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167 changes: 167 additions & 0 deletions
167
app/lib/whats_opt/templates/egmdo/random_vec_analysis.py.erb
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,167 @@ | ||
| import os | ||
| import numpy as np | ||
| from numpy import nan, inf | ||
| import pickle | ||
|
|
||
| import openmdao.api as om | ||
| <% if @impl.nonlinear_solver.reckless? -%> | ||
| from openmdao_extensions.reckless_nonlinear_block_gs import RecklessNonlinearBlockGS | ||
| <% else -%> | ||
| from openmdao.api import <%= @impl.nonlinear_solver.name %> | ||
| <% end -%> | ||
| from openmdao.api import NewtonSolver | ||
| from openmdao.api import <%= @impl.linear_solver.name %> | ||
| <%- @mda.egmdo_random_disciplines.each do |disc| -%> | ||
|
|
||
| class <%= disc.py_classname %>RandomVecDiscipline(om.ExplicitComponent): | ||
| """ An OpenMDAO base component to encapsulate <%= disc.py_classname %> discipline """ | ||
| def __init__(self, gp_factory, n_cases=1, **kwargs): | ||
| super().__init__(**kwargs) | ||
| <%- disc.output_variables.each do |v| -%> | ||
| with open(gp_factory.gp_filename("<%= disc.snake_modulename %>", "<%= v.py_varname %>"), 'rb') as f: | ||
| self.gp_<%= v.py_varname %> = pickle.load(f) | ||
| <%- end %> | ||
| self.n_cases = n_cases | ||
|
|
||
| <%- unless disc.variables.empty? -%> | ||
| def setup(self): | ||
| <%- disc.input_variables.numeric.each do |var| %> | ||
| <%- if @mda.is_egmdo_random_variable?(var) -%> | ||
| <%= var.py_varname %> = np.ones((self.n_cases, <%= var.dim %>)) | ||
| <%- else -%> | ||
| <%= var.py_varname %> = <%= var.init_py_value %> | ||
| <%- end -%> | ||
| self.add_input('<%= var.py_varname %>', val=<%= var.py_varname %>, desc='<%= var.escaped_desc %>'<%= @impl.use_units && !var.units.blank? ? ", units='#{var.units}'":"" %>)<%- end %> | ||
| <%- disc.output_variables.each do |var| %> | ||
| <%- if @mda.is_egmdo_random_variable?(var) -%> | ||
| _xi_<%= var.py_varname %> = np.zeros(self.n_cases) | ||
| <%- else -%> | ||
| _xi_<%= var.py_varname %> = 0.0 | ||
| <%- end -%> | ||
| self.add_input('_xi_<%= var.py_varname %>', val=_xi_<%= var.py_varname %>)<%- end %> | ||
| <%- disc.output_variables.numeric.each do |var| -%> | ||
| <%= var.py_varname %> = np.ones((self.n_cases, <%= var.dim %>)) | ||
| <%- if var.scaling.blank? -%> | ||
| self.add_output('<%= var.py_varname %>', val=<%= var.py_varname %>, desc='<%= var.escaped_desc %>'<%= @impl.use_units && !var.units.blank? ? ", units='#{var.units}'":"" %>) | ||
| <%- else -%> | ||
| self.add_output('<%= var.py_varname %>', val=<%= var.py_varname %>, desc='<%= var.escaped_desc %>', | ||
| ref=<%= var.scaling_ref_py_value %>, ref0=<%= var.scaling_ref0_py_value %>, res_ref=<%= var.scaling_res_ref_py_value %><%= @impl.use_units && !var.units.blank? ? ", units='#{var.units}'":"" %>) | ||
| <%- end -%> | ||
| <%- end -%> | ||
|
|
||
| def compute(self, inputs, outputs): | ||
| inputs_gp = np.zeros((self.n_cases, <%= disc.input_variables.map(&:dim).inject(0, :+) %>)) | ||
| random_inputs = [<%= disc.output_variables.map{|v| "'_xi_#{v.py_varname}'"}.join(', ') %>] | ||
| design_vars = [<%= @mda.design_variables.map{|v| "'#{v.name}'"}.join(', ') %>] | ||
| coupling_vars = [<%= @mda.coupling_variables.map{|v| "'#{v.name}'"}.join(', ') %>] | ||
| i = 0 | ||
| for name in sorted(inputs.keys()): | ||
| if name not in random_inputs: | ||
| if name in design_vars: | ||
| # design variables should be reshaped | ||
| dim = inputs[name].shape[0] | ||
| input_temp = np.tile(inputs[name], (self.n_cases, 1)) | ||
| inputs_gp[:, i:i+dim] = input_temp | ||
| i = i + dim | ||
| elif name in coupling_vars: | ||
| # coupling variables | ||
| dim = inputs[name].shape[1] | ||
| inputs_gp[:, i:i+dim] = inputs[name] | ||
| i = i + dim | ||
|
|
||
| inputs_gp = np.atleast_2d(inputs_gp) | ||
|
|
||
| <% disc.output_variables.each do |v|%> | ||
| sigma = np.sqrt(self.gp_<%= v.py_varname %>.predict_variances(inputs_gp)) | ||
| mean = self.gp_<%= v.py_varname %>.predict_values(inputs_gp) | ||
| outputs['<%= v.py_varname %>'] = mean[:, 0] + inputs['_xi_<%= v.py_varname %>'] * sigma[:, 0] | ||
| <%- end -%> | ||
| <%- end -%> | ||
| <%- end -%> | ||
| <%- @mda.plain_disciplines.each do |disc| -%> | ||
| <% if !@mda.egmdo_random_disciplines.include?(disc) %> | ||
|
|
||
| class <%= disc.py_classname %>RandomVecDiscipline(om.ExplicitComponent): | ||
| """ An OpenMDAO base component to encapsulate <%= disc.py_classname %> discipline """ | ||
| def __init__(self, disc, n_cases=1, **kwargs): | ||
| super().__init__(**kwargs) | ||
| self.disc = disc | ||
| self.n_cases = n_cases | ||
|
|
||
| <%- unless disc.variables.empty? -%> | ||
| def setup(self): | ||
| <%- disc.input_variables.numeric.each do |var| %> | ||
| <%- if @mda.is_egmdo_random_variable?(var) -%> | ||
| <%= var.py_varname %> = np.ones((self.n_cases, <%= var.dim %>)) | ||
| <%- else -%> | ||
| <%= var.py_varname %> = <%= var.init_py_value %> | ||
| <%- end -%> | ||
| self.add_input('<%= var.py_varname %>', val=<%= var.py_varname %>, desc='<%= var.escaped_desc %>'<%= @impl.use_units && !var.units.blank? ? ", units='#{var.units}'":"" %>)<%- end %> | ||
| <%- disc.output_variables.numeric.each do |var| -%> | ||
| <%= var.py_varname %> = np.ones((self.n_cases, <%= var.dim %>)) | ||
| <%- if var.scaling.blank? -%> | ||
| self.add_output('<%= var.py_varname %>', val=<%= var.py_varname %>, desc='<%= var.escaped_desc %>'<%= @impl.use_units && !var.units.blank? ? ", units='#{var.units}'":"" %>) | ||
| <%- else -%> | ||
| self.add_output('<%= var.py_varname %>', val=<%= var.py_varname %>, desc='<%= var.escaped_desc %>', | ||
| ref=<%= var.scaling_ref_py_value %>, ref0=<%= var.scaling_ref0_py_value %>, res_ref=<%= var.scaling_res_ref_py_value %><%= @impl.use_units && !var.units.blank? ? ", units='#{var.units}'":"" %>) | ||
| <%- end -%> | ||
| <%- end -%> | ||
|
|
||
| def compute(self, inputs, outputs): | ||
| self.disc.compute(inputs, outputs) | ||
|
|
||
| <%- end -%> | ||
| <%- end -%> | ||
| <%- end -%> | ||
|
|
||
|
|
||
| class <%= @mda.py_classname %>RandomVecAnalysis(<%= @impl.parallel_group ? "om.ParallelGroup" : "om.Group" %>): | ||
| """ An OpenMDAO base component to encapsulate <%= @mda.py_classname %> random MDA """ | ||
| def __init__(self, discipline_factory, gp_factory, n_cases=1, **kwargs): | ||
| super(). __init__(**kwargs) | ||
| self.disc_factory = discipline_factory | ||
| self.gp_factory = gp_factory | ||
| self.n_cases = n_cases | ||
|
|
||
| # self.nonlinear_solver = NewtonSolver(solve_subsystems=False) | ||
| self.nonlinear_solver = NonlinearBlockGS() | ||
|
|
||
| <% unless @impl.nonlinear_solver.runonce? -%> | ||
| self.nonlinear_solver.options['atol'] = <%= @impl.nonlinear_solver.atol %> | ||
| self.nonlinear_solver.options['rtol'] = <%= @impl.nonlinear_solver.rtol %> | ||
| self.nonlinear_solver.options['err_on_non_converge'] = <%= @impl.to_code(:nonlinear_solver, :err_on_non_converge) %> | ||
| self.nonlinear_solver.options['iprint'] = <%= @impl.nonlinear_solver.iprint %> | ||
| self.nonlinear_solver.options['maxiter'] = <%= @impl.nonlinear_solver.maxiter %> | ||
| <% end -%> | ||
|
|
||
| self.linear_solver = <%= @impl.linear_solver.name %>() | ||
| self.linear_solver.options['atol'] = <%= @impl.linear_solver.atol %> | ||
| self.linear_solver.options['rtol'] = <%= @impl.linear_solver.rtol %> | ||
| self.linear_solver.options['err_on_non_converge'] = <%= @impl.to_code(:linear_solver, :err_on_non_converge) %> | ||
| self.linear_solver.options['iprint'] = <%= @impl.linear_solver.iprint %> | ||
| self.linear_solver.options['maxiter'] = <%= @impl.linear_solver.maxiter %> | ||
|
|
||
| def setup(self): | ||
| <%- @mda.input_variables.each do |dv| -%> | ||
| self.set_input_defaults('<%= dv.name %>', val=<%= dv.init_py_value %><%= @impl.use_units && !dv.units.blank? ? ", units='#{dv.units}'":"" %>) | ||
| <%- end -%> | ||
| <%- @mda.egmdo_random_variables.each do |v| -%> | ||
| self.set_input_defaults('_xi_<%= v.name %>', val=np.zeros(self.n_cases)) | ||
| <%- end -%> | ||
| <%- @mda.plain_disciplines.each do |disc| -%> | ||
| name = '<%= disc.py_classname %>RandomVec' | ||
| <%- if disc.openmdao_impl&.egmdo_surrogate -%> | ||
| disc = <%= disc.py_classname %>RandomVecDiscipline(self.gp_factory, self.n_cases) | ||
| <%- else -%> | ||
| true_disc = self.disc_factory.create_<%= disc.snake_modulename %>() | ||
| disc = <%= disc.py_classname %>RandomVecDiscipline(true_disc, self.n_cases) | ||
| <%- end -%> | ||
| self.add_subsystem(name, disc, promotes=['*']) | ||
| <%- end -%> | ||
|
|
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