Side-by-side plot of user selected variables across scenarios

[tonnrueter]

Function generates a facet wrap/grid plot that shows user defined variables side by side for comparison across different scenarios. Solves Improve cs2 climate plots issue. Plot examples can be found in here

[fbenke-pik]

Please add the man page for your newly created function as well.

[fbenke-pik]

Currently, using the variables option is not working as expected

data <- readxl::read_xlsx("~/Downloads/ngfs-magicc-data.xlsx")
vars <- c(
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|10.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|16.7th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|17.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|25.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|33.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|5.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|50.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|66.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|67.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|75.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|83.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|83.3th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|90.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|95.0th Percentile"
)

df <- quitte::as.quitte(data)
mip::plotPercentiles(df, variables = vars)

This gives the error

Warning: 'AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|10.0th Percentile' missing in available dataError in mip::plotPercentiles(df, variables = vars) : Provided variable is missing in data

[tonnrueter]

Currently, using the variables option is not working as expected

data <- readxl::read_xlsx("~/Downloads/ngfs-magicc-data.xlsx")
vars <- c(
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|10.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|16.7th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|17.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|25.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|33.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|5.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|50.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|66.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|67.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|75.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|83.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|83.3th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|90.0th Percentile",
  "AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|95.0th Percentile"
)

df <- quitte::as.quitte(data)
mip::plotPercentiles(df, variables = vars)

This gives the error

Warning: 'AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3|10.0th Percentile' missing in available dataError in mip::plotPercentiles(df, variables = vars) : Provided variable is missing in data

Try calling plotPercentiles with AR6 climate diagnostics|Net Atmosphere to Land Flux|CO2|MAGICCv7.5.3, ie. the variable prefix without the Percentile suffix.

Also please note that the data as provided by Oliver cannot directly be fed into plotPercentiles. The following pre-processing steps are necessary:

data <- readxl::read_xlsx("~/Downloads/ngfs-magicc-data.xlsx", sheet = "ngfs-magicc-data") %>%
  mutate_at(vars(starts_with(c("1", "2"))), as.double) %>% 
  filter(Variable %in% vars) %>% 
  reshape2::melt(c("Model", "Scenario", "Region", "Variable", "Unit"), variable.name = "period") %>%
  as.quitte()

[fbenke-pik]

#84 (comment)

Ok, so please enhance the description of the variables parameter, so that it is clear what is expected (a list of variables without the percentile fragments)

[fbenke-pik]

Here you write "if available" (as in: optional), below you say "must be given" (as in: mandatory). Can you clarify?

[fbenke-pik]

" In the quitte data frame all percentiles must be given as individual variables ..."
Please add an example to avoid misunderstandings.

"Manipulate input data frame ....."
This should not be here, as it is code documentation, but not a specification of the input parameter and therefore nothing a user has to worry about, right?

[fbenke-pik]

Implementation looks great, thank you! Now, we have to wait for @orichters approval to be sure that the function works as intended by him.

[orichters]

Thanks a lot, I looked at the examples and they look really good, as I hoped for. We could now add that to the climate section of compareScenarios2 (conditional on data availability)? I did not check the code, but trust Falk's assessment here

[fbenke-pik]

We could now add that to the climate section of compareScenarios2 (conditional on data availability)?

I think this needs to be merged first? remindmodel/remind#1475
Anyways, as soon as you can give us a run that contains these variables, we can extend remind2.

I did not check the code, but trust Falk's assessment here

The code is fine, but some decisions concerning the expected format of the input parameters are debatable (as in: there is no right or wrong given the data we have right now). We probably have to revisit this point once we have a run with actual data.