#' Perform SpatialDE test
 #'
 #' Wraps the `run` function from the
 #' [SpatialDE](https://github.com/Teichlab/SpatialDE) Python package.
 #'
 #' @param x `matrix`-like object of normalized counts. E.g. resulting from
 #'          [regress_out()].
 #' @param coordinates `data.frame` with sample coordinates.
 #' Each row is a sample, the columns with coordinates must be named 'x' and 'y'.
 #' @param verbose `logical` controlling the display of the progress bar.
 #'

 #' @return A `data.frame` with DE results where each row is a gene and columns
 #'   contain relevant statistics.
 #'
 #'   The most important columns are:
 #'
 #'   * `g`: the name of the gene
 #'   * `pval`: the p-value for spatial differential expression
 #'   * `qval`: the q-value, indicating significance after correcting for
 #'   multiple testing
 #'   * `l`: A parameter indicating the distance scale a gene changes expression
 #'   over

 #'
 #' @examples

 #' ## Mock up a SpatialExperiment object wit 400 cells and 3 genes

 #' set.seed(42)

 #' mock <- mockSVG(size = 20, tot_genes = 3, de_genes = 1)
 #'

 #' stabilized <- stabilize(mock$counts)
 #' sample_info <- mock$coordinates
 #' sample_info$total_counts <- colSums(mock$counts)
 #' regressed <- regress_out(counts = stabilized, sample_info = sample_info)
 #'
 #' ## Run SpatialDE
 #' de_results <- run(regressed, coordinates = mock$coordinates)
 #'
 #' @references
 #' Svensson, V., Teichmann, S. & Stegle, O.
 #' SpatialDE: identification of spatially variable genes.
 #' Nat Methods 15, 343–346 (2018). \url{https://doi.org/10.1038/nmeth.4636}
 #'
 #' @export
 #' @importFrom checkmate assert_data_frame assert_names assert_matrix
 #' @importFrom checkmate assert_flag

 #' @importFrom basilisk basiliskStart basiliskRun

 run <- function(x, coordinates, verbose = FALSE) {
     assert_data_frame(coordinates, any.missing = FALSE)
     assert_names(colnames(coordinates), identical.to = c("x", "y"))
     assert_matrix(x, any.missing = FALSE)
     assert_flag(verbose)

     
     proc <- basiliskStart(spatialDE_env, testload="scipy.optimize")
     

     .importPyModule(proc, !verbose)

     .spatialDE_run(proc, x, coordinates)
     
     out <- basiliskRun(proc, function(store) {
         as.data.frame(store$de_results)
     }, persist=TRUE)
     

     out

 }
 
 #' @importFrom reticulate r_to_py

 #' @importFrom basilisk basiliskRun
 .spatialDE_run <- function(proc, x, coordinates) {
     basiliskRun(proc, function(x, coordinates, store) {
         spatialDE <- store$spatialDE
         
         X <- r_to_py(coordinates)
         ## Need to transpose counts for `spatialDE$run`
         res_py <- r_to_py(as.data.frame(t(x)))
         
         de_results <- spatialDE$run(X, res_py)
         
         store$de_results <- as.data.frame(de_results)
         
         invisible(NULL)
     }, x=x, coordinates=coordinates, persist=TRUE)

 }