Feat/18 packagize

.Rbuildignore

@@ -1,2 +1,7 @@
 ^.*\.Rproj$
+^.github/
+^.lintr$
+^Dockerfile$
+^LICENSE\.md$
 ^\.Rproj\.user$
+^docker-compose.yml$

.github/workflows/R.yml

@@ -0,0 +1,23 @@
+---
+# This example file will enable R language checks on push or PR to the main
+# branch.
+# It will also run the checks every weeknight at midnight UTC
+#
+# Note the @main in `uses:` on the last line. This will call the latest version
+# of the workflow from the `main` brnach in the RMI-PACTA/actions repo. You can
+# also specify a tag from that repo, or a commit SHA to pin action versions.
+on:
+  pull_request:
+  push:
+    branches: [main]
+  schedule:
+    - cron: '0 0 * * 1,2,3,4,5'
+  workflow_dispatch:
+
+name: R
+
+jobs:
+  R-package:
+    name: R Package Checks
+    uses: RMI-PACTA/actions/.github/workflows/R.yml@main
+    secrets: inherit

.gitignore

@@ -4,3 +4,7 @@ inputs/
 outputs/
 data/
 .Rhistory
+analysis_output_dir/**/*
+benchmarks_dir/**/*
+dashboard_output_dir/**/*
+dashboard_data_dir/**/*

.lintr

@@ -0,0 +1,4 @@
+linters: linters_with_defaults(
+    object_length_linter = NULL,
+    commented_code_linter = NULL
+  )

DESCRIPTION

@@ -1,8 +1,13 @@
 Package: workflow.pacta.dashboard
 Title: Run PACTA dashboard JSON generation
-Version: 0.0.0.9001
+Version: 0.0.0.9002
 Authors@R:
-    c(person(given = "CJ",
+    c(person(given = "Alex",
+             family = "Axthelm",
+             role = c("aut", "cre", "ctr"),
+             email = "[email protected]",
+             comment = c(ORCID = "0000-0001-8579-8565")),
+      person(given = "CJ",
              family = "Yetman",
              role = c("aut", "ctr"),
              email = "[email protected]",
@@ -23,9 +28,14 @@ RoxygenNote: 7.3.2
 Imports:
     dplyr,
     jsonlite,
+    logger,
     pacta.portfolio.report,
     pacta.portfolio.utils,
-    readr
+    pacta.workflow.utils,
+    readr,
+    rlang,
+    tidyr
 Remotes:
     RMI-PACTA/pacta.portfolio.report,
-    RMI-PACTA/pacta.portfolio.utils
+    RMI-PACTA/pacta.portfolio.utils,
+    RMI-PACTA/pacta.workflow.utils

Dockerfile

@@ -1,4 +1,4 @@
-FROM docker.io/rocker/r-ver:4.3.1
+FROM docker.io/rocker/r-ver:4.3.1 as base
 
 RUN CRAN_LIKE_URL="https://packagemanager.posit.co/cran/__linux__/jammy/2024-04-05"; \
     echo "options(repos = c(CRAN = '$CRAN_LIKE_URL'))" \
@@ -19,8 +19,11 @@ COPY DESCRIPTION /workflow.pacta.dashboard/DESCRIPTION
 # install pak, find dependencises from DESCRIPTION, and install them.
 RUN Rscript -e "pak::local_install_deps('/workflow.pacta.dashboard')"
 
-COPY main.R /workflow.pacta.dashboard/main.R
+FROM base AS install-pacta
 
-WORKDIR /workflow.pacta.dashboard
+COPY . /workflow.pacta.dashboard/
 
-CMD ["Rscript", "--vanilla", "/workflow.pacta.dashboard/main.R"]
+RUN Rscript -e "pak::local_install(root = '/workflow.pacta.dashboard')"
+
+# set default run behavior
+ENTRYPOINT ["Rscript", "--vanilla", "/workflow.pacta.dashboard/inst/extdata/scripts/prepare_dashboard_data.R"]

LICENSE

@@ -0,0 +1,2 @@
+YEAR: 2024
+COPYRIGHT HOLDER: workflow.pacta.dashboard authors

LICENSE.md

@@ -0,0 +1,21 @@
+# MIT License
+
+Copyright (c) 2024 workflow.pacta.dashboard authors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

NAMESPACE

@@ -0,0 +1,9 @@
+# Generated by roxygen2: do not edit by hand
+
+importFrom(logger,log_debug)
+importFrom(logger,log_error)
+importFrom(logger,log_info)
+importFrom(logger,log_trace)
+importFrom(logger,log_warn)
+importFrom(rlang,.data)
+importFrom(rlang,.env)

R/prep_company_bubble.R

@@ -0,0 +1,139 @@
+# prep_company_bubble ----------------------------------------------------------
+# based on pacta.portfolio.report:::prep_company_bubble, but does not filter to
+# allocation == "portfolio_weight" nor by scenario and scenario source
+prep_company_bubble <- function(
+  equity_results_company,
+  bonds_results_company,
+  portfolio_name,
+  start_year,
+  green_techs
+) {
+
+  equity_data <-
+    equity_results_company |>
+    dplyr::filter(.data$portfolio_name == .env$portfolio_name) |>
+    dplyr::filter(
+      .data$ald_sector %in% c(
+        "Power",
+        "Automotive"
+      )
+    ) |>
+    dplyr::filter(.data$equity_market == "GlobalMarket") |>
+    dplyr::filter(.data$scenario_geography == "Global") |>
+    dplyr::filter(
+      .data$year %in% c(
+        .env$start_year,
+        .env$start_year + 5
+      )
+    ) |>
+    dplyr::mutate(
+      plan_buildout = (
+        dplyr::last(.data$plan_tech_prod, order_by = .data$year) -
+          dplyr::first(.data$plan_tech_prod, order_by = .data$year)
+      ),
+      scen_buildout = (
+        dplyr::last(.data$scen_tech_prod, order_by = .data$year) -
+          dplyr::first(.data$scen_tech_prod, order_by = .data$year)
+      ),
+      .by = c(
+        "company_name",
+        "technology",
+        "scenario_source",
+        "scenario",
+        "allocation"
+      )
+    ) |>
+    dplyr::filter(.data$year == .env$start_year) |>
+    dplyr::mutate(green = .data$technology %in% .env$green_techs) |>
+    dplyr::reframe(
+      plan_tech_share = sum(.data$plan_tech_share, na.rm = TRUE),
+      plan_buildout = sum(.data$plan_buildout, na.rm = TRUE),
+      scen_buildout = sum(.data$scen_buildout, na.rm = TRUE),
+      plan_carsten = sum(.data$plan_carsten, na.rm = TRUE),
+      port_weight = unique(.data$port_weight),
+      .by = c(
+        "company_name",
+        "allocation",
+        "scenario_source",
+        "scenario",
+        "ald_sector",
+        "green",
+        "year"
+      )
+    ) |>
+    dplyr::mutate(y = .data$plan_buildout / .data$scen_buildout) |>
+    dplyr::filter(.data$green) |>
+    dplyr::select(
+      -"plan_buildout",
+      -"scen_buildout",
+      -"green"
+    ) |>
+    dplyr::filter(!is.na(.data$plan_tech_share)) |>
+    dplyr::mutate(y = pmax(.data$y, 0, na.rm = TRUE)) |>
+    dplyr::mutate(asset_class = "Listed Equity")
+
+  bonds_data <-
+    bonds_results_company |>
+    dplyr::filter(.data$portfolio_name == .env$portfolio_name) |>
+    dplyr::filter(
+      .data$ald_sector %in% c(
+        "Power",
+        "Automotive"
+      )
+    ) |>
+    dplyr::filter(.data$equity_market == "GlobalMarket") |>
+    dplyr::filter(.data$scenario_geography == "Global") |>
+    dplyr::filter(
+      .data$year %in% c(
+        .env$start_year,
+        .env$start_year + 5
+      )
+    ) |>
+    dplyr::mutate(
+      plan_buildout = (
+        dplyr::last(.data$plan_tech_prod, order_by = .data$year) -
+          dplyr::first(.data$plan_tech_prod, order_by = .data$year)
+      ),
+      scen_buildout = (
+        dplyr::last(.data$scen_tech_prod, order_by = .data$year) -
+          dplyr::first(.data$scen_tech_prod, order_by = .data$year)
+      ),
+      .by = c(
+        "company_name",
+        "technology",
+        "scenario_source",
+        "scenario",
+        "allocation"
+      )
+    ) |>
+    dplyr::filter(.data$year == .env$start_year) |>
+    dplyr::mutate(green = .data$technology %in% .env$green_techs) |>
+    dplyr::reframe(
+      plan_tech_share = sum(.data$plan_tech_share, na.rm = TRUE),
+      plan_buildout = sum(.data$plan_buildout, na.rm = TRUE),
+      scen_buildout = sum(.data$scen_buildout, na.rm = TRUE),
+      plan_carsten = sum(.data$plan_carsten, na.rm = TRUE),
+      port_weight = unique(.data$port_weight),
+      .by = c(
+        "company_name",
+        "allocation",
+        "scenario_source",
+        "scenario",
+        "ald_sector",
+        "green",
+        "year"
+      )
+    ) |>
+    dplyr::mutate(y = .data$plan_buildout / .data$scen_buildout) |>
+    dplyr::filter(.data$green) |>
+    dplyr::select(
+      -"plan_buildout",
+      -"scen_buildout",
+      -"green"
+    ) |>
+    dplyr::filter(!is.na(.data$plan_tech_share)) |>
+    dplyr::mutate(y = pmax(.data$y, 0, na.rm = TRUE)) |>
+    dplyr::mutate(asset_class = "Corporate Bonds")
+
+  dplyr::bind_rows(equity_data, bonds_data)
+}

R/prep_exposure_stats.R

@@ -0,0 +1,112 @@
+prep_exposure_stats <- function(
+  audit_file,
+  investor_name,
+  portfolio_name,
+  pacta_sectors,
+  currency_exchange_value
+) {
+  pacta_asset_classes <- c(
+    "Bonds",
+    "Equity"
+  )
+
+  audit_table <- pacta.portfolio.report:::prep_audit_table(
+    audit_file,
+    investor_name = investor_name,
+    portfolio_name = portfolio_name,
+    currency_exchange_value = currency_exchange_value
+  )
+
+  exposure_stats <- audit_file |>
+    dplyr::filter(
+      .data$investor_name == .env$investor_name &
+        .data$portfolio_name == .env$portfolio_name
+    ) |>
+    dplyr::filter(.data$asset_type %in% pacta_asset_classes) |>
+    dplyr::filter(.data$valid_input == TRUE) |>
+    dplyr::mutate(
+      dplyr::across(
+        c(
+          "bics_sector",
+          "financial_sector"
+        ),
+        as.character
+      )
+    ) |>
+    dplyr::mutate(
+      sector =
+        dplyr::if_else(!.data$financial_sector %in% .env$pacta_sectors,
+          "Other",
+          .data$financial_sector
+        )
+    ) |>
+    dplyr::summarise(
+      value = sum(.data$value_usd, na.rm = TRUE) / .env$currency_exchange_value,
+      .by = c("asset_type", "sector")
+    ) |>
+    dplyr::mutate(
+      perc_asset_val_sector = .data$value / sum(.data$value, na.rm = TRUE),
+      .by = c("asset_type")
+    ) |>
+    dplyr::inner_join(
+      audit_table,
+      by = dplyr::join_by("asset_type" == "asset_type_analysis")
+    ) |>
+    dplyr::select(
+      "asset_type",
+      "percentage_value_invested",
+      "sector",
+      "perc_asset_val_sector"
+    )
+
+  asset_classes_in_portfolio <- intersect(
+    pacta_asset_classes,
+    unique(exposure_stats$asset_type)
+  )
+
+  all_stats_with_zero_sector_exposure <- expand.grid(
+    asset_type = asset_classes_in_portfolio,
+    sector = pacta_sectors,
+    val_sector = 0
+  ) |>
+    dplyr::inner_join(
+      dplyr::distinct(
+        dplyr::select(
+          exposure_stats,
+          c("asset_type", "percentage_value_invested")
+        )
+      ),
+      by = dplyr::join_by("asset_type" == "asset_type")
+    )
+
+  exposure_stats_all <- all_stats_with_zero_sector_exposure |>
+    dplyr::left_join(
+      exposure_stats,
+      by = dplyr::join_by(
+        "asset_type" == "asset_type",
+        "sector" == "sector",
+        "percentage_value_invested" == "percentage_value_invested"
+      )
+    ) |>
+    dplyr::mutate(
+      perc_asset_val_sector = dplyr::if_else(
+        is.na(.data$perc_asset_val_sector),
+        .data$val_sector,
+        .data$perc_asset_val_sector
+      )
+    ) |>
+    dplyr::mutate(
+      asset_type = dplyr::case_when(
+        .data$asset_type == "Bonds" ~ "Corporate Bonds",
+        .data$asset_type == "Equity" ~ "Listed Equity"
+      )
+    ) |>
+    dplyr::select(
+      "asset_type",
+      "percentage_value_invested",
+      "sector",
+      "perc_asset_val_sector"
+    )
+
+  exposure_stats_all
+}