[pre-commit.ci] auto fixes from pre-commit.com hooks

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omnideconv · May 6, 2024 · b256c32 · b256c32
1 parent c7f5d9d
commit b256c32
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Showing 4 changed files with 22 additions and 24 deletions.
diff --git a/R/basilisk.R b/R/basilisk.R
@@ -1,4 +1,3 @@
-
 # dependencies for sfaira and anndata0.7.6 (taken from zellkonverter package)
 SimBu_env <- basilisk::BasiliskEnvironment(
   envname = "SimBu_env_1_1_1",

diff --git a/R/census.R b/R/census.R
@@ -1,4 +1,3 @@
-
 #' Applies the Census count transformation on a count matrix
 #'
 #' needs a sparse matrix with cells in columns and genes in rows. You can find the detailed explaination here:

diff --git a/R/simulator.R b/R/simulator.R
@@ -74,7 +74,7 @@ simulate_sample <- function(data,
       if (n == 0) {
         n <- 1
       }
-      if(!is.na(seed)){
+      if (!is.na(seed)) {
         # fix seed for random selection of cells
         set.seed(seed)
       }
@@ -437,7 +437,6 @@ simulate_bulk <- function(data,
 
   # sample cells and generate pseudo-bulk profiles
   all_samples <- BiocParallel::bplapply(seq_along(simulation_vector_list), function(i) {
-
     simulation_vector <- simulation_vector_list[[i]]
     sample <- simulate_sample(
       data = data,
@@ -454,22 +453,24 @@ simulate_bulk <- function(data,
     return(sample)
   }, BPPARAM = BPPARAM)
 
-  bulk_counts <- Matrix::Matrix(vapply(
-    X = all_samples,
-    FUN = "[[",
-    ... = 1,
-    FUN.VALUE = double(dim(SummarizedExperiment::assays(data)[["counts"]])[1])
-  ),
-  sparse = TRUE
-  )
-  if ("tpm" %in% names(SummarizedExperiment::assays(data))) {
-    bulk_tpm <- Matrix::Matrix(vapply(
+  bulk_counts <- Matrix::Matrix(
+    vapply(
       X = all_samples,
       FUN = "[[",
-      ... = 2,
-      FUN.VALUE = double(dim(SummarizedExperiment::assays(data)[["tpm"]])[1])
+      ... = 1,
+      FUN.VALUE = double(dim(SummarizedExperiment::assays(data)[["counts"]])[1])
     ),
     sparse = TRUE
+  )
+  if ("tpm" %in% names(SummarizedExperiment::assays(data))) {
+    bulk_tpm <- Matrix::Matrix(
+      vapply(
+        X = all_samples,
+        FUN = "[[",
+        ... = 2,
+        FUN.VALUE = double(dim(SummarizedExperiment::assays(data)[["tpm"]])[1])
+      ),
+      sparse = TRUE
     )
     assays <- list(bulk_counts = bulk_counts, bulk_tpm = bulk_tpm)
   } else {

diff --git a/tests/testthat/test_simulator.R b/tests/testthat/test_simulator.R
@@ -48,15 +48,14 @@ test_that("test RNG", {
   seed <- 123
   sim1 <- SimBu::simulate_bulk(data = dataset, scenario = "even", scaling_factor = "NONE", balance_even_mirror_scenario = 0, nsamples = 10, ncells = 100, run_parallel = FALSE, seed = seed)
   sim2 <- SimBu::simulate_bulk(data = dataset, scenario = "even", scaling_factor = "NONE", balance_even_mirror_scenario = 0, nsamples = 10, ncells = 100, run_parallel = FALSE, seed = seed)
-  x1 <- Matrix::rowSums(assays(sim1$bulk)[['bulk_counts']])
-  x2 <- Matrix::rowSums(assays(sim2$bulk)[['bulk_counts']])
-  testthat::expect_equal(x1,x2)
-
-  # test that samples inside one simulation still are different
-  sample1 <- sim1$bulk[,1]
-  sample2 <- sim1$bulk[,2]
-  testthat::expect_false(all(assays(sample1)[['bulk_counts']] == assays(sample2)[['bulk_counts']]))
+  x1 <- Matrix::rowSums(assays(sim1$bulk)[["bulk_counts"]])
+  x2 <- Matrix::rowSums(assays(sim2$bulk)[["bulk_counts"]])
+  testthat::expect_equal(x1, x2)
 
+  # test that samples inside one simulation still are different
+  sample1 <- sim1$bulk[, 1]
+  sample2 <- sim1$bulk[, 2]
+  testthat::expect_false(all(assays(sample1)[["bulk_counts"]] == assays(sample2)[["bulk_counts"]]))
 })
 
 test_that("test different scaling factor calculations + mRNA bias removal from counts", {