Segfault when plotting to axis of closed figure
Ninguém assumiu esta issue ainda.
Avaliação
- Dificuldade
- 4/5
- Tempo estimado
- 3-5 dias
- Facilidade para iniciantes
- 35/100
- Tipo de issue
- Bug
- Clareza
- Razoavelmente clara
- Status de atividade
- Estagnada
- Domínio
- data-visualization
Direção de pesquisa
Comece reproduzindo o cenário de uma figure fechada com PythonPlot v1.0.2 e o exemplo em Julia presente na issue. Em seguida, inspecione o tratamento da GUI do PythonPlot nas proximidades de src/pygui.jl, linha 199, e a stack matplotlib/Tk exibida no trace. Considera-se concluído quando plotar em uma figure fechada não causar mais um segmentation fault e, em vez disso, se comportar com segurança, idealmente gerando um erro caso a operação não seja compatível.
Escrita pelo modelo de indexação a partir do texto da issue.
Descrição
If we attempt to plot to the axis of a figure that has already been displayed and closed, then on my machine Juliaa segfaults.
julia> fig, ax = subplots() # opens plot window, leave open
Python: (<Figure size 640x480 with 1 Axes>, <Axes: >)
julia> ax.scatter(randn(10), randn(10)) # adds plot to window
Python: <matplotlib.collections.PathCollection object at 0x7f0df059df50>
Then close the opened plot window and run the following, which causes the segfault.
julia> ax.scatter(randn(10), randn(10))
Python: <matplotlib.collections.PathCollection object at 0x7f0df19db050>
julia>
[306116] signal (11.1): Segmentation fault
in expression starting at none:0
Tk_GetImageMasterData at /tmp/jl_GaEsxY/.CondaPkg/env/lib/python3.11/lib-dynload/../../libtk8.6.so (unknown line)
Tk_FindPhoto at /tmp/jl_GaEsxY/.CondaPkg/env/lib/python3.11/lib-dynload/../../libtk8.6.so (unknown line)
_ZL11mpl_tk_blitP7_objectS0_ at /tmp/jl_GaEsxY/.CondaPkg/env/lib/python3.11/site-packages/matplotlib/backends/_tkagg.cpython-311-x86_64-linux-gnu.so (unknown line)
cfunction_call at /usr/local/src/conda/python-3.11.4/Objects/methodobject.c:553
_PyObject_MakeTpCall at /usr/local/src/conda/python-3.11.4/Objects/call.c:214
_PyEval_EvalFrameDefault at /usr/local/src/conda/python-3.11.4/Python/ceval.c:4774
_PyEval_EvalFrame at /usr/local/src/conda/python-3.11.4/Include/internal/pycore_ceval.h:73 [inlined]
_PyEval_Vector at /usr/local/src/conda/python-3.11.4/Python/ceval.c:6439 [inlined]
_PyFunction_Vectorcall at /usr/local/src/conda/python-3.11.4/Objects/call.c:393
PythonCmd at /usr/local/src/conda/python-3.11.4/Modules/_tkinter.c:2252
TclNRRunCallbacks at /tmp/jl_GaEsxY/.CondaPkg/env/lib/python3.11/lib-dynload/../../libtcl8.6.so (unknown line)
Tkapp_Call at /usr/local/src/conda/python-3.11.4/Modules/_tkinter.c:1462
method_vectorcall_VARARGS at /usr/local/src/conda/python-3.11.4/Objects/descrobject.c:330
_PyObject_VectorcallTstate at /usr/local/src/conda/python-3.11.4/Include/internal/pycore_call.h:92 [inlined]
PyObject_Vectorcall at /usr/local/src/conda/python-3.11.4/Objects/call.c:299
_PyEval_EvalFrameDefault at /usr/local/src/conda/python-3.11.4/Python/ceval.c:4774
_PyEval_EvalFrame at /usr/local/src/conda/python-3.11.4/Include/internal/pycore_ceval.h:73 [inlined]
_PyEval_Vector at /usr/local/src/conda/python-3.11.4/Python/ceval.c:6439 [inlined]
_PyFunction_Vectorcall at /usr/local/src/conda/python-3.11.4/Objects/call.c:393
do_call_core at /usr/local/src/conda/python-3.11.4/Python/ceval.c:7357 [inlined]
_PyEval_EvalFrameDefault at /usr/local/src/conda/python-3.11.4/Python/ceval.c:5381
_PyEval_EvalFrame at /usr/local/src/conda/python-3.11.4/Include/internal/pycore_ceval.h:73 [inlined]
_PyEval_Vector at /usr/local/src/conda/python-3.11.4/Python/ceval.c:6439 [inlined]
_PyFunction_Vectorcall at /usr/local/src/conda/python-3.11.4/Objects/call.c:393
do_call_core at /usr/local/src/conda/python-3.11.4/Python/ceval.c:7357 [inlined]
_PyEval_EvalFrameDefault at /usr/local/src/conda/python-3.11.4/Python/ceval.c:5381
_PyEval_EvalFrame at /usr/local/src/conda/python-3.11.4/Include/internal/pycore_ceval.h:73 [inlined]
_PyEval_Vector at /usr/local/src/conda/python-3.11.4/Python/ceval.c:6439 [inlined]
_PyFunction_Vectorcall at /usr/local/src/conda/python-3.11.4/Objects/call.c:393 [inlined]
_PyObject_VectorcallTstate at /usr/local/src/conda/python-3.11.4/Include/internal/pycore_call.h:92
method_vectorcall at /usr/local/src/conda/python-3.11.4/Objects/classobject.c:67
PythonCmd at /usr/local/src/conda/python-3.11.4/Modules/_tkinter.c:2252
TclNRRunCallbacks at /tmp/jl_GaEsxY/.CondaPkg/env/lib/python3.11/lib-dynload/../../libtcl8.6.so (unknown line)
AfterProc at /tmp/jl_GaEsxY/.CondaPkg/env/lib/python3.11/lib-dynload/../../libtcl8.6.so (unknown line)
TclServiceIdle at /tmp/jl_GaEsxY/.CondaPkg/env/lib/python3.11/lib-dynload/../../libtcl8.6.so (unknown line)
Tcl_DoOneEvent at /tmp/jl_GaEsxY/.CondaPkg/env/lib/python3.11/lib-dynload/../../libtcl8.6.so (unknown line)
_tkinter_tkapp_dooneevent_impl at /usr/local/src/conda/python-3.11.4/Modules/_tkinter.c:2785 [inlined]
_tkinter_tkapp_dooneevent at /usr/local/src/conda/python-3.11.4/Modules/clinic/_tkinter.c.h:566
cfunction_vectorcall_FASTCALL at /usr/local/src/conda/python-3.11.4/Objects/methodobject.c:427
PyObject_CallObject at /home/sethaxen/.julia/packages/PythonCall/qTEA1/src/cpython/pointers.jl:299 [inlined]
macro expansion at /home/sethaxen/.julia/packages/PythonCall/qTEA1/src/Py.jl:131 [inlined]
pycallargs at /home/sethaxen/.julia/packages/PythonCall/qTEA1/src/abstract/object.jl:210
unknown function (ip: 0x7f4b801c1ea6)
_jl_invoke at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/gf.c:2758 [inlined]
ijl_apply_generic at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/gf.c:2940
#pycall#59 at /home/sethaxen/.julia/packages/PythonCall/qTEA1/src/abstract/object.jl:228
_jl_invoke at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/gf.c:2758 [inlined]
ijl_apply_generic at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/gf.c:2940
jl_apply at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/julia.h:1879 [inlined]
do_apply at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/builtins.c:730
pycall at /home/sethaxen/.julia/packages/PythonCall/qTEA1/src/abstract/object.jl:218
_jl_invoke at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/gf.c:2758 [inlined]
ijl_apply_generic at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/gf.c:2940
jl_apply at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/julia.h:1879 [inlined]
do_apply at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/builtins.c:730
#_#11 at /home/sethaxen/.julia/packages/PythonCall/qTEA1/src/Py.jl:341
_jl_invoke at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/gf.c:2758 [inlined]
ijl_apply_generic at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/gf.c:2940
jl_apply at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/julia.h:1879 [inlined]
do_apply at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/builtins.c:730
Py at /home/sethaxen/.julia/packages/PythonCall/qTEA1/src/Py.jl:341
_jl_invoke at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/gf.c:2758 [inlined]
ijl_apply_generic at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/gf.c:2940
#9 at /home/sethaxen/.julia/packages/PythonPlot/f591M/src/pygui.jl:199
macro expansion at ./asyncevent.jl:281 [inlined]
#702 at ./task.jl:134
unknown function (ip: 0x7f4b801d59df)
_jl_invoke at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/gf.c:2758 [inlined]
ijl_apply_generic at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/gf.c:2940
jl_apply at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/julia.h:1879 [inlined]
start_task at /cache/build/default-amdci5-2/julialang/julia-release-1-dot-9/src/task.c:1092
Allocations: 10747647 (Pool: 10739903; Big: 7744); GC: 15
Segmentation fault (core dumped)
If plotting to this axis is not supported, it would be much better to throw an error.
Environment
julia> versioninfo()
Julia Version 1.9.2
Commit e4ee485e909 (2023-07-05 09:39 UTC)
Platform Info:
OS: Linux (x86_64-linux-gnu)
CPU: 8 × 11th Gen Intel(R) Core(TM) i5-1135G7 @ 2.40GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-14.0.6 (ORCJIT, tigerlake)
Threads: 8 on 8 virtual cores
Environment:
JULIA_CMDSTAN_HOME = /home/sethaxen/software/cmdstan/2.30.1/
JULIA_NUM_THREADS = auto
JULIA_EDITOR = code
(jl_jbDJBf) pkg> st
Status `/tmp/jl_jbDJBf/Project.toml`
[274fc56d] PythonPlot v1.0.2
- Linguagem predominante
- Julia
- Estrelas
- 85
- Forks
- 9
- Métricas de merge de PRs
- Nenhum PR com merge em 30d
Preparar o ambiente
Este projeto não oferece contêiner de desenvolvimento, Dockerfile nem guia de contribuição, então a configuração fica por sua conta: comece pelo README e veja nosso guia da primeira contribuição para os passos gerais.
Primeiros passos
- Leia a issue inteira e depois o guia de contribuição do projeto.
- Comente na issue dizendo que vai assumir — evita que duas pessoas façam o mesmo trabalho.
- Faça um fork do repositório e trabalhe em uma branch.
- Abra um pull request que referencie o número da issue.
Mais de JuliaPy/PythonPlot.jl
-
Dificuldade 4/5 3-5 dias Facilidade para iniciantes 38/100
JuliaPy/PythonPlot.jl#55 · 3 comentários ·
-
Dificuldade 3/5 1-2 dias Facilidade para iniciantes 45/100
JuliaPy/PythonPlot.jl#54 ·
-
Dificuldade 3/5 1-2 dias Facilidade para iniciantes 45/100
JuliaPy/PythonPlot.jl#53 ·
-
Dificuldade 1/5 Menos de uma hora Facilidade para iniciantes 35/100
JuliaPy/PythonPlot.jl#52 · 2 reações ·
-
Dificuldade 4/5 3-5 dias Facilidade para iniciantes 20/100
JuliaPy/PythonPlot.jl#51 ·
Todas as issues de JuliaPy/PythonPlot.jl
Issues semelhantes
-
Chains resumed from `initial_state` take `num_warmup + 1` warm-up stepsTalvez já em andamento @thevolatilebit assumiu hoje. Aberta
Dificuldade 2/5 1-3 horas Facilidade para iniciantes 80/100
TuringLang/AbstractMCMC.jl#220 ·
-
found-by-agent
Dificuldade 2/5 1-3 horas Facilidade para iniciantes 68/100
exanauts/SparseDirectSolver.jl#92 ·
Mantenedores costumam responder em até 1 dia
-
`inv` of a dense matrix fails for arrays whose `parent` is not an array of the same kindTalvez já em andamento @devmotion assumiu hoje. Aberta
Dificuldade 2/5 1-3 horas Facilidade para iniciantes 76/100
JuliaLang/LinearAlgebra.jl#1740 ·
Mantenedores costumam responder em até 2 dias
-
Dificuldade 2/5 1-3 horas Facilidade para iniciantes 78/100
Mantenedores costumam responder em até 1 dia
-
Dificuldade 2/5 1-3 horas Facilidade para iniciantes 90/100
NumericalEarth/Breeze.jl#1051 ·
Mantenedores costumam responder em até 1 dia