Fix comment

.buildlibrary

@@ -1,4 +1,4 @@
-ValidationKey: '8096160'
+ValidationKey: '8116605'
 AutocreateReadme: yes
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'

CITATION.cff

@@ -2,8 +2,8 @@ cff-version: 1.2.0
 message: If you use this software, please cite it using the metadata from this file.
 type: software
 title: 'mrdrivers: Create GDP and Population Scenarios'
-version: 4.0.4
-date-released: '2024-11-13'
+version: 4.0.5
+date-released: '2024-11-14'
 abstract: Create GDP and population scenarios This package constructs the GDP and
   population scenarios used as drivers in both the REMIND and MAgPIE models.
 authors:

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: mrdrivers
 Type: Package
 Title: Create GDP and Population Scenarios
-Version: 4.0.4
+Version: 4.0.5
 Authors@R: c(person(given = "Johannes", 
                     family = "Koch", 
                     email = "[email protected]", 
@@ -44,6 +44,6 @@ Suggests:
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
 RoxygenNote: 7.3.2
-Date: 2024-11-13
+Date: 2024-11-14
 Config/testthat/edition: 3
 VignetteBuilder: knitr

R/toolHarmonizeGDP.R

@@ -262,8 +262,9 @@ toolSHAPEgrowth <- function(shapeGDPScenario, gdppcapSSP1, startFromYear) {
         stop("cannot create SHAPE GDP scenarios: unknown scenario")
       }
 
-      # for service (SDP_MC) and society (SDP_RC) additionally add a smoothing for 2020 and 2025 timesteps
-      # apply only 1/3 (2020-2024) and 2/3 (2025-2029) of the modification
+      # For service (SDP_MC) and society (SDP_RC) additionally add a smoothing for the first two 5-year timesteps
+      # (2025 and 2030 with current default startFromYear = 2025)
+      # Apply only 1/3 of the modification for first 5 years, and 2/3 of the modification for another 5 years      
       if (shapeGDPScenario %in% c("SDP_MC", "SDP_RC")) {
         if (yr >= startFromYear && yr < startFromYear + 5) {
           modificationFactor[, yr, ] <- 1 / 3. * (modificationFactor[, yr, ] - 1) + 1
@@ -274,7 +275,7 @@ toolSHAPEgrowth <- function(shapeGDPScenario, gdppcapSSP1, startFromYear) {
       growthrate[, yr, ] <- growthrate[, yr, ] * modificationFactor[, yr, ]
     }
 
-    # calculate next gdp/cap based on current value and (modified) growth rate
+    # Calculate next gdp/cap based on current value and (modified) growth rate
     gdppcap[, yr + as.integer(timestep[, yr, ]), ] <- gdppcap[, yr, ] * (1 + growthrate[, yr, ] / 100.)^timestep[, yr, ]
   }
 

README.md

@@ -1,6 +1,6 @@
 # Create GDP and Population Scenarios
 
-R package **mrdrivers**, version **4.0.4**
+R package **mrdrivers**, version **4.0.5**
 
 [![CRAN status](https://www.r-pkg.org/badges/version/mrdrivers)](https://cran.r-project.org/package=mrdrivers)  [![R build status](https://pik-piam.github.io/mrdrivers/workflows/check/badge.svg)](https://pik-piam.github.io/mrdrivers/actions) [![codecov](https://codecov.io/gh/mrdrivers/branch/master/graph/badge.svg)](https://app.codecov.io/gh/mrdrivers) [![r-universe](https://pik-piam.r-universe.dev/badges/mrdrivers)](https://pik-piam.r-universe.dev/builds)
 
@@ -100,7 +100,7 @@ In case of questions / problems please contact Johannes Koch <jokoch@pik-potsdam
 
 To cite package **mrdrivers** in publications use:
 
-Koch J, Soergel B, Leip D, Benke F, Dietrich J (2024). _mrdrivers: Create GDP and Population Scenarios_. R package version 4.0.4, <https://pik-piam.github.io/mrdrivershttps://github.com/pik-piam/mrdrivers>.
+Koch J, Soergel B, Leip D, Benke F, Dietrich J (2024). _mrdrivers: Create GDP and Population Scenarios_. R package version 4.0.5, <https://pik-piam.github.io/mrdrivershttps://github.com/pik-piam/mrdrivers>.
 
 A BibTeX entry for LaTeX users is
 
@@ -109,7 +109,7 @@ A BibTeX entry for LaTeX users is
   title = {mrdrivers: Create GDP and Population Scenarios},
   author = {Johannes Koch and Bjoern Soergel and Deborra Leip and Falk Benke and Jan Philipp Dietrich},
   year = {2024},
-  note = {R package version 4.0.4},
+  note = {R package version 4.0.5},
   url = {https://pik-piam.github.io/mrdrivers},
   url = {https://github.com/pik-piam/mrdrivers},
 }

vignettes/scenarios.Rmd

@@ -9,76 +9,61 @@ editor_options:
   chunk_output_type: console
 ---
 
-# Available Scenarios
+# Default scenarios
 
-The tool function `toolGetScenarioDefinition()` can be used to see what driver/scenario options are available.
+By default, the following scenarios are returned for all drivers:
 
-```{r, include = FALSE}
-knitr::opts_chunk$set(
-  collapse = TRUE,
-  comment = "#>"
-)
-```
+-   the SSPs, i.e. SSP1-5
+-   the SDPs, i.e. SDP, SDP_EI, SDP_MC and SDP_RC
+-   (SSP2EU - deprecated, but still returned as a placeholder. Identical to SSP2)
 
-```{r setup, echo=FALSE, message=FALSE}
-library(mrdrivers) # nolint
-library(magrittr) # nolint
-```
+The scenarios span from 1960 to 2150, with yearly data until 2030, and data every 5 years thereafter.
 
-```{r}
-toolGetScenarioDefinition() %>% print(n = 200)
-```
+## GDP per capita and GDP
 
-# User Defined Scenarios
+### SSPs
 
-The user can create custom scenarios by creating a tibble called "mrdivers_scenarios" in the global environment, and filling it with the desired scenario definitions. The structure of the "mrdivers_scenarios" object should be identical to that of the return object of `toolGetScenarioDefinition()`, and the scenario building blocks have to be available. For example, say the user wanted to create SSP scenarios, but without using the Missing Islands data-set. The following command executed in the global environment would make the "nomi" (no-missing islands) scenario available.
+Suggested overall reference for the scenario construction: Koch and Leimbach 2023 ([link](https://doi.org/10.1016/j.ecolecon.2023.107751)).
 
-```{r}
-mrdrivers_scenarios <- tibble::tribble( # nolint
-  ~driver,      ~scenario,      ~pastData,   ~futureData,  ~harmonization,
-  "GDPpc",      "nomi",         "WDI",       "SSPs",       "GDPpcSSPs",
-  "Population", "nomi",         "WDI",       "SSPs",       "PopSSPs",
-  "GDP",        "nomi",         "-",         "-",          "GDPpcWithPop"
-)
-```
+The SSP GDP per capita scenarios are constructed using:
 
+-   WDI data ([link](https://databank.worldbank.org/source/world-development-indicators)) from 1990 to 2022 (missing country data filled in with MI data ([link](https://doi.org/10.5281/zenodo.4421504)) and James data ([link](https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-10-12), specifically the WB_ID series) extended backwards until 1960 using growth rates from MI and James,
 
-# Default Scenarios
+-   growth rates from IMF GDP per capita projections ([link](https://www.imf.org/-/media/Files/Publications/WEO/WEO-Database/2022/WEOOct2022all.ashx)) until 2029,
 
-By default, the following scenarios are returned for all drivers:
+-   and SSP GDP per capita projections (SSP OECD projections [link](https://data.ece.iiasa.ac.at/ssp/#/about), release 3.0.1 (March 2024)) until 2100.
 
--   the SSPs, i.e. SSP1-5
--   the SDPs, i.e. SDP, SDP_EI, SDP_MC and SDP_RC
+The scenarios are extended until 2150 using a bezier curve method that assumes that the slope in 2100 is flattened by half by 2150. For countries lacking projection data, the last historical data point is used in all future years. For more details on the harmonization, see Koch and Leimbach 2023 ([link](https://doi.org/10.1016/j.ecolecon.2023.107751)).
 
-The scenarios span from 1960 to 2150, with yearly data until 2030, and data every 5 years thereafter.
+The SSP GDP scenarios are the product of the GDP per capita and population scenarios.
 
-# References
+### SDPs
 
-## GDP per capita and GDP scenarios
+Suggested overall reference for the SDP scenarios: Bjoern Soergel et al 2024 Environ. Res. Lett. 19 124009 ([link](http://dx.doi.org/10.1088/1748-9326/ad80af)).
 
-### SSPs
+The SDP GDP per capita scenarios are all based off of SSP1, with different harmonization functions for the different SDPs. 
 
-Suggested overall reference for the scenario construction: Koch and Leimbach 2023 ([link](https://doi.org/10.1016/j.ecolecon.2023.107751)).
+The SDP GDP scenarios are the product of the GDP per capita and population scenarios.
 
-The SSP GDP per capita scenarios are constructed using past WDI data ([link](https://databank.worldbank.org/source/world-development-indicators)) from 1990 to 2022 (missing country data filled in with MI data ([link](https://doi.org/10.5281/zenodo.4421504)) and James data ([link](https://pophealthmetrics.biomedcentral.com/articles/10.1186/1478-7954-10-12), specifically the WB_ID series), extended backwards until 1960 using growth rates from MI and James), growth rates from IMF GDP per capita projections ([link](https://www.imf.org/-/media/Files/Publications/WEO/WEO-Database/2022/WEOOct2022all.ashx)) until 2029, and SSP GDP per capita projections (SSP OECD projections [link](https://data.ece.iiasa.ac.at/ssp/#/about), release 3.0.1 (March 2024)) until 2100. The scenarios are extended until 2150 using a bezier curve method that assumes that the slope in 2100 is flattened by half by 2150. For countries lacking projection data, the last historical data point is used in all future years. For more details on the harmonization, see Koch and Leimbach 2023 ([link](https://doi.org/10.1016/j.ecolecon.2023.107751)). 
+## Population
 
-The SSP GDP scenarios are the product of the GDP per capita and population scenarios.
+### SSPs
 
-### SDPs
+The SSP population scenarios are constructed using:
 
-The SDPs are all based off of SSP1, with different harmonization functions for the different SDPs. (Reference needed.) The SDP GDP scenarios are the product of the GDP per capita and population scenarios.
+-   WDI data ([link](https://databank.worldbank.org/source/world-development-indicators)) from 1960 to 2022 (missing country data filled in with UN_PopDiv data ([link](https://population.un.org/wpp/), 2022 revision) and MI data ([link](https://doi.org/10.5281/zenodo.4421504))),
 
-## Population scenarios
+-   growth rates from the World Bank's Population and Projections database ([link](https://databank.worldbank.org/source/population-estimates-and-projections#)) until 2029, and
 
-### SSPs
+-   growth rates from from the SSP population projections (release 3.0.1 (March 2024) [link](https://data.ece.iiasa.ac.at/ssp/#/about) and [link](https://doi.org/10.5281/zenodo.10618931)), filled in with UN_PopDiv data ([link](https://population.un.org/wpp/), 2022 revision)) until 2100.
 
-The SSP population scenarios are constructed using past WDI data ([link](https://databank.worldbank.org/source/world-development-indicators)) from 1960 to 2022 (missing country data filled in with UN_PopDiv data ([link](https://population.un.org/wpp/), 2022 revision)) and MI data ([link](https://doi.org/10.5281/zenodo.4421504))), growth rates from the World Bank's Population and Projections database ([link](https://databank.worldbank.org/source/population-estimates-and-projections#)) until 2029, and growth rates from from the SSP population projections (release 3.0.1 (March 2024) [link](https://data.ece.iiasa.ac.at/ssp/#/about) and [link](https://doi.org/10.5281/zenodo.10618931)), filled in with UN_PopDiv data ([link](https://population.un.org/wpp/), 2022 revision)) until 2100. The scenarios are extended until 2150 using a bezier curve method that assumes that the slope in 2100 is flattened by half by 2150. For countries lacking projection data, the last historical data point is used in all future years. For more details on the harmonization, see Koch and Leimbach 2023 ([link](https://doi.org/10.1016/j.ecolecon.2023.107751)).
+The scenarios are extended until 2150 using a bezier curve method that assumes that the slope in 2100 is flattened by half by 2150. For countries lacking projection data, the last historical data point is used in all future years. For more details on the harmonization, see Koch and Leimbach 2023 ([link](https://doi.org/10.1016/j.ecolecon.2023.107751)).
 
 ### SDPs
 
 The SDP scenarios are all equal to the SSP1 scenario.
 
-## Labour scenarios
+## Labour
 
 ### SSPs
 
@@ -88,12 +73,47 @@ The SSPs labour scenarios are constructed using past WDI data ([link](https://da
 
 The SDP scenarios are all equal to the SSP1 scenario.
 
-## Urban population share scenarios
+## Urban population share
 
 ### SSPs
 
 The SSPs urban population share scenarios are constructed using past WDI data starting in 1960 ([link](https://databank.worldbank.org/source/world-development-indicators)), and SSP urban population share projections (2018 Release [link](https://data.ece.iiasa.ac.at/ssp/#/about)). The harmonization uses the past levels, and future growth rates.
 
 ### SDPs
 
-The SDP, SDP_EI, and SDP_MC  scenarios are all equal to the SSP1 scenario. The SDP_RC is equal to the SSP3 for OECD countries, and SSP2 for non-OECD countries.
+The SDP, SDP_EI, and SDP_MC scenarios are all equal to the SSP1 scenario. The SDP_RC is equal to the SSP3 for OECD countries, and SSP2 for non-OECD countries.
+
+
+
+# Available Scenarios
+
+The tool function `toolGetScenarioDefinition()` can be used to see what driver/scenario options are available.
+
+```{r, include = FALSE}
+knitr::opts_chunk$set(
+  collapse = TRUE,
+  comment = "#>"
+)
+```
+
+```{r setup, echo=FALSE, message=FALSE}
+library(mrdrivers) # nolint
+library(magrittr) # nolint
+```
+
+```{r}
+toolGetScenarioDefinition() %>% print(n = 200)
+```
+
+# User Defined Scenarios
+
+The user can create custom scenarios by creating a tibble called "mrdivers_scenarios" in the global environment, and filling it with the desired scenario definitions. The structure of the "mrdivers_scenarios" object should be identical to that of the return object of `toolGetScenarioDefinition()`, and the scenario building blocks have to be available. For example, say the user wanted to create SSP scenarios, but without using the Missing Islands data-set. The following command executed in the global environment would make the "nomi" (no-missing islands) scenario available.
+
+```{r}
+mrdrivers_scenarios <- tibble::tribble( # nolint
+  ~driver,      ~scenario,      ~pastData,   ~futureData,  ~harmonization,
+  "GDPpc",      "nomi",         "WDI",       "SSPs",       "GDPpcSSPs",
+  "Population", "nomi",         "WDI",       "SSPs",       "PopSSPs",
+  "GDP",        "nomi",         "-",         "-",          "GDPpcWithPop"
+)
+```