Why is pygrapviz(neato) overlapping my clusters? - dot

I am trying to draw a graph from the following dot file. The neato algo is overlapping the nodes while the dot one puts the clusters side by side when I want them to be like in a top down order.
This was added here because StackOv says I did not add enough detais
graph {
graph [mindist=0.5,
overlap=False,
ranksep=1
];
node [fontsize=11];
edge [fontsize=9,
len=4
];
subgraph cluster_avvc {
graph [label=AVVC,
rank="same; 1"
];
avvcsw1 [data="<__main__.N9KSwitch object at 0x02E24490>"];
avvcsw2 [data="<__main__.N9KSwitch object at 0x02E248D0>"];
}
subgraph cluster_spines {
graph [label=Spines,
rank="same; 2"
];
sp1 [data="<__main__.N9KSwitch object at 0x02E15D50>"];
sp2 [data="<__main__.N9KSwitch object at 0x02E156B0>"];
}
subgraph cluster_bl {
graph [label="Border Leafs",
rank="same; 3"
];
bl1 [data="<__main__.N9KSwitch object at 0x02E15F10>"];
bl2 [data="<__main__.N9KSwitch object at 0x02E153B0>"];
}
avvcsw1 -- sp1 [key=0,
color=blue,
headlabel="Eth1/52",
interfaces="{'sp1': 'Eth1/52', 'avvcsw1': 'Eth2/1'}",
taillabel="Eth2/1"];
avvcsw1 -- extLB [key=0,
color=blue,
headlabel="E1/2",
interfaces="{'avvcsw1': 'Eth1/34', 'extLB': 'E1/2'}",
taillabel="Eth1/34"];
avvcsw1 -- extLB [key=1,
color=blue,
headlabel="E1/1",
interfaces="{'avvcsw1': 'Eth1/33', 'extLB': 'E1/1'}",
taillabel="Eth1/33"];
avvcsw2 -- sp2 [key=0,
color=blue,
headlabel="Eth1/36",
interfaces="{'sp2': 'Eth1/36', 'avvcsw2': 'Eth2/1'}",
taillabel="Eth2/1"];
avvcsw2 -- intFW [key=0,
color=blue,
headlabel="Gi0/0/1",
interfaces="{'avvcsw2': 'Eth1/33', 'intFW': 'Gi0/0/1'}",
taillabel="Eth1/33"];
avvcsw2 -- intFW [key=1,
color=blue,
headlabel="Gi0/0/0",
interfaces="{'avvcsw2': 'Eth1/34', 'intFW': 'Gi0/0/0'}",
taillabel="Eth1/34"];
avvcsw2 -- extFW [key=0,
color=blue,
headlabel="Gi0/0/0",
interfaces="{'avvcsw2': 'Eth1/36', 'extFW': 'Gi0/0/0'}",
taillabel="Eth1/36"];
avvcsw2 -- extFW [key=1,
color=blue,
headlabel="Gi0/0/1",
interfaces="{'avvcsw2': 'Eth1/35', 'extFW': 'Gi0/0/1'}",
taillabel="Eth1/35"];
avvcsw2 -- fgFW [key=0,
color=blue,
headlabel="??",
interfaces="{'avvcsw2': 'Eth1/32', 'fgFW': '??'}",
taillabel="Eth1/32"];
avvcsw2 -- esxSvr [key=0,
color=blue,
headlabel=vmnic5,
interfaces="{'avvcsw2': 'Eth1/31', 'esxSvr': 'vmnic5'}",
taillabel="Eth1/31"];
bl1 -- sp1 [key=0,
color=blue,
headlabel="Eth1/49",
interfaces="{'sp1': 'Eth1/49', 'bl1': 'Eth2/1'}",
taillabel="Eth2/1"];
bl1 -- sp2 [key=0,
color=blue,
headlabel="Eth1/1",
interfaces="{'sp2': 'Eth1/1', 'bl1': 'Eth2/2'}",
taillabel="Eth2/2"];
bl1 -- intLB [key=0,
color=blue,
headlabel=1.1,
interfaces="{'bl1': 'Eth1/32', 'intLB': '1.1'}",
taillabel="Eth1/32"];
bl2 -- sp1 [key=0,
color=blue,
headlabel="Eth1/50",
interfaces="{'sp1': 'Eth1/50', 'bl2': 'Eth2/1'}",
taillabel="Eth2/1"];
bl2 -- sp2 [key=0,
color=blue,
headlabel="Eth1/1",
interfaces="{'sp2': 'Eth1/1', 'bl2': 'Eth2/2'}",
taillabel="Eth2/2"];
bl2 -- esxSvr [key=0,
color=blue,
headlabel=vmnic2,
interfaces="{'bl2': 'Eth1/28', 'esxSvr': 'vmnic2'}",
taillabel="Eth1/28"];
bl2 -- intLB [key=0,
color=blue,
headlabel=1.2,
interfaces="{'bl2': 'Eth1/32', 'intLB': '1.2'}",
taillabel="Eth1/32"];
}
Edit: I updated the dot file with the complete config so you can try it yourself

Related

Cannot install JuliaSymbolics / SymbolicUtils.jl

I'm using Ubuntu 20.04.3 LTS (GNU/Linux 5.4.0-100-generic x86_64), julia v1.7.
] add SymbolicUtils failed to install this package.
The output of Pkg.precompile() is:
Precompiling project...
✗ Groebner
✗ Symbolics
0 dependencies successfully precompiled in 8 seconds (327 already precompiled)
ERROR: The following 2 direct dependencies failed to precompile:
SymbolicUtils [d1185830-fcd6-423d-90d6-eec64667417b]
Error: Missing source file for SymbolicUtils [d1185830-fcd6-423d-90d6-eec64667417b]
Symbolics [0c5d862f-8b57-4792-8d23-62f2024744c7]
Failed to precompile Symbolics [0c5d862f-8b57-4792-8d23-62f2024744c7] to ~/.julia/compiled/v1.7/Symbolics/jl_VPYpQf.
ERROR: LoadError: ArgumentError: Package SymbolicUtils [d1185830-fcd6-423d-90d6-eec64667417b] is required but does not seem to be installed:
- Run `Pkg.instantiate()` to install all recorded dependencies.
Stacktrace:
[1] _require(pkg::Base.PkgId)
# Base ./loading.jl:1089
[2] require(uuidkey::Base.PkgId)
# Base ./loading.jl:1013
[3] require(into::Module, mod::Symbol)
# Base ./loading.jl:997
[4] include
# ./Base.jl:418 [inlined]
[5] include_package_for_output(pkg::Base.PkgId, input::String, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt64}}, source::Nothing)
# Base ./loading.jl:1318
[6] top-level scope
# none:1
[7] eval
# ./boot.jl:373 [inlined]
[8] eval(x::Expr)
# Base.MainInclude ./client.jl:453
[9] top-level scope
# none:1
in expression starting at ~/.julia/packages/Symbolics/kG5bl/src/Symbolics.jl:1
Stacktrace:
[1] pkgerror(msg::String)
# Pkg.Types ~/software/julia-1.7.3/share/julia/stdlib/v1.7/Pkg/src/Types.jl:68
[2] precompile(ctx::Pkg.Types.Context; internal_call::Bool, strict::Bool, warn_loaded::Bool, already_instantiated::Bool, kwargs::Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
# Pkg.API ~/software/julia-1.7.3/share/julia/stdlib/v1.7/Pkg/src/API.jl:1362
[3] precompile
# ~/software/julia-1.7.3/share/julia/stdlib/v1.7/Pkg/src/API.jl:1013 [inlined]
[4] #precompile#220
# ~/software/julia-1.7.3/share/julia/stdlib/v1.7/Pkg/src/API.jl:1011 [inlined]
[5] precompile()
# Pkg.API ~/software/julia-1.7.3/share/julia/stdlib/v1.7/Pkg/src/API.jl:1011
[6] top-level scope
# REPL[1]:1
Why can't I install it? I'm happy to provide more info if needed.
If I remove them by Pkg.rm("SymbolicUtils"); Pkg.rm("Symbolics"), Pkg.precomile() does work. Then ] add SymbolicUtils yields:
Resolving package versions...2.3
Updating `~/.julia/environments/v1.7/Project.toml`
[d1185830] + SymbolicUtils v0.19.11
Updating `~/.julia/environments/v1.7/Manifest.toml`
[1520ce14] + AbstractTrees v0.4.2
[dce04be8] + ArgCheck v2.3.0
[15f4f7f2] + AutoHashEquals v0.2.0
[198e06fe] + BangBang v0.3.36
[9718e550] + Baselet v0.1.1
[e2ed5e7c] + Bijections v0.1.4
[861a8166] + Combinatorics v1.0.2
[a33af91c] + CompositionsBase v0.1.1
[244e2a9f] + DefineSingletons v0.1.2
[7c1d4256] + DynamicPolynomials v0.4.5
[22cec73e] + InitialValues v0.3.1
[2ee39098] + LabelledArrays v1.11.1
[e9d8d322] + Metatheory v1.3.4
[128add7d] + MicroCollections v0.1.2
[102ac46a] + MultivariatePolynomials v0.4.6
[42d2dcc6] + Referenceables v0.1.2
[171d559e] + SplittablesBase v0.1.14
[d1185830] + SymbolicUtils v0.19.11
[8ea1fca8] + TermInterface v0.2.3
[ac1d9e8a] + ThreadsX v0.1.10
[28d57a85] + Transducers v0.4.73
0 dependencies successfully precompiled in 2 seconds (319 already precompiled)
1 dependency errored. To see a full report either run `import Pkg; Pkg.precompile()` or load the package
precompile yields:
ERROR: The following 1 direct dependency failed to precompile:
SymbolicUtils [d1185830-fcd6-423d-90d6-eec64667417b]
Error: Missing source file for SymbolicUtils [d1185830-fcd6-423d-90d6-eec64667417b```

Installing Flux.jl on Linux: NNlibCUDA fails to precompile

While trying to install Flux I run into an error where it fails to precompile the NNlibCUDA library.
Running ] test NNlibCUDA results in LoadError: UndefVarError: upsample_linear_wcn! not defined:
(#v1.7) pkg> test NNlibCUDA
Testing NNlibCUDA
Status `/tmp/jl_1psy2E/Project.toml`
[052768ef] CUDA v3.10.1
[f6369f11] ForwardDiff v0.10.30
[872c559c] NNlib v0.8.6
[a00861dc] NNlibCUDA v0.2.3
[e88e6eb3] Zygote v0.6.40
[37e2e46d] LinearAlgebra `#stdlib/LinearAlgebra`
[9a3f8284] Random `#stdlib/Random`
[10745b16] Statistics `#stdlib/Statistics`
[8dfed614] Test `#stdlib/Test`
Status `/tmp/jl_1psy2E/Manifest.toml`
[621f4979] AbstractFFTs v1.1.0
[79e6a3ab] Adapt v3.3.3
[ab4f0b2a] BFloat16s v0.2.0
[fa961155] CEnum v0.4.2
[052768ef] CUDA v3.10.1
[082447d4] ChainRules v1.35.1
[d360d2e6] ChainRulesCore v1.15.0
[9e997f8a] ChangesOfVariables v0.1.3
[bbf7d656] CommonSubexpressions v0.3.0
[34da2185] Compat v3.44.0
[163ba53b] DiffResults v1.0.3
[b552c78f] DiffRules v1.11.0
[ffbed154] DocStringExtensions v0.8.6
[e2ba6199] ExprTools v0.1.8
[1a297f60] FillArrays v0.13.2
[f6369f11] ForwardDiff v0.10.30
[0c68f7d7] GPUArrays v8.3.2
[61eb1bfa] GPUCompiler v0.15.2
[7869d1d1] IRTools v0.4.6
[3587e190] InverseFunctions v0.1.4
[92d709cd] IrrationalConstants v0.1.1
[692b3bcd] JLLWrappers v1.4.1
[929cbde3] LLVM v4.13.0
[2ab3a3ac] LogExpFunctions v0.3.15
[1914dd2f] MacroTools v0.5.9
[872c559c] NNlib v0.8.6
[a00861dc] NNlibCUDA v0.2.3
[77ba4419] NaNMath v1.0.0
[21216c6a] Preferences v1.3.0
[74087812] Random123 v1.5.0
[e6cf234a] RandomNumbers v1.5.3
[c1ae055f] RealDot v0.1.0
[189a3867] Reexport v1.2.2
[ae029012] Requires v1.3.0
[276daf66] SpecialFunctions v2.1.5
[90137ffa] StaticArrays v1.4.4
[a759f4b9] TimerOutputs v0.5.19
[e88e6eb3] Zygote v0.6.40
[700de1a5] ZygoteRules v0.2.2
[dad2f222] LLVMExtra_jll v0.0.16+0
[efe28fd5] OpenSpecFun_jll v0.5.5+0
[0dad84c5] ArgTools `#stdlib/ArgTools`
[56f22d72] Artifacts `#stdlib/Artifacts`
[2a0f44e3] Base64 `#stdlib/Base64`
[ade2ca70] Dates `#stdlib/Dates`
[8bb1440f] DelimitedFiles `#stdlib/DelimitedFiles`
[8ba89e20] Distributed `#stdlib/Distributed`
[f43a241f] Downloads `#stdlib/Downloads`
[7b1f6079] FileWatching `#stdlib/FileWatching`
[b77e0a4c] InteractiveUtils `#stdlib/InteractiveUtils`
[4af54fe1] LazyArtifacts `#stdlib/LazyArtifacts`
[b27032c2] LibCURL `#stdlib/LibCURL`
[76f85450] LibGit2 `#stdlib/LibGit2`
[8f399da3] Libdl `#stdlib/Libdl`
[37e2e46d] LinearAlgebra `#stdlib/LinearAlgebra`
[56ddb016] Logging `#stdlib/Logging`
[d6f4376e] Markdown `#stdlib/Markdown`
[a63ad114] Mmap `#stdlib/Mmap`
[ca575930] NetworkOptions `#stdlib/NetworkOptions`
[44cfe95a] Pkg `#stdlib/Pkg`
[de0858da] Printf `#stdlib/Printf`
[3fa0cd96] REPL `#stdlib/REPL`
[9a3f8284] Random `#stdlib/Random`
[ea8e919c] SHA `#stdlib/SHA`
[9e88b42a] Serialization `#stdlib/Serialization`
[1a1011a3] SharedArrays `#stdlib/SharedArrays`
[6462fe0b] Sockets `#stdlib/Sockets`
[2f01184e] SparseArrays `#stdlib/SparseArrays`
[10745b16] Statistics `#stdlib/Statistics`
[fa267f1f] TOML `#stdlib/TOML`
[a4e569a6] Tar `#stdlib/Tar`
[8dfed614] Test `#stdlib/Test`
[cf7118a7] UUIDs `#stdlib/UUIDs`
[4ec0a83e] Unicode `#stdlib/Unicode`
[e66e0078] CompilerSupportLibraries_jll `#stdlib/CompilerSupportLibraries_jll`
[deac9b47] LibCURL_jll `#stdlib/LibCURL_jll`
[29816b5a] LibSSH2_jll `#stdlib/LibSSH2_jll`
[c8ffd9c3] MbedTLS_jll `#stdlib/MbedTLS_jll`
[14a3606d] MozillaCACerts_jll `#stdlib/MozillaCACerts_jll`
[4536629a] OpenBLAS_jll `#stdlib/OpenBLAS_jll`
[05823500] OpenLibm_jll `#stdlib/OpenLibm_jll`
[83775a58] Zlib_jll `#stdlib/Zlib_jll`
[8e850b90] libblastrampoline_jll `#stdlib/libblastrampoline_jll`
[8e850ede] nghttp2_jll `#stdlib/nghttp2_jll`
[3f19e933] p7zip_jll `#stdlib/p7zip_jll`
Precompiling project...
✗ NNlibCUDA
0 dependencies successfully precompiled in 4 seconds (47 already precompiled)
1 dependency errored. To see a full report either run `import Pkg; Pkg.precompile()` or load the package
Testing Running tests...
ERROR: LoadError: UndefVarError: upsample_linear_wcn! not defined
Stacktrace:
[1] getproperty(x::Module, f::Symbol)
# Base ./Base.jl:35
[2] top-level scope
# ~/.julia/packages/NNlibCUDA/vECff/src/upsample.jl:118
[3] include(mod::Module, _path::String)
# Base ./Base.jl:418
[4] include(x::String)
# NNlibCUDA ~/.julia/packages/NNlibCUDA/vECff/src/NNlibCUDA.jl:1
[5] top-level scope
# ~/.julia/packages/NNlibCUDA/vECff/src/NNlibCUDA.jl:9
[6] include
# ./Base.jl:418 [inlined]
[7] include_package_for_output(pkg::Base.PkgId, input::String, depot_path::Vector{String}, dl_load_path::Vector{String}, load_path::Vector{String}, concrete_deps::Vector{Pair{Base.PkgId, UInt64}}, source::String)
# Base ./loading.jl:1318
[8] top-level scope
# none:1
[9] eval
# ./boot.jl:373 [inlined]
[10] eval(x::Expr)
# Base.MainInclude ./client.jl:453
[11] top-level scope
# none:1
in expression starting at /home/manman/.julia/packages/NNlibCUDA/vECff/src/upsample.jl:118
in expression starting at /home/manman/.julia/packages/NNlibCUDA/vECff/src/NNlibCUDA.jl:1
ERROR: LoadError: Failed to precompile NNlibCUDA [a00861dc-f156-4864-bf3c-e6376f28a68d] to /home/manman/.julia/compiled/v1.7/NNlibCUDA/jl_kwzmLD.
Stacktrace:
[1] error(s::String)
# Base ./error.jl:33
[2] compilecache(pkg::Base.PkgId, path::String, internal_stderr::IO, internal_stdout::IO, ignore_loaded_modules::Bool)
# Base ./loading.jl:1466
[3] compilecache(pkg::Base.PkgId, path::String)
# Base ./loading.jl:1410
[4] _require(pkg::Base.PkgId)
# Base ./loading.jl:1120
[5] require(uuidkey::Base.PkgId)
# Base ./loading.jl:1013
[6] require(into::Module, mod::Symbol)
# Base ./loading.jl:997
[7] include(fname::String)
# Base.MainInclude ./client.jl:451
[8] top-level scope
# none:6
in expression starting at /home/manman/.julia/packages/NNlibCUDA/vECff/test/runtests.jl:4
ERROR: Package NNlibCUDA errored during testing
I am running Julia 1.7.3 on Pop!_OS 22.04 with a GTX 1050Ti Mobile.
I just had this issue. I found that running ] update fixed it.

Writing a MAPLE procedure for adding the legends inside in plots

How to write a procedure to add the legends of any given two functions to the suitable location in the graphs? Or we can select the location at the beginning of the procedure (like left-top, right-bottom etc.)?
For example; Let's consider the sin(x) and cos(x), and try to write a Maple code as follows:
restart:
with(plottools): with(plots):
f:=x->sin(x):
g:=x->cos(x):
A:=plot(f(x), x=0..2*3.14, style=pointline, symbol= diamond, color=red, symbolsize=11, numpoints=40, adaptive=false):
B:=plot(g(x), x=0..2*3.14, style=pointline, symbol= solidcircle, color=blue, symbolsize=11, numpoints=40, adaptive=false):
location:=0.8:
L1, L2:=line([2.75,location],[3.2,location],color=red), line([3.65,location],[4.1,location],color=blue):
P1:=plot([seq([2.75+i*(3.2-2.75)/3,location], i=1..2)],style=point,symbol= diamond, color=red, symbolsize=11):
P2:=plot([seq([3.65+i*(3.2-2.75)/3,location], i=1..2)],style=point,symbol= solidcircle, color=blue, symbolsize=11):
T:=textplot([[3.4,location,sin(x)],[4.3,location,cos(x)]]):
P:=polygon([[2.7,0.7],[2.7,0.9],[4.5,0.9],[4.5,0.7]], style=line, thickness=0):
plots:-display(A, B, P, L1, L2, T, P1, P2, scaling=constrained, size=[800,300],axes=boxed);
The image of the above code

Running Community detection and visualising Output in VisNetwork

I am trying to run betweeness and closeness centrality using VISNETWORK package in R.
The nodes are computed for the degree and visualized using below code. Does anyone has idea of how can I compute the other centrality measures and plot using the Visnetwork.
Attaching the code below to compute degree and sample dataset on which i am trying to compute other centrality measures.
graph <- graph.data.frame(retweeter_poster, directed=T) ##retweeter_poster who_retweet and who_post twitter network
graph <- simplify(graph)
V(graph)$indegree <- centr_degree(graph, mode = "in")$res
nodes <- get.data.frame(graph, what="vertices")
nodes <- data.frame(id = nodes$name, title = nodes$name, group = nodes$indegree, indegree = nodes$indegree)
setnames(nodes, "indegree", "in-degree centrality")
nodes <- nodes[order(nodes$id, decreasing = F),]
edges <- get.data.frame(graph, what="edges")[1:2]
visNetwork(nodes, edges, height = "500px", width = "100%") %>%
visOptions(selectedBy = "in-degree centrality", highlightNearest = TRUE, nodesIdSelection = TRUE)%>%
visPhysics(stabilization = FALSE)
Source Target
futatun2228 nanauehara0812
Weltregierung jounger
soccelovexxxxx evian_moe
berlinerzeitung 13susang75
ot113 evian_arswest
ot113 evian_arswest
berlinerzeitung Letnapark
ot113 evian_arswest
sternde xXNero03
mkdirecto Ms_Kowalsky
ot113 evian_arswest
p90tr2 evian_9
sternde MARKENCHECKS
ot113 evian_arswest
ot113 evian_arswest
shoko_ayu_1008 evian_arswest
meikelobo Andreas__Nagel
mkdirecto markiteando
mkdirecto nilsonliscano
FlippinAlbanian LChanio
sternde WWinfos
HIFIMANJAPAN evian
berlinerzeitung daniel_makuch
faznet JrgenNaeve
berlinerzeitung BerlinerNYC
suarezphoto cebenna
SPIEGELONLINE Pahn2304Norbert
SPIEGEL_Top Kawajoerg
Klaus_Mueller Rechtalltaglich
an_evian #an_evian Emiliya1207
MDRaktuell MARKANTdjPOOL
salzburg_com PeterHeinzl
faznet ingouschner
derStandardat Liese_Mueller
faznet RhydanR
Klaus_Mueller KolbaPeter
SPIEGELONLINE OneStepBayond
Klaus_Mueller VanessFred
SPIEGELONLINE frankschroedter
SPIEGELONLINE bolounitlne
faznet Rudini48
berlinerzeitung Marina_Ilona
jzaaaa80 evian_812
HasnainKazim OneStepBayond
SPIEGELONLINE OneStepBayond
faznet JcM_mr
SPIEGELONLINE HasnainKazim
makaronn1gou evian_arswest
SPIEGELONLINE askourgias
SPIEGELONLINE CausesPetitions
faznet Nur_mal_so1
faznet Ghostdogcs

tutorial example fails: mismatch with alt-ergo?

I have installed frama-c using opam and homebrew, following the instructions from the frama-c site. I'm on Mac OS X (El Capitan), and the versions are:
frama-c: Magnesium-20151002
alt-ergo: 1.01
ocaml: 4.02.3
When I attempt to run with the swap.c tutorial, it fails to verify. Here's the error I get:
[ frama-c ]> frama-c -wp -wp-out temp swap.c swap1.h
[kernel] Parsing FRAMAC_SHARE/libc/__fc_builtin_for_normalization.i (no preprocessing)
[kernel] Parsing swap.c (with preprocessing)
[kernel] Parsing swap1.h (with preprocessing)
[wp] warning: Missing RTE guards
[wp] 2 goals scheduled
------------------------------------------------------------
--- Alt-Ergo (stdout) :
------------------------------------------------------------
File "temp/typed/swap_post_A_Alt-Ergo.mlw", line 786, characters 1-299:Valid (0.0093) (12 steps)
------------------------------------------------------------
[wp] [Alt-Ergo] Goal typed_swap_post_A : Failed
Error: Can not understand Alt-Ergo output.
[wp] Proved goals: 1 / 2
Qed: 1
Alt-Ergo: 0 (failed: 1)
The output message seems to suggest that alt-ergo could prove the assertion, but then frama-c could not parse the output. Could this be because the alt-ergo version is too new? Here is the goal on line 786 of the generated file, referenced in the above output:
goal swap_post_A:
forall t : (addr,int) farray.
forall a_1,a : addr.
let x = t[a] : int in
let x_1 = t[a_1] : int in
let x_2 = t[a_1 <- x][a <- x_1][a_1] : int in
is_sint32(x) ->
is_sint32(x_1) ->
(region(a.base) <= 0) ->
(region(a_1.base) <= 0) ->
is_sint32(x_2) ->
(x = x_2)
If I run alt-ergo on this generated file directly, it returns with code 0.

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