# -*- coding: utf-8 -*- """ >>> from pyrgg.functions import * >>> from pyrgg.graph_gen import * >>> import pyrgg.params >>> import random >>> import os >>> import json >>> import pyrgg.engines.geometric_graph as engine >>> os.environ["PYRGG_TEST_MODE"] = "1" >>> ###################################### >>> ## ========= logger function ========= >>> ###################################### >>> with open('logfile.log','a') as file: ... engine.logger(file,'test','2min',{'vertices':100,'edge_number':50,'space_dimension':2,'cutoff_threshold':0.5,'engine':7,'output_format':1}) >>> file = open('logfile.log','r') >>> print("\\n".join(file.read().splitlines()[1:-1])) Filename : test Vertices : 100 Space Dimension : 2 Cutoff Threshold : 0.5 Total Edges : 50 Engine : 7 (gg) Elapsed Time : 2min >>> class StrError: ... def __init__(self): ... pass ... def __str__(self): ... raise ValueError >>> str_error_object = StrError() >>> with open('logfile.log','a') as file: ... engine.logger(file,'test','2min',{'vertices':str_error_object,'edge_number':50,'space_dimension':2,'cutoff_threshold':0.5,'engine':7,'output_format':1}) [Error] Logger failed! >>> ########################################## >>> ## ========= edge_gen function ========= >>> ########################################## >>> random.seed(2) >>> edge_dict, weight_dict, edge_number = engine.generate_edges(10, 2, 0.5) >>> edge_dict == {1: [3, 5, 8, 9], 2: [7, 10], 3: [4, 5, 8, 9], 4: [5, 6, 7, 9, 10], 5: [6, 7, 8, 9, 10], 6: [7, 10], 7: [10], 8: [], 9: [], 10: []} True >>> weight_dict == {1: [0.24375, 0.48873, 0.23771, 0.40371], 2: [0.48501, 0.42942], 3: [0.45883, 0.2634, 0.28223, 0.22306], 4: [0.3054, 0.17396, 0.25386, 0.36596, 0.22839], 5: [0.4491, 0.27605, 0.40529, 0.34911, 0.37493], 6: [0.27921, 0.1751], 7: [0.12609], 8: [], 9: [], 10: []} True >>> edge_number == 23 True >>> engine.generate_edges(0) Traceback (most recent call last): ... TypeError: generate_edges() missing 2 required positional arguments: 'd' and 'r' >>> ######################################### >>> ## ========= generate_graph function ========= >>> ######################################### >>> #################### generate_dimacs_file #################### >>> random.seed(2) >>> engine.generate_graph(generate_dimacs_file, 'testfile', {'vertices': 10, 'space_dimension': 2, 'cutoff_threshold': 0.5}) 23 >>> file=open('testfile.gr','r') >>> print(file.read()) c FILE :testfile.gr c No. of vertices :10 c No. of edges :23 c Max. weight :0.48873 c Min. weight :0.12609 p sp 10 23 a 1 3 0.24375 a 1 5 0.48873 a 1 8 0.23771 a 1 9 0.40371 a 2 7 0.48501 a 2 10 0.42942 a 3 4 0.45883 a 3 5 0.2634 a 3 8 0.28223 a 3 9 0.22306 a 4 5 0.3054 a 4 6 0.17396 a 4 7 0.25386 a 4 9 0.36596 a 4 10 0.22839 a 5 6 0.4491 a 5 7 0.27605 a 5 8 0.40529 a 5 9 0.34911 a 5 10 0.37493 a 6 7 0.27921 a 6 10 0.1751 a 7 10 0.12609 >>> #################### generate_json_file #################### >>> random.seed(2) >>> engine.generate_graph(generate_json_file, 'testfile', {'vertices': 10, 'space_dimension': 2, 'cutoff_threshold': 0.5}) 23 >>> file=open('testfile.json','r') >>> testfile_1=json.load(file) >>> testfile_1['graph']['nodes'][1] {'id': 2} >>> testfile_1['graph']['edges'][1]['source'] 1 >>> testfile_1['graph']['edges'][1]['target'] 5 >>> #################### generate_csv_file #################### >>> random.seed(2) >>> engine.generate_graph(generate_csv_file, 'testfile', {'vertices': 10, 'space_dimension': 2, 'cutoff_threshold': 0.5}) 23 >>> file=open('testfile.csv','r') >>> print(file.read()) 1,3,0.24375 1,5,0.48873 1,8,0.23771 1,9,0.40371 2,7,0.48501 2,10,0.42942 3,4,0.45883 3,5,0.2634 3,8,0.28223 3,9,0.22306 4,5,0.3054 4,6,0.17396 4,7,0.25386 4,9,0.36596 4,10,0.22839 5,6,0.4491 5,7,0.27605 5,8,0.40529 5,9,0.34911 5,10,0.37493 6,7,0.27921 6,10,0.1751 7,10,0.12609 >>> #################### generate_gdf_file #################### >>> random.seed(2) >>> engine.generate_graph(generate_gdf_file, 'testfile', {'vertices': 10, 'space_dimension': 2, 'cutoff_threshold': 0.5}) 23 >>> file=open('testfile.gdf','r') >>> print(file.read()) nodedef>name VARCHAR,label VARCHAR 1,Node1 2,Node2 3,Node3 4,Node4 5,Node5 6,Node6 7,Node7 8,Node8 9,Node9 10,Node10 edgedef>node1 VARCHAR,node2 VARCHAR,weight DOUBLE 1,3,0.24375 1,5,0.48873 1,8,0.23771 1,9,0.40371 2,7,0.48501 2,10,0.42942 3,4,0.45883 3,5,0.2634 3,8,0.28223 3,9,0.22306 4,5,0.3054 4,6,0.17396 4,7,0.25386 4,9,0.36596 4,10,0.22839 5,6,0.4491 5,7,0.27605 5,8,0.40529 5,9,0.34911 5,10,0.37493 6,7,0.27921 6,10,0.1751 7,10,0.12609 >>> #################### generate_gl_file #################### >>> random.seed(2) >>> engine.generate_graph(generate_gl_file, 'testfile', {'vertices': 10, 'space_dimension': 2, 'cutoff_threshold': 0.5}) 23 >>> file=open('testfile.gl','r') >>> print(file.read()) 1 3:0.24375 5:0.48873 8:0.23771 9:0.40371 2 7:0.48501 10:0.42942 3 4:0.45883 5:0.2634 8:0.28223 9:0.22306 4 5:0.3054 6:0.17396 7:0.25386 9:0.36596 10:0.22839 5 6:0.4491 7:0.27605 8:0.40529 9:0.34911 10:0.37493 6 7:0.27921 10:0.1751 7 10:0.12609 >>> #################### generate_mtx_file #################### >>> from scipy.io import mmread >>> random.seed(2) >>> engine.generate_graph(generate_mtx_file, 'testfile', {'vertices': 10, 'space_dimension': 2, 'cutoff_threshold': 0.5}) 23 >>> g = mmread("testfile.mtx") >>> print(g.data.tolist()) [0.24375, 0.48873, 0.23771, 0.40371, 0.48501, 0.42942, 0.45883, 0.2634, 0.28223, 0.22306, 0.3054, 0.17396, 0.25386, 0.36596, 0.22839, 0.4491, 0.27605, 0.40529, 0.34911, 0.37493, 0.27921, 0.1751, 0.12609] >>> #################### generate_tsv_file #################### >>> random.seed(2) >>> engine.generate_graph(generate_tsv_file, 'testfile', {'vertices': 10, 'space_dimension': 2, 'cutoff_threshold': 0.5}) 23 >>> file=open('testfile.tsv','r') >>> print(file.read()) 1 3 0.24375 1 5 0.48873 1 8 0.23771 1 9 0.40371 2 7 0.48501 2 10 0.42942 3 4 0.45883 3 5 0.2634 3 8 0.28223 3 9 0.22306 4 5 0.3054 4 6 0.17396 4 7 0.25386 4 9 0.36596 4 10 0.22839 5 6 0.4491 5 7 0.27605 5 8 0.40529 5 9 0.34911 5 10 0.37493 6 7 0.27921 6 10 0.1751 7 10 0.12609 >>> #################### generate_wel_file #################### >>> random.seed(2) >>> engine.generate_graph(generate_wel_file, 'testfile', {'vertices': 10, 'space_dimension': 2, 'cutoff_threshold': 0.5}) 23 >>> file=open('testfile.wel','r') >>> print(file.read()) 1 3 0.24375 1 5 0.48873 1 8 0.23771 1 9 0.40371 2 7 0.48501 2 10 0.42942 3 4 0.45883 3 5 0.2634 3 8 0.28223 3 9 0.22306 4 5 0.3054 4 6 0.17396 4 7 0.25386 4 9 0.36596 4 10 0.22839 5 6 0.4491 5 7 0.27605 5 8 0.40529 5 9 0.34911 5 10 0.37493 6 7 0.27921 6 10 0.1751 7 10 0.12609 >>> #################### generate_lp_file #################### >>> random.seed(2) >>> engine.generate_graph(generate_lp_file, 'testfile', {'vertices': 10, 'space_dimension': 2, 'cutoff_threshold': 0.5}) 23 >>> file=open('testfile.lp','r') >>> print(file.read()) node(1). node(2). node(3). node(4). node(5). node(6). node(7). node(8). node(9). node(10). edge(1,3,0.24375). edge(1,5,0.48873). edge(1,8,0.23771). edge(1,9,0.40371). edge(2,7,0.48501). edge(2,10,0.42942). edge(3,4,0.45883). edge(3,5,0.2634). edge(3,8,0.28223). edge(3,9,0.22306). edge(4,5,0.3054). edge(4,6,0.17396). edge(4,7,0.25386). edge(4,9,0.36596). edge(4,10,0.22839). edge(5,6,0.4491). edge(5,7,0.27605). edge(5,8,0.40529). edge(5,9,0.34911). edge(5,10,0.37493). edge(6,7,0.27921). edge(6,10,0.1751). edge(7,10,0.12609). >>> #################### generate_tgf_file #################### >>> random.seed(2) >>> engine.generate_graph(generate_tgf_file, 'testfile', {'vertices': 10, 'space_dimension': 2, 'cutoff_threshold': 0.5}) 23 >>> file=open('testfile.tgf','r') >>> print(file.read()) 1 2 3 4 5 6 7 8 9 10 # 1 3 0.24375 1 5 0.48873 1 8 0.23771 1 9 0.40371 2 7 0.48501 2 10 0.42942 3 4 0.45883 3 5 0.2634 3 8 0.28223 3 9 0.22306 4 5 0.3054 4 6 0.17396 4 7 0.25386 4 9 0.36596 4 10 0.22839 5 6 0.4491 5 7 0.27605 5 8 0.40529 5 9 0.34911 5 10 0.37493 6 7 0.27921 6 10 0.1751 7 10 0.12609 >>> #################### generate_dl_file #################### >>> random.seed(2) >>> engine.generate_graph(generate_dl_file, 'testfile', {'vertices': 10, 'space_dimension': 2, 'cutoff_threshold': 0.5}) 23 >>> file=open('testfile.dl','r') >>> print(file.read()) dl format=edgelist1 n=10 data: 1 3 0.24375 1 5 0.48873 1 8 0.23771 1 9 0.40371 2 7 0.48501 2 10 0.42942 3 4 0.45883 3 5 0.2634 3 8 0.28223 3 9 0.22306 4 5 0.3054 4 6 0.17396 4 7 0.25386 4 9 0.36596 4 10 0.22839 5 6 0.4491 5 7 0.27605 5 8 0.40529 5 9 0.34911 5 10 0.37493 6 7 0.27921 6 10 0.1751 7 10 0.12609 >>> #################### generate_gml_file #################### >>> from networkx.readwrite.gml import read_gml >>> random.seed(2) >>> engine.generate_graph(generate_gml_file, 'testfile', {'vertices': 10, 'space_dimension': 2, 'cutoff_threshold': 0.5}) 23 >>> gml1 = read_gml("testfile.gml") >>> type(gml1) >>> #################### generate_gexf_file #################### >>> from networkx.readwrite.gexf import read_gexf >>> random.seed(2) >>> engine.generate_graph(generate_gexf_file, 'testfile', {'vertices': 10, 'space_dimension': 2, 'cutoff_threshold': 0.5}) 23 >>> gexf1 = read_gexf("testfile.gexf") >>> type(gexf1) >>> #################### generate_dot_file #################### >>> import pydot >>> random.seed(2) >>> engine.generate_graph(generate_dot_file, 'testfile', {'vertices': 10, 'space_dimension': 2, 'cutoff_threshold': 0.5}) 23 >>> file=open('testfile.gv','r') >>> g1 = pydot.graph_from_dot_data(file.read()) >>> g1[0].get_type() 'graph' >>> len(g1[0].get_edge_list()) 23 >>> file.close() >>> os.remove('testfile.gr') >>> os.remove('testfile.json') >>> os.remove('testfile.csv') >>> os.remove('testfile.gdf') >>> os.remove('testfile.gl') >>> os.remove('testfile.mtx') >>> os.remove('testfile.tsv') >>> os.remove('testfile.wel') >>> os.remove('testfile.lp') >>> os.remove('testfile.tgf') >>> os.remove('testfile.dl') >>> os.remove('testfile.gml') >>> os.remove('testfile.gexf') >>> os.remove('testfile.gv') >>> os.remove('logfile.log') """