Graph Simulation

Graph 1	Calculate algebratic connectivity and spectral gap and others for erdos renyi and watts strogatz and barabasi albert graph
Graph2	Create RSRBG Graph and other parameters
Graph 3	A pseudo-regular RSRG graph is constructed and the plots for degree distribution, eigenvalue distribution and Also, the parameters of spectral gap, natural connectivity, symmetry ratio, energy and Laplacian energy is drawn.Next we Choose one from the set of p values in each step and Calculate values for that and run 100 to 1000 times . then we calculated average algebraic connection by Monte Carlo simulation and plot the probability density distribution for the allowed values of d .
Graph4	In this part , 100 nodes are considered for each graph. from the function bipartite.random_graph We create a random bipartite graph. Then, using bipartite.projected_graph, project the bipartite graph on the first set of nodes to obtain the recursive bipartite graph without measure S. Finally, the degree distribution and The PDF is calculated and plotted.
Graph 4-part 2	Eigenvalues of the adjacency matrix of each graph using np.linalg.eigvals function Is calculated . Then, we generate a histogram of eigenvalues and also calculate the PDF. Finally, we plot the eigenvalue distribution for each graph.
Graph 5	We generate SF graph with 500 nodes and degree 4 for each node 1000 times or more ,Then we generate the probability density function of the degree distribution (PDF) in the log-log scale for each. In the next step, we divide the production of SF graphs into categories that Each batch contains the number of batch_size (ten). after producing each batch, We print the progress. We calculate the average degree for each network size by generating num_graphs SF graphs for each size and their average degrees. Then we get the Average degree plot drawn based on the size of the corresponding network.
Graph 6	Calculation of inconsistency probability for x-regular graphs when we eliminate edges one by one to make the graph inconsistent using simulation test.then we do so for RSRBG graphs in size 500 for nodes and 1500 for edges. Edge, algebraic and nodal connectivity is calculated in each step.
Graph7	Generating graphs with most waist with an specific average degree and size.
Graph 8	Calculation of network isolation probability using simulation tests.
Graph 9-Part 1	TTT plot based on scaled time for nodes lifetime distributions in constructed networks is drawn.
Graph 9-Part 2	NWUE-ness in thick tail , Weibull and pareto distribution when plot parameters is considered stable and scale parameters is changing is studied . after that considering 5% for error , we calculate p-value for H0:X~Y versus HA:X>=NWUE Y