Skip to content

GitLab

Commit a06f0c50 authored by Sebastian Heimann's avatar Sebastian Heimann
Browse files

updated readme

parent ade8e28f
Hide whitespace changes
Inline Side-by-side
README.md
View file @ a06f0c50
......@@ -19,7 +19,7 @@ sudo python setup.py install
## Updating an existing installation
```bash
cd grond # change to the directory where you cloned grond to initially
cd grond # change to the directory to where you cloned grond initially
git pull origin master
sudo python setup.py install
```
......@@ -30,16 +30,17 @@ sudo python setup.py install
Grond can be run as a command line tool or by calling Grond's library functions
from a Python script. To get a brief description on available options of
Grond's command line tool, run `grond --help` or `grond <subcommand> --help`.
Once dataset and configuration are ready, the command
`grond go <configfile> <eventname>` starts the optimization algorithm for a
selected event. Before running the optimization, to debug problems with the
dataset and configuration, use `grond check <configfile> <eventname>`. To get
a list of event names available in a configured setup, run
`grond events <configfile>`.
During the optimization, results are aggregated in a directory,
referred to in the configuration as `<rundir>`. To visualize the results run
`grond plot <plotnames> <rundir>`. The results can be exported in various way
by running the subcommand `grond export <what> <rundir>`.
Once dataset and configuration are ready, the command `grond go <configfile>
<eventname>` starts the optimization algorithm for a selected event. Before
running the optimization, to debug problems with the dataset and configuration,
use `grond check <configfile> <eventname>`. To get a list of event names
available in a configured setup, run `grond events <configfile>`. During the
optimization, results are aggregated in a directory, referred to in the
configuration as `<rundir>`. To visualize the results run `grond plot
<plotnames> <rundir>`. The results can be exported in various ways by running
the subcommand `grond export <what> <rundir>`. Finally, you may run `grond
report <rundir>` to aggregate results to a browsable summary, (by default)
under the directory `reports`.
## Example configuration file
......@@ -51,7 +52,6 @@ by running the subcommand `grond export <what> <rundir>`.
# Path, where to store output (run-directories)
rundir_template: 'gruns/${problem_name}.run'
# -----------------------------------------------------------------------------
# Configuration section for dataset (input data)
# -----------------------------------------------------------------------------
......@@ -60,22 +60,31 @@ dataset_config: !grond.DatasetConfig
# List of files with station coordinates
stations_stationxml_paths:
- 'events/${event_name}/responses.stationxml'
- 'events/${event_name}/responses-geofon.stationxml'
- 'events/${event_name}/responses-iris.stationxml'
# File with hypocenter information and possibly reference solution
events_path: 'events/${event_name}/event.txt'
events_path: 'events/${event_name}/prepared/event.txt'
# List of directories with raw waveform data
waveform_paths:
- 'data/${event_name}/raw'
- 'events/${event_name}/raw'
# List of files with instrument response information
responses_stationxml_paths:
- 'meta/${event_name}/responses.stationxml'
- 'events/${event_name}/responses-geofon.stationxml'
- 'events/${event_name}/responses-iris.stationxml'
# List with station/channel codes to exclude
blacklist: [OTAV, RCBR, PTGA, AXAS2, SNAA, PAYG, RAR, SDV, VAL, XMAS, ODZ,
Z51A, MSVF, SHEL, SUR, ROSA, 'IU.PTCN.00.T', 'C1.VA02..T', RPN]
#blacklist: ['STA','NET.STA', 'NET.STA.LOC', 'NET.STA.LOC.CHA']
# Same but using a file, one exclusion entry per line
blacklist_paths:
- 'events/${event_name}/blacklist.txt'
# Make available picks for forced trace alignment, file must be in Pyrocko's
# marker file format
#picks_paths: ['events/${event_name}/picks.markers']
# -----------------------------------------------------------------------------
......@@ -100,21 +109,21 @@ engine_config: !grond.EngineConfig
# represented by a !grond.TargetConfig section.
# -----------------------------------------------------------------------------
target_configs:
target_groups:
- !grond.TargetConfig
- !grond.WaveformTargetGroup
# Name of the super-group to which this contribution belongs
super_group: 'time_domain'
# misfits are normalized within each normalization_family separately
normalization_family: 'td'
# Name of the group to which this contribution belongs
group: 'rayleigh'
path: 'td.rayleigh'
# Minimum distance of stations to be considered
distance_min: 1000e3
distance_min: 0e3
# Maximum distance of stations to be considered
distance_max: 10000e3
distance_max: 1000e3
# List with names of channels to be considered
channels: ['Z']
......@@ -123,52 +132,75 @@ target_configs:
weight: 1.0
# Subsection on how to fit the traces
inner_misfit_config: !grond.InnerMisfitConfig
misfit_config: !grond.WaveformMisfitConfig
# Frequency band [Hz] of acausal filter (flat part of frequency taper)
fmin: 0.002
fmax: 0.008
fmin: 0.01
fmax: 0.05
# Factor defining fall-off of frequency taper
# (zero at fmin/ffactor, fmax*ffactor)
ffactor: 1.5
# Time window to include in the data fitting. Times can be defined offset
# to given phase arrivals. E.g. 'begin-100' would mean 100 s before arrival
# of the phase named 'begin', which must be defined in the travel time
# tables in the GF store.
tmin: '{stored:begin}-100'
tmax: '{stored:end}+100'
# to given phase arrivals. E.g. '{stored:begin}-100' would mean 100 s
# before arrival of the phase named 'begin', which must be defined in the
# travel time tables in the GF store.
tmin: '{stored:anyP_no_Pdiff}'
tmax: '{vel_surface:2.5}'
# Align traces by picks (will lose some control on origin time and
# location). Define the synthetic phasename, for which a travel time table
# must be available in the GF store,
#pick_synthetic_traveltime: 'anyP_no_Pdiff'
# and the name of the picks to use in the picks file (defined in
# dataset_config)
#pick_phasename: 'P'
# How to fit the data (available choices: 'time_domain',
# 'frequency_domain', 'absolute', 'envelope', 'cc_max_norm')
domain: 'time_domain'
# allow for some time-shifting of individual traces, maximum shift [s]
tautoshift_max: 4.0
# whether to penalise time-shifting (0.0 for no penalty)
autoshift_penalty_max: 0.0
# exponent of the norm used when comparing traces, 1 or 2
norm_exponent: 1
# How to interpolate the Green's functions (available choices:
# 'nearest_neighbor', 'multilinear')
# 'nearest_neighbor', 'multilinear'). Note that the GFs have to be densely
# sampled when using interpolation other than nearest_neighbor.
interpolation: 'nearest_neighbor'
# Name of GF store to use
store_id: 'global_20s_shallow'
store_id: 'global_2s'
# A second contribution to the misfit function (for descriptions, see above)
- !grond.TargetConfig
super_group: 'time_domain'
group: 'love'
distance_min: 1000e3
distance_max: 10000e3
channels: ['T']
- !grond.WaveformTargetGroup
normalisation_family: 'td'
path: 'td.love'
distance_min: 0e3
distance_max: 1000e3
channels: [T]
weight: 1.0
inner_misfit_config: !grond.InnerMisfitConfig
fmin: 0.002
fmax: 0.008
#limit: 20
misfit_config: !grond.WaveformMisfitConfig
fmin: 0.01
fmax: 0.05
ffactor: 1.5
tmin: '{stored:begin}-100'
tmax: '{stored:end}+100'
domain: 'time_domain'
interpolation: 'nearest_neighbor'
store_id: 'global_20s_shallow'
tmin: 'stored:anyP_no_Pdiff'
tmax: 'vel_surface:2.5'
domain: time_domain
tautoshift_max: 4.0
autoshift_penalty_max: 0.0
norm_exponent: 1
interpolation: nearest_neighbor
store_id: 'global_2s'
# -----------------------------------------------------------------------------
......@@ -179,20 +211,20 @@ target_configs:
problem_config: !grond.CMTProblemConfig
# Name used when creating output directory
name_template: 'cmt_surface_wave_${event_name}'
name_template: 'timedomain_${event_name}'
# Definition of model parameter space to be searched in the optimization
ranges:
# Time relative to hypocenter origin time [s]
time: '-100 .. 100 | add'
time: '-10 .. 10 | add'
# Centroid location with respect to hypocenter origin [m]
north_shift: '-200e3 .. 200e3'
east_shift: '-200e3 .. 200e3'
north_shift: '-40e3 .. 40e3'
east_shift: '-40e3 .. 40e3'
depth: '0 .. 50e3'
# Range of magnitudes to allow
magnitude: '7.0 .. 9.0'
magnitude: '4.0 .. 7.0'
# Relative moment tensor component ranges (don't touch)
rmnn: '-1.41421 .. 1.41421'
......@@ -203,16 +235,12 @@ problem_config: !grond.CMTProblemConfig
rmed: '-1 .. 1'
# Source duration range [s]
duration: '30. .. 120.'
duration: '0. .. 0.'
# Clearance distance around stations (no models with origin closer than this
# distance to any station are produced by the sampler)
distance_min: 0.
# Number of bootstrap realizations to be tracked simultaneously in the
# optimization
nbootstrap: 100
# Type of moment tensor to restrict to (choices: 'full', 'deviatoric')
mt_type: 'deviatoric'
......@@ -220,38 +248,44 @@ problem_config: !grond.CMTProblemConfig
# spreading etc.
apply_balancing_weights: true
# Under what norm to combine targets into the global misfit
# (exponent of norm, 1 or 2)
norm_exponent: 1
nbootstrap: 100
# -----------------------------------------------------------------------------
# Configuration of the optimization procedure
# -----------------------------------------------------------------------------
solver_config: !grond.SolverConfig
# Distribution used when drawing new candidate models (choices: 'normal',
# 'multivariate_normal') (used in 'transition', 'explorative', and
# 'non_explorative' phase)
sampler_distribution: 'normal'
# This configuration will run the BABO (Bayesian Bootstrap) optimization
optimizer_config: !grond.HighScoreOptimizerConfig
# Number of bootstrap realizations to be tracked simultaneously in the
# optimization
nbootstrap: 100
sampler_phases:
# Number of iterations to operate in 'uniform' mode
niter_uniform: 1000
- !grond.UniformSamplerPhase
# Number of iterations to operate in 'transition' mode
niter_transition: 2000
# Number of iterations to operate in 'uniform' phase
niterations: 1000
# Number of iterations to operate in 'explorative' mode
niter_explorative: 2000
- !grond.DirectedSamplerPhase
# Number of iterations to operate in 'non_explorative' mode
niter_non_explorative: 0
# Number of iterations to operate in 'directed' phase
niterations: 10000
# Multiplicator for width of sampler distribution in 'explorative' and
# 'non-explorative' phases
scatter_scale: 0.25
# Multiplicator for width of sampler distribution at end of this phase
scatter_scale_begin: 2.0
# Multiplicator for width of sampler distribution at start of 'transition'
# phase. (From there, it exponentially decreases to the value defined in
# 'scatter_scale' during the 'transition' phase).
scatter_scale_transition: 2.
# Multiplicator for width of sampler distribution at end of this phase
scatter_scale_end: 0.5
# -----------------------------------------------------------------------------
......@@ -263,5 +297,5 @@ analyser_config: !grond.AnalyserConfig
# Number of iterations (number of models to forward model in the analysis,
# larger number -> better statistics)
niter: 1000
niterations: 1000
```
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment