cran release updated

Author: TomKellyGenetics

.Rbuildignore

@@ -11,6 +11,7 @@
 ^\.circleci$
 ^codecov\.yml$
 ^LICENSE\.md$
+^CITATION.cff$
 ^cran-comments\.md$
 ^.*\.pdf$
 ^.*\.png$

inst/CITATION

@@ -2,7 +2,7 @@ citHeader("To cite the leiden package in publications use:")
 
 citEntry(entry = "Manual",
          title        = "leiden: R implementation of the Leiden algorithm",
-         author       = personList(as.person("S. Thomas Kelly")),
+         author       = c(as.person("S. Thomas Kelly")),
          year         = "2023",
          note         = "R package version 0.4.3.1",
          url          = "https://github.com/TomKellyGenetics/leiden",

tests/testthat/test_multiplex.R

@@ -215,11 +215,7 @@ skip_if_no_python <- function() {
     testthat::skip("leidenalg not available for testing")
 }
 
-<<<<<<< HEAD
-
-=======
 set.seed(9000)
->>>>>>> 7d904bd98ec75ea8cc9bda7b50896458b3c26522
 test_that("run with CPMVertexPartition multiplexed", {
   skip_if_no_python()
   partition <- leiden(multiplex_graph,
@@ -231,19 +227,12 @@ test_that("run with CPMVertexPartition multiplexed", {
   expect_equal(partition,
                c(8, 2, 7, 5, 2, 5, 1, 2, 6, 5, 5, 2, 2, 5, 5, 5, 3, 6, 1, 2,
                  7, 10, 3, 1, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 4, 4, 2,
-<<<<<<< HEAD
-                 2, 2, 6, 4, 2, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 6, 7, 6, 4, 9, 4
-=======
                  2, 2, 6, 4, 2, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 7, 6, 4, 9, 4
->>>>>>> 7d904bd98ec75ea8cc9bda7b50896458b3c26522
                ))
   multiplex_graph
 })
 
-<<<<<<< HEAD
-=======
 set.seed(9000)
->>>>>>> 7d904bd98ec75ea8cc9bda7b50896458b3c26522
 test_that("run with ModularityVertexPartition multiplexed", {
   skip_if_no_python()
   partition <- leiden(multiplex_graph,
@@ -253,14 +242,6 @@ test_that("run with ModularityVertexPartition multiplexed", {
                       seed = 9001)
   expect_length(partition, length(V(multiplex_graph[[1]])))
   expect_equal(sort(unique(partition)), 1:6)
-<<<<<<< HEAD
-  expect_equal(partition,
-               c(3, 3, 1, 4, 3, 4, 4, 3, 1, 4, 4, 3, 3, 4, 4, 4, 1, 1, 2, 3,
-                 1, 3, 1, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 5, 5, 3, 3,
-                 3, 1, 5, 3, 1, 1, 1, 1, 1, 1, 1, 5, 5, 5, 1, 1, 1, 5, 6, 5))
-})
-
-=======
   expect_equal(table(partition),
                structure(c(`1` = 15L, `2` = 13L, `3` = 13L, `4` = 11L, `5` = 8L,
                            `6` = 1L), .Dim = 6L, .Dimnames = list(partition = c("1", "2",
@@ -272,7 +253,6 @@ test_that("run with ModularityVertexPartition multiplexed", {
 })
 
 set.seed(9000)
->>>>>>> 7d904bd98ec75ea8cc9bda7b50896458b3c26522
 test_that("run with ModularityVertexPartition multiplexed and max_comm_size", {
   skip_if_no_python()
   partition <- leiden(multiplex_graph,
@@ -284,16 +264,9 @@ test_that("run with ModularityVertexPartition multiplexed and max_comm_size", {
   expect_length(partition, length(V(multiplex_graph[[1]])))
   expect_equal(sort(unique(partition)), 1:10)
   expect_equal(max(table(partition)), 8)
-<<<<<<< HEAD
-  expect_equal(partition,
-               c(4, 4, 2, 3, 8, 3, 3, 4, 2, 3, 3, 8, 8, 3, 3, 3, 6, 6, 5, 8,
-                 2, 8, 6, 7, 2, 5, 5, 5, 7, 5, 7, 7, 5, 5, 7, 5, 4, 1, 1, 4, 4,
-                 4, 2, 1, 4, 6, 6, 6, 6, 9, 2, 6, 1, 1, 1, 2, 2, 7, 1, 10, 1))
-=======
   expect_equal(table(partition),
                structure(c(`1` = 8L, `2` = 8L, `3` = 8L, `4` = 8L, `5` = 8L,
                            `6` = 8L, `7` = 6L, `8` = 5L, `9` = 1L, `10` = 1L), .Dim = 10L, .Dimnames = list(
                              partition = c("1", "2", "3", "4", "5", "6", "7", "8", "9",
                                            "10")), class = "table"))
->>>>>>> 7d904bd98ec75ea8cc9bda7b50896458b3c26522
 })

tests/testthat/test_weighted.R

@@ -22,24 +22,6 @@ graph <- igraph::graph_from_adjacency_matrix(mat, weighted = NULL)
 test_that("run with unweighted dense matrix", {
   skip_if_no_python()
   set.seed(9000)
-<<<<<<< HEAD
-  mat <- round(matrix(runif(100, max = 1), 10, 10, ), 0)
-  mat
-  part_mat0 <- leiden::leiden(mat, seed = 9000)
-  expect_equal(part_mat0, c(1, 2, 2, 2, 1, 2, 2, 1, 1, 1))
-})
-
-test_that("run with unweighted sparse matrix", {
-  skip_if_no_python()
-  sp.mat <- as(mat, Class = "dgCMatrix")
-  part_sp.mat0 <- leiden::leiden(sp.mat, seed = 9000)
-  expect_equal(part_sp.mat0, c(1, 2, 2, 2, 1, 2, 2, 1, 1, 1))
-})
-
-
-test_that("run with unweighted graph object", {
-  skip_if_no_python()
-=======
   mat <- round(matrix(runif(100, max = 1), 10, 10), 0)
   mat
   part_mat0 <- leiden::leiden(mat, seed = 9000, resolution_parameter = 0.8)
@@ -65,26 +47,10 @@ set.seed(9000)
 test_that("run with unweighted graph object", {
   skip_if_no_python()
   set.seed(9000)
->>>>>>> 7d904bd98ec75ea8cc9bda7b50896458b3c26522
   graph <- igraph::graph_from_adjacency_matrix(mat, weighted = NULL)
   graph
   part_graph0 <- leiden::leiden(graph, seed = 9000)
   part_graph0
-<<<<<<< HEAD
-  expect_equal(part_graph0,  c(1, 2, 2, 2, 1, 2, 2, 1, 1, 1))
-})
-
-test_that("same output with different input class", {
-  skip_if_no_python()
-  part_mat0 <- leiden::leiden(mat, seed = 9000)
-  part_graph0 <- leiden::leiden(graph, seed = 9000)
-  expect_equivalent(part_mat0, c(1, 2, 2, 2, 1, 2, 2, 1, 1, 1))
-  expect_equivalent(part_graph0, c(1, 2, 2, 2, 1, 2, 2, 1, 1, 1))
-  expect_equivalent(part_mat0, part_graph0)
-  expect_equal(sum(diag(table(part_mat0, part_graph0))), length(part_mat0))
-  expect_equal(sum(diag(table(part_mat0, part_graph0))), nrow(mat))
-  expect_equal(sum(diag(table(part_mat0, part_graph0))), length(V(graph)))
-=======
   expect_equal(table(part_graph0), structure(c(`1` = 5L, `2` = 5L), .Dim = 2L, .Dimnames = list(
     part_graph0 = c("1", "2")), class = "table"))
   expect_length(object = unique(part_graph0[which(c(1, 2, 2, 2, 1, 2, 2, 1, 1, 1) == 1)]), n = 1)
@@ -104,7 +70,6 @@ test_that("same output with different input class", {
   expect_length(object = unique(part_graph0[which(c(1, 2, 2, 2, 1, 2, 2, 1, 1, 1) == 1)]), n = 1)
   expect_length(object = unique(part_graph0[which(c(1, 2, 2, 2, 1, 2, 2, 1, 1, 1) == 2)]), n = 1)
   expect_true(all(part_mat0 + part_graph0 == 3) ||  all(part_mat0 == part_graph0))
->>>>>>> 7d904bd98ec75ea8cc9bda7b50896458b3c26522
 })
 
 # # Test Seurat (development version)