- 01 Apr, 2020 1 commit
-
-
Chris Jewell authored
1. Bugfix in initial condition setting for MCMC and prediction. 2. Rationalised data import. Now uses a load_data function in the covid.model module. 3. Updated model doc to reflect loss of background infectious pressure, implementation of commuting frequency. 4. Fixes in covid_ode.py reflecting updated model interface.
-
- 31 Mar, 2020 1 commit
-
-
Chris Jewell authored
-
- 30 Mar, 2020 5 commits
-
-
Chris Jewell authored
-
Chris Jewell authored
-
Chris Jewell authored
-
Chris Jewell authored
-
Chris Jewell authored
Updated ODE model with overall number of starting individuals parameter, and daily confirmed cases up to 27th March (PHE, whole of England).
-
- 28 Mar, 2020 5 commits
-
-
Chris Jewell authored
-
Chris Jewell authored
-
Chris Jewell authored
-
Chris Jewell authored
Fix binomial probs errors
-
Christopher Suter authored
-
- 27 Mar, 2020 6 commits
-
-
Chris Jewell authored
Add requirements.txt file
-
Christopher Suter authored
Excludes TF and TFP since we may want to switch between stable and nightly versions
-
Chris Jewell authored
Rewrite Multinomial as hand rolled iterated binomial.
-
Christopher Suter authored
-
Chris Jewell authored
Improve efficiency of stochastic model.
-
Christopher Suter authored
Big changes: 1. replace python for loop with tf.while_loop 2. work with a transposed state tensor shape - instead of [4, nlads * nages], use [nlads * nages, 4] - this made it pretty easy to eliminate some transposes in propagate_fn (there were comments there seemingly contemplating this shape arrangement) - this feels a little more natural to me, too; in TFP we'd call the 4 SEIR states components of the "event shape" of the system, and the nlads * nages part a "batch shape" (although one could reasonably also combine these together into one big matrix "event shape") - anyway, this allowed elimination of 3 transpose ops which makes for simpler code and avoids some memcpys - I also made an effort to update surrounding code to use the same data layout, but it seems like mcmc.py and covid_ode.py are broken right now anyway, due to other changes made in support of stochastic mode, so I couldn't confirm that my changes were sufficient. 3. switch off XLA (which didn't yield any clear improvement, although it also didn't really hurt), and disable autograph (which tries to do things like rewrite python for loops into TF graph code but tends to produce less performant than manually optimized code like what I've done here)
-
- 26 Mar, 2020 5 commits
-
-
Chris Jewell authored
-
Chris Jewell authored
-
Chris Jewell authored
-
Chris Jewell authored
-
Chris Jewell authored
Wrote chainbinom_simulate.py function. Halfway through re-writing the ODE class (which should now not be an ODE!).
-
- 25 Mar, 2020 4 commits
-
-
Chris Jewell authored
-
Chris Jewell authored
# Conflicts: # mcmc.py
-
Chris Jewell authored
-
Chris Jewell authored
-
- 24 Mar, 2020 2 commits
-
-
Chris Jewell authored
-
Chris Jewell authored
-
- 23 Mar, 2020 1 commit
-
-
Chris Jewell authored
-
- 22 Mar, 2020 1 commit
-
-
Chris Jewell authored
-
- 21 Mar, 2020 3 commits
-
-
Chris Jewell authored
-
Chris Jewell authored
-
Chris Jewell authored
-
- 20 Mar, 2020 6 commits
-
-
Chris Jewell authored
-
Chris Jewell authored
-
Chris Jewell authored
-
Chris Jewell authored
-
Chris Jewell authored
-
Chris Jewell authored
-