[R-SIG-Finance] need apply.paramset logging

[Diego Peroni]

Thanks Ulrich,

process ID as file name seem a valid solution!

Is there a documented way to redirect quantstrat default system out and 
ERROR messages to a file?

Regards

Diego


On 22/03/2016 18:22, Joshua Ulrich wrote:
> On Tue, Mar 22, 2016 at 10:21 AM, Diego Peroni <diegoperoni at vodafone.it> wrote:
>>
>> On 22/03/2016 16:03, Brian G. Peterson wrote:
>>> Executing on minute data won't drive the speed of the path-dependent
>>> rules loop, the total number of signals which need to be evaluated will,
>>> or the inclusion of things like trailing stops.
>> Trailing Stops is my case :-)
>>>
>>> You should be able to sort out which parameter combination is failing
>>> from the print statements.  you should also be able to look at the audit
>>> environment to see which portfolio you're expecting is missing.
>> During multicore execution I'm enable to see print out.
>> I'm sure there is a way to redirect each thread print out to a file but I
>> don't know how.
> doMC runs in separate processes, not threads.  You could add some code
> to print the process ID before each message, or write to a file named
> with the process ID.
>> Sys.getpid()
> [1] 29236
>> registerDoMC(2)
>> foreach(1:6) %dopar% { Sys.getpid() }
> [[1]]
> [1] 29345
>
> [[2]]
> [1] 29346
>
> [[3]]
> [1] 29345
>
> [[4]]
> [1] 29346
>
> [[5]]
> [1] 29345
>
> [[6]]
> [1] 29346
>
>>>
>>> Ultimately, this is a problem in your strategy specification...  You've
>>> created an infeasible parameter combination.  You likely want to debug
>>> what, specifically, is failing, rather than just skipping the failing
>>> parameter set.
>>>
>>> If you're determined to work with the combine funtion...
>> Sure :)
>>>
>>> The .combine argument for foreach is described in the documentation for
>>> foreach.  See ?foreach.
>>>
>>> The combine function in apply.paramset is inside the apply.paramset
>>> function.  We could probably check for a user-supplied combine, or you
>>> could modify the combine function inside apply.paramset yourself.
>> Thanks a lot, I take a look
>>
>>
>> Regards
>>
>> Diego
>>
>>
>>
>>>
>>>
>>> On Tue, 2016-03-22 at 15:45 +0100, Diego Peroni wrote:
>>>> Brain thanks for your answers!
>>>>
>>>> My strategy take a long time to run because it is "minute" based and
>>>> runs over 6 years.
>>>>
>>>> I've just 100 combinations so it is not the best to reduce nsamples to
>>>> find errors.
>>>>
>>>> If I reduce time range (2 o 3 years) it doesn't fail.
>>>>
>>>> If I run sequentially it take a very long time.
>>>>
>>>> The best solution remains the last you have indicated: "custom .combine
>>>> function that could trap errors".
>>>> Does exist some documentation or example to read?
>>>>
>>>> Regards
>>>>
>>>> Diego Peroni
>>>>
>>>>
>>>>
>>>>
>>>> On 22/03/2016 09:46, Brian G. Peterson wrote:
>>>>> On 03/22/2016 03:37 AM, Diego Peroni wrote:
>>>>>> I'm testing paramset combinations with:
>>>>>>
>>>>>> .....
>>>>>> library(doMC)
>>>>>> registerDoMC(cores=detectCores())
>>>>>> paramsetenv = new.env()
>>>>>> results = apply.paramset(qs.strategy, paramset.label = "MACDOPT",
>>>>>> verbose = TRUE,
>>>>>>                              portfolio=qs.strategy, account=qs.strategy,
>>>>>> nsamples=0, audit=paramsetenv)
>>>>>>
>>>>>> but the procedure returns NULL object with this message:
>>>>>>
>>>>>> error calling combine function:
>>>>>> <simpleError: $ operator is invalid for atomic vectors>
>>>>>>
>>>>>> Is there a way to log threads errors?
>>>>>>
>>>>>> Or how can I modify "apply.paramset" function to "catch" single
>>>>>> simultation error or void result and discard it?
>>>>> you're setting
>>>>>
>>>>> nsamples=0
>>>>>
>>>>> so you have zero results to combine.
>>>>>
>>>>> In this case, you told it to run no samples, but I can conceive of a
>>>>> strategy using some MCMC sampler that could fail spontaneously in some
>>>>> circumstances.
>>>>>
> A point of clarification: nsamples = 0 is the default for
> apply.paramset. While confusing, that means that no sampling is done
> and all parameter combinations are evaluated.  Sampling is only done
> when nsamples > 0.
>
>>>>> In a more general sense, you could specify a custom .combine function
>>>>> that could trap errors if there was some possibility that your
>>>>> strategy would fail to return a viable result.
>>>>>
>>>>> A strategy that runs fine in a single core should run fine in
>>>>> apply.paramset.  A reasonable way to start testing this beyond a
>>>>> single parameterization would be to set a small number of samples,
>>>>> like nsamples=50 and run it with registerDoSEQ() to run it sequentially.
>>>>>
>>>>> Regards,
>>>>>
>>>>> Brian
>>>>>
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>>
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