library(GrasslandAllocatr)
library(tidyverse)
library(RNetica)
library(ggplot2)
start_netica_with_license("../data/LicenseKey")
model_1 <- RNetica::ReadNetworks(paths = "../processed_data/grassland_bbn_learned_1.dne")
CompileNetwork(model_1)
ClearAllErrors()
model_2 <- RNetica::ReadNetworks(paths = "../processed_data/grassland_bbn_learned_2.dne")
CompileNetwork(model_2)
ClearAllErrors()
model_3 <- RNetica::ReadNetworks(paths = "../processed_data/grassland_bbn_learned_3.dne")
CompileNetwork(model_3)
ClearAllErrors()

Target (aka query) Nodes for sensitivity analysis:

  1. IndigSpp_transect_t1
  2. WeedCover_t1
  3. BareGround_t1
  4. WeedDiversity_t1
  5. GrasslandCondition_t1

Nodes whose effect on target nodes we are interested in:

sensitivity <- data_frame(model = list(model_1, model_2, model_3), names = c("model_1", "model_2", "model_3")) %>%
        dplyr::mutate(sensitivity_analysis = purrr::map(.x = model, .f = ~ analyse_sensitivity(network = .x, year = 1))) %>%
        unnest(sensitivity_analysis) %>%
        rename(model = names)

sensitivity %>%
        ggplot(., aes(x = nodelist_node_name, y = mutual_info, fill = model)) + 
        geom_col(position = "dodge") +
        facet_grid(~node_name) +
        theme_bw() +
        theme(axis.text.x=element_text(angle=90,hjust=1))


egouldo/GrasslandAllocatr documentation built on Oct. 19, 2022, 8:18 a.m.