Started: 2021-11-18 11:07:20
Last activity: 2021-11-18 11:07:20
Topics: DMC Software MUSTANG QA
We are pleased to announce the public release of ISPAQ version 3.0.0, available at [ https://github.com/iris-edu/ispaq | https://github.com/iris-edu/ispaq ] .
ISPAQ is a command line application that enables you to calculate quality metrics for seismic data locally, by leveraging MUSTANG R-code within a Python client. Over 40 MUSTANG metrics can be calculated for either local miniSEED files or for data available through any Data Center that supports FDSN web services. These metrics include basic trace statistics, metrics based on miniSEED state-of-health flags (if available), metrics based on event arrivals, Power Spectral Densities (PSDs), Probability Density Functions (PDFs), and metrics derived from PSDs. All results are computed and stored on the user's local machine.
Improvements and changes for this release include:
* ability to write metric values to an SQLite database
* addition of MUSTANG metrics sample_rate_resp, sample_rate_channel, max_range
* access to IRIS PH5 archive data, using IRISPH5 alias
* new Jupyter notebook tutorials
* bug fixes and usage improvements
* code port to Python3
In addition, the new ISPAQ SQLite database is compatible with QuARG, the Quality Assurance Report Generator ( [ https://github.com/iris-edu/quarg | https://github.com/iris-edu/quarg ] ) and can be used as a source to import metric values into that tool.
- Linux or macOS operating system
- Anaconda ( [ https://www.anaconda.com/ | https://www.anaconda.com ] ) or Miniconda ( [ http://conda.pydata.org/miniconda.html | http://conda.pydata.org/miniconda.html ] )
ISPAQ was written by Jonathan Callahan (Mazama Science) and the IRIS Quality Assurance Team (dmc_qa<at>iris.washington.edu). It is maintained by Laura Keyson (laura<at>iris.washington.edu).