So this reproduces the table that you need, but from what you are
describing I'm not sure whether this is what you want.
Best,
rm(list=ls())
x <- c("A", "A", "B", "B", "B")
# An entry in mat will be 1 iff x_i != x_j
M <- outer(x, x, "!=")
M[] <- as.integer(M)
diag(M) <- 0
dimnames(M) <- list(x,x)
M
# A nicer way of printing it
library(Matrix)
methods::as(M, "dgCMatrix")
> methods::as(M, "dgCMatrix")
5 x 5 sparse Matrix of class "dgCMatrix"
A A B B B
A . . 1 1 1
A . . 1 1 1
B 1 1 . . .
B 1 1 . . .
B 1 1 . . .
George G. Vega Yon
+1 (626) 381 8171
http://cana.usc.edu/vegayon
On Tue, Dec 27, 2016 at 7:07 PM, Sebastián Goinheix <[email protected]>
wrote:
> Hi:
> I need a simmetric matrix.
> Mcol <- outer(y, x, "==")
> Mcol[] <- as.integer(Mcol)
> Mrow <- outer(x, y, "==")
> Mrow[] <- as.integer(Mrow)
>
> Could I combine rows and columns or I need another different approach?
> Thanks
>
>
> --------
>
> *Sebastián Goinheix*Instituto de Economía - UdelaR
> Tel: 24001369 (int. 116)
> *Por favor, evite imprimir este correo.*
>
> 2016-12-27 17:32 GMT-03:00 Sebastián Goinheix <[email protected]>:
>
>> Thank you, i'll try in this way
>>
>>
>> --------
>>
>> *Sebastián Goinheix*Instituto de Economía - UdelaR
>> Tel: 24001369 (int. 116)
>> *Por favor, evite imprimir este correo.*
>>
>> 2016-12-27 16:52 GMT-03:00 George Vega Yon <[email protected]>:
>>
>>> Let M={m_ij} be a square matrix of size n, then m_ij = 1 iff x_j="A" and
>>> i != j. If you want to build something like that, then this should work:
>>>
>>> rm(list=ls())
>>>
>>> x <- c("A", "A", "B", "B", "A")
>>> y <- rep("A", length(x))
>>>
>>> # An entry in mat will be 1 iff target == "A"
>>> M <- outer(y, x, "==")
>>> M[] <- as.integer(M)
>>> diag(M) <- 0
>>>
>>> dimnames(M) <- list(x,x)
>>> M
>>>
>>> # A nicer way of printing it
>>> library(Matrix)
>>> methods::as(M, "dgCMatrix")
>>>
>>> > methods::as(M, "dgCMatrix")
>>> 5 x 5 sparse Matrix of class "dgCMatrix"
>>> A A B B A
>>> A . 1 . . 1
>>> A 1 . . . 1
>>> B 1 1 . . 1
>>> B 1 1 . . 1
>>> A 1 1 . . .
>>>
>>>
>>> Best,
>>>
>>> George G. Vega Yon
>>> +1 (626) 381 8171 <(626)%20381-8171>
>>> http://cana.usc.edu/vegayon
>>>
>>> On Tue, Dec 27, 2016 at 11:41 AM, Sebastián Goinheix <[email protected]
>>> > wrote:
>>>
>>>> Hi:
>>>> I tried the outer function but I couldn't fix it.
>>>> The solution you suggest is another way of generate homophilia matrices
>>>> (linking vertices with equal characteristics). Actually what I need is to
>>>> generate links between all the nodes and those that have a specific
>>>> attribute, as:
>>>> A A B B B
>>>> A 0 1 1 1 1
>>>> A 1 0 1 1 1
>>>> B 1 1 0 0 0
>>>> B 1 1 0 0 0
>>>> B 1 1 0 0 0
>>>>
>>>> Any ideas?
>>>> thank you very much!
>>>>
>>>>
>>>> --------
>>>>
>>>> *Sebastián Goinheix*Instituto de Economía - UdelaR
>>>> Tel: 24001369 (int. 116)
>>>> *Por favor, evite imprimir este correo.*
>>>>
>>>> 2016-12-21 23:24 GMT-03:00 Sebastián Goinheix <[email protected]>:
>>>>
>>>>> Thanks George
>>>>>
>>>>>
>>>>> --------
>>>>>
>>>>> *Sebastián Goinheix*Instituto de Economía - UdelaR
>>>>> Tel: 24001369 (int. 116)
>>>>> *Por favor, evite imprimir este correo.*
>>>>>
>>>>> 2016-12-21 16:33 GMT-03:00 George Vega Yon <[email protected]>:
>>>>>
>>>>>> Does this works?
>>>>>>
>>>>>> rm(list=ls())
>>>>>>
>>>>>> x <- c("A", "A", "B", "B", "B")
>>>>>> mat <- outer(x, x, "==")
>>>>>> mat[] <- as.integer(mat)
>>>>>>
>>>>>> dimnames(mat) <- list(x,x)
>>>>>> mat
>>>>>>
>>>>>> > mat
>>>>>> A A B B B
>>>>>> A 1 1 0 0 0
>>>>>> A 1 1 0 0 0
>>>>>> B 0 0 1 1 1
>>>>>> B 0 0 1 1 1
>>>>>> B 0 0 1 1 1
>>>>>>
>>>>>> Best,
>>>>>>
>>>>>> George G. Vega Yon
>>>>>> +1 (626) 381 8171 <(626)%20381-8171>
>>>>>> http://cana.usc.edu/vegayon
>>>>>>
>>>>>> On Wed, Dec 21, 2016 at 9:21 AM, Sebastián Goinheix <
>>>>>> [email protected]> wrote:
>>>>>>
>>>>>>> Hi,
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> I want to perform network regresion with QAP procedure (netlm
>>>>>>> function of sna package).
>>>>>>> I have matrices with some inter-organizational relations, and
>>>>>>> with calculated matrices for homophily hypotheses through the
>>>>>>> bipartite.projection function.
>>>>>>> But now I need a matrix that contains links from all nodes to those
>>>>>>> that have a specific attribute, say "A". For example:
>>>>>>>
>>>>>>> nodes attributes
>>>>>>> 1 A
>>>>>>> 2 A
>>>>>>> 3 B
>>>>>>> 4 B
>>>>>>> 5 B
>>>>>>>
>>>>>>> Therefore, the resulting adjacency matrix will be:
>>>>>>>
>>>>>>> 1 2 3 4 5
>>>>>>> 1 0 1 1 1 1
>>>>>>> 2 1 0 1 1 1
>>>>>>> 3 1 1 0 0 0
>>>>>>> 4 1 1 0 0 0
>>>>>>> 5 1 1 0 0 0
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> I assume the sample_pa function will not work since the network is
>>>>>>> based on vertex attributes
>>>>>>> and
>>>>>>> the model should not be random
>>>>>>> .
>>>>>>>
>>>>>>> How can I get it in Igraph (or other)?
>>>>>>> Thanks
>>>>>>>
>>>>>>>
>>>>>>> --------
>>>>>>>
>>>>>>> *Sebastián Goinheix*Instituto de Economía - UdelaR
>>>>>>> Tel: 24001369 (int. 116)
>>>>>>> *Por favor, evite imprimir este correo.*
>>>>>>>
>>>>>>>
>>>>>>> _______________________________________________
>>>>>>> igraph-help mailing list
>>>>>>> [email protected]
>>>>>>> https://lists.nongnu.org/mailman/listinfo/igraph-help
>>>>>>>
>>>>>>>
>>>>>>
>>>>>> _______________________________________________
>>>>>> igraph-help mailing list
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>>>>>>
>>>>>>
>>>>>
>>>>
>>>> _______________________________________________
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>>>>
>>>
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>>
>
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