(dummies, sym, indices)
return res
Return list of minima of the orbits of indices in group of dummies
    see `double_coset_can_rep` for the description of `dummies` and `sym`
    indices is the initial list of dummy indices

    Examples
    ========

    >>> from sympy.combinatorics.tensor_can import _min_dummies
    >>> _min_dummies([list(range(2, 8))], [0], list(range(10)))
    [0, 1, 2, 2, 2, 2, 2, 2, 8, 9]
Return list of minima of the orbits of indices in group of dummies
    see `double_coset_can_rep` for the description of `dummies` and `sym`
    indices is the initial list of dummy indices
Return list of minima of the orbits of indices in group of dummies see double_coset_can_rep for the description of dummies and sym indices is the initial list of dummy indices
def _min_dummies(dummies, sym, indices):
    """
    Return list of minima of the orbits of indices in group of dummies
    see `double_coset_can_rep` for the description of `dummies` and `sym`
    indices is the initial list of dummy indices

    Examples
    ========

    >>> from sympy.combinatorics.tensor_can import _min_dummies
    >>> _min_dummies([list(range(2, 8))], [0], list(range(10)))
    [0, 1, 2, 2, 2, 2, 2, 2, 8, 9]
    """
    num_types = len(sym)
    m = []
    for dx in dummies:
        if dx:
            m.append(min(dx))
        else:
            m.append(None)
    res = indices[:]
    for i in range(num_types):
        for c, i in enumerate(indices):
            for j in range(num_types):
                if i in dummies[j]:
                    res[c] = m[j]
                    break
    return res
def _min_dummies ( dummies , sym , indices ) : num_types = len ( sym ) m = [ ] for dx in dummies : if dx : m . append ( min ( dx ) ) else : m . append ( None ) res = indices [ : ] for i in range ( num_types ) : for c , i in enumerate ( indices ) : for j in range ( num_types ) : if i in dummies [ j ] : res [ c ] = m [ j ] break return res