Showcase

      ## the original dataset has three three-year scenarios, 
      ## only two years of two branches are used here 
        testdata <- sii_z_ex1_data[sii_z_ex1_data$id <= 7,]
        testdata <- testdata[testdata$time <= 2018,]

      ## printing SCR values and interdependency of 'id' and 'comparewithid'
        testdata[testdata$description == "SCR", ]
#>   time ratio description    value id comparewithid
#> 1 2016   230         SCR 23.00000  1            NA
#> 2 2017   233         SCR 23.14993  2             1
#> 3 2018   238         SCR 19.99461  3             2
#> 5 2017   231         SCR 19.60600  5             1
#> 6 2018   232         SCR 25.74336  6             5

## horizontalscaling to get round circles is depending on the dimensions of the canvas. 
## automated scaling to canvas size is on the to do list.
  horizontalscaling = .22 

ggplot2::ggplot() +
##  a plain vanilla plot of one SCR buildup, the 'current situation': 
  geom_sii_risksurface(data = testdata[testdata$id == 1, ], 
        mapping = ggplot2::aes(x = time, 
                               y = ratio,
                               ## x and y could for example be 
                               ## longitude and latitude 
                               ## in combination with plotted map
                               value = value, 
                               id = id, 
                               description = description, 
                               fill = description, ## optional
                               color = description  ## optional
                               ),
            ## all parameters are shown here, 
            ## the values behind the outcommented are the default values
              ## how and what
                ## structure = sii_structure_sf16_eng,
                ## plotdetails = NULL,
              ## grouping
                # levelmax = 99, 
                # aggregatesuffix = "other",
              ## scaling
                ## since the data in this geom is only a subset 
                ## of 'testdata' manual scaling is needed
                ## each geom_sii_risksurface and geom_sii_riskoutline
                ## call returns the calculated (or given) maximum in an
                ## outputmessage
                maxscrvalue =  25.7433642812936,
                scalingx = horizontalscaling, 
                # scalingy = 1,
              ## rotation and squared
                # rotationdegrees = NULL,
                # rotationdescription = NULL, 
                # squared = FALSE,
              ## cosmetic
                lwd = 0.25,
                # alpha = 1
        ) +
  
  ggplot2::theme_bw() +

## Combining several geom-calls might result in unexpected ordering of the legends
## It can help to plot the dataset which results in the most individual risks first.  
  ggplot2::scale_fill_manual(name = "risks", values = sii_z_ex1_fillcolors) +
  
  ggplot2::scale_color_manual(name = "risks", values = sii_z_ex1_edgecolors) +

## a second instance of geom_sii_risksurface, all data (1+2*2 id's) is used
## by using a plotdetails dataframe not all calculated circle segments are plotted
  geom_sii_risksurface(data = testdata, 
          mapping = aes(x = time,y = ratio,value = value,  id = id, 
                         description = description, 
                         fill = description, color = description
                       ),
  ## two plotdetailstables are used for this showcase: 
  ## this one indicates that only levels 1-3 are plotted in geom_sii_risksurface
  ## sii_z_ex1_plotdetails2 indicates only levels 4.xx and 5.xx are plotted
  ## this dataset has only 4.01, 4.02 levels present (market- and life subrisks )
      plotdetails = sii_z_ex1_plotdetails,
      scalingx = horizontalscaling, 
      lwd = 0.25,
      alpha = 1.0
  ) +

## this third instance of geom_sii_risksurface plots only the levels 4.01 and 4.02
## by using the other plotdetails dataframe.  
## A small alpha has the effect that these levels are less obtrusive, 
## giving a overview of SCR results, but still showing all information
## 'color is NA', in the options means it does only plot the surface of the polygons.
## (geom_polygon is the basis for the actual plotting),
  geom_sii_risksurface(data = testdata,
              mapping = aes(x = time, y = ratio, value = value,  id = id, 
                             description = description, 
                             fill = description #,
                             ## outcommenting here is not enough to prevent
                             ## outlines to be plotted ...
                             # color = description
                           ),
        plotdetails = sii_z_ex1_plotdetails2,
        scalingx = horizontalscaling, 
        alpha = 0.15,
      ## ... explicit no (edge)coloring is neccesary
        color = NA
        ) +
## Arrows are plotted to connect 'id' and 'comparewithid' combinations. 
## This helps in understanding the outlines of the following geom_sii_riskoutline call  
  geom_sii_riskconnection(data = testdata, 
                mapping = aes(x = time, y = ratio, id = id,
                ## for geom_sii_riskconnection comparewithid is a required aesthetic.
                ## (this is is not the case for geom_sii_riskoutline)
                              comparewithid = comparewithid
                              ), 
                arrow = ggplot2::arrow(angle = 10, type = "open" ), 
                alpha = 0.15
                ) +
  
## geoms_sii_riskoutline uses other columns in plotdetails than geoms_sii_risksurface
## for each line segment for each defined description or level plotting can be
## switched on or off.
## a risk-partition (apart from the full circle SCR) has four outline segments. 
## two radii and an inner and outer circle segment.
## sii_z_ex1_plotdetails defines only the outer circle segments ('outline2') to be plotted
## for levels 1, 4.01 and 4.02 AND for the indivual risks operational and cp-default.
## these individual risks are on level 2 and 3 but have no subrisks.
  geom_sii_riskoutline(data = testdata, 
          mapping = aes(x = time, y = ratio, value = value,  id = id, 
                         description = description, 
                         comparewithid = comparewithid,
                        ),
    ## only sii_z_ex1_plotdetails is used with the outline-geom.
      plotdetails = sii_z_ex1_plotdetails,
      scalingx = horizontalscaling, 
      color = "red",
      lwd = 0.25,
      alpha = 0.6,
) 
#> [1] "reminder: anonymous userdata is send to www.vanzanden.nl. This behaviour can be switched of by sii_setoption_statistics_participate(participate = FALSE). This reminder can be switched of with sii_setoption_statistics_remind(remind = FALSE)"
#> scaling is based on inputvalue (maxscrvalue) of 25.7433642812936
#> scaling is based on a max (level= 1) value of 25.7433642812936
#> scaling is based on a max (level= 1) value of 25.7433642812936
#> scaling is based on a max (level= 1) value of 25.7433642812936

## cleanup ============================================================== =====
rm(testdata) ; rm(horizontalscaling)
## ====================================================================== =====