dag_merge: Merge two non-intersecting 'causact_graph' objects

In causact: Fast, Easy, and Visual Bayesian Inference

Merge two non-intersecting causact_graph objects

Description

Generates a single causact_graph graph object that combines multiple graphs.

Usage

dag_merge(graph1, ...)

Arguments

graph1	A causact_graph objects to be merged with
...	As many causact_graph's as wish to be merged

Value

a merged graph object of class causact_graph. Useful for creating simple graphs and then merging them into a more complex structure.

Examples

# With `dag_merge()` we
# reset the node ID's and all other item ID's,
# bind together the rows of all given graphs, and
# add in nodes and edges later
# with other functions
# to connect the graph.
#
# THE GRAPHS TO BE MERGED MUST BE DISJOINT
# THERE CAN BE NO IDENTICAL NODES OR PLATES
# IN EACH GRAPH TO BE MERGED, AT THIS TIME


g1 = dag_create() %>%
 dag_node("Demand for A","dA",
           rhs = normal(15,4)) %>%
  dag_node("Supply for A","sA",
           rhs = uniform(0,100)) %>%
  dag_node("Profit for A","pA",
           rhs = min(sA,dA)) %>%
  dag_edge(from = c("dA","sA"),to = c("pA"))


g2 <- dag_create() %>%
  dag_node("Demand for B","dB",
           rhs = normal(20,8)) %>%
  dag_node("Supply for B","sB",
           rhs = uniform(0,100)) %>%
  dag_node("Profit for B","pB",
           rhs = min(sB,dB)) %>%
  dag_edge(from = c("dB","sB"),to = c("pB"))

g1 %>% dag_merge(g2) %>%
  dag_node("Total Profit", "TP",
           rhs = sum(pA,pB)) %>%
  dag_edge(from=c("pA","pB"), to=c("TP")) %>%
  dag_render()

causact documentation built on April 12, 2025, 1:40 a.m.