# weight_matrix2states: Returns unique state assignment from a (row-wise) weight matrix

### Description

Converts a probabilistic cluster assignment to a unique cluster assignment using the

'argmax' rule:

state of row i is assigned as the position of the maximum in that row (ties are broken at random).

'sample' rule

state of row i is sampled from the discrete distribution where probabilities equal the weight vector in row i

### Usage

 1 weight_matrix2states(weight.matrix, rule = c("argmax", "sample")) 

### Arguments

 weight.matrix an N \times K matrix rule how do we choose the state given the weight matrix. c("argmax", "sample").

states2weight_matrix
 1 2 3 4 5 6 7 8 WW <- matrix(runif(12), ncol = 3) WW <- normalize(WW) WW weight_matrix2states(WW) weight_matrix2states(WW, "sample") # another 'sample' is in general different from previous conversion unless WW is # a 0/1 matrix weight_matrix2states(WW, "sample")