generate_multiple_graphs_with_same_setting.py
from subprocess import call
import math
def generate():
#root_folder = "experiment_non_uniform_ER"
#root_folder = "experiment_non_uniform_ER2"
#root_folder = "experiment_non_uniform_ER3"
#root_folder = "experiment_non_uniform_ER_test"
#root_folder = "experiment_ER4"
#root_folder = "experiment_WS"
#root_folder = "experiment_WS2"
#root_folder = "experiment_BA2"
#root_folder = "exp_ER_wgt_subset"
#root_folder = "exp_ER_wgt_subset_2"
#root_folder = "exp_ER_wgt_subset_3"
#root_folder = "exp_ER_wgt_subset_4"
#root_folder = "exp_GE_wgt_subset_5"
#root_folder = "exp_all_wgt_subset_6"
root_folder = "exp_all_wgt_large"
#root_folder = "experiment_2"
#root_folder = "experiment_4"
#call(["rm", "-rf", "Graph_generator/"+experiment_name])
call(["mkdir", root_folder])
name_of_graph_class = ['WS','ER','BA','GE']
name_of_graph_class_code = ['0','1','2','3']
#name_of_graph_class = ['ER']
#name_of_graph_class = ['WS']
#name_of_graph_class = ['BA']
#name_of_graph_class = ['GE']
#name_of_graph_class_code = ['1']
#name_of_graph_class_code = ['0']
#name_of_graph_class_code = ['2']
#name_of_graph_class_code = ['3']
#number_of_nodes_progression = [100, 100, 100]
#number_of_nodes_progression = [80, 80, 80]
#number_of_nodes_progression = [40, 40, 40]
number_of_nodes_progression = [500 for i in range(10)]
#number_of_nodes_progression = [100, 100, 100, 100, 100, 100]
#number_of_nodes_progression = [300]
#number_of_nodes_progression = [100]
#number_of_nodes_progression = [30, 30]
#number_of_levels = [1, 2, 3]
number_of_levels = [i for i in range(1, 11)]
#number_of_levels = [1]
#number_of_levels = [2, 3, 4, 5, 6, 7]
#number_of_levels = [2, 3]
#number_of_nodes_progression = [15, 15, 15]
#number_of_levels = [1, 2, 3]
node_distribution_in_levels = ['L','E']
node_distribution_in_levels_code = ['0','1']
#node_distribution_in_levels = ['L']
#node_distribution_in_levels_code = ['0']
param1 = ['6', '.25', '5', '1.62']
param2 = ['.2', '0', '0', '0']
#param1 = ['.25']
#param2 = ['0']
#param1 = ['6']
#param2 = ['.2']
#param1 = ['5']
#param2 = ['0']
#initial_nodes = 10
initial_nodes = 50
#node_increment = 5
#node_increment = 2
node_increment = 50
#initial_nodes = 20
#node_increment = 20
number_of_graphs_with_same_setting = 5
#number_of_graphs_with_same_setting = 10
curr_id = 1
f1 = open(root_folder + '/id_to_file.csv', 'w')
f2 = open(root_folder + '/id_to_file_subset.csv', 'w')
f3 = open(root_folder + '/id_to_file_local.csv', 'w')
f4 = open(root_folder + '/id_to_file_pairwise2W.csv', 'w')
f5 = open(root_folder + '/id_to_file_local4W.csv', 'w')
f6 = open(root_folder + '/id_to_file_pairwise4W.csv', 'w')
f7 = open(root_folder + '/id_to_file_global6W.csv', 'w')
f8 = open(root_folder + '/id_to_file_pairwise6W.csv', 'w')
f9 = open(root_folder + '/id_to_file_pairwise2W_d2.csv', 'w')
f10 = open(root_folder + '/id_to_file_pairwise2W_d4.csv', 'w')
f11 = open(root_folder + '/id_to_file_pairwise2W_d8.csv', 'w')
#f2 = open(root_folder + '/id_to_file_qos.csv', 'w')
#f3 = open(root_folder + '/id_to_file_cmp.csv', 'w')
#f4 = open(root_folder + '/id_to_file_CMP_exact.csv', 'w')
#f5 = open(root_folder + '/id_to_file_kruskal.csv', 'w')
for cl in range(len(name_of_graph_class)):
for l in range(len(number_of_levels)):
for nd in range(len(node_distribution_in_levels)):
common_part_of_name = name_of_graph_class[cl]+'_'+str(number_of_nodes_progression[l])+'_'+str(number_of_levels[l])+'_'+node_distribution_in_levels[nd]
for p in range(initial_nodes, number_of_nodes_progression[l]+1, node_increment):
for i in range(number_of_graphs_with_same_setting):
if name_of_graph_class[cl] == 'ER':
param1[cl] = str((1+1)*math.log(p)/p)
elif name_of_graph_class[cl] == 'GE':
param1[cl] = str(math.sqrt((1+1)*math.log(p)/(math.pi*p)))
#call(["python3", "graph_non_uniform_generator.py", str(number_of_levels[l]), str(p), root_folder + "/graph_" + common_part_of_name + '_' + str(p) + '_' + str(i), name_of_graph_class_code[cl], param1[cl], param2[cl], node_distribution_in_levels_code[nd]])
# Uncomment the following, not above one
#call(["python3", "graph_generator_v2.py", str(number_of_levels[l]), str(p), root_folder + "/graph_" + common_part_of_name + '_' + str(p) + '_' + str(i), name_of_graph_class_code[cl], param1[cl], param2[cl], node_distribution_in_levels_code[nd]])
#f1.write(str(curr_id) + ';' + 'mlst_exact.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + 'output_exact.csv' + ';\n')
f1.write(str(curr_id) + ';' + 'additive_spanner_exact_algorithm.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + '2' + ';\n')
#f2.write(str(curr_id) + ';' + 'mlst_charikar.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + 'output_qos.csv' + ';\n')
#f2.write(str(curr_id) + ';' + 'mlst_qos.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + 'output_qos.csv' + ';\n')
#f2.write(str(curr_id) + ';' + 'subsetwise.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + 'output_subset.csv' + ';\n')
f2.write(str(curr_id) + ';' + 'subsetwise_2W.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + 'output_subset.csv' + ';\n')
f3.write(str(curr_id) + ';' + 'additive_spanner_exact_algorithm_local.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + '2' + ';\n')
f4.write(str(curr_id) + ';' + 'pairwise.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + '2' + ';\n')
f5.write(str(curr_id) + ';' + 'additive_spanner_exact_algorithm_local.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + '4' + ';\n')
f6.write(str(curr_id) + ';' + 'pairwise.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + '4' + ';\n')
f7.write(str(curr_id) + ';' + 'additive_spanner_exact_algorithm.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + '6' + ';\n')
f8.write(str(curr_id) + ';' + 'pairwise.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + '6' + ';\n')
f9.write(str(curr_id) + ';' + 'pairwise_d.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + '2' + ';' + '2' + ';\n')
f10.write(str(curr_id) + ';' + 'pairwise_d.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + '2' + ';' + '4' + ';\n')
f11.write(str(curr_id) + ';' + 'pairwise_d.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + '2' + ';' + '8' + ';\n')
#f3.write(str(curr_id) + ';' + 'mlst_cmp.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + 'output_cmp.csv' + ';\n')
#f5.write(str(curr_id) + ';' + 'mlst_kruskal_non_uniform2.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + 'output_kruskal.csv' + ';\n')
#f5.write(str(curr_id) + ';' + 'mlst_kruskal_non_uniform_update_cost.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + 'output_kruskal.csv' + ';\n')
#f5.write(str(curr_id) + ';' + 'mlst_cmp.py' + ';' + root_folder + ';' + "graph_" + common_part_of_name + '_' + str(p) + '_' + str(i) + ';' + 'output_kruskal.csv' + ';\n')
curr_id = curr_id + 1
f1.close()
f2.close()
f3.close()
f4.close()
f5.close()
f6.close()
f7.close()
f8.close()
f9.close()
f10.close()
f11.close()
generate()
