1) Test run for whole NZ validation (subduction) -- waveform comparison

2) 400m Whole NZ validation run

3) Rerun for 200 m (400m)

Jason/Robin

3) Sung

1) Done

2) Waiting on tectonic classification

3) Done (Robin verified)

3) https://uceqeng.slack.com/archives/C3SGQHXT8/p1589497169457800

1) Ground Motion Extraction

2) Hikurangi Geometry

3) Tectonic Classification

4) Mw Reconciliation

1) Viktor

2) James

3) Mike /  James

4) ?

5) ?

1. Almost done (See right)
2. Progress made
3. Mike continuing

Earthquake Detection#HighPass, CSV comparison

Hikurangi surface geometry

1) Cybershake Subduction (8 faults) :

a) optimised HF code

b) Run LF 400 m

2)Running 200m sims LF only - on Kisti / Maui (until Maui allocation leaves 100k)

1. lower south island/1 rel – run on maui now (KISTI) (Maui)
2. all faults/1 rel (KISTI) (Maui)
3. lower south island / all rels (KISTI) (Maui)
4. all faults/all rels (KISTI) (Maui)

cs20p4 : 200m . Initially join HF from 400m.

4) Empirical DS - DB calculation

5) Empirical / Cybershake / ratio hazard maps

1)Jason

1b) Jonney

2) Sung

2) In progress. Generated sources/ VMs.

2.1) Complete (except plot_ts) - Kisti // Complete - Maui

2.3) Complete - Maui

4) In-progress - About a third complete

2)PBS

1. Generalize hacks for KISTI
2. CH estimation based on linear regression (Use Maui data as basis. Jason to tidy up data)
3. Integrate with pre-processing (starting with VM)
   1. Separate db creation out of install
   2. Create generic slurm for the rest of install, make install operate on each fault
   3. Create a generic slurm for VM generation
4. Tectonic Type – Add some hack into GCMT to SRF. – flag hack. Part of the GMDB in the future
   
   

1. James
2. Jason / Brendon
3. Jonney
4. James

1) Deferred

2) Provided data to Brendon

4) Deferred

1. GM Selection for Empirical
   1. Integrate workflow into seistech master
   2. Synthetic tests for GCIM between Empirical and Simulation (1 rupture, N ruptures)
2. Automate documentation
3. Front-end
   
   
   1. Milestone #2
      1. authentication.
      2. user access to individual tab controlled by authentication
      3. User data managed by API, and additional user data kept in a separate db
      4. Data integrity and consistency between Auth0 and separate db maintained.
   2. Milestone #3
      1. API call framework - plan the API proxy
      2. Create Mock API's with canned JSON response
      3. Call mocked API from the front end and ingest JSON. To demonstrate an example of full functionality of the front end
   3. Milestone #4: API – 2
      1. Create an API proxy - including error messages for restricted access
   1. 1. Call existing Core API’s from the front end replacing the mocks.
      2. JWT authorisation between the proxy and the core API
   2. Milestone #5: Deployment of 3 core environments
      1. Deploy DEV, TEST/EA, PROD versions
      2. Deployment is fully automated via scripts and config files.
      3. Update or switch-over is easily achieved utilizing deployment slots 
      4. Disruption is kept minimal when updated.

1. Daniel / Claudio
2. Background task (Jason)
3. Andy

1. Almost completed

3. Resolved hosting-related issues (mostly m#5), API proxy (m#3+m#4) touching m#2.

Roadmap (scientific functionality list)

Production - TODO (longer term tasks)

1. NN - GMM
   1. Implement an initial basic pipeline with some NN config + flexible feature selection & preprocessing
   2. Add hypo-depth to NN GMM dataset
2. GM Classifier – see link

• Look at de-skew, automate if possible
• Add feature plots back in [Low priority]
• Setup comparison "tests" with Xavier's model
• Better way to save custom model
• Save feature pre-proc config as part of the model

3. Implement Grid search

1. SimAtlas simulation+animation:
   1. Test auto workflow with batch 4. (total 100 faults)
   2. Once batch 4 is done. Keep fueling the fire
2. Relocate data to nearline (waveform, retired user, txt based empirical)
   
   
3. NoisePy

1. Sung/Jonney
2. Sung

2. Done (NeSI to verify)

1.SimAtlas simulation+animation

2. Nearline

3. https://pubs-geoscienceworld-org.ezproxy.canterbury.ac.nz/ssa/srl/article/91/3/1853/583390/NoisePy-A-New-High-Performance-Python-Tool-for