[Rd] R optim(method="L-BFGS-B"): unexpected behavior when working with parent environments

[Duncan Murdoch]

It looks as though this happens when calculating numerical gradients:  x 
is reduced by eps, and fn is called; then x is increased by eps, and fn 
is called again.  No check is made that x has other references after the 
first call to fn.

I'll put together a patch if nobody else gets there first...

Duncan Murdoch

On 03/05/2019 7:13 a.m., peter dalgaard wrote:
> Yes, I think you are right. I was at first confused by the fact that after the optim() call,
> 
>> environment(fn)$xx
> [1] 10
>> environment(fn)$ret
> [1] 100.02
> 
> so not 9.999, but this could come from x being assigned the final value without calling fn.
> 
> -pd
> 
> 
>> On 3 May 2019, at 11:58 , Duncan Murdoch <murdoch.duncan using gmail.com> wrote:
>>
>> Your results below make it look like a bug in optim():  it is not duplicating a value when it should, so changes to x affect xx as well.
>>
>> Duncan Murdoch
>>
>> On 03/05/2019 4:41 a.m., Serguei Sokol wrote:
>>> On 03/05/2019 10:31, Serguei Sokol wrote:
>>>> On 02/05/2019 21:35, Florian Gerber wrote:
>>>>> Dear all,
>>>>>
>>>>> when using optim() for a function that uses the parent environment, I
>>>>> see the following unexpected behavior:
>>>>>
>>>>> makeFn <- function(){
>>>>>       xx <- ret <- NA
>>>>>       fn <- function(x){
>>>>>          if(!is.na(xx) && x==xx){
>>>>>              cat("x=", xx, ", ret=", ret, " (memory)", fill=TRUE, sep="")
>>>>>              return(ret)
>>>>>          }
>>>>>          xx <<- x; ret <<- sum(x^2)
>>>>>          cat("x=", xx, ", ret=", ret, " (calculate)", fill=TRUE, sep="")
>>>>>          ret
>>>>>       }
>>>>>       fn
>>>>> }
>>>>> fn <- makeFn()
>>>>> optim(par=10, fn=fn, method="L-BFGS-B")
>>>>> # x=10, ret=100 (calculate)
>>>>> # x=10.001, ret=100.02 (calculate)
>>>>> # x=9.999, ret=100.02 (memory)
>>>>> # $par
>>>>> # [1] 10
>>>>> #
>>>>> # $value
>>>>> # [1] 100
>>>>> # (...)
>>>>>
>>>>> I would expect that optim() does more than 3 function evaluations and
>>>>> that the optimization converges to 0.
>>>>>
>>>>> Same problem with optim(par=10, fn=fn, method="BFGS").
>>>>>
>>>>> Any ideas?
>>>> I don't have an answer but may be an insight. For some mysterious
>>>> reason xx is getting changed when in should not. Consider:
>>>>> fn=local({n=0; xx=ret=NA; function(x) {n <<- n+1; cat(n, "in
>>>> x,xx,ret=", x, xx, ret, "\n"); if (!is.na(xx) && x==xx) ret else {xx
>>>> <<- x; ret <<- x**2; cat("out x,xx,ret=", x, xx, ret, "\n"); ret}}})
>>>>> optim(par=10, fn=fn, method="L-BFGS-B")
>>>> 1 in x,xx,ret= 10 NA NA
>>>> out x,xx,ret= 10 10 100
>>>> 2 in x,xx,ret= 10.001 10 100
>>>> out x,xx,ret= 10.001 10.001 100.02
>>>> 3 in x,xx,ret= 9.999 9.999 100.02
>>>> $par
>>>> [1] 10
>>>>
>>>> $value
>>>> [1] 100
>>>>
>>>> $counts
>>>> function gradient
>>>>         1        1
>>>>
>>>> $convergence
>>>> [1] 0
>>>>
>>>> $message
>>>> [1] "CONVERGENCE: NORM OF PROJECTED GRADIENT <= PGTOL"
>>>>
>>>> At the third call, xx has value 9.999 while it should have kept the
>>>> value 10.001.
>>>>
>>> A little follow-up: if you untie the link between xx and x by replacing
>>> the expression "xx <<- x" by "xx <<- x+0" it works as expected:
>>>   > fn=local({n=0; xx=ret=NA; function(x) {n <<- n+1; cat(n, "in
>>> x,xx,ret=", x, xx, ret, "\n"); if (!is.na(xx) && x==xx) ret else {xx <<-
>>> x+0; ret <<- x**2; cat("out x,xx,ret=", x, xx, ret, "\n"); ret}}})
>>>   > optim(par=10, fn=fn, method="L-BFGS-B")
>>> 1 in x,xx,ret= 10 NA NA
>>> out x,xx,ret= 10 10 100
>>> 2 in x,xx,ret= 10.001 10 100
>>> out x,xx,ret= 10.001 10.001 100.02
>>> 3 in x,xx,ret= 9.999 10.001 100.02
>>> out x,xx,ret= 9.999 9.999 99.98
>>> 4 in x,xx,ret= 9 9.999 99.98
>>> out x,xx,ret= 9 9 81
>>> 5 in x,xx,ret= 9.001 9 81
>>> out x,xx,ret= 9.001 9.001 81.018
>>> 6 in x,xx,ret= 8.999 9.001 81.018
>>> out x,xx,ret= 8.999 8.999 80.982
>>> 7 in x,xx,ret= 1.776357e-11 8.999 80.982
>>> out x,xx,ret= 1.776357e-11 1.776357e-11 3.155444e-22
>>> 8 in x,xx,ret= 0.001 1.776357e-11 3.155444e-22
>>> out x,xx,ret= 0.001 0.001 1e-06
>>> 9 in x,xx,ret= -0.001 0.001 1e-06
>>> out x,xx,ret= -0.001 -0.001 1e-06
>>> 10 in x,xx,ret= -1.334475e-23 -0.001 1e-06
>>> out x,xx,ret= -1.334475e-23 -1.334475e-23 1.780823e-46
>>> 11 in x,xx,ret= 0.001 -1.334475e-23 1.780823e-46
>>> out x,xx,ret= 0.001 0.001 1e-06
>>> 12 in x,xx,ret= -0.001 0.001 1e-06
>>> out x,xx,ret= -0.001 -0.001 1e-06
>>> $par
>>> [1] -1.334475e-23
>>> $value
>>> [1] 1.780823e-46
>>> $counts
>>> function gradient
>>>          4        4
>>> $convergence
>>> [1] 0
>>> $message
>>> [1] "CONVERGENCE: NORM OF PROJECTED GRADIENT <= PGTOL"
>>> Serguei.
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