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Step By Step Full Example for gcamreport v7.0*

Source: vignettes/Step_By_Step_Full_Example_v7-0.Rmd
Step_By_Step_Full_Example_v7-0.Rmd

ATTENTION: this tutorial is compatible with gcamreport v7.0*, i.e, with gcamreport v7.0.0 and gcamreport v7.0.1 releases. For other releases, please check in the Tutorials drop-down menu in the main bar.

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In this tutorial, we will 1) generate a dataset from a provided GCAM7.0 database and launch the associated user interface, 2) generate a dataset from a provided project and launch the corresponding user interface, and 3) launch the user interface from a provided standardized dataset. To know more about the gcamreport package possibilities, look at these tutorials: dataset generation tutorial and user interface tutorial.

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Example 1: step-by-step standardized dataset generation from a provided database

  1. Follow the installation guide either with R or Docker.

  2. Download the example GCAM7.0 database, store it inside gcamreport/examples, and unpack it. Make sure that the database is directly located in gcamreport/examples/database_basexdb_ref and an intermediate folder has not appeared.

  3. Load the gcamreport library. If you are using Rstudio or Docker, run

devtools::load_all()

and if you are using R, run

  1. Generate the standardized dataset:
## -- store the database path, name, and scenarios in a variable.
dbpath <- "examples"
dbname <- "database_basexdb_ref"
scen <- "Reference"

## -- choose a project name
prjname <- "example1.dat"

## -- generate the reporting dataset until 2050 for EU-12 and EU-15 for all the 
## -- Agricultural variables, save the output in .RData, .csv and .xlsx format, 
## -- and lunch the user interface
generate_report(db_path = dbpath, db_name = dbname, scenarios = scen, 
                prj_name = prjname, final_year = 2050, 
                desired_regions = c('EU-12', 'EU-15'), 
                desired_variables = c('Agricultural*'), 
                save_output = TRUE, launch_ui = TRUE)

In case you experience some trouble, check this troubleshooting section.

  1. Once the project has been generated and the standardized dataset created, the user interface will prompt. If you are using Rstudio, it will automatically open. For a better experience, click the open in browser button. If you are using Docker, either type http://localhost:4000 in the browser or go to Docker Desktop and click the last started port.

UI error

Note: Remember that the user interface can only be launched through the full R installation or the Docker installation.

  1. Check the generated dataset: look in the examples folder and you should see two files named example1_standardized.csv and example1_standardized.xlsx containing the standardized dataset.

  2. Note that a file called database_basexdb_ref_example1.dat has appeared in the examples folder. This is the generated project file from the provided database. If you want to rebuild the standardized dataset or launch the user interface, you can use this file directly and avoid rebuilding the project. If you want to proceed as mentioned, you can follow Example 2.

  3. Note that a file named example1_standardized.RData has appeared in the examples folder. This is the report file generated from the provided database. If you want to launch the user interface in the future, you can use this file directly and avoid creating or loading the project again. If you want to proceed as mentioned, you can follow Example 3.

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Example 2: step-by-step standardized dataset generation from a provided project

  1. Follow the installation guide either with R or Docker

  2. In this example we will use an example rgcam project stored in examples called example2.dat

  3. Load the gcamreport library. If you are using Rstudio or Docker, run

devtools::load_all()

and if you are using R, run

  1. Generate the standardized dataset:
## -- store the project path and name in a variable.
prjname <- "examples/example2.dat"

## -- generate the reporting dataset until 2050 for EU-12 and EU-15 for all the 
## -- Agricultural variables, save the output in .RData, .csv and .xlsx format, 
## -- and lunch the user interface
generate_report(prj_name = prjname, final_year = 2050, 
                desired_regions = c('EU-12', 'EU-15'),
                desired_variables = c('Agricultural*'), 
                save_output = TRUE, launch_ui = TRUE)

In case you experience some trouble, check this troubleshooting section.

  1. Once the project has been generated and the standardized dataset created, the user interface will prompt. If you are using Rstudio, it will automatically open. For a better experience, click the open in browser button. If you are using Docker, either type http://localhost:4000 in the browser or go to Docker Desktop and click the last started port.

UI error

Note: Remember that the user interface can only be launched through the full R installation or the Docker installation.

  1. Check the generated dataset: look in the examples folder and you should see two files named example2_standardized.csv and example2_standardized.xlsx containing the standardized dataset.

  2. Note that a file called example2_standardized.RData has appeared in the examples folder. This is the report file generated from the provided database. If you want to launch the user interface in the future, you can use this file directly and avoid creating or loading the project again. If you want to proceed as mentioned, you can follow Example 3.

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Example 3: step-by-step user interface launching from a provided standardized dataset

Note: Remember that the user interface can only be launched through the full R installation or the Docker installation.

  1. Follow the installation guide either with the R full installation or the Docker installation.

  2. In this example we will use a standardized example dataset stored in examples called example3.RData.

  3. Load the gcamreport library:

devtools::load_all()
  1. Launch the user interface for the standardized dataset:
## -- load gcamreport library.
devtools::load_all() # if using Rstudio or Docker
library(gcamreport) # if using R

## -- store the project path and name in a variable.
datapath <- "examples/example3.RData"

## -- launch the user interface
launch_gcamreport_ui(data_path = datapath)

In case you experience some trouble, check this troubleshooting section.

  1. Once the project has been generated and the standardized dataset created, the user interface will prompt. If you are using Rstudio, it will automatically open. For a better experience, click the open in browser button. If you are using Docker, either type http://localhost:4000 in the browser or go to Docker Desktop and click the last started port.

UI error

  1. If you just ran Example 1 or Example 2, you should have a variable called report in the environment. You can also use it to launch the user interface:
## -- load gcamreport library.
devtools::load_all() # if using Rstudio or Docker
library(gcamreport) # if using R

## -- store the database path, name, and scenarios in a variable.
dataname <- "report"

## -- launch the user interface
launch_gcamreport_ui(data = dataname)