From da5b7310d2fcaee971c3a5b3577b3d6fd291df6a Mon Sep 17 00:00:00 2001 From: linlin Date: Tue, 6 Oct 2020 17:25:56 +0200 Subject: [PATCH] New translations xp_random_preimage.py (Chinese Simplified) --- .../preimage/experiments/xp_random_preimage.py | 1192 ++++++++++++++++++++ 1 file changed, 1192 insertions(+) create mode 100644 lang/zh/gklearn/preimage/experiments/xp_random_preimage.py diff --git a/lang/zh/gklearn/preimage/experiments/xp_random_preimage.py b/lang/zh/gklearn/preimage/experiments/xp_random_preimage.py new file mode 100644 index 0000000..8700ad8 --- /dev/null +++ b/lang/zh/gklearn/preimage/experiments/xp_random_preimage.py @@ -0,0 +1,1192 @@ +#!/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()