Read meshes from chunked graph (graphene) server via CloudVolume

save_cloudvolume_meshes saves meshes to disk.

read_cloudvolume_meshes uses save_cloudvolume_meshes internally to save meshes to disk and then reads them into memory as a neuronlist.

Usage

save_cloudvolume_meshes(
  segments,
  savedir = tempfile(),
  OmitFailures = TRUE,
  Force = FALSE,
  format = c("obj", "ply"),
  ...,
  cloudvolume.url = getOption("fafbseg.cloudvolume.url")
)

read_cloudvolume_meshes(
  segments,
  savedir = NULL,
  ...,
  cloudvolume.url = getOption("fafbseg.cloudvolume.url")
)

Arguments

segments: The segment ids to fetch (probably as a character vector)
savedir: Optional path to a directory in which obj format files will be stored. If not specified, a temporary directory will be created and removed at the end of the call.
OmitFailures: Whether to omit neurons for which FUN gives an error. The default value (NA) will result in nlapply stopping with an error message the moment there is an error. For other values, see details.
Force: whether to overwrite a downloaded mesh of the same name
format: whether to save meshes in Wavefront obj or Stanford poly format. obj is the default but ply is a simpler and more compact format.
...: Additional arguments passed to save_cloudvolume_meshes and then eventually to the Python CloudVolume constructor (see https://github.com/seung-lab/cloud-volume for details.
cloudvolume.url: Optional url from which to fetch meshes normally specified by the fafbseg.cloudvolume.url option.

Value

A rgl::shapelist3d list containing one or more mesh3d objects named by the segment id.

Details

You may to use this to fetch meshes from https://flywire.ai among other sources. You may need to select your preferred remote data source using choose_segmentation (see examples). Under the hood, it uses the CloudVolume serverless Python client for reading data in Neuroglancer compatible formats. You will therefore need to have a working python3 install of CloudVolume.

Please install the Python CloudVolume module as described at: https://github.com/seung-lab/cloud-volume#setup. You must ensure that you are using python3 (implicitly or explicitly) as mesh fetching from graphene servers depends on this. This should normally work: pip3 install cloud-volume. If you have already installed CloudVolume but it is not found, then I recommend editing your Renviron file to set an environment variable pointing to the correct Python. You can do this with usethis::edit_r_environ() and then setting e.g. RETICULATE_PYTHON="/usr/local/bin/python3".

You will normally need to set up some kind of authentication in order to fetch data. For flywire, we recommend the function flywire_set_token. For other data sources or more details, see https://github.com/seung-lab/cloud-volume#chunkedgraph-secretjson for how to get a token and where to save it. You can either save a json snippet to ~/.cloudvolume/secrets/cave-secret.json or set an environment variable (CHUNKEDGRAPH_SECRET="XXXX".

Finally you will also need to set an option pointing to your server. This is most conveniently achieved using e.g. choose_segmentation('flywire31'), which is now the default, but for sources without built-in support, you can also specify a full source URL, which might look something like

options(fafbseg.cloudvolume.url='graphene://https://xxx.dynamicannotationframework.com/segmentation/xxx/xxx')

You can easily add this to your startup Rprofile with usethis::edit_r_profile().

Examples


if (FALSE) { # \dontrun{
kcmesh=save_cloudvolume_meshes("720575940623755722", savedir=".")
kc=read.neurons(kcmesh)
} # }
if (FALSE) { # \dontrun{
# The very first time you access FlyWire data you need to get/store a token
flywire_set_token()

# Each R session, you should choose the default segmentation you want
choose_segmentation('flywire31')
pmn1.flywire=read_cloudvolume_meshes("720575940623979522")
pmn1.fafb=read.neuron.catmaid(5321581)

# Read and plot sample KCs from a FlyWire (short) URL
u="https://ngl.flywire.ai/?json_url=https://globalv1.flywire-daf.com/nglstate/6230669436911616"
kcs=read_cloudvolume_meshes(u)
kcs
plot3d(kcs)

nclear3d()
plot3d(pmn1.fafb, col='red', lwd=2, WithNodes = F)
wire3d(pmn1.flywire)

# you can select specific locations like so
library(elmr)
# CATMAID URL
open_fafb(pmn1.flywire[[1]], open=F)
# CATMAID coords to paste into PIN location box
cat(xyzmatrix(catmaid::catmaid_parse_url(open_fafb(pmn1.flywire[[1]], open=F))), sep=',')
# Neuroglancer coords (raw pixels not nm)
open_fafb_ngl(pmn1.flywire[[1]], open=F, coords.only = T)
} # }