Merge remote-tracking branch 'upstream/master'

.github/workflows/upload_to_zoltar.yml

@@ -3,7 +3,7 @@ on:
   workflow_dispatch:
     inputs:
       name:
-        description: 'Trigger Zoltar Upload'
+        description: 'Trigger'
 
 jobs:
   upload_zoltar:

.gitignore

@@ -9,6 +9,7 @@ visualization/data
 visualization/vis-master/data
 .ipynb_checkpoints
 covid19-forecast-hub.Rproj
+hub.code-workspace
 
 .vscode
 packrat/lib*/

.travis.yml

@@ -3,7 +3,7 @@ language: node_js
 dist: bionic
 sudo: required
 git:
-  depth: 5
+  depth: 3
 
 before_install:
   # Key for cran trusty ppa

README.md

@@ -77,38 +77,50 @@ For details about this file format specifications, please see the
 Our list of teams whose forecasts are currently standardized and in the 
 repository are (with data reuse license):
 
- - [Auquan](https://covid19-infection-model.auquan.com/) (none given)
- - [CDDEP](https://cddep.org/covid-19/) (none given)
+ - [Auquan](https://covid19-infection-model.auquan.com/) (CC-BY-4.0)
+ - [CDDEP](https://cddep.org/covid-19/) (CC-BY-4.0)
+ - [Carnegie Mellon Delphi Group](https://delphi.cmu.edu) (CC-BY-4.0)
  - [Columbia University](https://github.com/shaman-lab/COVID-19Projection) (Apache 2.0)
- - [CovidActNow](https://covidactnow.org/) (none given)
+ - [Columbia_UNC](https://github.com/COVID19BIOSTAT/covid19_prediction) (Apache 2.0)
+ - [CovidActNow](https://covidactnow.org/) (CC-BY-4.0)
  - [COVID-19 Simulator Consortium](https://covid19sim.org/) (CC-BY-4.0)
+ - [Discrete Dynamical Systems](https://dds-covid19.github.io/) (MIT)
  - [epiforecasts](https://github.com/epiforecasts/covid-us-deaths) (MIT)
  - [GLEAM from Northeastern University](https://www.gleamproject.org/covid-19) (CC-BY-4.0)
- - [Georgia Institute of Technology](https://www.cc.gatech.edu/~badityap/covid.html) (none given)
- - [Georgia Institute of Technology - Center for Health and Humanitarian Systems](https://github.com/pkeskinocak/COVID19GA) (none given)
+ - [Georgia Institute of Technology](https://www.cc.gatech.edu/~badityap/covid.html) (CC-BY-4.0)
+ - [Georgia Institute of Technology - Center for Health and Humanitarian Systems](https://github.com/pkeskinocak/COVID19GA) (CC-BY-4.0)
  - [IHME](https://covid19.healthdata.org/united-states-of-america) (CC-AT-NC-4.0)
- - [Iowa State University](http://www.covid19dashboard.us/) (none given)
- - [Iowa State University and Peking University](https://yumouqiu.shinyapps.io/covid-predict/) (none given)
+ - [Iowa State University](http://www.covid19dashboard.us/) (CC-BY-4.0)
+ - [Iowa State University and Peking University](https://yumouqiu.shinyapps.io/covid-predict/) (CC-BY-4.0)
  - [Karlen Working Group](https://pypm.github.io/home/) (gpl-3.0)
  - [LANL](https://covid-19.bsvgateway.org/) (see [license](./data-processed/LANL-GrowthRate/LICENSE.txt))
+ - LockNQuay (MIT)
  - [Imperial](https://github.com/sangeetabhatia03/covid19-short-term-forecasts) (CC-BY-NC-ND 4.0)
+ - [John Burant (JCB)](https://github.com/JohnBurant/COVID19-PRM) (CC-BY-4.0)
  - [Johns Hopkins ID Dynamics COVID-19 Working Group](https://github.com/HopkinsIDD/COVIDScenarioPipeline) (MIT)
- - [Massachusetts Institute of Technology](https://www.covidanalytics.io/) (Apache 2.0)
- - [Notre Dame](https://github.com/confunguido/covid19_ND_forecasting) (none given)
+ - [Massachusetts Institute of Technology - Covid Analytics](https://www.covidanalytics.io/) (Apache 2.0)
+ - [Massachusetts Institute of Technology - Covid Alliance](http://infectiontrajectory.covidalliance.com/) (CC-BY-4.0)
+ - [Notre Dame - FRED](https://github.com/confunguido/covid19_ND_forecasting) (CC-BY-4.0)
+ - [Notre Dame - mobility](https://github.com/TAlexPerkins/covid19_NDmobility_forecasting) (CC-BY-4.0)
+ - [Oliver Wyman](https://pandemicnavigator.oliverwyman.com/) (see [license](./data-processed/OliverWyman-Navigator/LICENSE.txt))
  - [Predictive Science Inc](https://predsci.com) (MIT)
- - [Areon Oliver Wyman](https://pandemicnavigator.oliverwyman.com/)(none given)
- - Quantori (none given)
- - Snyder Wilson Consulting (none given)
- - [STH](https://public.tableau.com/profile/covid19model#!/vizhome/COVID-19DeathProjections/USDeaths) (none given)
+ - [QJHong](https://qjhong.github.io) (CC-BY-4.0)
+ - Quantori (CC-BY-4.0)
+ - [Robert Walraven](http://rwalraven.com/COVID19)(CC-BY-4.0)
+ - Snyder Wilson Consulting (CC-BY-4.0)
+ - [STH](https://public.tableau.com/profile/covid19model#!/vizhome/COVID-19DeathProjections/USDeaths) (CC-BY-4.0)
  - US Army Engineer Research and Development Center (ERDC) (see [license](./data-processed/USACE-ERDC_SEIR/LICENSE.txt))
- - University of Arizona (CC-BY-NC-SA 4.0)
+ - [University of Arizona](https://jocelinelega.github.io/EpiGro/) (CC-BY-NC-SA 4.0)
  - [University of California, Los Angeles](https://covid19.uclaml.org/) (CC-BY-4.0)
- - [University of Geneva / Swiss Data Science Center](https://renkulab.shinyapps.io/COVID-19-Epidemic-Forecasting/) (none given)
+ - [University of California Merced MESA Lab](http://mechatronics.ucmerced.edu/covid19) (CC-BY-4.0)
+ - University of Chicago (CC-BY-NC-4.0)
+ - [University of Geneva / Swiss Data Science Center](https://renkulab.shinyapps.io/COVID-19-Epidemic-Forecasting/) (see [license](./data-processed/Geneva-DetGrowth/LICENSE.txt))
  - [University of Massachusetts - Expert Model](https://github.com/tomcm39/COVID19_expert_survey) (MIT)
  - [University of Massachusetts - Mechanistic Bayesian model](https://github.com/dsheldon/covid) (MIT)
- - [University of Michigan](https://gitlab.com/sabcorse/covid-19-collaboration) (cc-by-4.0)
+ - [University of Michigan](https://gitlab.com/sabcorse/covid-19-collaboration) (CC-BY-4.0)
+ - [University of Southern California Data Science Lab](https://scc-usc.github.io/ReCOVER-COVID-19) (MIT)
  - [University of Texas-Austin](https://covid-19.tacc.utexas.edu/projections/) (BSD-3)
- - [University of Virginia](https://biocomplexity.virginia.edu/) (cc-by-4.0)
+ - [University of Virginia](https://biocomplexity.virginia.edu/) (CC-BY-4.0)
  - [YYG](http://covid19-projections.com) (MIT) 
  - COVIDhub ensemble forecast: this is a combination of the above models. 
 

code/exploration/get_zoltar_PI.R

@@ -19,12 +19,13 @@ get_zoltar_PI <- function(data, forecast_date, targets, location, alpha) {
 
     for(target in targets) {
         step_ahead <- as.numeric(substr(target, 0,1))
+        format(round(as.numeric(1000.64)), big.mark=",")
         print(paste0("The forecasted ", target, " for ", loc_name, " by ", target_end_dates[step_ahead], " is ", 
-            tmp$value[tmp$target==target & tmp$class=="point" & tmp$unit==location], " with a ",
+            format(round(data$value[data$target==target & data$class=="point" & data$unit==location]), big.mark=","), " with a ",
             pi_level, "% PI of ",
-            tmp$value[tmp$target==target & tmp$class=="quantile" & tmp$unit=="US" & tmp$quantile==alpha_low], 
+            format(round(data$value[data$target==target & data$class=="quantile" & data$unit==location & data$quantile==alpha_low]), big.mark=","), 
             "-",
-            tmp$value[tmp$target==target & tmp$class=="quantile" & tmp$unit=="US" & tmp$quantile==alpha_high],
+            format(round(data$value[data$target==target & data$class=="quantile" & data$unit==location & data$quantile==alpha_high]), big.mark=","),
             "."))
     }
 }

code/exploration/summarize-ensemble-forecasts.R

@@ -11,29 +11,26 @@ source("code/exploration/get_zoltar_PI.R")
 this_ensemble_timezero <- as.character(get_next_saturday(Sys.Date())-5)
 target_end_dates <- get_next_saturday(this_ensemble_timezero)+7*c(0:3)
 
+inc_death_targets <- paste(1:4, "wk ahead inc death")
+cum_death_targets <- paste(1:4, "wk ahead cum death")
+
 ## connect to Zoltar
 zoltar_connection <- new_connection()
 zoltar_authenticate(zoltar_connection, Sys.getenv("Z_USERNAME"), Sys.getenv("Z_PASSWORD"))
 
 ## construct Zoltar query
 project_url <- "https://www.zoltardata.com/api/project/44/"
-list_query <- list(
-    "models" = list("ensemble"),
-    "timezeros" = as.list(this_ensemble_timezero),
-    "targets" = as.list(c(paste(1:4, "wk ahead inc death"), paste(1:4, "wk ahead cum death")))
-)
-zoltar_query <- zoltr::query_with_ids(zoltar_connection, project_url, list_query)
 
 # submit query
-job_url <- zoltr::submit_query(zoltar_connection, project_url, zoltar_query)
-
-## extract query data
-tmp <- job_data(zoltar_connection, job_url)
+dat <- do_zoltar_query(
+    zoltar_connection, project_url, 
+    model_abbrs = "COVIDhub-ensemble",
+    targets = c(inc_death_targets, cum_death_targets),
+    timezeros = this_ensemble_timezero,
+    types = c("point", "quantile"))
 
-inc_deaths <- paste(1:4, "wk ahead inc death")
-cum_deaths <- paste(1:4, "wk ahead cum death")
 
-get_zoltar_PI(tmp, this_ensemble_timezero, targets = cum_deaths, location = "US", alpha = .1)
-get_zoltar_PI(tmp, this_ensemble_timezero, targets = inc_deaths, location = 25, alpha = .1)
-get_zoltar_PI(tmp, this_ensemble_timezero, targets = cum_deaths, location = 25, alpha = .5)
+get_zoltar_PI(dat, this_ensemble_timezero, targets = cum_death_targets, location = "US", alpha = .1)
+get_zoltar_PI(dat, this_ensemble_timezero, targets = inc_death_targets, location = 25, alpha = .1)
+get_zoltar_PI(dat, this_ensemble_timezero, targets = cum_death_targets, location = 25, alpha = .5)