added LeaderRankAlgo for finding key vertices

[Dabzelos]

added: parameterizable LeaderRank algorithm also added visualization for this algorithm To see the results click "Find Key vertices with leader Rank" button You'll see the dialogue window with parameters to input: you may input amount of vertices XOR the gap of ranks to see after that TopRankedVertices will be coloured with red

the idea of algorithn itself: LeaderRank(graph G, damping_factor d, convergence_threshold epsilon)

1. Initialize the vertex ratings: each vertex v_i has a rating R(v_i) = 1 / |V|, where |V| is the total number of vertices in graph G.
2. Let's construct the adjacency matrix A of graph G.
3. Let's construct a matrix of transition probabilities P: P = A / deg, where deg is the number of outgoing edges for each vertex.
4. Repeat until convergence: 4.1. Calculate the new vertex ratings: R_new = (1-d) / | V| + d P R, where d is the attenuation coefficient. 4.2. Calculate the change in ratings: diff = ||R_new - R|| 4.3. If diff < epsilon, interrupt the iterations. 4.4. Assign R = R_new and continue iterating.
5. We display the ratings of the vertices in descending order.

[xamelllion]