Basically using Reduce as an lapply in that example, but I think that was caused by how people started talking about things in the first place =) But the point is the accumulator can be anything as far as I can tell. On Thu, Jul 28, 2016 at 12:14 PM, jeremiah rounds <roundsjeremiah at gmail.com> wrote:> Re: > "What I'm trying to > work out is how to have the accumulator in Reduce not be the same type as > the elements of the vector/list being reduced - ideally it could be an S3 > instance, list, vector, or data frame." > > Pretty sure that is not true. See code that follows. I would never solve > this task in this way though so no comment on the use of Reduce for what > you described. (Note the accumulation of "functions" in a list is just a > demo of possibilities). You could accumulate in an environment too and > potentially gain a lot of copy efficiency. > > > lookup = list() > lookup[[as.character(1)]] = function() print("1") > lookup[[as.character(2)]] = function() print("2") > lookup[[as.character(3)]] = function() print("3") > > data = list(c(1,2), c(1,4), c(3,3), c(2,30)) > > > r = Reduce(function(acc, item) { > append(acc, list(lookup[[as.character(min(item))]])) > }, data,list()) > r > for(f in r) f() > > > On Thu, Jul 28, 2016 at 5:09 AM, Stefan Kruger <stefan.kruger at gmail.com> > wrote: > >> Ulrik - many thanks for your reply. >> >> I'm aware of many simple solutions as the one you suggest, both iterative >> and functional style - but I'm trying to learn how to bend Reduce() for >> the >> purpose of using it in more complex processing tasks. What I'm trying to >> work out is how to have the accumulator in Reduce not be the same type as >> the elements of the vector/list being reduced - ideally it could be an S3 >> instance, list, vector, or data frame. >> >> Here's a more realistic example (in Elixir, sorry) >> >> Given two lists: >> >> 1. data: maps an id string to a vector of revision strings >> 2. dict: maps known id/revision pairs as a string to true (or 1) >> >> find the items in data not already in dict, returned as a named list. >> >> ```elixir >> data = %{ >> "id1" => ["rev1.1", "rev1.2"], >> "id2" => ["rev2.1"], >> "id3" => ["rev3.1", "rev3.2", "rev3.3"] >> } >> >> dict = %{ >> "id1/rev1.1" => 1, >> "id1/rev1.2" => 1, >> "id3/rev3.1" => 1 >> } >> >> # Find the items in data not already in dict. Return as a grouped map >> >> Map.keys(data) >> |> Enum.flat_map(fn id -> Enum.map(data[id], fn rev -> {id, rev} end) >> end) >> |> Enum.filter(fn {id, rev} -> !Dict.has_key?(dict, "#{id}/#{rev}") >> end) >> |> Enum.reduce(%{}, fn ({k, v}, d) -> Map.update(d, k, [v], &[v|&1]) >> end) >> ``` >> >> >> >> >> On 28 July 2016 at 12:03, Ulrik Stervbo <ulrik.stervbo at gmail.com> wrote: >> >> > Hi Stefan, >> > >> > in that case,lapply(data, length) should do the trick. >> > >> > Best wishes, >> > Ulrik >> > >> > On Thu, 28 Jul 2016 at 12:57 Stefan Kruger <stefan.kruger at gmail.com> >> > wrote: >> > >> >> David - many thanks for your response. >> >> >> >> What I tried to do was to turn >> >> >> >> data <- list(one = c(1, 1), three = c(3), two = c(2, 2)) >> >> >> >> into >> >> >> >> result <- list(one = 2, three = 1, two = 2) >> >> >> >> that is creating a new list which has the same names as the first, but >> >> where the values are the vector lengths. >> >> >> >> I know there are many other (and better) trivial ways of achieving >> this - >> >> my aim is less the task itself, and more figuring out if this can be >> done >> >> using Reduce() in the fashion I showed in the other examples I gave. >> It's >> >> a >> >> building block of doing map-filter-reduce type pipelines that I'd like >> to >> >> understand how to do in R. >> >> >> >> Fumbling in the dark, I tried: >> >> >> >> Reduce(function(acc, item) { setNames(c(acc, length(data[item])), item >> }, >> >> names(data), accumulate=TRUE) >> >> >> >> but setNames sets all the names, not adding one - and acc is still a >> >> vector, not a list. >> >> >> >> It looks like 'lambda.tools.fold()' and possibly 'purrr.reduce()' aim >> at >> >> doing what I'd like to do - but I've not been able to figure out quite >> >> how. >> >> >> >> Thanks >> >> >> >> Stefan >> >> >> >> >> >> >> >> On 27 July 2016 at 20:35, David Winsemius <dwinsemius at comcast.net> >> wrote: >> >> >> >> > >> >> > > On Jul 27, 2016, at 8:20 AM, Stefan Kruger < >> stefan.kruger at gmail.com> >> >> > wrote: >> >> > > >> >> > > Hi - >> >> > > >> >> > > I'm new to R. >> >> > > >> >> > > In other functional languages I'm familiar with you can often seed >> a >> >> call >> >> > > to reduce() with a custom accumulator. Here's an example in Elixir: >> >> > > >> >> > > map = %{"one" => [1, 1], "three" => [3], "two" => [2, 2]} >> >> > > map |> Enum.reduce(%{}, fn ({k,v}, acc) -> Map.update(acc, k, >> >> > > Enum.count(v), nil) end) >> >> > > # %{"one" => 2, "three" => 1, "two" => 2} >> >> > > >> >> > > In R-terms that's reducing a list of vectors to become a new list >> >> mapping >> >> > > the names to the vector lengths. >> >> > > >> >> > > Even in JavaScript, you can do similar things: >> >> > > >> >> > > list = { one: [1, 1], three: [3], two: [2, 2] }; >> >> > > var result = Object.keys(list).reduceRight(function (acc, item) { >> >> > > acc[item] = list[item].length; >> >> > > return acc; >> >> > > }, {}); >> >> > > // result == { two: 2, three: 1, one: 2 } >> >> > > >> >> > > In R, from what I can gather, Reduce() is restricted such that any >> >> init >> >> > > value you feed it is required to be of the same type as the >> elements >> >> of >> >> > the >> >> > > vector you're reducing -- so I can't build up. So whilst I can do, >> say >> >> > > >> >> > >> Reduce(function(acc, item) { acc + item }, c(1,2,3,4,5), 96) >> >> > > [1] 111 >> >> > > >> >> > > I can't use Reduce to build up a list, vector or data frame? >> >> > > >> >> > > What am I missing? >> >> > > >> >> > > Many thanks for any pointers, >> >> > >> >> > This builds a list: >> >> > >> >> > > Reduce(function(acc, item) { c(acc , item) }, c(1,2,3,4,5), 96, >> >> > accumulate=TRUE) >> >> > [[1]] >> >> > [1] 96 >> >> > >> >> > [[2]] >> >> > [1] 96 1 >> >> > >> >> > [[3]] >> >> > [1] 96 1 2 >> >> > >> >> > [[4]] >> >> > [1] 96 1 2 3 >> >> > >> >> > [[5]] >> >> > [1] 96 1 2 3 4 >> >> > >> >> > [[6]] >> >> > [1] 96 1 2 3 4 5 >> >> > >> >> > But you are not saying what you want. The other examples were doing >> >> > something with names but you provided no names for the R example. >> >> > >> >> > This would return a list of named vectors: >> >> > >> >> > > Reduce(function(acc, item) { setNames( c(acc,item), 1:(item+1)) }, >> >> > c(1,2,3,4,5), 96, accumulate=TRUE) >> >> > [[1]] >> >> > [1] 96 >> >> > >> >> > [[2]] >> >> > 1 2 >> >> > 96 1 >> >> > >> >> > [[3]] >> >> > 1 2 3 >> >> > 96 1 2 >> >> > >> >> > [[4]] >> >> > 1 2 3 4 >> >> > 96 1 2 3 >> >> > >> >> > [[5]] >> >> > 1 2 3 4 5 >> >> > 96 1 2 3 4 >> >> > >> >> > [[6]] >> >> > 1 2 3 4 5 6 >> >> > 96 1 2 3 4 5 >> >> > >> >> > >> >> > >> >> > >> >> > > Stefan >> >> > > >> >> > > >> >> > > >> >> > > -- >> >> > > Stefan Kruger <stefan.kruger at gmail.com> >> >> > > >> >> > > [[alternative HTML version deleted]] >> >> > > >> >> > > ______________________________________________ >> >> > > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >> >> > > https://stat.ethz.ch/mailman/listinfo/r-help >> >> > > PLEASE do read the posting guide >> >> > http://www.R-project.org/posting-guide.html >> >> > > and provide commented, minimal, self-contained, reproducible code. >> >> > >> >> > David Winsemius >> >> > Alameda, CA, USA >> >> > >> >> > >> >> >> >> >> >> -- >> >> Stefan Kruger <stefan.kruger at gmail.com> >> >> >> >> [[alternative HTML version deleted]] >> >> >> >> ______________________________________________ >> >> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >> >> https://stat.ethz.ch/mailman/listinfo/r-help >> >> PLEASE do read the posting guide >> >> http://www.R-project.org/posting-guide.html >> >> and provide commented, minimal, self-contained, reproducible code. >> >> >> > >> >> >> -- >> Stefan Kruger <stefan.kruger at gmail.com> >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > >[[alternative HTML version deleted]]
Jeremiah - neat - that's one step closer, but one small thing I still don't understand:> data <- list(one = c(1, 1), three = c(3), two = c(2, 2)) > r = Reduce(function(acc, item) { append(acc, setNames(length(item),names(item))) }, data, list())> str(r)List of 3 $ : int 2 $ : int 1 $ : int 2 I wanted the names to remain, but it seems like the "data" parameter loses its names when consumed by the Reduce()? If I print "item" inside the reducing function, it's not got the names. I'm probably missing some central tenet of R here. As to your comment of this being lapply() implemented by Reduce() - as I understand lapply() (or map() in other functional languages), it's limited to returning a list/vector of the same length as the original. Consider this contrived example:> r = Reduce(function(acc, item) { if (length(item) > 1) {append(acc,setNames(length(item), names(item)))} }, data, list())> str(r)int 2> r[1] 2 I don't think you could achieve that with lapply()? Thanks Stefan On 28 July 2016 at 20:19, jeremiah rounds <roundsjeremiah at gmail.com> wrote:> Basically using Reduce as an lapply in that example, but I think that was > caused by how people started talking about things in the first place =) But > the point is the accumulator can be anything as far as I can tell. > > On Thu, Jul 28, 2016 at 12:14 PM, jeremiah rounds < > roundsjeremiah at gmail.com> wrote: > >> Re: >> "What I'm trying to >> work out is how to have the accumulator in Reduce not be the same type as >> the elements of the vector/list being reduced - ideally it could be an S3 >> instance, list, vector, or data frame." >> >> Pretty sure that is not true. See code that follows. I would never >> solve this task in this way though so no comment on the use of Reduce for >> what you described. (Note the accumulation of "functions" in a list is >> just a demo of possibilities). You could accumulate in an environment too >> and potentially gain a lot of copy efficiency. >> >> >> lookup = list() >> lookup[[as.character(1)]] = function() print("1") >> lookup[[as.character(2)]] = function() print("2") >> lookup[[as.character(3)]] = function() print("3") >> >> data = list(c(1,2), c(1,4), c(3,3), c(2,30)) >> >> >> r = Reduce(function(acc, item) { >> append(acc, list(lookup[[as.character(min(item))]])) >> }, data,list()) >> r >> for(f in r) f() >> >> >> On Thu, Jul 28, 2016 at 5:09 AM, Stefan Kruger <stefan.kruger at gmail.com> >> wrote: >> >>> Ulrik - many thanks for your reply. >>> >>> I'm aware of many simple solutions as the one you suggest, both iterative >>> and functional style - but I'm trying to learn how to bend Reduce() for >>> the >>> purpose of using it in more complex processing tasks. What I'm trying to >>> work out is how to have the accumulator in Reduce not be the same type as >>> the elements of the vector/list being reduced - ideally it could be an S3 >>> instance, list, vector, or data frame. >>> >>> Here's a more realistic example (in Elixir, sorry) >>> >>> Given two lists: >>> >>> 1. data: maps an id string to a vector of revision strings >>> 2. dict: maps known id/revision pairs as a string to true (or 1) >>> >>> find the items in data not already in dict, returned as a named list. >>> >>> ```elixir >>> data = %{ >>> "id1" => ["rev1.1", "rev1.2"], >>> "id2" => ["rev2.1"], >>> "id3" => ["rev3.1", "rev3.2", "rev3.3"] >>> } >>> >>> dict = %{ >>> "id1/rev1.1" => 1, >>> "id1/rev1.2" => 1, >>> "id3/rev3.1" => 1 >>> } >>> >>> # Find the items in data not already in dict. Return as a grouped map >>> >>> Map.keys(data) >>> |> Enum.flat_map(fn id -> Enum.map(data[id], fn rev -> {id, rev} end) >>> end) >>> |> Enum.filter(fn {id, rev} -> !Dict.has_key?(dict, "#{id}/#{rev}") >>> end) >>> |> Enum.reduce(%{}, fn ({k, v}, d) -> Map.update(d, k, [v], &[v|&1]) >>> end) >>> ``` >>> >>> >>> >>> >>> On 28 July 2016 at 12:03, Ulrik Stervbo <ulrik.stervbo at gmail.com> wrote: >>> >>> > Hi Stefan, >>> > >>> > in that case,lapply(data, length) should do the trick. >>> > >>> > Best wishes, >>> > Ulrik >>> > >>> > On Thu, 28 Jul 2016 at 12:57 Stefan Kruger <stefan.kruger at gmail.com> >>> > wrote: >>> > >>> >> David - many thanks for your response. >>> >> >>> >> What I tried to do was to turn >>> >> >>> >> data <- list(one = c(1, 1), three = c(3), two = c(2, 2)) >>> >> >>> >> into >>> >> >>> >> result <- list(one = 2, three = 1, two = 2) >>> >> >>> >> that is creating a new list which has the same names as the first, but >>> >> where the values are the vector lengths. >>> >> >>> >> I know there are many other (and better) trivial ways of achieving >>> this - >>> >> my aim is less the task itself, and more figuring out if this can be >>> done >>> >> using Reduce() in the fashion I showed in the other examples I gave. >>> It's >>> >> a >>> >> building block of doing map-filter-reduce type pipelines that I'd >>> like to >>> >> understand how to do in R. >>> >> >>> >> Fumbling in the dark, I tried: >>> >> >>> >> Reduce(function(acc, item) { setNames(c(acc, length(data[item])), >>> item }, >>> >> names(data), accumulate=TRUE) >>> >> >>> >> but setNames sets all the names, not adding one - and acc is still a >>> >> vector, not a list. >>> >> >>> >> It looks like 'lambda.tools.fold()' and possibly 'purrr.reduce()' aim >>> at >>> >> doing what I'd like to do - but I've not been able to figure out quite >>> >> how. >>> >> >>> >> Thanks >>> >> >>> >> Stefan >>> >> >>> >> >>> >> >>> >> On 27 July 2016 at 20:35, David Winsemius <dwinsemius at comcast.net> >>> wrote: >>> >> >>> >> > >>> >> > > On Jul 27, 2016, at 8:20 AM, Stefan Kruger < >>> stefan.kruger at gmail.com> >>> >> > wrote: >>> >> > > >>> >> > > Hi - >>> >> > > >>> >> > > I'm new to R. >>> >> > > >>> >> > > In other functional languages I'm familiar with you can often >>> seed a >>> >> call >>> >> > > to reduce() with a custom accumulator. Here's an example in >>> Elixir: >>> >> > > >>> >> > > map = %{"one" => [1, 1], "three" => [3], "two" => [2, 2]} >>> >> > > map |> Enum.reduce(%{}, fn ({k,v}, acc) -> Map.update(acc, k, >>> >> > > Enum.count(v), nil) end) >>> >> > > # %{"one" => 2, "three" => 1, "two" => 2} >>> >> > > >>> >> > > In R-terms that's reducing a list of vectors to become a new list >>> >> mapping >>> >> > > the names to the vector lengths. >>> >> > > >>> >> > > Even in JavaScript, you can do similar things: >>> >> > > >>> >> > > list = { one: [1, 1], three: [3], two: [2, 2] }; >>> >> > > var result = Object.keys(list).reduceRight(function (acc, item) { >>> >> > > acc[item] = list[item].length; >>> >> > > return acc; >>> >> > > }, {}); >>> >> > > // result == { two: 2, three: 1, one: 2 } >>> >> > > >>> >> > > In R, from what I can gather, Reduce() is restricted such that any >>> >> init >>> >> > > value you feed it is required to be of the same type as the >>> elements >>> >> of >>> >> > the >>> >> > > vector you're reducing -- so I can't build up. So whilst I can >>> do, say >>> >> > > >>> >> > >> Reduce(function(acc, item) { acc + item }, c(1,2,3,4,5), 96) >>> >> > > [1] 111 >>> >> > > >>> >> > > I can't use Reduce to build up a list, vector or data frame? >>> >> > > >>> >> > > What am I missing? >>> >> > > >>> >> > > Many thanks for any pointers, >>> >> > >>> >> > This builds a list: >>> >> > >>> >> > > Reduce(function(acc, item) { c(acc , item) }, c(1,2,3,4,5), 96, >>> >> > accumulate=TRUE) >>> >> > [[1]] >>> >> > [1] 96 >>> >> > >>> >> > [[2]] >>> >> > [1] 96 1 >>> >> > >>> >> > [[3]] >>> >> > [1] 96 1 2 >>> >> > >>> >> > [[4]] >>> >> > [1] 96 1 2 3 >>> >> > >>> >> > [[5]] >>> >> > [1] 96 1 2 3 4 >>> >> > >>> >> > [[6]] >>> >> > [1] 96 1 2 3 4 5 >>> >> > >>> >> > But you are not saying what you want. The other examples were doing >>> >> > something with names but you provided no names for the R example. >>> >> > >>> >> > This would return a list of named vectors: >>> >> > >>> >> > > Reduce(function(acc, item) { setNames( c(acc,item), 1:(item+1)) >>> }, >>> >> > c(1,2,3,4,5), 96, accumulate=TRUE) >>> >> > [[1]] >>> >> > [1] 96 >>> >> > >>> >> > [[2]] >>> >> > 1 2 >>> >> > 96 1 >>> >> > >>> >> > [[3]] >>> >> > 1 2 3 >>> >> > 96 1 2 >>> >> > >>> >> > [[4]] >>> >> > 1 2 3 4 >>> >> > 96 1 2 3 >>> >> > >>> >> > [[5]] >>> >> > 1 2 3 4 5 >>> >> > 96 1 2 3 4 >>> >> > >>> >> > [[6]] >>> >> > 1 2 3 4 5 6 >>> >> > 96 1 2 3 4 5 >>> >> > >>> >> > >>> >> > >>> >> > >>> >> > > Stefan >>> >> > > >>> >> > > >>> >> > > >>> >> > > -- >>> >> > > Stefan Kruger <stefan.kruger at gmail.com> >>> >> > > >>> >> > > [[alternative HTML version deleted]] >>> >> > > >>> >> > > ______________________________________________ >>> >> > > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >>> >> > > https://stat.ethz.ch/mailman/listinfo/r-help >>> >> > > PLEASE do read the posting guide >>> >> > http://www.R-project.org/posting-guide.html >>> >> > > and provide commented, minimal, self-contained, reproducible code. >>> >> > >>> >> > David Winsemius >>> >> > Alameda, CA, USA >>> >> > >>> >> > >>> >> >>> >> >>> >> -- >>> >> Stefan Kruger <stefan.kruger at gmail.com> >>> >> >>> >> [[alternative HTML version deleted]] >>> >> >>> >> ______________________________________________ >>> >> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >>> >> https://stat.ethz.ch/mailman/listinfo/r-help >>> >> PLEASE do read the posting guide >>> >> http://www.R-project.org/posting-guide.html >>> >> and provide commented, minimal, self-contained, reproducible code. >>> >> >>> > >>> >>> >>> -- >>> Stefan Kruger <stefan.kruger at gmail.com> >>> >>> [[alternative HTML version deleted]] >>> >>> ______________________________________________ >>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide >>> http://www.R-project.org/posting-guide.html >>> and provide commented, minimal, self-contained, reproducible code. >>> >> >> >-- Stefan Kruger <stefan.kruger at gmail.com> [[alternative HTML version deleted]]
Reduce (like lapply) apparently uses the [[ operator to extract components from the list given to it. X[[i]] does not attach names(X)[i] to its output (where would it put it?). Hence your se To help understand what these functions are doing try putting print statements in your test functions:> data <- list(one = c(1, 1), three = c(3), two = c(2, 2)) > r <- Reduce(function(acc, item) { cat("acc="); str(acc) ; cat("item=");str(item); length(item) }, data, init=list()) acc= list() item= num [1:2] 1 1 acc= int 2 item= num 3 acc= int 1 item= num [1:2] 2 2> data2 <- list(one = c(oneA=1, onB=1), three = c(threeA=3), two c(twoA=2, twoB=2)) > r <- Reduce(function(acc, item) { cat("acc="); str(acc) ; cat("item=");str(item); length(item) }, data2, init=list()) acc= list() item= Named num [1:2] 1 1 - attr(*, "names")= chr [1:2] "oneA" "onB" acc= int 2 item= Named num 3 - attr(*, "names")= chr "threeA" acc= int 1 item= Named num [1:2] 2 2 - attr(*, "names")= chr [1:2] "twoA" "twoB" I still don't understand why you want Reduce to to lapply's job. Reduce maps many to one and lapply maps many to many. Bill Dunlap TIBCO Software wdunlap tibco.com On Fri, Jul 29, 2016 at 1:37 AM, Stefan Kruger <stefan.kruger at gmail.com> wrote:> Jeremiah - > > neat - that's one step closer, but one small thing I still don't > understand: > > > data <- list(one = c(1, 1), three = c(3), two = c(2, 2)) > > r = Reduce(function(acc, item) { append(acc, setNames(length(item), > names(item))) }, data, list()) > > str(r) > List of 3 > $ : int 2 > $ : int 1 > $ : int 2 > > I wanted the names to remain, but it seems like the "data" parameter loses > its names when consumed by the Reduce()? If I print "item" inside the > reducing function, it's not got the names. I'm probably missing some > central tenet of R here. > > As to your comment of this being lapply() implemented by Reduce() - as I > understand lapply() (or map() in other functional languages), it's limited > to returning a list/vector of the same length as the original. Consider > this contrived example: > > > r = Reduce(function(acc, item) { if (length(item) > 1) {append(acc, > setNames(length(item), names(item)))} }, data, list()) > > str(r) > int 2 > > r > [1] 2 > > I don't think you could achieve that with lapply()? > > Thanks > > Stefan > > > On 28 July 2016 at 20:19, jeremiah rounds <roundsjeremiah at gmail.com> > wrote: > > > Basically using Reduce as an lapply in that example, but I think that was > > caused by how people started talking about things in the first place =) > But > > the point is the accumulator can be anything as far as I can tell. > > > > On Thu, Jul 28, 2016 at 12:14 PM, jeremiah rounds < > > roundsjeremiah at gmail.com> wrote: > > > >> Re: > >> "What I'm trying to > >> work out is how to have the accumulator in Reduce not be the same type > as > >> the elements of the vector/list being reduced - ideally it could be an > S3 > >> instance, list, vector, or data frame." > >> > >> Pretty sure that is not true. See code that follows. I would never > >> solve this task in this way though so no comment on the use of Reduce > for > >> what you described. (Note the accumulation of "functions" in a list is > >> just a demo of possibilities). You could accumulate in an environment > too > >> and potentially gain a lot of copy efficiency. > >> > >> > >> lookup = list() > >> lookup[[as.character(1)]] = function() print("1") > >> lookup[[as.character(2)]] = function() print("2") > >> lookup[[as.character(3)]] = function() print("3") > >> > >> data = list(c(1,2), c(1,4), c(3,3), c(2,30)) > >> > >> > >> r = Reduce(function(acc, item) { > >> append(acc, list(lookup[[as.character(min(item))]])) > >> }, data,list()) > >> r > >> for(f in r) f() > >> > >> > >> On Thu, Jul 28, 2016 at 5:09 AM, Stefan Kruger <stefan.kruger at gmail.com > > > >> wrote: > >> > >>> Ulrik - many thanks for your reply. > >>> > >>> I'm aware of many simple solutions as the one you suggest, both > iterative > >>> and functional style - but I'm trying to learn how to bend Reduce() for > >>> the > >>> purpose of using it in more complex processing tasks. What I'm trying > to > >>> work out is how to have the accumulator in Reduce not be the same type > as > >>> the elements of the vector/list being reduced - ideally it could be an > S3 > >>> instance, list, vector, or data frame. > >>> > >>> Here's a more realistic example (in Elixir, sorry) > >>> > >>> Given two lists: > >>> > >>> 1. data: maps an id string to a vector of revision strings > >>> 2. dict: maps known id/revision pairs as a string to true (or 1) > >>> > >>> find the items in data not already in dict, returned as a named list. > >>> > >>> ```elixir > >>> data = %{ > >>> "id1" => ["rev1.1", "rev1.2"], > >>> "id2" => ["rev2.1"], > >>> "id3" => ["rev3.1", "rev3.2", "rev3.3"] > >>> } > >>> > >>> dict = %{ > >>> "id1/rev1.1" => 1, > >>> "id1/rev1.2" => 1, > >>> "id3/rev3.1" => 1 > >>> } > >>> > >>> # Find the items in data not already in dict. Return as a grouped map > >>> > >>> Map.keys(data) > >>> |> Enum.flat_map(fn id -> Enum.map(data[id], fn rev -> {id, rev} > end) > >>> end) > >>> |> Enum.filter(fn {id, rev} -> !Dict.has_key?(dict, "#{id}/#{rev}") > >>> end) > >>> |> Enum.reduce(%{}, fn ({k, v}, d) -> Map.update(d, k, [v], > &[v|&1]) > >>> end) > >>> ``` > >>> > >>> > >>> > >>> > >>> On 28 July 2016 at 12:03, Ulrik Stervbo <ulrik.stervbo at gmail.com> > wrote: > >>> > >>> > Hi Stefan, > >>> > > >>> > in that case,lapply(data, length) should do the trick. > >>> > > >>> > Best wishes, > >>> > Ulrik > >>> > > >>> > On Thu, 28 Jul 2016 at 12:57 Stefan Kruger <stefan.kruger at gmail.com> > >>> > wrote: > >>> > > >>> >> David - many thanks for your response. > >>> >> > >>> >> What I tried to do was to turn > >>> >> > >>> >> data <- list(one = c(1, 1), three = c(3), two = c(2, 2)) > >>> >> > >>> >> into > >>> >> > >>> >> result <- list(one = 2, three = 1, two = 2) > >>> >> > >>> >> that is creating a new list which has the same names as the first, > but > >>> >> where the values are the vector lengths. > >>> >> > >>> >> I know there are many other (and better) trivial ways of achieving > >>> this - > >>> >> my aim is less the task itself, and more figuring out if this can be > >>> done > >>> >> using Reduce() in the fashion I showed in the other examples I gave. > >>> It's > >>> >> a > >>> >> building block of doing map-filter-reduce type pipelines that I'd > >>> like to > >>> >> understand how to do in R. > >>> >> > >>> >> Fumbling in the dark, I tried: > >>> >> > >>> >> Reduce(function(acc, item) { setNames(c(acc, length(data[item])), > >>> item }, > >>> >> names(data), accumulate=TRUE) > >>> >> > >>> >> but setNames sets all the names, not adding one - and acc is still a > >>> >> vector, not a list. > >>> >> > >>> >> It looks like 'lambda.tools.fold()' and possibly 'purrr.reduce()' > aim > >>> at > >>> >> doing what I'd like to do - but I've not been able to figure out > quite > >>> >> how. > >>> >> > >>> >> Thanks > >>> >> > >>> >> Stefan > >>> >> > >>> >> > >>> >> > >>> >> On 27 July 2016 at 20:35, David Winsemius <dwinsemius at comcast.net> > >>> wrote: > >>> >> > >>> >> > > >>> >> > > On Jul 27, 2016, at 8:20 AM, Stefan Kruger < > >>> stefan.kruger at gmail.com> > >>> >> > wrote: > >>> >> > > > >>> >> > > Hi - > >>> >> > > > >>> >> > > I'm new to R. > >>> >> > > > >>> >> > > In other functional languages I'm familiar with you can often > >>> seed a > >>> >> call > >>> >> > > to reduce() with a custom accumulator. Here's an example in > >>> Elixir: > >>> >> > > > >>> >> > > map = %{"one" => [1, 1], "three" => [3], "two" => [2, 2]} > >>> >> > > map |> Enum.reduce(%{}, fn ({k,v}, acc) -> Map.update(acc, k, > >>> >> > > Enum.count(v), nil) end) > >>> >> > > # %{"one" => 2, "three" => 1, "two" => 2} > >>> >> > > > >>> >> > > In R-terms that's reducing a list of vectors to become a new > list > >>> >> mapping > >>> >> > > the names to the vector lengths. > >>> >> > > > >>> >> > > Even in JavaScript, you can do similar things: > >>> >> > > > >>> >> > > list = { one: [1, 1], three: [3], two: [2, 2] }; > >>> >> > > var result = Object.keys(list).reduceRight(function (acc, item) > { > >>> >> > > acc[item] = list[item].length; > >>> >> > > return acc; > >>> >> > > }, {}); > >>> >> > > // result == { two: 2, three: 1, one: 2 } > >>> >> > > > >>> >> > > In R, from what I can gather, Reduce() is restricted such that > any > >>> >> init > >>> >> > > value you feed it is required to be of the same type as the > >>> elements > >>> >> of > >>> >> > the > >>> >> > > vector you're reducing -- so I can't build up. So whilst I can > >>> do, say > >>> >> > > > >>> >> > >> Reduce(function(acc, item) { acc + item }, c(1,2,3,4,5), 96) > >>> >> > > [1] 111 > >>> >> > > > >>> >> > > I can't use Reduce to build up a list, vector or data frame? > >>> >> > > > >>> >> > > What am I missing? > >>> >> > > > >>> >> > > Many thanks for any pointers, > >>> >> > > >>> >> > This builds a list: > >>> >> > > >>> >> > > Reduce(function(acc, item) { c(acc , item) }, c(1,2,3,4,5), 96, > >>> >> > accumulate=TRUE) > >>> >> > [[1]] > >>> >> > [1] 96 > >>> >> > > >>> >> > [[2]] > >>> >> > [1] 96 1 > >>> >> > > >>> >> > [[3]] > >>> >> > [1] 96 1 2 > >>> >> > > >>> >> > [[4]] > >>> >> > [1] 96 1 2 3 > >>> >> > > >>> >> > [[5]] > >>> >> > [1] 96 1 2 3 4 > >>> >> > > >>> >> > [[6]] > >>> >> > [1] 96 1 2 3 4 5 > >>> >> > > >>> >> > But you are not saying what you want. The other examples were > doing > >>> >> > something with names but you provided no names for the R example. > >>> >> > > >>> >> > This would return a list of named vectors: > >>> >> > > >>> >> > > Reduce(function(acc, item) { setNames( c(acc,item), 1:(item+1)) > >>> }, > >>> >> > c(1,2,3,4,5), 96, accumulate=TRUE) > >>> >> > [[1]] > >>> >> > [1] 96 > >>> >> > > >>> >> > [[2]] > >>> >> > 1 2 > >>> >> > 96 1 > >>> >> > > >>> >> > [[3]] > >>> >> > 1 2 3 > >>> >> > 96 1 2 > >>> >> > > >>> >> > [[4]] > >>> >> > 1 2 3 4 > >>> >> > 96 1 2 3 > >>> >> > > >>> >> > [[5]] > >>> >> > 1 2 3 4 5 > >>> >> > 96 1 2 3 4 > >>> >> > > >>> >> > [[6]] > >>> >> > 1 2 3 4 5 6 > >>> >> > 96 1 2 3 4 5 > >>> >> > > >>> >> > > >>> >> > > >>> >> > > >>> >> > > Stefan > >>> >> > > > >>> >> > > > >>> >> > > > >>> >> > > -- > >>> >> > > Stefan Kruger <stefan.kruger at gmail.com> > >>> >> > > > >>> >> > > [[alternative HTML version deleted]] > >>> >> > > > >>> >> > > ______________________________________________ > >>> >> > > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, > see > >>> >> > > https://stat.ethz.ch/mailman/listinfo/r-help > >>> >> > > PLEASE do read the posting guide > >>> >> > http://www.R-project.org/posting-guide.html > >>> >> > > and provide commented, minimal, self-contained, reproducible > code. > >>> >> > > >>> >> > David Winsemius > >>> >> > Alameda, CA, USA > >>> >> > > >>> >> > > >>> >> > >>> >> > >>> >> -- > >>> >> Stefan Kruger <stefan.kruger at gmail.com> > >>> >> > >>> >> [[alternative HTML version deleted]] > >>> >> > >>> >> ______________________________________________ > >>> >> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > >>> >> https://stat.ethz.ch/mailman/listinfo/r-help > >>> >> PLEASE do read the posting guide > >>> >> http://www.R-project.org/posting-guide.html > >>> >> and provide commented, minimal, self-contained, reproducible code. > >>> >> > >>> > > >>> > >>> > >>> -- > >>> Stefan Kruger <stefan.kruger at gmail.com> > >>> > >>> [[alternative HTML version deleted]] > >>> > >>> ______________________________________________ > >>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > >>> https://stat.ethz.ch/mailman/listinfo/r-help > >>> PLEASE do read the posting guide > >>> http://www.R-project.org/posting-guide.html > >>> and provide commented, minimal, self-contained, reproducible code. > >>> > >> > >> > > > > > -- > Stefan Kruger <stefan.kruger at gmail.com> > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >[[alternative HTML version deleted]]