PsiMod.set_global_option('WFN', user_wfn) if not b_user_wfn: PsiMod.revoke_global_option_changed('WFN') PsiMod.set_global_option('WRITER_FILE_LABEL', user_writer_file_label) PsiMod.set_variable('CBS REFERENCE ENERGY', GRAND_NEED[0]['d_energy']) PsiMod.set_variable('CBS CORRELATION ENERGY', finalenergy - GRAND_NEED[0]['d_energy']) PsiMod.set_variable('CBS TOTAL ENERGY', finalenergy) PsiMod.set_variable('CURRENT REFERENCE ENERGY', GRAND_NEED[0]['d_energy']) PsiMod.set_variable('CURRENT CORRELATION ENERGY', finalenergy - GRAND_NEED[0]['d_energy']) PsiMod.set_variable('CURRENT ENERGY', finalenergy) return finalenergy # Transform and validate basis sets from 'cc-pV[Q5]Z' into [cc-pVQZ, cc-pV5Z] and [4, 5]
[docs]def validate_bracketed_basis(basisstring): r"""Function to transform and validate basis sets for cbs(). A basis set with no paired square brackets is passed through with zeta level 0 (e.g., '6-31+G(d,p)' is returned as [6-31+G(d,p)] and [0]). A basis set with square brackets is checked for sensible sequence and Dunning-ness and returned as separate basis sets (e.g., 'cc-pV[Q5]Z' is returned as [cc-pVQZ, cc-pV5Z] and [4, 5]). Note that this function has no communication with the basis set library to check if the basis actually exists. Used by :py:func:`~wrappers.complete_basis_set`. """ ZETA = ['d', 't', 'q', '5', '6'] BSET = [] ZSET = [] if re.match(r'.*cc-.*\[.*\].*z$', basisstring, flags=re.IGNORECASE): basispattern = re.compile(r'^(.*)\[(.*)\](.*)$') basisname = basispattern.match(basisstring) for b in basisname.group(2): if b not in ZETA: raise ValidationError('Basis set \'%s\' has invalid zeta level \'%s\'.' % (basisstring, b)) if len(ZSET) != 0: if (int(ZSET[len(ZSET) - 1]) - ZETA.index(b)) != 1: raise ValidationError('Basis set \'%s\' has out-of-order zeta level \'%s\'.' % (basisstring, b)) BSET.append(basisname.group(1) + b + basisname.group(3)) if b == 'd': b = '2' if b == 't': b = '3' if b == 'q': b = '4' ZSET.append(int(b)) elif re.match(r'.*\[.*\].*$', basisstring, flags=re.IGNORECASE): raise ValidationError('Basis set surrounding series indicator [] in \'%s\' is invalid.' % (basisstring)) else: BSET.append(basisstring) ZSET.append(0) return [BSET, ZSET] # Reform string basis set descriptor from basis set strings, 'cc-pv[q5]z' from [cc-pvqz, cc-pv5z]
[docs]def reconstitute_bracketed_basis(needarray): r"""Function to reform a bracketed basis set string from a sequential series of basis sets (e.g, form 'cc-pv[q5]z' from array [cc-pvqz, cc-pv5z]). The basis set array is extracted from the *f_basis* field of a *NEED* dictionary in :py:func:`~wrappers.complete_basis_set`. Result is used to print a nicely formatted basis set string in the results table. """ ZETA = {'d': 2, 't': 3, 'q': 4, '5': 5, '6': 6} ZSET = [''] * len(ZETA) BSET = [] for lvl in needarray.items(): BSET.append(lvl[1]['f_basis']) if (len(BSET) == 1): basisstring = BSET[0] else: indx = 0 while indx < len(BSET[0]): if (BSET[0][indx] != BSET[1][indx]): zetaindx = indx indx += 1 for basis in BSET: ZSET[ZETA[basis[zetaindx]] - 2] = basis[zetaindx] pre = BSET[0][:zetaindx] post = BSET[0][zetaindx + 1:] basisstring = pre + '[' + ''.join(ZSET) + ']' + post return basisstring
[docs]def highest_1(**largs): r"""Scheme for total or correlation energies with a single basis or the highest zeta-level among an array of bases. Used by :py:func:`~wrappers.complete_basis_set`. .. math:: E_{total}^X = E_{total}^X """ energypiece = 0.0 functionname = sys._getframe().f_code.co_name f_fields = ['f_wfn', 'f_portion', 'f_basis', 'f_zeta', 'f_energy'] [mode, NEED, wfnname, BSET, ZSET] = validate_scheme_args(functionname, **largs) if (mode == 'requisition'): # Impose restrictions on zeta sequence if (len(ZSET) == 0): raise ValidationError('Call to \'%s\' not valid with \'%s\' basis sets.' % (functionname, len(ZSET))) # Return array that logs the requisite jobs if (wfnname == 'scf'): portion = 'tot' else: portion = 'corl' NEED = {'HI': dict(zip(f_fields, [wfnname, portion, BSET[len(ZSET) - 1], ZSET[len(ZSET) - 1], 0.0]))} return NEED elif (mode == 'evaluate'): # Extract required energies and zeta integers from array # Compute extrapolated energy energypiece = NEED['HI']['f_energy'] # Output string with extrapolation parameters cbsscheme = '' cbsscheme += """\n ==> %s <==\n\n""" % (functionname) if (NEED['HI']['f_wfn'] == 'scf'): cbsscheme += """ HI-zeta (%s) Total Energy: %16.8f\n""" % (str(NEED['HI']['f_zeta']), energypiece) else: cbsscheme += """ HI-zeta (%s) Correlation Energy: %16.8f\n""" % (str(NEED['HI']['f_zeta']), energypiece) PsiMod.print_out(cbsscheme) return energypiece # Solution equation in LaTeX: $E_{corl}^{\infty} = \frac{E_{corl}^{X} X^3 - E_{corl}^{X-1} (X-1)^3}{X^3 - (X-1)^3}$ # Solution equation in LaTeX: $\beta = \frac{E_{corl}^{X} - E_{corl}^{X-1}}{X^{-3} - (X-1)^{-3}}$
[docs]def corl_xtpl_helgaker_2(**largs): r"""Extrapolation scheme for correlation energies with two adjacent zeta-level bases. Used by :py:func:`~wrappers.complete_basis_set`. .. math:: E_{corl}^X = E_{corl}^{\infty} + \beta X^{-3} """ energypiece = 0.0 functionname = sys._getframe().f_code.co_name f_fields = ['f_wfn', 'f_portion', 'f_basis', 'f_zeta', 'f_energy'] [mode, NEED, wfnname, BSET, ZSET] = validate_scheme_args(functionname, **largs) if (mode == 'requisition'): # Impose restrictions on zeta sequence if (len(ZSET) != 2): raise ValidationError('Call to \'%s\' not valid with \'%s\' basis sets.' % (functionname, len(ZSET))) # Return array that logs the requisite jobs NEED = {'HI': dict(zip(f_fields, [wfnname, 'corl', BSET[1], ZSET[1], 0.0])), 'LO': dict(zip(f_fields, [wfnname, 'corl', BSET[0], ZSET[0], 0.0]))} return NEED elif (mode == 'evaluate'): # Extract required energies and zeta integers from array eHI = NEED['HI']['f_energy'] zHI = NEED['HI']['f_zeta'] eLO = NEED['LO']['f_energy'] zLO = NEED['LO']['f_zeta'] # Compute extrapolated energy energypiece = (eHI * zHI ** 3 - eLO * zLO ** 3) / (zHI ** 3 - zLO ** 3) beta = (eHI - eLO) / (zHI ** (-3) - zLO ** (-3)) # Output string with extrapolation parameters cbsscheme = '' cbsscheme += """\n ==> %s <==\n\n""" % (functionname) cbsscheme += """ LO-zeta (%s) Correlation Energy: %16.8f\n""" % (str(zLO), eLO) cbsscheme += """ HI-zeta (%s) Correlation Energy: %16.8f\n""" % (str(zHI), eHI) cbsscheme += """ Extrapolated Correlation Energy: %16.8f\n""" % (energypiece) cbsscheme += """ Beta (coefficient) Value: %16.8f\n""" % (beta) PsiMod.print_out(cbsscheme) return energypiece
[docs]def scf_xtpl_helgaker_3(**largs): r"""Extrapolation scheme for reference energies with three adjacent zeta-level bases. Used by :py:func:`~wrappers.complete_basis_set`. .. math:: E_{total}^X = E_{total}^{\infty} + \beta e^{-\alpha X} """ energypiece = 0.0 functionname = sys._getframe().f_code.co_name f_fields = ['f_wfn', 'f_portion', 'f_basis', 'f_zeta', 'f_energy'] [mode, NEED, wfnname, BSET, ZSET] = validate_scheme_args(functionname, **largs) if (mode == 'requisition'): # Impose restrictions on zeta sequence if (len(ZSET) != 3): raise ValidationError('Call to \'%s\' not valid with \'%s\' basis sets.' % (functionname, len(ZSET))) # Return array that logs the requisite jobs NEED = {'HI': dict(zip(f_fields, [wfnname, 'tot', BSET[2], ZSET[2], 0.0])), 'MD': dict(zip(f_fields, [wfnname, 'tot', BSET[1], ZSET[1], 0.0])), 'LO': dict(zip(f_fields, [wfnname, 'tot', BSET[0], ZSET[0], 0.0]))} return NEED elif (mode == 'evaluate'): # Extract required energies and zeta integers from array eHI = NEED['HI']['f_energy'] eMD = NEED['MD']['f_energy'] eLO = NEED['LO']['f_energy'] zHI = NEED['HI']['f_zeta'] zMD = NEED['MD']['f_zeta'] zLO = NEED['LO']['f_zeta'] # Compute extrapolated energy ratio = (eHI - eMD) / (eMD - eLO) alpha = -1 * math.log(ratio) beta = (eHI - eMD) / (math.exp(-1 * alpha * zMD) * (ratio - 1)) energypiece = eHI - beta * math.exp(-1 * alpha * zHI) # Output string with extrapolation parameters cbsscheme = '' cbsscheme += """\n ==> %s <==\n\n""" % (functionname) cbsscheme += """ LO-zeta (%s) Correlation Energy: %16.8f\n""" % (str(zLO), eLO) cbsscheme += """ MD-zeta (%s) Correlation Energy: %16.8f\n""" % (str(zMD), eMD) cbsscheme += """ HI-zeta (%s) Correlation Energy: %16.8f\n""" % (str(zHI), eHI) cbsscheme += """ Extrapolated Correlation Energy: %16.8f\n""" % (energypiece) cbsscheme += """ Alpha (exponent) Value: %16.8f\n""" % (alpha) cbsscheme += """ Beta (coefficient) Value: %16.8f\n""" % (beta) PsiMod.print_out(cbsscheme) return energypiece
[docs]def scf_xtpl_helgaker_2(**largs): r"""Extrapolation scheme for reference energies with two adjacent zeta-level bases. Used by :py:func:`~wrappers.complete_basis_set`. .. math:: E_{total}^X = E_{total}^{\infty} + \beta e^{-\alpha X}, \alpha = 1.63 """ energypiece = 0.0 functionname = sys._getframe().f_code.co_name f_fields = ['f_wfn', 'f_portion', 'f_basis', 'f_zeta', 'f_energy'] [mode, NEED, wfnname, BSET, ZSET] = validate_scheme_args(functionname, **largs) if (mode == 'requisition'): # Impose restrictions on zeta sequence if (len(ZSET) != 2): raise ValidationError('Call to \'%s\' not valid with \'%s\' basis sets.' % (functionname, len(ZSET))) # Return array that logs the requisite jobs NEED = {'HI': dict(zip(f_fields, [wfnname, 'tot', BSET[1], ZSET[1], 0.0])), 'LO': dict(zip(f_fields, [wfnname, 'tot', BSET[0], ZSET[0], 0.0]))} return NEED elif (mode == 'evaluate'): # Extract required energies and zeta integers from array eHI = NEED['HI']['f_energy'] eLO = NEED['LO']['f_energy'] zHI = NEED['HI']['f_zeta'] zLO = NEED['LO']['f_zeta'] # LAB TODO add ability to pass alternate parameter values in # Return extrapolated energy alpha = 1.63 beta = (eHI - eLO) / (math.exp(-1 * alpha * zLO) * (math.exp(-1 * alpha) - 1)) energypiece = eHI - beta * math.exp(-1 * alpha * zHI) # Output string with extrapolation parameters cbsscheme = '' cbsscheme += """\n ==> %s <==\n\n""" % (functionname) cbsscheme += """ LO-zeta (%s) Correlation Energy: %16.8f\n""" % (str(zLO), eLO) cbsscheme += """ HI-zeta (%s) Correlation Energy: %16.8f\n""" % (str(zHI), eHI) cbsscheme += """ Extrapolated Correlation Energy: %16.8f\n""" % (energypiece) cbsscheme += """ Alpha (exponent) Value: %16.8f\n""" % (alpha) cbsscheme += """ Beta (coefficient) Value: %16.8f\n""" % (beta) PsiMod.print_out(cbsscheme) return energypiece
[docs]def validate_scheme_args(functionname, **largs): r"""Function called by each extrapolation scheme in :py:func:`~wrappers.complete_basis_set`. Checks that all the input arguments are present and suitable so that the scheme function can focus on defining the extrapolation. """ mode = '' NEED = [] wfnname = '' BSET = [] ZSET = [] # Mode where function fills out a form NEED with the computations needed to fulfill its call if (largs['mode'].lower() == 'requisition'): mode = largs['mode'].lower() if 'wfnname' in largs: wfnname = largs['wfnname'] else: raise ValidationError('Call to \'%s\' has keyword \'wfnname\' missing.' % (functionname)) if re.match(r'scf_.*$', functionname) and (wfnname != 'scf'): raise ValidationError('Call to \'%s\' is intended for scf portion of calculation.' % (functionname)) if re.match(r'corl_.*$', functionname) and (wfnname == 'scf'): raise ValidationError('Call to \'%s\' is not intended for scf portion of calculation.' % (functionname)) if 'basisname' in largs: BSET = largs['basisname'] else: raise ValidationError('Call to \'%s\' has keyword \'basisname\' missing.' % (functionname)) if 'basiszeta' in largs: ZSET = largs['basiszeta'] else: raise ValidationError('Call to \'%s\' has keyword \'basiszeta\' missing.' % (functionname)) # Mode where function reads the now-filled-in energies from that same form and performs the sp, xtpl, delta, etc. elif (largs['mode'].lower() == 'evaluate'): mode = largs['mode'].lower() if 'needname' in largs: NEED = largs['needname'] else: raise ValidationError('Call to \'%s\' has keyword \'needname\' missing.' % (functionname)) else: raise ValidationError('Call to \'%s\' has keyword \'mode\' missing or invalid.' % (functionname)) return [mode, NEED, wfnname, BSET, ZSET]
[docs]def split_menial(menial): r"""Function used by :py:func:`~wrappers.complete_basis_set` to separate *menial* 'scftot' into [scf, tot] and 'mp2corl' into [mp2, corl]. """ PTYP = ['tot', 'corl'] for temp in PTYP: if menial.endswith(temp): temp_wfn = menial[:-len(temp)] temp_portion = temp return [temp_wfn, temp_portion] # Quickly normalize the types for both python 2 and 3
try: unicode = unicode except NameError: # 'unicode' is undefined, must be Python 3 str = str unicode = str bytes = bytes basestring = (str,bytes) else: # 'unicode' exists, must be Python 2 str = str unicode = unicode bytes = str basestring = basestring ## Aliases ## cbs = complete_basis_set ################################# ## End of Complete Basis Set ## #################################