diff --git a/CHANGELOG.md b/CHANGELOG.md new file mode 100644 index 0000000..a16859b --- /dev/null +++ b/CHANGELOG.md @@ -0,0 +1,19 @@ +# PySEP Changelog + +## Version 0.2.0 (Master) + +- RecSec plot aesthetics altered to provide more information efficiently +- Shifted documentation to GitHub Wiki page +- Added moment tensor gathering routines from Pyatoa + +## Version 0.3.0 (Devel) + +- Removed llnl_db_client dependency from package and made it optional +- Re-instated 'mass_downloader' option +- Added `Declust` class for declustering and weighting +- Completed and re-organized PySEP and RecSec docstrings +- Bugfix: rotation was not able to be set as null +- Bugfix: some flag check parameters were not being used during processing +- Removed hard restriction on requiring event depth and magnitude for default event selection +- Add feature 'tmarks' to record section to plot vertical lines at reference times +- Fix ordering of multi-page record sections when using plotw_rs diff --git a/docs/Makefile b/docs/Makefile new file mode 100644 index 0000000..d4bb2cb --- /dev/null +++ b/docs/Makefile @@ -0,0 +1,20 @@ +# Minimal makefile for Sphinx documentation +# + +# You can set these variables from the command line, and also +# from the environment for the first two. +SPHINXOPTS ?= +SPHINXBUILD ?= sphinx-build +SOURCEDIR = . +BUILDDIR = _build + +# Put it first so that "make" without argument is like "make help". +help: + @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) + +.PHONY: help Makefile + +# Catch-all target: route all unknown targets to Sphinx using the new +# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). +%: Makefile + @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) diff --git a/docs/conf.py b/docs/conf.py new file mode 100644 index 0000000..61335b0 --- /dev/null +++ b/docs/conf.py @@ -0,0 +1,60 @@ +# Configuration file for the Sphinx documentation builder. +# +# For the full list of built-in configuration values, see the documentation: +# https://www.sphinx-doc.org/en/master/usage/configuration.html + +def skip(app, what, name, obj, would_skip, options): + if name == "__init__": + return False + return would_skip + +def setup(app): + app.connect("autodoc-skip-member", skip) + +# -- Project information ----------------------------------------------------- +# https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information + +project = 'PySEP' +copyright = '2023, adjTomo Dev Team' +author = 'adjTomo Dev Team' +release = '' +version = '0.2.0' + +# -- General configuration --------------------------------------------------- +# https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration + +extensions = [ + 'sphinx.ext.doctest', + 'sphinx.ext.intersphinx', + 'sphinx.ext.todo', + 'sphinx.ext.coverage', + 'sphinx.ext.viewcode', + 'sphinx.ext.napoleon', + 'sphinx.ext.autosummary', + "autoapi.extension", + "myst_parser" + ] + +templates_path = ['_templates'] +exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store'] + +# Need to tell the autoapi that our source code is one level up +autoapi_type = "python" +autoapi_dirs = [ + "../pysep", + "../pysep/utils", + "../pysep/tests" + ] +autoapi_add_toctree_entry = True +autoapi_python_class_content = 'both' +# autoclass_content = 'both' # show init + +source_suffix = {'.rst': 'restructuredtext', + '.md': 'markdown'} + + +# -- Options for HTML output ------------------------------------------------- +# https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output + +html_theme = 'furo' +html_static_path = ['_static'] diff --git a/docs/cookbook.md b/docs/cookbook.md new file mode 100644 index 0000000..0a3ee6a --- /dev/null +++ b/docs/cookbook.md @@ -0,0 +1,250 @@ +# Cookbook + +Here we provide some code snippets using PySEP routines or utilities to perform +tasks useful for manipulating or preparing data for moment tensor and waveform +inversion software. + +## Create STATIONS file for SPECFEM + +SPECFEM requires a STATIONS file that defines geographical coordinates of stations that +will be used in a simulation. Using PySEP and ObsPy, you can quickly generate a STATIONS +file for a given region + +```python +from obspy import UTCDateTime +from obspy.clients.fdsn import Client +from pysep.utils.io import write_stations_file + +c = Client("IRIS") +# This is for the region of northern Alaska, broadband seismometers only +# collecting online stations from Jan. 1, 2000 until present time +inv = c.get_stations(network="*", station="*", + channel="BH?,BL?,HH?,HL?", + minlatitude=64.5, maxlatitude=72., + minlongitude=-168., maxlongitude=-140., + level="station", + starttime=UTCDateTime("2000-01-01T00:00:00"), + endtime=UTCDateTime() + ) + +# Write 'STATIONS' file, ordered alphabetically by station name +write_specfem_stations_file(inv, fid="STATIONS", order_by="station") +``` + +``` +$ head STATIONS + A19K AK 70.2043 -161.0713 0.0 0.0 + A21K AK 71.3221 -156.6175 0.0 0.0 + A22K AK 71.0033 -154.9742 0.0 0.0 + ANM AK 64.5646 -165.3732 0.0 0.0 + B18K AK 69.3641 -161.8016 0.0 0.0 + B20K AK 70.0079 -157.1599 0.0 0.0 + B22K AK 70.3400 -153.4196 0.0 0.0 + C16K AK 68.2746 -165.3436 0.0 0.0 + C18K AK 68.6483 -161.1943 0.0 0.0 + C19K AK 69.1049 -159.5874 0.0 0.0 + +``` + +## Fetch moment tensors as CMTSOLUTION files + +It's often useful to gather a catalog of events and their moment tensors as a starting point +for waveform inversion. PySEP has some built in moment tensor routines that can help us +with that. + +### From the GCMT catalog + +This routine queries the GCMT catalog for moment tensors matching a given origin time and +magnitude. Given an example event, we can return a Catalog object containing the GCMT +moment tensor. Taking this [M6.4 in northern Alaska](https://earthquake.alaska.edu/event/018aap2cqu) as an example. + +```python +from obspy import UTCDateTime +from pysep.utils.mt import get_gcmt_moment_tensor + +origintime = UTCDateTime("2018-08-12T14:58:53") +magnitude=6.4 +cat = get_gcmt_moment_tensor(origintime=origintime, magnitude=magnitude) +cat.write("CMTSOLUTION_GCMT", format="CMTSOLUTION") +``` + +``` +$ cat CMTSOLUTION_GCMT + PDE 2018 08 12 14 58 54.30 69.5600 -145.3000 2.2 6.4 6.4 NORTHERN ALASKA +event name: C201808121458A +time shift: 7.9000 +half duration: 4.0000 +latitude: 69.7400 +longitude: -144.7800 +depth: 12.0000 +Mrr: -7.690000E+24 +Mtt: -1.990000E+25 +Mpp: 2.760000E+25 +Mrt: 4.890000E+24 +Mrp: -1.510000E+25 +Mtp: -4.730000E+25 +``` + +### From USGS Catalog + +Using the event we grabbed in the previous section (from GCMT), we can query +the USGS catalog for their moment tensor solution. + +>__NOTE__: USGS moment tensor searches are more strict and require an existing + Event object from which it takes the hypocentral location, origin time and magnitude + +```python +# Continuing from codeblock above +from pysep.utils.mt import get_usgs_moment_tensor + +cat = get_usgs_moment_tensor(event=cat[0]) +cat.write("CMTSOLUTION_USGS", format="CMTSOLUTION") +UserWarning: Moment tensor has no source time function. Half duration will be set to 1.0. +``` + +``` +$ cat CMTSOLUTION_USGS + PDE 2018 08 12 14 58 53.50 69.5762 -145.2910 15.8 6.4 6.4 NORTHERN ALASKA +event name:89 km SW of Kaktovik, Alaska +time shift: -0.2030 +half duration: 1.0000 +latitude: 69.6864 +longitude: -144.8187 +depth: 11.5000 +Mrr: -1.015100E+25 +Mtt: -1.644300E+25 +Mpp: 2.659300E+25 +Mrt: -8.487000E+24 +Mrp: -1.468700E+25 +Mtp: -4.792400E+25 +``` + +### From GeoNet Catalog (New Zealand) + +For those working with New Zealand data, it is possible to grab +moment tensor data from [John Ristau's catalog](https://github.com/GeoNet/data/tree/main/moment-tensor). +For these events you will need to provide a corresponding GeoNet event id. +We'll take [event 2018p130600](https://www.geonet.org.nz/earthquake/2018p130600) as an example. + +```python +from obspy.clients.fdsn import Client +from pysep.utils.mt import get_geonet_mt + +c = Client("GEONET") +cat = c.get_events(eventid="2018p130600") +focal_mechanism = get_geonet_mt(event_id="2018p130600", units="nm") # units can also be dynecm +cat[0].focal_mechanisms = [focal_mechanism] +cat.write("CMTSOLUTION_GEONET", format="CMTSOLUTION") +``` +``` +$ cat CMTSOLUTION_GEONET + PDE 2018 02 18 07 43 48.13 -39.9490 176.2995 20.6 5.2 5.2 NORTH ISLAND, NEW ZEALAND +event name: 8E23C1 +time shift: 0.0000 +half duration: 0.6989 +latitude: -39.9490 +longitude: 176.2995 +depth: 20.5946 +Mrr: -2.479380E+23 +Mtt: 1.314880E+23 +Mpp: 1.164500E+23 +Mrt: 5.032500E+22 +Mrp: 6.607700E+22 +Mtp: 9.359300E+22 +``` +------------------------- + +## Convert SPECFEM-generated synthetics to SAC files + +Some may find it useful to convert synthetic seismograms into SAC files to simplify later processing. +The following code snippet will write out SAC files on a per-component basis for synthetics generated +in a geographic coordinate system (lat/lon) from SPECFEM2D, 3D or 3D_GLOBE. + +>__NOTE:__ The `read_sem` function automatically appends SAC headers using the provided metadata + +```python +# cd path/to/specfem_workdir +from glob import glob +from pysep.utils.io import read_sem + +for fid in glob("./OUTPUT_FILES/*sem*): + st = read_sem(fid=fid, source="./DATA/CMTSOLUTION", stations="./DATA/STATIONS") + st.write(os.path.basename(fid), format="SAC") +``` + +If your synthetics were generated in a Cartesian coordinate system (XYZ) you will need to use a +separate function, as ObsPy does not like coordinate systems that do not adhere to WGS84 + +```python +# cd path/to/specfem_workdir +from glob import glob +from pysep.utils.io import read_sem_cartesian + +for fid in glob("./OUTPUT_FILES/*sem*): + st = read_sem_cartesian(fid=fid, source="./DATA/CMTSOLUTION", stations="./DATA/STATIONS") + st.write(f"{st[0].get_id()}.sac", format="SAC") +``` + +------------------------- + +## Append SAC headers to existing Streams + +To append SAC headers to your own seismic data, you can directly use the +`PySEP` utility functions `append_sac_headers` and +`format_sac_header_w_taup_traveltimes` + +```python +from obspy import read, read_events, read_inventory +from pysep.utils.cap_sac import append_sac_headers, format_sac_header_w_taup_traveltimes + +st = read() +inv = read_inventory() +event = read_events()[0] +st = append_sac_headers(st=st, inv=inv, event=event) +st = format_sac_header_w_taup_traveltimes(st=st, model="ak135") +``` + +------------------------- + +## Set custom order on output station file + +PySEP creates a text file for stations gathered. This list contains station IDs, coordinates, +epicentral distance and azimuth from a given event. By default, this list is ordered by the +internal order of the station metadata (usually alphabetical). + +Users can set the order of this station list by specifying the `order_stations_by` parameter. +This is provided as a keyword argument to the initiation of PySEP and can be set with: + +```bash +pysep -c pysep_config.yaml --order_stations_list_by distance +``` + +Acceptable arguments for this are: 'network', 'station', 'latitude', 'longitude', 'distance', 'azimuth' + +You can also call this from a Python environment + +```python +from pysep import Pysep + +sep = Pysep(..., order_stations_list_by="distance") +``` + + +------------------------- + +## Pointing PySEP to custom, local databases + +Data are often stored in custom databases that we cannot predict the +structure of. To point PySEP at your local databases, the simplest method would +be to find a way to read your data and metadata into ObsPy objects, which +you can then feed into the PySEP machinery. + +```python +from pysep import Pysep +from obspy import read, read_events, read_inventory +st = read() +inv = read_inventory() +event = read_events()[0] +sep = Pysep(st=st, inv=inv, event=event, config_file="config.yaml") +``` + diff --git a/docs/declust.md b/docs/declust.md new file mode 100644 index 0000000..b622133 --- /dev/null +++ b/docs/declust.md @@ -0,0 +1,86 @@ +# Declust: catalog declustering + +>__WARNING__: This docs page is still under construction + +`Declust` is a core module which can decluster event catalogs and apply +geographical weighting to events and stations. These tools are mainly used for +curating input data for tomographic inversions. + +## Motivation (Seismic Tomography) + +Declustering: Say you gather a general catalog of events and a list of stations for a given region using ObsPy. +If you directly used this catalog without any many of the simulations run have the possibility of being redundant, +as clusters of seismicity (e.g., foreshock aftershock sequences) tend to sample the same spatial area, providing a +limited amount of new knowledge at the price of an entire waveform simulation (expensive!). + + +Weighting: For this same dataset, let's say 90% of your stations are focused in one part of your domain, but you +have a select few (10%) that are geographically isolated. If all equally weighted, then the 90% of stations will +tend to overshadow the 10%. Source receiver weighting helps alleviate this by penalizing stations or events that +have many nearby counterparts, and promoting more geographically isolated sources. + +## Scripting Declust + +`Declust` must be scripted or used in a Python interactive environment, it currently does not have a command line interface. + +### Initializing + +Declust requires two inputs, an Obspy `Catalog` defining the events you would like to include, and an ObsPy `Inventory` defining +stations. + +```python +from pysep import Declust +from obspy import read_events, read_inventory + +# Example data +cat = read_events() +inv = read_inventory() + +declust = Declust(cat=cat, inv=inv) +``` + +Internally, `Declust` will comb through the Catalog and Inventory for relevant metadata (locations, IDs, data availability). +Users may provide their own Catalog and Inventory gathered via ObsPy or other methods. + +### Data Availability + +`Declust` calculates data availability based on station uptime. That is, for each event and its corresponding origin time, +`Declust` will check if each station in the Inventory was "on" during the event origin time. + +```python +declust.data_avail +``` +```bash +{'quakeml:eu.emsc/event/20120404_0000041': ['GR.FUR', 'GR.WET', 'BW.RJOB'], 'quakeml:eu.emsc/event/20120404_0000038': ['GR.FUR', 'GR.WET', 'BW.RJOB'], 'quakeml:eu.emsc/event/20120404_0000039': ['GR.FUR', 'GR.WET', 'BW.RJOB']} +``` + +Users may provide their own data availability dictionary to `Declust` that can be based on more sophisticated measurements, +such as the presence of a P-wave arrival, or a measurement window compared with synthetics. The keys of such a dictionary +must match the resource ID of each event in the catalog (i.e., `event.resource_id.id`) and the values are lists of +stations which are 'available', and in the format NN.SSS (N=network, S=station). + +### Threshold Catalog + +`Declust` has a function `threshold_catalog` which removes events in the Catalog based on depth values. This is very similar +to the `Catalog.filter()` function provided natively in ObsPy. Users input a number of depth boundaries (units: km) and the +minimum magnitude and minimum data availability allowed for all Events within those boundaries. + +This function updates the internal Catalog attribute of the `Declust` class + +```python +declust.threshold_catalog(zedges=[0, 10, 30, 100], min_mags=[4, 5, 6], min_data=10) +``` + +The above example partitions all events in the Catalog between depths of 0-10km, 10-30km and 30-100km. Within each depth range, +it defines the minimum magnitude allowed (e.g., M4 for 0-10km), and the minimum data availability (i.e., an event must have +atleast 10 stations 'available' to be considered). + +### Declustering + +Declustering breaks up the domain into a number of cells and groups events based on which cell they are in. Within each cell +a group of events are sorted by a specific criteria (e.g., magnitude, depth), and only a chosen number of events are retained. + + + + + diff --git a/docs/environment.yml b/docs/environment.yml new file mode 100644 index 0000000..a861555 --- /dev/null +++ b/docs/environment.yml @@ -0,0 +1,14 @@ +name: pysep-docs +channels: + - conda-forge +dependencies: + - sphinx + - sphinx_rtd_theme + - ipykernel + - nbsphinx + - jupyter + - myst-parser + - pip + - pip: + - sphinx-autoapi + - sphinx_rtd_theme diff --git a/docs/index.rst b/docs/index.rst new file mode 100644 index 0000000..6289627 --- /dev/null +++ b/docs/index.rst @@ -0,0 +1,93 @@ +.. pysep documentation master file, created by + sphinx-quickstart on Wed Feb 15 13:04:35 2023. + You can adapt this file completely to your liking, but it should at least + contain the root `toctree` directive. + +PySEP +=========================================== + +``PySEP`` (`Python Seismogram Extraction and Processing`) is a package revolving +around the collection, visualization and curation +of seismic data and metadata. It is built around ObsPy and uses a number of +core classes to achieve its goals: + +- `PySep `__: data download and processing tool +- `RecSec `__: record section plotter for data visualization +- `Declust `__: event and station declustering and weighting + +`PySEP` is hosted on `GitHub `_ as part of the +`adjTomo organization `_. + +As part of the `SCOPED toolkit `_, `PySEP` +has been +`containerized `_ +using Docker. + +--------------------------------- + +Installation +------------ + +We recommend installing PySEP into a Conda environment. Most dependencies are +installed via Conda while PySEP itself is installed in editable mode via Pip. + +This installation also creates two command line entry points for +`pysep` and `recsec`. See the `pysep `_ and `recsec `_ +documentation pages for how to use these command line tools. + +Installing to a new Conda environment (recommended) +``````````````````````````````````````````````````` +To create a new Conda environment for PySEP and its dependencies: + +.. code:: bash + + git clone --branch devel https://github.com/uafgeotools/pysep.git + cd pysep + conda env create -f environment.yml + conda activate pysep + +Updating an existing Conda environment +`````````````````````````````````````` + +If you have an existing Conda environment that you want to install PySEP and its +dependencies into, you can do so with the following commands: + +.. code:: bash + + git clone -- branch devel https://github.com/uafgeotools/pysep.git + cd pysep + conda activate + conda env update -f environment.yml + +.. note:: + + We are currently working to get `PySEP hosted on PyPi and Conda + `_ + + +--------------------------------- + +Running Tests +------------- + +PySEP comes with unit testing which should be run before and after making any +changes to see if your changes have altered the expected code behavior. + +.. code:: bash + + cd pysep/tests + pytest + +--------------------------------- + +.. toctree:: + :maxdepth: 2 + :hidden: + + pysep + recsec + declust + cookbook + usage + + diff --git a/docs/images/record_section.png b/docs/legacy/images/record_section.png similarity index 100% rename from docs/images/record_section.png rename to docs/legacy/images/record_section.png diff --git a/docs/images/station_map.png b/docs/legacy/images/station_map.png similarity index 100% rename from docs/images/station_map.png rename to docs/legacy/images/station_map.png diff --git a/docs/network_client_issues b/docs/legacy/network_client_issues similarity index 100% rename from docs/network_client_issues rename to docs/legacy/network_client_issues diff --git a/docs/make.bat b/docs/make.bat new file mode 100644 index 0000000..32bb245 --- /dev/null +++ b/docs/make.bat @@ -0,0 +1,35 @@ +@ECHO OFF + +pushd %~dp0 + +REM Command file for Sphinx documentation + +if "%SPHINXBUILD%" == "" ( + set SPHINXBUILD=sphinx-build +) +set SOURCEDIR=. +set BUILDDIR=_build + +%SPHINXBUILD% >NUL 2>NUL +if errorlevel 9009 ( + echo. + echo.The 'sphinx-build' command was not found. Make sure you have Sphinx + echo.installed, then set the SPHINXBUILD environment variable to point + echo.to the full path of the 'sphinx-build' executable. Alternatively you + echo.may add the Sphinx directory to PATH. + echo. + echo.If you don't have Sphinx installed, grab it from + echo.https://www.sphinx-doc.org/ + exit /b 1 +) + +if "%1" == "" goto help + +%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% +goto end + +:help +%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% + +:end +popd diff --git a/docs/pysep.md b/docs/pysep.md new file mode 100644 index 0000000..b2df349 --- /dev/null +++ b/docs/pysep.md @@ -0,0 +1,220 @@ +# PySEP: data download + +The PySEP class is a tool for downloading seismic waveform and metadata +en-masse. It applies some preprocessing, instrument response removal and +rotation to all data for use in moment tensor and tomographic inversions. +PySEP can be used via the command line, or through scripting. + +> __Note__: See [PySEP class API documentation]( + https://adjtomo.github.io/pysep/autoapi/pysep/pysep/index.html#pysep.pysep.Pysep) + for a list of available input parameters + +### What it does +1. Create or gather event metadata (QuakeML) with user-defined event parameters +2. Gather station metdata (StationXML) in a bounding box surrounding an event, +3. Curtail station list due to distance or azimuth constraints +4. Gather three-component waveform data for chosen station catalog +5. Quality check waveforms: remove gaps, null out missing components, address + clipped amplitudes +6. Preprocess waveforms: detrend, remove response, amplitude scaling, + standardizing time series +7. Rotate streams to desired components: ZNE, RTZ, UVW (triaxial orthogonal) +8. Append SAC headers with event and station metadata, and TauP arrivals +9. Write per-component SAC files, plus StationXML, QuakeML and MSEED files +10. Write CAP (Cut-and-Paste) weight files for moment tensor inversions +11. Write config YAML files which can be used to reproduce data gathering/processing + + +-------------------------------------------------------------------------------- + +## PySEP via Command Line + +Normal users should use PySEP as a command line tool. + +To bring up the command line tool help message: + +```bash +pysep -h +``` + +To list out available pre-defined configuration files + +```bash +pysep -l # or pysep --list + +-p/--preset -e/--event +-p MTUQ2022_workshop -e 2009-04-07T201255_ANCHORAGE.yaml +-p MTUQ2022_workshop -e 2014-08-25T161903_ICELAND.yaml +-p MTUQ2022_workshop -e 2017-09-03T033001_NORTH_KOREA.yaml +-p MTUQ2022_workshop -e 2020-04-04T015318_SOUTHERN_CALIFORNIA.yaml +``` + +To run one of the pre-defined configuration files + +``` bash +pysep -p MTUQ2022_workshop -e 2017-09-03T033001_NORTH_KOREA.yaml +``` + +To create a template configuration file that you must fill out with your own +parameters + +```bash +pysep -W # or pysep --write +``` + +To run this newly created configuration file + +```bash +pysep -c pysep_config.yaml +``` + + +### Input Parameters and YAML Parameter File + +> __Note__: See [PySEP class API documentation]( + https://adjtomo.github.io/pysep/autoapi/pysep/pysep/index.html#pysep.pysep.Pysep) + for a list of available input parameters + +When using PySEP from the command line, all input variables are controlled by a +[YAML](https://yaml.org/) parameter file, which is a text file containing +a set of parameter names and corresponding values, for example: + +```yaml +# key: value +origin_time: '2009-04-07T20:12:55.351000Z' +``` + +These parameters control everything from the hypocentral location of +your earthquake, to the specific waveform data you want to collect, to the +types of preprocessing steps to be applied. + +To generate a template parameter file you can run: + +```bash +pysep -W # or pysep --write +``` + + +### Multiple Event Input + +To use the same configuration file with multiple events, you can use an event +file passed to PySEP through the command line. + +When using this option, the event parameters inside the config file will be +ignored, but all the other parameters will be used to gather data and metadata. + +Event input files should be text files where each row describes one event with +the following parameters as columns: + +> ORIGIN_TIME LONGITUDE LATITUDE DEPTH[KM] MAGNITUDE + +For an example event input file called 'event_input.txt', call structure is: + +```bash +pysep -c pysep_config.yaml -E event_input.txt +``` + +-------------------------------------------------------------------------------- +### Legacy Filenaming Schema + +The new version of PySEP uses a file naming schema that is incompatible with +previous versions, which may lead to problems in established workflows. + +To honor the legacy naming schema of PySEP, simply use the ``--legacy_naming`` +argument in the command line. This will change how the event tag is formatted, +how the output directory is structured, and how the output SAC files are named. + +```bash +pysep -c pysep_config.yaml --legacy_naming +``` + + +### Output Filename Control + +The event tag used to name the output directory and written SAC files can be set +manually by the user using the ``--event_tag`` argument. If not given, the tag +will default to a string consisting of event origin time and Flinn-Engdahl +region (or just origin time if ``--legacy_naming`` is used). Other output files +such as the config file and ObsPy objects can be set as in the following: + +```bash +pysep -c pysep_config.yaml \ + --overwrite_event_tag event_abc \ + --config_fid event_abc.yaml \ + --stations_fid event_abc_stations.txt \ + --inv_fid event_abc_inv.xml \ + --event_fid event_abc_event.xml \ + --stream_fid event_abc_st.ms +``` + +Please note: the output SAC file names are hardcoded and cannot be changed +by the user. If this is a required feature, please open up a GitHub issue, and +the developers will address this need. + + +### ObsPy Mass Downloader + +[ObsPy's Mass Download](https://docs.obspy.org/packages/autogen/obspy.clients.fdsn.mass_downloader.html) +feature allows for large data downloads over all available data services. This may be useful if +you don't care where your data comes from and just want to download all data available. This +ignores the ``client`` option and downloads waveform and station metadata for all available +data services. + +To use the mass download option from the command line, you will first need to add the following +parameter to your YAML config file: + +```yaml +use_mass_download: true +``` + +Then from the command line, you can run things as normal, PySEP will know to use the mass download option +to grab waveform and station metadata. There are two additional keyword arguments which you can provide +from the command line. + +- domain_type (str): Define the search region domain as + - ``rectangular``: rectangular bounding box defined by `minlatitude`, + `minlongitude,` `maxlatitude` and `maxlongitude` + - ``circular``: circular bounding circle defined by the `event_latitude`, + `event_longitude` and min and max radii defined by `mindistance` and + `maxdistance` +- delete_tmpdir (bool): Removes the temporary directories that store the MSEED and + StationXML files which were downloaded by the mass downloader. + Saves space but also if anything fails prior to saving data, + the downloaded data will not be saved. Defaults to True. + +```bash +pysep -c config.yaml --domain_type circular --delete_tmpdir False +``` +------------------------------------------------------------------------------- + +## Scripting PySEP + +Check out the Cookbook section for additional useful functions and routines +that can be implemented. + +All of the gathered data/metadata are saved as attributes of the Pysep class +with typical ObsPy naming schema + +```python +from pysep import Pysep +sep = Pysep(config_file='pysep_config.yaml') +sep.run() +print(sep.st[0].stats.sac) +sep.inv +sep.event +``` + +You can also pass parameters directly to the instantiation of the PySEP +class. See the PySEP docstring for input parameter types and definitions. + +```python +from pysep import Pysep +sep = Pysep(origin_time="2000-01-01T00:00:00", event_latitude=64.8596, + event_longitude=-147.8498, event_depth_km=15., .... + ) +``` + +> __Note__: See [PySEP class API documentation]( + https://adjtomo.github.io/pysep/autoapi/pysep/pysep/index.html#pysep.pysep.Pysep) + for a list of available input parameters + diff --git a/docs/recsec.md b/docs/recsec.md new file mode 100644 index 0000000..d47a6b4 --- /dev/null +++ b/docs/recsec.md @@ -0,0 +1,180 @@ +# RecSec: record sections + +RecordSection (abbreviated RecSec) is a record section tool used to plot +a number of waveforms on a single figure. Waveforms can be processed, and sorted +by various attributes, such as epicentral distance or azimuth. Data can be +further modified, for example amplitudes can be scaled by expected geometrical +spreading factor to visualize site amplification effects. + +> __Note__: See [RecordSection class API documentation]( + https://adjtomo.github.io/pysep/autoapi/pysep/recsec/index.html#pysep.recsec.RecordSection ) for a list of available input parameters + +### What it does: +* Plot waveform data and synthetic seismograms (by themselves or together) +* Sort source-receiver pairs by absolute or relative distance or (back)azimuth +* Apply time shifts, zero padding, move out and amplitude scaling +* Scale amplitudes by global maximum, trace maximum or empirical geometric spreading factor +* Preprocess data with filters and detrends prior to plotting + + + +## Record Section via the Command Line + +PySEP also comes with a pretty sophisticated record section tool, which plots +seismic data acquired by PySEP. When you have successfully collected your data, +it will reside in the /SAC folder of the PySEP output directory. + + +To see available record section plotting commands + +```bash +recsec -h # RECordSECtion +``` + +To plot the waveform data in a record section with default parameters + +```bash +recsec --pysep_path ./SAC +``` + +To plot a record section with a 7km/s move out, high-pass filtered at 1s +s +```bash +recsec --pysep_path ./SAC --move_out 7 --min_period_s 1 +``` + +To sort your record section by azimuth and not distance (default sorting) + +```bash +recsec --pysep_path ./SAC --sort_by azimuth +``` + +Have a look at the -h/--help message and the docstring at the top of `recsec.py` +for more options. + + +> __Note__: See [RecordSection class API documentation]( + https://adjtomo.github.io/pysep/autoapi/pysep/recsec/index.html#pysep.recsec.RecordSection ) for a list of available input parameters + +### Customizing RecSec figures + +Much of the aesthetic look of RecSec figures is hardcoded, however there are +some keyword arguments that you can provide as flags which may help. The +following parameters correspond to Matplotlib plot adjustments. + +- ytick_fontsize: Fontsize of the Y-axis tick labels +- xtick_fontsize: Fontsize of the X-axis tick labels +- tick_linewidth: Linewidth of axes tick marks +- tick_length: Length of axes tick marks +- label_fontsize: Fontsize of X and Y axis labels +- axis_linewidth: Linewidth of border around figure +- title_fontsize: Fontsize of the title +- xtick_minor: Frequency of minor ticks on the X axis +- xtick_major: Frequency of major ticks on the X axis + +To set one of these parameters, just set as a flag, e.g., + +```bash +recsec --pysep_path ./SAC --xtick_minor 100 --xtick_major 500 +``` + + +### Plotting SPECFEM synthetics + +RecSec can plot SPECFEM-generated synthetic seismograms in ASCII format. Here +the domain should be defined by geographic coordinates (latitude/longitude). If +your domain is defined in Cartesian, see below. + +Record sections can be plotted standalone, or alongside observed seismograms +to look at data-synthetic misfit. + +To access metadata, RecSec requires the CMTSOLUTION and STATIONS file that were +used by SPECFEM to generate the synthetics. Based on a standard +SPECFEM3D_Cartesian working directory, plotting synthetics only would have +the following call structure: + +```bash +recsec --syn_path OUTPUT_FILES/ --cmtsolution DATA/CMTSOLUTION --stations DATA/STATIONS +``` + +To compare observed and synthetic data, you would have name the --pysep_path +and tell RecSec to preprocess both data streams identically + +```bash +recsec --pysep_path ./SAC --syn_path OUTPUT_FILES/ --cmtsolution DATA/CMTSOLUTION --stations DATA/STATIONS --preprocess both +``` + +Preprocessing flags such as filtering and move out will be applied to both +observed and synthetic data. + + +### Plotting SPECFEM synthetics in Cartesian + +Under the hood, RecSec uses some of ObsPy's geodetic +functions to calculate distances and azimuths. Because of this, RecSec will +fail if coordinates are defined in a Cartesian coordinate system (XYZ), which +may often be the case when working in SPECFEM2D or in a local domain of +SPECFEM3D_Cartesian. + +To circumvent this, RecSec has a flag `--cartesian`, which will swap out the +read functions to work with a Cartesian coordinate system. The call is very +similar to the above: + +For SPECFEM3D_Cartesian this would look like + +```bash +recsec --syn_path OUTPUT_FILES --cmtsolution DATA/CMTSOLUTION --stations DATA/STATIONS --cartesian +``` + +For SPECFEM2D, the source file may not be a CMTSOLUTION. Additionally, the +default seismogram components may not be defined in ZNE + +```bash +recsec --syn_path OUTPUT_FILES --cmtsolution DATA/SOURCE --stations DATA/STATIONS --components Y --cartesian +``` + + +### Plotting two sets of synthetics (synsyn) + +It is often useful to compare two sets of synthetic seismograms, where one set +represents 'data', while the other represents synthetics. For example, during +a tomographic inversion, a Target model may be used to generate data. + +RecSec can plot two sets of synthetics in a similar vein as plotting +data and synthetics together. The User only needs to add the `--synsyn` flag +and provide paths to both `--pysep_path` and `--syn_path`. + +>__NOTE__: RecSec makes the assumption that both sets of synthetics share the +> same metadata provided in the `--cmtsolution` and `--stations` flags. + +Let's say you've stored your 'data' in a directory called 'observed/' and your +synthetics in a directory called 'synthetic/' + +```bash +recsec --pysep_path observed/ --syn_path synthetic/ --cmtsolution DATA/CMTSOLUTION --stations DATA/STATIONS --synsyn +``` + + +-------------------------------------------------- + +## Scripting RecSec + +The RECord SECtion tool can also be scripted. It simply requires an ObsPy Stream +object as input. Tuning parameters can be fed in as input variables. + +> __Note__: See [RecordSection class API documentation]( + https://adjtomo.github.io/pysep/autoapi/pysep/recsec/index.html#pysep.recsec.RecordSection ) for a list of available input parameters + +```python +from obspy import read, read_inventory, read_events +from pysep import RecordSection +from pysep.utils.cap_sac import append_sac_headers +st = read() +inv = read_inventory() +event = read_events()[0] +st = append_sac_headers(st, event, inv) # RecordSection requires SAC headers +rs = RecordSection(st=st, sort_by="distance", scale_by="normalize") +rs.run() +``` + + diff --git a/docs/usage.md b/docs/usage.md new file mode 100644 index 0000000..fc22ed0 --- /dev/null +++ b/docs/usage.md @@ -0,0 +1,63 @@ +# Usage + +This page contains information on using PySEP in non-standard environments + +## Running PySEP on UAF Chinook + +Chinook is University of Alaska Fairbanks' (UAF) high performance computer. +We can run PySEP on Chinook using Docker containers through +Singularity/Apptainer. + +PySEP has been containerized directly, and any changes pushed to the repo will +trigger the container to rebuild, keeping everything up-to-date. +The following code snippet downloads the correct +[SCOPED container](https://github.com/SeisSCOPED/pysep/pkgs/container/pysep). +and runs the PySEP help message on Chinook. + +```bash +module load singularity +singularity pull ghcr.io/seisscoped/pysep:centos7 +singularity exec -c pysep_centos7.sif pysep -h +``` + +To run a data download we will need to mount the local filesystem into the +container using the ``--bind`` command. Using the Anchorage example event: + +```bash +singularity exec -c --bind $(pwd):/home1 pysep_centos7.sif \ + bash -c "cd /home1/; pysep -p mtuq_workshop_2022 -e 2009-04-07T201255_ANCHORAGE.yaml" +``` + +In the above example, the `-c/--contain` flag preserves the internal container +filesystem, the `-B/--bind` flag binds the current working directory on Chinook +(i.e., pwd)to a directory called */home1* within the container, and then the +`bash -c` command changes to this */home1* directory and runs PySEP. Files are +subsequently saved to the local filesystem in our current working directory. + +`RecSec`, the record section plotting tool, can be run from the command line +using a similar format. With the Anchorange example files we just generated: + +```bash +cd 2009-04-07T201255_SOUTHERN_ALASKA/ +singularity exec -c --bind $(pwd):/home1 ../pysep_centos7.sif \ + bash -c "cd /home1; recsec --pysep_path SAC/ --min_period 10 --save record_section_tmin10.png" +``` + +--------------------- + +## Accessing LLNL Waveform Database + +`PySEP` interfaces with the databases of: + +* W. Walter et al. (2006) + An assembled western United States dataset for regional seismic analysis + ISSO 9660 CD, LLNL release UCRL-MI-222502 + + Download link: https://ds.iris.edu/mda/18-001 + +To use the LLNL database, set the input parameter `client` as: + +```yaml +client: 'LLNL' +``` + diff --git a/environment.yml b/environment.yml index c8d4f9e..14e0140 100644 --- a/environment.yml +++ b/environment.yml @@ -8,6 +8,5 @@ dependencies: - cartopy - pyyaml - pip: - - git+https://github.com/krischer/llnl_db_client.git - -e . diff --git a/pyproject.toml b/pyproject.toml index b6e7f10..6bd79b8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta" [project] name = "pysep" -version = "0.2.0" +version = "0.3.0" description = "Python Seismogram Extraction and Processing" readme = "README.md" requires-python = ">=3.7" @@ -17,10 +17,10 @@ dependencies = [ "obspy", "cartopy", "pyyaml", - "llnl_db_client @ git+https://github.com/krischer/llnl_db_client.git" ] [project.optional-dependencies] +llnl = ["llnl_db_client @ git+https://github.com/krischer/llnl_db_client.git"] test = ["pytest"] dev = ["pytest", "ipython", "ipdb"] diff --git a/pysep/__init__.py b/pysep/__init__.py index f961d70..b59a3e3 100644 --- a/pysep/__init__.py +++ b/pysep/__init__.py @@ -11,4 +11,5 @@ # from pysep.pysep import Pysep, get_data # NOQA from pysep.pysep import Pysep, get_data # NOQA -from pysep.recsec import RecordSection # NOQA \ No newline at end of file +from pysep.recsec import RecordSection # NOQA +from pysep.declust import Declust # NOQA \ No newline at end of file diff --git a/pysep/configs/README.md b/pysep/configs/README.md index ca967b6..532c5e6 100644 --- a/pysep/configs/README.md +++ b/pysep/configs/README.md @@ -6,3 +6,6 @@ The below information describes each of the category directories. Quantification (MTUQ) workshop to demonstrate code capabilities. - denali_nodal: Events recorded by the PASSCAL Denali Fault nodal deployment - misc_events: One-off events with no overarching category +- test: test data collection that exhibits certain traits that are useful for + checking rejection criteria etc. Check comments at top of file to show + what the file is used for diff --git a/pysep/configs/test/check_rotate_12Z.yaml b/pysep/configs/test/check_rotate_12Z.yaml new file mode 100644 index 0000000..7ca0a86 --- /dev/null +++ b/pysep/configs/test/check_rotate_12Z.yaml @@ -0,0 +1,46 @@ +# Testing IU Rotation Error - PySEP Issue #37 +# IU.COLA raw stream returns 12Z which gets rotated appropriately +event_tag: null +config_file: null +client: IRIS +client_debug: false +timeout: 600 +taup_model: ak135 +event_selection: default +origin_time: '2012-04-11T09:21:57.444' +seconds_before_event: 20 +seconds_after_event: 20 +event_latitude: 64.9222 +event_longitude: -148.9461 +event_depth_km: 160.00 +event_magnitude: 3.8 +networks: 'IU' +stations: 'COLA' +channels: 'BH?,HH?' +locations: '*' +reference_time: null +seconds_before_ref: 100 +seconds_after_ref: 600 +phase_list: null +mindistance: 0 +maxdistance: 200.0 +minazimuth: 0 +maxazimuth: 360 +minlatitude: null +maxlatitude: null +minlongitude: null +maxlongitude: null +demean: true +detrend: true +taper_percentage: 0 +rotate: +- ENZ +- RTZ +remove_response: true +output_unit: VEL +water_level: 60 +pre_filt: default +scale_factor: 1.0 +resample_freq: 50 +remove_clipped: false +log_level: DEBUG diff --git a/pysep/configs/test/test_config_rotate_bug.yaml b/pysep/configs/test/test_config_rotate_bug.yaml new file mode 100644 index 0000000..0102b94 --- /dev/null +++ b/pysep/configs/test/test_config_rotate_bug.yaml @@ -0,0 +1,48 @@ +# Related to GitHub Issue #35, TypeError thrown when attempting to rotate +# a stream with missing metadata. This issue is fixed but the Config is +# here to provide the station data used to test this issue +event_tag: null +config_file: null +client: IRIS +client_debug: false +timeout: 600 +taup_model: ak135 +event_selection: default +origin_time: "2015-06-24T22:32:21.166000Z" +seconds_before_event: 20 +seconds_after_event: 20 +event_latitude: 61.664 +event_longitude: -151.962 +event_depth_km: 114.2 +event_magnitude: 5.8 +networks: 'TA' +stations: 'O18K' +channels: 'BH?,LH?,UH?,VH?' # These have missing dip or azi values +locations: '*' +reference_time: null +seconds_before_ref: 100 +seconds_after_ref: 300 +phase_list: null +mindistance: 0 +maxdistance: 20000.0 +minazimuth: 0 +maxazimuth: 360 +minlatitude: null +maxlatitude: null +minlongitude: null +maxlongitude: null +demean: true +detrend: true +taper_percentage: 0 +rotate: +- ZNE +- RTZ +remove_response: true +output_unit: VEL +water_level: 60 +pre_filt: default +scale_factor: 1 +resample_freq: null +remove_clipped: false +log_level: DEBUG +kwargs: {} diff --git a/pysep/configs/test/test_mass_download.yaml b/pysep/configs/test/test_mass_download.yaml new file mode 100644 index 0000000..16cd157 --- /dev/null +++ b/pysep/configs/test/test_mass_download.yaml @@ -0,0 +1,45 @@ +event_tag: 2009-04-07T201255_SOUTHERN_ALASKA +config_file: null +client: IRIS +client_debug: false +use_mass_download: true +timeout: 600 +taup_model: ak135 +event_selection: default +origin_time: '2009-04-07T20:12:55.351000Z' +seconds_before_event: 20 +seconds_after_event: 20 +event_latitude: 61.4542 +event_longitude: -149.7428 +event_depth_km: 33.033 +event_magnitude: 4.6 +networks: AK,YV,AV,AT,XZ,PN +stations: '*,-GOAT' +channels: BH? +locations: '*' +reference_time: '2009-04-07T20:12:55.351000Z' +seconds_before_ref: 100 +seconds_after_ref: 300 +phase_list: null +mindistance: 0 +maxdistance: 300.0 +minazimuth: 0 +maxazimuth: 360 +minlatitude: null +maxlatitude: null +minlongitude: null +maxlongitude: null +demean: true +detrend: true +taper_percentage: 0 +rotate: +- ENZ +- RTZ +remove_response: true +output_unit: VEL +water_level: 60 +pre_filt: default +scale_factor: 1.0 +resample_freq: 50 +remove_clipped: false +log_level: DEBUG diff --git a/pysep/configs/test/test_remove_data_gaps.yaml b/pysep/configs/test/test_remove_data_gaps.yaml new file mode 100644 index 0000000..41ddd21 --- /dev/null +++ b/pysep/configs/test/test_remove_data_gaps.yaml @@ -0,0 +1,47 @@ +# Testing Data gap removal +# FIB has data gaps, should be removed from final data retrieval +event_tag: 2009-04-07T201255_SOUTHERN_ALASKA +config_file: null +client: IRIS +client_debug: false +timeout: 600 +taup_model: ak135 +event_selection: default +origin_time: '2009-04-07T20:12:55.351000Z' +seconds_before_event: 20 +seconds_after_event: 20 +event_latitude: 61.4542 +event_longitude: -149.7428 +event_depth_km: 33.033 +event_magnitude: 4.6 +networks: AK +stations: 'FIB,SWD' +channels: BH? +locations: '*' +reference_time: '2009-04-07T20:12:55.351000Z' +seconds_before_ref: 100 +seconds_after_ref: 300 +phase_list: null +mindistance: 0 +maxdistance: 300.0 +minazimuth: 0 +maxazimuth: 360 +minlatitude: null +maxlatitude: null +minlongitude: null +maxlongitude: null +demean: true +detrend: true +taper_percentage: 0 +rotate: +- ENZ +- RTZ +remove_response: true +output_unit: VEL +water_level: 60 +pre_filt: default +scale_factor: 1.0 +resample_freq: 50 +remove_clipped: false +log_level: DEBUG + diff --git a/pysep/declust.py b/pysep/declust.py new file mode 100644 index 0000000..d98f11f --- /dev/null +++ b/pysep/declust.py @@ -0,0 +1,1044 @@ +#!/usr/bin/evn python3 +""" +Event and station declustering and weighting algorithms for adjoint tomography. + +Provides routines for downsizing an event catalog by performing a declustering +algorithm to remove nearby stations, and also implements a weighting scheme to +promote unique source receiver pairs. + +:authors: + adjTomo Dev Team (2023) + Amanda McPherson (2021) + Carl Tape (2018) +""" +import matplotlib.pyplot as plt +import numpy as np +import os +from obspy.geodetics import locations2degrees +from pysep import logger +from pysep.utils.fmt import index_cat, get_data_availability +from pysep.utils.plot import set_plot_aesthetic + + +class Declust: + """ + Declustering class in charge of declustering and source receiver weighting + """ + def __init__(self, cat, inv=None, data_avail=None, min_lat=None, + max_lat=None, min_lon=None, max_lon=None): + """ + User-input parameters to determine algorithm behavior + + :type cat: obspy.core.catalog.Catalog + :param cat: Catalog of events to consider. Events must include origin + information `latitude` and `longitude` + :type inv: obspy.core.inventory.Inventory + :param inv: Inventory of stations to consider + :type data_avail: dict + :param data_avail: If None, Declust assumes that all events in `cat` + were recorded by all stations in `inv`. This is typically not the + case however, so this dict allows the user to tell `Declust` about + data availability. Keys of `data_avail` must match resource + IDs, and values must be lists of station names (NN.SSSS) + :type min_lat: float + :param min_lat: optional, minimum latitude for bounding box defining the + region of interest. If not given, will use the minimum latitude + in the catalog of events + :type max_lat: float + :param max_lat: optional, maximum latitude for bounding box defining the + region of interest. If not given, will use the maximum latitude + in the catalog of events + :type min_lon: float + :param min_lon: optional, minimum longitude for bounding box defining + the region of interest. If not given, will use the minimum longitude + in the catalog of events + :type max_lon: float + :param max_lon: optional, maximum longitude for bounding box defining + the region of interest. If not given, will use the maximum longitude + in the catalog of events + """ + self.cat = cat + self.inv = inv + + # Allow a user-defined bounding box to define the region. Otherwise + # will be set based on the min/max values of the Cat and Inv + self._user_min_lat = min_lat + self._user_max_lat = max_lat + self._user_min_lon = min_lon + self._user_max_lon = max_lon + + # Allow user to define data availability, otherwise it will be + # calculated on the fly based on the `inv` object + self._user_data_avail = data_avail + + # Instantiate Nones and then fill up internal lists with metadata getter + self.evlats = None + self.evlons = None + self.evids = None + self.stalats = None + self.stalons = None + self.staids = None + self.min_lat = None + self.max_lat = None + self.min_lon = None + self.max_lon = None + self.depths = None + self.mags = None + self.data_avail = None + self.navail = None + self.update_metadata() + + def update_metadata(self, cat=None, inv=None): + """ + Get metadata like location and event depth and magnitude from a given + Cat and Inv and set as internal attributes. + Needs to be as separate function as `threshold_events` will cut down + the internal catalog representation so this will need to be re-run + """ + if cat is None: + cat = self.cat + else: + self.cat = cat + + if inv is None: + inv = self.inv + else: + self.inv = inv + + # Get longitude and latitude values from the Catalog and Inventory + self.evlats = np.array( + [event.preferred_origin().latitude for event in cat] + ) + self.evlons = np.array( + [event.preferred_origin().longitude for event in cat] + ) + # Get additional information about events + self.depths = np.array( + [event.preferred_origin().depth * 1E-3 for event in cat] + ) + self.mags = np.array( + [event.preferred_magnitude().mag for event in cat] + ) + self.evids = np.array( + [event.resource_id.id for event in cat] + ) + + # Get information on stations + self.stalats, self.stalons, self.staids = [], [], [] + if inv is not None: + for net in inv: + for sta in net: + self.stalats.append(sta.latitude) + self.stalons.append(sta.longitude) + self.staids.append(f"{net.code}.{sta.code}") + self.stalats = np.array(self.stalats) + self.stalons = np.array(self.stalons) + self.staids = np.array(self.staids) + + # Bound domain region based on min/max lat/lons of events and stations + self.min_lat = \ + self._user_min_lat or np.append(self.evlats, self.stalats).min() + self.max_lat = \ + self._user_max_lat or np.append(self.evlats, self.stalats).max() + self.min_lon = \ + self._user_min_lon or np.append(self.evlons, self.stalons).min() + self.max_lon = \ + self._user_max_lon or np.append(self.evlons, self.stalons).max() + + # Determine data availability based on station "on" time + self.data_avail = \ + self._user_data_avail or get_data_availability(cat, inv) + + # Count the number of availabler stations for the entire catalog + self.navail = np.array([len(val) for val in self.data_avail.values()]) + + def threshold_catalog(self, zedges=None, min_mags=None, min_data=None): + """ + Kick out events that fall below a given magnitude range or a given + data availability range. Allow this to be done for various depth + ranges or for the entire volume at once. + + .. note:: + + Updates internal `cat` Catalog object and metadata in place + + :type zedges: list of float + :param zedges: depth [km] slices to partition domain into when + thresholding data + :type min_mags: int or list + :param min_mags: a list of minimum magnitude thresholds for each depth + slice. If `zedges` is None, should be a list of length==1, which + provides minimum magnitude for entire catalog. + Elif `zedges` is given, should be a list of len(zedges)-1, which + defines minimum magnitude for each depth bin. + For example if zedges=[0, 35, 400], then one example is + min_mags=[4, 6]. Meaning between 0-34km the minimum magnitude is 4, + and between 35-400km the minimum magnitude is 6. + :type min_data: int or list + :param min_data: an integer or list of length len(zedges)-1 that defines + the minimum number of stations on for a given event origin time, + which allows user to prioritize stations with available data + """ + if zedges is None: + logger.warning("`zedges` not set, all depth values will be " + "weighted equally") + zedges = [min(self.depths), max(self.depths)] + if min_mags is not None: + # Allow integer value of min mags as a blanket for all depths + if isinstance(min_mags, int): + min_mags = np.array([min_mags] * (len(zedges) - 1)) + assert(len(min_mags) == len(zedges) - 1), ( + f"`min_mags` must be a list of magnitudes with length of " + f"`zedges` - 1 ({len(zedges)-1}" + ) + if min_data is not None: + # Allow integer value of min data as a blanket for all depths + if isinstance(min_data, int): + min_data = np.array([min_data] * (len(zedges) - 1)) + assert (len(min_data) == len(zedges) - 1), ( + f"`min_data` must be a list of available stations with " + f"length of `zedges` - 1 ({len(zedges) - 1}" + ) + + cat_flag = np.ones(len(self.cat), dtype=int) + for i, z_top in enumerate(zedges[:-1]): + z_bot = zedges[i+1] + + # Deal with one depth partition at a time + idxs = np.where( + (np.abs(self.depths) < np.abs(z_bot)) & + (np.abs(self.depths) >= np.abs(z_top)) + )[0] + + # Kick out events with magnitudes below a certain threshold + if min_mags is not None: + # Remove events that clear the threshold magnitude criteria + idxs_remove = np.delete( + idxs, np.where(self.mags[idxs] >= min_mags[i]), + axis=0 + ) + + if idxs_remove.size > 0: + logger.info(f"{z_top:.2f}<=Z<{z_bot:.2f} min mag " + f"(M{min_mags[i]}) threshold matched " + f"{len(idxs_remove)} events") + cat_flag[idxs_remove] *= 0 + # Kick out events that do not have enough stations available + if min_data is not None: + # Remove events that clear the threshold data availability + idxs_remove = np.delete( + idxs, np.where(self.navail[idxs] >= min_data[i]), + axis=0 + ) + if idxs_remove.size > 0: + logger.info(f"{z_top:.2f}<=Z<{z_bot:.2f} min data avail " + f"(N={min_data[i]}) threshold matched " + f"{len(idxs_remove)} events") + cat_flag[idxs_remove] *= 0 + + logger.info(f"event thresholding removed " + f"{len(self.cat) - cat_flag.sum()} events from cat") + + # Updates the internal Catalog and metadata in place + self.cat = index_cat(cat=self.cat, idxs=np.where(cat_flag == 1)[0]) + self.update_metadata() + + def calculate_srcrcv_weights(self, cat=None, inv=None, write="weights.txt", + plot=False, show=False, save="srcrcvwght.png"): + """ + Calculate event and station specific weights based on event geographic + weights, and event-dependent station geographic weights which take into + account data availability for each event. + + Uses the internal `cat` and `inv` attributes of the class. If + declustering was run to thin out the catalog, run `update_metadata` + first to update internal attributes which are used for defining weights. + + :type cat: obspy.core.catalog.Catalog + :param cat: Optional, catalog of events to consider. If none given, + will use whatever internal catalog is available + :type inv: obspy.core.inventory.Inventory + :param inv: Inventory of stations to consider + :type plot: bool + :param plot: plot source weights and an average of station weights on + a single figure. + :type write: str + :param write: filename used to write station weights to text file. + if None, will not write + :type show: bool + :param show: show figure in GUI + :type save: str + :param save: if given, file id for the name of the output figure to save + if not given, will not save figure + :rtype: np.array + :return: a 2D array where each row corresponds to a station and each + column corresponds to an event. The value for a given row and + column is the weight of that station w.r.t all other available + stations. Stations that were not available (not on) are given a + weight of 0 + """ + if cat is not None or inv is not None: + self.update_metadata(cat, inv) + + logger.info("calculating source receiver weights") + # Used for index lookups + sorted_idx = np.argsort(self.staids) + + # The summation of source weights should equal the number of sources + source_weights = self._get_weights(lons=self.evlons, lats=self.evlats, + norm="avg") + + # For each source we get weights based only on available stations + station_weights = [] + for i, eid in enumerate(self.evids): + data_avail = np.array(self.data_avail[eid]) + logger.info(f"'{eid}' has {len(data_avail)} stations available") + + # Determine the indices of all stations available based on sta ID + idx_avail = np.searchsorted(self.staids[sorted_idx], data_avail) + + sta_avail_weights = self._get_weights(lons=self.stalons[idx_avail], + lats=self.stalats[idx_avail], + norm="avg" + ) + + # Multiply weights by the weight of the given source + sta_avail_weights *= source_weights[i] + + # Place these weights within a full size array, fill blanks w/ 0 + # Assuming that the `get_weights` algorithm will not return 0 weight + sta_full_weights = np.zeros(len(self.staids)) # zeros + sta_full_weights[idx_avail] = sta_avail_weights + + station_weights.append(sta_full_weights) + + # Rows: events; Cols: stations + station_weights = np.array(station_weights) + + # Write out a text file with weights + if write is not None: + header = (f"ROWS:{' '.join([_ for _ in self.evids])}\n" + f"COLS:{' '.join([_ for _ in self.staids])}" + ) + np.savetxt(write, station_weights, header=header, fmt="%.3f") + + # Normalize by the average for each station only taking into account + # available data (i.e. ignoring zero weight values). For plotting only + if plot: + avg_sta_weight = (station_weights.T.sum(axis=1) / + np.count_nonzero(station_weights.T, axis=1) + ) + title = (f"Geographic Weighting (NSTA={len(self.stalons)}, " + f"NEVNT={len(self.evlons)})") + self.plot(inv=self.inv, show=show, save=save, title=title, + color_by="custom", event_colors=source_weights, + station_colors=avg_sta_weight, + event_cbar_label="event weights", + station_cbar_label="average station weights", + cmap="RdBu", station_cmap="PRGn", + station_markersize=75, connect_data_avail=True, + event_size_scale=(60, 300) + ) + + return station_weights + + def _get_weights(self, lons, lats, norm=None, plot=False, + save="reference_distance_scan.png"): + """ + Given a set of coordinates (either stations or earthquakes), calculate + a reference distance and a set of weights for each coordinate. + Reference distance is chosen as one-third the largest possible value for + all possible reference distances + + :type lons: np.array + :param lons: array of longitude values + :type lats: np.array + :param lats: array of latitude values + :type plot: bool + :param plot: plot a simple scatterplot showing the weights for each + station + :type norm: str + :param norm: how to normalize the weights + - None: don't normalize, provide raw weights + - 'max': normalize by the maximum weight + - 'len': normalize by the length of the array + - 'avg': normalize by the mean weight value + :rtype: np.array + :return: relative, normalized weights for each lon/lat pair + """ + # Weights will be 1 if any station amount less than 2 + if len(lons) <= 2: + weights = np.ones(len(lons)) + return weights + + # Calculate the matrix of inter-point distances (source or receiver) + dists = [] + for i, (lat_i, lon_i) in enumerate(zip(lats, lons)): + dists_ij = [] + for j, (lat_j, lon_j) in enumerate(zip(lats, lons)): + if i == j: + dist_m = 0 + else: + dist_m = locations2degrees(lat1=lat_i, long1=lon_i, + lat2=lat_j, long2=lon_j) + dists_ij.append(dist_m) + dists.append(dists_ij) + dists = np.array(dists) + + # Calculate a range of reference distances + min_ref_dist = 1 # km + max_ref_dist = np.ceil(dists.max()) + ref_dists = np.arange(min_ref_dist, max_ref_dist, 0.25) + + # Loop through reference distances and calculate weights + ratios = [] + for ref_dist in ref_dists: + weights_try = self._covert_dist_to_weight(dists, ref_dist) + ratios.append(max(weights_try) / min(weights_try)) + ratios = np.array(ratios) + + # Select the reference distance that provides 1/3 the max amplitude + idx = (np.abs(ratios - ratios.max()//3)).argmin() + optimal_ref_dist = ref_dists[idx] + + logger.debug(f"ref. dist. = {optimal_ref_dist} chosen from " + f"{min_ref_dist} <= d <= {max_ref_dist}") + + # Convert relative inter-source distances to a given weight + weights = self._covert_dist_to_weight(dists, optimal_ref_dist) + + # Allow normalization for a variety of types + if norm is None: + normalize = 1 + elif norm == "avg": + normalize = sum(weights) / len(weights) + elif norm == "len": + normalize = len(weights) + elif norm == "max": + normalize = max(weights) + else: + raise NotImplementedError(f"`norm` cannot be {norm}") + weights /= normalize + + # Plot the reference distance scan to allow user to double-check + if plot: + plt.plot(dists, ratios, "ko-", linewidth=2) + plt.axhline(dists[idx], c="r", linewidth=2, label="optimal value") + plt.xlabel("Reference Distance (deg)") + plt.ylabel("Condition Number") + plt.title("Scan for Reference Distance") + plt.legend() + if save: + plt.savefig(save) + plt.show() + + return weights + + @staticmethod + def _covert_dist_to_weight(dists, ref_dist): + """ + Calculate distance weights from a matrix of distances and a + reference distance + + :type dists: np.array + :param dists: array of inter-source distances + :type ref_dist: float + :param ref_dist: user-defined reference distance in units km. + larger values for reference distances increase the sensitivity to + inter-station distances. lower values tend to reduce scatter. + """ + weights = [] + for dists_ij in dists: + # Calculate the weight for station i as the summation of + # weighted distance to all other stations j (i != j) + weight_i = 0 + for dist_ij in dists_ij: + weight_i += np.exp(-1 * (dist_ij / ref_dist) ** 2) + weights.append(1 / weight_i) + + return np.array(weights) + + def decluster_events(self, cat=None, inv=None, choice="cartesian", + zedges=None, min_mags=None, nkeep=1, + select_by="magnitude", **kwargs): + """ + Main logic function for choosing how to decluster events. Allow for + both cartesian and polar binning of the domain. + + See `_decluster_events_cartesian` and `_decluster_events_polar` for + specific input parameters to control declustering. + + + :type cat: obspy.core.catalog.Catalog + :param cat: Optional, catalog of events to consider. If none given, + will use whatever internal catalog is available + :type inv: obspy.core.inventory.Inventory + :param inv: Inventory of stations to consider + :type choice: str + :param choice: choice of domain partitioning, can be one of: + - cartesian: grid the domain as a cube with `nx` by `ny` cells + - polar: grid the domain with polar coordinates and `ntheta` bins + :type zedges: list of float + :param zedges: depth [km] slices to partition domain into. Each slice + will be given equal weighting w.r.t to all other slices, independent + of slice size. e.g., allows upweighting crustal events + :type min_mags: list + :param min_mags: a list of minimum magnitude thresholds for each depth + slice. If `zedges` is None, should be a list of length==1, which + provides minimum magnitude for entire catalog. + Elif `zedges` is given, should be a list of len(zedges)-1, which + defines minimum magnitude for each depth bin. + For example if zedges=[0, 35, 400], then one example is + min_mags=[4, 6]. Meaning between 0-34km the minimum magnitude is 4, + and between 35-400km the minimum magnitude is 6. + :type nkeep: int or list of int + :param nkeep: number of events to keep per cell. If `zedges` is None, + then this must be an integer which defines a blanket value to apply. + If `zedges` is given, then this must be a list of length + `zedges` - 1, defining the number of events to keep per cell, per + depth slice. See `min_mags` definition for example. + :type select_by: str + :param select_by: determine how to prioritize events in the cell + - magnitude (default): largest magnitudes prioritized + - magnitude_r: smallest magnitudes prioritized + - depth: shallower depths prioritized + - depth_r: deeper depths prioritized + - data: prioritize events which have the most data availability + """ + if cat is not None or inv is not None: + self.update_metadata(cat, inv) + + acceptable_select_by = ["magnitude", "magnitude_r", "depth", "depth_r", + "data", "data_r"] + assert(select_by in acceptable_select_by), \ + f"`select_by` must be in {acceptable_select_by}" + + if zedges is None: + logger.warning("`zedges` not set, all depth values will be " + "weighted equally") + zedges = [min(self.depths), max(self.depths)] + assert(isinstance(nkeep, int)), ( + f"if `zedges` not given , `nkeep` should be an integer" + ) + nkeep = [nkeep] + else: + # Make `nkeep` iterable even if given as single value + if isinstance(nkeep, int): + nkeep = [nkeep] + assert(len(nkeep) == len(zedges) - 1), ( + f"`nkeep` must be a list of integers with length of " + f"`zedges` - 1 ({len(zedges)-1}" + ) + + if choice == "cartesian": + cat = self._decluster_events_cartesian( + zedges=zedges, min_mags=min_mags, nkeep=nkeep, + select_by=select_by, **kwargs + ) + elif choice == "polar": + cat = self._decluster_events_polar( + zedges=zedges, min_mags=min_mags, nkeep=nkeep, + select_by=select_by, **kwargs + ) + + return cat + + def _decluster_events_cartesian(self, nx=10, ny=10, zedges=None, nkeep=1, + select_by="magnitude_r", plot=False, + plot_dir="./", **kwargs): + """ + Decluster event catalog by partitioning the 3D domain in the X, Y and Z + directions, and then selecting a given number of events in each cell. + + :type nx: int + :param nx: Number of X/longitude cells to partition domain into + :type ny: int + :param ny: Number of Y/latitude cells to partition domain into + :type zedges: list of float + :param zedges: depth [km] slices to partition domain into. Each slice + will be given equal weighting w.r.t to all other slices, independent + of slice size. e.g., allows upweighting crustal events + :type nkeep: int or list of int + :param nkeep: number of events to keep per cell. If `zedges` is None, + then this must be an integer which defines a blanket value to apply. + If `zedges` is given, then this must be a list of length + `zedges` - 1, defining the number of events to keep per cell, per + depth slice. See `min_mags` definition for example. + :type select_by: str + :param select_by: determine how to prioritize events in the cell + - magnitude (default): largest magnitudes prioritized + - magnitude_r: smallest magnitudes prioritized + - depth: shallower depths prioritized + - depth_r: deeper depths prioritized + - data: less data availability prioritized + - data_r: more data availability prioritized + :type plot: bool + :param plot: create a before and after catalog scatter plot to + compare which events were kept/removed. Plots within the cwd + :type plot_dir: str + :param plot_dir: directory to save figures to. file names will be + generated automatically + :rtype: obspy.core.catalog.Catalog + :return: a declustered event catalog + """ + # Figure out how to prioritize the events in each cell + if "magnitude" in select_by: + arr = self.mags + elif "depth" in select_by: + arr = self.depths + elif "data" in select_by: + arr = self.navail + else: + raise NotImplementedError + + # Ensure depth slices are ordered + zedges = sorted(zedges) + + # Generate equidistant bin edges for X and Y directions. + h, xedges, yedges = np.histogram2d( + x=self.evlons, y=self.evlats, bins=[nx, ny], + range=((self.min_lon, self.max_lon), (self.min_lat, self.max_lat)) + ) + logger.info(f"XY partitioning (events per cell)\n{h}") + + # Use a binary data array to determine which events to return + cat_flag = np.zeros(len(self.cat)) + + # Begin brute force grid search through all possible cells + for i, z_top in enumerate(zedges[:-1]): + z_bot = zedges[i+1] + for j, x_right in enumerate(xedges[:-1]): + x_left = xedges[j+1] + for k, y_bot in enumerate(yedges[:-1]): + y_top = yedges[k+1] + # Determine the indices that define the events in cell + # Use absolute values to only avoid negative signs causing + # indexing issues + idxs = np.where( + (np.abs(self.evlons) < np.abs(x_right)) & + (np.abs(self.evlons) >= np.abs(x_left)) & + (np.abs(self.evlats) >= np.abs(y_bot)) & + (np.abs(self.evlats) < np.abs(y_top)) & + (np.abs(self.depths) < np.abs(z_bot)) & + (np.abs(self.depths) >= np.abs(z_top)) + )[0] + # Ignore empty cells + if idxs.size == 0: + continue + + logger.debug(f"{len(idxs)} events found for " + f"{x_left:.2f} <= lon < {x_right:.2f}; " + f"{y_bot:.2f} <= lat < {y_top:.2f}; " + f"{z_top:.2f} <= depth < {z_bot:.2f}" + ) + + # Sort the given events by characteristic, reverse if req. + sort_arr = arr[idxs].argsort() + if "_r" in select_by: + sort_arr = sort_arr[::-1] + + # Select only the first `nkeep` events from this sorted arr + idxs = idxs[sort_arr][:nkeep[i]] + cat_flag[idxs] = 1 # flip the switch to keep these events + + if not cat_flag.any(): + logger.warning("no events found in declustered catalog") + return None + + logger.info(f"returning {len(np.where(cat_flag == 1)[0])} events in " + f"declustered catalog (og={len(self.cat)})") + + cat_out = index_cat(cat=self.cat, idxs=np.where(cat_flag == 1)[0]) + + if plot: + # Plot the original catalog + self._plot_cartesian( + cat=self.cat, inv=self.inv, xedges=xedges, yedges=yedges, + title=f"Pre-Declustered Event Catalog N={len(self.cat)}", + save=os.path.join(plot_dir, f"pre_decluster_crtsn.png") + ) + # Plot the declustered catalog + self._plot_cartesian( + cat=cat_out, inv=self.inv, xedges=xedges, yedges=yedges, + title=f"Declustered Event Catalog N={len(cat_out)}\n" + f"(zedges={zedges} / nkeep={nkeep})", + save=os.path.join(plot_dir, f"declustered_crtsn.png"), + ) + # Plot events that were removed during declustering + cat_rem = index_cat(cat=self.cat, idxs=np.where(cat_flag == 0)[0]) + + self._plot_cartesian( + cat=cat_rem, inv=self.inv, xedges=xedges, yedges=yedges, + title=f"Removed Events N={len(cat_rem)}", + save=os.path.join(plot_dir, f"removed_crtsn.png") + ) + + return cat_out + + def _decluster_events_polar(self, ntheta=16, zedges=None, nkeep=1, + select_by="magnitude_r", plot=False, + plot_dir="./", **kwargs): + """ + Run the declustering agorithm but partition the domain in polar. That + is, divide each depth slice into a pie with `ntheta` partitions and + keep events based on events within each slice of the pie. Option to + cut each slice of pie by radius (distance from center of domain) and + put additional constraints (e.g., more distant events require larger + magnitude). + + :type ntheta: int + :param ntheta: Number of theta bins to break a polar search into. + Used to break up 360 degrees, so e.g., `ntheta`==17 will return + bins of size 22.5 degrees ([0, 22.5, 45., 67.5 .... 360.]) + :type zedges: list of float + :param zedges: depth [km] slices to partition domain into. Each slice + will be given equal weighting w.r.t to all other slices, independent + of slice size. e.g., allows upweighting crustal events + :type nkeep: int or list of int + :param nkeep: number of events to keep per cell. If `zedges` is None, + then this must be an integer which defines a blanket value to apply. + If `zedges` is given, then this must be a list of length + `zedges` - 1, defining the number of events to keep per cell, per + depth slice. See `min_mags` definition for example. + :type select_by: str + :param select_by: determine how to prioritize events in the cell + - magnitude (default): largest magnitudes prioritized + - magnitude_r: smallest magnitudes prioritized + - depth: shallower depths prioritized + - depth_r: deeper depths prioritized + - data: less data availability prioritized + - data_r: more data availability prioritized + :type plot: bool + :param plot: create a before and after catalog scatter plot to + compare which events were kept/removed. Plots within the cwd + :type plot_dir: str + :param plot_dir: directory to save figures to. file names will be + generated automatically + :rtype: obspy.core.catalog.Catalog + :return: a declustered event catalog + """ + # Figure out how to prioritize the events in each cell + if "magnitude" in select_by: + arr = self.mags + elif "depth" in select_by: + arr = self.depths + elif "data" in select_by: + arr = self.navail + else: + raise NotImplementedError + + # Partition the domain in polar with `ntheta` bins + theta_array = np.linspace(0, 360, ntheta + 1) # units: deg + dtheta = theta_array[1] - theta_array[0] + + # Ensure depth slices are ordered + zedges = sorted(zedges) + + # Convert XY coordinates to polar by considering the middle of the + # domain as the origin point + mid_lat = (self.max_lat + self.min_lat) / 2 + mid_lon = (self.max_lon + self.min_lon) / 2 + # Find the distance from origin to each point + evlats = self.evlats - mid_lat + evlons = self.evlons - mid_lon + # Convert from cartesian to polar coordinates + evrad = np.sqrt(evlons**2 + evlats**2) + evtheta = np.arctan2(evlats, evlons) * 180 / np.pi + 180 # [0, 360] + + # Use a binary data array to determine which events to return + cat_flag = np.zeros(len(self.cat)) + + # Begin brute force grid search through all possible cells + for i, z_top in enumerate(zedges[:-1]): + z_bot = zedges[i + 1] + for j, theta_start in enumerate(theta_array): + theta_end = theta_start + dtheta + # Potentially the number of theta bins does not equally divide + # 360 so ensure that the last bin covers all the way to 360 + if theta_start == theta_array[-2]: + theta_end = 360 + # Determine the indices that define the events in cell + # Use absolute values to only avoid negative signs causing + # indexing issues + idxs = np.where( + (evtheta >= theta_start) & + (evtheta < theta_end) & + (np.abs(self.depths) < np.abs(z_bot)) & + (np.abs(self.depths) >= np.abs(z_top)) + )[0] + # Ignore empty cells + if idxs.size == 0: + continue + + logger.debug(f"{len(idxs)} events found for " + f"{theta_start:.2f} <= theta < {theta_end:.2f}") + + # Sort the given events by characteristic, reverse if req. + sort_arr = arr[idxs].argsort() + if "_r" in select_by: + sort_arr = sort_arr[::-1] + + # Select only the first `nkeep` events from this sorted arr + idxs = idxs[sort_arr][:nkeep[i]] + cat_flag[idxs] = 1 # flip the switch to keep these events + + if not cat_flag.any(): + logger.warning("no events found in declustered catalog") + return None + + logger.info(f"returning {len(np.where(cat_flag == 1)[0])} events in " + f"declustered catalog (og={len(self.cat)})") + + cat_out = index_cat(cat=self.cat, idxs=np.where(cat_flag == 1)[0]) + + if plot: + self._plot_polar( + self.cat, self.inv, evrad, theta_array, mid_lon, mid_lat, + title=f"Pre-Declustering Event Catalog N={len(self.cat)}", + save=os.path.join(plot_dir, f"pre_decluster_plr.png") + ) + self._plot_polar( + cat_out, self.inv, evrad, theta_array, mid_lon, mid_lat, + title=f"Declustered Event Catalog N={len(cat_out)}\n" + f"(zedges={zedges} / nkeep={nkeep})", + save=os.path.join(plot_dir, f"decluster_plr.png") + ) + # Plot events that were removed during declustering + cat_rem = index_cat(cat=self.cat, idxs=np.where(cat_flag == 0)[0]) + self._plot_polar( + cat_rem, self.inv, evrad, theta_array, mid_lon, mid_lat, + title=f"Removed Events N={len(cat_rem)}\n", + save=os.path.join(plot_dir, f"removed_plr.png") + ) + return cat_out + + def plot(self, cat=None, inv=None, color_by="depth", + connect_data_avail=False, vmin=None, vmax=None, title=None, + cmap="inferno_r", show=True, save=None, equal_scale=False, + **kwargs): + """ + Geranalized plot function used to plot an event catalog and station + inventory. + + :type cat: obspy.core.catalog.Catalog + :param cat: Catalog of events to consider. Events must include origin + information `latitude` and `longitude` + :type inv: obspy.core.inventory.Inventory + :param inv: Inventory of stations to consider + :type color_by: str + :param color_by: how to color the event markers, available are + - 'depth': color by the event depth + - 'data': color by data availability for given event + - 'custom': used by internal plotting routines to provide custom + color array to the plot + :type connect_data_avail: bool + :param connect_data_avail: connect sources and receivers with a thin + line based on data availability + :type vmin: float + :param vmin: min value for the colorbar, defaults to smallest value in + array defined by `color_by` + :type vmax: float: + :param vmax: maximum value for colorbar, defaults to largest value in + the array defined by `color_by` + :type title: str + :param title: custom user-input title for the figure, otherwise defaults + to useful information about the catalog and inventory + :type cmap: str + :param cmap: matplotlib colormap to use for array defined by `color_by` + :type show: bool + :param show: show figure in GUI + :type save: str + :param save: if given, file id for the name of the output figure to save + if not given, will not save figure + :type equal_scale: bool + :param equal_scale: set the scale of lat and lon equal, False by default + """ + # Fine-tuning look of the plot with reasonable defaults + event_marker = kwargs.get("event_marker", "o") + event_legend_mags = kwargs.get("event_legend_mags", [4, 5, 6]) + event_size_scale = kwargs.get("event_size_scale", (30, 200)) + station_marker = kwargs.get("station_marker", "v") + station_alpha = kwargs.get("station_alpha", 1) + station_markersize = kwargs.get("station_markersize", 10) + append_title = kwargs.get("append_title", True) + + # Kwargs for fine tuning some internal plotting routines. Not necessary + # for general users + event_colors = kwargs.get("event_colors", None) + event_cbar_label = kwargs.get("event_cbar_label", None) + station_colors = kwargs.get("station_colors", "None") + station_cbar_label = kwargs.get("station_cbar_label", None) + station_cmap = kwargs.get("station_cmap", "viridis") + + if cat is None: + cat = self.cat + mags = self.mags + depths = self.depths + evlats = self.evlats + evlons = self.evlons + data_avail = self.data_avail + else: + evlats = np.array([e.preferred_origin().latitude for e in cat]) + evlons = np.array([e.preferred_origin().longitude for e in cat]) + mags = np.array([event.preferred_magnitude().mag for event in cat]) + depths = np.array([event.preferred_origin().depth * 1E-3 for + event in cat]) + data_avail = get_data_availability(cat, inv) + + if connect_data_avail: + assert(inv is not None), f"`connect_data_avail` requires `inv`" + assert(data_avail is not None), \ + f"`connect_data_avail` requires `data_avail`" + + # Calculate number of stations on for each event + data = np.array([len(val) for val in data_avail.values()]) + + f, ax = plt.subplots() + + # Normalize exp of magnitudes between `a` and `b` to get good size diff. + legend_mags = sorted(event_legend_mags, reverse=True) + mags = np.append(mags, legend_mags) + mags = np.e ** mags + a, b = event_size_scale + mags = ((b - a) * (mags - mags.min()) / (mags.max() - mags.min())) + a + + # Choose how to color + if color_by == "depth": + color_arr = depths + cbar_label = "depths [km]" + elif color_by == "data": + color_arr = data + cbar_label = "data availability" + elif color_by == "custom": + color_arr = event_colors + cbar_label = event_cbar_label + else: + raise NotImplementedError + + # Plot events as a scatter of markers, sized by mag, colored by smthng + sc = ax.scatter(x=evlons, y=evlats, s=mags[:-3], c=color_arr, + marker=event_marker, cmap=cmap, edgecolor="k", + linewidth=1, vmin=vmin or color_arr.min(), + vmax=vmax or color_arr.max(), zorder=10) + plt.colorbar(sc, label=cbar_label) + + # Plot inventory if provided + if inv is not None: + if inv is True: + stalats = self.stalats + stalons = self.stalons + else: + stalats, stalons = [], [] + for net in inv: + for sta in net: + stalats.append(sta.latitude) + stalons.append(sta.longitude) + stalats = np.array(stalats) + stalons = np.array(stalons) + sc2 = plt.scatter(x=stalons, y=stalats, c=station_colors, + edgecolor="k", linewidth=1, s=station_markersize, + marker=station_marker, zorder=9, + alpha=station_alpha, cmap=station_cmap + ) + # Only used by internal plottign routines + if station_cbar_label: + plt.colorbar(sc2, label=station_cbar_label) + + # Connect sources and receivers with a straight line based on + # data availability. Assuming that data availability order is the + # same as the latitude and longitude + # NOTE: Pretty brute force so this may take a while + if connect_data_avail: + evids = np.array([event.resource_id.id for event in cat]) + for i, (event, stalist) in enumerate(data_avail.items()): + assert(evids[i] == event), f"incorrect event ID encountered" + for netsta in stalist: + net, sta = netsta.split(".") + inv_ = self.inv.select(network=net, station=sta) + assert(len(inv_) == 1), f"too many stations found" + stalat = inv_[0][0].latitude + stalon = inv_[0][0].longitude + plt.plot([evlons[i], stalon], [evlats[i], stalat], c="k", + linewidth=0.5, alpha=0.05, zorder=8) + if title is None: + title = "" + if append_title: + title += f"\n({data.sum()} source-receiver pairs)" + + # Plot attributes + buff = 0.01 + ax.set_xlim([self.min_lon - np.abs(buff * self.min_lon), + self.max_lon + np.abs(buff * self.max_lon)]) + ax.set_ylim([self.min_lat - np.abs(buff * self.min_lat), + self.max_lat + np.abs(buff * self.max_lat)]) + ax.set_xlabel("Longitude") + ax.set_ylabel("Latitude") + + if title is not None: + ax.set_title(title) + # May be useful but decided things look better without + if equal_scale: + ax.set_aspect("equal") + + # Generate a scale bar for magnitude sizes. Must do this after setting + # the x limit because we will plot based on axis display coordinates + # Display the `legend_mags` as black markers at the top left of axis + for i, x in enumerate([0.02, 0.05, 0.095]): + index = -1 * (i + 1) # -1, -2, -3,... + ax.scatter(x, 0.95, s=mags[index], c="w", edgecolor="k", + linewidth=1, transform=ax.transAxes, zorder=15) + ax.text(x, 0.9, s=f"{int(legend_mags[index]):d}", c="k", + fontsize=7, transform=ax.transAxes, ha="center", zorder=15) + + # Adjust linewidths and fontsizes to make the figure look nicer + set_plot_aesthetic(ax, xtick_major=5, xtick_minor=1, ytick_major=5, + ytick_minor=1, ytick_fontsize=12, + xtick_fontsize=12, xlabel_fontsize=15, + ylabel_fontsize=15, title_fontsize=15, + xgrid_major=True, xgrid_minor=False, + ygrid_major=True, ygrid_minor=False + ) + + if save: + plt.savefig(save) + if show: + plt.show() + + return f, ax + + def _plot_cartesian(self, cat, inv, xedges, yedges, title, save): + """Convenience function to plot catalogs with edges""" + f, ax = self.plot( + cat=cat, inv=inv, show=False, save=None, title=title, + color_by="depth", vmin=0, vmax=self.depths.max() + ) + lkwargs = dict(c="k", linewidth=0.5, alpha=0.5) + + # Add gridlines to the plot + for xe in xedges: + ax.axvline(xe, **lkwargs) + for ye in yedges: + ax.axhline(ye, **lkwargs) + + plt.savefig(save) + plt.close() + + def _plot_polar(self, cat, inv, evrad, theta_array, mid_lon, mid_lat, + title, save): + """Convenience function to plot catalogs with radial bin lines""" + f, ax = self.plot( + cat=cat, inv=inv, show=False, save=None, title=title, + color_by="depth", vmin=0, vmax=self.depths.max() + ) + + ax.scatter(mid_lon, mid_lat, c="y", edgecolor="k", marker="o", s=10, + linewidth=1) + + # Plot each of the radial bins + for theta in theta_array: + x = evrad.max() * np.cos(theta * np.pi / 180) + mid_lon + y = evrad.max() * np.sin(theta * np.pi / 180) + mid_lat + ax.plot([mid_lon, x], [mid_lat, y], "k-", alpha=0.3) + + plt.savefig(save) + plt.close() diff --git a/pysep/pysep.py b/pysep/pysep.py index e8d1dcc..08f62df 100644 --- a/pysep/pysep.py +++ b/pysep/pysep.py @@ -1,26 +1,33 @@ +#!/usr/bin/evn python3 """ -Python Seismogram Extraction and Processing +Python Seismogram Extraction and Processing (PySEP) Download, pre-process, and organize seismic waveforms, event and station -metadata - -TODO - * flesh out the template config file - * save intermediate files? or some form of checkpointing +metadata. Save waveforms as SAC files for use in moment tensor inversion and +adjoint tomography codes. """ import argparse import os +import shutil import sys import yaml import warnings -import llnl_db_client # NOQA +try: + import llnl_db_client # NOQA +except ImportError: + _has_llnl = False +else: + _has_llnl = True from glob import glob from pathlib import Path -from obspy import UTCDateTime, Stream +from obspy import UTCDateTime, Stream, Inventory, read, read_inventory from obspy.clients.fdsn import Client from obspy.clients.fdsn.header import FDSNBadRequestException +from obspy.clients.fdsn.mass_downloader import (RectangularDomain, Restrictions, + CircularDomain, MassDownloader) from obspy.core.event import Event, Origin, Magnitude +from obspy.geodetics import kilometer2degrees from pysep import logger from pysep.utils.cap_sac import (append_sac_headers, write_cap_weights_files, @@ -28,7 +35,8 @@ format_sac_headers_post_rotation) from pysep.utils.curtail import (curtail_by_station_distance_azimuth, quality_check_waveforms_before_processing, - quality_check_waveforms_after_processing) + quality_check_waveforms_after_processing, + ) from pysep.utils.fmt import format_event_tag, format_event_tag_legacy, get_codes from pysep.utils.io import read_yaml, read_event_file, write_pysep_stations_file from pysep.utils.llnl import scale_llnl_waveform_amplitudes @@ -36,22 +44,20 @@ format_streams_for_rotation, rotate_to_uvw, estimate_prefilter_corners) from pysep.utils.plot import plot_source_receiver_map -from pysep.recsec import plotw_rs +from pysep.recsec import RecordSection class Pysep: - """ - Download, preprocess, and save waveform data using ObsPy - """ + """Download, preprocess, and save waveform data using ObsPy""" def __init__(self, config_file=None, event_selection="default", client="IRIS", origin_time=None, reference_time=None, networks="*", stations="*", locations="*", channels="*", event_latitude=None, event_longitude=None, event_depth_km=None, event_magnitude=None, remove_response=True, - remove_clipped=False, water_level=60, detrend=True, - demean=True, taper_percentage=0, rotate=None, - pre_filt="default", mindistance=0, maxdistance=20E3, - minazimuth=0, maxazimuth=360, + remove_clipped=False, remove_insufficient_length=True, + water_level=60, detrend=True, demean=True, taper_percentage=0, + rotate=None, pre_filt="default", + mindistance=0, maxdistance=20E3, minazimuth=0, maxazimuth=360, minlatitude=None, minlongitude=None, maxlatitude=None, maxlongitude=None, resample_freq=None, scale_factor=1, phase_list=None, seconds_before_event=20, @@ -61,120 +67,286 @@ def __init__(self, config_file=None, event_selection="default", log_level="DEBUG", timeout=600, write_files="all", plot_files="all", llnl_db_path=None, output_dir=None, overwrite=False, legacy_naming=False, overwrite_event_tag=None, + use_mass_download=False, **kwargs): """ - Define a default set of parameters - - TODO - * removed resample_TF, was this used? - * load config FIRST and then set defaults, make all defaults None? + .. note:: + Parameters for general data gathering control :type client: str :param client: ObsPy FDSN client to query data from, e.g., IRIS, LLNL, - NCEDC or any FDSN clients accepted by ObsPy - :type network: str - :param network: name or names of networks to query for, if names plural, - must be a comma-separated list, i.e., "AK,AT,AV", else "AK". - Wildcard okay - :type station: str - :param station: station name or names to query for, wildcard okay - :type location: str - :param location: locations name or names to query for, wildcard okay - :type channel: str - :param channel: channel name or names to query for, wildcard okay - :type remove_response: bool - :param remove_response: Remove instrument response or not - :type remove_clipped: remove any clipped stations from final output - :param remove_clipped: Check if waveforms are clipped, remove if so - :type water_level: float - :param water_level: water_level to apply during filtering for small vals + NCEDC or any FDSN clients accepted by ObsPy. Defaults to 'IRIS' + :type minlatitude: float + :param minlatitude: for event, station and waveform retrieval. Defines + the minimum latitude for a rectangular bounding box that is used to + search for data. Only used for events if `event_selection`=='search' + :type maxlatitude: float + :param maxlatitude: for event, station and waveform retrieval. Defines + the maximum latitude for a rectangular bounding box that is used to + search for data. Only used for events if `event_selection`=='search' + :type minlongitude: float + :param minlongitude: for event, station and waveform retrieval. Defines + the minimum longitude for a rectangular bounding box that is used to + search for data. Only used for events if `event_selection`=='search' + :type maxlongitude: float + :param maxlongitude: for event, station and waveform retrieval. Defines + the maximum longitude for a rectangular bounding box that is used to + search for data. Only used for events if `event_selection`=='search' + :type user: str + :param user: User ID if IRIS embargoes data behind passwords. This is + passed into the instantiation of `client`. + :type password: str + :param password: Password if IRIS embargoes data behind passwords. This + is passed into the instantiation of 'client' + :type use_mass_download: bool + :param use_mass_download: Use ObsPy's mass download option to download + all available stations in the region regardless of data provider. + :type client_debug: bool + :param client_debug: turn on DEBUG mode for the ObsPy FDSN client, which + outputs information-rich log messages to std out. Use for debugging + when FDSN fails mysteriously. + :type timeout: float + :param timeout: time out time in units of seconds, passed to the + `client` to determine how long to wait for return data before + exiting. Defaults to 600s. + :type llnl_db_path: str + :param llnl_db_path: If `client`=='LLNL', PySEP assumes we are accesing + data from the LLNL waveeform database (which must be stored local). + Points to the path where this is saved. + + .. note:: + Event selection parameters + + :type event_selection: str + :param event_selection: How to define the Event which is used to define + the event origin time and hypocentral location. + - 'default': User defines Event `origin_time`, and location with + `event_latitude` and `event_longitude` + - 'search': PySEP will use `client` to search for a Catalog event + defined by `event_origintime`, `event_magnitude` and + `event_depth_km`. Buffer time around the `origin_time` can + be defined by `seconds_before_event` and `seconds_after_event`. + :type origin_time: str + :param origin_time: the event origin time used as a central reference + point for data gathering. Must be in a string format that is + recognized by ObsPy UTCDateTime. For example '2000-01-01T00:00:00'. + :type event_latitude: float + :param event_latitude: latitude of the event in units of degrees. + used for defining the event hypocenter and for removing stations + based on distance from the event. + :type event_longitude: float + :param event_longitude: longitude of the event in units of degrees. + used for defining the event hypocenter and for removing stations + based on distance from the event. + :type seconds_before_event: float + :param seconds_before_event: For event selection only, only used if + `event_selection`=='search'. Time [s] before given `origin_time` to + search for a matching catalog event from the given `client` + :type seconds_after_event: float + :param seconds_after_event: For event selection only, only used if + `event_selection`=='search'. Time [s] after given `origin_time` to + search for a matching catalog event from the given `client` + + .. note:: + Waveform and station metadata gathering parameters + + :type reference_time: str + :param reference_time: Waveform origin time. If not given, defaults to + the event origin time. This allows for a static time shift from the + event origin time, e.g., if there are timing errors with relation + to the `origin_time`. Defaults to NoneType (`origin_time`). + :type seconds_before_ref: float + :param seconds_before_ref: For waveform fetching. Defines the time + before `reference_time` to fetch waveform data. Units [s] + :type seconds_after_ref: float + :param seconds_after_ref: For waveform fetching. Defines the time + after `reference_time` to fetch waveform data. Units [s] + :type networks: str + :param networks: name or names of networks to query for, if names plural, + must be a comma-separated list, i.e., 'AK,AT,AV'. Wildcards okay, + defaults to '*'. + :type stations: str + :param stations: station name or names to query for. If multiple + stations, input as a list of comma-separated values, e.g., + 'STA01,STA02,STA03'. Wildcards acceptable, if using wildcards, use + a '-' to exclude stations (e.g., '*,-STA01' will gather all stations + available, except STA01. Defaults to '*' + :type locations: str + :param locations: locations name or names to query for, wildcard okay. + See `stations` for inputting multiple location values. Default '*'. + :type channels: str + :param channels: channel name or names to query for, wildcard okay. If + multiple stations, input as a list of comma-separated values, e.g., + 'HH?,BH?'. Wildcards acceptable. Defaults to '*'. + + .. note:: + Station removal and curtailing parameters + + :type mindistance: float + :param mindistance: Used for removing stations and mass download option + + - Removing stations: Remove any stations who are closer than the + given minimum distance away from event (units: km). Always applied + - Mass Download: If `use_mass_download` is True and + `domain_type`=='circular', defines the minimum radius around the + event hypocenter to gather waveform data and station metadata + :type maxdistance: float + :param maxdistance: Used for removing stations and mass download option + + - Removing stations: Remove any stations who are farther than the + given maximum distance away from event (units: km). Always applied + - Mass Download: If `use_mass_download` is True and + `domain_type`=='circular', defines the maximum radius around the + event hypocenter to gather waveform data and station metadata + :type minazimuth: float + :param minazimuth: for station removal. stations whose azimuth relative + to the event hypocenter that do not fall within the bounds + [`minazimuth`, `maxazimuth`] are removed from the final list. + Defaults to 0 degrees. + :param minazimuth: for station removal. stations whose azimuth relative + to the event hypocenter that do not fall within the bounds + [`minazimuth`, `maxazimuth`] are removed from the final list. + Defaults to 360 degrees. + :type remove_clipped: bool + :param remove_clipped: remove any clipped stations from gathered + stations. Checks the max amplitude of against a maximum value + expected for a 24 bit signal. Defaults False + :type remove_insufficient_length: bool + :param remove_insufficient_length: remove waveforms whose trace length + does not match the average (mode) trace length in the stream. + Defaults to True + + .. note:: + Data processing parameters + :type detrend: bool - :param detrend: apply simple detrend to data during preprocessing + :param detrend: apply simple linear detrend to data during prior to + removing instrument response (if `remove_response`==True) :type demean: bool - :param demean: apply demeaning to data during preprocessing + :param demean: apply demeaning to data during instrument reseponse + removal. Only applied if `remove_response` == True. :type taper: float :param taper: apply a taper to the waveform with ObsPy taper, fraction between 0 and 1 as the percentage of the waveform to be tapered Applied generally used when data is noisy, e.g., HutchisonGhosh2016 - To get the same results as the default taper in SAC, + Note: To get the same results as the default taper in SAC, use max_percentage=0.05 and leave type as hann. - Tapering also happens while resampling (see util_write_cap.py) - :type rotate: list of str - :param rotate: choose how to rotate the waveform data. Can include - the following options (order insensitive): + Tapering also happens while resampling (see util_write_cap.py). + Only applied if `remove_response` == True. + :type rotate: list of str or NoneType + :param rotate: choose how to rotate the waveform data. pre-rotation + processing will be applied. Can include the following options + (order insensitive): + * ZNE: Rotate from arbitrary components to North, East, Up * RTZ: Rotate from ZNE to Radial, Transverse, Up (requires ZNE) * UVW: Rotate from ZNE to orthogonal UVW orientation + If set to None, no rotation processing will take place. + :type resample_freq: float + :param resample_freq: frequency to resample data in units Hz. If not + given, no data resampling will take place. Defaults to NoneType + :type scale_factor: float + :param scale_factor: scale all data by a constant factor + Note: for CAP use 10**2 (to convert m/s to cm/s). + Defaults to NoneType (no scaling applied) + + .. note:: + Instrument response removal parameters + + :type remove_response: bool + :param remove_response: remove instrument response using station + response information gathered from `client`. Defaults to True. + :type output_unit: str + :param output_unit: the output format of the waveforms if instrument + response removal is applied. Only relevant if + `remove_response`==True. See ObsPy.core.trace.Trace.remove_response + for acceptable values. Typical values are: 'DISP', 'VEL', 'ACC' + (displacement [m], velocity [m/s], acceleration [m/s^2]). + :type water_level: float + :param water_level: a water level threshold to apply during filtering + for small values. Passed to Obspy.core.trace.Trace.remove_response :type prefilt: str, tuple or NoneType :param prefilt: apply a pre-filter to the waveforms before deconvolving instrument response. Options are: + * 'default': automatically calculate (f0, f1, f2, f3) based on the - length of the waveform (dictating longest allowable period) and - the sampling rate (dictating shortest allowable period). This is - the default behavior. + length of the waveform (dictating longest allowable period) and + the sampling rate (dictating shortest allowable period). This is + the default behavior. * NoneType: do not apply any pre-filtering * tuple of float: (f0, f1, f2, f3) define the corners of your pre - filter in units of frequency (Hz) - :type mindistance: float - :param mindistance: get waveforms from stations starting from a minimum - distance away from event (km) - :type maxdistance: float - :param maxdistance: get waveforms from stations up to a maximum distance - from event (km) - :type minazimuth: float - :param minazimuth: get waveforms from a station starting at a given - minimum azimuth (deg) out to a final maximum azimuth (deg) where - 0 degrees points North from the event - :type maxazimuth: float - :param maxazimuth: get waveforms from a station starting at a given - minimum azimuth (deg) out to a final maximum azimuth (deg) where - 0 degrees points North from the event - :type minlatitude: float - :param minlatitude: minimum latitude for bounding box to search for - stations and events - :type maxlatitude: float - :param maxlatitude: maximum latitude for bounding box to search for - stations and events - :type minlongitude: float - :param minlongitude: minimum longitude for bounding box to search for - stations and events - :type maxlongitude: float - :param maxlongitude: maximum longitude for bounding box to search for - stations and events - :type resample_freq: float - :param resample_freq: frequency to resample data at - :type scale_factor: float - :param scale_factor: scale data by a constant, for CAP use 10**2 - (to convert m/s to cm/s) + filter in units of frequency (Hz) + + .. note:: + SAC header control parameters + :type phase_list: list of str :param phase_list: phase names to get ray information from TauP with. - Defaults to direct arrivals 'P' and 'S' - :type reference_time: str - :param reference_time: Waveform origin time. Allows for a static time - shift from the event origin time, e.g., if there are timing errors - with relation to o time. If not given, defaults to event origin time - :type seconds_before_ref: float - :param seconds_before_ref: time before origintime to fetch waveform data - :type seconds_after_ref: float - :param seconds_after_ref: time after origintime to fetch waveform data + Defaults to direct arrivals 'P' and 'S'. Must match Phases expected + by TauP (see ObsPy TauP documentation for acceptable phases). Phase + information will be added to SAC headers. :type taup_model: str :param taup_model: name of TauP model to use to calculate phase arrivals - :type output_unit: str - :param output_unit: the output format of the waveforms, something like - 'DISP', 'VEL', 'ACC' - :type user: str - :param user: User ID if IRIS embargoes data behind passwords - :type password: str - :param password: Password if IRIS embargoes data behind passwords - :type overwrite: bool - :param overwrite: overwrite an existing PySEP event directory if - the current process is trying to write to it + See also `phase_list` which defines phases to grab arrival data + for. Defaults to 'AK135'. See ObsPy TauP documentation for avilable + models. + + .. note:: + PySEP Configuration parameters + + :type config_file: str + :param config_file: path to YAML configuration file which will be used + to overwrite internal default parameters. Used for command-line + version of PySEP + :type log_level: str + :param log_level: Level of verbosity for the internal PySEP logger. + In decreasing order of verbosity: 'DEBUG', 'INFO', 'WARNING', + 'CRITICAL' :type legacy_naming: bool - :param legacy_naming: revert to old PySEP naming schema for event tag, - which names the directory and output SAC files + :param legacy_naming: if True, revert to old PySEP naming schema for + event tags, which is responsible for naming the output directory and + SAC files. Legacy filenames look something like + '20000101000000.NN.SSS.LL.CC.c' (event origin time, network, + station, location, channel, component). Default to False :type overwrite_event_tag: str :param overwrite_event_tag: option to allow the user to set their own event tag, rather than the automatically generated one + + .. note:: + Output file and figure control + + :type write_files: str or NoneType + :param write_files: Which files to write out after data gathering. + Should be a comma-separated list of the following + + - weights_az: write out CAP weight file sorted by azimuth + - weights_dist: write out CAP weight file sorted by distance + - weights_code: write out CAP weight file sorted by station code + - station_list: write out a text file with station informatino + - inv: save a StationXML (.xml) file (ObsPy inventory) + - event: save a QuakeML (.xml) file (ObsPy Catalog) + - stream: save an ObsPy stream in Mseed (.ms) (ObsPy Stream) + - config_file: save YAML config file containing all input parameters + - sac: save all waveforms as SAC (.sac) files separated by component + - sac_raw: save the raw (pre-rotation) SAC files + - all: write all of the above (default value) + Example input: `write_files`=='inv,event,stream,sac' + If None, no files will be written. This is generally not advised. + :type plot_files: str or NoneType + :param write_files: What to plot after data gathering. + Should be a comma-separated list of the following: + + - map: plot a source-receiver map with event and all stations + - record_section: plot a record section with default parameters + - all: plot all of the above (default value) + If None, no files will be plotted. + :type output_dir: str + :param output_dir: path to output directory where all the files and + figures defined by `write_files` and `plot_files` will be stored. + Defaults to the current working directory. + :type overwrite: bool + :param overwrite: If True, overwrite an existing PySEP event directory. + This prevents Users from re-downloading data. Defaults to False. """ # Internal attribute but define first so that it sits at the top of # written config files @@ -188,6 +360,14 @@ def __init__(self, config_file=None, event_selection="default", self._user = user self._password = password self.taup_model = taup_model + self.use_mass_download = use_mass_download + + # Check for LLNL requirement + if self.client == "LLNL" and not _has_llnl: + raise ImportError(f"`client`=='LLNL' requires optional " + f"dependency 'llnl_db_client' which was not " + f"found. Please reinstall PySEP with the command " + f"'pip install -e .[llnl]") # Parameters related to event selection self.event_selection = event_selection @@ -217,7 +397,8 @@ def __init__(self, config_file=None, event_selection="default", self.seconds_after_ref = seconds_after_ref self.phase_list = phase_list - # NOTE: This default is a UAF LUNGS system-specific database path + # NOTE: This default is a UAF LUNGS system-specific database path. + # If you are not on LUNGS, you will need to set this path manually self.llnl_db_path = ( llnl_db_path or "/store/raw/LLNL/UCRL-MI-222502/westernus.wfdisc" @@ -237,7 +418,7 @@ def __init__(self, config_file=None, event_selection="default", self.demean = bool(demean) self.detrend = bool(detrend) self.taper_percentage = taper_percentage - self.rotate = rotate or ["ZNE", "RTZ"] + self.rotate = rotate self.remove_response = bool(remove_response) self.output_unit = output_unit self.water_level = water_level @@ -245,6 +426,7 @@ def __init__(self, config_file=None, event_selection="default", self.scale_factor = scale_factor self.resample_freq = resample_freq self.remove_clipped = bool(remove_clipped) + self.remove_insufficient_length = remove_insufficient_length # Program related parameters self.output_dir = output_dir or os.getcwd() @@ -269,6 +451,10 @@ def __init__(self, config_file=None, event_selection="default", else: logger.disabled = True + # Allow User to throw in general kwargs. This allows things to be + # more general, but also may obscure some parameters. + self.kwargs = kwargs + def check(self): """ Check input parameter validity against expected Pysep behavior @@ -284,8 +470,7 @@ def check(self): "Event selection requires the following parameters: " "`seconds_before_event` and `seconds_after_event`") elif self.event_selection == "default": - for par in [self.event_latitude, self.event_longitude, - self.event_depth_km, self.event_magnitude]: + for par in [self.event_latitude, self.event_longitude]: assert(par is not None), ( "`event_selection`=='default' requires " "`event_latitude`, `event_longitude`, `event_depth_km` " @@ -294,6 +479,10 @@ def check(self): raise ValueError("`event_selection` must be one of the following: " "'search' or 'default'") + if self.event_depth_km is None: + logger.warning("TauP arrival times will be incorrect as no depth " + "information is provided") + if self.client.upper() == "LLNL": assert(os.path.exists(self.llnl_db_path)), ( f"`llnl_db_path` {self.llnl_db_path} does not exist but must " @@ -340,8 +529,6 @@ def check(self): assert("UVW" not in self.rotate), ( f"rotate can only have one of the following: 'UVW', 'RTZ'" ) - else: - self.rotate = [] acceptable_units = ["DISP", "VEL", "ACC", "DEF"] self.output_unit = self.output_unit.upper() @@ -384,6 +571,10 @@ def check(self): f"{acceptable_plot_files}" ) + if self.use_mass_download is True: + logger.info("will use option `mass_download`, ignoring `client` " + "and downloading data from all available data centers") + def get_client(self): """ Options to choose different Clients based on attribute `client` which @@ -448,6 +639,13 @@ def load(self, config_file=None, overwrite_event=True): logger.debug(f"{key}: {old_val} -> {val}") setattr(self, key, val) + # Reset log level based on the config file + if self.log_level is not None: + logger.debug(f"`log_level` set to {self.log_level}") + logger.setLevel(self.log_level) + else: + logger.disabled = True + def get_event(self): """ Exposed API for grabbing event metadata depending on the @@ -475,12 +673,21 @@ def get_event(self): # This is how we will access the event info so print out and check lat = event.preferred_origin().latitude lon = event.preferred_origin().longitude - depth_km = event.preferred_origin().depth * 1E-3 otime = event.preferred_origin().time - mag = event.preferred_magnitude().mag + + # These values may not be present. General exception because its only + # used for log statement so not that important. + try: + depth_km = event.preferred_origin().depth * 1E-3 + except Exception: # NOQA + depth_km = None + try: + mag = event.preferred_magnitude().mag + except Exception: # NOQA + mag = None logger.info(f"event info summary - origin time: {otime}; " - f"lat={lat:.2f}; lon={lon:.2f}; depth[km]={depth_km:.2f}; " - f"magnitude={mag:.2f}") + f"lat={lat:.2f}; lon={lon:.2f}; depth[km]={depth_km}; " + f"magnitude={mag}") return event @@ -556,16 +763,27 @@ def _create_event_from_scratch(self): """ logger.info("creating event metadata with user parameters") + if self.event_depth_km is not None: + depth = self.event_depth_km * 1E3 + else: + depth = None + origin = Origin(latitude=self.event_latitude, longitude=self.event_longitude, - depth=self.event_depth_km * 1E3, # units: m + depth=depth, # units: m time=self.origin_time ) - magnitude = Magnitude(mag=self.event_magnitude, magnitude_type="Mw") + if self.event_magnitude: + magnitude = Magnitude(mag=self.event_magnitude, magnitude_type="Mw") + magnitudes = [magnitude] + else: + magnitudes = [] - event = Event(origins=[origin], magnitudes=[magnitude]) + event = Event(origins=[origin], magnitudes=magnitudes) event.preferred_origin_id = origin.resource_id.id - event.preferred_magnitude_id = magnitude.resource_id.id + + if magnitudes: + event.preferred_magnitude_id = magnitude.resource_id.id return event @@ -712,6 +930,101 @@ def _bulk_query_waveforms_from_client(self): return st + def mass_download(self): + """ + Use ObsPy Mass downloader to grab events from a pre-determined region + + Keyword Arguments + :: + str domain_type: + How to define the search region domain + - rectangular: rectangular bounding box defined by min/max + latitude/longitude + - circular: circular bounding circle defined by the events + latitude and longitude, with radii defined by `mindistance` + and `maxdistance` + bool delete_tmpdir: + Remove the temporary directories that store the MSEED and + StationXML files which were downloaded by the mass downloader. + Saves space but also if anything fails prior to saving data, + the downloaded data will not be saved. Defaults to True. + """ + domain_type = self.kwargs.get("domain_type", "rectangular") + delete_tmpdir = self.kwargs.get("delete_tmpdir", True) + # Get around the fact that command line arguments are input as strings + if isinstance(delete_tmpdir, str): + assert(delete_tmpdir.capitalize() in ["True", "False"]) + delete_tmpdir = bool(delete_tmpdir.capitalize() == "True") + + logger.info("using ObsPy mass downloader to download waveform and " + "station metadata") + + # Define the bounding box/circle that specifies our region of interest + if domain_type == "rectangular": + logger.info("using a rectangular domain for mass downloader") + domain = RectangularDomain(minlatitude=self.minlatitude, + maxlatitude=self.maxlatitude, + minlongitude=self.minlongitude, + maxlongitude=self.maxlongitude) + elif domain_type == "circular": + logger.info("using a circular domain for mass downloader") + domain = CircularDomain( + latitude=self.event_latitude, longitude=self.event_longitude, + minradius=kilometer2degrees(self.mindistance), + maxradius=kilometer2degrees(self.maxdistance) + ) + else: + raise NotImplementedError(f"`domain_type` must be 'rectangular' or" + f"'circular'") + + # Drop any excluded stations + stations = ",".join([sta for sta in self.stations.split(",") + if "-" not in sta]) + sta_exclude = [sta[1:] for sta in self.stations.split(",") + if "-" in sta] + networks = ",".join([sta for sta in self.networks.split(",") + if "-" not in sta]) + net_exclude = [net[1:] for net in self.networks.split(",") + if "-" in net] + + # Set restrictions on the search criteria for data + restrictions = Restrictions( + starttime=self.reference_time - self.seconds_before_ref, + endtime=self.reference_time + self.seconds_after_ref, + reject_channels_with_gaps=False, minimum_length=0., + network=networks, station=stations, location=self.locations, + channel=self.channels, exclude_networks=net_exclude, + exclude_stations=sta_exclude, + ) + + # Mass downloader will download files to a temp directory which we + # will read back from to continue the workflow + tmp_dir = os.path.join(self.output_dir, "tmpdir_md") + tmp_wav = os.path.join(tmp_dir, "waveforms") + tmp_inv = os.path.join(tmp_dir, "inventory") + + mdl = MassDownloader() + mdl.download(domain, restrictions, mseed_storage=tmp_wav, + stationxml_storage=tmp_inv, download_chunk_size_in_mb=20, + threads_per_client=3, print_report=True) + + # Read back in waveforms and stationxml data + st = Stream() + for fid in glob(os.path.join(tmp_wav, "*.mseed")): + st += read(fid) + logger.info(f"mass downloader downloaded {len(st)} traces") + + inv = Inventory() + for fid in glob(os.path.join(tmp_inv, "*.xml")): + inv += read_inventory(fid) + + # Delete the tmpdir + if delete_tmpdir: + logger.info("deleting temporary mass downloader directories") + shutil.rmtree(tmp_dir) + + return st, inv + def curtail_stations(self): """ Remove stations from `inv` based on station distance, azimuth, etc. @@ -856,6 +1169,7 @@ def rotate_streams(self): other components """ st_raw = self.st.copy() + st_raw = format_streams_for_rotation(st_raw) # For writing RAW seismograms (prior to ANY rotation). Must be @@ -864,7 +1178,7 @@ def rotate_streams(self): if "sac_raw" in self.write_files: self.st_raw = st_raw.copy() - # Empty stream so we can take advantage of class __add__ method + # Empty stream, so we can take advantage of class __add__ method st_out = Stream() # RTZ requires rotating to ZNE first. Make sure this happens even if the @@ -873,44 +1187,83 @@ def rotate_streams(self): logger.info("rotating to components ZNE") st_zne = st_raw.copy() stations = set([tr.stats.station for tr in st_zne]) + # Assuming each channel has its own azimuth and dip value + channels = set([f"{tr.stats.channel[:-1]}?" for tr in st_zne]) + metadata_getter = self.inv.get_channel_metadata for sta in stations: - _st = st_zne.select(station=sta) - _inv = self.inv.select(station=sta) - # Print out azimuth and dip angles for debugging purposes - for _net in _inv: - for _sta in _net: - for _cha in _sta: - logger.debug( - f"rotating -> ZNE " - f"{_net.code}.{_sta.code}.{_cha.code} with " - f"az={_cha.azimuth}, dip={_cha.dip}" - ) - # components=['ZNE'] FORCES rotation using azimuth and dip - # values, even if components are already in 'ZNE'. This is - # important as some IRIS data will be in ZNE but not be aligned - # https://github.com/obspy/obspy/issues/2056 - _st.rotate(method="->ZNE", inventory=self.inv, - components=["ZNE"]) - st_out += st_zne + for cha in channels: + _st = st_zne.select(station=sta, channel=cha) + + # Check if 'dip' or 'azimuth' is None, because that causes + # ObsPy rotate to throw a TypeError. See PySEP Issue #35 + channel_okay = bool(_st) + for _tr in _st: + try: + meta = metadata_getter(_tr.id, _tr.stats.starttime) + az = meta["azimuth"] + dip = meta["dip"] + except Exception: + logger.warning(f"no matching metadata for {_tr.id}") + channel_okay = False + break + + logger.debug(f"{_tr.id} azimuth=={az}; dip=={dip}") + if az is None or dip is None: + channel_okay = False + break + + if not channel_okay: + logger.warning(f"{sta}.{cha} bad rotation metadata, " + f"removing") + continue + + # components=['ZNE'] FORCES rotation using azimuth and dip + # values, even if components are already in 'ZNE'. This is + # important as some IRIS data will be in ZNE but not be + # aligned (https://github.com/obspy/obspy/issues/2056) + try: + _st.rotate(method="->ZNE", inventory=self.inv, + components=["ZNE", "Z12", "123"]) + # General error catching for rotation because any number of + # things can go wrong here based on the ObsPy rotation algo + except Exception as e: + logger.warning(f"rotate issue for {sta}.{cha}, " + "removing from stream") + logger.debug(f"rotate error: {e}") + continue + st_out += _st + # Check to see if rotation errors kicked out all stations + if not st_out: + logger.critical("rotation errors have reduced Stream to len 0, " + "cannot continue") + sys.exit(-1) + # Rotate to radial transverse coordinate system + if "RTZ" in self.rotate: + logger.info("rotating to components RTZ") + # If we rotate the ENTIRE stream at once, ObsPy only uses the + # first backazimuth value which will create incorrect outputs + # https://github.com/obspy/obspy/issues/2623 + st_rtz = st_out.copy() # contains ZNE rotated components + stations = set([tr.stats.station for tr in st_rtz]) + for sta in stations: + _st = st_rtz.select(station=sta, channel=cha) + if _st and hasattr(_st[0].stats, "back_azimuth"): + _st.rotate(method="NE->RT") # in place rot. + st_out += _st + else: + logger.warning(f"no back azimuth for '{sta}', cannot " + f"rotate NE->RT") + continue + # Allow UVW rotation independent on ENZ or RTZ rotation if "UVW" in self.rotate: logger.info("rotating to components UVW") - st_uvw = rotate_to_uvw(st_out) + st_uvw = rotate_to_uvw(st_raw) st_out += st_uvw - elif "RTZ" in self.rotate: - logger.info("rotating to components RTZ") - # If we rotate the ENTIRE stream at once, ObsPy will only use the - # first backazimuth value which will create incorrect outputs - # https://github.com/obspy/obspy/issues/2623 - st_rtz = st_zne.copy() # `st_zne` has been rotated to ZNE - stations = set([tr.stats.station for tr in st_rtz]) - for sta in stations: - _st = st_rtz.select(station=sta) - _st.rotate(method="NE->RT") # in place rot. - if hasattr(_st[0].stats, "back_azimuth"): - logger.debug(f"{sta}: BAz={_st[0].stats.back_azimuth}") - st_out += st_rtz - - st_out = format_sac_headers_post_rotation(st_out) + + try: + st_out = format_sac_headers_post_rotation(st_out) + except AttributeError as e: + logger.warning(f"cannot format SAC headers after rotating {e}") return st_out @@ -957,12 +1310,14 @@ def write(self, write_files=None, _return_filenames=False, :type stream_fid: optional name for saved ObsPy Stream miniseed object, defaults to 'stream.ms' """ + # Collect kwargs for writing + order_stations_list_by = kwargs.get("order_stations_list_by", None) + # This is defined here so that all these filenames are in one place, # but really this set is just required by check(), not by write() _acceptable_files = {"weights_az", "weights_dist", "weights_code", "station_list", "inv", "event", "stream", - "config_file", "sac", "sac_raw", "sac_rotated", - "all"} + "config_file", "sac", "sac_raw", "all"} if _return_filenames: return _acceptable_files @@ -995,7 +1350,10 @@ def write(self, write_files=None, _return_filenames=False, stations_fid or "stations_list.txt") logger.info("writing stations file") logger.debug(fid) - write_pysep_stations_file(self.inv, self.event, fid) + write_pysep_stations_file( + self.inv, self.event, fid, + order_stations_list_by=order_stations_list_by + ) if "inv" in write_files or "all" in write_files: fid = os.path.join(self.output_dir, inv_fid or f"inv.xml") @@ -1091,8 +1449,6 @@ def write_config(self, fid=None): def plot(self): """ Plot map and record section if requested - - TODO improve source receiver map plotting """ if "map" in self.plot_files or "all" in self.plot_files: logger.info("plotting source receiver map") @@ -1102,8 +1458,10 @@ def plot(self): if "record_section" in self.plot_files or "all" in self.plot_files: fid = os.path.join(self.output_dir, f"record_section.png") # Default settings to create a general record section - plotw_rs(st=self.st, sort_by="distance_r", scale_by="normalize", - overwrite=True, show=False, save=fid) + rs = RecordSection(st=self.st, sort_by="distance", + scale_by="normalize", overwrite=True, show=False, + save=fid) + rs.run() def _event_tag_and_output_dir(self): """ @@ -1170,22 +1528,31 @@ def run(self, event=None, inv=None, st=None, **kwargs): self.event_tag, self.output_dir = self._event_tag_and_output_dir() - if inv is None: - self.inv = self.get_stations() - else: - self.inv = inv - self.inv = self.curtail_stations() + # Standard method of retrieving waveforms from data center + if self.use_mass_download is False: + if inv is None: + self.inv = self.get_stations() + else: + self.inv = inv + self.inv = self.curtail_stations() - # Get waveforms, format and assess waveform quality - if st is None: - self.st = self.get_waveforms() + # Get waveforms, format and assess waveform quality + if st is None: + self.st = self.get_waveforms() + else: + self.st = st + # Use ObsPy's mass download option to gather all available data else: - self.st = st - self.st = quality_check_waveforms_before_processing(self.st) + self.st, self.inv = self.mass_download() + + self.st = quality_check_waveforms_before_processing( + self.st, remove_clipped=self.remove_clipped + ) self.st = append_sac_headers(self.st, self.event, self.inv) if self.taup_model is not None: self.st = format_sac_header_w_taup_traveltimes(self.st, - self.taup_model) + self.taup_model, + self.phase_list) # Waveform preprocessing and standardization self.st = self.preprocess() @@ -1196,10 +1563,12 @@ def run(self, event=None, inv=None, st=None, **kwargs): self.st = self.rotate_streams() # Final quality checks on ALL waveforms before we write them out - self.st = quality_check_waveforms_after_processing(self.st) + self.st = quality_check_waveforms_after_processing( + self.st, remove_insufficient_length=self.remove_insufficient_length + ) # Generate outputs for user consumption - self.write(**kwargs) + self.write(**{**kwargs, **self.kwargs}) self.plot() @@ -1239,7 +1608,7 @@ def parse_args(): "filled in by the User") parser.add_argument("-l", "--list", default=False, action="store_true", help="list out avaialable `preset` config options") - parser.add_argument("-L", "--log_level", default="INFO", type=str, + parser.add_argument("-L", "--log_level", default="DEBUG", type=str, nargs="?", help="verbosity of logging: 'WARNING', " "'INFO', 'DEBUG'") parser.add_argument("--legacy_naming", default=False, action="store_true", diff --git a/pysep/recsec.py b/pysep/recsec.py index bef2a11..54bd74c 100755 --- a/pysep/recsec.py +++ b/pysep/recsec.py @@ -6,16 +6,19 @@ plotting script. The intent of this script is to plot multiple time series' based on source-receiver characteristics (i.e., src-rcv distance, backazimuth). -.. note:: Code History - Written by Carl Tape (11/21/2011) and Yun Wang (11/2011) in Matlab - Translated to Python by Nealy Sims (1/2021) - Upgraded by Aakash Gupta (9/2021) - Refactored by Bryant Chow (3/2022) +.. note:: + Code History: + - Written by Carl Tape (11/21/2011) and Yun Wang (11/2011) in Matlab + - Translated to Python by Nealy Sims (1/2021) + - Upgraded by Aakash Gupta (9/2021) + - Refactored by Bryant Chow (3/2022) + - Currently maintained by adjTomo Dev Team .. requires:: obspy >= 1.2 (expected to bring in numpy and matplotlib) -.. rubric:: Examples +.. rubric:: + 1) Print the help message to see available options and flags $ python recsec.py -h @@ -105,28 +108,6 @@ DEG = u"\N{DEGREE SIGN}" -def myround(x, base=5, choice="near"): - """ - Round value x to nearest base, round 'up','down' or to 'near'est base - - :type x: float - :param x: value to be rounded - :type base: int - :param base: nearest integer to be rounded to - :type choice: str - :param choice: method of rounding, 'up', 'down' or 'near' - :rtype roundout: int - :return: rounded value - """ - if choice == "near": - roundout = int(base * round(float(x)/base)) - elif choice == "down": - roundout = int(base * np.floor(float(x)/base)) - elif choice == "up": - roundout = int(base * np.ceil(float(x)/base)) - return roundout - - class Dict(dict): """Simple dictionary overload for nicer get/set attribute characteristics""" def __setattr__(self, key, value): @@ -138,9 +119,10 @@ def __getattr__(self, key): class RecordSection: """ - Record section plotting tool which takes ObsPy streams and + Record section plotting tool which takes ObsPy streams and: + 1) preprocesses and filters waveforms, - 2) sorts source-receiver pairs based on User input, + 2) sorts source-receiver pairs based on User input, 3) produces record section waveform figures. """ def __init__(self, pysep_path=None, syn_path=None, stations=None, @@ -150,7 +132,7 @@ def __init__(self, pysep_path=None, syn_path=None, stations=None, preprocess=None, max_traces_per_rs=None, integrate=0, xlim_s=None, components="ZRTNE12", y_label_loc="default", y_axis_spacing=1, amplitude_scale_factor=1, - azimuth_start_deg=0., distance_units="km", + azimuth_start_deg=0., distance_units="km", tmarks=None, geometric_spreading_factor=0.5, geometric_spreading_k_val=None, geometric_spreading_exclude=None, geometric_spreading_ymax=None, geometric_spreading_save=None, @@ -158,21 +140,21 @@ def __init__(self, pysep_path=None, syn_path=None, stations=None, overwrite=False, log_level="DEBUG", cartesian=False, synsyn=False, **kwargs): """ - Set the default record section plotting parameters and enforce types. - Run some internal parameter derivation functions by manipulating input - data and parameters. + .. note:: + Used for reading in Pysep-generated waveforms :type pysep_path: str :param pysep_path: path to Pysep output, which is expected to contain - trace-wise SAC waveform files which will be read + trace-wise SAC waveform files which will be read in. + + .. note:: + Used for reading in SPECFEM-generated synthetic waveforms + :type syn_path: str - :param syn_path: path to SPECFEM generated ASCII synthetics. - :type st: obspy.core.stream.Stream - :param st: Stream objects containing observed time series to be plotted - on the record section. Can contain any number of traces - :type st_syn: obspy.core.stream.Stream - :param st_syn: Stream objects containing synthetic time series to be - plotted on the record section. Must be same length as `st` + :param syn_path: full path to directory containing synthetic + seismograms that have been outputted by SPECFEM. The synthetics + are expected in the format: '*??.*.*.sem?*', which generally matches + SPECFEM files like 'NZ.BFZ.BXE.semd' :type stations: str :param stations: full path to STATIONS file used to define the station coordinates. Format is dictated by SPECFEM @@ -180,10 +162,36 @@ def __init__(self, pysep_path=None, syn_path=None, stations=None, :type cmtsolution: required for synthetics, full path to SPECFEM source file, which was used to generate SPECFEM synthetics. Example filenames are CMTSOLUTION, FORCESOLUTION, SOURCE. + :type cartesian: bool + :param cartesian: lets RecSec know that the domain is set in Cartesian + coordinates (SPECFEM2D or SPECFEM3D_CARTESIAN in UTM), such that + data/metadata reading will need to adjust acoordingly because the + ObsPy tools used to read metadata will fail for domains defined in + XYZ + :type synsyn: bool + :param synsyn: flag to let RecSec know that we are plotting two sets + of synthetic seismograms. Such that both `pysep_path` and `syn_path` + will be both attempt to read in synthetic data. Both sets of + synthetics MUST share the same `cmtsolution` and `stations` metadata + + .. note:: + Used for defining user-input waveforms data + + :type st: obspy.core.stream.Stream + :param st: Stream objects containing observed time series to be plotted + on the record section. Can contain any number of traces + :type st_syn: obspy.core.stream.Stream + :param st_syn: Stream objects containing synthetic time series to be + plotted on the record section. Must be same length as `st` + + .. note:: + Waveform plotting organization parameters + :type sort_by: str :param sort_by: How to sort the Y-axis of the record section, available: + - 'default': Don't sort, just iterate directly through Stream - - 'alphabetical': sort alphabetically A->Z. Components sorted + - 'alphabetical': sort alphabetically A->Z. Components sorted separately with parameter `components` - 'azimuth': sort by source-receiver azimuth (deg) with constant vertical spacing on the y-axis. Requires `azimuth_start_deg` @@ -199,28 +207,33 @@ def __init__(self, pysep_path=None, syn_path=None, stations=None, source-receiver backazimuth (deg). - '*_r': Add a '_r' to any of the values about to REVERSE the sort, e.g., 'alphabetical_r' sort will go Z->A - :type scale_by: list + :type scale_by: str :param scale_by: scale amplitude of waveforms by available: + - None: Not set, no amplitude scaling, waveforms shown raw - 'normalize': scale each trace by the maximum amplitude, i.e., > a /= max(abs(a)) # where 'a' is time series amplitudes - 'global_norm': scale by the largest amplitude to be displayed on - the screen. Will not consider waveforms which have been + the screen. Will not consider waveforms which have been excluded on other basis (e.g., wrong component) i.e., > st[i].max /= max([max(abs(tr.data)) for tr in st]) - 'geometric_spreading': scale amplitudes by expected reduction through geometric spreading. Related parameters are: - - `geometric_spreading_factor` - - `geometric_spreading_k_val` - - `geometric_spreading_exclude` - - `geometric_spreading_ymax` + + - `geometric_spreading_factor` + - `geometric_spreading_k_val` + - `geometric_spreading_exclude` + - `geometric_spreading_ymax` A + Equation is A(d) = k / sin(d) ** f + Where A(d) is the amplitude reduction factor as a function of distnace, d. 'k' is the `geometric_spreading_k_val` and 'f' is the `geometric_spreading_factor`. 'k' is calculated automatically if not given. :type time_shift_s: float OR list of float :param time_shift_s: apply static time shift to waveforms, two options: + 1. float (e.g., -10.2), will shift ALL waveforms by that number (i.e., -10.2 second time shift applied) 2. list (e.g., [5., -2., ... 11.2]), will apply individual time @@ -229,6 +242,7 @@ def __init__(self, pysep_path=None, syn_path=None, stations=None, :type zero_pad_s: list :param zero_pad_s: zero pad data in units of seconsd. applied after tapering and before filtering. Input as a tuple of floats, + * (start, end): a list of floats will zero-pad the START and END of the trace. Either can be 0 to ignore zero-padding at either end @@ -236,6 +250,7 @@ def __init__(self, pysep_path=None, syn_path=None, stations=None, :param amplitude_scale_factor: apply scale factor to all amplitudes. Used as a dial to adjust amplitudes manually. Defaults to 1. Two options: + 1. float (e.g., 1.2), will multiply ALL waveforms by that number 2. list (e.g., [5., -2., ... 11.2]), will apply individual amplitude scale to EACH trace in the stream. The length of this list MUST @@ -246,22 +261,30 @@ def __init__(self, pysep_path=None, syn_path=None, stations=None, their source receiver distance. This parameter will be ADDED to time_shift_s (both float and list), if it is provided. Should be in units of `distance_units`/s - :type min_period_s: float - :param min_period_s: minimum filter period in seconds - :type max_period_s: float - :param max_period_s: maximum filter period in seconds + :type azimuth_start_deg: float + :param azimuth_start_deg: If sorting by azimuth, this defines the + azimuthal angle for the waveform at the top of the figure. + Set to 0 for default behavior + :type distance_units: str + :param distance_units: Y-axis units when sorting by epicentral distance + 'km': kilometers on the sphere + 'deg': degrees on the sphere + 'km_utm': kilometers on flat plane, UTM coordinate system + + .. note:: + Data processing parameters + :type preprocess: str :param preprocess: choose which data to preprocess, options are: + - None: do not run preprocessing step, including filter (Default) - 'st': process waveforms in `st` - 'st_syn': process waveforms in `st_syn`. st still must be given - 'both': process waveforms in both `st` and `st_syn` - :type max_traces_per_rs: int - :param max_traces_per_rs: maximum number of traces to show on a single - record section plot. Defaults to all traces in the Stream - :type xlim_s: list of float - :param xlim_s: [start, stop] in units of time, seconds, to set the - xlimits of the figure + :type min_period_s: float + :param min_period_s: minimum filter period in seconds + :type max_period_s: float + :param max_period_s: maximum filter period in seconds :type components: str :param components: a sequence of strings representing acceptable components from the data. Also determines the order these are shown @@ -272,34 +295,14 @@ def __init__(self, pysep_path=None, syn_path=None, stations=None, :param integrate: apply integration `integrate` times on all traces. acceptable values [-inf, inf], where positive values are integration and negative values are differentiation + e.g., if integrate == 2, will integrate each trace twice. or if integrate == -1, will differentiate once or if integrate == 0, do nothing (default) - :type y_axis_spacing: float - :param y_axis_spacing: spacing between adjacent seismograms applied to - Y-axis on relative (not absolute) scales. Defaults to 1. - :type y_label_loc: str - :param y_label_loc: Location to place waveform labels on the y-axis - - 'default': auto choose the best location based on `sort_by` - - 'y_axis': Replace tick labels on the y-axis (left side of figure), - This won't work if using absolute sorting and will be over- - written by 'default' - - 'y_axis_right': Replace tick labels on the right side of the - y-axis. This option won't work with absolute sorting - - 'x_min': Place labels on top of the waveforms at the global min - x-value on the figure - - 'x_min': Place labels on top of the waveforms at the global max - x-value on the figure - - None: Don't plot any text labels - :type azimuth_start_deg: float - :param azimuth_start_deg: If sorting by azimuth, this defines the - azimuthal angle for the waveform at the top of the figure. - Set to 0 for default behavior - :type distance_units: str - :param distance_units: Y-axis units when sorting by epicentral distance - 'km': kilometers on the sphere - 'deg': degrees on the sphere - 'km_utm': kilometers on flat plane, UTM coordinate system + + .. note:: + Geometric spreading parameters, used for amplitude scaling + :type geometric_spreading_factor: float :param geometric_spreading_factor: factor to scale amplitudes by predicting the expected geometric spreading amplitude reduction and @@ -321,8 +324,41 @@ def __init__(self, pysep_path=None, syn_path=None, stations=None, whatever the peak y-value plotted is. :type geometric_spreading_save: str :param geometric_spreading_save: file id to save separate geometric - spreading scatter plot iff `scale_by`=='geometric_spreading'. If + spreading scatter plot iff `scale_by`=='geometric_spreading'. If NoneType, will not save. By default, turned OFF + + .. note:: + Figure generation control parameters + + :type max_traces_per_rs: int + :param max_traces_per_rs: maximum number of traces to show on a single + record section plot. Defaults to all traces in the Stream + :type xlim_s: list of float + :param xlim_s: [start, stop] in units of time, seconds, to set the + xlimits of the figure + :type y_axis_spacing: float + :param y_axis_spacing: spacing between adjacent seismograms applied to + Y-axis on relative (not absolute) scales. Defaults to 1. + :type y_label_loc: str + :param y_label_loc: Location to place waveform labels on the y-axis + + - 'default': auto choose the best location based on `sort_by` + - 'y_axis': Replace tick labels on the y-axis (left side of figure), + This won't work if using absolute sorting and will be over- + written by 'default' + - 'y_axis_right': Replace tick labels on the right side of the + y-axis. This option won't work with absolute sorting + - 'x_min': Place labels on top of the waveforms at the global min + x-value on the figure + - 'x_min': Place labels on top of the waveforms at the global max + x-value on the figure + - None: Don't plot any text labels + :type tmarks: list of float + :param tmarks: place vertical lines at given reference times. Used for + marking reference times such as the event origin, or phase arrival. + Input as a list of times in units of seconds (where T=0 is the + event origin time). For example `tmarks`=[0, 100, 200] would set + vertical lines at 0s, 100s and 200s :type figsize: tuple of float :param figsize: size the of the figure, passed into plt.subplots() :type show: bool @@ -330,22 +366,17 @@ def __init__(self, pysep_path=None, syn_path=None, stations=None, :type save: str :param save: path to save output figure, will create the parent directory if it doesn't exist. If None, will not save. + + .. note:: + Internal RecSec parameters + :type overwrite: bool :param overwrite: if the path defined by `save` exists, will overwrite the existing figure :type log_level: str - :param log_level: level of the internal logger, 'WARNING', 'INFO', - 'DEBUG'. - :type cartesian: bool - :param cartesian: lets RecSec know that the domain is set in Cartesian - coordinates, such that data/metadata reading will need to adjust - acoordingly because the ObsPy tools used to read metadata will fail - for domains defined in XYZ - :type synsyn: bool - :param synsyn: flag to let RecSec know that we are plotting two sets - of synthetic seismograms. Such that both `pysep_path` and `syn_path` - will be read in as synthetics. Both sets of synthetics MUST share - the same SOURCE and STATIONS metadata + :param log_level: level of the internal logger. In order of ascending + verbosity: 'CRITICAL', 'WARNING', 'INFO', 'DEBUG'. + :raises AssertionError: if any parameters are set incorrectly """ # Set the logger level before running anything @@ -428,6 +459,7 @@ def __init__(self, pysep_path=None, syn_path=None, stations=None, self.xlim_s = xlim_s self.distance_units = distance_units.lower() self.y_label_loc = y_label_loc + self.tmarks = tmarks self.figsize = figsize self.show = bool(show) self.save = save @@ -455,7 +487,7 @@ def __init__(self, pysep_path=None, syn_path=None, stations=None, self.sorted_idx = [] def _generate_synthetic_stream(self, syn_path, source, stations, - cartesian=False, fmt="*??.*.*.sem?*"): + cartesian=False, fmt="*.*.*.sem?*"): """ Convenience fucntion to read in synthetic seismograms from SPECFEM2D, SPECFEM3D or SPECFEM3D_GLOBE. Can be used to read in both `st` and @@ -1420,6 +1452,11 @@ def plot(self, subset=None, page_num=None, **kwargs): choice=choice, **kwargs) logger.debug(log_str) + + # Plot vertical bars at given reference times + if self.tmarks: + self._plot_tmarks() + # Change the aesthetic look of the figure, should be run before other # set functions as they may overwrite what is done here self.ax = set_plot_aesthetic(ax=self.ax, **self.kwargs) @@ -1521,6 +1558,20 @@ def _plot_trace(self, idx, y_index, choice="st"): return log_str + def _plot_tmarks(self): + """ + Plot vertical lines at given reference times based on user input values + """ + c = self.kwargs.get("tmark_c", "r") + lw = self.kwargs.get("tmark_lw", 1.5) + ls = self.kwargs.get("tmark_ls", "-") + alpha = self.kwargs.get("tmark_alpha", 0.75) + z = self.kwargs.get("tmark_zorder", 5) + + for tmark in self.tmarks: + plt.axvline(x=tmark, c=c, linewidth=lw, linestyle=ls, zorder=z, + alpha=alpha) + def _plot_azimuth_bins(self): """ If plotting by azimuth, create visual bin separators so the user has @@ -1796,8 +1847,6 @@ def _plot_title(self, nwav=None): Create the title of the plot based on event and station information Allow dynamic creation of title based on user input parameters - TODO Can we make this two-column to save space? - :type nwav: int :param nwav: if using subset, the title needs to know how many waveforms it's showing on the page. self.plot() should tell it @@ -1820,10 +1869,20 @@ def _plot_title(self, nwav=None): # HYPO: If only one event, show hypocenter information if self.stats.nevents == 1: sac = self.st[0].stats.sac + # Accomodate unknown depth and magnitude + if "evdp" in sac: + evdp = f"{sac['evdp']:.2f}km" + else: + evdp = "None" + if "mag" in sac: + mag = f"M{sac['mag']:.2f}" + else: + mag = "None" + # HYPO: lon, lat, depth, mag hypo = ( f"\nHYPO: ({sac['evlo']:.2f}{DEG}, {sac['evla']:.2f}{DEG}), " - f"Z={sac['evdp']:.2f}km, M{sac['mag']:.2f}" + f"Z={evdp}, Mag={mag}" ) else: hypo = "" @@ -1862,6 +1921,16 @@ def _plot_title(self, nwav=None): ) self.ax.set_title(title) + def run(self): + """ + Convenience run function to run the RecordSection workflow in order. + No internal logic for breaking the figure up into multiple record + sections. For that see main function `plotw_rs`. + """ + self.process_st() + self.get_parameters() + self.plot() + def parse_args(): """ @@ -2001,6 +2070,10 @@ def parse_args(): "starting value, with azimuth 0 <= az <= 360") parser.add_argument("--distance_units", default="km", type=str, nargs="?", help="Set units when sorting by distance") + parser.add_argument("--tmarks", default=None, type=float, + nargs="+", help="Plot vertical lines at given reference" + "times [s]. Input as a list of values, " + "e.g., --tmarks 0 100 200") parser.add_argument("--save", default="./record_section.png", type=str, nargs="?", help="Path to save the resulting record section fig") @@ -2030,9 +2103,10 @@ def parse_args(): def plotw_rs(*args, **kwargs): """ - Main call function, replacing `plotw_rs`. Run the record section plotting - functions in order. Contains the logic for breaking up figure into multiple - pages. + Main call function for command line use of RecordSection. + + Runs the record section plotting functions in order. Contains the logic for + breaking up figure into multiple pages. .. note:: All arguments should be parsed into the argparser, *args and **kwargs @@ -2049,13 +2123,20 @@ def plotw_rs(*args, **kwargs): rs.plot() # More complicated case where we need to split onto multiple pages else: - for i, start in enumerate(np.arange(0, len(rs.st), - rs.max_traces_per_rs)): - stop = start + rs.max_traces_per_rs - # Case where the num waveforms is less than max_traces_per_rs - if stop < rs.max_traces_per_rs: - stop = len(rs.st) - rs.plot(subset=[start, stop], page_num=i+1) + # Iterate backwards through the range so that the order of pages is + # more natural, i.e., plotting the record section from the top down, + # rather than the bottom up + rnge = np.arange(len(rs.st), 0, -1 * rs.max_traces_per_rs) + + # When `max_traces_per_rs` is not an integer divisor of the number of + # streams, the range will not hit zero, so we need to ensure it does + if rnge[-1] != 0: + rnge = np.append(rnge, 0) + + for i, stop in enumerate(rnge[:-1]): + j = i + 1 + start = rnge[j] + rs.plot(subset=[start, stop], page_num=j) _end = datetime.now() logger.info(f"finished record section in t={(_end - _start)}s") diff --git a/pysep/tests/test_data/test_12Z_data/inv.xml b/pysep/tests/test_data/test_12Z_data/inv.xml new file mode 100644 index 0000000..588afc8 --- /dev/null +++ b/pysep/tests/test_data/test_12Z_data/inv.xml @@ -0,0 +1,1887 @@ + + + IRIS-DMC + IRIS-DMC + IRIS WEB SERVICE: fdsnws-station | version: 1.1.52 + http://service.iris.edu/fdsnws/station/1/query?starttime=2012-04-11T09%3A20%3A17.444000&endtime=2012-04-11T09%3A31%3A57.444000&network=IU&station=COLA&location=%2A&channel=BH%3F%2CHH%3F&level=response + 2022-12-08T02:54:50.056900Z + + Global Seismograph Network - IRIS/USGS (GSN) + 10.7914/SN/IU + + 128 + 1 + + (GSN) IRIS/USGS (IU), Univ. of Alaska, and ANSS + 64.873599 + -147.8616 + 200.0 + + College Outpost, Alaska, USA + + 2009-07-09T00:00:00.000000Z + 144 + 9 + + 64.873599 + -147.8616 + 80.0 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[SENSOR::STS-2::80414], [LOGGER::Q330::742] + 2006-08-18T18:10:00.000000Z + 2011-05-02T21:13:30.000000Z + + 64.7774 + -141.1581 + 296.6 + 0.0 + 0.0 + 0.0 + TRIGGERED + GEOPHYSICAL + 100.0 + + KINEMETRICS + Accelerometer + KINEMETRICS + EPISENSOR ES-T + 2020 + + + QUANTERRA + QUANTERRA + Q330 + 742 + + + + 428186.0 + 1.0 + + m/s**2 + Acceleration in meters per second squared + + + counts + Digital Count in Digital counts + + + + + + + [SENSOR::EPISENSOR ES-T::2020], [SENSOR::STS-2::80414], [LOGGER::Q330::742] + 2006-08-18T18:10:00.000000Z + 2011-05-02T21:13:30.000000Z + + 64.7774 + -141.1581 + 296.6 + 0.0 + 0.0 + -90.0 + TRIGGERED + GEOPHYSICAL + 100.0 + + KINEMETRICS + Accelerometer + KINEMETRICS + EPISENSOR ES-T + 2020 + + + QUANTERRA + QUANTERRA + Q330 + 742 + + + + 428186.0 + 1.0 + + m/s**2 + Acceleration in meters per second squared + + + counts + Digital Count in Digital counts + + + + + + + [SENSOR::EPISENSOR ES-T::2020], [SENSOR::STS-2::80414], [LOGGER::Q330::742] + 2011-05-02T21:13:30.000000Z + 2011-06-26T09:30:00.000000Z + + 64.7774 + -141.1581 + 296.6 + 0.0 + 0.0 + 0.0 + CONTINUOUS + GEOPHYSICAL + 40.0 + + STRECKEISEN + Velocity Sensor + STRECKEISEN + STS-2 + 80414 + + + QUANTERRA + QUANTERRA + Q330 + 742 + + + + 615725000.0 + 0.02 + + m/s + Velocity in meters per second + + + counts + Digital Count in Digital counts + + + + + + + [SENSOR::EPISENSOR ES-T::2020], [SENSOR::STS-2::80414], [LOGGER::Q330::3792] + 2011-06-26T09:30:00.000000Z + + 64.7774 + -141.1581 + 296.6 + 0.0 + 0.0 + 0.0 + CONTINUOUS + GEOPHYSICAL + 40.0 + + STRECKEISEN + Velocity Sensor + STRECKEISEN + STS-2 + 80414 + + + QUANTERRA + QUANTERRA + Q330 + 3792 + + + + 615725000.0 + 0.02 + + m/s + Velocity in meters per second + + + counts + Digital Count in Digital counts + + + + + + + [SENSOR::EPISENSOR ES-T::2020], [SENSOR::STS-2::80414], [LOGGER::Q330::742] + 2011-05-02T21:13:30.000000Z + 2011-06-26T09:30:00.000000Z + + 64.7774 + -141.1581 + 296.6 + 0.0 + 90.0 + 0.0 + CONTINUOUS + GEOPHYSICAL + 40.0 + + STRECKEISEN + Velocity Sensor + STRECKEISEN + STS-2 + 80414 + + + QUANTERRA + QUANTERRA + Q330 + 742 + + + + 615725000.0 + 0.02 + + m/s + Velocity in meters per second + + + counts + Digital Count in Digital counts + + + + + + + [SENSOR::EPISENSOR ES-T::2020], [SENSOR::STS-2::80414], [LOGGER::Q330::3792] + 2011-06-26T09:30:00.000000Z + + 64.7774 + -141.1581 + 296.6 + 0.0 + 90.0 + 0.0 + CONTINUOUS + GEOPHYSICAL + 40.0 + + STRECKEISEN + Velocity Sensor + STRECKEISEN + STS-2 + 80414 + + + QUANTERRA + QUANTERRA + Q330 + 3792 + + + + 615725000.0 + 0.02 + + m/s + Velocity in meters per second + + + counts + Digital Count in Digital counts + + + + + + + [SENSOR::EPISENSOR ES-T::2020], [SENSOR::STS-2::80414], [LOGGER::Q330::742] + 2011-05-02T21:13:30.000000Z + 2011-06-26T09:30:00.000000Z + + 64.7774 + -141.1581 + 296.6 + 0.0 + 0.0 + -90.0 + CONTINUOUS + GEOPHYSICAL + 40.0 + + STRECKEISEN + Velocity Sensor + STRECKEISEN + STS-2 + 80414 + + + QUANTERRA + QUANTERRA + Q330 + 742 + + + + 615725000.0 + 0.02 + + m/s + Velocity in meters per second + + + counts + Digital Count in Digital counts + + + + + + + [SENSOR::EPISENSOR ES-T::2020], [SENSOR::STS-2::80414], [LOGGER::Q330::3792] + 2011-06-26T09:30:00.000000Z + + 64.7774 + -141.1581 + 296.6 + 0.0 + 0.0 + -90.0 + CONTINUOUS + GEOPHYSICAL + 40.0 + + STRECKEISEN + Velocity Sensor + STRECKEISEN + STS-2 + 80414 + + + QUANTERRA + QUANTERRA + Q330 + 3792 + + + + 615725000.0 + 0.02 + + m/s + Velocity in meters per second + + + counts + Digital Count in Digital counts + + + + + + + diff --git a/pysep/tests/test_declust.py b/pysep/tests/test_declust.py new file mode 100644 index 0000000..9079dd7 --- /dev/null +++ b/pysep/tests/test_declust.py @@ -0,0 +1,107 @@ +""" +Test the declustering algorithm +""" +import os +import pytest +from obspy import read_events, read_inventory +from pysep import Declust + +from pysep import logger +logger.setLevel("DEBUG") + + +@pytest.fixture +def test_declust(): + """ + Setup a decluster class + """ + cat = read_events("./test_data/test_nalaska_events.xml") + inv = read_inventory("./test_data/test_nalaska_inv.xml") + + return Declust(cat=cat, inv=inv) + +def test_data_availability(test_declust): + """ + Make sure data availability calculation returns the same each time + """ + # Just check one of the events in the catalog + resource_id = "smi:service.iris.edu/fdsnws/event/1/query?eventid=4599111" + assert(len(test_declust.data_avail[resource_id]) == 15) + + +def test_threshold_catalog(test_declust): + """ + Ensure that thresholding removes the proper number of events + """ + test_declust.threshold_catalog(zedges=[0, 8, 36, 100], min_data=5, + min_mags=[3, 3, 5]) + assert(len(test_declust.cat) == 215) + + +def test_decluster_events_cartesian(test_declust): + """ + Test event declustering algorithm + """ + for select_by in ["magnitude", "magnitude_r", "depth", "depth_r", + "data", "data_r"]: + cat = test_declust.decluster_events(choice="cartesian", nx=2, ny=2, + min_mags=[4.5], nkeep=4, + select_by=select_by) + assert(len(cat) == 16) + + +def test_decluster_events_polar(test_declust): + """ + Test event declustering algorithm + """ + for select_by in ["magnitude", "magnitude_r", "depth", "depth_r", + "data", "data_r"]: + cat = test_declust.decluster_events(choice="polar", nx=2, ny=2, + min_mags=[4.5], nkeep=4, + select_by=select_by) + assert(len(cat) == 24) + + +def test_decluster_plot_cartesian(tmpdir, test_declust): + """ + Test event declustering algorithm + """ + cat = test_declust.decluster_events( + choice="cartesian", nx=25, ny=25, zedges=[0, 10, 35], + min_mags=[4., 5.], nkeep=[4, 4], select_by="magnitude", plot=True, + plot_dir=tmpdir + ) + assert(os.path.exists(os.path.join(tmpdir, "pre_decluster_crtsn.png"))) + assert(os.path.exists(os.path.join(tmpdir, "declustered_crtsn.png"))) + assert(os.path.exists(os.path.join(tmpdir, "removed_crtsn.png"))) + + +def test_decluster_plot_polar(tmpdir, test_declust): + """ + Test event declustering algorithm + """ + cat = test_declust.decluster_events( + choice="polar", zedges=[0, 35], min_mags=None, nkeep=5, + select_by="magnitude_r", plot=True, plot_dir=tmpdir + ) + assert(os.path.exists(os.path.join(tmpdir, "pre_decluster_plr.png"))) + assert(os.path.exists(os.path.join(tmpdir, "decluster_plr.png"))) + assert(os.path.exists(os.path.join(tmpdir, "removed_plr.png"))) + + +def test_plot(tmpdir, test_declust): + """ + Test the plot function on its own + """ + test_declust.plot(inv=True, show=False, color_by="data", cmap="inferno", + save=os.path.join(tmpdir, "test_plot.png")) + assert(os.path.exists(os.path.join(tmpdir, "test_plot.png"))) + + +def test_srcrcv_weight(tmpdir, test_declust): + """test srcrv weight calculation""" + test_declust.calculate_srcrcv_weights( + write=os.path.join(tmpdir, "weights.txt"), plot=True, show=False, + save=os.path.join(tmpdir, "srcrcvwght.png") + ) + diff --git a/pysep/tests/test_process.py b/pysep/tests/test_process.py index d6e9315..1d3d861 100644 --- a/pysep/tests/test_process.py +++ b/pysep/tests/test_process.py @@ -133,7 +133,7 @@ def test_rotate_streams_fail(test_st, test_inv, test_event): Ensure that stream rotation does not go ahead if no back azimuth values are specified """ - sep = Pysep(log_level="CRITICAL", rotate=["ZNE", "RTZ"]) + sep = Pysep(log_level="DEBUG", rotate=["ZNE", "RTZ"]) for tr in test_st: del tr.stats.back_azimuth assert("back_azimuth" not in test_st[0].stats) @@ -143,10 +143,10 @@ def test_rotate_streams_fail(test_st, test_inv, test_event): sep.event = test_event sep.st = sep.preprocess() # make sure that streams are formatted correctly - # No back aizmuth attribute found - with pytest.raises(TypeError): - sep.rotate_streams() - + # No back aizmuth attribute found so streams will NOT be rotated + st = sep.rotate_streams() + components = set([tr.stats.component for tr in st]) + assert(not {"R", "T"}.issubset(components)) def test_rotate_streams(test_st, test_inv, test_event): """ @@ -173,32 +173,57 @@ def test_rotate_streams_enz(test_st, test_inv): """ Test that streams rotate from ENZ even if components are already ENZ """ - sep = Pysep(log_level="DEBUG", rotate=["ZNE"]) + sep = Pysep(log_level="DEBUG", rotate=["ENZ"]) sep.st = test_st.select(station="ALPI").copy() st_check = test_st.select(station="ALPI").copy() sep.inv = test_inv.select(station="ALPI") sep.event = test_event + # This rotates ->ZNE from ZNE. We expect the data to be the same (with some + # error due to floating point rounding) st_rotated = sep.rotate_streams() for component in ["E", "N", "Z"]: st_rot = st_rotated.select(component=component) - st_check = st_check.select(component=component) - for tr_rot, tr_check in zip(st_rot, st_check): - assert(np.all(tr_rot.data == tr_check.data)) + st_chk = st_check.select(component=component) + for tr_rot, tr_check in zip(st_rot, st_chk): + assert(pytest.approx(np.max(tr_rot.data - tr_check.data), 3) == 0) - # Randomly assign azimuths and dips + # Now we randomly assign azimuths and dips to stations and rotate. We + # expect data streams to have been rotated and therefore to be different + n = 0 for net in sep.inv: + s = 0 for sta in net: + c = 0 for cha in sta: - sta.azimuth = random.randint(1, 89) - sta.dip = random.randint(1, 89) + sep.inv[n][s][c].azimuth = random.randint(1, 89) + sep.inv[n][s][c].dip = random.randint(1, 89) + c += 1 + s += 1 + n += 1 st_rotated = sep.rotate_streams() for component in ["E", "N", "Z"]: st_rot = st_rotated.select(component=component) - st_check = st_check.select(component=component) - for tr_rot, tr_check in zip(st_rot, st_check): - assert(not np.all(tr_rot.data == tr_check.data)) + st_chk = st_check.select(component=component) + + for tr_rot, tr_check in zip(st_rot, st_chk): + assert(not pytest.approx( + np.max(tr_rot.data - tr_check.data), 3) != 0 + ) + + +def test_rotate_streams_12z(): + """ + Test that 12Z components can be rotated to ZNE + """ + sep = Pysep(rotate=["ENZ"]) + sep.st = read("./test_data/test_12Z_data/stream.ms") + sep.inv = read_inventory("./test_data/test_12Z_data/inv.xml") + + st_rotate = sep.rotate_streams() + components = "".join(sorted([_.stats.component for _ in st_rotate])) + assert(components == "ENZ") diff --git a/pysep/tests/test_utils.py b/pysep/tests/test_utils.py index 54fc1df..9999740 100644 --- a/pysep/tests/test_utils.py +++ b/pysep/tests/test_utils.py @@ -6,6 +6,7 @@ """ import os import pytest +import numpy as np from glob import glob from obspy import read, read_events, read_inventory, Stream from obspy.io.sac.sactrace import SACTrace @@ -14,6 +15,7 @@ from pysep.utils.curtail import (remove_for_clipped_amplitudes, rename_channels, remove_stations_for_missing_channels, remove_stations_for_insufficient_length, + remove_traces_for_bad_data_types, subset_streams) from pysep.utils.fmt import format_event_tag, format_event_tag_legacy from pysep.utils.process import estimate_prefilter_corners @@ -128,6 +130,18 @@ def test_remove_stations_for_missing_channels(test_st): assert(len(test_st) == 11) +def test_traces_for_bad_data_types(test_st): + """ + Make sure data types that aren't float or integer arent' allowed through + Sometimes LOG streams are stored as |S1 dtype which is string of len 1 + """ + st_out = test_st.copy() + st_out[0].data = np.array(len(test_st[0].data) *["a"], dtype="|S1") + st_out = remove_traces_for_bad_data_types(st_out) + # Removed 1 trace for bad data type + assert(len(test_st) - len(st_out) == 1) + + def test_plot_map(test_event, test_inv): """ Make a simple source-receiver map diff --git a/pysep/utils/cap_sac.py b/pysep/utils/cap_sac.py index fa291c9..611c0bc 100644 --- a/pysep/utils/cap_sac.py +++ b/pysep/utils/cap_sac.py @@ -188,8 +188,6 @@ def _append_sac_headers_trace(tr, event, inv): "e": tr.stats.npts * tr.stats.delta, # end time "evla": event.preferred_origin().latitude, "evlo": event.preferred_origin().longitude, - "evdp": event.preferred_origin().depth / 1E3, # depth in km - "mag": event.preferred_magnitude().mag, "stla": sta.latitude, "stlo": sta.longitude, "stel": sta.elevation / 1E3, # elevation in km @@ -215,6 +213,19 @@ def _append_sac_headers_trace(tr, event, inv): except IndexError: pass + # Allow for no magnitude and no depth information + try: + evdp = event.preferred_origin().depth / 1E3 # units: km + sac_header["evdp"] = evdp + except Exception: # NOQA + pass + + try: + mag = event.preferred_magnitude().mag + sac_header["mag"] = mag + except Exception: # NOQA + pass + # Append SAC header and include back azimuth for rotation tr.stats.sac = sac_header tr.stats.back_azimuth = baz @@ -222,7 +233,7 @@ def _append_sac_headers_trace(tr, event, inv): return tr -def format_sac_header_w_taup_traveltimes(st, model="ak135"): +def format_sac_header_w_taup_traveltimes(st, model="ak135", phase_list=None): """ Add TauP travel times to the SAC headers using information in the SAC header Also get some information from TauP regarding incident angle, takeoff angle @@ -243,15 +254,25 @@ def format_sac_header_w_taup_traveltimes(st, model="ak135"): :type model: str :param model: name of the TauP model to use for arrival times etc. defaults to 'ak135' + :type phase_list: list of str + :param phase_list: phase names to get ray information from TauP with. + Defaults to direct arrivals 'P' and 'S'. Must match Phases expected + by TauP (see ObsPy TauP documentation for acceptable phases). """ st_out = st.copy() # Call TauP with a specific model to retrieve travel times etc. - phases = ["p", "P", "s", "S"] + if not phase_list: + phase_list = ["p", "P", "s", "S"] + phase_dict = get_taup_arrivals_with_sac_headers(st=st, model=model, - phase_list=phases) + phase_list=phase_list) # Arrivals may return multiple entires for each phase, pick earliest for tr in st_out[:]: + # Missing SAC header values may cause certain or all stations to not + # be present in the `phase_dict` + if tr.get_id() not in phase_dict: + continue arrivals = phase_dict[tr.get_id()] # If the TauP arrival calculation fails, `arrivals` will be empty if not arrivals: @@ -338,6 +359,6 @@ def origin_time_from_sac_header(sac_header): min_ = sac_header["nzmin"] sec_ = sac_header["nzsec"] msec = sac_header["nzmsec"] - time_string = f"{year}-{jday:0>3}T{hour}:{min_}:{sec_}.{msec}" + time_string = f"{year}-{jday:0>3}T{hour:0>2}:{min_:0>2}:{sec_:0>2}.{msec}" return UTCDateTime(time_string) diff --git a/pysep/utils/curtail.py b/pysep/utils/curtail.py index bb88316..6540230 100644 --- a/pysep/utils/curtail.py +++ b/pysep/utils/curtail.py @@ -77,24 +77,29 @@ def curtail_by_station_distance_azimuth(event, inv, mindistance=0., return inv -def quality_check_waveforms_before_processing(st): +def quality_check_waveforms_before_processing(st, remove_clipped=True): """ Quality assurance to deal with bad data before running the preprocessing steps. Replaces: `do_waveform_QA` :type st: obspy.core.stream.Stream :param st: Stream object to pass through QA procedures + :type remove_clipped: bool + :param remove_clipped: boolean flag to turn on/off amplitude clipping check """ st_out = st.copy() st_out = rename_channels(st_out) st_out = remove_stations_for_missing_channels(st_out) # LL network ONLY! - st_out = remove_for_clipped_amplitudes(st_out) + st_out = remove_traces_for_bad_data_types(st_out) + if remove_clipped: + st_out = remove_for_clipped_amplitudes(st_out) return st_out -def quality_check_waveforms_after_processing(st): +def quality_check_waveforms_after_processing(st, + remove_insufficient_length=True): """ Quality assurance to deal with bad data after preprocessing, because preprocesing step will merge, filter and rotate data. @@ -102,14 +107,42 @@ def quality_check_waveforms_after_processing(st): :type st: obspy.core.stream.Stream :param st: Stream object to pass through QA procedures + :type remove_insufficient_length: bool + :param remove_insufficient_length: boolean flag to turn on/off insufficient + length checker """ st_out = st.copy() - st_out = remove_stations_for_insufficient_length(st_out) + if remove_insufficient_length: + st_out = remove_stations_for_insufficient_length(st_out) return st_out +def remove_traces_for_bad_data_types(st): + """ + Removed traces from a Stream that have unexpected data types. This might + occur if e.g., you wildcard the channel and end up grabbing LOG data, which + uses letters. + + :type st: obspy.core.stream.Stream + :param st: Stream to check clipping for + :rtype st: obspy.core.stream.Stream + :return st: curtailed stream with clipped traces removed + """ + # NumPy data types smart enough that int32 or int64 will match to 'int' + acceptable_data_types = [np.integer, np.floating] + st_out = st.copy() + for tr in st_out[:]: + for dtype in acceptable_data_types: + if np.issubdtype(tr.data.dtype, dtype): + break + else: + logger.warning(f"{tr.get_id()} bad data type: {tr.data.dtype}") + st_out.remove(tr) + return st_out + + def remove_for_clipped_amplitudes(st): """ Removed stations with clipped amplitudes @@ -125,7 +158,7 @@ def remove_for_clipped_amplitudes(st): clip_factor = 0.8 * ((2 ** (24 - 1)) ** 2) ** 0.5 # For a 24-bit signal for tr in st_out[:]: # Figure out the if any amplitudes are clipped - if len(tr.data[np.abs(tr.data**2)**0.5 > clip_factor]): + if (tr.data[np.abs(tr.data**2)**0.5 > clip_factor]).any(): logger.info(f"removing {tr.get_id()} for clipped amplitudes") st_out.remove(tr) return st_out diff --git a/pysep/utils/fetch.py b/pysep/utils/fetch.py index d7329be..bb3931b 100644 --- a/pysep/utils/fetch.py +++ b/pysep/utils/fetch.py @@ -44,8 +44,12 @@ def get_taup_arrivals_with_sac_headers(st, phase_list=None, model="ak135",): logger.debug(f"fetching arrivals, phases {phase_list} and model '{model}'") for tr in st: - depth_km = tr.stats.sac["evdp"] # units: km - dist_deg = tr.stats.sac["gcarc"] + sac_header = tr.stats.sac + if "evdp" not in sac_header or "gcarc" not in sac_header: + logger.debug(f"skip {tr.get_id()} phase arr., no 'evdp' or 'gcarc") + continue + depth_km = sac_header["evdp"] # units: km + dist_deg = sac_header["gcarc"] while True: try: arrivals = taup_func(source_depth_in_km=depth_km, diff --git a/pysep/utils/fmt.py b/pysep/utils/fmt.py index 62d7380..f8b0963 100644 --- a/pysep/utils/fmt.py +++ b/pysep/utils/fmt.py @@ -1,6 +1,7 @@ """ Pysep-specific formatting functions """ +from obspy import Catalog, UTCDateTime from obspy.clients.iris import Client @@ -86,6 +87,43 @@ def get_codes(st=None, choice=None, suffix=None, up_to=True): return sorted(list(set(codes))) +def get_data_availability(cat, inv): + """ + Determine data availability based on whether stations are 'on' for a + given event origin time. Does not check waveforms, only station + metadata, so not foolproof. + + :type cat: obspy.core.catalog.Catalog + :param cat: Catalog of events to consider. Events must include origin + information `latitude` and `longitude` + :type inv: obspy.core.inventory.Inventory + :param inv: Inventory of stations to consider + :rtype: dict + :return: keys are event resource ids and values are IDs for stations + that were on during the event origin time + """ + # Collect install and removal (if applicaple) for all stations + station_times = {} + for net in inv: + for sta in net: + if sta.end_date is None: + sta.end_date = UTCDateTime() # set to right now + station_times[f"{net.code}.{sta.code}"] = (sta.start_date, + sta.end_date) + + # Check event origin time against station uptime + data_avail = {} + for event in cat: + data_avail[event.resource_id.id] = [] + for sta, time in station_times.items(): + start_date, end_date = time + # Check that event origin time falls between start and end date + if start_date <= event.preferred_origin().time <= end_date: + data_avail[event.resource_id.id].append(sta) + + return data_avail + + def format_event_tag(event): """ Generate a unique event tag based on event origin time and location using @@ -122,3 +160,20 @@ def format_event_tag_legacy(event): :return: event_name specified by event time """ return event.preferred_origin().time.strftime("%Y%m%d%H%M%S%f")[:-3] + + +def index_cat(cat, idxs): + """ + ObsPy Catalog does not allow indexing by a list of values + (e.g., cat[0, 1, 3]) so this convenience function takes care of that by + forming a new catalog of events chosen by indices + + :type idxs: list of int + :param idxs: list of indices to index catalog by + :type cat: obspy.core.catalog.Catalog + :param cat: Catalog to index. If not given defaults to internal Cat + """ + cat_out = Catalog() + for idx in idxs: + cat_out.append(cat[idx]) + return cat_out \ No newline at end of file diff --git a/pysep/utils/io.py b/pysep/utils/io.py index 00ff4c5..7360a5e 100644 --- a/pysep/utils/io.py +++ b/pysep/utils/io.py @@ -559,7 +559,8 @@ def write_sem(st, unit, path="./", time_offset=0): np.savetxt(fid, data, ["%13.7f", "%17.7f"]) -def write_pysep_stations_file(inv, event, fid="./stations_list.txt"): +def write_pysep_stations_file(inv, event, fid="./stations_list.txt", + order_stations_list_by=None): """ Write a list of station codes, distances, etc. useful for understanding characterization of all collected stations @@ -572,28 +573,51 @@ def write_pysep_stations_file(inv, event, fid="./stations_list.txt"): skip over StationXML/inventory searching :type fid: str :param fid: name of the file to write to. defaults to ./stations_list.txt + :type order_by: str + :param order_by: how to order the stations written to file. Available + are: network, station, latitude, longitude, elevation, burial. + If not given, order is determined by the internal sorting of the + input Inventory """ + # Key indices correspond to stations list + keys = ["station", "network", "latitude", "longitude", "distance", + "azimuth"] + if order_stations_list_by and order_stations_list_by not in keys: + logger.warning(f"`order_stations_by` must be in {keys}, " + f"setting default") + order_stations_by = None + event_latitude = event.preferred_origin().latitude event_longitude = event.preferred_origin().longitude + + stations = [] + for net in inv: + for sta in net: + dist_m, az, baz = gps2dist_azimuth(lat1=event_latitude, + lon1=event_longitude, + lat2=sta.latitude, + lon2=sta.longitude + ) + dist_km = dist_m * 1E-3 + stations.append([sta.code, net.code, sta.latitude, sta.longitude, + dist_km, az]) + + # Set the order of the station file based on the order of keys + if order_stations_list_by: + idx = keys.index(order_stations_list_by) + stations.sort(key=lambda x: x[idx]) with open(fid, "w") as f: - for net in inv: - for sta in net: - dist_m, az, baz = gps2dist_azimuth(lat1=event_latitude, - lon1=event_longitude, - lat2=sta.latitude, - lon2=sta.longitude - ) - dist_km = dist_m * 1E-3 - f.write(f"{sta.code:<6} {net.code:<2} " - f"{sta.latitude:9.4f} {sta.longitude:9.4f} " - f"{dist_km:8.3f} {az:6.2f}\n") - - -def write_specfem_stations_file(inv, fid="./STATIONS", elevation=False, - burial=0.): + for s in stations: + # Order follows that listed in 'keys' + f.write(f"{s[0]:<6} {s[1]:<2} {s[2]:9.4f} {s[3]:9.4f} {s[4]:8.3f} " + f"{s[5]:6.2f}\n") + + +def write_stations_file(inv, fid="./STATIONS", order_by=None, + use_elevation=False, burials=None): """ - Write a SPECFEM3D STATIONS file given an ObsPy inventory object + Write a SPECFEM STATIONS file given an ObsPy inventory object .. note:: If topography is implemented in your mesh, elevation values should be @@ -607,21 +631,72 @@ def write_specfem_stations_file(inv, fid="./STATIONS", elevation=False, :param inv: Inventory object with station locations to write :type fid: str :param fid: path and file id to save the STATIONS file to. - :type elevation: bool - :param elevation: if True, sets the actual elevation value from the + :type order_by: str + :param order_by: how to order the stations written to file. Available + are: network, station, latitude, longitude, elevation, burial. + If not given, order is determined by the internal sorting of the + input Inventory + :type use_elevation: bool + :param use_elevation: if True, sets the actual elevation value from the inventory. if False, sets elevation to 0. - :type burial: float - :param burial: the constant value to set burial values to. defaults to 0. + :type burials: list of float + :param burials: If the User has burial information they want to be used as + the last column. Length of `burials` must match the number of stations + in the inventory when traversing by network and station """ + # Simply generate lists by traversing through the inventory + i = 0 + stations = [] + keys = ["network", "station", "latitude", + "longitude", "elevation", "burial"] + if order_by: + assert(order_by in keys), f"`order_by` must be in {keys}" + with open(fid, "w") as f: for net in inv: for sta in net: - lat = sta.latitude - lon = sta.longitude - if elevation: - elv = sta.elevation + if use_elevation: + elevation = sta.elevation else: - elv = 0. + elevation = 0. + if burials: + burial = burials[i] + else: + burial = 0. + stations.append([sta.code, net.code, sta.latitude, + sta.longitude, elevation, burial]) + i += 1 + + # Set the order of the station file based on the order of keys + if order_by: + idx = keys.index(order_by) + stations.sort(key=lambda x: x[idx]) + + with open(fid, "w") as f: + for s in stations: + f.write(f"{s[0]:>6}{s[1]:>6}{s[2]:12.4f}{s[3]:12.4f}" + f"{s[4]:7.1f}{s[5]:7.1f}\n" + ) + +def write_cat_to_event_list(cat, fid_out="event_input.txt"): + """ + Writes out an event Catalog (ObsPy object) information to an ASCII file that + PySEP can use for collecting data. The format of the output file is + + ORIGIN_TIME LONGITUDE LATITUDE DEPTH[KM] MAGNITUDE + + :type cat: obspy.core.catalog.Catalog + :param cat: Catalog of events to write out + """ + with open(fid_out, "w") as f: + for event in cat: + origintime = str(event.preferred_origin().time) + longitude = event.preferred_origin().longitude + latitude = event.preferred_origin().latitude + depth = event.preferred_origin().depth * 1E-3 + mag = event.preferred_magnitude().mag + + f.write(f"{origintime:<31}{longitude:8.2f}{latitude:8.2f}" + f"{depth:8.2f}{mag:6.1f}\n") + - f.write(f"{sta.code:>6}{net.code:>6}{lat:12.4f}{lon:12.4f}" - f"{elv:7.1f}{burial:7.1f}\n") \ No newline at end of file diff --git a/pysep/utils/mt.py b/pysep/utils/mt.py index fa20365..cf8d8ec 100644 --- a/pysep/utils/mt.py +++ b/pysep/utils/mt.py @@ -159,7 +159,7 @@ def get_gcmt_moment_tensor(event=None, origintime=None, magnitude=None, "https://www.ldeo.columbia.edu/~gcmt/projects/CMT/" f"catalog/NEW_MONTHLY/{year_long}/{fid}" ) - except HTTPError: + except requests.HTTPError: cat = read_events( "http://www.ldeo.columbia.edu/~gcmt/projects/CMT/" "catalog/NEW_QUICK/qcmt.ndk" diff --git a/pysep/utils/plot.py b/pysep/utils/plot.py index 725ca5e..d622fa5 100644 --- a/pysep/utils/plot.py +++ b/pysep/utils/plot.py @@ -206,9 +206,6 @@ def set_plot_aesthetic(ax, **kwargs): Give a nice look to the output figure by creating thick borders on the axis, adjusting fontsize etc. All plot aesthetics should be placed here so it's easiest to find. - - .. note:: - This was copy-pasted from Pyatoa.visuals.insp_plot.default_axes() """ ytick_fontsize = kwargs.get("ytick_fontsize", 8) xtick_fontsize = kwargs.get("xtick_fontsize", 12) @@ -221,6 +218,12 @@ def set_plot_aesthetic(ax, **kwargs): title_fontsize = kwargs.get("title_fontsize", 10) xtick_minor = kwargs.get("xtick_minor", 25) xtick_major = kwargs.get("xtick_major", 100) + ytick_minor = kwargs.get("ytick_minor", None) + ytick_major = kwargs.get("ytick_major", None) + xgrid_major = kwargs.get("xgrid_major", True) + xgrid_minor = kwargs.get("xgrid_minor", True) + ygrid_major = kwargs.get("ygrid_major", True) + ygrid_minor = kwargs.get("ygrid_minor", True) spine_zorder = kwargs.get("spine_zorder", 8) ax.title.set_fontsize(title_fontsize) @@ -242,9 +245,19 @@ def set_plot_aesthetic(ax, **kwargs): # Set xtick label major and minor which is assumed to be a time series ax.xaxis.set_major_locator(MultipleLocator(float(xtick_major))) ax.xaxis.set_minor_locator(MultipleLocator(float(xtick_minor))) + if ytick_minor: + ax.yaxis.set_major_locator(MultipleLocator(float(ytick_major))) + if ytick_major: + ax.yaxis.set_minor_locator(MultipleLocator(float(ytick_minor))) plt.sca(ax) - plt.grid(visible=True, which="major", axis="x", alpha=0.5, linewidth=1) - plt.grid(visible=True, which="minor", axis="x", alpha=0.2, linewidth=.5) + if xgrid_major: + plt.grid(visible=True, which="major", axis="x", alpha=0.5, linewidth=1) + if xgrid_minor: + plt.grid(visible=True, which="minor", axis="x", alpha=0.2, linewidth=.5) + if ygrid_major: + plt.grid(visible=True, which="major", axis="y", alpha=0.5, linewidth=1) + if ygrid_minor: + plt.grid(visible=True, which="minor", axis="y", alpha=0.2, linewidth=.5) return ax diff --git a/setup.py b/setup.py new file mode 100644 index 0000000..6068493 --- /dev/null +++ b/setup.py @@ -0,0 +1,3 @@ +from setuptools import setup + +setup()