dpshorten / cotete.jl Goto Github PK

Thanks for making this interesting package.

The install instructions are not working for me.

david@home:~$ git clone --recurse-submodules --branch v0.2.2 https://github.com/dpshorten/CoTETE.jl.git
make sure that CoTETE.jl/src/ is on your JULIA_LOAD_PATH. eg:

david@home:~$ export JULIA_LOAD_PATH=:/home/user/git/CoTETE.jl/src/
Fire up the Julia REPL

david@home:~$ julia

I wonder if it would be possible to the package to the Julia registry?

I am testing the CoTETE package in Python and keep running into this odd error:

IndexError: <PyCall.jlwrap (in a Julia function called from Python)

JULIA: BoundsError: attempt to access 4333-element Vector{Float64} at index [0]

Stacktrace:

[1] getindex(A::Vector{Float64}, i1::Int64) @ Base ./array.jl:805

[2] make_one_embedding(observation_time_point::Float64, event_time_arrays::Vector{Vector{Float64}}, most_recent_event_indices::Vector{Integer}, embedding_lengths::Vector{Int64}) @ CoTETE ~/.bin/CoTETE.jl/src/preprocessing.jl:99

[3] make_embeddings_along_observation_time_points(observation_time_points::Vector{Float64}, start_observation_time_point::Int64, num_observation_time_points_to_use::Int64, event_time_arrays::Vector{Vector{Float64}}, embedding_lengths::Vector{Int64}) @ CoTETE ~/.bin/CoTETE.jl/src/preprocessing.jl:166

[4] preprocess_event_times(parameters::CoTETE.CoTETEParameters, target_events::Vector{Float64}; source_events::Vector{Float64}, conditioning_events::Vector{Vector{Float32}}) @ CoTETE ~/.bin/CoTETE.jl/src/preprocessing.jl:452

[5] estimate_TE_and_p_value_from_event_times(parameters::CoTETE.CoTETEParameters, target_events::Vector{Float64}, source_events::Vector{Float64}; conditioning_events::Vector{Vector{Float32}}, return_surrogate_TE_values::Bool) @ CoTETE ~/.bin/CoTETE.jl/src/CoTETE.jl:363

[6] invokelatest(::Any, ::Any, ::Vararg{Any, N} where N; kwargs::Base.Iterators.Pairs{Symbol, Bool, Tuple{Symbol}, NamedTuple{(:return_surrogate_TE_values,), Tuple{Bool}}}) @ Base ./essentials.jl:710

[7] _pyjlwrap_call(f::Function, args_::Ptr{PyCall.PyObject_struct}, kw_::Ptr{PyCall.PyObject_struct}) @ PyCall ~/.julia/packages/PyCall/BD546/src/callback.jl:32

[8] pyjlwrap_call(self_::Ptr{PyCall.PyObject_struct}, args_::Ptr{PyCall.PyObject_struct}, kw_::Ptr{PyCall.PyObject_struct}) @ PyCall ~/.julia/packages/PyCall/BD546/src/callback.jl:44>

The length of the source and the target numpy arrays are both several thousand timesteps, and they are both float64 type.

The code runs fine for apparently identical inputs - I can't seem to figure out what is wrong with this particular set of sources and targets.