Error when estimating boundaries

[kleejin]

Hi there, I have tried running this on CentOS and MacOS and both instances, the run fails to estimate boundaries and I get the following error. The run still completes and generates the rest of the output files. Any thoughts or troubleshooting tips would be helpful. Thank you!

run parameters:
Baysor run -x x -y y -z z --gene gene -m 30 --n-clusters 3 -s 50 -p --save-polygons=geojson -o $OUTDIR$f $f

error:

[07:57:16] Info: Estimating boundary polygons
[07:58:54] Error: MethodError(Matrix{var"#s565"} where var"#s565"<:Unsigned, (Matrix{Int64}(undef, 0, 0),), 0x00000000000074c6)
|
| convert(#unused#::Type{Matrix{var"#s565"} where var"#s565"<:Unsigned}, a::Matrix{Int64}) at array.jl:532
| find_grid_point_labels_kde(pos_data::Matrix{Float64}, cell_labels::Vector{Int64}, min_x::Vector{Float64}, max_x::Vector{Float64}; grid_step::Float64, bandwidth::Float64, dens_threshold::Float64, min_molecules_per_cell::Int64, verbose::Bool) at boundary_estimation.jl:165
| (::Baysor.var"#find_grid_point_labels_kde##kw")(::NamedTuple{(:grid_step, :bandwidth), Tuple{Float64, Float64}}, ::typeof(Baysor.find_grid_point_labels_kde), pos_data::Matrix{Float64}, cell_labels::Vector{Int64}, min_x::Vector{Float64}, max_x::Vector{Float64}) at boundary_estimation.jl:159
| boundary_polygons(pos_data::Matrix{Float64}, cell_labels::Vector{Int64}; min_x::Nothing, max_x::Nothing, grid_step::Float64, min_border_length::Int64, shape_method::Symbol, max_dev::Float64, bandwidth::Float64, exclude_labels::Vector{Int64}, kwargs::Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}) at boundary_estimation.jl:263
| boundary_polygons at boundary_estimation.jl:254 [inlined]
| #boundary_polygons#214 at boundary_estimation.jl:248 [inlined]
| (::Baysor.var"#boundary_polygons##kw")(::NamedTuple{(:grid_step, :bandwidth), Tuple{Float64, Float64}}, ::typeof(Baysor.boundary_polygons), spatial_df::DataFrames.DataFrame, args::Vector{Int64}) at boundary_estimation.jl:248
| (::Baysor.var"#330#334"{DataFrames.DataFrame, Vector{Int64}, Dict{String, Any}, Float64})(mask::BitVector) at main.jl:220
| #47 at ProgressMeter.jl:991 [inlined]
| iterate at generator.jl:47 [inlined]
| _collect(c::Vector{BitVector}, itr::Base.Generator{Vector{BitVector}, ProgressMeter.var"#47#50"{Distributed.RemoteChannel{Channel{Bool}}, Baysor.var"#330#334"{DataFrames.DataFrame, Vector{Int64}, Dict{String, Any}, Float64}}}, #unused#::Base.EltypeUnknown, isz::Base.HasShape{1}) at array.jl:695
| collect_similar(cont::Vector{BitVector}, itr::Base.Generator{Vector{BitVector}, ProgressMeter.var"#47#50"{Distributed.RemoteChannel{Channel{Bool}}, Baysor.var"#330#334"{DataFrames.DataFrame, Vector{Int64}, Dict{String, Any}, Float64}}}) at array.jl:606
| map(f::Function, A::Vector{BitVector}) at abstractarray.jl:2294
| macro expansion at ProgressMeter.jl:990 [inlined]
| macro expansion at task.jl:387 [inlined]
| macro expansion at ProgressMeter.jl:989 [inlined]
| macro expansion at task.jl:387 [inlined]
| progress_map(::Function, ::Vararg{Any, N} where N; mapfun::Function, progress::ProgressMeter.Progress, channel_bufflen::Int64, kwargs::Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}) at ProgressMeter.jl:982
| progress_map(::Function, ::Vararg{Any, N} where N) at ProgressMeter.jl:978
| plot_transcript_assignment_panel(df_res::DataFrames.DataFrame, assignment::Vector{Int64}, args::Dict{String, Any}; clusters::Vector{Int64}, prior_polygons::Vector{Matrix{Float64}}, gene_colors::Vector{ColorTypes.Lab{Float64}}) at main.jl:220
| (::Baysor.var"#plot_transcript_assignment_panel##kw")(::NamedTuple{(:clusters, :prior_polygons, :gene_colors), Tuple{Vector{Int64}, Vector{Matrix{Float64}}, Vector{ColorTypes.Lab{Float64}}}}, ::typeof(Baysor.plot_transcript_assignment_panel), df_res::DataFrames.DataFrame, assignment::Vector{Int64}, args::Dict{String, Any}) at main.jl:205
| save_segmentation_results(bm_data::Baysor.BmmData{3}, gene_names::Vector{String}, args::Dict{String, Any}; mol_clusts::NamedTuple{(:exprs, :assignment, :diffs, :assignment_probs, :change_fracs), Tuple{Matrix{Float64}, Vector{Int64}, Vector{Float64}, Matrix{Float64}, Vector{Float64}}}, comp_segs::Nothing, prior_polygons::Vector{Matrix{Float64}}) at main.jl:414
| (::Baysor.var"#save_segmentation_results##kw")(::NamedTuple{(:mol_clusts, :comp_segs, :prior_polygons), Tuple{NamedTuple{(:exprs, :assignment, :diffs, :assignment_probs, :change_fracs), Tuple{Matrix{Float64}, Vector{Int64}, Vector{Float64}, Matrix{Float64}, Vector{Float64}}}, Nothing, Vector{Matrix{Float64}}}}, ::typeof(Baysor.save_segmentation_results), bm_data::Baysor.BmmData{3}, gene_names::Vector{String}, args::Dict{String, Any}) at main.jl:394
| run_cli_main(args::Vector{String}) at main.jl:479
| run_cli(args::Vector{String}) at common.jl:118
| run_cli at common.jl:103 [inlined]
| julia_main at common.jl:139 [inlined]
| julia_main() at none:36
└ Baysor /home/runner/work/Baysor/Baysor/src/cli/common.jl:132

env:

LSB Version: :core-4.1-amd64:core-4.1-noarch:cxx-4.1-amd64:cxx-4.1-noarch:desktop-4.1-amd64:desktop-4.1-noarch:languages-4.1-amd64:languages-4.1-noarch:printing-4.1-amd64:printing-4.1-noarch
Distributor ID: CentOS
Description: CentOS Linux release 7.8.2003 (Core)
Release: 7.8.2003
Codename: Core

[Bisho2122]

I also got the same error, @kleejin have you found a solution already ?

[kleejin]

@Bisho2122 No I have not yet found a solution. The upside is the cell by gene info is still output, so I can continue to analyze the data without the boundary info.

[VPetukhov]

Apologies for the late response! The new version 0.6.0 has a different method for polygon estimation, and shouldn't suffer from this problem. Please, let me know if it persists.