1 | import numpy as np
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2 |
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3 | from checkfield import checkfield
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4 | from fielddisplay import fielddisplay
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5 | from marshallcostfunctions import marshallcostfunctions
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6 | from project3d import project3d
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7 | from supportedcontrols import supportedcontrols
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8 | from supportedcostfunctions import supportedcostfunctions
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9 | from WriteData import WriteData
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10 |
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11 |
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12 | class inversion(object):
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13 | """INVERSION class definition
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14 |
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15 | Usage:
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16 | inversion = inversion()
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17 | """
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18 |
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19 | def __init__(self): # {{{
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20 | self.iscontrol = 0
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21 | self.incomplete_adjoint = 0
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22 | self.control_parameters = np.nan
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23 | self.nsteps = 0
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24 | self.maxiter_per_step = np.nan
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25 | self.cost_functions = ''
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26 | self.cost_functions_coefficients = np.nan
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27 | self.gradient_scaling = np.nan
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28 | self.cost_function_threshold = 0
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29 | self.min_parameters = np.nan
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30 | self.max_parameters = np.nan
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31 | self.step_threshold = np.nan
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32 | self.vx_obs = np.nan
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33 | self.vy_obs = np.nan
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34 | self.vz_obs = np.nan
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35 | self.vel_obs = np.nan
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36 | self.thickness_obs = np.nan
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37 | self.surface_obs = np.nan
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38 |
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39 | self.setdefaultparameters()
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40 | # }}}
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41 |
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42 | def __repr__(self): # {{{
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43 | s = ' inversion parameters:\n'
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44 | s += '{}\n'.format(fielddisplay(self, 'iscontrol', 'is inversion activated?'))
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45 | s += '{}\n'.format(fielddisplay(self, 'incomplete_adjoint', '1: linear viscosity, 0: non - linear viscosity'))
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46 | s += '{}\n'.format(fielddisplay(self, 'control_parameters', 'ex: {''FrictionCoefficient''}, or {''MaterialsRheologyBbar''}'))
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47 | s += '{}\n'.format(fielddisplay(self, 'nsteps', 'number of optimization searches'))
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48 | s += '{}\n'.format(fielddisplay(self, 'cost_functions', 'indicate the type of response for each optimization step'))
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49 | s += '{}\n'.format(fielddisplay(self, 'cost_functions_coefficients', 'cost_functions_coefficients applied to the misfit of each vertex and for each control_parameter'))
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50 | s += '{}\n'.format(fielddisplay(self, 'cost_function_threshold', 'misfit convergence criterion. Default is 1%, NaN if not applied'))
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51 | s += '{}\n'.format(fielddisplay(self, 'maxiter_per_step', 'maximum iterations during each optimization step'))
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52 | s += '{}\n'.format(fielddisplay(self, 'gradient_scaling', 'scaling factor on gradient direction during optimization, for each optimization step'))
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53 | s += '{}\n'.format(fielddisplay(self, 'step_threshold', 'decrease threshold for misfit, default is 30%'))
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54 | s += '{}\n'.format(fielddisplay(self, 'min_parameters', 'absolute minimum acceptable value of the inversed parameter on each vertex'))
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55 | s += '{}\n'.format(fielddisplay(self, 'max_parameters', 'absolute maximum acceptable value of the inversed parameter on each vertex'))
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56 | s += '{}\n'.format(fielddisplay(self, 'vx_obs', 'observed velocity x component [m/yr]'))
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57 | s += '{}\n'.format(fielddisplay(self, 'vy_obs', 'observed velocity y component [m/yr]'))
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58 | s += '{}\n'.format(fielddisplay(self, 'vel_obs', 'observed velocity magnitude [m/yr]'))
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59 | s += '{}\n'.format(fielddisplay(self, 'thickness_obs', 'observed thickness [m]'))
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60 | s += '{}\n'.format(fielddisplay(self, 'surface_obs', 'observed surface elevation [m]'))
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61 | s += '{}\n'.format('Available cost functions:')
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62 | s += '{}\n'.format(' 101: SurfaceAbsVelMisfit')
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63 | s += '{}\n'.format(' 102: SurfaceRelVelMisfit')
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64 | s += '{}\n'.format(' 103: SurfaceLogVelMisfit')
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65 | s += '{}\n'.format(' 104: SurfaceLogVxVyMisfit')
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66 | s += '{}\n'.format(' 105: SurfaceAverageVelMisfit')
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67 | s += '{}\n'.format(' 201: ThicknessAbsMisfit')
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68 | s += '{}\n'.format(' 501: DragCoefficientAbsGradient')
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69 | s += '{}\n'.format(' 502: RheologyBbarAbsGradient')
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70 | s += '{}\n'.format(' 503: ThicknessAbsGradient')
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71 | return s
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72 | # }}}
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73 |
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74 | def setdefaultparameters(self): # {{{
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75 | #default is incomplete adjoint for now
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76 | self.incomplete_adjoint = 1
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77 | #parameter to be inferred by control methods (only
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78 | #drag and B are supported yet)
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79 | self.control_parameters = 'FrictionCoefficient'
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80 | #number of steps in the control methods
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81 | self.nsteps = 20
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82 | #maximum number of iteration in the optimization algorithm for
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83 | #each step
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84 | self.maxiter_per_step = 20 * np.ones(self.nsteps)
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85 | #the inversed parameter is updated as follows:
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86 | #new_par = old_par + gradient_scaling(n) * C * gradient with C in [0 1]
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87 | #usually the gradient_scaling must be of the order of magnitude of the
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88 | #inversed parameter (1.0e8 for B, 50 for drag) and can be decreased
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89 | #after the first iterations
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90 | self.gradient_scaling = 50 * np.ones((self.nsteps, 1))
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91 | #several responses can be used:
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92 | self.cost_functions = [101, ]
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93 | #step_threshold is used to speed up control method. When
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94 | #misfit(1) / misfit(0) < self.step_threshold, we go directly to
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95 | #the next step
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96 | self.step_threshold = 0.7 * np.ones(self.nsteps) #30 per cent decrement
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97 | #cost_function_threshold is a criteria to stop the control methods.
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98 | #if J[n] - J[n - 1] / J[n] < criteria, the control run stops
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99 | #NaN if not applied
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100 | self.cost_function_threshold = np.nan #not activated
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101 | return self
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102 | # }}}
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103 |
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104 | def extrude(self, md): # {{{
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105 | self.vx_obs = project3d(md, 'vector', self.vx_obs, 'type', 'node')
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106 | self.vy_obs = project3d(md, 'vector', self.vy_obs, 'type', 'node')
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107 | self.vel_obs = project3d(md, 'vector', self.vel_obs, 'type', 'node')
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108 | self.thickness_obs = project3d(md, 'vector', self.thickness_obs, 'type', 'node')
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109 | if not np.any(np.isnan(self.cost_functions_coefficients)):
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110 | self.cost_functions_coefficients = project3d(md, 'vector', self.cost_functions_coefficients, 'type', 'node')
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111 | if not np.any(np.isnan(self.min_parameters)):
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112 | self.min_parameters = project3d(md, 'vector', self.min_parameters, 'type', 'node')
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113 | if not np.any(np.isnan(self.max_parameters)):
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114 | self.max_parameters = project3d(md, 'vector', self.max_parameters, 'type', 'node')
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115 | return self
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116 | # }}}
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117 |
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118 | def checkconsistency(self, md, solution, analyses): # {{{
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119 | # Early return
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120 | if not self.iscontrol:
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121 | return md
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122 |
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123 | num_controls = np.size(md.inversion.control_parameters)
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124 | num_costfunc = np.size(md.inversion.cost_functions)
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125 |
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126 | md = checkfield(md, 'fieldname', 'inversion.iscontrol', 'values', [0, 1])
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127 | md = checkfield(md, 'fieldname', 'inversion.incomplete_adjoint', 'values', [0, 1])
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128 | md = checkfield(md, 'fieldname', 'inversion.control_parameters', 'cell', 1, 'values', supportedcontrols())
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129 | md = checkfield(md, 'fieldname', 'inversion.nsteps', 'numel', [1], '>=', 0)
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130 | md = checkfield(md, 'fieldname', 'inversion.maxiter_per_step', 'size', [md.inversion.nsteps], '>=', 0)
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131 | md = checkfield(md, 'fieldname', 'inversion.step_threshold', 'size', [md.inversion.nsteps])
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132 | md = checkfield(md, 'fieldname', 'inversion.cost_functions', 'size', [num_costfunc], 'values', supportedcostfunctions())
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133 | if num_costfunc == 1:
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134 | md.inversion.cost_functions_coefficients = np.squeeze(md.inversion.cost_functions_coefficients)
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135 | md = checkfield(md, 'fieldname', 'inversion.cost_functions_coefficients', 'size', [md.mesh.numberofvertices], '>=', 0)
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136 | else:
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137 | md = checkfield(md, 'fieldname', 'inversion.cost_functions_coefficients', 'size', [md.mesh.numberofvertices, num_costfunc], '>=', 0)
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138 |
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139 | if num_controls == 1:
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140 | md.inversion.gradient_scaling = np.squeeze(md.inversion.gradient_scaling)
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141 | md.inversion.min_parameters = np.squeeze(md.inversion.min_parameters)
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142 | md.inversion.max_parameters = np.squeeze(md.inversion.max_parameters)
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143 | md = checkfield(md, 'fieldname', 'inversion.gradient_scaling', 'size', [md.inversion.nsteps])
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144 | md = checkfield(md, 'fieldname', 'inversion.min_parameters', 'size', [md.mesh.numberofvertices])
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145 | md = checkfield(md, 'fieldname', 'inversion.max_parameters', 'size', [md.mesh.numberofvertices])
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146 | else:
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147 | md = checkfield(md, 'fieldname', 'inversion.gradient_scaling', 'size', [md.inversion.nsteps, num_controls])
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148 | md = checkfield(md, 'fieldname', 'inversion.min_parameters', 'size', [md.mesh.numberofvertices, num_controls])
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149 | md = checkfield(md, 'fieldname', 'inversion.max_parameters', 'size', [md.mesh.numberofvertices, num_controls])
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150 |
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151 | # Only SSA, HO and FS are supported right now
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152 | if solution == 'StressbalanceSolution':
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153 | if not (md.flowequation.isSSA or md.flowequation.isMOLHO or md.flowequation.isHO or md.flowequation.isFS or md.flowequation.isL1L2):
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154 | md.checkmessage("'inversion can only be performed for SSA, MOLHO, HO or FS ice flow models")
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155 | if solution == 'BalancethicknessSolution':
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156 | md = checkfield(md, 'fieldname', 'inversion.thickness_obs', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1)
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157 | elif solution == 'BalancethicknessSoftSolution':
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158 | md = checkfield(md, 'fieldname', 'inversion.thickness_obs', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1)
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159 | else:
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160 | md = checkfield(md, 'fieldname', 'inversion.vx_obs', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1)
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161 | md = checkfield(md, 'fieldname', 'inversion.vy_obs', 'size', [md.mesh.numberofvertices], 'NaN', 1, 'Inf', 1)
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162 | return md
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163 | # }}}
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164 |
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165 | def marshall(self, prefix, md, fid): # {{{
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166 | yts = md.constants.yts
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167 |
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168 | WriteData(fid, prefix, 'name', 'md.inversion.type', 'data', 0, 'format', 'Integer')
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169 | WriteData(fid, prefix, 'object', self, 'fieldname', 'iscontrol', 'format', 'Boolean')
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170 | WriteData(fid, prefix, 'object', self, 'fieldname', 'incomplete_adjoint', 'format', 'Boolean')
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171 | WriteData(fid, prefix, 'object', self, 'fieldname', 'vel_obs', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts)
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172 | if not self.iscontrol:
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173 | return
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174 | WriteData(fid, prefix, 'object', self, 'fieldname', 'nsteps', 'format', 'Integer')
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175 | WriteData(fid, prefix, 'object', self, 'fieldname', 'maxiter_per_step', 'format', 'IntMat', 'mattype', 3)
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176 | WriteData(fid, prefix, 'object', self, 'fieldname', 'cost_functions_coefficients', 'format', 'DoubleMat', 'mattype', 1)
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177 | WriteData(fid, prefix, 'object', self, 'fieldname', 'gradient_scaling', 'format', 'DoubleMat', 'mattype', 3)
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178 | WriteData(fid, prefix, 'object', self, 'fieldname', 'cost_function_threshold', 'format', 'Double')
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179 | WriteData(fid, prefix, 'object', self, 'fieldname', 'min_parameters', 'format', 'DoubleMat', 'mattype', 3)
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180 | WriteData(fid, prefix, 'object', self, 'fieldname', 'max_parameters', 'format', 'DoubleMat', 'mattype', 3)
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181 | WriteData(fid, prefix, 'object', self, 'fieldname', 'step_threshold', 'format', 'DoubleMat', 'mattype', 3)
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182 | WriteData(fid, prefix, 'object', self, 'fieldname', 'vx_obs', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts)
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183 | WriteData(fid, prefix, 'object', self, 'fieldname', 'vy_obs', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts)
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184 | WriteData(fid, prefix, 'object', self, 'fieldname', 'vz_obs', 'format', 'DoubleMat', 'mattype', 1, 'scale', 1. / yts)
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185 | WriteData(fid, prefix, 'object', self, 'fieldname', 'thickness_obs', 'format', 'DoubleMat', 'mattype', 1)
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186 | WriteData(fid, prefix, 'object', self, 'fieldname', 'surface_obs', 'format', 'DoubleMat', 'mattype', 1)
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187 |
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188 | # Process control parameters
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189 | num_control_parameters = len(self.control_parameters)
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190 | WriteData(fid, prefix, 'object', self, 'fieldname', 'control_parameters', 'format', 'StringArray')
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191 | WriteData(fid, prefix, 'data', num_control_parameters, 'name', 'md.inversion.num_control_parameters', 'format', 'Integer')
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192 |
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193 | # Process cost functions
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194 | num_cost_functions = np.size(self.cost_functions)
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195 | data = marshallcostfunctions(self.cost_functions)
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196 | WriteData(fid, prefix, 'data', data, 'name', 'md.inversion.cost_functions', 'format', 'StringArray')
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197 | WriteData(fid, prefix, 'data', num_cost_functions, 'name', 'md.inversion.num_cost_functions', 'format', 'Integer')
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198 | # }}}
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