[FLR-list] FLCohort

Laurie lauriekell at googlemail.com
Tue Oct 18 14:34:28 CEST 2011


On 10/18/2011 01:34 PM, ernesto.jardim at jrc.ec.europa.eu wrote:
> On 10/18/2011 01:22 PM, Laurie wrote:
>> On 10/18/2011 01:10 PM, Ernesto Jardim wrote:
>>>
>>>
>>> On Tue, Oct 18, 2011 at 1:03 PM, Laurie <lauriekell at googlemail.com 
>>> <mailto:lauriekell at googlemail.com>> wrote:
>>>
>>>     On 10/18/2011 12:50 PM, ernesto.jardim at jrc.ec.europa.eu
>>>     <mailto:ernesto.jardim at jrc.ec.europa.eu> wrote:
>>>>     On 10/18/2011 12:02 PM, Laurie wrote:
>>>>>     On 10/18/2011 11:41 AM, ernesto.jardim at jrc.ec.europa.eu
>>>>>     <mailto:ernesto.jardim at jrc.ec.europa.eu> wrote:
>>>>>>     On 10/18/2011 11:26 AM, Laurie wrote:
>>>>>>>     I am working on tagging models, where tags are released for
>>>>>>>     a number of  years and then recaptured in subsequent years.
>>>>>>>     This allows M & Z to be estimated along a cohort.
>>>>>>>
>>>>>>>     The data are in the form of number of fish tagged and
>>>>>>>     recovered each year of a cohort. This means that you can´t
>>>>>>>     use FLCohort which has age & cohort as dims 1&2.
>>>>>>>
>>>>>>>     However, if you use the 1st dim for cohort then you can
>>>>>>>     model this with an FLQuant, i.e.
>>>>>>>
>>>>>>>     library(plyr)
>>>>>>>
>>>>>>>     setGeneric("I",              function(object,...)
>>>>>>>         standardGeneric("I"))
>>>>>>>     setGeneric('O',              function(object, ...)
>>>>>>>         standardGeneric("O"))
>>>>>>>
>>>>>>>     setMethod('I', signature(object='FLQuant'),
>>>>>>>       function(object,...){
>>>>>>>         dmns <-dimnames(object)
>>>>>>>         dmns[[1]]
>>>>>>>     <-ac((dims(object)$minyear-dims(object)$max):(dims(object)$maxyear-
>>>>>>>     dims(object)$min))
>>>>>>>         names(dmns)[1]<-"quant"
>>>>>>>         flc <-FLQuant(NA,dimnames=dmns)
>>>>>>>
>>>>>>>         t. <-as.data.frame(object)
>>>>>>>         t.$cohort <-t.$year-t.$age
>>>>>>>         flc[]
>>>>>>>     <-daply(t.,c("cohort","year","unit","season","area","iter"),function(x)
>>>>>>>     sum(x$data))
>>>>>>>
>>>>>>>         return(flc)})
>>>>>>>
>>>>>>>     setMethod('O', signature(object='FLQuant'),
>>>>>>>       function(object,...){
>>>>>>>         dmns <-dimnames(object)
>>>>>>>         dmns[[1]]
>>>>>>>     <-ac((dims(object)$maxyear-dims(object)$max):(dims(object)$minyear-dims(object)$min))
>>>>>>>         names(dmns)[1]<-"age"
>>>>>>>         flc <-FLQuant(NA,dimnames=dmns)
>>>>>>>
>>>>>>>         t. <-as.data.frame(object)
>>>>>>>         t.$age <-t.$year-t.$quant
>>>>>>>         t. <-t.[!is.na <http://is.na>(t.$data),]
>>>>>>>         flc[]
>>>>>>>     <-daply(t.,c("age","year","unit","season","area","iter"),function(x)
>>>>>>>     sum(x$data))
>>>>>>>
>>>>>>>         return(flc)})
>>>>>>>
>>>>>>>     data(ple4)
>>>>>>>
>>>>>>>     m1=I(m(ple4))
>>>>>>>     m2=O(m1)
>>>>>>>
>>>>>>>     It is probably best to derive a new class for this object
>>>>>>>     just to break VPAs etc. But what to call it? Also how does
>>>>>>>     it relate to FLCohort.
>>>>>>>     Laurie
>>>>>>
>>>>>>     You may change the age in FLCohort
>>>>>>
>>>>>>     library(FLCore)
>>>>>>     data(ple4)
>>>>>>     flc <- FLCohort(catch.n(ple4))
>>>>>>     quant(flc) <- "year"
>>>>>>
>>>>>>     why not using year in the first dimension ? it should work
>>>>>>     out of the box.
>>>>>>
>>>>>>     EJ
>>>>>>
>>>>>>
>>>>>     But you don´t get what you want.
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>     I(m(ple4))[1:10,1:10]
>>>>>     An object of class "FLQuant"
>>>>>     , , unit = unique, season = all, area = unique
>>>>>
>>>>>            year
>>>>>     quant  1957 1958 1959 1960 1961 1962 1963 1964 1965 1966
>>>>>        1947 0.1   NA   NA   NA   NA   NA   NA   NA   NA   NA
>>>>>        1948 0.1  0.1  <tel:1948%200.1%20%200.1>    NA   NA   NA   NA   NA   NA   NA   NA
>>>>>        1949 0.1  0.1  <tel:1949%200.1%20%200.1>   0.1   NA   NA   NA   NA   NA   NA   NA
>>>>>        1950 0.1  0.1  0.1  0.1   NA   NA   NA   NA   NA   NA
>>>>>        19510.1  0.1  0.1  0.1  0.1  <tel:0.1%20%200.1%20%200.1%20%200.1%20%200.1>    NA   NA   NA   NA   NA
>>>>>        1952 0.1  0.1  0.1  0.1  0.1  0.1   NA   NA   NA   NA
>>>>>        1953 0.1  0.1  0.1  0.1  0.1  0.1  0.1   NA   NA   NA
>>>>>        1954 0.1  0.1  0.1  0.1  0.1  0.1  0.1  0.1   NA   NA
>>>>>        1955 0.1  0.1  0.1  0.1  0.1  0.1  0.1  0.1  0.1   NA
>>>>>        1956 0.1  0.1  0.1  0.1  0.1  0.1  0.1  0.1  0.1  0.1
>>>>>
>>>>>     units:  NA
>>>>>     >  FLCohort(m(ple4))[1:10,1:10]
>>>>>     An object of class "FLCohort"
>>>>>     , , unit = unique, season = all, area = unique
>>>>>
>>>>>          cohort
>>>>>     age  1947 1948 1949 1950 1951 1952 1953 1954 1955 1956
>>>>>        1   NA   NA   NA   NA   NA   NA   NA   NA   NA  0.1
>>>>>        2   NA   NA   NA   NA   NA   NA   NA   NA  0.1  0.1
>>>>>        3   NA   NA   NA   NA   NA   NA   NA  0.1  0.1  0.1
>>>>>        4   NA   NA   NA   NA   NA   NA  0.1  0.1  0.1  0.1
>>>>>        5   NA   NA   NA   NA   NA0.1  0.1  0.1  0.1  0.1  <tel:0.1%20%200.1%20%200.1%20%200.1%20%200.1>
>>>>>        6   NA   NA   NA   NA  0.10.1  0.1  0.1  0.1  0.1  <tel:0.1%20%200.1%20%200.1%20%200.1%20%200.1>
>>>>>        7   NA   NA   NA  0.1  0.1  0.1  0.1  0.1  0.1  0.1
>>>>>        8   NA   NA  0.1  0.1  0.1  0.1  0.1  0.1  0.1  0.1
>>>>>        9   NA  0.1  0.1  0.1  0.1  0.1  0.1  0.1  0.1  0.1
>>>>>
>>>>>     laurie
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>
>>>>     Lost me. What do you want ?
>>>>
>>>>     EJ
>>>>
>>>>
>>>>
>>>     There are three ways to represent the 1st two dims in an FLQuant.
>>>
>>>     i) age & year
>>>     ii) age & cohort
>>>     iii) cohort & year
>>>
>>>     (i) is FLQuant and (ii) is FLCohort; However we do not have
>>>     (iii) which is what I need for my tagging model.
>>>
>>>     I have created an "FLCohortYear" from an FLQuant by adding I() &
>>>     O() as coercion methods and validity that only allows 1st dim to
>>>     be called cohort.
>>>     But then we have two FLCohort objects which might conflict.
>>>
>>>     Laurie
>>>
>>>
>>>
>>> But you can use FLQuant and change the first dimension. You may need 
>>> a method to convert i) or ii) into it but shouldn't create any 
>>> conflicts. If you really need a new data structure and the problem 
>>> only affects tag data, call it FLTag and extend FLQuant.
>>>
>>> Best
>>> EJ
>>>
>> I would have called in FLCohort but some body got there 1st!
>>
>> Having 2 versions of FLCohorts with different properties does raise 
>> an issue though.
>>
>> Laurie
>
> Yes, sure ! But you get what you need computing year=cohort+age, so I 
> don't see the need for a new one.
>
> Best
>
> EJ

Same argument applies to FLQuant! However, the maths is easier in my 
case using sweep & plyr if dims are year & cohort

Laurie
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