View source: R/calculate_tdm.R
calculate_tdm | R Documentation |
This function takes a typical PACTA output, and uses it to calculate the transition disruption metric.
calculate_tdm(
data,
t0,
delta_t1 = 5,
delta_t2 = 10,
additional_groups = NULL,
scenarios = "IPR FPS 2021"
)
data |
A data.frame (or tibble), with a format similar to the
|
t0 |
The start year, from which the TDM value should be calculated. This value should coincide with the earliest year in the PACTA results dataset. |
delta_t1 |
The number of years into the future for which there is production data. The default value is 5 years since this is often the limit of the forward-looking data. |
delta_t2 |
The number of years into the future against which you want to calculate disruption. |
additional_groups |
Character vector. The names of columns to group by, in addition to these ones (which are always used): technology, ald_sector |
scenarios |
Character vector. The names of scenarios for which TDM should be calculated. |
A tibble with the columns specified in the additional_groups
input
as well as tdm_technology_value
: the technology level transition
disruption metric, tdm_sector_value
: the sector level transition
disruption metric, tdm_portfolio_value
: the portfolio level transition
disruption metric, tdm_metric
: a flag that indicates what each
tdm_*_value
is being calculated against (e.g. "portfolio" or "scenario"),
as well as tdm_t0
, tdm_delta_t1
and tdm_delta_t2
: corresponding to
the input arguments.
library(tibble)
pacta_results <- tibble(
investor_name = rep("some_investor", 3),
portfolio_name = rep("some_portfolio", 3),
scenario = rep("IPR FPS 2021", 3),
allocation = rep("portfolio_weight", 3),
equity_market = rep("GlobalMarket", 3),
scenario_geography = rep("Global", 3),
ald_sector = rep("Power", 3),
technology = rep("RenewablesCap", 3),
year = c(2020, 2025, 2030),
plan_alloc_wt_tech_prod = rep(1, 3),
scen_alloc_wt_tech_prod = 1:3,
plan_carsten = rep(0.5, 3)
)
pacta_results
calculate_tdm(pacta_results, t0 = 2020)
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