source: issm/trunk-jpl/src/m/classes/inversion.py@ 12958

#module imports
from fielddisplay import fielddisplay

class inversion(object):
        #properties
        def __init__(self):
                # {{{ Properties
                self.iscontrol                   = 0
                self.tao                         = 0
                self.incomplete_adjoint          = 0
                self.control_parameters          = float('NaN')
                self.nsteps                      = 0
                self.maxiter_per_step            = float('NaN')
                self.cost_functions              = float('NaN')
                self.cost_functions_coefficients = float('NaN')
                self.gradient_scaling            = float('NaN')
                self.cost_function_threshold     = 0
                self.min_parameters              = float('NaN')
                self.max_parameters              = float('NaN')
                self.step_threshold              = float('NaN')
                self.gradient_only               = 0
                self.vx_obs                      = float('NaN')
                self.vy_obs                      = float('NaN')
                self.vz_obs                      = float('NaN')
                self.vel_obs                     = float('NaN')
                self.thickness_obs               = float('NaN')
                #}}}
        def __repr__(obj):
                # {{{ Display
                string='\n   Inversion parameters:'
                string="%s\n%s"%(string,fielddisplay(obj,'iscontrol','is inversion activated?'))
                string="%s\n%s"%(string,fielddisplay(obj,'incomplete_adjoint','do we assume linear viscosity?'))
                string="%s\n%s"%(string,fielddisplay(obj,'control_parameters','parameter where inverse control is carried out; ex: {''FrictionCoefficient''}, or {''MaterialsRheologyBbar''}'))
                string="%s\n%s"%(string,fielddisplay(obj,'nsteps','number of optimization searches'))
                string="%s\n%s"%(string,fielddisplay(obj,'cost_functions','indicate the type of response for each optimization step'))
                string="%s\n%s"%(string,fielddisplay(obj,'cost_functions_coefficients','cost_functions_coefficients applied to the misfit of each vertex and for each control_parameter'))
                string="%s\n%s"%(string,fielddisplay(obj,'cost_function_threshold','misfit convergence criterion. Default is 1%, NaN if not applied'))
                string="%s\n%s"%(string,fielddisplay(obj,'maxiter_per_step','maximum iterations during each optimization step'))
                string="%s\n%s"%(string,fielddisplay(obj,'gradient_scaling','scaling factor on gradient direction during optimization, for each optimization step'))
                string="%s\n%s"%(string,fielddisplay(obj,'step_threshold','decrease threshold for misfit, default is 30%'))
                string="%s\n%s"%(string,fielddisplay(obj,'min_parameters','absolute minimum acceptable value of the inversed parameter on each vertex'))
                string="%s\n%s"%(string,fielddisplay(obj,'max_parameters','absolute maximum acceptable value of the inversed parameter on each vertex'))
                string="%s\n%s"%(string,fielddisplay(obj,'gradient_only','stop control method solution at gradient'))
                string="%s\n%s"%(string,fielddisplay(obj,'vx_obs','observed velocity x component [m/a]'))
                string="%s\n%s"%(string,fielddisplay(obj,'vy_obs','observed velocity y component [m/a]'))
                string="%s\n%s"%(string,fielddisplay(obj,'vel_obs','observed velocity magnitude [m/a]'))
                string="%s\n%s"%(string,fielddisplay(obj,'thickness_obs','observed thickness [m]'))
                string="%s\n%s"%(string,'Available cost functions:')
                string="%s\n%s"%(string,'   101: SurfaceAbsVelMisfit')
                string="%s\n%s"%(string,'   102: SurfaceRelVelMisfit')
                string="%s\n%s"%(string,'   103: SurfaceLogVelMisfit')
                string="%s\n%s"%(string,'   104: SurfaceLogVxVyMisfit')
                string="%s\n%s"%(string,'   105: SurfaceAverageVelMisfit')
                string="%s\n%s"%(string,'   201: ThicknessAbsMisfit')
                string="%s\n%s"%(string,'   501: DragCoefficientAbsGradient')
                string="%s\n%s"%(string,'   502: RheologyBbarAbsGradient')
                string="%s\n%s"%(string,'   503: ThicknessAbsGradient')
                return string
                #}}}

        def setdefaultparameters(obj):
                # {{{setdefaultparameters
                
                #default is incomplete adjoint for now
                obj.incomplete_adjoint=1

                #parameter to be inferred by control methods (only
                #drag and B are supported yet)
                obj.control_parameters=['FrictionCoefficient']

                #number of steps in the control methods
                obj.nsteps=20

                #maximum number of iteration in the optimization algorithm for
                #each step
                obj.maxiter_per_step=20*ones(obj.nsteps)

                #the inversed parameter is updated as follows:
                #new_par=old_par + gradient_scaling(n)*C*gradient with C in [0 1];
                #usually the gradient_scaling must be of the order of magnitude of the 
                #inversed parameter (10^8 for B, 50 for drag) and can be decreased
                #after the first iterations
                obj.gradient_scaling=50*ones(obj.nsteps)

                #several responses can be used:
                obj.cost_functions=101*ones(obj.nsteps)

                #step_threshold is used to speed up control method. When
                #misfit(1)/misfit(0) < obj.step_threshold, we go directly to
                #the next step
                obj.step_threshold=.7*ones(obj.nsteps) #30 per cent decrement

                #stop control solution at the gradient computation and return it? 
                obj.gradient_only=0

                #cost_function_threshold is a criteria to stop the control methods.
                #if J[n]-J[n-1]/J[n] < criteria, the control run stops
                #NaN if not applied
                obj.cost_function_threshold=NaN #not activated 

                return obj
                #}}}