From 939758f339b1959924985c1135bcb0eeb22dd2ac Mon Sep 17 00:00:00 2001 From: Bryant Chow Date: Fri, 17 Feb 2023 15:51:18 -0900 Subject: [PATCH] PySEP v0.3.0 (#78) * Fix various bugs and adds features to code (#60) * renamed specfem station writing function, and added an ordering component * bumping version in setup and changing url and author * small mt typo change * added an example config that gathers a small amount of data for testing/dev purposes * added a new kwarg 'order_stations_list_by' which sets the order of the output stations list, related to #36 * bugfix typo parameter call * bugfix rotating was not actually rotating streams in place for arbitrary components ->ENZ * bugfix fixed rotation testing, which was not actually evaluating as expected. some confusion about editing streams and inventories in place which was not actually happening. Fixed and now rotate test works as expected * added 12Z test data for rotating 12Z -> ENZ which works now, added test to cover this case * moved 2012 central alaska IU gather script (which gathers 12Z component) into examples * bugfix pysep was not setting log level properly from the config file. now in the load() function, config log level is allowed to override logger level * changed config examples dir name to test, to be used as a test bed for checking specific data gathering features such as data gap removal * bugfix #57, reading event origin time from sac header was shifting times unexpectedly * added utility function to convert obspy catalog to event input list * Bugfix missing rotation metadata throwing TypeError (#63) * bugfix clipped amplitude check was not properly checking the data array * added error catch and release during rotate code to avoid processing breakdown. also rotate now goes by channel rather than the entire stream at once * rearranged rotation algorithm to be a bit cleaner, previously too many different streams floating around and being fed to one another. * pysep rotation now has additional checks for station metadata and error catching to get around any rotation bugs that used to cause the rotation to fail added new tests to cover rotation and fixed a rotation test that was failing due to change added a config for testing the rotation bug, providing station info * updating bug config file * feature mass download (#64) * fixed exclude string making and added a bool check for deleting tmpdir in mass download function * removed accidental debug statement * Remove llnl_db_client hard dependency (#65) * moved llnl_db_client as a hard dep of pysep and moved it into an optional dependency hid llnl_db_client import statement behind a try-except block and threw a check in the init of pysep only requiring this dep if the client choice is LLNL * Added setup.py legacy file * removed llnl dep from conda env yml file * tested install with and without llnl dep and tested check statement for missing llnl import * Feature: event declustering and source receiver weighting (#66) * started adding declustering rewrite with test and test data * finished cartesian gridding decluster script, added radial gridding decluster script, added tests to cover both and plotting * decluster catalog added feature to threshold events by min magnitude and data availability separate from declustering added plot feture to connect source receiver pairs based on data availability added feature to allow sorting by data availability * adjusting default figure names for declust plotting scripts * cleaned up plotting functions into functions to avoid repeat plotting calls, added removed events to plotting routines * small typo updte declust * moved some declustering functions into util * declust started srcrcv weighting function * individual source or receiver list weighting working with the smart scan feature next up is to implement the entire weighting scheme with normalization and based on data availability * declust slow progression * finished srcrcv weighting scheme * finished declustering and weighting algos with additional plotting and text file writing for weights * added basic test for srcrcv weight calc * clean up docstrings of pysep/recsec, bugfix pysep restrictions (#68) * reformatted PySEP init docstring, added missing parameters and categorized parameters to make things easier to find * removed hard requirement that user provides event depth and magnitude if event selection is default * added boolean flag to toggle insufficient length checker bugfix: added remove_clipped boolean toggle on the actual processing step, which was not there before * bugfix phase list passed from pysep into util function for phase getting * last minute touch ups on docstring * recsec removed unneeded myround function from top of script * categorized recsec init docstring for easier readability * bugfix: rotate parameter check function was setting rotate parameter as an empty list, but it was expected as NoneType within the main processing function. removed this type conversion * bugfix: log message failing when magnitude or depth set to NoneType * bugfix allow NoneType event magnitude and depth, ass ign dummy values to cap header because these are required by record section * Update docs (#69) * moved docstring of pysep into class description for autoapi * instantiated sphinx for doc creation and autoapi building, reorganized pysep and recsec docstrings to be well formatted for autoapi * migrated wiki docs into docs directory * fixed docstrings and corrected links for API references in docs * fixed up typos and cleaned up docs * Delete jekyll-gh-pages.yml * Bugfix: unable to set event_depth_km or event_magnitude as NoneType (#72) * allow taup arrival time get to be skipped if event depth not provided * sac header functions that required 'evdp' are now skipped over if 'evdp' is not present in the sac header * Update pysep.py bugfix: removing debug statement left in pysep * Feature recsec tmarks (#73) * replace plotw_rs with record section run command in pysep plotting, sets default sorting to 'distance' and not 'distance_r' for pysep-generated record section * working on ordering of multiple pages * added feature tmark to add static lines at given time values, does not address time shifts or move out * Bugfix: plotw rs sort (#76) * reformatting plotw_rs page separation logic * sort order of multi-page record sections is now reversed to be more natural * Update CHANGELOG.md * version bump v0.3.0 --- CHANGELOG.md | 19 + docs/Makefile | 20 + docs/conf.py | 60 + docs/cookbook.md | 250 + docs/declust.md | 86 + docs/environment.yml | 14 + docs/index.rst | 93 + docs/{ => legacy}/images/record_section.png | Bin docs/{ => legacy}/images/station_map.png | Bin docs/{ => legacy}/network_client_issues | 0 docs/make.bat | 35 + docs/pysep.md | 220 + docs/recsec.md | 180 + docs/usage.md | 63 + environment.yml | 1 - pyproject.toml | 4 +- pysep/__init__.py | 3 +- pysep/configs/README.md | 3 + pysep/configs/test/check_rotate_12Z.yaml | 46 + .../configs/test/test_config_rotate_bug.yaml | 48 + pysep/configs/test/test_mass_download.yaml | 45 + pysep/configs/test/test_remove_data_gaps.yaml | 47 + pysep/declust.py | 1044 + pysep/pysep.py | 713 +- pysep/recsec.py | 303 +- pysep/tests/test_data/test_12Z_data/inv.xml | 1887 ++ pysep/tests/test_data/test_12Z_data/stream.ms | Bin 0 -> 688128 bytes pysep/tests/test_data/test_nalaska_events.xml | 9656 ++++++ pysep/tests/test_data/test_nalaska_inv.xml | 24701 ++++++++++++++++ pysep/tests/test_declust.py | 107 + pysep/tests/test_process.py | 55 +- pysep/tests/test_utils.py | 14 + pysep/utils/cap_sac.py | 33 +- pysep/utils/curtail.py | 43 +- pysep/utils/fetch.py | 8 +- pysep/utils/fmt.py | 55 + pysep/utils/io.py | 131 +- pysep/utils/mt.py | 2 +- pysep/utils/plot.py | 23 +- setup.py | 3 + 40 files changed, 39666 insertions(+), 349 deletions(-) create mode 100644 CHANGELOG.md create mode 100644 docs/Makefile create mode 100644 docs/conf.py create mode 100644 docs/cookbook.md create mode 100644 docs/declust.md create mode 100644 docs/environment.yml create mode 100644 docs/index.rst rename docs/{ => legacy}/images/record_section.png (100%) rename docs/{ => legacy}/images/station_map.png (100%) rename docs/{ => legacy}/network_client_issues (100%) create mode 100644 docs/make.bat create mode 100644 docs/pysep.md create mode 100644 docs/recsec.md create mode 100644 docs/usage.md create mode 100644 pysep/configs/test/check_rotate_12Z.yaml create mode 100644 pysep/configs/test/test_config_rotate_bug.yaml create mode 100644 pysep/configs/test/test_mass_download.yaml create mode 100644 pysep/configs/test/test_remove_data_gaps.yaml create mode 100644 pysep/declust.py create mode 100644 pysep/tests/test_data/test_12Z_data/inv.xml create mode 100644 pysep/tests/test_data/test_12Z_data/stream.ms create mode 100644 pysep/tests/test_data/test_nalaska_events.xml create mode 100644 pysep/tests/test_data/test_nalaska_inv.xml create mode 100644 pysep/tests/test_declust.py create mode 100644 setup.py 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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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()

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