# File tests/testthat/test-term-mm.R in package ergm, part of the # Statnet suite of packages for network analysis, https://statnet.org . # # This software is distributed under the GPL-3 license. It is free, # open source, and has the attribution requirements (GPL Section 7) at # https://statnet.org/attribution . # # Copyright 2003-2024 Statnet Commons ################################################################################ # a bipartite nw set.seed(143) b1 <- floor(runif(60, 1,100)) b2 <- floor(runif(60, 101, 130)) exbip.el <- cbind(b1,b2) bipnw <- as.network(exbip.el, matrix.type="edgelist", bipartite=100, directed=FALSE) bipnw %v% "Letter" <- letters[1:3] bipnw %v% "Cost" <- c(3,2,1) # another bipartite nw with more ties and 2 attributes set.seed(258) b1 <- floor(runif(150, 1,200)) b2 <- floor(runif(150, 201, 400)) exbip.el <- cbind(b1,b2) bipnw2 <- as.network(exbip.el, matrix.type="edgelist", bipartite=100, directed=FALSE) bipnw2 %v% "Letter" <- letters[1:2] color <- rbinom(400, 1, .4) color[color ==1] <- "Purple" color[color ==0] <- "Gold" bipnw2 %v% "Color" <- color # a directed nw data(sampson) set.seed(42) set.edge.attribute(samplike, "YearsTrusted", rbinom(88, 4, .5)) set.seed(296) set.vertex.attribute(samplike, "YearsServed", rbinom(18, 10, .5)) samplike %v% "Trinity" <- c("F", "S", "H") # an undirected nw data(faux.mesa.high) fmh <- faux.mesa.high set.seed(7) set.edge.attribute(fmh, "GradeMet", rbinom(203, 6, .5)) # a small undirected nw w/ lots o' triangles set.seed(20) t<-trunc(runif(160, 1, 20)) set.seed(21) h<-trunc(runif(160, 1, 20)) el <- cbind(t,h) bad <- which(el[,2]==el[,1]) el[bad,2] = el[bad,2]+1 unnw <- network(el, directed=FALSE) unnw %v% "Pet" <- c("dog", "cat") test_that("Undirected mm() summary", { s.a <- summary(fmh ~ mm("Grade")) expect_equal(s.a, c(`mm[Grade=7,Grade=8]` = 0, `mm[Grade=8,Grade=8]` = 33, `mm[Grade=7,Grade=9]` = 0, `mm[Grade=8,Grade=9]` = 2, `mm[Grade=9,Grade=9]` = 23, `mm[Grade=7,Grade=10]` = 1, `mm[Grade=8,Grade=10]` = 4, `mm[Grade=9,Grade=10]` = 7, `mm[Grade=10,Grade=10]` = 9, `mm[Grade=7,Grade=11]` = 1, `mm[Grade=8,Grade=11]` = 2, `mm[Grade=9,Grade=11]` = 6, `mm[Grade=10,Grade=11]` = 1, `mm[Grade=11,Grade=11]` = 17, `mm[Grade=7,Grade=12]` = 1, `mm[Grade=8,Grade=12]` = 1, `mm[Grade=9,Grade=12]` = 4, `mm[Grade=10,Grade=12]` = 5, `mm[Grade=11,Grade=12]` = 5, `mm[Grade=12,Grade=12]` = 6)) }) test_that("Undirected mm() summary with expression, levels, and levels2 selectors", { s.a <- summary(fmh ~ mm(~Grade >= 10, levels=-1, levels2=NULL)) expect_equal(s.a, c(`mm[Grade>=10=TRUE,Grade>=10=TRUE]` = 43)) }) test_that("Undirected mm() summary with expression, levels selector, no terms", { s.a <- summary(fmh ~ mm(~Grade >= 10, levels=-1)) expect_equal(s.a, numeric(0)) }) test_that("Directed mm() ERGM", { e.a <- ergm(samplike ~ mm("group", levels2=TRUE)) expect_equal(coef(e.a), c(0.191055236762708, -3.29583686600359, -2.17475172140943, -2.5649493574587, 1.6094379124341, -3.29583686600359, -1.49165487677766, -1.09861228866811, 0.916290731874155), ignore_attr=TRUE) }) test_that("Bipartite mm() summary", { s.ab <- summary(bipnw ~ mm("Letter")) expect_equal(s.ab, c(`mm[Letter=b,Letter=a]` = 8, `mm[Letter=c,Letter=a]` = 8, `mm[Letter=a,Letter=b]` = 7, `mm[Letter=b,Letter=b]` = 7, `mm[Letter=c,Letter=b]` = 5, `mm[Letter=a,Letter=c]` = 4, `mm[Letter=b,Letter=c]` = 6, `mm[Letter=c,Letter=c]` = 6)) }) test_that("Bipartite mm() ERGM with level2 filter", { e.ab <- ergm(bipnw ~ mm("Letter", levels2=-(2:6))) expect_equal(coef(e.ab), c(-3.49650756126405, -4.43081679479004, -3.98898404450688, -3.98898404450688), ignore_attr=TRUE) }) fmh.mm.Race <- c(`mm[Race=Black,Race=Black]` = 0, `mm[Race=Black,Race=Hisp]` = 8, `mm[Race=Hisp,Race=Hisp]` = 53, `mm[Race=Black,Race=NatAm]` = 13, `mm[Race=Hisp,Race=NatAm]` = 41, `mm[Race=NatAm,Race=NatAm]` = 46, `mm[Race=Black,Race=Other]` = 0, `mm[Race=Hisp,Race=Other]` = 1, `mm[Race=NatAm,Race=Other]` = 0, `mm[Race=Other,Race=Other]` = 0, `mm[Race=Black,Race=White]` = 5, `mm[Race=Hisp,Race=White]` = 22, `mm[Race=NatAm,Race=White]` = 10, `mm[Race=Other,Race=White]` = 0, `mm[Race=White,Race=White]` = 4) test_that("Undirected mm() summary with level2 filter", { s.ab2 <- summary(fmh ~ mm("Race", levels2=-1)) expect_equal(s.ab2, fmh.mm.Race[-1], ignore_attr=TRUE) }) test_that("Undirected mm() summary with level2 filter by logical matrix", { M <- matrix(TRUE, 5, 5) M[1,1] <- M[3,2] <- M[2,3] <- FALSE s.ab2 <- summary(fmh ~ mm("Race", levels2=M)) expect_equal(s.ab2, fmh.mm.Race[M[upper.tri(M, TRUE)]], ignore_attr=TRUE) }) test_that("Undirected mm() summary with level2 filter by numeric matrix", { M <- cbind(2,3) s.ab2 <- summary(fmh ~ mm("Race", levels2=M)) expect_equal(s.ab2, fmh.mm.Race[5], ignore_attr=TRUE) }) test_that("Directed mm() ERGM with level2 filter", { e.ab2 <- ergm(samplike ~ mm("Trinity", levels2=-(3:9))) expect_equal(coef(e.ab2), c(-1.01160091056776, -0.693147180549145), ignore_attr=TRUE) }) test_that("Directed mm() ERGM with level2 filter", { e.ab2 <- ergm(samplike ~ mm("Trinity", levels2=-(3:9))) expect_equal(coef(e.ab2), c(-1.01160091056776, -0.693147180549145), ignore_attr=TRUE) }) samp.mm.Trinity <- c(`mm[Trinity=F,Trinity=F]` = 8, `mm[Trinity=H,Trinity=F]` = 12, `mm[Trinity=S,Trinity=F]` = 12, `mm[Trinity=F,Trinity=H]` = 8, `mm[Trinity=H,Trinity=H]` = 5, `mm[Trinity=S,Trinity=H]` = 9, `mm[Trinity=F,Trinity=S]` = 13, `mm[Trinity=H,Trinity=S]` = 12, `mm[Trinity=S,Trinity=S]` = 9) test_that("Directed mm() summary with level2 matrix filter", { M <- matrix(FALSE, 3, 3) M[1,2] <- M[1,3] <- TRUE s.ab2 <- summary(samplike ~ mm("Trinity", levels2=M)) expect_equal(s.ab2, samp.mm.Trinity[c(M)], ignore_attr=TRUE) }) test_that("Undirected mm() marginal summary", { s.a <- summary(fmh ~ mm(.~Grade)) expect_equal(s.a, c(`mm[.,Grade=8]` = 75, `mm[.,Grade=9]` = 65, `mm[.,Grade=10]` = 36, `mm[.,Grade=11]` = 49, `mm[.,Grade=12]` = 28)) }) test_that("Undirected mm() asymmetric two-sided summary", { s.a.tab <- as.matrix(fmh, matrix.type="edgelist") %>% rbind(.,.[,2:1,drop=FALSE]) %>% (function(x) data.frame(Race=factor(fmh%v%"Race")[x[,1]], Grade=factor(fmh%v%"Grade")[x[,2]])) %>% table() s.a <- summary(fmh ~ mm(Race~Grade, levels2=TRUE)) expect_equal(s.a, c(s.a.tab), ignore_attr=TRUE) }) test_that("Undirected mm() asymmetric two-sided summary and pipe operator on one side", { Grade <- fmh%v%"Grade" %>% factor() Race <- fmh%v%"Race" %>% replace(., . %in% c("Black","White","Other"), "BWO") %>% factor() s.a.tab <- as.matrix(fmh, matrix.type="edgelist") %>% rbind(.,.[,2:1,drop=FALSE]) %>% (function(x) data.frame(Grade=Grade[x[,2]], Race=Race[x[,1]])) %>% table() s.a <- summary(fmh ~ mm(Grade~(~Race) %>% COLLAPSE_SMALLEST(3,"BWO"), levels2=TRUE)) expect_equal(s.a, c(s.a.tab), ignore_attr=TRUE) }) test_that("Undirected mm() marginal summary with fixed levels set", { s.a <- summary(fmh ~ mm(.~Grade, levels=I(c(7,6,9,8)), levels2=TRUE)) expect_equal(s.a, c(153, 0, 65, 75), ignore_attr=TRUE) }) test_that("Undirected mm() summary with fixed levels set", { s.a <- summary(fmh ~ mm("Grade", levels=I(c(7,6,9,8)), levels2=TRUE)) expect_equal(s.a, c(`mm[Grade=7,Grade=7]` = 75, `mm[Grade=7,Grade=6]` = 0, `mm[Grade=6,Grade=6]` = 0, `mm[Grade=7,Grade=9]` = 0, `mm[Grade=6,Grade=9]` = 0, `mm[Grade=9,Grade=9]` = 23, `mm[Grade=7,Grade=8]` = 0, `mm[Grade=6,Grade=8]` = 0, `mm[Grade=9,Grade=8]` = 2, `mm[Grade=8,Grade=8]` = 33)) }) test_that("Undirected valued mm() sum summary", { s.a <- summary(fmh ~ mm("Grade"), response="GradeMet") expect_equal(s.a, c(`mm.sum[Grade=7,Grade=8]` = 0, `mm.sum[Grade=8,Grade=8]` = 96, `mm.sum[Grade=7,Grade=9]` = 0, `mm.sum[Grade=8,Grade=9]` = 6, `mm.sum[Grade=9,Grade=9]` = 75, `mm.sum[Grade=7,Grade=10]` = 3, `mm.sum[Grade=8,Grade=10]` = 15, `mm.sum[Grade=9,Grade=10]` = 21, `mm.sum[Grade=10,Grade=10]` = 24, `mm.sum[Grade=7,Grade=11]` = 3, `mm.sum[Grade=8,Grade=11]` = 6, `mm.sum[Grade=9,Grade=11]` = 19, `mm.sum[Grade=10,Grade=11]` = 4, `mm.sum[Grade=11,Grade=11]` = 54, `mm.sum[Grade=7,Grade=12]` = 2, `mm.sum[Grade=8,Grade=12]` = 5, `mm.sum[Grade=9,Grade=12]` = 11, `mm.sum[Grade=10,Grade=12]` = 17, `mm.sum[Grade=11,Grade=12]` = 18, `mm.sum[Grade=12,Grade=12]` = 16 )) }) test_that("Undirected valued mm() nonzero summary", { fmh %ergmlhs% "response" <- "GradeMet" s.a <- summary(fmh ~ mm("Grade", form="nonzero")) expect_equal(s.a, c(`mm.nonzero[Grade=7,Grade=8]` = 0, `mm.nonzero[Grade=8,Grade=8]` = 33, `mm.nonzero[Grade=7,Grade=9]` = 0, `mm.nonzero[Grade=8,Grade=9]` = 2, `mm.nonzero[Grade=9,Grade=9]` = 22, `mm.nonzero[Grade=7,Grade=10]` = 1, `mm.nonzero[Grade=8,Grade=10]` = 4, `mm.nonzero[Grade=9,Grade=10]` = 7, `mm.nonzero[Grade=10,Grade=10]` = 8, `mm.nonzero[Grade=7,Grade=11]` = 1, `mm.nonzero[Grade=8,Grade=11]` = 2, `mm.nonzero[Grade=9,Grade=11]` = 6, `mm.nonzero[Grade=10,Grade=11]` = 1, `mm.nonzero[Grade=11,Grade=11]` = 17, `mm.nonzero[Grade=7,Grade=12]` = 1, `mm.nonzero[Grade=8,Grade=12]` = 1, `mm.nonzero[Grade=9,Grade=12]` = 4, `mm.nonzero[Grade=10,Grade=12]` = 5, `mm.nonzero[Grade=11,Grade=12]` = 5, `mm.nonzero[Grade=12,Grade=12]` = 6)) }) test_that("Undirected mm() summary with just one unique attribute level and levels imposed exogenously", { nw2 <- network.initialize(2, directed = FALSE) nw2[1, 2] <- TRUE nw2 %v% "x" <- c("b", "b") s.a <- summary(nw2 ~ mm("x", levels = letters[1:3], levels2 = TRUE)) expect_equal(s.a, c(`mm[x=a,x=a]` = 0, `mm[x=a,x=b]` = 0, `mm[x=b,x=b]` = 1, `mm[x=a,x=c]` = 0, `mm[x=b,x=c]` = 0, `mm[x=c,x=c]` = 0)) })