#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Tue Jan 14 15:39:29 2020 @author: ljia """ import multiprocessing import functools import sys import os import logging from gklearn.utils.kernels import deltakernel, gaussiankernel, kernelproduct from gklearn.preimage import generate_random_preimages_by_class from gklearn.utils import compute_gram_matrices_by_class dir_root = '../results/xp_random_preimage/' def xp_median_preimage_15_1(): """xp 15_1: AIDS, StructuralSP, using CONSTANT, symbolic only. """ # set parameters. ds_name = 'AIDS' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} mixkernel = functools.partial(kernelproduct, deltakernel, gaussiankernel) sub_kernels = {'symb': deltakernel, 'nsymb': gaussiankernel, 'mix': mixkernel} kernel_options = {'name': 'StructuralSP', 'edge_weight': None, 'node_kernels': sub_kernels, 'edge_kernels': sub_kernels, 'compute_method': 'naive', 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '.symb/' irrelevant_labels = {'node_attrs': ['chem', 'charge', 'x', 'y'], 'edge_labels': ['valence']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_15_2(): """xp 15_2: AIDS, PathUpToH, using CONSTANT, symbolic only. """ # set parameters. ds_name = 'AIDS' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} kernel_options = {'name': 'PathUpToH', 'depth': 1, # 'k_func': 'MinMax', # 'compute_method': 'trie', 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '.symb/' irrelevant_labels = {'node_attrs': ['chem', 'charge', 'x', 'y'], 'edge_labels': ['valence']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_15_3(): """xp 15_3: AIDS, Treelet, using CONSTANT, symbolic only. """ from gklearn.utils.kernels import polynomialkernel # set parameters. ds_name = 'AIDS' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} pkernel = functools.partial(polynomialkernel, d=1, c=1e+2) kernel_options = {'name': 'Treelet', # 'sub_kernel': pkernel, 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '.symb/' irrelevant_labels = {'node_attrs': ['chem', 'charge', 'x', 'y'], 'edge_labels': ['valence']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_15_4(): """xp 15_4: AIDS, WeisfeilerLehman, using CONSTANT, symbolic only. """ # set parameters. ds_name = 'AIDS' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} kernel_options = {'name': 'WeisfeilerLehman', 'height': 10, 'base_kernel': 'subtree', 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '.symb/' irrelevant_labels = {'node_attrs': ['chem', 'charge', 'x', 'y'], 'edge_labels': ['valence']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # # compute gram matrices for each class a priori. # print('Compute gram matrices for each class a priori.') # compute_gram_matrices_by_class(ds_name, kernel_options, save_results=True, dir_save=dir_save, irrelevant_labels=irrelevant_labels) # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_14_1(): """xp 14_1: DD, PathUpToH, using CONSTANT. """ # set parameters. ds_name = 'DD' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} kernel_options = {'name': 'PathUpToH', 'depth': 2, # 'k_func': 'MinMax', # 'compute_method': 'trie', 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '/' irrelevant_labels = None # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # # compute gram matrices for each class a priori. # print('Compute gram matrices for each class a priori.') # compute_gram_matrices_by_class(ds_name, kernel_options, save_results=save_results, dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_12_1(): """xp 12_1: PAH, StructuralSP, using NON_SYMBOLIC, unlabeled. """ # set parameters. ds_name = 'PAH' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} mixkernel = functools.partial(kernelproduct, deltakernel, gaussiankernel) sub_kernels = {'symb': deltakernel, 'nsymb': gaussiankernel, 'mix': mixkernel} kernel_options = {'name': 'StructuralSP', 'edge_weight': None, 'node_kernels': sub_kernels, 'edge_kernels': sub_kernels, 'compute_method': 'naive', 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '.unlabeled/' irrelevant_labels = {'node_attrs': ['x', 'y', 'z'], 'edge_labels': ['bond_stereo']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_12_2(): """xp 12_2: PAH, PathUpToH, using CONSTANT, unlabeled. """ # set parameters. ds_name = 'PAH' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} kernel_options = {'name': 'PathUpToH', 'depth': 1, # 'k_func': 'MinMax', # 'compute_method': 'trie', 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '.unlabeled/' irrelevant_labels = {'node_attrs': ['x', 'y', 'z'], 'edge_labels': ['bond_stereo']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_12_3(): """xp 12_3: PAH, Treelet, using CONSTANT, unlabeled. """ from gklearn.utils.kernels import gaussiankernel # set parameters. ds_name = 'PAH' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} pkernel = functools.partial(gaussiankernel, gamma=None) # @todo kernel_options = {'name': 'Treelet', # 'sub_kernel': pkernel, 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '.unlabeled/' irrelevant_labels = {'node_attrs': ['x', 'y', 'z'], 'edge_labels': ['bond_stereo']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_12_4(): """xp 12_4: PAH, WeisfeilerLehman, using CONSTANT, unlabeled. """ # set parameters. ds_name = 'PAH' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} kernel_options = {'name': 'WeisfeilerLehman', 'height': 14, 'base_kernel': 'subtree', 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '.unlabeled/' irrelevant_labels = {'node_attrs': ['x', 'y', 'z'], 'edge_labels': ['bond_stereo']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # # compute gram matrices for each class a priori. # print('Compute gram matrices for each class a priori.') # compute_gram_matrices_by_class(ds_name, kernel_options, save_results=True, dir_save=dir_save, irrelevant_labels=irrelevant_labels) # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_12_5(): """xp 12_5: PAH, ShortestPath, using NON_SYMBOLIC, unlabeled. """ # set parameters. ds_name = 'PAH' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} mixkernel = functools.partial(kernelproduct, deltakernel, gaussiankernel) sub_kernels = {'symb': deltakernel, 'nsymb': gaussiankernel, 'mix': mixkernel} kernel_options = {'name': 'ShortestPath', 'edge_weight': None, 'node_kernels': sub_kernels, 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '.unlabeled/' # irrelevant_labels = {'node_attrs': ['x', 'y', 'z'], 'edge_labels': ['bond_stereo']} # edge_required = True # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_9_1(): """xp 9_1: MAO, StructuralSP, using CONSTANT, symbolic only. """ # set parameters. ds_name = 'MAO' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} mixkernel = functools.partial(kernelproduct, deltakernel, gaussiankernel) sub_kernels = {'symb': deltakernel, 'nsymb': gaussiankernel, 'mix': mixkernel} kernel_options = {'name': 'StructuralSP', 'edge_weight': None, 'node_kernels': sub_kernels, 'edge_kernels': sub_kernels, 'compute_method': 'naive', 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '.symb/' irrelevant_labels = {'node_attrs': ['x', 'y', 'z'], 'edge_labels': ['bond_type', 'bond_stereo']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_9_2(): """xp 9_2: MAO, PathUpToH, using CONSTANT, symbolic only. """ # set parameters. ds_name = 'MAO' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} kernel_options = {'name': 'PathUpToH', 'depth': 9, # 'k_func': 'MinMax', # 'compute_method': 'trie', 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '.symb/' irrelevant_labels = {'node_attrs': ['x', 'y', 'z'], 'edge_labels': ['bond_type', 'bond_stereo']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_9_3(): """xp 9_3: MAO, Treelet, using CONSTANT, symbolic only. """ from gklearn.utils.kernels import polynomialkernel # set parameters. ds_name = 'MAO' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} pkernel = functools.partial(polynomialkernel, d=4, c=1e+7) kernel_options = {'name': 'Treelet', # 'sub_kernel': pkernel, 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '.symb/' irrelevant_labels = {'node_attrs': ['x', 'y', 'z'], 'edge_labels': ['bond_type', 'bond_stereo']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_9_4(): """xp 9_4: MAO, WeisfeilerLehman, using CONSTANT, symbolic only. """ # set parameters. ds_name = 'MAO' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} kernel_options = {'name': 'WeisfeilerLehman', 'height': 6, 'base_kernel': 'subtree', 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '.symb/' irrelevant_labels = {'node_attrs': ['x', 'y', 'z'], 'edge_labels': ['bond_type', 'bond_stereo']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # # compute gram matrices for each class a priori. # print('Compute gram matrices for each class a priori.') # compute_gram_matrices_by_class(ds_name, kernel_options, save_results=True, dir_save=dir_save, irrelevant_labels=irrelevant_labels) # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_8_1(): """xp 8_1: Monoterpenoides, StructuralSP, using CONSTANT. """ # set parameters. ds_name = 'Monoterpenoides' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} mixkernel = functools.partial(kernelproduct, deltakernel, gaussiankernel) sub_kernels = {'symb': deltakernel, 'nsymb': gaussiankernel, 'mix': mixkernel} kernel_options = {'name': 'StructuralSP', 'edge_weight': None, 'node_kernels': sub_kernels, 'edge_kernels': sub_kernels, 'compute_method': 'naive', 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '/' irrelevant_labels = {'edge_labels': ['valence']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_8_2(): """xp 8_2: Monoterpenoides, PathUpToH, using CONSTANT. """ # set parameters. ds_name = 'Monoterpenoides' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} kernel_options = {'name': 'PathUpToH', 'depth': 7, # 'k_func': 'MinMax', # 'compute_method': 'trie', 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '/' irrelevant_labels = {'edge_labels': ['valence']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_8_3(): """xp 8_3: Monoterpenoides, Treelet, using CONSTANT. """ from gklearn.utils.kernels import polynomialkernel # set parameters. ds_name = 'Monoterpenoides' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 0} pkernel = functools.partial(polynomialkernel, d=2, c=1e+5) kernel_options = {'name': 'Treelet', 'sub_kernel': pkernel, 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '/' irrelevant_labels = {'edge_labels': ['valence']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_8_4(): """xp 8_4: Monoterpenoides, WeisfeilerLehman, using CONSTANT. """ # set parameters. ds_name = 'Monoterpenoides' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} kernel_options = {'name': 'WeisfeilerLehman', 'height': 4, 'base_kernel': 'subtree', 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '/' irrelevant_labels = {'edge_labels': ['valence']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_7_1(): """xp 7_1: MUTAG, StructuralSP, using CONSTANT. """ # set parameters. ds_name = 'MUTAG' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} mixkernel = functools.partial(kernelproduct, deltakernel, gaussiankernel) sub_kernels = {'symb': deltakernel, 'nsymb': gaussiankernel, 'mix': mixkernel} kernel_options = {'name': 'StructuralSP', 'edge_weight': None, 'node_kernels': sub_kernels, 'edge_kernels': sub_kernels, 'compute_method': 'naive', 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '/' irrelevant_labels = {'edge_labels': ['label_0']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_7_2(): """xp 7_2: MUTAG, PathUpToH, using CONSTANT. """ # set parameters. ds_name = 'MUTAG' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} kernel_options = {'name': 'PathUpToH', 'depth': 2, # 'k_func': 'MinMax', # 'compute_method': 'trie', 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '/' irrelevant_labels = {'edge_labels': ['label_0']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required, cut_range=None) except Exception as exp: print('An exception occured when running experiment on xp_median_preimage_7_2:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_7_3(): """xp 7_3: MUTAG, Treelet, using CONSTANT. """ from gklearn.utils.kernels import polynomialkernel # set parameters. ds_name = 'MUTAG' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} pkernel = functools.partial(polynomialkernel, d=3, c=1e+8) kernel_options = {'name': 'Treelet', 'sub_kernel': pkernel, 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '/' irrelevant_labels = {'edge_labels': ['label_0']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) def xp_median_preimage_7_4(): """xp 7_4: MUTAG, WeisfeilerLehman, using CONSTANT. """ # set parameters. ds_name = 'MUTAG' # rpg_options = {'k': 5, 'r_max': 10, # 'l': 500, 'alphas': None, 'parallel': True, 'verbose': 2} kernel_options = {'name': 'WeisfeilerLehman', 'height': 1, 'base_kernel': 'subtree', 'parallel': 'imap_unordered', # 'parallel': None, 'n_jobs': multiprocessing.cpu_count(), 'normalize': True, 'verbose': 0} save_results = True dir_save = dir_root + ds_name + '.' + kernel_options['name'] + '/' irrelevant_labels = {'edge_labels': ['label_0']} # edge_required = False # if not os.path.exists(dir_save): os.makedirs(dir_save) file_output = open(dir_save + 'output.txt', 'a') sys.stdout = file_output # print settings. print('parameters:') print('dataset name:', ds_name) print('kernel_options:', kernel_options) print('save_results:', save_results) print('irrelevant_labels:', irrelevant_labels) print() # generate preimages. try: generate_random_preimages_by_class(ds_name, rpg_options, kernel_options, save_results=save_results, save_preimages=True, load_gm='auto', dir_save=dir_save, irrelevant_labels=irrelevant_labels, edge_required=edge_required) except Exception as exp: print('An exception occured when running this experiment:') LOG_FILENAME = dir_save + 'error.txt' logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG) logging.exception('') print(repr(exp)) if __name__ == "__main__": # #### xp 7_2: MUTAG, PathUpToH, using CONSTANT. xp_median_preimage_7_2() # #### xp 7_3: MUTAG, Treelet, using CONSTANT. xp_median_preimage_7_3() # #### xp 7_4: MUTAG, WeisfeilerLehman, using CONSTANT. xp_median_preimage_7_4() # # #### xp 7_1: MUTAG, StructuralSP, using CONSTANT. xp_median_preimage_7_1() # #### xp 8_2: Monoterpenoides, PathUpToH, using CONSTANT. xp_median_preimage_8_2() # #### xp 8_3: Monoterpenoides, Treelet, using CONSTANT. xp_median_preimage_8_3() # #### xp 8_4: Monoterpenoides, WeisfeilerLehman, using CONSTANT. xp_median_preimage_8_4() # #### xp 8_1: Monoterpenoides, StructuralSP, using CONSTANT. xp_median_preimage_8_1() # #### xp 9_2: MAO, PathUpToH, using CONSTANT, symbolic only. xp_median_preimage_9_2() # #### xp 9_3: MAO, Treelet, using CONSTANT, symbolic only. xp_median_preimage_9_3() # #### xp 9_4: MAO, WeisfeilerLehman, using CONSTANT, symbolic only. xp_median_preimage_9_4() # #### xp 9_1: MAO, StructuralSP, using CONSTANT, symbolic only. xp_median_preimage_9_1() #### xp 12_1: PAH, StructuralSP, using NON_SYMBOLIC, unlabeled. xp_median_preimage_12_1() #### xp 12_2: PAH, PathUpToH, using CONSTANT, unlabeled. xp_median_preimage_12_2() #### xp 12_3: PAH, Treelet, using CONSTANT, unlabeled. xp_median_preimage_12_3() #### xp 12_4: PAH, WeisfeilerLehman, using CONSTANT, unlabeled. xp_median_preimage_12_4() #### xp 12_5: PAH, ShortestPath, using NON_SYMBOLIC, unlabeled. xp_median_preimage_12_5() # #### xp 15_1: AIDS, StructuralSP, using CONSTANT, symbolic only. xp_median_preimage_15_1() # #### xp 15_2: AIDS, PathUpToH, using CONSTANT, symbolic only. xp_median_preimage_15_2() # #### xp 15_3: AIDS, Treelet, using CONSTANT, symbolic only. xp_median_preimage_15_3() # #### xp 15_4: AIDS, WeisfeilerLehman, using CONSTANT, symbolic only. xp_median_preimage_15_4() # #### xp 14_1: DD, PathUpToH, using CONSTANT. xp_median_preimage_14_1()