Running JuMP example
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I am trying to run this example on a fresh julia installation (Version 1.0.2 (2018-11-08)):
https://github.com/JuliaOpt/JuMP.jl/blob/master/examples/basic.jl
But I always get this error.
julia> using JuMP, Clp
julia> m = Model(with_optimizer(Clp.Optimizer))
ERROR: UndefVarError: with_optimizer not defined
Stacktrace:
[1] top-level scope at none:0
What am I doing wrong? It seems such a simple example should run quite easily.
julia-lang julia-jump
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up vote
0
down vote
favorite
I am trying to run this example on a fresh julia installation (Version 1.0.2 (2018-11-08)):
https://github.com/JuliaOpt/JuMP.jl/blob/master/examples/basic.jl
But I always get this error.
julia> using JuMP, Clp
julia> m = Model(with_optimizer(Clp.Optimizer))
ERROR: UndefVarError: with_optimizer not defined
Stacktrace:
[1] top-level scope at none:0
What am I doing wrong? It seems such a simple example should run quite easily.
julia-lang julia-jump
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I am trying to run this example on a fresh julia installation (Version 1.0.2 (2018-11-08)):
https://github.com/JuliaOpt/JuMP.jl/blob/master/examples/basic.jl
But I always get this error.
julia> using JuMP, Clp
julia> m = Model(with_optimizer(Clp.Optimizer))
ERROR: UndefVarError: with_optimizer not defined
Stacktrace:
[1] top-level scope at none:0
What am I doing wrong? It seems such a simple example should run quite easily.
julia-lang julia-jump
I am trying to run this example on a fresh julia installation (Version 1.0.2 (2018-11-08)):
https://github.com/JuliaOpt/JuMP.jl/blob/master/examples/basic.jl
But I always get this error.
julia> using JuMP, Clp
julia> m = Model(with_optimizer(Clp.Optimizer))
ERROR: UndefVarError: with_optimizer not defined
Stacktrace:
[1] top-level scope at none:0
What am I doing wrong? It seems such a simple example should run quite easily.
julia-lang julia-jump
julia-lang julia-jump
asked Nov 22 at 9:38
Stein
79521032
79521032
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add a comment |
1 Answer
1
active
oldest
votes
up vote
3
down vote
accepted
You are looking at the example from master
branch from the GitHub repository. There are breaking changes in JuMP API since its last release.
You should look at basic.jl file in your local repository. It should be located in a directory location like ~/.julia/packages/JuMP/Xvn0n/examples/basic.jl
(the Xvn0n
part might be different in your case but the path pattern should be the same; if you are on Windows then ~
is a directory of your user profile).
The example you are referring to looks like this in the released version of the package:
using JuMP, Clp
m = Model(solver = ClpSolver())
@variable(m, 0 <= x <= 2)
@variable(m, 0 <= y <= 30)
@objective(m, Max, 5x + 3y)
@constraint(m, 1x + 5y <= 3.0)
print(m)
status = solve(m)
println("Objective value: ", getobjectivevalue(m))
println("x = ", getvalue(x))
println("y = ", getvalue(y))
You can also find the zipped sources of the latest release here https://github.com/JuliaOpt/JuMP.jl/releases/tag/v0.18.4, but of course as new releases are published the number will change so the most reliable place to look at the codes are examples that JuMP has on your local machine.
Thanks this worked. This is quite hidden for someone new to Julia.
– Stein
Nov 22 at 10:29
add a comment |
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
3
down vote
accepted
You are looking at the example from master
branch from the GitHub repository. There are breaking changes in JuMP API since its last release.
You should look at basic.jl file in your local repository. It should be located in a directory location like ~/.julia/packages/JuMP/Xvn0n/examples/basic.jl
(the Xvn0n
part might be different in your case but the path pattern should be the same; if you are on Windows then ~
is a directory of your user profile).
The example you are referring to looks like this in the released version of the package:
using JuMP, Clp
m = Model(solver = ClpSolver())
@variable(m, 0 <= x <= 2)
@variable(m, 0 <= y <= 30)
@objective(m, Max, 5x + 3y)
@constraint(m, 1x + 5y <= 3.0)
print(m)
status = solve(m)
println("Objective value: ", getobjectivevalue(m))
println("x = ", getvalue(x))
println("y = ", getvalue(y))
You can also find the zipped sources of the latest release here https://github.com/JuliaOpt/JuMP.jl/releases/tag/v0.18.4, but of course as new releases are published the number will change so the most reliable place to look at the codes are examples that JuMP has on your local machine.
Thanks this worked. This is quite hidden for someone new to Julia.
– Stein
Nov 22 at 10:29
add a comment |
up vote
3
down vote
accepted
You are looking at the example from master
branch from the GitHub repository. There are breaking changes in JuMP API since its last release.
You should look at basic.jl file in your local repository. It should be located in a directory location like ~/.julia/packages/JuMP/Xvn0n/examples/basic.jl
(the Xvn0n
part might be different in your case but the path pattern should be the same; if you are on Windows then ~
is a directory of your user profile).
The example you are referring to looks like this in the released version of the package:
using JuMP, Clp
m = Model(solver = ClpSolver())
@variable(m, 0 <= x <= 2)
@variable(m, 0 <= y <= 30)
@objective(m, Max, 5x + 3y)
@constraint(m, 1x + 5y <= 3.0)
print(m)
status = solve(m)
println("Objective value: ", getobjectivevalue(m))
println("x = ", getvalue(x))
println("y = ", getvalue(y))
You can also find the zipped sources of the latest release here https://github.com/JuliaOpt/JuMP.jl/releases/tag/v0.18.4, but of course as new releases are published the number will change so the most reliable place to look at the codes are examples that JuMP has on your local machine.
Thanks this worked. This is quite hidden for someone new to Julia.
– Stein
Nov 22 at 10:29
add a comment |
up vote
3
down vote
accepted
up vote
3
down vote
accepted
You are looking at the example from master
branch from the GitHub repository. There are breaking changes in JuMP API since its last release.
You should look at basic.jl file in your local repository. It should be located in a directory location like ~/.julia/packages/JuMP/Xvn0n/examples/basic.jl
(the Xvn0n
part might be different in your case but the path pattern should be the same; if you are on Windows then ~
is a directory of your user profile).
The example you are referring to looks like this in the released version of the package:
using JuMP, Clp
m = Model(solver = ClpSolver())
@variable(m, 0 <= x <= 2)
@variable(m, 0 <= y <= 30)
@objective(m, Max, 5x + 3y)
@constraint(m, 1x + 5y <= 3.0)
print(m)
status = solve(m)
println("Objective value: ", getobjectivevalue(m))
println("x = ", getvalue(x))
println("y = ", getvalue(y))
You can also find the zipped sources of the latest release here https://github.com/JuliaOpt/JuMP.jl/releases/tag/v0.18.4, but of course as new releases are published the number will change so the most reliable place to look at the codes are examples that JuMP has on your local machine.
You are looking at the example from master
branch from the GitHub repository. There are breaking changes in JuMP API since its last release.
You should look at basic.jl file in your local repository. It should be located in a directory location like ~/.julia/packages/JuMP/Xvn0n/examples/basic.jl
(the Xvn0n
part might be different in your case but the path pattern should be the same; if you are on Windows then ~
is a directory of your user profile).
The example you are referring to looks like this in the released version of the package:
using JuMP, Clp
m = Model(solver = ClpSolver())
@variable(m, 0 <= x <= 2)
@variable(m, 0 <= y <= 30)
@objective(m, Max, 5x + 3y)
@constraint(m, 1x + 5y <= 3.0)
print(m)
status = solve(m)
println("Objective value: ", getobjectivevalue(m))
println("x = ", getvalue(x))
println("y = ", getvalue(y))
You can also find the zipped sources of the latest release here https://github.com/JuliaOpt/JuMP.jl/releases/tag/v0.18.4, but of course as new releases are published the number will change so the most reliable place to look at the codes are examples that JuMP has on your local machine.
answered Nov 22 at 9:59
Bogumił Kamiński
11.6k11120
11.6k11120
Thanks this worked. This is quite hidden for someone new to Julia.
– Stein
Nov 22 at 10:29
add a comment |
Thanks this worked. This is quite hidden for someone new to Julia.
– Stein
Nov 22 at 10:29
Thanks this worked. This is quite hidden for someone new to Julia.
– Stein
Nov 22 at 10:29
Thanks this worked. This is quite hidden for someone new to Julia.
– Stein
Nov 22 at 10:29
add a comment |
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