seismic.ASDFdatabase package

Submodules

seismic.ASDFdatabase.ClientUtils module

class seismic.ASDFdatabase.ClientUtils.Client2ASDF(client='IRIS', network='AU')[source]

Bases: object

Object to query IRIS or other client with a bounding box and time interval. Returns ASDF containing station information and data for interval.

queryByBBoxInterval(outputFileName, bbox, timeinterval, chan='*Z', bbpadding=2, event_id=None, verbose=False)[source]

Time interval is a tuple (starttime,endtime)

seismic.ASDFdatabase.FederatedASDFDataSet module

Description:

Wrapper Class for providing fast access to data contained within a set of ASDF files

References:

CreationDate: 12/12/18 Developer: rakib.hassan@ga.gov.au

Revision History:

LastUpdate: 12/12/18 RH LastUpdate: 2020-04-10 Fei Zhang clean up + added example run for the script

class seismic.ASDFdatabase.FederatedASDFDataSet.FederatedASDFDataSet(asdf_source, logger=None, single_item_read_limit_in_mb=1024)[source]

Bases: object

Initializer for FederatedASDFDataSet.

Parameters

  • asdf_source – Path to a text file containing a list of ASDF files. Entries can be commented out with ‘#’

  • logger – logger instance

get_closest_stations(lon, lat, nn=1)[source]
Parameters

  • lon – longitude (degree)

  • lat – latitude (degrees)

  • nn – number of closest stations to fetch

Returns

A tuple containing a list of closest ‘network.station’ names and a list of distances (in ascending order) in kms

get_global_time_range(network, station, location=None, channel=None)[source]
Parameters

  • network – network code

  • station – station code

  • location – location code (optional)

  • channel – channel code (optional)

Returns

tuple containing min and max times as UTCDateTime objects. If no matching records are found min is set to 2100-01-01T00:00:00.000000Z and max is set to 1900-01-01T00:00:00.000000Z

get_stations(starttime, endtime, network=None, station=None, location=None, channel=None)[source]
Parameters

  • starttime – start time string in UTCDateTime format; can also be an instance of obspy.UTCDateTime

  • endtime – end time string in UTCDateTime format; can also be an instance of obspy.UTCDateTime

  • network – network code (optional)

  • station – station code (optional)

  • location – location code (optional)

  • channel – channel code (optional)

Returns

a list containing [net, sta, loc, cha, lon, lat] in each row

get_waveform_count(network, station, location, channel, starttime, endtime)[source]

Count the number of traces within the given parameters of network, station, etc.. and date range. This is a fast method of determing whether any trace data exists in a given time period, if you don’t actually need the waveform data itself.

Parameters

  • network – network code

  • station – station code

  • location – location code

  • channel – channel code

  • starttime – start time string in UTCDateTime format; can also be an instance of obspy.UTCDateTime

  • endtime – end time string in UTCDateTime format; can also be an instance of obspy.UTCDateTime

Returns

The number of streams containing waveform data over the time-range provided

get_waveforms(network, station, location, channel, starttime, endtime, trace_count_threshold=200)[source]
Parameters

  • network – network code

  • station – station code

  • location – location code

  • channel – channel code

  • starttime – start time string in UTCDateTime format; can also be an instance of obspy.UTCDateTime

  • endtime – end time string in UTCDateTime format; can also be an instance of obspy.UTCDateTime

  • trace_count_threshold – returns an empty Stream if the number of traces within the time-range provided exceeds the threshold (default 200). This is particularly useful for filtering out data from bad stations, e.g. those from the AU.Schools network

Returns

an obspy.Stream containing waveform data over the time-rage provided

local_net_sta_list()[source]

This function provides an iterator over the entire data volume contained in all the ASDF files listed in the text file during instantiation. When FederatedASDFDataSet is instantiated in an MPI-parallel environment, meta-data for the entire data volume are equally partitioned over all processors – in such instances, this function provides an iterator over the data allocated to a given processor. This functionality underpins parallel operations, e.g. picking arrivals.

Returns

tuples containing [net, sta, start_time, end_time]; start- and end-times are instances of obspy.UTCDateTime

property unique_coordinates
Returns

dictionary containing [lon, lat] coordinates indexed by ‘net.sta’

seismic.ASDFdatabase.asdf2mseed module

Description:

Small utility for exporting mseed files from an asdf file in parallel.

References:

CreationDate: 06/08/18 Developer: rakib.hassan@ga.gov.au

Revision History:

LastUpdate: 04/12/17 RH LastUpdate: dd/mm/yyyy Who Optional description

seismic.ASDFdatabase.asdf2mseed.dump_traces(ds, sn_list, start_date, end_date, length, output_folder)[source]

Dump mseed traces from an ASDF file in parallel

Parameters

  • ds – ASDF Dataset

  • sn_list – station list to process

  • start_date – start date

  • end_date – end date

  • length – length of each mseed file

  • output_folder – output folder

seismic.ASDFdatabase.asdf2mseed.split_list(lst, npartitions)[source]

seismic.ASDFdatabase.asdf_preprocess module

Description:

Reads waveforms from an ASDF file, optionally applies instrument response correction, resamples and outputs them to another ASDF file. This preprocessing is crucial for large-scale studies involving > 10000 Green’s Functions, e.g. in ambient noise tomography. This approach significantly reduces IO bottlenecks and computational costs associated with having to apply instrument response corrections on data from a given station in alternative workflows.

References:

CreationDate: 18/07/19

Developer: rakib.hassan@ga.gov.au

Revision History:

LastUpdate: 18/07/19 RH LastUpdate: dd/mm/yyyy Who Optional description

seismic.ASDFdatabase.asdf_preprocess.create_station_asdf(input_asdf, output_folder, resample_rate, instrument_response_inventory, instrument_response_output, water_level)[source]
seismic.ASDFdatabase.asdf_preprocess.getStationInventory(master_inventory, inventory_cache, netsta)[source]
seismic.ASDFdatabase.asdf_preprocess.split_list(lst, npartitions)[source]

seismic.ASDFdatabase.create_small_chunks module

seismic.ASDFdatabase.create_small_chunks.create_chunk(out_dir, trace, st_time, end_time, sta)[source]
seismic.ASDFdatabase.create_small_chunks.main()[source]

seismic.ASDFdatabase.plot_data_quality module

Description:

Reads waveform data from a FederatedASDFDataSet and generates data-quality plots into a multi-page PDF file

For each station, the program read-in all the waveform data over the period specified (usually over a year), and then perform statistics analysis over the waveform data for subsequent plotting.

The first page of the PDF shows the stations on a basemap with marker colored according to the number of usable days (“good” data available in the day, not gap, not all zeros) And the color is determined by c=mapper.to_rgba(days): Relatively speaking, black/blue/cold-ish colors indicate higher percentage of good data in the station. And red/yellow/warm-ish colors indicate higher percentage of problematic data.

The following pages of the PDF will be plotting the daily-averaged seismic wave data with gaps and all-zeros days are shaded.

CreationDate: 19/09/19 Developer: rakib.hassan@ga.gov.au

Revision History:

LastUpdate: 19/09/2019 RH LastUpdate: 27/05/2020 FZ Refactoring and docs run examples etc.

Todo:

The script currently have a low pylint score 4.3/10. Need to refactor to comply with Python standard pep-8: add required docstrings. use smaller function to modularize better. Consider to generate an additional page to executive summarise info for user.

seismic.ASDFdatabase.plot_data_quality.plot_results(stations, results, output_basename)[source]
seismic.ASDFdatabase.plot_data_quality.process_data(rank, fds, stations, start_time, end_time)[source]
Parameters

  • rank – processor rank in parallel runs

  • fds – FederatedASDFDataSer instance

  • stations – list containing tuples (net, sta, loc, cha, lon, lat)

  • start_time – start-time in UTCDateTime format

  • end_time – end-time in UTCDateTime format

Returns

a list containing UTCDateTimes marking the start of each day and their corresponding means in each row

seismic.ASDFdatabase.plot_data_quality.setup_logger(name, log_file, level=20)[source]

Function to setup a logger; adapted from stackoverflow

seismic.ASDFdatabase.plot_data_quality.split_list(lst, npartitions)[source]

seismic.ASDFdatabase.query_input_yes_no module

From http://code.activestate.com/recipes/577058/

seismic.ASDFdatabase.query_input_yes_no.query_yes_no(question, default='yes')[source]

Ask a yes/no question via input() and return their answer.

“question” is a string that is presented to the user. “default” is the presumed answer if the user just hits <Enter>. It must be “yes” (the default), “no” or None (meaning an answer is required of the user).

The “answer” return value is one of “yes” or “no”.

seismic.ASDFdatabase.sc3toasdf module

Description:

Reads waveforms (within a given time-range) from a Seiscomp3 server and dumps out ASDF files, along with a json file containing associated metadata

References:

CreationDate: 13/09/18 Developer: rakib.hassan@ga.gov.au

Revision History:

LastUpdate: 22/08/18 RH LastUpdate: dd/mm/yyyy Who Optional description

class seismic.ASDFdatabase.sc3toasdf.DictToStr[source]

Bases: dict

seismic.ASDFdatabase.sc3toasdf.hasOverlap(stime1, etime1, stime2, etime2)[source]
seismic.ASDFdatabase.sc3toasdf.make_ASDF_tag(tr, tag)[source]

seismic.ASDFdatabase.seisds module

class seismic.ASDFdatabase.seisds.SeisDB(json_file=False, generate_numpy_index=True)[source]

Bases: object

generateIndex()[source]
get_data_percentage(net, sta, chan, tags)[source]
get_gaps_intervals(net, sta, chan, tags)[source]
get_recording_intervals(net, sta, chan, tags)[source]
get_unique_information()[source]

Method to retreive the unique channels and tags within an ASDF file from the JSON Database :return: (unique channels, unique tags)

Method to test if a channel code is related to a given net/stn/tag/loc :param chan: Channel Code, String :param net: Network Code, String :param sta: Station Code, String :param sta: Location Code, String :return: True/False, Bool

queryByTime(net, sta, chan, tags, query_starttime, query_endtime)[source]
retrieve_full_db_entry(json_key)[source]

Method to take an output from queryByTime and get the full information from the original JSON db :return: full DB

seismic.ASDFdatabase.utils module

seismic.ASDFdatabase.utils.rtp2xyz(r, theta, phi)[source]

Module contents