NA_options
Contents
Data Structure: NA_options |
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Description |
NA inversion algorithm control data |
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NA_options NUM=ival where ival is the data structure number |
Description |
Overview The NA_options data structure defines the control options for the nearest neighbour inverse identification algorithm, also known as the Neighbourhood (NA) Algorithm.
References •M. Sambridge, 1999a. Geophysical inversion with a neighbourhood algorithm - I. Searching the parameter space. Geophys. J. Int. , Vo.138, p.479-494. •M. Sambridge, 1999b. Geophysical inversion with a neighbourhood algorithm - II. Appraising the ensemble. Geophys. J. Int. , Vo.138, p.727-746.
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 | Algorithm Solution algorithm |
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Valid solution algorithms are: •"Fixed" - Fixed number of iterations (models) •"Auto" - Termination once the convergence tolerance is reached
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| Maximum_num_samples Number of iterations |
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Number of iterations for the nearest neighbour inverse algorithm (default 20).
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| Num_models_in_initial_sample Number of samples in the initial set |
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Number of samples in the initial set. This must be greater or equal to the number of samples for subsequent iterations. By default Num_models_in_initial_sample = Num_models_in_sample
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| Num_models_in_sample Sample size for each subsequent iteration |
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Sample size for each subsequent iteration (Default 10)
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| Num_models_in_resample Number of samples for neighbourhood resampling |
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Number of samples for neighbourhood resampling ( nr ). The parameter nr influences the nature of the neighbourhood algorithm search; i.e. for larger values, the sampling is spread over more cells, and so that the algorithm is exploratory in nature, conversely smaller values it is restricted to fewer cells and the sampling is more localized. By default default the number of resamples is set to half the number of samples. i.e. on the subsequent iteration two new samples will be generated in the most optimal half of the current sample set.
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| Convergence_tolerance Convergence tolerance for inversion |
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If Convergence_tolerance is specified then the iterative process is terminated once a model with a misfit below the Convergence_tolerance. If Convergence_tolerance is not specified then the specified Maximum_num_samples will be performed.
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| Number_models_output Number of samples for neighbourhood resampling |
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Number of best models for output to the output file. The models are output in order of minimum misfit error
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| Model_delete_option Flag to denote whether the model results should be saved or deleted |
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Model_delete_option defines whether the model results should be saved or deleted. Valid options are: •"DeleteAll" - Delete all model files •"KeepAll" - Keep all model files •"KeepBest" - (default) delete files with extensions specified using the keyword Model_results_keep. If k1 Model_results_keep is not defined the default is to delete all files with the exception of data files, history files and error files |
| Model_clean_option Flag to denote which model result files should be saved or deleted |
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Model_delete_option defines whether the model result files to besaved or deleted. Valid options are: •"KeepAll" - keep all models (default) •"KeepSpec" - delete all models |
| Model_results_keep List of output file types to be kept |
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Model_results_keep defines a list of file types to be kept. For ParaGeo applications, by default all output files are deleted with exception of data, history and error files.
Notes The list of file types to be kept can include: •"History" - History files •"Geometry" - Geometry plot files •"PlotFile" - Result plot files •"Grid" - Grid plot files •"Mesh" - Mesh plot files •"Result" - Result plot files •"Restart" - Restart files
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| Output_level Output level for log file |
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Output level for log file. Valid values are: •0 - Minimum output •1 - Standard •2 - Verbose (default) |
| Output_screen_level Output level for screen |
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Output level for screen. Valid values are: •0 - Minimum output •1 - Standard (default) •2 - Verbose |