index out of bound error

[jingpengw]

index out of bound error

[jingpengw]

this error comes from a super big neuron (id: 76197), which expands to the whole range of XY section!

[jingpengw]

suggestions from @nicholasturner1

I'd try the same thing I mentioned before - compare `prod(max_dims)` to the max index into the sparse vector (`maximum(Int[sub2ind(max_dims, points[i,:]... ) for i=1:num_points ])`) (edited)


[10:43] 
the `prod` value should always be greater than or equal to the other one unless the indexing scheme is somehow wrong

indeed, it is this problem.
max_dims = (3276,975,1750)

ERROR: LoadError: AssertionError: prod(max_dims) > maximum(Int[sub2ind(max_dims,points[i,:]...) for i = 1:num_points])
 in create_node_lookup(::Array{UInt32,2}) at /home/nico/.julia/v0.5/RealNeuralNetworks/src/NodeNets.jl:349
 in #NodeNet#3(::Array{Float64,1}, ::RealNeuralNetworks.NodeNets.#alexs_penalty, ::Tuple{UInt32,UInt32,UInt32}, ::Type{T}, 
::Array{UInt32,2}) at /home/nico/.julia/v0.5/RealNeuralNetworks/src/NodeNets.jl:74
 in (::Core.#kw#Type)(::Array{Any,1}, ::Type{RealNeuralNetworks.NodeNets.NodeNet}, ::Array{UInt32,2}) at ./<missing>:0
 in macro expansion at ./util.jl:188 [inlined]
 in trace(::RealNeuralNetworks.Manifests.Manifest, ::Int64) at /home/nico/.julia/v0.5/RealNeuralNetworks/src/Manifests.jl:7
8
 in #trace#1(::String, ::String, ::UInt32, ::Function, ::Int64) at /home/nico/.julia/v0.5/RealNeuralNetworks/scripts/skelet
onize.jl:20
 in (::#kw##trace)(::Array{Any,1}, ::#trace, ::Int64) at ./<missing>:0
 in main() at /home/nico/.julia/v0.5/RealNeuralNetworks/scripts/skeletonize.jl:94
 in include_from_node1(::String) at ./loading.jl:488
 in process_options(::Base.JLOptions) at ./client.jl:265
 in _start() at ./client.jl:321
while loading /home/nico/.julia/v0.5/RealNeuralNetworks/scripts/skeletonize.jl, in expression starting on line 99

[nicholasturner1]

You mentioned that your chunk size is (512,512,512) before, and that the coordinates were local. If that's the case, the maximum possible value of max_dims should be (512,512,512), since it should be the maximum value in each dimension of the passed coordinates. Perhaps you're just making the data structures for the graph once you've finished chunk-wise processing.

[nicholasturner1]

You're using UInt32, so this is another overflow problem. prod(3276,975,1750) > typemax(UInt32)

[jingpengw]

exactly, this is overflow. but not because the 512x512x512, but because the neuron spans a big space and the max_dims is too big.
prod((3276,975,1750)) > Int(typemax(UInt32)) = true

fixing issue:
6f581de
a5c7d2f