CHANGES:

1. Replaced `read_phe_cases` with `CasesData`
2. Column-name fix in `case_exceedance`
3. Fix column heading in `summarize.infec_incidence`
4. Add Rt_exceed to `summarize.rt`
5. Add layer option to `summary_geopackage`
6. Update `ruffus_pipeline.py` to reflect above changes
7. Update `template_config.yaml` to reflect above changes

Note: in the actual analysis, the effect of December Tiers was
removed.

CHANGES:

1. New data adapter `read_challen_tier_restriction`
2. Modified `model_spec.py` to use new data adapter

CHANGES:

1. Re-introduced Tier lockdown covariates.  National lockdown covariate is set to 0 because
   we cannot identify this from the time-varying baseline force of infection.

2. Added inference on variance parameter for the temporal Gaussian process on beta.

CHANGES:

1. update date and data name in enqueue_pipeline.sh
2. update infection time initialisation in model_spec.py

CHANGES:

1. Implemented log-linear model for weekday effect in I->R hazard;
2. Updated summary.py and within_between.py to match;
3. Implemented linear random walk for new gamma0 parameter.
4. Implemented per-parameter data structure in output HDF5 file.

CHANGES:

1. Updated the model to use the new gemlib library;
2. Removed automatic deletion of results directory by prepare_config.py;
3. Parameterised `gamma` prior parameters and added to template_config.yaml;
4. Updated within_between.py to use global configuration file.

CHANGES:

1. Added `data/example_cases.py`, `data/uk_clip.py`, `covid/summary.py`, `summary.py`
2. `summary.py` computes summary values required by reports to SAGE
3. Small changes to `inference.py` and `simulate.py` to reflect baked-in `nu` parameter in `model_spec.py`.

Removed redundant code from `inference.py` (duplicated in `model_spec.py`). Small change to `xi_freq` parameter in `model_spec.py`.

Changes:

1. Created a TFP JointDistribution to represent full probability model;
2. Renamed CovidUKStochastic --> DiscreteTimeStateTransitionModel;
3. DiscreteTimeStateTransitionModel now inherits from tfp.Distribution.