Re: [julia-users] Got an exception of type ErrorException outside of a @test: type DataType has no field FactorMargin
Hey Yichao, it's late here, I will continue tomorrow. Thanks for your help!
> On Nov 23, 2016, at 22:59, Yichao Yu wrote:
>
>> On Wed, Nov 23, 2016 at 7:31 PM, Kevin Liu wrote:
>> In `permute_dims = [Remain_dims,Remove_dims]`, both Remain and Remove_dims
>
> Which is why it is wrong.
>
>> are vectors. Even if I `permute_dims = [Remain_dims]`, I still get the same
>> error.
>
>
> julia> [[1]]
> 1-element Array{Array{Int64,1},1}:
> [1]
>
> julia> [[1];]
> 1-element Array{Int64,1}:
> 1
>
>
>>
>>> On Wed, Nov 23, 2016 at 9:54 PM, Yichao Yu wrote:
>>>
On Wed, Nov 23, 2016 at 6:50 PM, Kevin Liu wrote:
Attached!
>>>
>>> ```
>>> help?> permutedims
>>> search: permutedims permutedims! ipermutedims
>>>
>>> permutedims(A, perm)
>>>
>>> Permute the dimensions of array A. perm is a vector specifying a
>>> permutation
>>> of length ndims(A). This is a generalization of transpose for
>>> multi-dimensional arrays. Transpose is equivalent to permutedims(A,
>>> [2,1]).
>>>
>>> julia> A = reshape(collect(1:8), (2,2,2))
>>> 2×2×2 Array{Int64,3}:
>>> [:, :, 1] =
>>> 1 3
>>> 2 4
>>>
>>> [:, :, 2] =
>>> 5 7
>>> 6 8
>>>
>>> julia> permutedims(A, [3, 2, 1])
>>> 2×2×2 Array{Int64,3}:
>>> [:, :, 1] =
>>> 1 3
>>> 5 7
>>>
>>> [:, :, 2] =
>>> 2 4
>>> 6 8
>>> ```
>>>
>>> You are not giving `permutedims` the correct second parameters
>>>
>>> (https://github.com/hpoit/MLN.jl/blob/1c13725666f34587e57c4a1757e6222cacaeab73/BN/src/FactorOperations.jl#L66).
>>>
>>>
> On Wed, Nov 23, 2016 at 9:44 PM, Yichao Yu wrote:
>
>> On Wed, Nov 23, 2016 at 4:02 PM, Kevin Liu wrote:
>> Yichao, would you give me some direction? I am a bit lost.
>
> Post and/or identify the error after you've fixed the `Factor.` problem
>
>>
>>> On Tue, Nov 22, 2016 at 7:58 PM, Kevin Liu wrote:
>>>
>>> Do you want a cut in the profits for helping me get it to work? It's
>>> a
>>> marathon. I still have Markov Random Field and Markov Logic Network
>>> in
>>> line... and two of the largest private Brazilian banks on standby.
>>>
> On Nov 22, 2016, at 19:39, Yichao Yu wrote:
>
> On Tue, Nov 22, 2016 at 4:23 PM, Kevin Liu
> wrote:
> I would like to remove variable "c" from factor C. I tried
> removing
> `Factor.` but it didn't work.
There might be (almost certainly) multiple mistakes in the code so
fixing one won't fix all of them.
>
>> On Tue, Nov 22, 2016 at 6:54 PM, Yichao Yu
>> wrote:
>>
>>> On Tue, Nov 22, 2016 at 3:45 PM, Kevin Liu
>>> wrote:
>>> Yichao, I used a hashtag in the last message to show you what I
>>> want
>>> to
>>> do. Is it clear?
>>
>> No
>>
>> I'm just talking about the `Factor.` in the line I linked. I
>> don't
>> know what you want to access. Do you just want `FactorMargin`?
>> What's
>> the extra `Factor.` for?
>>
>>>
>>> On Nov 22, 2016, at 18:27, Yichao Yu wrote:
>>>
> Yichao and DPSanders, I have already used instances of Factor
> on
> runtests.jl, instances A, B, and C
AFAICT you are still accessing a non existing field of a
type[1]
and
it's unclear what you actually want to do.
[1]
https://github.com/hpoit/MLN.jl/blob/1c13725666f34587e57c4a1757e6222cacaeab73/BN/src/FactorOperations.jl#L87
>
> A=Factor(["a", "b"],[3, 2],[0.5, 0.1, 0.3, 0.8, 0, 0.9])
> B=Factor(["b", "c"],[2, 2],[0.5, 0.1, 0.7, 0.2])
> C = FactorProduct(A, B)
> FactorDropMargin(C, ["c"])
>
> Do you recommend I make any of the functions in
> FactorOperations.jl
> into inner constructors of `type Factor` in Factor.jl?
>
>
>>
>>
>>
>>
Re: [julia-users] Got an exception of type ErrorException outside of a @test: type DataType has no field FactorMargin
On Wed, Nov 23, 2016 at 7:31 PM, Kevin Liu wrote:
> In `permute_dims = [Remain_dims,Remove_dims]`, both Remain and Remove_dims
Which is why it is wrong.
> are vectors. Even if I `permute_dims = [Remain_dims]`, I still get the same
> error.
julia> [[1]]
1-element Array{Array{Int64,1},1}:
[1]
julia> [[1];]
1-element Array{Int64,1}:
1
>
> On Wed, Nov 23, 2016 at 9:54 PM, Yichao Yu wrote:
>>
>> On Wed, Nov 23, 2016 at 6:50 PM, Kevin Liu wrote:
>> > Attached!
>>
>> ```
>> help?> permutedims
>> search: permutedims permutedims! ipermutedims
>>
>> permutedims(A, perm)
>>
>> Permute the dimensions of array A. perm is a vector specifying a
>> permutation
>> of length ndims(A). This is a generalization of transpose for
>> multi-dimensional arrays. Transpose is equivalent to permutedims(A,
>> [2,1]).
>>
>> julia> A = reshape(collect(1:8), (2,2,2))
>> 2×2×2 Array{Int64,3}:
>> [:, :, 1] =
>>1 3
>>2 4
>>
>> [:, :, 2] =
>>5 7
>>6 8
>>
>> julia> permutedims(A, [3, 2, 1])
>> 2×2×2 Array{Int64,3}:
>> [:, :, 1] =
>>1 3
>>5 7
>>
>> [:, :, 2] =
>>2 4
>>6 8
>> ```
>>
>> You are not giving `permutedims` the correct second parameters
>>
>> (https://github.com/hpoit/MLN.jl/blob/1c13725666f34587e57c4a1757e6222cacaeab73/BN/src/FactorOperations.jl#L66).
>>
>>
>> >
>> > On Wed, Nov 23, 2016 at 9:44 PM, Yichao Yu wrote:
>> >>
>> >> On Wed, Nov 23, 2016 at 4:02 PM, Kevin Liu wrote:
>> >> > Yichao, would you give me some direction? I am a bit lost.
>> >>
>> >> Post and/or identify the error after you've fixed the `Factor.` problem
>> >>
>> >> >
>> >> > On Tue, Nov 22, 2016 at 7:58 PM, Kevin Liu wrote:
>> >> >>
>> >> >> Do you want a cut in the profits for helping me get it to work? It's
>> >> >> a
>> >> >> marathon. I still have Markov Random Field and Markov Logic Network
>> >> >> in
>> >> >> line... and two of the largest private Brazilian banks on standby.
>> >> >>
>> >> >> > On Nov 22, 2016, at 19:39, Yichao Yu wrote:
>> >> >> >
>> >> >> >> On Tue, Nov 22, 2016 at 4:23 PM, Kevin Liu
>> >> >> >> wrote:
>> >> >> >> I would like to remove variable "c" from factor C. I tried
>> >> >> >> removing
>> >> >> >> `Factor.` but it didn't work.
>> >> >> >
>> >> >> > There might be (almost certainly) multiple mistakes in the code so
>> >> >> > fixing one won't fix all of them.
>> >> >> >
>> >> >> >>
>> >> >> >>> On Tue, Nov 22, 2016 at 6:54 PM, Yichao Yu
>> >> >> >>> wrote:
>> >> >> >>>
>> >> >> On Tue, Nov 22, 2016 at 3:45 PM, Kevin Liu
>> >> >> wrote:
>> >> >> Yichao, I used a hashtag in the last message to show you what I
>> >> >> want
>> >> >> to
>> >> >> do. Is it clear?
>> >> >> >>>
>> >> >> >>> No
>> >> >> >>>
>> >> >> >>> I'm just talking about the `Factor.` in the line I linked. I
>> >> >> >>> don't
>> >> >> >>> know what you want to access. Do you just want `FactorMargin`?
>> >> >> >>> What's
>> >> >> >>> the extra `Factor.` for?
>> >> >> >>>
>> >> >>
>> >> >> On Nov 22, 2016, at 18:27, Yichao Yu wrote:
>> >> >>
>> >> >> >> Yichao and DPSanders, I have already used instances of Factor
>> >> >> >> on
>> >> >> >> runtests.jl, instances A, B, and C
>> >> >> >
>> >> >> > AFAICT you are still accessing a non existing field of a
>> >> >> > type[1]
>> >> >> > and
>> >> >> > it's unclear what you actually want to do.
>> >> >> >
>> >> >> > [1]
>> >> >> >
>> >> >> >
>> >> >> >
>> >> >> > https://github.com/hpoit/MLN.jl/blob/1c13725666f34587e57c4a1757e6222cacaeab73/BN/src/FactorOperations.jl#L87
>> >> >> >
>> >> >> >>
>> >> >> >> A=Factor(["a", "b"],[3, 2],[0.5, 0.1, 0.3, 0.8, 0, 0.9])
>> >> >> >> B=Factor(["b", "c"],[2, 2],[0.5, 0.1, 0.7, 0.2])
>> >> >> >> C = FactorProduct(A, B)
>> >> >> >> FactorDropMargin(C, ["c"])
>> >> >> >>
>> >> >> >> Do you recommend I make any of the functions in
>> >> >> >> FactorOperations.jl
>> >> >> >> into inner constructors of `type Factor` in Factor.jl?
>> >> >> >>
>> >> >> >>
>> >> >
>> >> >
>> >
>> >
>
>
Re: [julia-users] Got an exception of type ErrorException outside of a @test: type DataType has no field FactorMargin
In `permute_dims = [Remain_dims,Remove_dims]`, both Remain and Remove_dims
are vectors. Even if I `permute_dims = [Remain_dims]`, I still get the same
error.
On Wed, Nov 23, 2016 at 9:54 PM, Yichao Yu wrote:
> On Wed, Nov 23, 2016 at 6:50 PM, Kevin Liu wrote:
> > Attached!
>
> ```
> help?> permutedims
> search: permutedims permutedims! ipermutedims
>
> permutedims(A, perm)
>
> Permute the dimensions of array A. perm is a vector specifying a
> permutation
> of length ndims(A). This is a generalization of transpose for
> multi-dimensional arrays. Transpose is equivalent to permutedims(A,
> [2,1]).
>
> julia> A = reshape(collect(1:8), (2,2,2))
> 2×2×2 Array{Int64,3}:
> [:, :, 1] =
>1 3
>2 4
>
> [:, :, 2] =
>5 7
>6 8
>
> julia> permutedims(A, [3, 2, 1])
> 2×2×2 Array{Int64,3}:
> [:, :, 1] =
>1 3
>5 7
>
> [:, :, 2] =
>2 4
>6 8
> ```
>
> You are not giving `permutedims` the correct second parameters
> (https://github.com/hpoit/MLN.jl/blob/1c13725666f34587e57c4a1757e622
> 2cacaeab73/BN/src/FactorOperations.jl#L66).
>
>
> >
> > On Wed, Nov 23, 2016 at 9:44 PM, Yichao Yu wrote:
> >>
> >> On Wed, Nov 23, 2016 at 4:02 PM, Kevin Liu wrote:
> >> > Yichao, would you give me some direction? I am a bit lost.
> >>
> >> Post and/or identify the error after you've fixed the `Factor.` problem
> >>
> >> >
> >> > On Tue, Nov 22, 2016 at 7:58 PM, Kevin Liu wrote:
> >> >>
> >> >> Do you want a cut in the profits for helping me get it to work? It's
> a
> >> >> marathon. I still have Markov Random Field and Markov Logic Network
> in
> >> >> line... and two of the largest private Brazilian banks on standby.
> >> >>
> >> >> > On Nov 22, 2016, at 19:39, Yichao Yu wrote:
> >> >> >
> >> >> >> On Tue, Nov 22, 2016 at 4:23 PM, Kevin Liu
> wrote:
> >> >> >> I would like to remove variable "c" from factor C. I tried
> removing
> >> >> >> `Factor.` but it didn't work.
> >> >> >
> >> >> > There might be (almost certainly) multiple mistakes in the code so
> >> >> > fixing one won't fix all of them.
> >> >> >
> >> >> >>
> >> >> >>> On Tue, Nov 22, 2016 at 6:54 PM, Yichao Yu
> >> >> >>> wrote:
> >> >> >>>
> >> >> On Tue, Nov 22, 2016 at 3:45 PM, Kevin Liu
> >> >> wrote:
> >> >> Yichao, I used a hashtag in the last message to show you what I
> >> >> want
> >> >> to
> >> >> do. Is it clear?
> >> >> >>>
> >> >> >>> No
> >> >> >>>
> >> >> >>> I'm just talking about the `Factor.` in the line I linked. I
> don't
> >> >> >>> know what you want to access. Do you just want `FactorMargin`?
> >> >> >>> What's
> >> >> >>> the extra `Factor.` for?
> >> >> >>>
> >> >>
> >> >> On Nov 22, 2016, at 18:27, Yichao Yu wrote:
> >> >>
> >> >> >> Yichao and DPSanders, I have already used instances of Factor
> on
> >> >> >> runtests.jl, instances A, B, and C
> >> >> >
> >> >> > AFAICT you are still accessing a non existing field of a
> type[1]
> >> >> > and
> >> >> > it's unclear what you actually want to do.
> >> >> >
> >> >> > [1]
> >> >> >
> >> >> >
> >> >> > https://github.com/hpoit/MLN.jl/blob/
> 1c13725666f34587e57c4a1757e6222cacaeab73/BN/src/FactorOperations.jl#L87
> >> >> >
> >> >> >>
> >> >> >> A=Factor(["a", "b"],[3, 2],[0.5, 0.1, 0.3, 0.8, 0, 0.9])
> >> >> >> B=Factor(["b", "c"],[2, 2],[0.5, 0.1, 0.7, 0.2])
> >> >> >> C = FactorProduct(A, B)
> >> >> >> FactorDropMargin(C, ["c"])
> >> >> >>
> >> >> >> Do you recommend I make any of the functions in
> >> >> >> FactorOperations.jl
> >> >> >> into inner constructors of `type Factor` in Factor.jl?
> >> >> >>
> >> >> >>
> >> >
> >> >
> >
> >
>
Re: [julia-users] Got an exception of type ErrorException outside of a @test: type DataType has no field FactorMargin
On Wed, Nov 23, 2016 at 6:50 PM, Kevin Liu wrote:
> Attached!
```
help?> permutedims
search: permutedims permutedims! ipermutedims
permutedims(A, perm)
Permute the dimensions of array A. perm is a vector specifying a permutation
of length ndims(A). This is a generalization of transpose for
multi-dimensional arrays. Transpose is equivalent to permutedims(A, [2,1]).
julia> A = reshape(collect(1:8), (2,2,2))
2×2×2 Array{Int64,3}:
[:, :, 1] =
1 3
2 4
[:, :, 2] =
5 7
6 8
julia> permutedims(A, [3, 2, 1])
2×2×2 Array{Int64,3}:
[:, :, 1] =
1 3
5 7
[:, :, 2] =
2 4
6 8
```
You are not giving `permutedims` the correct second parameters
(https://github.com/hpoit/MLN.jl/blob/1c13725666f34587e57c4a1757e6222cacaeab73/BN/src/FactorOperations.jl#L66).
>
> On Wed, Nov 23, 2016 at 9:44 PM, Yichao Yu wrote:
>>
>> On Wed, Nov 23, 2016 at 4:02 PM, Kevin Liu wrote:
>> > Yichao, would you give me some direction? I am a bit lost.
>>
>> Post and/or identify the error after you've fixed the `Factor.` problem
>>
>> >
>> > On Tue, Nov 22, 2016 at 7:58 PM, Kevin Liu wrote:
>> >>
>> >> Do you want a cut in the profits for helping me get it to work? It's a
>> >> marathon. I still have Markov Random Field and Markov Logic Network in
>> >> line... and two of the largest private Brazilian banks on standby.
>> >>
>> >> > On Nov 22, 2016, at 19:39, Yichao Yu wrote:
>> >> >
>> >> >> On Tue, Nov 22, 2016 at 4:23 PM, Kevin Liu wrote:
>> >> >> I would like to remove variable "c" from factor C. I tried removing
>> >> >> `Factor.` but it didn't work.
>> >> >
>> >> > There might be (almost certainly) multiple mistakes in the code so
>> >> > fixing one won't fix all of them.
>> >> >
>> >> >>
>> >> >>> On Tue, Nov 22, 2016 at 6:54 PM, Yichao Yu
>> >> >>> wrote:
>> >> >>>
>> >> On Tue, Nov 22, 2016 at 3:45 PM, Kevin Liu
>> >> wrote:
>> >> Yichao, I used a hashtag in the last message to show you what I
>> >> want
>> >> to
>> >> do. Is it clear?
>> >> >>>
>> >> >>> No
>> >> >>>
>> >> >>> I'm just talking about the `Factor.` in the line I linked. I don't
>> >> >>> know what you want to access. Do you just want `FactorMargin`?
>> >> >>> What's
>> >> >>> the extra `Factor.` for?
>> >> >>>
>> >>
>> >> On Nov 22, 2016, at 18:27, Yichao Yu wrote:
>> >>
>> >> >> Yichao and DPSanders, I have already used instances of Factor on
>> >> >> runtests.jl, instances A, B, and C
>> >> >
>> >> > AFAICT you are still accessing a non existing field of a type[1]
>> >> > and
>> >> > it's unclear what you actually want to do.
>> >> >
>> >> > [1]
>> >> >
>> >> >
>> >> > https://github.com/hpoit/MLN.jl/blob/1c13725666f34587e57c4a1757e6222cacaeab73/BN/src/FactorOperations.jl#L87
>> >> >
>> >> >>
>> >> >> A=Factor(["a", "b"],[3, 2],[0.5, 0.1, 0.3, 0.8, 0, 0.9])
>> >> >> B=Factor(["b", "c"],[2, 2],[0.5, 0.1, 0.7, 0.2])
>> >> >> C = FactorProduct(A, B)
>> >> >> FactorDropMargin(C, ["c"])
>> >> >>
>> >> >> Do you recommend I make any of the functions in
>> >> >> FactorOperations.jl
>> >> >> into inner constructors of `type Factor` in Factor.jl?
>> >> >>
>> >> >>
>> >
>> >
>
>
Re: [julia-users] Got an exception of type ErrorException outside of a @test: type DataType has no field FactorMargin
On Wed, Nov 23, 2016 at 4:02 PM, Kevin Liu wrote: > Yichao, would you give me some direction? I am a bit lost. Post and/or identify the error after you've fixed the `Factor.` problem > > On Tue, Nov 22, 2016 at 7:58 PM, Kevin Liu wrote: >> >> Do you want a cut in the profits for helping me get it to work? It's a >> marathon. I still have Markov Random Field and Markov Logic Network in >> line... and two of the largest private Brazilian banks on standby. >> >> > On Nov 22, 2016, at 19:39, Yichao Yu wrote: >> > >> >> On Tue, Nov 22, 2016 at 4:23 PM, Kevin Liu wrote: >> >> I would like to remove variable "c" from factor C. I tried removing >> >> `Factor.` but it didn't work. >> > >> > There might be (almost certainly) multiple mistakes in the code so >> > fixing one won't fix all of them. >> > >> >> >> >>> On Tue, Nov 22, 2016 at 6:54 PM, Yichao Yu wrote: >> >>> >> On Tue, Nov 22, 2016 at 3:45 PM, Kevin Liu wrote: >> Yichao, I used a hashtag in the last message to show you what I want >> to >> do. Is it clear? >> >>> >> >>> No >> >>> >> >>> I'm just talking about the `Factor.` in the line I linked. I don't >> >>> know what you want to access. Do you just want `FactorMargin`? What's >> >>> the extra `Factor.` for? >> >>> >> >> On Nov 22, 2016, at 18:27, Yichao Yu wrote: >> >> >> Yichao and DPSanders, I have already used instances of Factor on >> >> runtests.jl, instances A, B, and C >> > >> > AFAICT you are still accessing a non existing field of a type[1] and >> > it's unclear what you actually want to do. >> > >> > [1] >> > >> > https://github.com/hpoit/MLN.jl/blob/1c13725666f34587e57c4a1757e6222cacaeab73/BN/src/FactorOperations.jl#L87 >> > >> >> >> >> A=Factor(["a", "b"],[3, 2],[0.5, 0.1, 0.3, 0.8, 0, 0.9]) >> >> B=Factor(["b", "c"],[2, 2],[0.5, 0.1, 0.7, 0.2]) >> >> C = FactorProduct(A, B) >> >> FactorDropMargin(C, ["c"]) >> >> >> >> Do you recommend I make any of the functions in FactorOperations.jl >> >> into inner constructors of `type Factor` in Factor.jl? >> >> >> >> > >
Re: [julia-users] Updated performance tips?
I have copied my code in the below link (Julia user group), let me know if
you cant access that
https://discourse.julialang.org/t/julia-call-from-python3-running-in-single-core/508/5
On Wed, Nov 23, 2016 at 2:03 PM, Douglas Bates wrote:
> On Tuesday, November 22, 2016 at 1:12:26 PM UTC-6, Harish Kumar wrote:
> > I found the cause for this ... When i run julia 0.3.2 or 0.5 as
> standalone (mix model) it uses all the available cores from my server, so
> it was fast.
>
> Fitting a linear mixed effects model only uses multiple threads for the
> BLAS (Basic Linear Algebra Subroutine) calls and a few LAPACK calls. In
> Julia v0.5 you may be able to set the number of threads for the BLAS by
> calling, say,
>
> BLAS.set_num_threads(4)
>
> (or some other number) before trying to fit a model. Be aware that
> increasing the number of threads doesn't always make things faster. You
> may need to do a bit of experimentation to determine a suitable number of
> threads.
>
> Can you describe the formula you are using? If you are trying to fit a
> "maximal" model with large-dimensional vector-valued random effects for
> crossed grouping factors you should be aware that most of the time fitting
> such models is just a convenient way of burning up a lot of computing time.
>
>
> > If i call Julia from Python (Pyjulia), i see only one core is busy with
> python process (100% cpu) and all other cores are free. Can you help me
> how can i force Pyjulia/python to use available cores from my server?
> >
> >
> > Regards,
> > Harish
> >
> >
> >
> >
> >
> >
> >
> >
> > On Sat, Nov 19, 2016 at 8:32 PM, Mauro wrote:
> > On Sat, 2016-11-19 at 20:48, Harish Kumar wrote:
> >
> > > Thank you. I agree on python.. but my question was did they update the
> >
> > > Pyjulia libraries for latest Julia version? . We tried with 0.4.3 which
> >
> > > failed 6 months back. So we revered to 0.3.4. Or is this library remain
> >
> > > same for all Julia versions?
> >
> > >
> >
> > > Any suggestion on this?
> >
> >
> >
> > They are testing against the latest release, i.e. 0.5:
> >
> > https://github.com/JuliaPy/pyjulia/blob/master/.travis.yml
> >
> >
> >
> > You should try and file an issue if it doesn't work. 6 months are a
> >
> > long time at the current julia development pace.
> >
> >
> >
> >
> >
> > >
> >
> > > On Sat, Nov 19, 2016 at 7:38 PM, Mauro wrote:
> >
> > >
> >
> > >> On Sat, 2016-11-19 at 18:36, Harish Kumar
> >
> > >> wrote:
> >
> > >> > Will it support Python 3.4 ? I am calling this from pyjulia
> interface
> >
> > >>
> >
> > >> https://github.com/JuliaPy/pyjulia says that it is tested against
> 3.5,
> >
> > >> but it doesn't say that 3.4 is not supported. So you should try.
> >
> > >>
> >
> > >> > On Nov 19, 2016 4:58 PM, "Mauro" wrote:
> >
> > >> >
> >
> > >> >> Julia 0.3.12, that's a stone-age version of Julia. You should
> move to
> >
> > >> 0.5!
> >
> > >> >>
> >
> > >> >> On Sat, 2016-11-19 at 16:42, Harish Kumar
> >
> > >> >> wrote:
> >
> > >> >> > I am using Version 0.3.12 calling from python (pyjulia). I do
> LME fit
> >
> > >> >> with
> >
> > >> >> > 2.8 M rows and 60-70 Variables. It is taking 2 hours just to
> model (+
> >
> > >> >> data
> >
> > >> >> > transfer time). Any tips?
> >
> > >> >> > using MixedModels
> >
> > >> >> > modelREML = lmm({formula}, dataset)
> >
> > >> >> > reml!(modelREML,true)
> >
> > >> >> > lmeModel = fit(modelREML)
> >
> > >> >> > fixedDF = DataFrame(fixedEffVar =
> coeftable(lmeModel).rownms,
> >
> > >> >> estimate
> >
> > >> >> > = coeftable(lmeModel).mat[:,1],
> >
> > >> >> > stdError = coeftable(lmeModel).mat[:,2],zVal
> =
> >
> > >> >> > coeftable(lmeModel).mat[:,3])
> >
> > >> >> >
> >
> > >> >> > On Tuesday, February 23, 2016 at 9:16:47 AM UTC-6, Stefan
> Karpinski
> >
> > >> >> wrote:
> >
> > >> >> >>
> >
> > >> >> >> I'm glad that particular slow case got faster! If you want to
> submit
> >
> > >> >> some
> >
> > >> >> >> reduced version of it as a performance test, we could still
> include
> >
> > >> it
> >
> > >> >> in
> >
> > >> >> >> our perf suite. And of course, if you find that anything else
> has
> >
> > >> ever
> >
> > >> >> >> slowed down, please don't hesitate to file an issue.
> >
> > >> >> >>
> >
> > >> >> >> On Tue, Feb 23, 2016 at 9:55 AM, Jonathan Goldfarb <
> >
> > >> jgol...@gmail.com
> >
> > >> >> >> > wrote:
> >
> > >> >> >>
> >
> > >> >> >>> Yes, understood about difficulty keeping track of regressions.
> I was
> >
> > >> >> >>> originally going to send a message relating up to 2x longer
> test
> >
> > >> time
> >
> > >> >> on
> >
> > >> >> >>> the same code on Travis, but it appears as though something has
> >
> > >> >> changed in
> >
> > >> >> >>> the nightly build available to CI that now gives significantly
> >
> > >> faster
> >
> > >> >> >>> builds, even though the previous poor performance had been
> >
> > >> >> dependable...
> >
> > >> >> >>> Evidently that build is not as up-to-date as I thoug
Re: [julia-users] Updated performance tips?
On Tuesday, November 22, 2016 at 1:12:26 PM UTC-6, Harish Kumar wrote:
> I found the cause for this ... When i run julia 0.3.2 or 0.5 as standalone
> (mix model) it uses all the available cores from my server, so it was fast.
Fitting a linear mixed effects model only uses multiple threads for the BLAS
(Basic Linear Algebra Subroutine) calls and a few LAPACK calls. In Julia v0.5
you may be able to set the number of threads for the BLAS by calling, say,
BLAS.set_num_threads(4)
(or some other number) before trying to fit a model. Be aware that increasing
the number of threads doesn't always make things faster. You may need to do a
bit of experimentation to determine a suitable number of threads.
Can you describe the formula you are using? If you are trying to fit a
"maximal" model with large-dimensional vector-valued random effects for crossed
grouping factors you should be aware that most of the time fitting such models
is just a convenient way of burning up a lot of computing time.
> If i call Julia from Python (Pyjulia), i see only one core is busy with
> python process (100% cpu) and all other cores are free. Can you help me how
> can i force Pyjulia/python to use available cores from my server?
>
>
> Regards,
> Harish
>
>
>
>
>
>
>
>
> On Sat, Nov 19, 2016 at 8:32 PM, Mauro wrote:
> On Sat, 2016-11-19 at 20:48, Harish Kumar wrote:
>
> > Thank you. I agree on python.. but my question was did they update the
>
> > Pyjulia libraries for latest Julia version? . We tried with 0.4.3 which
>
> > failed 6 months back. So we revered to 0.3.4. Or is this library remain
>
> > same for all Julia versions?
>
> >
>
> > Any suggestion on this?
>
>
>
> They are testing against the latest release, i.e. 0.5:
>
> https://github.com/JuliaPy/pyjulia/blob/master/.travis.yml
>
>
>
> You should try and file an issue if it doesn't work. 6 months are a
>
> long time at the current julia development pace.
>
>
>
>
>
> >
>
> > On Sat, Nov 19, 2016 at 7:38 PM, Mauro wrote:
>
> >
>
> >> On Sat, 2016-11-19 at 18:36, Harish Kumar
>
> >> wrote:
>
> >> > Will it support Python 3.4 ? I am calling this from pyjulia interface
>
> >>
>
> >> https://github.com/JuliaPy/pyjulia says that it is tested against 3.5,
>
> >> but it doesn't say that 3.4 is not supported. So you should try.
>
> >>
>
> >> > On Nov 19, 2016 4:58 PM, "Mauro" wrote:
>
> >> >
>
> >> >> Julia 0.3.12, that's a stone-age version of Julia. You should move to
>
> >> 0.5!
>
> >> >>
>
> >> >> On Sat, 2016-11-19 at 16:42, Harish Kumar
>
> >> >> wrote:
>
> >> >> > I am using Version 0.3.12 calling from python (pyjulia). I do LME fit
>
> >> >> with
>
> >> >> > 2.8 M rows and 60-70 Variables. It is taking 2 hours just to model (+
>
> >> >> data
>
> >> >> > transfer time). Any tips?
>
> >> >> > using MixedModels
>
> >> >> > modelREML = lmm({formula}, dataset)
>
> >> >> > reml!(modelREML,true)
>
> >> >> > lmeModel = fit(modelREML)
>
> >> >> > fixedDF = DataFrame(fixedEffVar = coeftable(lmeModel).rownms,
>
> >> >> estimate
>
> >> >> > = coeftable(lmeModel).mat[:,1],
>
> >> >> > stdError = coeftable(lmeModel).mat[:,2],zVal =
>
> >> >> > coeftable(lmeModel).mat[:,3])
>
> >> >> >
>
> >> >> > On Tuesday, February 23, 2016 at 9:16:47 AM UTC-6, Stefan Karpinski
>
> >> >> wrote:
>
> >> >> >>
>
> >> >> >> I'm glad that particular slow case got faster! If you want to submit
>
> >> >> some
>
> >> >> >> reduced version of it as a performance test, we could still include
>
> >> it
>
> >> >> in
>
> >> >> >> our perf suite. And of course, if you find that anything else has
>
> >> ever
>
> >> >> >> slowed down, please don't hesitate to file an issue.
>
> >> >> >>
>
> >> >> >> On Tue, Feb 23, 2016 at 9:55 AM, Jonathan Goldfarb <
>
> >> jgol...@gmail.com
>
> >> >> >> > wrote:
>
> >> >> >>
>
> >> >> >>> Yes, understood about difficulty keeping track of regressions. I was
>
> >> >> >>> originally going to send a message relating up to 2x longer test
>
> >> time
>
> >> >> on
>
> >> >> >>> the same code on Travis, but it appears as though something has
>
> >> >> changed in
>
> >> >> >>> the nightly build available to CI that now gives significantly
>
> >> faster
>
> >> >> >>> builds, even though the previous poor performance had been
>
> >> >> dependable...
>
> >> >> >>> Evidently that build is not as up-to-date as I thought. Our code is
>
> >> >> >>> currently not open source, but should be soon after which I can
>
> >> share
>
> >> >> an
>
> >> >> >>> example.
>
> >> >> >>>
>
> >> >> >>> Thanks for your comments, and thanks again for your work on Julia.
>
> >> >> >>>
>
> >> >> >>> -Max
>
> >> >> >>>
>
> >> >> >>>
>
> >> >> >>> On Monday, February 22, 2016 at 11:12:58 AM UTC-5, Stefan Karpinski
>
> >> >> wrote:
>
> >> >>
>
> >> >> Yes, ideally code should not get slower with new releases –
>
> >> >> unfortunate
[julia-users] Re: [ANN] GLVisualize
On Monday, November 21, 2016 at 1:23:05 PM UTC-8, Simon Danisch wrote: > I finally tagged a new version of GLVisualize with a lot of new goodies and > overall improved stability. > For more information please see my blog post: > > > GLVisualize - a modern graphics platform for julia > > > > [Lets deprecate Julia-Users, so please answer on the discourse thread] > > > Best, > Simon I'm going to play with this over the Thanksgiving break, as it seems very cool.
