R/TIS.R
In TrigosTeam/spaSim: Spatial point data simulator for tissue images
Defines functions
TIS
Documented in
TIS
#' Tissue Image Simulator (TIS)
#'
#' @description Tissue Image Simulator (TIS) integrates the basic simulation
#' functions in spaSim, including simulating (mixed) background image,
#' clusters, immune rings, double immune rings and stripes. The patterns are
#' simulated on separate layers sequentially (e.g. immune rings are simulated
#' after/on top of background cells). And each layer is also plot
#' sequentially.
#'
#' Pattern properties (e.g. `properties_of_clusters`) contain the properties
#' of a pattern in the format of list where each element is one pattern. These
#' properties need to be manually defined. Details about the format of the
#' properties see the examples in \link{simulate_clusters}
#' \link{simulate_immune_rings} \link{simulate_double_rings}
#' \link{simulate_stripes}
#'
#' @param bg_sample (OPTIONAL) A data frame or `SpatialExperiment` class object
#' with locations of points representing background cells. Further cell types
#' will be simulated based on this background sample. The data.frame or the
#' `spatialCoords` of the SPE object should have colnames including
#' "Cell.X.Positions" and "Cell.Y.Positions". By default use the internal
#' \code{\link{bg1}} background image.
#' @param n_cells (OPTIONAL) Number of background cells to simulate. Only when
#' `bg_sample` is NULL.
#' @param width (OPTIONAL) Number The width of the image.
#' @param height (OPTIONAL) Number The height of the image.
#' @param bg_method (OPTIONAL) String specifying the distribution of the
#' background cells. Choose from "Hardcore" and "Even".
#' @param min_d (OPTIONAL) Number The minimum distance between two cells.
#' @param oversampling_rate (OPTIONAL) Numeric. The multiplier for oversampling.
#' Without oversampling, the simulation deletes cells that are within `min_d`
#' from each other, resulting in a less total number of cells than `n_cells`.
#' Default is 1.2 (this should be set based on `n_cells` and `min_d`; should
#' always be larger than 1).
#' @param jitter (OPTIONAL) Numeric. Use when `method` is "Even". The uniform
#' distribution parameter to generate the jitter distance for each cell from
#' the vertices of the hexagon.
#' @param names_of_bg_cells (OPTIONAL) Vector The cell types of the background
#' cells. If NULL, the background cells are of one type.
#' @param proportions_of_bg_cells (OPTIONAL) Vector The corresponding proportion
#' of each cell type in the background cells.
#' @param n_clusters (OPTIONAL) Number of cell clusters. If NULL, no clusters to
#' simulate.
#' @param properties_of_clusters (OPTIONAL) List of parameters to define the
#' clusters.
#' @param n_immune_rings (OPTIONAL) Number of immune rings. If NULL, no immune
#' rings to simulate.
#' @param properties_of_immune_rings (OPTIONAL) List of parameters to define the
#' immune rings.
#' @param n_double_rings (OPTIONAL) Number of double immune rings. If NULL, no
#' double rings to simulate.
#' @param properties_of_double_rings (OPTIONAL) List of parameters to define the
#' double immune rings.
#' @param n_stripe_type (OPTIONAL) Number of stripe (vessel) types. If NULL, no
#' stripes to simulate.
#' @param properties_of_stripes (OPTIONAL) List of parameters to define the
#' stripes.
#' @param image_name (OPTIONAL) String to name the output tissue image.
#' @param plot_image Boolean. Whether the simulated image is plotted.
#' @param plot_categories String Vector specifying the order of the cell
#' categories to be plotted. Default is NULL - the cell categories under the
#' "Cell.Type" column would be used for plotting.
#' @param plot_colours String Vector specifying the order of the colours that
#' correspond to the `plot_categories` arg. Default is NULL - the predefined
#' colour vector would be used for plotting.
#'
#' @return An spe object of the simulated image
#' @export
#' @examples
#' set.seed(610)
#' double_ring_image <- TIS(bg_sample=bg1, n_clusters=1,
#' properties_of_clusters=list(C1=list( name_of_cluster_cell="Tumour",
#' size=300, shape="Oval", centre_loc=data.frame("x"=500, "y"=500),
#' infiltration_types=c("Immune1", "Others"), infiltration_proportions=c(0.1, 0.05))),
#' plot_image=TRUE)
TIS <- function(bg_sample = NULL,
n_cells = NULL,
width = NULL,
height = NULL,
bg_method = NULL,
min_d = NULL,
oversampling_rate = 1.2,
jitter = 0.3,
names_of_bg_cells = NULL,
proportions_of_bg_cells = NULL,
n_clusters = NULL,
properties_of_clusters = NULL,
n_immune_rings = NULL,
properties_of_immune_rings = NULL,
n_double_rings = NULL,
properties_of_double_rings = NULL,
n_stripe_type = NULL,
properties_of_stripes = NULL,
image_name = NULL,
plot_image = FALSE,
plot_categories = NULL,
plot_colours = NULL) {
## CHECK
if (is.null(bg_sample)) {
if (is.null(oversampling_rate)) oversampling_rate <- 1.2
if (is.null(jitter)) jitter <- 0.3
bg_sample <- simulate_background_cells(n_cells, width, height, method = bg_method,
min_d = min_d,
oversampling_rate = oversampling_rate,
jitter = jitter)
X <- width
Y <- height
}
if (!is.null(bg_sample)){
if (!is.data.frame(bg_sample) & !methods::is(bg_sample, "SpatialExperiment")) {
stop("`bg_sample` should be either a data.frame or a SpatialExperiment object!")
}
}
if (!is.null(plot_colours) & !is.null(plot_categories)){
if (length(plot_categories) != length(plot_colours)){
stop("`plot_categories` and `plot_colours` should be of the same length!")}}
if (methods::is(bg_sample,"SpatialExperiment")) {
bg_sample <- get_colData(bg_sample)}
image <- bg_sample
X <- max(bg_sample$Cell.X.Position)
Y <- max(bg_sample$Cell.Y.Position)
# get background information
bg_size <- c(X, Y)
# simulate bg with mixing types of cells ####
if (!is.null(names_of_bg_cells)) {
# check
if (length(names_of_bg_cells) != length(proportions_of_bg_cells)){
stop("The length of `names_of_bg_cells` does not match the length of `proportions_of_bg_cells`!")
}
image <- simulate_mixing(
bg_sample = image,
idents = names_of_bg_cells,
props = proportions_of_bg_cells,
plot_image = FALSE
)
}
# simulate clusters ####
if (!is.null(n_clusters)) {
# check
if (!is.list(properties_of_clusters)){
stop("`properties_of_clusters` should be a list of lists where each list contains the properties of a cluster!")
}
if (length(properties_of_clusters) != n_clusters){
stop("`n_clusters` should be the same as the length of `properties_of_clusters`!")
}
for (i in seq_len(length(properties_of_clusters))){
if (!setequal(names(properties_of_clusters[[i]]),
c("name_of_cluster_cell", "size", "shape", "centre_loc",
"infiltration_types", "infiltration_proportions"))) {
stop("`properties_of_clusters` is a list of lists. Each list under `properties_of_clusters` should contain fields:
`name_of_cluster_cell`, `size`, `shape`, `centre_loc`, `infiltration_types`, `infiltration_proportions`.")}
if (length(properties_of_clusters[[i]]$infiltration_types) != length(properties_of_clusters[[i]]$infiltration_proportions)){
stop("The ", i, "th list of `properties_of_clusters` has different length of `infiltration_types` and `infiltration_proportions`.")
}
}
image <- simulate_clusters(
bg_sample = image,
n_clusters = n_clusters,
bg_type = "Others",
cluster_properties = properties_of_clusters,
plot_image = FALSE
)
}
# simulate_immune_rings ####
if (!is.null(n_immune_rings)) {
#check
if (!is.list(properties_of_immune_rings)){
stop("`properties_of_immune_rings` should be a list of lists where each list contains the properties of an immune ring!")
}
for (i in seq_len(length(properties_of_immune_rings))){
if (!setequal(names(properties_of_immune_rings[[i]]),
c("name_of_cluster_cell", "size", "shape", "centre_loc",
"infiltration_types", "infiltration_proportions",
"name_of_ring_cell", "immune_ring_width",
"immune_ring_infiltration_types", "immune_ring_infiltration_proportions"))) {
stop("`properties_of_immune_rings` is a list of lists. Each list under `properties_of_immune_rings` should contain fields:
`name_of_cluster_cell`, `size`, `shape`, `centre_loc`, `infiltration_types`, `infiltration_proportions`,
`name_of_ring_cell`, `immune_ring_width`, `immune_ring_infiltration_types`, `immune_ring_infiltration_proportions`.")
}
if (length(properties_of_immune_rings[[i]]$infiltration_types) !=
length(properties_of_immune_rings[[i]]$infiltration_proportions)){
stop("The ", i, "th list of `properties_of_immune_rings` has different length of `infiltration_types` and `infiltration_proportions`.")
}
if (length(properties_of_immune_rings[[i]]$immune_ring_infiltration_types) !=
length(properties_of_immune_rings[[i]]$immune_ring_infiltration_proportions)){
stop("The ", i, "th list of `properties_of_immune_rings` has different length of `immune_ring_infiltration_types` and `immune_ring_infiltration_proportions`.")
}
}
image <- simulate_immune_rings(
bg_sample = image,
n_ir = n_immune_rings,
bg_type = "Others",
ir_properties = properties_of_immune_rings,
plot_image = FALSE
)
}
# simulate_double_rings ####
if (!is.null(n_double_rings)) {
#check
if (!is.list(properties_of_double_rings)){
stop("`properties_of_double_rings` should be a list of lists where each list contains the properties of a double ring!")
}
for (i in seq_len(length(properties_of_double_rings))){
if (!setequal(names(properties_of_double_rings[[i]]),
c("name_of_cluster_cell", "size", "shape", "centre_loc",
"infiltration_types", "infiltration_proportions",
"name_of_ring_cell", "immune_ring_width",
"immune_ring_infiltration_types", "immune_ring_infiltration_proportions",
"name_of_double_ring_cell", "double_ring_width",
"double_ring_infiltration_types", "double_ring_infiltration_proportions"))) {
stop("`properties_of_double_rings` is a list of lists. Each list under `properties_of_double_rings` should contain fields:
`name_of_cluster_cell`, `size`, `shape`, `centre_loc`, `infiltration_types`, `infiltration_proportions`,
`name_of_ring_cell`, `immune_ring_width`, `immune_ring_infiltration_types`, `immune_ring_infiltration_proportions`,
`name_of_double_ring_cell`, `double_ring_width`, `double_ring_infiltration_types`, `double_ring_infiltration_proportions`.")
}
if (length(properties_of_double_rings[[i]]$infiltration_types) !=
length(properties_of_double_rings[[i]]$infiltration_proportions)){
stop("The ", i, "th list of `properties_of_double_rings` has different length of `infiltration_types` and `infiltration_proportions`.")
}
if (length(properties_of_double_rings[[i]]$immune_ring_infiltration_types) !=
length(properties_of_double_rings[[i]]$immune_ring_infiltration_proportions)){
stop("The ", i, "th list of `properties_of_double_rings` has different length of `immune_ring_infiltration_types` and `immune_ring_infiltration_proportions`.")
}
if (length(properties_of_double_rings[[i]]$double_ring_infiltration_types) !=
length(properties_of_double_rings[[i]]$double_ring_infiltration_proportions)){
stop("The ", i, "th list of `properties_of_double_rings` has different length of `double_ring_infiltration_types` and `double_ring_infiltration_proportions`.")
}
}
image <- simulate_double_rings(
bg_sample = image,
n_dr = n_double_rings,
bg_type = "Others",
dr_properties = properties_of_double_rings,
plot_image = FALSE
)
}
# simulate_stripes ####
if (!is.null(n_stripe_type)) {
#check
if (!is.list(properties_of_stripes)){
stop("`properties_of_stripes` should be a list of lists where each list contains the properties of a stripe type!")
}
if (length(properties_of_stripes) != n_stripe_type){
stop("`n_stripe_type` should be the same as the length of `properties_of_stripes`!")
}
for (i in seq_len(length(properties_of_stripes))){
if (!setequal(names(properties_of_stripes[[i]]),
c("number_of_stripes", "name_of_stripe_cell", "width_of_stripe",
"infiltration_types", "infiltration_proportions"))) {
stop("`properties_of_stripes` is be a list of lists. Each list under `properties_of_stripes` should contain fields:
`number_of_stripes`, `name_of_stripe_cell`, `width_of_stripe`, `infiltration_types`, `infiltration_proportions`.")
}
if (length(properties_of_stripes[[i]]$infiltration_types) !=
length(properties_of_stripes[[i]]$infiltration_proportions)){
stop("The ", i, "th list of `properties_of_stripes` has different length of `infiltration_types` and `infiltration_proportions`.")
}
}
image <- simulate_stripes(
bg_sample = image,
n_stripe_type = n_stripe_type,
stripe_properties = properties_of_stripes,
plot_image = FALSE
)
}
# format spe object
spe <- format_spe(image)
attr(spe, "name") <- image_name
if(plot_image){
if(is.null(plot_categories)) plot_categories <- unique(spe$Cell.Type)
if (is.null(plot_colours)){
plot_colours <- c("gray","darkgreen", "red", "darkblue", "brown", "purple", "lightblue",
"lightgreen", "yellow", "black", "pink")
}
phenos <- plot_categories
plot_cells(image, phenos, plot_colours[seq_len(length(phenos))], "Cell.Type")
}
return(spe)
}
TrigosTeam/spaSim documentation built on May 25, 2023, 4:20 p.m.
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Defines functions TIS
Documented in TIS
#' Tissue Image Simulator (TIS)
#'
#' @description Tissue Image Simulator (TIS) integrates the basic simulation
#' functions in spaSim, including simulating (mixed) background image,
#' clusters, immune rings, double immune rings and stripes. The patterns are
#' simulated on separate layers sequentially (e.g. immune rings are simulated
#' after/on top of background cells). And each layer is also plot
#' sequentially.
#'
#' Pattern properties (e.g. `properties_of_clusters`) contain the properties
#' of a pattern in the format of list where each element is one pattern. These
#' properties need to be manually defined. Details about the format of the
#' properties see the examples in \link{simulate_clusters}
#' \link{simulate_immune_rings} \link{simulate_double_rings}
#' \link{simulate_stripes}
#'
#' @param bg_sample (OPTIONAL) A data frame or `SpatialExperiment` class object
#' with locations of points representing background cells. Further cell types
#' will be simulated based on this background sample. The data.frame or the
#' `spatialCoords` of the SPE object should have colnames including
#' "Cell.X.Positions" and "Cell.Y.Positions". By default use the internal
#' \code{\link{bg1}} background image.
#' @param n_cells (OPTIONAL) Number of background cells to simulate. Only when
#' `bg_sample` is NULL.
#' @param width (OPTIONAL) Number The width of the image.
#' @param height (OPTIONAL) Number The height of the image.
#' @param bg_method (OPTIONAL) String specifying the distribution of the
#' background cells. Choose from "Hardcore" and "Even".
#' @param min_d (OPTIONAL) Number The minimum distance between two cells.
#' @param oversampling_rate (OPTIONAL) Numeric. The multiplier for oversampling.
#' Without oversampling, the simulation deletes cells that are within `min_d`
#' from each other, resulting in a less total number of cells than `n_cells`.
#' Default is 1.2 (this should be set based on `n_cells` and `min_d`; should
#' always be larger than 1).
#' @param jitter (OPTIONAL) Numeric. Use when `method` is "Even". The uniform
#' distribution parameter to generate the jitter distance for each cell from
#' the vertices of the hexagon.
#' @param names_of_bg_cells (OPTIONAL) Vector The cell types of the background
#' cells. If NULL, the background cells are of one type.
#' @param proportions_of_bg_cells (OPTIONAL) Vector The corresponding proportion
#' of each cell type in the background cells.
#' @param n_clusters (OPTIONAL) Number of cell clusters. If NULL, no clusters to
#' simulate.
#' @param properties_of_clusters (OPTIONAL) List of parameters to define the
#' clusters.
#' @param n_immune_rings (OPTIONAL) Number of immune rings. If NULL, no immune
#' rings to simulate.
#' @param properties_of_immune_rings (OPTIONAL) List of parameters to define the
#' immune rings.
#' @param n_double_rings (OPTIONAL) Number of double immune rings. If NULL, no
#' double rings to simulate.
#' @param properties_of_double_rings (OPTIONAL) List of parameters to define the
#' double immune rings.
#' @param n_stripe_type (OPTIONAL) Number of stripe (vessel) types. If NULL, no
#' stripes to simulate.
#' @param properties_of_stripes (OPTIONAL) List of parameters to define the
#' stripes.
#' @param image_name (OPTIONAL) String to name the output tissue image.
#' @param plot_image Boolean. Whether the simulated image is plotted.
#' @param plot_categories String Vector specifying the order of the cell
#' categories to be plotted. Default is NULL - the cell categories under the
#' "Cell.Type" column would be used for plotting.
#' @param plot_colours String Vector specifying the order of the colours that
#' correspond to the `plot_categories` arg. Default is NULL - the predefined
#' colour vector would be used for plotting.
#'
#' @return An spe object of the simulated image
#' @export
#' @examples
#' set.seed(610)
#' double_ring_image <- TIS(bg_sample=bg1, n_clusters=1,
#' properties_of_clusters=list(C1=list( name_of_cluster_cell="Tumour",
#' size=300, shape="Oval", centre_loc=data.frame("x"=500, "y"=500),
#' infiltration_types=c("Immune1", "Others"), infiltration_proportions=c(0.1, 0.05))),
#' plot_image=TRUE)
TIS <- function(bg_sample = NULL,
n_cells = NULL,
width = NULL,
height = NULL,
bg_method = NULL,
min_d = NULL,
oversampling_rate = 1.2,
jitter = 0.3,
names_of_bg_cells = NULL,
proportions_of_bg_cells = NULL,
n_clusters = NULL,
properties_of_clusters = NULL,
n_immune_rings = NULL,
properties_of_immune_rings = NULL,
n_double_rings = NULL,
properties_of_double_rings = NULL,
n_stripe_type = NULL,
properties_of_stripes = NULL,
image_name = NULL,
plot_image = FALSE,
plot_categories = NULL,
plot_colours = NULL) {
## CHECK
if (is.null(bg_sample)) {
if (is.null(oversampling_rate)) oversampling_rate <- 1.2
if (is.null(jitter)) jitter <- 0.3
bg_sample <- simulate_background_cells(n_cells, width, height, method = bg_method,
min_d = min_d,
oversampling_rate = oversampling_rate,
jitter = jitter)
X <- width
Y <- height
}
if (!is.null(bg_sample)){
if (!is.data.frame(bg_sample) & !methods::is(bg_sample, "SpatialExperiment")) {
stop("`bg_sample` should be either a data.frame or a SpatialExperiment object!")
}
}
if (!is.null(plot_colours) & !is.null(plot_categories)){
if (length(plot_categories) != length(plot_colours)){
stop("`plot_categories` and `plot_colours` should be of the same length!")}}
if (methods::is(bg_sample,"SpatialExperiment")) {
bg_sample <- get_colData(bg_sample)}
image <- bg_sample
X <- max(bg_sample$Cell.X.Position)
Y <- max(bg_sample$Cell.Y.Position)
# get background information
bg_size <- c(X, Y)
# simulate bg with mixing types of cells ####
if (!is.null(names_of_bg_cells)) {
# check
if (length(names_of_bg_cells) != length(proportions_of_bg_cells)){
stop("The length of `names_of_bg_cells` does not match the length of `proportions_of_bg_cells`!")
}
image <- simulate_mixing(
bg_sample = image,
idents = names_of_bg_cells,
props = proportions_of_bg_cells,
plot_image = FALSE
)
}
# simulate clusters ####
if (!is.null(n_clusters)) {
# check
if (!is.list(properties_of_clusters)){
stop("`properties_of_clusters` should be a list of lists where each list contains the properties of a cluster!")
}
if (length(properties_of_clusters) != n_clusters){
stop("`n_clusters` should be the same as the length of `properties_of_clusters`!")
}
for (i in seq_len(length(properties_of_clusters))){
if (!setequal(names(properties_of_clusters[[i]]),
c("name_of_cluster_cell", "size", "shape", "centre_loc",
"infiltration_types", "infiltration_proportions"))) {
stop("`properties_of_clusters` is a list of lists. Each list under `properties_of_clusters` should contain fields:
`name_of_cluster_cell`, `size`, `shape`, `centre_loc`, `infiltration_types`, `infiltration_proportions`.")}
if (length(properties_of_clusters[[i]]$infiltration_types) != length(properties_of_clusters[[i]]$infiltration_proportions)){
stop("The ", i, "th list of `properties_of_clusters` has different length of `infiltration_types` and `infiltration_proportions`.")
}
}
image <- simulate_clusters(
bg_sample = image,
n_clusters = n_clusters,
bg_type = "Others",
cluster_properties = properties_of_clusters,
plot_image = FALSE
)
}
# simulate_immune_rings ####
if (!is.null(n_immune_rings)) {
#check
if (!is.list(properties_of_immune_rings)){
stop("`properties_of_immune_rings` should be a list of lists where each list contains the properties of an immune ring!")
}
for (i in seq_len(length(properties_of_immune_rings))){
if (!setequal(names(properties_of_immune_rings[[i]]),
c("name_of_cluster_cell", "size", "shape", "centre_loc",
"infiltration_types", "infiltration_proportions",
"name_of_ring_cell", "immune_ring_width",
"immune_ring_infiltration_types", "immune_ring_infiltration_proportions"))) {
stop("`properties_of_immune_rings` is a list of lists. Each list under `properties_of_immune_rings` should contain fields:
`name_of_cluster_cell`, `size`, `shape`, `centre_loc`, `infiltration_types`, `infiltration_proportions`,
`name_of_ring_cell`, `immune_ring_width`, `immune_ring_infiltration_types`, `immune_ring_infiltration_proportions`.")
}
if (length(properties_of_immune_rings[[i]]$infiltration_types) !=
length(properties_of_immune_rings[[i]]$infiltration_proportions)){
stop("The ", i, "th list of `properties_of_immune_rings` has different length of `infiltration_types` and `infiltration_proportions`.")
}
if (length(properties_of_immune_rings[[i]]$immune_ring_infiltration_types) !=
length(properties_of_immune_rings[[i]]$immune_ring_infiltration_proportions)){
stop("The ", i, "th list of `properties_of_immune_rings` has different length of `immune_ring_infiltration_types` and `immune_ring_infiltration_proportions`.")
}
}
image <- simulate_immune_rings(
bg_sample = image,
n_ir = n_immune_rings,
bg_type = "Others",
ir_properties = properties_of_immune_rings,
plot_image = FALSE
)
}
# simulate_double_rings ####
if (!is.null(n_double_rings)) {
#check
if (!is.list(properties_of_double_rings)){
stop("`properties_of_double_rings` should be a list of lists where each list contains the properties of a double ring!")
}
for (i in seq_len(length(properties_of_double_rings))){
if (!setequal(names(properties_of_double_rings[[i]]),
c("name_of_cluster_cell", "size", "shape", "centre_loc",
"infiltration_types", "infiltration_proportions",
"name_of_ring_cell", "immune_ring_width",
"immune_ring_infiltration_types", "immune_ring_infiltration_proportions",
"name_of_double_ring_cell", "double_ring_width",
"double_ring_infiltration_types", "double_ring_infiltration_proportions"))) {
stop("`properties_of_double_rings` is a list of lists. Each list under `properties_of_double_rings` should contain fields:
`name_of_cluster_cell`, `size`, `shape`, `centre_loc`, `infiltration_types`, `infiltration_proportions`,
`name_of_ring_cell`, `immune_ring_width`, `immune_ring_infiltration_types`, `immune_ring_infiltration_proportions`,
`name_of_double_ring_cell`, `double_ring_width`, `double_ring_infiltration_types`, `double_ring_infiltration_proportions`.")
}
if (length(properties_of_double_rings[[i]]$infiltration_types) !=
length(properties_of_double_rings[[i]]$infiltration_proportions)){
stop("The ", i, "th list of `properties_of_double_rings` has different length of `infiltration_types` and `infiltration_proportions`.")
}
if (length(properties_of_double_rings[[i]]$immune_ring_infiltration_types) !=
length(properties_of_double_rings[[i]]$immune_ring_infiltration_proportions)){
stop("The ", i, "th list of `properties_of_double_rings` has different length of `immune_ring_infiltration_types` and `immune_ring_infiltration_proportions`.")
}
if (length(properties_of_double_rings[[i]]$double_ring_infiltration_types) !=
length(properties_of_double_rings[[i]]$double_ring_infiltration_proportions)){
stop("The ", i, "th list of `properties_of_double_rings` has different length of `double_ring_infiltration_types` and `double_ring_infiltration_proportions`.")
}
}
image <- simulate_double_rings(
bg_sample = image,
n_dr = n_double_rings,
bg_type = "Others",
dr_properties = properties_of_double_rings,
plot_image = FALSE
)
}
# simulate_stripes ####
if (!is.null(n_stripe_type)) {
#check
if (!is.list(properties_of_stripes)){
stop("`properties_of_stripes` should be a list of lists where each list contains the properties of a stripe type!")
}
if (length(properties_of_stripes) != n_stripe_type){
stop("`n_stripe_type` should be the same as the length of `properties_of_stripes`!")
}
for (i in seq_len(length(properties_of_stripes))){
if (!setequal(names(properties_of_stripes[[i]]),
c("number_of_stripes", "name_of_stripe_cell", "width_of_stripe",
"infiltration_types", "infiltration_proportions"))) {
stop("`properties_of_stripes` is be a list of lists. Each list under `properties_of_stripes` should contain fields:
`number_of_stripes`, `name_of_stripe_cell`, `width_of_stripe`, `infiltration_types`, `infiltration_proportions`.")
}
if (length(properties_of_stripes[[i]]$infiltration_types) !=
length(properties_of_stripes[[i]]$infiltration_proportions)){
stop("The ", i, "th list of `properties_of_stripes` has different length of `infiltration_types` and `infiltration_proportions`.")
}
}
image <- simulate_stripes(
bg_sample = image,
n_stripe_type = n_stripe_type,
stripe_properties = properties_of_stripes,
plot_image = FALSE
)
}
# format spe object
spe <- format_spe(image)
attr(spe, "name") <- image_name
if(plot_image){
if(is.null(plot_categories)) plot_categories <- unique(spe$Cell.Type)
if (is.null(plot_colours)){
plot_colours <- c("gray","darkgreen", "red", "darkblue", "brown", "purple", "lightblue",
"lightgreen", "yellow", "black", "pink")
}
phenos <- plot_categories
plot_cells(image, phenos, plot_colours[seq_len(length(phenos))], "Cell.Type")
}
return(spe)
}
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