knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
The CL-PFU database uses many sources of input data
spanning hundreds of data files.
The targets pipeline
in the PFUPipeline package creates
RUVY matrices for the
PSUT
framework
in matsindf format,
containing descriptions of energy conversion chains (ECCs)
in energy and exergy terms.
Those ECCs can be used as input data
to create many aggregated versions of the ECCs,
which are amenable to presentation and efficiency calculations.
Computational tools to aggregate and calculate efficiencies
are needed.
This package (PFUAggPipeline) creates another
targets computational pipeline,
one that aggregates and calculates efficiencies
from the results of PFUPipeline package.
The targets computational pipeline
provides helpful dependency management
so what is done stays done
during debugging.
You can install the development version of PFUAggPipeline from GitHub with:
# install.packages("devtools") devtools::install_github("EnergyEconomyDecoupling/PFUAggPipeline")
At the RStudio console, type
library(targets) # to load the targets package tar_visnetwork() # to see a directed acyclic graph of the calculations that will take place tar_make_future(workers = 2) # to execute the calculations (or `workers = 8`, if you have enough cores)
targets::tar_read(<<target>>) pulls the value of a target out of the targets cache.
(<<target>> should be an unquoted symbol such as Specified.)
targets::tar_destroy() invalidates the targets cache and forces reanalysis of everything.
Reanalyzing everything may take a while.
See the vignette entitled "Access PFU Database Products Via Pins".
For information about the targets package,
see the targets manual.
For documentation on the PFUAggPipeline package,
see https://EnergyEconomyDecoupling.github.io/PFUAggPipeline/.
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