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# Handle access to Psi scf module
require 'pp'
module Psi
class SCF
include InputGenerator
include Executor
# Which references does this method support
def self.supports_analytic_gradients
{ "rhf" => true, "rohf" => true, "uhf" => true, "twocon" => true }
end
def self.supports_analytic_second_derivatives
{ "rhf" => true, "rohf" => false, "uhf" => false, "twocon" => false }
end
def initialize(task_obj)
@task = task_obj
# Set the generic command for this class
set_binary_command Psi::Commands::SCF
end
end
# Add scf ability to Task
class Task
def scf(*args)
# convert to a hash
args_hash = args[0]
# Make sure cints is called
if args_hash != nil
if args_hash.has_key?(:ints) == false or
(args_hash.has_key?(:ints) and args_hash[:ints] == true)
ints("wfn" => "scf")
end
else
ints("wfn" => "scf")
end
# Create a new scf object
scf_obj = Psi::SCF.new self
# Form the input hash and generate the input file
input_hash = { }
# Check to see if the user overrode the wavefunction
if args_hash == nil or args_hash.has_key?("wfn") == false
input_hash["wfn"] = wavefunction
else
input_hash["wfn"] = args_hash["wfn"]
end
args_hash.delete("wfn") unless args_hash == nil
# Check to see if the user gave the reference wavefunction. if it is given, do not use the
# global setting
if args_hash == nil or args_hash.has_key?("reference") == false
input_hash["reference"] = reference
else
input_hash["reference"] = args_hash["reference"]
end
args_hash.delete("reference") unless args_hash == nil
# If we are doing analytical gradients then cscf needs to know
if get_gradients == true and SCF.supports_analytic_gradients[reference] == true
input_hash["dertype"] = "first"
elsif get_second_deriv == true and SCF.supports_analytic_second_derivatives[reference] == true
input_hash["dertype"] = "second"
else
input_hash["dertype"] = "none"
end
# Merge what we've done with what the user wants
input_hash = input_hash.merge(args_hash) unless args_hash == nil
# Run the scf module, sending the input file as keyboard input
puts "scf"
scf_obj.execute(input_hash)
# Check to see if we are supposed to compute analytical gradients, only do if
# 1. It is supported
# 2. The user requested it
# 3. The wavefunction is SCF
if get_gradients == true and SCF.supports_analytic_gradients[reference] == true and wavefunction.casecmp("scf") == 0
# Make sure the wavefunction is set
input_hash["wfn"] = "scf"
deriv(input_hash)
elsif get_second_deriv == true and SCF.supports_analytic_second_derivatives[reference] == true and wavefunction.casecmp("scf") == 0
# Make sure the wavefunction is set
input_hash["wfn"] = "scf"
transqt(input_hash)
deriv2(input_hash)
propint(input_hash)
cphf(input_hash)
end
# Return the total energy to the user
etot
end
def rhf(*args)
# Convert to hash
args_hash = args[0]
# Set the Task reference to RHF
# Must use @ sign here to access the instance variable, if we did reference then only
# local variable is set
@reference = "rhf"
# Call scf
scf(args_hash)
end
def rohf(*args)
args_hash = args[0]
# Set the Task reference to ROHF
@reference = "rohf"
# Call scf
scf(args_hash)
end
def uhf(*args)
args_hash = args[0]
# Set the global reference to UHF
@reference = "uhf"
# Call scf
scf(args_hash)
end
end
end
# Create some global functions
# User can send additional input parameters to the function
def scf(*args)
# convert to a hash
args_hash = args[0]
Psi::global_task.scf(args_hash)
end
def rhf(*args)
# Convert to hash
args_hash = args[0]
Psi::global_task.rhf(args_hash)
end
def rohf(*args)
args_hash = args[0]
Psi::global_task.rohf(args_hash)
end
def uhf(*args)
args_hash = args[0]
Psi::global_task.uhf(args_hash)
end
|
