1. 02 Feb, 2021 1 commit
  2. 25 Jan, 2021 1 commit
  3. 11 Jan, 2021 2 commits
  4. 10 Jan, 2021 1 commit
    • Chris Jewell's avatar
      Pipeline bugfixes · 9fe819d7
      Chris Jewell authored
      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
      9fe819d7
  5. 08 Jan, 2021 1 commit
  6. 07 Jan, 2021 1 commit
  7. 06 Jan, 2021 1 commit
  8. 04 Jan, 2021 1 commit
  9. 09 Dec, 2020 1 commit
  10. 03 Dec, 2020 1 commit
    • Chris Jewell's avatar
      As of analysis 2020-11-30 · 595ea2eb
      Chris Jewell authored
      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.
      595ea2eb
  11. 27 Nov, 2020 1 commit
  12. 19 Nov, 2020 1 commit
    • Chris Jewell's avatar
      Implemented weekday effect for I->R · 107186d1
      Chris Jewell authored
      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.
      107186d1
  13. 09 Nov, 2020 2 commits
  14. 08 Nov, 2020 1 commit
  15. 03 Nov, 2020 1 commit
  16. 02 Nov, 2020 1 commit
  17. 01 Nov, 2020 1 commit
  18. 26 Oct, 2020 1 commit
  19. 22 Oct, 2020 5 commits
  20. 05 Oct, 2020 1 commit
    • Chris Jewell's avatar
      Major new pipelining structure · bfcaf904
      Chris Jewell authored
      ==============================
      
      enqueue_pipeline.sh --> covid_pipeline.sge --> prepare_config.py --> inference.py --> summary.py
      
      enqueue_pipeline.sh identifies the dataset and analysis period, launching 4 SGE jobs [P1, P1+2]\times[specimen_date, report_date]
      
      Each SGE job runs the inference and summary scripts, using information contained in a config.yaml file.
      
      The config.yaml file, together with results outputs, are stored in a results directory specified the config file
      and over-ridden in the top-level enqueue_pipeline.sh script.
      bfcaf904
  21. 03 Oct, 2020 2 commits
  22. 01 Oct, 2020 2 commits
  23. 27 Sep, 2020 1 commit
  24. 25 Sep, 2020 2 commits
    • Chris Jewell's avatar
      Code tidy. · d247c771
      Chris Jewell authored
      d247c771
    • Chris Jewell's avatar
      Refactored model specification · e52283b6
      Chris Jewell authored
      Changes:
      
      1. Created a TFP JointDistribution to represent full probability model;
      2. Renamed CovidUKStochastic --> DiscreteTimeStateTransitionModel;
      3. DiscreteTimeStateTransitionModel now inherits from tfp.Distribution.
      e52283b6
  25. 23 Sep, 2020 1 commit
  26. 11 Sep, 2020 1 commit
  27. 05 Sep, 2020 1 commit
  28. 04 Sep, 2020 1 commit
    • Chris Jewell's avatar
      Pulled dates out of CovidUKStochastic class · 588d479e
      Chris Jewell authored
      Changes:
      
      1. Dates are pulled out of CovidUKStochastic
      2. CovidUKStochastic now behaves more like a tfd.Distribution
          * CovidUKStochastic is now instantiated with an initial time, number of time steps and
      time step size
          * CovidUKStochastic is now instantiated with the initial state.
      588d479e
  29. 30 Aug, 2020 1 commit
    • Chris Jewell's avatar
      Corrected Add/Delete move bounds. · 71205807
      Chris Jewell authored
      Consider an SEIR model.  For adding $x \geq 0$ S->E event times we have:
      \begin{equation}
      S(t+1) &=& S(0) - (N_{se}(t) + x) \geq 0 \\
      E(t+1) &=& E(0) + (N_{se}(t) + x) \geq 0
      \end{equation}
      such that $x$ is bounded by
      $$
      x \leq S(0) - N_{se}(t).
      $$
      
      Similarly for adding $x \geq 0$ E->I event times we have:
      $$
      x \leq E(0) + N_{se}(t) - N_{ei}(t).
      $$
      
      For deleting $x \geq 0$ S->E event times we have:
      $$
      x \leq E(0) + N_{se}(t) - N_{ei}(t)
      $$
      and for E->I event times we have;
      $$
      x \leq I(0) + N_{ei}(t) - N_{ir}(t).
      $$
      71205807
  30. 28 Aug, 2020 1 commit
  31. 26 Aug, 2020 1 commit
    • Chris Jewell's avatar
      New initialisation method · 0c2498bd
      Chris Jewell authored
      Changes:
      
      1. Previously, we initialised from the first imputed event at T-s, where s was random due
      to the initialisation process;
      
      2. We now calculate the state at time T given s (and the event imputation).
      0c2498bd