forked from pyrocko/grond
docs: polish, added reports
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#!/bin/bash
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set -e
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DATA_PATH="data/events/2009laquila/insar/"
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mkdir -p $DATA_PATH
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EVENT_PATH="data/events/2009laquila"
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INSAR_PATH="$EVENT_PATH/insar/"
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mkdir -p $EVENT_PATH
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mkdir -p $INSAR_PATH
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wget http://data.pyrocko.org/examples/2009-LAquila-InSAR/README -P $DATA_PATH
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wget http://data.pyrocko.org/examples/2009-LAquila-InSAR/asc_insar.npz -P $DATA_PATH
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wget http://data.pyrocko.org/examples/2009-LAquila-InSAR/asc_insar.yml -P $DATA_PATH
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wget http://data.pyrocko.org/examples/2009-LAquila-InSAR/dsc_insar.npz -P $DATA_PATH
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wget http://data.pyrocko.org/examples/2009-LAquila-InSAR/dsc_insar.yml -P $DATA_PATH
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wget http://data.pyrocko.org/examples/2009-LAquila-InSAR/README -P $INSAR_PATH
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wget http://data.pyrocko.org/examples/2009-LAquila-InSAR/asc_insar.npz -P $INSAR_PATH
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wget http://data.pyrocko.org/examples/2009-LAquila-InSAR/asc_insar.yml -P $INSAR_PATH
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wget http://data.pyrocko.org/examples/2009-LAquila-InSAR/dsc_insar.npz -P $INSAR_PATH
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wget http://data.pyrocko.org/examples/2009-LAquila-InSAR/dsc_insar.yml -P $INSAR_PATH
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wget http://data.pyrocko.org/examples/2009-LAquila-InSAR/dsc_insar.yml -P $INSAR_PATH
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wget http://data.pyrocko.org/examples/2009-LAquila-InSAR/event.txt -P $EVENT_PATH
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@ -1,62 +1,197 @@
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--- !grond.Config
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path_prefix: ..
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rundir_template: rundir/${problem_name}.grun
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# All file paths referenced below are treated relative to the location of this
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# configuration file, here we may give a common prefix. E.g. setting it to '..'
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# if the configuration file is in the sub-directory '${project_root}/config'
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# allows us to give the paths below relative to '${project_root}'.
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path_prefix: '..'
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# Path, where to store output (run directories). The placeholder
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# '${problem_name}' will be expanded to a name configured below in
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# problem_config.name_template and will typically include a config identifier
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# and the event name.
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rundir_template: runs/${problem_name}.grun
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# If given, restrict to processing of listed events
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#event_names:
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#- 'gfz2018pmjk'
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# -----------------------------------------------------------------------------
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# Configuration section for dataset (input data)
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#
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# The placeholder '${event_name}' will be expanded to the current event. This
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# enables us to use the same configuration for multiple events. The available
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# events are detected by looking into possible expansions of
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# dataset_config.events_path
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# -----------------------------------------------------------------------------
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dataset_config: !grond.DatasetConfig
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events_path: event.txt
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extend_incomplete: false
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picks_paths: []
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blacklist_paths: []
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blacklist: []
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whitelist_paths: []
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kite_scene_paths: [insar]
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# File with hypocenter information and possibly reference solution
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events_path: 'data/events/${event_name}/event.txt'
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# List of directories for the InSAR scenes
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kite_scene_paths: ['data/events/${event_name}/insar']
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# -----------------------------------------------------------------------------
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# Configuration section for the observational data fitting
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#
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# This defines the objective function to be minimized in the optimisation. It
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# can be composed of one or more contributions, each represented by a
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# !grond.*TargetGroup section.
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# -----------------------------------------------------------------------------
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target_groups:
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- !grond.SatelliteTargetGroup
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normalisation_family: static
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path: all
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# Normalisation family (see the Grond documentation for how it works).
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# Use distinct normalisation families when mixing misfit contributors with
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# different magnitude scaling, like e.g. cross-correlation based misfit and
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# time-domain Lx norm.
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normalisation_family: 'static'
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# Just a name used to identify targets from this group. Use dot-separated path
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# notation to group related contributors
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path: 'insar'
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# How to weight contributions from this group in the global misfit
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weight: 1.0
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# Selector for kite scene ids, '*all' is a wildcard and load all scenes present
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kite_scenes: ['*all']
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# Subsection on how to fit the traces
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misfit_config: !grond.SatelliteMisfitConfig
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# Optimise a planar orbital ramp
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optimise_orbital_ramp: false
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# Parameters for the orbital ramp
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ranges:
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# Vertical offset in [m]
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offset: -0.5 .. 0.5
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# Ranges for the East-West and North-South inclination of the ramp
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ramp_east: -1e-4 .. 1e-4
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ramp_north: -1e-4 .. 1e-4
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# How to interpolate the Green's functions (available choices:
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# 'nearest_neighbor', 'multilinear'). Choices other than 'nearest_neighbor'
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# may require dense GF stores to avoid aliasing artifacts in the forward
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# modelling.
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interpolation: multilinear
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# Name of the GF Store to use
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store_id: crust2_ib_static
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# -----------------------------------------------------------------------------
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# Definition of the problem to be solved
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#
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# In this section the source model to be fitted is chosen, the parameter space
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# defined, and how to combine the misfit contributions defined in the
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# target_groups section above.
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#
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# The marker !grond.RectangularProblemConfig selects a finite rectancular
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# source model.
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# -----------------------------------------------------------------------------
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problem_config: !grond.RectangularProblemConfig
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name_template: rect_source
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# Name used to identify the output
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name_template: rect_2009LaAquila
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# How to combine the target misfits. For L1 norm: 1, L2 norm: 2, etc.
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norm_exponent: 2
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# Definition of model parameter space to be searched in the optimisation
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ranges:
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# Scaling ranges in [m]
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depth: 2500 .. 7000
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dip: 10 .. 50
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east_shift: 0 .. 20000
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length: 5000 .. 10000
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north_shift: 0 .. 20000
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rake: 120 .. 360
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length: 5000 .. 10000
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width: 2000 .. 10000
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slip: .2 .. 2
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# Orientation ranges in [deg]
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dip: 10 .. 50
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rake: 120 .. 360
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strike: 220 .. 360
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width: 2000 .. 10000
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# We are using a dense GF store and will reduce the number of discrete
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# subsources by this factor. Decrease the decimation for a finer sub-source
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# resolution, and increased computational time
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decimation_factor: 12
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# Clearance distance around stations (no models with origin closer than this
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# distance to any station are produced by the sampler)
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distance_min: 0.0
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# -----------------------------------------------------------------------------
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# Configuration of pre-optimisation analysis phases.
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# determined during this phase.
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# -----------------------------------------------------------------------------
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#
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analyser_configs:
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# DOES NOT APPLY FOR INSAR! Balancing weights are determined with this analyser
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- !grond.TargetBalancingAnalyserConfig
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niterations: 1000
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# -----------------------------------------------------------------------------
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# Configuration of the optimisation procedure
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# -----------------------------------------------------------------------------
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optimiser_config: !grond.HighScoreOptimiserConfig
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# Number of bootstrap realisations to be tracked simultaneously in the
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# optimisation
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nbootstrap: 25
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# Stages of the sampler then narrow down to the interesting regions
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# (!grond.DirectedSamplerPhase).
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sampler_phases:
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# Start with uniform sampling of the model space
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- !grond.UniformSamplerPhase
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# Number of iterations
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niterations: 10000
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# How often we shall try to find a valid sample
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ntries_preconstrain_limit: 1000
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# Narrow down to the interesting regions
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- !grond.DirectedSamplerPhase
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# Number of iterations
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niterations: 40000
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# How often we shall try to find a valid sample
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ntries_preconstrain_limit: 1000
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# Multiplicator for width of sampler distribution at start of this phase
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scatter_scale_begin: 2.0
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# Multiplicator for width of sampler distribution at end of this phase
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scatter_scale_end: 0.5
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starting_point: excentricity_compensated
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sampler_distribution: normal
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standard_deviation_estimator: median_density_single_chain
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ntries_sample_limit: 2000
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# This parameter determines the length of the chains
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chain_length_factor: 8.0
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nbootstrap: 25
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# -----------------------------------------------------------------------------
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# Configuration section for synthetic seismogram engine
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#
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# Configures where to look for GF stores.
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# -----------------------------------------------------------------------------
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engine_config: !grond.EngineConfig
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# Whether to use GF store directories listed in ~/.pyrocko/config.pf
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gf_stores_from_pyrocko_config: true
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gf_store_superdirs: [.]
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gf_store_dirs: []
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event_names: []
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# List of directories with GF stores
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gf_store_superdirs: ['gf_stores']
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