| ... | ... |
@@ -7,9 +7,13 @@ |
| 7 | 7 |
#' @param window Should the window around the regions be 'square', 'convex' or 'concave'. |
| 8 | 8 |
#' @param window.length A tuning parameter for controlling the level of concavity |
| 9 | 9 |
#' when estimating concave windows. |
| 10 |
+#' @param whichParallel Should the function use parallization on the imageID or |
|
| 11 |
+#' the cellType. |
|
| 10 | 12 |
#' @param sigma A numeric variable used for scaling when filting inhomogeneous L-curves. |
| 11 | 13 |
#' @param lisaFunc Either "K" or "L" curve. |
| 12 | 14 |
#' @param minLambda Minimum value for density for scaling when fitting inhomogeneous L-curves. |
| 15 |
+#' @param fast A logical describing whether to use a fast approximation of the |
|
| 16 |
+#' inhomogeneous local L-curves. |
|
| 13 | 17 |
#' @param spatialCoords The columns which contain the x and y spatial coordinates. |
| 14 | 18 |
#' @param cellType The column which contains the cell types. |
| 15 | 19 |
#' @param imageID The column which contains image identifiers. |
| ... | ... |
@@ -55,9 +59,11 @@ lisa <- |
| 55 | 59 |
BPPARAM = BiocParallel::SerialParam(), |
| 56 | 60 |
window = "convex", |
| 57 | 61 |
window.length = NULL, |
| 62 |
+ whichParallel = "imageID", |
|
| 58 | 63 |
sigma = NULL, |
| 59 | 64 |
lisaFunc = "K", |
| 60 | 65 |
minLambda = 0.05, |
| 66 |
+ fast = TRUE, |
|
| 61 | 67 |
spatialCoords = c("x", "y"),
|
| 62 | 68 |
cellType = "cellType", |
| 63 | 69 |
imageID = "imageID") {
|
| ... | ... |
@@ -72,28 +78,52 @@ lisa <- |
| 72 | 78 |
Rs <- c(20, 50, 100) |
| 73 | 79 |
} |
| 74 | 80 |
|
| 75 |
- BPimage <- BPPARAM |
|
| 76 |
- |
|
| 77 |
- message("Generating local L-curves.")
|
|
| 78 |
- |
|
| 79 |
- curveList <- |
|
| 80 |
- BiocParallel::bplapply( |
|
| 81 |
- cellSummary, |
|
| 82 |
- inhomLocalK, |
|
| 83 |
- Rs = Rs, |
|
| 84 |
- sigma = sigma, |
|
| 85 |
- window = window, |
|
| 86 |
- window.length = window.length, |
|
| 87 |
- minLambda = minLambda, |
|
| 88 |
- lisaFunc = lisaFunc, |
|
| 89 |
- BPPARAM = BPimage |
|
| 90 |
- ) |
|
| 81 |
+ BPimage <- BPcellType <- BiocParallel::SerialParam() |
|
| 82 |
+ if (whichParallel == "imageID") {
|
|
| 83 |
+ BPimage <- BPPARAM |
|
| 84 |
+ } |
|
| 85 |
+ if (whichParallel == "cellType") {
|
|
| 86 |
+ BPcellType <- BPPARAM |
|
| 87 |
+ } |
|
| 88 |
+ |
|
| 89 |
+ if (!fast) {
|
|
| 90 |
+ message("Generating local L-curves. ")
|
|
| 91 |
+ if (identical(BPimage, BPcellType)) {
|
|
| 92 |
+ message("You might like to consider setting BPPARAM to run the calculations in parallel.")
|
|
| 93 |
+ } |
|
| 94 |
+ curveList <- |
|
| 95 |
+ BiocParallel::bplapply( |
|
| 96 |
+ cellSummary, |
|
| 97 |
+ generateCurves, |
|
| 98 |
+ Rs = Rs, |
|
| 99 |
+ window = window, |
|
| 100 |
+ window.length = window.length, |
|
| 101 |
+ BPcellType = BPcellType, |
|
| 102 |
+ BPPARAM = BPimage, |
|
| 103 |
+ sigma = sigma |
|
| 104 |
+ ) |
|
| 105 |
+ } |
|
| 106 |
+ |
|
| 107 |
+ if (fast) {
|
|
| 108 |
+ message("Generating local L-curves. If you run out of memory, try 'fast = FALSE'.")
|
|
| 109 |
+ |
|
| 110 |
+ curveList <- |
|
| 111 |
+ BiocParallel::bplapply( |
|
| 112 |
+ cellSummary, |
|
| 113 |
+ inhomLocalK, |
|
| 114 |
+ Rs = Rs, |
|
| 115 |
+ sigma = sigma, |
|
| 116 |
+ window = window, |
|
| 117 |
+ window.length = window.length, |
|
| 118 |
+ minLambda = minLambda, |
|
| 119 |
+ lisaFunc = lisaFunc, |
|
| 120 |
+ BPPARAM = BPimage |
|
| 121 |
+ ) |
|
| 122 |
+ } |
|
| 91 | 123 |
|
| 92 | 124 |
curvelist <- lapply(curveList, as.data.frame) |
| 93 | 125 |
curves <- as.matrix(dplyr::bind_rows(curvelist)) |
| 94 |
- rownames(curves) <- as.character( |
|
| 95 |
- unlist(lapply(cellSummary, function(x) x$cellID)) |
|
| 96 |
- ) |
|
| 126 |
+ rownames(curves) <- as.character(unlist(lapply(cellSummary, function(x) x$cellID))) |
|
| 97 | 127 |
|
| 98 | 128 |
curves[is.na(curves)] <- 0 |
| 99 | 129 |
return(curves) |
