def _getarray(loci, tree):
    """ 
    parse the loci file list and return presence/absence matrix
    ordered by the tips on the tree
    """

    ## order tips
    tree.ladderize()

    ## get tip names
    snames = tree.get_leaf_names()

    ## make an empty matrix
    lxs = np.zeros((len(snames), len(loci)), dtype=np.int)

    ## fill the matrix
    for loc in xrange(len(loci)):
        for seq in loci[loc].split("\n")[:-1]:
            lxs[snames.index(seq.split()[0]), loc] += 1

    return lxs, snames
def _getarray(loci, tree):
    

    
    tree.ladderize()

    
    snames = tree.get_leaf_names()

    
    lxs = np.zeros((len(snames), len(loci)), dtype=np.int)

    
    for loc in xrange(len(loci)):
        for seq in loci[loc].split("\n")[:-1]:
            lxs[snames.index(seq.split()[0]), loc] += 1

    return lxs, snames
def _getarray ( loci , tree ) : ## order tips tree . ladderize ( ) ## get tip names snames = tree . get_leaf_names ( ) ## make an empty matrix lxs = np . zeros ( ( len ( snames ) , len ( loci ) ) , dtype = np . int ) ## fill the matrix for loc in xrange ( len ( loci ) ) : for seq in loci [ loc ] . split ( "\n" ) [ : - 1 ] : lxs [ snames . index ( seq . split ( ) [ 0 ] ) , loc ] += 1 return lxs , snames
parse the loci file list and return presence/absence matrix
    ordered by the tips on the tree
parse the loci file list and return presence / absence matrix ordered by the tips on the tree