### Demo with output data from the risk() and aggregate_risk() functions
# based on expert scores
# The examples can run for a longer time, thus they are in dontrun{}.
# Using default settings for the indicator-specific overall risk score (coloured value)
# and associated uncertainty score (black value) (i.e., combined across both types)
if (FALSE) {
p_radar <- plot_radar(
risk_scores = ex_output_risk_expert,
aggregated_scores = ex_output_aggregate_risk_expert
)
p_radar[[1]] # display radar chart for first indicator
# Show overall risk score based on direct effects only
p_radar_direct <- plot_radar(
risk_scores = ex_output_risk_expert,
aggregated_scores = ex_output_aggregate_risk_expert,
type = "direct"
)
p_radar_direct[[1]]
### Demo with combined expert-based and model-based pathways
combined_risk <- rbind(ex_output_risk_expert, ex_output_risk_model)
aggr_risk <- aggregate_risk(risk_results = combined_risk)
# Default settings (combined type and pathway)
p_radar_comb <- plot_radar(
risk_scores = combined_risk,
aggregated_scores = aggr_risk
)
p_radar_comb[[1]]
# Show overall risk score based on direct/indirect effects only for both
# pathways combined
p_radar_comb_dindi <- plot_radar(
risk_scores = ex_output_risk_expert,
aggregated_scores = ex_output_aggregate_risk_expert,
type = "direct_indirect"
)
p_radar_comb_dindi[[1]]
}
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