This is asimov-cogwheel, an interface to the cogwheel gravitational-wave parameter estimation code which allows the asimov analysis automation code to run it.

You can install asimov-cogwheel by running

$ pip install asimov-cogwheel

You can specify GWF (Gravitational Wave Frame) files as input data sources in your configuration file. This allows you to use strain data from local files or from previous analyses (e.g., from the asimov-gwdata pipeline) instead of downloading from GWOSC.

Frame files should be in the standard GWF format used by LIGO/Virgo/KAGRA.

To use frame files, add a data section to your configuration file:

event:
  name: GW150914
  event time: 1126259462.4  # GPS time is required when using frame files

data:
  frame files:
    H1: /path/to/H-H1_GWOSC_16KHZ_R1-1126257415-4096.gwf
    L1: /path/to/L-L1_GWOSC_16KHZ_R1-1126257415-4096.gwf
    V1: /path/to/V-V1_GWOSC_16KHZ_R1-1126257415-4096.gwf
  # Optional: Specify custom channel names for each detector
  # If not specified, defaults to {IFO}:GWOSC-16KHZ_R1_STRAIN
  channels:
    H1: H1:GWOSC-16KHZ_R1_STRAIN
    L1: L1:GWOSC-16KHZ_R1_STRAIN
    V1: V1:GWOSC-16KHZ_R1_STRAIN
  # Optional: Segment length in seconds (default: 32.0)
  segment length: 32.0

likelihood:
  # Optional: Post trigger time in seconds (default: 2.0)
  # Time after the event to include in the analysis
  post trigger time: 2.0

quality:
  # Optional: Maximum frequency in Hz (default: 1024.0)
  # Can be specified per-detector or as a single value
  maximum frequency:
    H1: 1024.0
    L1: 1024.0

When frame files are specified:

• The frame files are read using gwpy.timeseries.TimeSeries
• Strain data is extracted from the specified channels
• Data segment duration is configurable via data.segment length (default: 32s)
• Post-trigger time is configurable via likelihood.post trigger time (default: 2s)
• The time before the event is calculated as: segment length - post trigger time
• Maximum analysis frequency is configurable via quality.maximum frequency (default: 1024 Hz)
• The event time parameter is required to properly center the data
• If frame files are not specified, the default behavior is to download data from GWOSC

This approach makes the data handling compatible with bilby, allowing results from the two pipelines to be compared directly.

When using asimov to orchestrate analyses, you can pass frame files from previous pipeline stages (such as asimov-gwdata) by setting the data metadata on the production object. The asimov template will automatically include these in the configuration file following asimov's blueprint structure.

You can specify custom Power Spectral Density (PSD) files for each interferometer in your configuration file. This is useful when you want to use PSDs generated by other tools (e.g., BayesWave) for on-source analysis, rather than computing PSDs from the data.

PSD files should be in two-column text format:

# frequency (Hz)    PSD value
20.0                1.0e-46
50.0                1.0e-46
...

To use custom PSDs, add a psds section to your configuration file:

psds:
  H1: /path/to/H1_psd.txt
  L1: /path/to/L1_psd.txt
  V1: /path/to/V1_psd.txt
  # Optional: Configure whitening filter parameters
  whitening_filter:
    fmin: 15.0       # Minimum frequency (Hz), default: 15.0
    df_taper: 1.0    # Taper width (Hz), default: 1.0

When PSDs are specified in the configuration:

• The PSD files are loaded during the inference step
• Amplitude Spectral Densities (ASDs) are computed as the square root of the PSDs
• The ASDs are interpolated to match the event data frequencies
• New whitening filters are created and applied to the data
• The fmin and df_taper parameters control the highpass filter used in the whitening process
• If no PSDs are specified, the default behavior is to estimate them from the data using the Welch method

Frame files and custom PSDs can be used together to provide complete control over the input data and noise characterization.