Distributional and climate impacts of low-carbon transition pathways for California's oil refining (repo)

Setting up

This repo relies on the R package targets to maintain the pipeline of the scripts and the reproducibility of the project. Install the package if you have not already done so:

install.packages("targets")

Load the package:

library(targets)

All of the functions for the pipeline are in the R/ folder. To open the _targets.R script (which is where the workflow is built and specified), run:

tar_edit()

Changing the file directory

IMPORTANT: Before running the pipeline, one thing needs to be changed -- the path to the calepa-cn folder. Look for the user target:

tar_target(name = user, "meas"),

And replace the name in the quotations above with a specified user.

Using the repo to recreate the analysis

Debugging the pipeline

In order to check the pipeline is engineered properly, run the following command:

tar_manifest(fields=command)

The output should look something like:

# A tibble: 90 × 2
   name          command                                                                                                             
   <chr>         <chr>                                                                                                               
 1 ei_crude      "5.698"                                                                                                             
 2 ei_diesel     "5.77"                                                                                                              
 3 ei_gasoline   "5.052"                                                                                                             
 4 ei_jet        "(5.67 + 5.355)/2"                                                                                                  
 5 clus          "c(\"North\", \"South\")"                                                                                           
 6 main_path     "\"/Volumes/GoogleDrive-103159311076289514198/.shortcut-targets-by-id/139aDqzs5T2c-DtdKyLw7S5iJ9rqveGaP/calepa-cn\""
 7 pred_years    "2020:2045"                                                                                                         
 8 ref_threshold "0.6"                                                                                                               
 9 drop_in_perc  "1"                                                                                                                 
10 ref_scens     "c(\"historic exports\", \"historic production\", \"low exports\")"                                                 
# … with 80 more rows
# ℹ Use `print(n = ...)` to see more rows

If there are any issues (missing targets, bugs, etc), you should receive an error message.

Running the pipeline

To build and run the pipeline (this will execute everything), run:

tar_make()

If you are running this for the first time, it should take a few minutes, but the outputs should look something like:

• start target ei_crude
• built target ei_crude [0.019 seconds]
• start target ei_diesel
• built target ei_diesel [0 seconds]
• start target ei_gasoline
• built target ei_gasoline [0 seconds]
• start target ei_jet
• built target ei_jet [0.001 seconds]
• start target clus
• built target clus [0 seconds]
• start target main_path
• built target main_path [0 seconds]
...

Assuming none of the targets change, the next time(s) you run tar_make(), targets will skip building targets that are already up-to-date.

Viewing and loading targets

If you are new to targets you might be confused that there are no objects in your environment. That's because the objects are stored locally in a folder called _targets (in your local repo).

But let's say you want to inspect a specific object, like dt_its. If you want to just view it in your console, you can enter:

tar_read(dt_its)

And that should print the data.table.

If you want to load the data.table into your environment, you can run the following instead:

tar_load(dt_its)

You'll notice the object is in your environment.

You can also view plots. Running the following line should either load the plot in your Plots window or open a new window with the plot:

tar_read(fig_demand)

Visualizing the pipeline

If you want to visualize the pipeline, run:

tar_visnetwork()

You'll notice the diagram is very small -- you can use your mouse to zoom in on the objects if you'd like. If you make changes to the targets/pipeline and run tar_visnetwork() before running tar_make, you can see the colors of the objects change.

Example of target changes and impacts on the pipeline

Want an example of what happens when a target is changed? Here's an easy one:

1. Find the target ei_crude in _targets.R:

tar_target(name = ei_crude, command = 5.698)

2. Change the command value to something else, say 10 for example:

tar_target(name = ei_crude, command = 10)

3. Save the script. Then run:

tar_visnetwork()

4. You'll see the diagram now looks different, with a few lines and points assigned a different color, representing "Outdated". These are the targets affected by the updated ei_crude. Run tar_make() to rerun the pipeline with the new ei_crude value:

tar_make()

In the outputs you'll see that the targets that are affected are being updated, while the ones that are unaffected are not being rebuilt.

If you run tar_visnetwork() everything should be up-to-date now in the diagram.

Remember to change the value of the target back to normal (by ctrl + z for example).