Dictionary says
Integer or Boxed. x u^:n y ↔ x&u^:n y
So they should be the same
(_1+i.5)&({~)^:(<4)4
and
(_+i.5){~^:(<4)4
It seems like a bug in ^:
> On Sep 7, 2016, at 3:39 AM, Erling Hellenäs <erl...@erlinghellenas.se> wrote:
>
> I have the same problem in J8.0.4, Win 64, Library 8.04.15 on Windows 10.
> /Erling
>
>
> On 2016-09-07 07:32, 'Jon Hough' via Programming wrote:
>> This also works
>> (_1+i.5)&{~^:(<4)
>> so you could have used the & conjunction. I'm not sure what you version was
>> actually doing, or how it got stuck in a loop.
>>
>>
>> --------------------------------------------
>> On Wed, 9/7/16, 'Jon Hough' via Programming <programm...@jsoftware.com>
>> wrote:
>>
>> Subject: Re: [Jprogramming] Greatest Increasing Subsequence
>> To: programm...@jsoftware.com
>> Date: Wednesday, September 7, 2016, 2:26 PM
>> Someone more knowledgeable than I can
>> probably give a reason why this works, whereas yours
>> didn't:
>> {&(_1+i.5)^:(<4) 4
>> 4 3 2 1
>> --------------------------------------------
>> On Wed, 9/7/16, Xiao-Yong Jin <jinxiaoy...@gmail.com>
>> wrote:
>> Subject: Re: [Jprogramming] Greatest Increasing
>> Subsequence
>> To: programm...@jsoftware.com
>> Date: Wednesday, September 7, 2016, 12:53 PM
>> I’m trying to rewrite
>> lisM in a readable tacit form but hit something I didn’t
>> understand.
>> Supplying i.n to ^: works fine,
>> but <n does not work like the dictionary says.
>> Namely
>> (_1+i.5){~^:(i.4)4
>> produces
>> 4 3 2 1, but
>> (_1+i.5){~^:(<4)4
>> exhausts all the memory with J804 and
>> J805beta.
>> The dictionary
>> says
>> If n is boxed it
>> must be an atom, and u^:(<m)
>> ↔ u^:(i.m) y if
>> m is a non-negative integer
>> so the above two should be the same. What’s
>> going on here?
>> > On Sep
>> 5, 2016, at 3:17 AM, 'Mike Day' via Programming
>> <programm...@jsoftware.com>
>> wrote:
>> >
>> > Thanks
>> Jon
>> >
>> > lisM
>> isn't really "my" version - I was just
>> translating the pseudo-code...
>> > I expect
>> -without checking! - that its advantage over lisl resides
>> in
>> avoiding the do-it-yourself binary search by using J's
>> built-in dyadic I. , albeit at the expense of an explicit
>> sorted array, which I called mx . I tried
>> limiting the I. search to only the first L items of mx,
>> but with no benefit, at least for the sizes I tried.
>> > The time taken to recover the result is
>> fairly trivial, so I don't suppose my use of
>> > |. x{~(p{~])^:(i.L) L{m
>> > is particularly interesting, but it
>> avoided that explicit while loop.
>> >
>> > Mike
>> >
>> > Please reply to mike_liz....@tiscali.co.uk.
>> > Sent from my iPad
>> >
>> >> On 5 Sep 2016,
>> at 08:07, 'Jon Hough' via Programming <programm...@jsoftware.com>
>> wrote:
>> >>
>> >>
>> Just out of interest, I compared the various results.
>> >> I wrote a fully imperative version,
>> which uses in-place modification of the results array.
>> >>
>> >> I also wrote
>> a version that avoids any while / for loops (because I
>> wanted to avoid using them), and ended up putting
>> >> most of the logic in anonymous verbs.
>> Which is probably a big mistake because that gets very
>> slow.
>> Also barely readable.
>> >>
>> >>
>>
>> NB.===========================================================================
>> >>
>> >> NB. Jon -
>> bizarre version. Uses anonymous verbs for most of the
>> logic.
>> >> NB. Slow and, uses huge amounts of
>> memory.
>> >> appendOrInsert=:(3 :
>> 'insert max' [ 3 :
>> '(max=:<:#lst)[(min=:0)[val=:i{r[i=:y')`(3 :
>> '(lst=:lst,y)[prev=:(_1{lst) y} prev')@.(3 :
>> '(val>({:lst){r)[val=:y{r')
>> >> insert=:(3 : '(prev=:
>> ((y-1){lst)i}prev)[(lst=: i y }lst)' ] ])@:(3 :
>> 'mid'`(3 : 'min=: mid+1')@.(3 :
>> '(val>(mid{lst){r)[(mid=:<.(min+y)%2)')^:(0&<)^:_)
>> >>
>> >> lisJ =: 3 :
>> 0
>> >> r=:y NB.
>> array
>> >>
>> [val=:0[max=:0[mid=:0[min=:0 NB. useful numbers
>> >> lst=:0 NB. list of
>> indices
>> >> prev=: (#y)#0
>> NB. previous indices
>> >> i=:0
>> NB. current index
>> >>
>> >> appendOrInsert"0 >: i.<: #
>> y NB. append the items, or insert them, into lst (and
>> update prev)
>> >> res=:''
>> >> ptr=: _1{lst
>> >>
>> (ptr&buildEx)^:(#lst) res
>> >> |.
>> res
>> >> )
>> >>
>> >> buildEx =: 4 : 0
>> >> res=:y,ptr{r
>> >>
>> ptr=: ptr{prev
>> >> res
>> >> )
>> >>
>> >>
>> >>
>>
>> NB.===========================================================================
>> >>
>> >>
>> >> NB. Imperative version. just for
>> benchmarking
>> >> lisI =: 3 : 0
>> >> lst =: 0
>> >> r=:
>> y
>> >> parent=: (#y)#0
>> >> for_i.>:i.<:# r do.
>> >> if.((i{r) > ({: lst){r ) do.
>> >> parent=:(_1{lst) i}parent
>> >> lst =: lst, i
>> >>
>> else.
>> >> min=: 0
>> >> max =: <:#lst
>> >> while. min < max do.
>> >> mid =: <. (min + max) % 2
>> >> if. (i{r) > ((mid { lst{r)) do. min
>> =: mid + 1
>> >> else. max =: mid end.
>> >> end.
>> >> lst=:
>> (i) max} lst
>> >> parent=:
>> ((max-1){lst)(i}) parent
>> >> end.
>> >> end.
>> >> res=:
>> ''
>> >> ptr=: _1{lst
>> >> while. (# res) < # lst do.
>> >> res=:res,ptr{r
>> >> ptr=:ptr{parent
>> >> end.
>> >> I.
>> res
>> >> )
>> >>
>> >>
>> >>
>> >>
>>
>> NB.===========================================================================
>> >>
>> >>
>> >> NB. Mike's version.
>> >>
>> >> lisM =: 3 :
>> 0
>> >> n =.
>> #x =. y
>> >> if. 2>#x
>> do. x return. end. NB. special case empty
>> or singleton array
>> >> if. (-:/:~)x do.
>> ~.x return. end. NB. special case sorted arrays
>> >> if. (-:\:~)x do. {.x return. end.
>> >> p =. n#0
>> >> NB. seed m with trailing _1 so that
>> final L (as in wiki algorithm) can be found
>> >> m =. n 0 }
>> _1#~>:n
>> >> NB. set up sorted mx,
>> with just the first element of x, so that I. works
>> >> mx =. ({.x) 1 }
>> (<:<./x), n#>:>./x
>> >>
>> for_i. i.n do.
>> >> xi =. i{x
>> >> lo =. mx I. xi
>> >> p =. (m{~<:lo) i
>> } p NB. better than appending to short p for larger x
>> >> m =. i lo } m
>> >> mx =. xi lo } mx
>> >> end.
>> >> |.
>> x{~(p{~])^:(i.L) m{~ L =. <: m i. _1
>> >> )
>> >>
>> >>
>>
>> NB.===========================================================================
>> >>
>> >> NB.
>> Louis' version.
>> >> p=: ] , [
>> ,&.> ] #~ (< {.&>) (= >./)@:*
>> #&>@]
>> >> e=: }:@>@(#~ (=
>> >./)@:(#&>))@>
>> >>
>> >> s=: [: e (<<_) p&.>/@,~
>> <"0
>> >> pi=: ] , [ ,&.>
>> ] {~ (< {.&>) (i. >./)@:* #&>@]
>> >> lisL =: [: e (<<_)
>> pi&.>/@,~ <"0
>> NB. <------------- this one.
>> >>
>> >> f=: ((]
>> >: (-~ >./)) #&>) # ]
>> >>
>> >> P=: ] , [ ,&.> ] #~ (<
>> {.&>) (,@[ #^:_1 (= >./)@#) #&>@]
>> >> sp=: [: e (<<_) ({:@[ f {.@[ P
>> ])&.>/@,~ (,&.> i.@#)
>> >>
>> >>
>> >>
>> >>
>>
>> NB.===========================================================================
>> >>
>> >>
>> >> NB. Xiao's version with Raul's
>> modifications. Renamed verbs to avoid clashing.
>> >>
>> >> NB. dyads
>> >> exr=: (1 + {:@[ < ]) {. [ ;
>> ,
>> >> hxr=: [: ; exr&.>
>> >>
>> >> NB.
>> monads
>> >> gxr=: (}.@] ;~ {.@] ; (hxr
>> {.))&>/
>> >> cxr=: ({::~ [: (i.
>> >./) #@>)@>@{.
>> >> dxr=:
>> (<_) ; ]
>> >> lisXR=: ([: cxr
>> gxr^:(#@(>@{:)))@dxr
>> >>
>> >>
>>
>> NB.===========================================================================
>> >>
>> >> a=: 25 ?
>> 25
>> >> timespacex 'lisI a'
>> >> timespacex 'lisJ a'
>> >> timespacex 'lisM a'
>> >> timespacex 'lisL a'
>> >> timespacex 'lisXR a' NB.
>> comment out for larger arrays,a.
>> >>
>> >> Playing around with various
>> arrays, it seems lisM is the most efficient in time and
>> space (more than the imperative version).
>> >> lisM and lisI can handle array larger
>> than 10000. The others struggle or give up with them.
>> >>
>> >>
>> >>
>> --------------------------------------------
>> >> On Sun, 9/4/16, 'Mike Day' via
>> Programming <programm...@jsoftware.com>
>> wrote:
>> >>
>> >>
>> Subject: Re: [Jprogramming] Greatest Increasing
>> Subsequence
>> >> To: programm...@jsoftware.com
>> >> Date: Sunday, September 4, 2016, 4:30
>> AM
>> >>
>> >> This
>> version of
>> >> "lis" is a bit
>> more J-like, especially in using
>> >>
>> dyadic I.
>> >> instead of the diy binary
>> search,
>> >> at the expense of a
>> slightly more
>> >> complicated set-up
>> for the m and mx arrays.
>> >>
>> >> lis =: 3 : 0
>> >>
>> n =. #x =. y
>> >> if. 2>#x do. x return.
>> end.
>> >> NB.
>> special case empty or singleton array
>> >> if. (-:/:~)x do. ~.x return. end. NB.
>> special
>> >> case sorted arrays
>> >> if. (-:\:~)x do. {.x
>> >> return. end.
>> >>
>> p =. n#0
>> >> NB.
>> seed m with trailing _1 so that final L (as
>> >> in wiki algorithm) can
>> >> be found
>> >> m
>> =. n 0 } _1#~>:n
>> >> NB. set up sorted mx, with just the
>> first
>> >> element of x, so that I.
>> works
>> >> mx =.
>> >> ({.x) 1 } (<:<./x),
>> n#>:>./x
>> >> for_i. i.n do.
>> >> xi =.
>> >> i{x
>> >> lo
>> =. mx I. xi
>> >> p
>> =. (m{~<:lo) i } p
>> >>
>> NB. better than appending to short p for
>> >> larger x
>> >>
>> m
>> >> =. i lo } m
>> >> mx =.
>> >> xi lo } mx
>> >>
>> end.
>> >> |.
>> >>
>> x{~(p{~])^:(i.L) m{~ L =. <: m i. _1
>> >> )
>> >>
>> >> Mike
>> >>
>> >>
>> >> On
>> 02/09/2016 20:45, 'Mike
>> >>
>> Day' via Programming wrote:
>> >>>
>> Well,
>> >> assuming for now that it does
>> work, here's an attempt
>> >> at a
>> J
>> >>> version of
>> >> the pseudo-code listed at
>> >>>
>> https://en.wikipedia.org/wiki/Longest_increasing_subsequence#Efficient_algorithms
>> >>
>> >>>
>> >>>
>> >>> lis
>> =: 3 : 0 NB. longest
>> >>
>> increasing subsequence
>> >>>
>> m
>> >> =.
>> 0#~>:n =.
>> >>
>> #x =. y
>> >>>
>> L
>> >> =.
>> #p =. ''
>> >>> mx =. m{x NB. added this
>> vector
>> >> for better look-up of
>> x{~mid{m
>> >>> for_i.
>> >> i.n do.
>> >>> 'lo hi' =.
>> >> 1, L
>> >>>
>> xi =. i{x
>> >>>
>> while. lo <: hi do.
>> >>>
>> mid =. >.@-: lo +
>> hi
>> >> NB. if. xi
>> > x{~ mid{m do. NB. next
>> >> line a
>> bit better
>> >> if. xi >
>> mid{mx do.
>> >> lo =. >:
>> mid
>> >> else.
>> >>> hi =.
>> >> <: mid
>> >>> end.
>> >>> end.
>> >>> p
>> >> =. p, m{~<:lo
>> >>> m
>> >> =. i lo } m
>> >>> mx
>> >> =. xi lo } mx NB. update my
>> additional array
>> >>> L
>> =. L >. lo
>> >>> NB.
>> smoutput i; (x{.~ >:i);
>> >>
>> L{.m NB. diagnostic
>> >>
>> end.
>> >>> |. x{~(p{~])^:(i.L) L{m
>> >>> )
>> >>>
>> >>> It's reasonably fast on
>> ?10000#5000 -
>> >> but possibly wrong!It
>> does
>> >>> fail on an
>> >> empty array.
>> >>
>> Mike
>> >>>
>> >>>
>> >>>>
>> On 02/09/2016 17:30, Raul Miller wrote:
>> >>>> It seems to me that the
>> >> "efficient algorithm"
>> documented on the
>> >>>> wikipedia
>> page would have an analogous
>> >> flaw.
>> It is performing binary
>> >> searches on
>> unsorted lists. That said, it does perform
>> >> correctly for
>> >>>> this example.
>> >>>>
>> >>>> Thanks,
>> >>>
>> >>>
>> >>> ---
>> >>>
>> This email has been checked for viruses by
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>> >>> https://www.avast.com/antivirus
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>> >>
>> >> ---
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>> email
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