Added banc RGL views

.gitignore

@@ -4,3 +4,4 @@
 .Ruserdata
 docs
 inst/doc
+data-raw/*

DESCRIPTION

@@ -17,7 +17,7 @@ BugReports: https://github.com/flyconnectome/bancr/issues
 Depends: 
     R (>= 2.10),
     fafbseg (>= 0.13.0.9100),
-    Morpho,
+    fancr,
     nat.flybrains
 Imports: 
     nat,
@@ -47,6 +47,7 @@ Remotes:
     natverse/fafbseg,
     natverse/nat.flybrains,
     natverse/nat.templatebrains
+    flyconnectome/fancr
 Config/testthat/edition: 3
 Encoding: UTF-8
 Language: en-GB

NAMESPACE

@@ -33,7 +33,7 @@ export(banc_voxdims)
 export(banc_xyz2id)
 export(choose_banc)
 export(dr_banc)
-export(read_banc_meshes)
+export(banc_read_neuron_meshes)
 export(with_banc)
 import(bit64)
 import(fafbseg)

R/cave-tables.R

@@ -27,7 +27,8 @@
 #' points3d(nat::xyzmatrix(all_banc_soma_positions))
 #' }
 #'
-banc_cave_tables <- function(datastack_name = getOption("fafbseg.cave.datastack_name"), select = NULL){
+banc_cave_tables <- function(datastack_name = getOption("fafbseg.cave.datastack_name"),
+                             select = NULL){
   fac <- flywire_cave_client(datastack_name = datastack_name)
   dsinfo <- fac$info$get_datastack_info()
   if (!is.null(dsinfo$soma_table))
@@ -52,7 +53,7 @@ banc_cave_tables <- function(datastack_name = getOption("fafbseg.cave.datastack_
 #' @export
 banc_nuclei <- function (rootids = NULL,
                          nucleus_ids = NULL,
-                         table = c("somas_v1b","somas_v1a"),
+                         table = c("somas_v1a","somas_v1b"),
                          rawcoords = FALSE,
                          ...) {
   table <- match.arg(table)
@@ -84,7 +85,7 @@ banc_nuclei <- function (rootids = NULL,
       nuclei %>% dplyr::mutate(pt_root_id = flywire_updateids(.data$pt_root_id,
                                                        svids = .data$pt_supervoxel_id))
     }
-  }else {
+  }else{
     nid <- paste(nucleus_ids, collapse = ",")
     nidq <- reticulate::py_eval(sprintf("{\"id\": [%s]}",
                                        nid), convert = F)
@@ -96,17 +97,24 @@ banc_nuclei <- function (rootids = NULL,
   res
   #  apply coordinate transform
   # res <- standard_nuclei(res)
-  if (isFALSE(rawcoords))
+  if (isTRUE(rawcoords))
     res
   else {
-    res %>% dplyr::mutate(dplyr::across(dplyr::ends_with("position"), function(x) nat::xyzmatrix2str(flywire_nm2raw(x))))
+    res %>% dplyr::mutate(dplyr::across(dplyr::ends_with("position"), function(x)
+      nat::xyzmatrix2str(fancr::banc_raw2nm(x))))
   }
 }
 
 #' @export
-banc_cell_info <- function(rootids = NULL){
+banc_cell_info <- function(rootids = NULL, rawcoords = FALSE){
   table <- "cell_info"
-  get_cave_table_data(table)
+  res <- get_cave_table_data(table)
+  if (isTRUE(rawcoords))
+    res
+  else {
+    res %>% dplyr::mutate(dplyr::across(dplyr::ends_with("position"), function(x)
+      nat::xyzmatrix2str(fancr::banc_raw2nm(x))))
+  }
 }
 
 #' @export

R/meshes.R

@@ -18,12 +18,12 @@
 #' @seealso \code{fafbseg::\link{read_cloudvolume_meshes}}
 #' @examples
 #' \donttest{
-#' neuron.mesh <- read_banc_meshes("720575941650432785")
+#' neuron.mesh <- banc_read_neuron_meshes("720575941650432785")
 #' plot3d(neuron.mesh, alpha = 0.1)
-#' nucleus.mesh <- read_banc_meshes("72903876004544795")
+#' nucleus.mesh <- banc_read_neuron_meshes("72903876004544795")
 #' plot3d(nucleus.mesh, col = "black")
 #' }
-read_banc_meshes <- function(ids, savedir=NULL, format=c("ply", "obj"), ...) {
+banc_read_neuron_meshes <- function(ids, savedir=NULL, format=c("ply", "obj"), ...) {
   format=match.arg(format)
   read_cloudvolume_meshes(ids, savedir = savedir, cloudvolume.url = banc_cloudvolume_url(set=FALSE), format=format, ...)
 }
@@ -54,7 +54,7 @@ banc_read_nuclei_mesh <- function(ids, lod = 1L, savedir=NULL,  method=c('vf', '
 #' @export
 #' @examples
 #' \donttest{
-#' m = read_banc_meshes("720575941650432785")
+#' m = banc_read_neuron_meshes("720575941650432785")
 #' m.brain = banc_decapitate(m)
 #' m.vnc = banc_decapitate(m, invert = TRUE)
 #' plot3d(m.brain, col = "red")
@@ -110,7 +110,7 @@ banc_decapitate <- function(x, invert = FALSE, reference = "BANC"){
 #' @param url the URL that directs \code{bancr} to where BANC meshes are stored.
 #' @return a mesh3d object for the specified mesh.
 #' @export
-#' @seealso \code{\link{read_banc_meshes}}
+#' @seealso \code{\link{banc_read_neuron_meshes}}
 #' @examples
 #' \dontrun{
 #' banc.mesh  <- banc_read_neuroglancer_mesh()
@@ -122,12 +122,13 @@ banc_read_neuroglancer_mesh <- function(x = 1,
   res <- httr::GET(completed_url, ...)
   httr::stop_for_status(res)
   bytes <- httr::content(res, as = "raw")
-  decode_neuroglancer_mesh(bytes)
+  malevnc:::decode_neuroglancer_mesh(bytes)
 }
 
 # convert cloudvolume python mesh to an R mesh3d object
 # method vf just uses the vertex and face arrays
 # ply writes out to Stanford ply format and reads back in again
+# from hemibrainr
 cvmesh2mesh <- function(x, method=c('vf', 'ply'), ...) {
   method=match.arg(method)
   if(method=='vf') {
@@ -148,25 +149,3 @@ cvmesh2mesh <- function(x, method=c('vf', 'ply'), ...) {
   m
 }
 
-# from package: malevnc
-decode_neuroglancer_mesh <- function (bytes, format = c("mesh3d", "raw")) {
-  format = match.arg(format)
-  con = rawConnection(bytes)
-  on.exit(close(con))
-  nverts = readBin(con, what = "int", size = 4, n = 1)
-  verts = readBin(con, what = "numeric", n = nverts * 3, size = 4)
-  nidxs = length(bytes)/4 - 1L - length(verts)
-  idx = readBin(con, what = "int", n = nidxs, size = 4)
-  if (format == "raw") {
-    structure(list(v = matrix(verts, ncol = 3, byrow = T),
-                   i = matrix(idx, ncol = 3, byrow = T)), class = "ngmesh")
-  }
-  else {
-    rgl::tmesh3d(matrix(verts, nrow = 3, byrow = F), matrix(idx +
-                                                              1L, nrow = 3, byrow = F), homogeneous = F)
-  }
-}
-
-
-
-

R/synapses.R

@@ -8,6 +8,8 @@
 #' @param overwrite Logical, whether or not to overwrite an extant \code{banc_data.sqlite} file.
 #' @param n_max Numeric, the maximum number of rows ot read from \code{path} if you just want to see
 #' a taster of the file.
+#' @param Logical Whether or not to read all data columns in the target synapse \code{.csv}. Defaults to
+#' \code{FALSE} in order to read only the essential presynapse position data.
 #'
 #' @return a data.frame
 #'
@@ -20,7 +22,8 @@
 #' }
 banc_all_synapses <- function(path = "gs://zetta_lee_fly_cns_001_synapse/240623_run/assignment/final_edgelist.df",
                               overwrite = FALSE,
-                              n_max = 2000){
+                              n_max = 2000,
+                              details = FALSE){
 
   # Correct path to de-authenticate it, use https
   path <- gsub("^gs\\:\\/","https://storage.googleapis.com",path)
@@ -66,11 +69,21 @@ banc_all_synapses <- function(path = "gs://zetta_lee_fly_cns_001_synapse/240623_
 
   # Are we just sampling or going for the full thing?
   if(!is.null(n_max)){
-    syns <- readr::read_csv(file=path, col_types = col.types, lazy = TRUE, n_max = n_max)
+    if(details){
+      syns <- readr::read_csv(file=path, col_types = col.types, lazy = TRUE, n_max = n_max)
+    }else{
+      syns <- readr::read_csv(file=path, col_types = col.types, lazy = TRUE, n_max = n_max,
+                              select = c(presyn_segid, presyn_x, presyn_y, presyn_z, size))
+    }
     return(syns)
   }else if (!table_exists|overwrite){
     # Get all synapses
-    syns <- readr::read_csv(file=path, col_types = col.types, lazy = TRUE)
+    if (details){
+      syns <- readr::read_csv(file=path, col_types = col.types, lazy = TRUE)
+    }else{
+      syns <- readr::read_csv(file=path, col_types = col.types, lazy = TRUE,
+                              select = c(presyn_segid, presyn_x, presyn_y, presyn_z, size))
+    }
 
     # Process
 

R/xform.R

@@ -1 +1,33 @@
 
+# for nm
+banc_view <- function(){
+  rgl::rgl.viewpoint(userMatrix = structure(c(0.961547076702118, 0.037275392562151,
+                                0.27209860086441, 0, 0.0369537360966206, -0.999296963214874,
+                                0.00630810856819153, 0, 0.272142440080643, 0.00398948788642883,
+                                -0.962248742580414, 0, 0, 0, 0, 1), dim = c(4L, 4L)), zoom = 0.822702646255493)
+}
+
+# for nm
+banc_side_view <- function(){
+  rgl::rgl.viewpoint(userMatrix = structure(c(0.188666880130768, 0.137750864028931,
+                                -0.972331881523132, 0, 0.130992725491524, -0.98479551076889,
+                                -0.114099271595478, 0, -0.97326534986496, -0.105841755867004,
+                                -0.203842639923096, 0, 0, 0, 0, 1), dim = c(4L, 4L)), zoom = 0.783526360988617)
+}
+
+# for nm
+banc_front_view <- function(){
+  rgl::rgl.viewpoint(userMatrix = structure(c(0.99931389093399, 0.0139970388263464,
+                                -0.0342894680798054, 0, -0.0321401171386242, -0.132316529750824,
+                                -0.990686297416687, 0, -0.0184037387371063, 0.991108655929565,
+                                -0.131775915622711, 0, 0, 0, 0, 1), dim = c(4L, 4L)), zoom = 0.613913536071777)
+}
+
+# for nm
+banc_vnc_view <- function(){
+  rgl::rgl.viewpoint(userMatrix = structure(c(0.992902159690857, 0.113465532660484,
+                                0.0356490463018417, 0, 0.103959240019321, -0.973584711551666,
+                                0.203286483883858, 0, 0.0577733889222145, -0.198137611150742,
+                                -0.978470027446747, 0, 33598.359375, 191755.796875, -6508.533203125,
+                                1), dim = c(4L, 4L)), zoom = 0.505068242549896)
+}