added PrioriKnowledge to ttpm

[juliusd01]

As mentioned in #79 , it would be great, if more algorithms would be able to use PrioriKnowledge. I added this for the TTPM algorithm.

[kelizhang]

Thank you for your effort in enhancing the usability of TTPM. We would be pleased to merge your work into our main branch after a few modifications to your current commit.

Please feel free to ignore some minor issues, as we’ll address them during the merge. However, here are a few points for you to consider or clarify:

1. In the learn() function: To enhance robustness, just suggest you consider implementing it as follows，

   edge_mat[self.priori_knowledge.matrix == 1] = 1

2. In the _one_step_change() function: Your logic is sound, but the following structure might improve clarity:

   j, i = e
   if j == i:
       return edge_mat
   
   new_edge_mat = edge_mat.copy()
   
   # Only delete the edge if removal is allowed
   if new_edge_mat[j, i] == 1 and not priori_knowledge.is_required(j, i):
       new_edge_mat[j, i] = 0
   
   # Only add the edge if addition is allowed
   if new_edge_mat[j, i] == 0 and not priori_knowledge.is_forbidden(j, i) and not priori_knowledge.is_required(i, j):
       new_edge_mat[j, i] = 1
       new_edge_mat[i, j] = 0
   
   return edge_mat

[kelizhang]

As mentioned in #79 , it would be great, if more algorithms would be able to use PrioriKnowledge. I added this for the TTPM algorithm.

if you agree， we'll merge your commit first, and then tweak it.

[juliusd01]

Yes, that's fine for me