# unfold-methods

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##### Tensor Unfolding

Unfolds the tensor into a matrix, with the modes in rs onto the rows and modes in cs onto the columns. Note that c(rs,cs) must have the same elements (order doesn't matter) as x@modes. Within the rows and columns, the order of the unfolding is determined by the order of the modes. This convention is consistent with Kolda and Bader (2009).

##### Usage
unfold(tnsr, row_idx, col_idx)# S4 method for Tensor
unfold(tnsr, row_idx = NULL, col_idx = NULL)
##### Arguments
tnsr

the Tensor instance

row_idx

the indices of the modes to map onto the row space

col_idx

the indices of the modes to map onto the column space

##### Details

For Row Space Unfolding or m-mode Unfolding, see rs_unfold-methods. For Column Space Unfolding or matvec, see cs_unfold-methods.

vec-methods returns the vectorization of the tensor.

unfold(tnsr,row_idx=NULL,col_idx=NULL)

##### Value

matrix with prod(row_idx) rows and prod(col_idx) columns

##### References

T. Kolda, B. Bader, "Tensor decomposition and applications". SIAM Applied Mathematics and Applications 2009.

k_unfold-methods and matvec-methods

##### Aliases
• unfold-methods
• unfold
• unfold,Tensor-method
##### Examples
# NOT RUN {
tnsr <- rand_tensor()
matT3<-unfold(tnsr,row_idx=2,col_idx=c(3,1))
# }

Documentation reproduced from package rTensor, version 1.4, License: GPL (>= 2)

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