Thread: ISPAQ version 2.0.0 is released

Started: 2019-02-05 19:01:12
Last activity: 2019-02-05 19:01:12
2019-02-05 19:01:12
We are happy to announce the release of ISPAQ version 2.0.0, available at .

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:

- the ability to aggregate PSDs into a PDF that spans multiple days
- replacement of metric names 'pdf_text' and 'pdf_plot' with a single metric name 'pdf'
- output of the 'pdf' metric is controlled by a new section in the preferences file called 'PDF Preferences' or through the command line
- other changes to the preference file include new output directories for PSD and PDF files and modified default metric aliases. This release is not completely compatible with older preference files.
- PDFs require that PSD text files are available. These can be generated with metric name 'psd_corrected' either prior to or concurrently with 'pdf'.
- the dead_channel_exp metric has been retired from MUSTANG. This release removes this metric from ISPAQ.
- requires R-package IRISMustangMetrics_2.2.0 (included and also available on CRAN)
- fixes bug that affected PSD/PDF output when local RESP files are used
- updates recommended package versions for conda environment install

Software Requirements:

- Linux or macOS operating system
- Anaconda ( or Miniconda (

ISPAQ was written by Jonathan Callahan (Mazama Science) and the IRIS Quality Assurance Team (dmc_qa<at>
03:52:27 v.ad6b513c