Merge pull request #19 from USEPA/ver-0.2.0

Prepare v0.2.0 release
USEPA · Aug 18, 2022 · 3bffa79 · 3bffa79
2 parents bfe84c4 + 3e88f1c
commit 3bffa79
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diff --git a/.github/workflows/render-model-validation.yaml b/.github/workflows/render-model-validation.yaml
@@ -47,7 +47,7 @@ jobs:
       - uses: actions/checkout@v2
         with:
           fetch-depth: 0
-          ref: dev
+          ref: 'ver-0.2.0'
       # - run: git checkout HEAD^
 
       - uses: r-lib/actions/setup-pandoc@v2
@@ -69,17 +69,17 @@ jobs:
       - name: Render model validation Rmarkdown file
         run: |
           install.packages("rmarkdown")
-          for (year in 2012:2017) {
+          for (year in 2018:2020) {
             rmarkdown::render("inst/doc/ValidateModel.Rmd", output_dir = "inst/doc/output", output_file = paste0("ValidateModel_", year, ".md"))
           }
         shell: Rscript {0}
 
       - name: Commit model validation results
         run: |
-          git fetch origin dev
-          git pull origin dev
+          git fetch origin ver-0.2.0
+          git pull origin ver-0.2.0
           git config user.name "GitHub Actions Bot"
           git config user.email "41898282+github-actions[bot]@users.noreply.github.com"
           git add inst/doc/output/ValidateModel*.md
           git commit -m "Update model validation documents"
-          git push origin dev
+          git push origin ver-0.2.0
diff --git a/.github/workflows/save-raw-data.yaml b/.github/workflows/save-raw-data.yaml
@@ -8,24 +8,30 @@ jobs:
   generate-save-data:
     runs-on: ${{ matrix.config.os }}
 
-    name: ${{ matrix.script-run.script }}, ${{ matrix.script-run.year }} (${{ matrix.config.os}}, ${{ matrix.config.r}})
+    name: ${{ matrix.script-run }}, ${{ matrix.data-year }} (${{ matrix.config.os}}, ${{ matrix.config.r}})
 
     strategy:
       fail-fast: false
       matrix:
         config:
           - {os: ubuntu-latest, r: 'release'}
         script-run: 
-          - {script: data-raw/BEAData.R}
-          - {script: data-raw/CensusData.R}
-          - {script: data-raw/EIAData.R}
-          - {script: data-raw/FAFData.R}
-          - {script: data-raw/USASpendingData.R, year: 2012}
-          - {script: data-raw/USASpendingData.R, year: 2013}
-          - {script: data-raw/USASpendingData.R, year: 2014}
-          - {script: data-raw/USASpendingData.R, year: 2015}
-          - {script: data-raw/USASpendingData.R, year: 2016}
-          - {script: data-raw/USASpendingData.R, year: 2017}
+          - data-raw/BEAData.R
+          - data-raw/CensusData.R
+          - data-raw/EIAData.R
+          - data-raw/FAFData.R
+          - data-raw/USASpendingData.R
+        data-year:
+          - 2012
+          - 2013
+          - 2014
+          - 2015
+          - 2016
+          - 2017
+          - 2018
+          - 2019
+          - 2020
+
 
     # env:
       # R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
@@ -53,15 +59,13 @@ jobs:
           sudo rm -rf "/usr/local/share/boost"
           sudo rm -rf "$AGENT_TOOLSDIRECTORY"
 
-      # Load package
-      - name: Load stateior
-        run: Rscript -e 'devtools::load_all'
-
       # Generate data and save as .rds files
       - name: Generate data and save as .rds files (metadata saved as .json files)
         run: |
-          year <- ${{ matrix.script-run.year }}
-          source("${{ matrix.script-run.script }}")
+          devtools::load_all()
+          year <- ${{ matrix.data-year }}
+          options(timeout = 1000)
+          source("${{ matrix.script-run }}")
         shell: Rscript {0}
 
       # Upload .rds files

diff --git a/.github/workflows/save-state-supply-model-data.yaml b/.github/workflows/save-state-supply-model-data.yaml
@@ -1,5 +1,5 @@
 # This workflow is designed to be manually triggered only.
-name: Save state supply model data as .rds
+name: Save state supply model data as .rds in parallel runs
 
 on:
   workflow_dispatch: # allow manual trigger
@@ -8,13 +8,25 @@ jobs:
   generate-save-data:
     runs-on: ${{ matrix.config.os }}
 
-    name: ${{ matrix.config.os}} (${{ matrix.config.r}})
+    name: ${{ matrix.script-run }}, ${{ matrix.data-year }} (${{ matrix.config.os}}, ${{ matrix.config.r}})
 
     strategy:
       fail-fast: false
       matrix:
         config:
           - {os: ubuntu-latest, r: 'release'}
+        script-run:
+          - data-raw/StateSupplyModel.R
+        data-year:
+          - 2012
+          - 2013
+          - 2014
+          - 2015
+          - 2016
+          - 2017
+          - 2018
+          - 2019
+          - 2020
 
     # env:
       # R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
@@ -46,7 +58,8 @@ jobs:
       - name: Load stateior, generate and save state supply IO data
         run: |
           devtools::load_all()
-          source("data-raw/StateSupplyModel.R")
+          year <- ${{ matrix.data-year }}
+          source("${{ matrix.script-run }}")
         shell: Rscript {0}
 
       # Upload .rds files

diff --git a/.github/workflows/save-state-use-model-data.yaml b/.github/workflows/save-state-use-model-data.yaml
@@ -1,5 +1,5 @@
 # This workflow is designed to be manually triggered only.
-name: Save state use model data as .rds
+name: Save state use model data as .rds in parallel runs
 
 on:
   workflow_dispatch: # allow manual trigger
@@ -8,13 +8,25 @@ jobs:
   generate-save-data:
     runs-on: ${{ matrix.config.os }}
 
-    name: ${{ matrix.config.os}} (${{ matrix.config.r}})
+    name: ${{ matrix.script-run }}, ${{ matrix.data-year }} (${{ matrix.config.os}}, ${{ matrix.config.r}})
 
     strategy:
       fail-fast: false
       matrix:
         config:
           - {os: ubuntu-latest, r: 'release'}
+        script-run:
+          - data-raw/StateUseModel.R
+        data-year:
+          - 2012
+          - 2013
+          - 2014
+          - 2015
+          - 2016
+          - 2017
+          - 2018
+          - 2019
+          - 2020
 
     # env:
       # R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
@@ -46,7 +58,8 @@ jobs:
       - name: Load stateior, generate and save state use IO data
         run: |
           devtools::load_all()
-          source("data-raw/StateUseModel.R")
+          year <- ${{ matrix.data-year }}
+          source("${{ matrix.script-run }}")
         shell: Rscript {0}
 
       # Upload .rds files

diff --git a/.github/workflows/save-two-region-model-data.yaml b/.github/workflows/save-two-region-model-data.yaml
@@ -24,9 +24,9 @@ jobs:
           - 2015
           - 2016
           - 2017
-          # - 2018
-          # - 2019
-          # - 2020
+          - 2018
+          - 2019
+          - 2020
 
     # env:
       # R_REMOTES_NO_ERRORS_FROM_WARNINGS: true

diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,8 +1,8 @@
 Package: stateior
 Type: Package
 Title: US State Input-Output (stateio) R modeling software
-Version: 0.1.0
-Date: 2022-07-29
+Version: 0.2.0
+Date: 2022-05-17
 Authors@R: c(
   person("Mo", "Li", email="[email protected]", role="aut"),
   person("Joao-Pedro", "Ferreira", email="[email protected]", role= c("aut")),

diff --git a/NAMESPACE b/NAMESPACE
@@ -8,5 +8,6 @@ export(buildTwoRegionUseModel)
 export(loadStateIODataFile)
 export(plotICFandRPC)
 export(plotResidual)
+export(writeStateIODatatoCSV)
 import(ggplot2)
 importFrom(magrittr,"%>%")
diff --git a/R/BuildModel.R b/R/BuildModel.R
@@ -1,3 +1,6 @@
+# Define model version
+model_ver <- utils::packageDescription(pkg = "stateior", fields = "Version")
+
 #' Build a state supply model for all 52 states/regions (including DC and Overseas)
 #' for a given year
 #' @description Build a state supply model for all 52 states/regions
@@ -194,7 +197,8 @@ buildStateUseModel <- function(year) {
   US_ITA <- generateInternationalTradeAdjustmentVector("Summary", year)
   # Calculate state ITA by allocating US ITA via state/US COR (commodity output ratio)
   CommodityOutput <- loadStateIODataFile(paste0("State_Summary_CommodityOutput_",
-                                                year))
+                                                year),
+                                         ver = model_ver)
   for (state in states) {
     cor <- CommodityOutput[[state]] / rowSums(US_Use[commodities, c(industries, FD_cols)])
     model[["Use"]][[state]][commodities, "F051"] <- US_ITA*cor
@@ -301,13 +305,15 @@ buildTwoRegionUseModel <- function(state, year, ioschema, iolevel,
   SoI_DomesticUse <- loadStateIODataFile(paste0("State_",
                                                 iolevel,
                                                 "_DomesticUse_",
-                                                year))[[state]][commodities, ]
+                                                year),
+                                         ver = model_ver)[[state]][commodities, ]
   # Load state commodity output
   logging::loginfo("Loading state commodity output...")
   SoI_CommodityOutput <- loadStateIODataFile(paste0("State_",
                                                     iolevel,
                                                     "_CommodityOutput_",
-                                                    year))[[state]]
+                                                    year),
+                                             ver = model_ver)[[state]]
 
   # 2 - Generate 2-region ICFs
   logging::loginfo("Generating two-region interregional commodity flow (ICF) ratios...")
@@ -494,7 +500,8 @@ buildTwoRegionUseModel <- function(state, year, ioschema, iolevel,
   if (!domestic) {
     # Load US and SoI Use, calcuate RoUS_Use
     US_Use <- getNationalUse("Summary", year)
-    SoI_Use <- loadStateIODataFile(paste0("State_", iolevel, "_Use_", year))[[state]]
+    SoI_Use <- loadStateIODataFile(paste0("State_", iolevel, "_Use_", year),
+                                   ver = model_ver)[[state]]
     RoUS_Use <- US_Use - SoI_Use[commodities, c(industries, FD_cols)]
     # Calculate SoI_Import and RoUS_Import
     SoI_Import <- SoI_Use[commodities, c(industries, FD_cols)] - SoI_DomesticUse[commodities, c(industries, FD_cols)]
@@ -582,11 +589,13 @@ assembleTwoRegionIO <- function(year, iolevel) {
   State_IndustryOutput_ls <- loadStateIODataFile(paste0("State_",
                                                         iolevel,
                                                         "_IndustryOutput_",
-                                                        year))
+                                                        year),
+                                                 ver = model_ver)
   State_CommodityOutput_ls <- loadStateIODataFile(paste0("State_",
                                                          iolevel,
                                                          "_CommodityOutput_",
-                                                         year))
+                                                         year),
+                                                  ver = model_ver)
   # Assemble two-region IO tables
   TwoRegionIO <- list()
   for (state in sort(c(state.name, "District of Columbia"))) {
@@ -695,7 +704,8 @@ buildFullTwoRegionIOTable <- function(state, year, ioschema, iolevel) {
   logging::loginfo("Loading SoI Make table...")
   # SoI Make
   SoI_Make <- loadStateIODataFile(paste0("State_",iolevel,
-                                         "_Make_", year))[[state]]
+                                         "_Make_", year),
+                                  ver = model_ver)[[state]]
   rownames(SoI_Make) <- paste0(getBEASectorCodeLocation("Industry", state, "Summary"),
                                "/Industry")
   colnames(SoI_Make) <- paste0(getBEASectorCodeLocation("Commodity", state, "Summary"),
@@ -704,7 +714,8 @@ buildFullTwoRegionIOTable <- function(state, year, ioschema, iolevel) {
   SoI_CommodityOutput <- loadStateIODataFile(paste0("State_",
                                                     iolevel,
                                                     "_CommodityOutput_",
-                                                    year))[[state]]
+                                                    year),
+                                             ver = model_ver)[[state]]
 
   logging::loginfo("Generating RoUS Make table...")
   # RoUS Make
@@ -726,7 +737,8 @@ buildFullTwoRegionIOTable <- function(state, year, ioschema, iolevel) {
   logging::loginfo("Loading two-region Domestic Use tables...")
   # Two-region Use Transaction
   TwoRegionUse <- loadStateIODataFile(paste("TwoRegion", iolevel, "DomesticUse",
-                                            year, sep = "_"))[[state]]
+                                            year, sep = "_"),
+                                      ver = model_ver)[[state]]
   TwoRegionUseTrans_cols <- unlist(lapply(c(state, "RoUS"),
                                           function(x)
                                             getBEASectorCodeLocation("Industry",
@@ -751,8 +763,9 @@ buildFullTwoRegionIOTable <- function(state, year, ioschema, iolevel) {
   logging::loginfo("Calculating SoI and RoUS international imports by industry...")
   # International imports by industry
   SoI_Use <- loadStateIODataFile(paste("State", iolevel, "Use", year,
-                                       sep = "_"))[[state]][commodities,
-                                                            c(industries, FD_cols)]
+                                       sep = "_"),
+                                 ver = model_ver)[[state]][commodities,
+                                                           c(industries, FD_cols)]
   US_Use <- getNationalUse(iolevel, year)
   US_Import <- loadDatafromUSEEIOR(paste(iolevel, "Import", year, "BeforeRedef",
                                          sep = "_"))*1E6
@@ -769,7 +782,8 @@ buildFullTwoRegionIOTable <- function(state, year, ioschema, iolevel) {
   logging::loginfo("Calculating SoI and RoUS gross value added by industry...")
   # GVA
   GVA_rows <- getVectorOfCodes(iolevel, "ValueAdded")
-  SoI_GVA_ls <- loadStateIODataFile(paste("State", iolevel, "Use", year, sep = "_"))
+  SoI_GVA_ls <- loadStateIODataFile(paste("State", iolevel, "Use", year, sep = "_"),
+                                    ver = model_ver)
   SoI_GVA <- SoI_GVA_ls[[state]][GVA_rows, c(industries, FD_cols)]
   RoUS_GVA <- Reduce("+", SoI_GVA_ls)[GVA_rows, c(industries, FD_cols)] - SoI_GVA
   TwoRegionGVA <- cbind(SoI_GVA, RoUS_GVA)
@@ -785,12 +799,14 @@ buildFullTwoRegionIOTable <- function(state, year, ioschema, iolevel) {
   logging::loginfo("Loading foreign expenditure by U.S. residents and spending in the U.S. by nonresidents...")
   # Foreign expenditure by U.S. residents
   ForeignExp <- loadStateIODataFile(paste("State_ForeignExpenditureByResident",
-                                          year, sep = "_"))
+                                          year, sep = "_"),
+                                    ver = model_ver)
   SoIForeignExp <- ForeignExp[ForeignExp$GeoName == state, as.character(year)]
   RoUSForeignExp <- ForeignExp[ForeignExp$GeoName == "United States", as.character(year)] - SoIForeignExp
   # Spending in the U.S. by nonresidents
   DomesticExp <- loadStateIODataFile(paste("State_DomesticExpenditureByNonresident",
-                                           year, sep = "_"))
+                                           year, sep = "_"),
+                                     ver = model_ver)
   SoIDomesticExp <- DomesticExp[DomesticExp$GeoName == state, as.character(year)]
   RoUSDomesticExp <- DomesticExp[DomesticExp$GeoName == "United States", as.character(year)] - SoIDomesticExp
 
@@ -811,9 +827,11 @@ buildFullTwoRegionIOTable <- function(state, year, ioschema, iolevel) {
 
   # Append total output column
   tworegion_co_filename <- paste("TwoRegion", iolevel, "CommodityOutput", year, sep = "_")
-  TwoRegionCommodityOutput <- loadStateIODataFile(tworegion_co_filename)[[state]]
+  TwoRegionCommodityOutput <- loadStateIODataFile(tworegion_co_filename,
+                                                  ver = model_ver)[[state]]
   tworegion_io_filename <- paste("TwoRegion", iolevel, "IndustryOutput", year, sep = "_")
-  TwoRegionIndustryOutput <- loadStateIODataFile(tworegion_io_filename)[[state]]
+  TwoRegionIndustryOutput <- loadStateIODataFile(tworegion_io_filename,
+                                                 ver = model_ver)[[state]]
   FullTwoRegionTable[, "Total Output"] <- c(TwoRegionCommodityOutput,
                                             TwoRegionIndustryOutput)