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# Handle access to Psi detci module
module Psi
class DetCI
# Mixin the InputGenerator
include InputGenerator
include Executor
# Which references does this method support
def self.supports_analytic_gradients
{ "rhf" => false, "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::DETCI
end
end
# Add detci ability to Task
class Task
def detci(*args)
# convert to a hash
args_hash = args[0]
# Call transqt unless told not to
if args_hash != nil
if args_hash.has_key?(:transqt) == false or
(args_hash.has_key?(:transqt) and args_hash[:transqt] == true)
transqt(args_hash)
end
else
transqt(args_hash)
end
args_hash.delete(:transqt) unless args_hash == nil
# Create a new scf object
detci_obj = Psi::DetCI.new self
# Form the input hash and generate the input file
input_hash = { }
# Check to see if the function arguments have the reference, if so use it, otherwise use
# global setting
if args_hash == nil or args_hash.has_key?("reference") == false
input_hash["reference"] = reference
end
# If we are doing analytic gradients make sure detci knows
if get_gradients == true and DetCI.supports_analytic_gradients[reference] == true
input_hash["dertype"] = "first"
else
input_hash["dertype"] = "none"
end
# Check the wavefunction
if args_hash == nil or args_hash.has_key?("wfn") == false
input_hash["wfn"] = wavefunction
end
# Merge what we've done with what the user wants, user settings should override
input_hash = input_hash.merge(args_hash) unless args_hash == nil
# Run the ccenergy module, sending the input file as keyboard input
puts "detci"
detci_obj.execute(input_hash)
etot
end
end
end
# Create some global functions
# User can send additional input parameters to the function
def detci(*args)
# convert to a hash
args_hash = args[0]
Psi::global_task.detci(args_hash)
end
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