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80
- plot_waveform_posterior uses non representative samples
- Sanity_check_labels returns error when NoneType is in label keys
- Double check `theta_jn` and `iota` consistency in the docs
- CPNest resuming on HTCondor
- Make sure all conditional priors can draw multiple samples at once
- Discontinue Python 2.7 support?
- PowerLaw prior does not check if prior minimum/maximum are valid
- Add the waveforms check to the C.I.
- Issue when sampling using BasicGravitationalWaveTransient
- Error in the example of GW170817
- Define credible interval object
- Fix equality check for Beta prior
- Add cacheing of marginalized luminosity-distance lookup table
- Add time marginalisation to the ROQ likelihood
- Fake sampler for likelihood consistency check
- Nestle steps argument doesn't work
- Organise the examples
- Add detecor frame sky-parametrization
- Add ability to inject NR waveforms
- Stopping conditions to produce N independent samples
- Nice skyLoc priors
- Viewing angle as parameter
- Make a detector response function for time domain response
- Add numerical relativity support
- Vectorise likelihood function to accept arrays of parameters
- Fetching open data does not work for most events
- Add the "dynamic" nested sampler from `dynesty`.
- Fix automated docker builds
- Make sure marginalized parameters are not sampled
- Introduce correlated prior sets
- Interferometer.plot_data should default to using Interferometer._strain_data.frequency_domain_strain
- Allow results to be returned as an ArviZ InferenceData object
- `plot_corner` should have a straight forward way to not include truths in injection runs.
- Check for duplicate parameters
- Added a bounded KDE method
- GW-specific result object
- `theta_jn` and `iota`
- Proposal library
- import bilby fails out-of-the-box due to matplotlib backend issues
- improving CPNest integration
- Vary the cosmology used
- Extend capabilities of `load_data_from_cache_file`
- Replace inspect.getargspec references
- result.plot_with_corner fails if the source function does not contain **kwargs
- Use the `PriorSet` from the first step of PE as the `sampling_prior` for hyper-pe
- Enable Interpolated prior saving
- Time domain injections
- Try using the `hope` framework to optimize parts of the code.
- Store extra sample information
- Vectorise geometric functions
- Time varying detector response
- Add Multivariate Gaussian Mixture Model as prior
- Automagically (sic) set up prior rescaling.
- Add `start_time` for the `time_array` in `WaveformGenerator`
- Allow user specified frequency cutoffs to allow for unbiased inspiral-only PE
- Make functions to plot waveforms and posterior samples in time and frequency domain
- Turn the 'real data processing' steps into methods of InterferometerStrainData (e.g. download_open_data(), filter_data(), etc)
- Automate `get_event_data`
- units in latex labels
- `InterferometerData` proposal
- Check Windows compatibility
- Add Occam factor calculation
- mimic LALInference's proposal distribution
- Create html/pdf documentation
- condoriser
- Figure out time duration
- caching issue in GW150914 example
- hyper-parameter estimation likelihood
- Clean up detector.py
- Add profiling scripts
- Priors class
- Running tupak with one line + gracedb
- Check the template fits in the segment
- Include eccentricity as a searchable parameter (but defaults to zero) + log-uniform priors
- Make plots of inclination posteriors return cos(iota) by default
- Gaussian noise returns garbage below PSD fmin
- Implement ra, dec, geocent_time, and psi by default in the waveform generator
- Allow for different sampling parameters to prior
- Use gwpy for all handling of time and frequency series
- Create testsuite for the project
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