Class: CodeRunner::Trinity::Optimisation

Inherits:
Object
  • Object
show all
Includes:
GSL::MultiMin
Defined in:
lib/trinitycrdriver/optimisation.rb

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(optimised_quantity, optimisation_spec) ⇒ Optimisation

Returns a new instance of Optimisation.



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# File 'lib/trinitycrdriver/optimisation.rb', line 12

def initialize(optimised_quantity, optimisation_spec)
	#@folder = folder
	@optimised_quantity = optimised_quantity
	@optimisation_spec = optimisation_spec
	@optimisation_variables = optimisation_spec.map{|code, hash| hash.map{|var, pars| [code, var]}}.flatten(1)
	@optimisation_starts    = optimisation_spec.map{|code, hash| hash.map{|var, pars| pars[0]}}.flatten(1)
	@optimisation_steps     = optimisation_spec.map{|code, hash| hash.map{|var, pars| pars[1]}}.flatten(1)
	#@runner = CodeRunner.fetch_runner(
	#p ['optimisation_variables', @optimisation_variables]
end

Instance Attribute Details

#chease_runner ⇒ Object

Returns the value of attribute chease_runner.



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# File 'lib/trinitycrdriver/optimisation.rb', line 11

def chease_runner
  @chease_runner
end

#optimisation_spec ⇒ Object (readonly)

code_name is either trinity or chease (both can be used simultaneously)



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# File 'lib/trinitycrdriver/optimisation.rb', line 8

def optimisation_spec
  @optimisation_spec
end

#optimisation_variables ⇒ Object (readonly)

Returns the value of attribute optimisation_variables.



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# File 'lib/trinitycrdriver/optimisation.rb', line 9

def optimisation_variables
  @optimisation_variables
end

#trinity_runner ⇒ Object

Returns the value of attribute trinity_runner.



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# File 'lib/trinitycrdriver/optimisation.rb', line 10

def trinity_runner
  @trinity_runner
end

Instance Method Details

#dimension ⇒ Object

p [‘optimisation_variables’, @optimisation_variables]



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# File 'lib/trinitycrdriver/optimisation.rb', line 22

def dimension
	@optimisation_variables.size
end

#func(v) ⇒ Object 



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# File 'lib/trinitycrdriver/optimisation.rb', line 46

def func(v)
	pars = {}
	pars[:chease] = {}
	pars[:trinity] = {}
	for i in 0...v.size
		code, varname = @optimisation_variables[i]
		val = v[i]
		pars[code][varname] = val
	end
	if not @first_run_done
		pars[:trinity][:ntstep] = 300
		#@first_run_done = true
	#else
		#pars[:trinity][:ntstep] = 100
	end

	pars[:chease][:ap] = [0.3,0.5,0.4,0.0,0.4,0.0,0.0]
    pars[:chease][:at] = [0.16,1.0,1.0,-1.1,-1.1]


	trinity_runner.run_class.instance_variable_set(:@mpi_communicator, MPI::Comm::WORLD)
  if false and trinity_runner.run_list.size > 0
	else
		crun = chease_runner.run_class.new(chease_runner)
		crun.update_submission_parameters(pars[:chease].inspect)
		if chease_runner.run_list.size > 0
			crun.restart_id = @cid
		end
		chease_runner.submit(crun)
		crun = chease_runner.run_list[@cid = chease_runner.max_id]
		crun.recheck
		chease_runner.update
		#chease_runner.print_out(0)
		FileUtils.cp(crun.directory + '/ogyropsi.dat', trinity_runner.root_folder + '/.')

		run = trinity_runner.run_class.new(trinity_runner)
		run.update_submission_parameters(pars[:trinity].inspect)
		#trinity_runner.run_class.instance_variable_set(:@delay_execution, true)
		if trinity_runner.run_list.size > 0
			#run.restart_id = @id
		end
		trinity_runner.submit(run)
		run = trinity_runner.run_list[@id = trinity_runner.max_id]
		run.recheck
		trinity_runner.update
		#trinity_runner.print_out(0)
		result =  run.send(@optimised_quantity)
		p ['result is ', result]
		return -result
	end


  #v.square.sum
end

#serial_optimise(optimisation_method, parameters_obj) ⇒ Object 



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# File 'lib/trinitycrdriver/optimisation.rb', line 25

def serial_optimise(optimisation_method, parameters_obj)
	optimisation_meth = case optimisation_method
											when :simplex
												FMinimizer::NMSIMPLEX
											else 
												raise "Unknown optimisation_method"
											end
	opt = FMinimizer.alloc(optimisation_meth, @optimisation_variables.size)
	func = Proc.new{|v, optimiser| optimiser.func(v)}
	gsl_func = Function.alloc(func, dimension)
	gsl_func.set_params(self)
	opt.set(gsl_func, @optimisation_starts.to_gslv, @optimisation_steps.to_gslv)
	parameters_obj.nit.times do |i|
		opt.iterate
		p ['status', opt.x, opt.minimum, i, parameters_obj.nit]
	end

	p 'heellllllo'
	MPI.Finalize
	
end