diff --git a/.gitignore b/.gitignore index 5559d48..de3945d 100644 --- a/.gitignore +++ b/.gitignore @@ -47,3 +47,12 @@ htmlcov virtualenv .vscode/ + +# gedlibpy +gklearn/gedlib/build/ +gklearn/gedlib/build/__pycache__/ +gklearn/gedlib/collections/ +gklearn/gedlib/Median_Example/ +gklearn/gedlib/build/include/gedlib-master/median/collections/ +gklearn/gedlib/include/ +gklearn/gedlib/libgxlgedlib.so diff --git a/gklearn/ged/env/__init__.py b/gklearn/ged/env/__init__.py new file mode 100644 index 0000000..17aefc7 --- /dev/null +++ b/gklearn/ged/env/__init__.py @@ -0,0 +1 @@ +from gklearn.ged.env.common_types import AlgorithmState \ No newline at end of file diff --git a/gklearn/preimage/common_types.py b/gklearn/ged/env/common_types.py similarity index 100% rename from gklearn/preimage/common_types.py rename to gklearn/ged/env/common_types.py diff --git a/gklearn/ged/median/__init__.py b/gklearn/ged/median/__init__.py new file mode 100644 index 0000000..9a291ae --- /dev/null +++ b/gklearn/ged/median/__init__.py @@ -0,0 +1,2 @@ +from gklearn.ged.median.median_graph_estimator import MedianGraphEstimator +from gklearn.ged.median.utils import constant_node_costs, mge_options_to_string diff --git a/gklearn/preimage/median_graph_estimator.py b/gklearn/ged/median/median_graph_estimator.py similarity index 99% rename from gklearn/preimage/median_graph_estimator.py rename to gklearn/ged/median/median_graph_estimator.py index b70cc61..70651a9 100644 --- a/gklearn/preimage/median_graph_estimator.py +++ b/gklearn/ged/median/median_graph_estimator.py @@ -6,10 +6,9 @@ Created on Mon Mar 16 18:04:55 2020 @author: ljia """ import numpy as np -from gklearn.preimage.common_types import AlgorithmState -from gklearn.preimage import misc -from gklearn.preimage.timer import Timer -from gklearn.utils.utils import graph_isIdentical +from gklearn.ged.env import AlgorithmState +from gklearn.ged.util import misc +from gklearn.utils import Timer import time from tqdm import tqdm import sys @@ -822,5 +821,4 @@ class MedianGraphEstimator(object): def compute_my_cost(g, h, node_map): cost = 0.0 for node in g.nodes: - cost += 0 - \ No newline at end of file + cost += 0 \ No newline at end of file diff --git a/gklearn/preimage/test_median_graph_estimator.py b/gklearn/ged/median/test_median_graph_estimator.py similarity index 81% rename from gklearn/preimage/test_median_graph_estimator.py rename to gklearn/ged/median/test_median_graph_estimator.py index 2a930df..bc4beae 100644 --- a/gklearn/preimage/test_median_graph_estimator.py +++ b/gklearn/ged/median/test_median_graph_estimator.py @@ -8,7 +8,7 @@ Created on Mon Mar 16 17:26:40 2020 def test_median_graph_estimator(): from gklearn.utils.graphfiles import loadDataset - from gklearn.preimage.median_graph_estimator import MedianGraphEstimator + from gklearn.ged.median import MedianGraphEstimator, constant_node_costs from gklearn.gedlib import librariesImport, gedlibpy from gklearn.preimage.utils import get_same_item_indices from gklearn.preimage.ged import convertGraph @@ -31,7 +31,7 @@ def test_median_graph_estimator(): # Load dataset. # dataset = '../../datasets/COIL-DEL/COIL-DEL_A.txt' - dataset = '../../datasets/Letter-high/Letter-high_A.txt' + dataset = '../../../datasets/Letter-high/Letter-high_A.txt' Gn, y_all = loadDataset(dataset) y_idx = get_same_item_indices(y_all) for i, (y, values) in enumerate(y_idx.items()): @@ -75,16 +75,6 @@ def test_median_graph_estimator(): gen_median = ged_env.get_nx_graph(gen_median_id) return set_median, gen_median - - - -def constant_node_costs(edit_cost_name): - if edit_cost_name == 'NON_SYMBOLIC' or edit_cost_name == 'LETTER2' or edit_cost_name == 'LETTER': - return False -# elif edit_cost_name != '': -# # throw ged::Error("Invalid dataset " + dataset + ". Usage: ./median_tests "); -# return False - # return True if __name__ == '__main__': diff --git a/gklearn/ged/median/utils.py b/gklearn/ged/median/utils.py new file mode 100644 index 0000000..741320c --- /dev/null +++ b/gklearn/ged/median/utils.py @@ -0,0 +1,53 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +Created on Wed Apr 1 15:12:31 2020 + +@author: ljia +""" + +def constant_node_costs(edit_cost_name): + if edit_cost_name == 'NON_SYMBOLIC' or edit_cost_name == 'LETTER2' or edit_cost_name == 'LETTER': + return False +# elif edit_cost_name != '': +# # throw ged::Error("Invalid dataset " + dataset + ". Usage: ./median_tests "); +# return False + # return True + + +def mge_options_to_string(options): + opt_str = ' ' + for key, val in options.items(): + if key == 'init_type': + opt_str += '--init-type ' + str(val) + ' ' + elif key == 'random_inits': + opt_str += '--random-inits ' + str(val) + ' ' + elif key == 'randomness': + opt_str += '--randomness ' + str(val) + ' ' + elif key == 'verbose': + opt_str += '--stdout ' + str(val) + ' ' + elif key == 'refine': + opt_str += '--refine ' + ('TRUE' if val else 'FALSE') + ' ' + elif key == 'time_limit': + opt_str += '--time-limit ' + str(val) + ' ' + elif key == 'max_itrs': + opt_str += '--max-itrs ' + str(val) + ' ' + elif key == 'max_itrs_without_update': + opt_str += '--max-itrs-without-update ' + str(val) + ' ' + elif key == 'seed': + opt_str += '--seed ' + str(val) + ' ' + elif key == 'epsilon': + opt_str += '--epsilon ' + str(val) + ' ' + elif key == 'inits_increase_order': + opt_str += '--inits-increase-order ' + str(val) + ' ' + elif key == 'init_type_increase_order': + opt_str += '--init-type-increase-order ' + str(val) + ' ' + elif key == 'max_itrs_increase_order': + opt_str += '--max-itrs-increase-order ' + str(val) + ' ' +# else: +# valid_options = '[--init-type ] [--random_inits ] [--randomness ] [--seed ] [--verbose ] ' +# valid_options += '[--time_limit ] [--max_itrs ] [--epsilon ] ' +# valid_options += '[--inits_increase_order ] [--init_type_increase_order ] [--max_itrs_increase_order ]' +# raise Exception('Invalid option "' + key + '". Options available = "' + valid_options + '"') + + return opt_str \ No newline at end of file diff --git a/gklearn/ged/util/__init__.py b/gklearn/ged/util/__init__.py new file mode 100644 index 0000000..a288557 --- /dev/null +++ b/gklearn/ged/util/__init__.py @@ -0,0 +1 @@ +from gklearn.ged.util.util import compute_geds, ged_options_to_string diff --git a/gklearn/preimage/cpp2python.py b/gklearn/ged/util/cpp2python.py similarity index 100% rename from gklearn/preimage/cpp2python.py rename to gklearn/ged/util/cpp2python.py diff --git a/gklearn/ged/util/cpp_code.cpp b/gklearn/ged/util/cpp_code.cpp new file mode 100644 index 0000000..acbe22a --- /dev/null +++ b/gklearn/ged/util/cpp_code.cpp @@ -0,0 +1,122 @@ + else if (option.first == "random-inits") { + try { + num_random_inits_ = std::stoul(option.second); + desired_num_random_inits_ = num_random_inits_; + } + catch (...) { + throw Error(std::string("Invalid argument \"") + option.second + "\" for option random-inits. Usage: options = \"[--random-inits ]\""); + } + if (num_random_inits_ <= 0) { + throw Error(std::string("Invalid argument \"") + option.second + "\" for option random-inits. Usage: options = \"[--random-inits ]\""); + } + } + else if (option.first == "randomness") { + if (option.second == "PSEUDO") { + use_real_randomness_ = false; + } + else if (option.second == "REAL") { + use_real_randomness_ = true; + } + else { + throw Error(std::string("Invalid argument \"") + option.second + "\" for option randomness. Usage: options = \"[--randomness REAL|PSEUDO] [...]\""); + } + } + else if (option.first == "stdout") { + if (option.second == "0") { + print_to_stdout_ = 0; + } + else if (option.second == "1") { + print_to_stdout_ = 1; + } + else if (option.second == "2") { + print_to_stdout_ = 2; + } + else { + throw Error(std::string("Invalid argument \"") + option.second + "\" for option stdout. Usage: options = \"[--stdout 0|1|2] [...]\""); + } + } + else if (option.first == "refine") { + if (option.second == "TRUE") { + refine_ = true; + } + else if (option.second == "FALSE") { + refine_ = false; + } + else { + throw Error(std::string("Invalid argument \"") + option.second + "\" for option refine. Usage: options = \"[--refine TRUE|FALSE] [...]\""); + } + } + else if (option.first == "time-limit") { + try { + time_limit_in_sec_ = std::stod(option.second); + } + catch (...) { + throw Error(std::string("Invalid argument \"") + option.second + "\" for option time-limit. Usage: options = \"[--time-limit ] [...]"); + } + } + else if (option.first == "max-itrs") { + try { + max_itrs_ = std::stoi(option.second); + } + catch (...) { + throw Error(std::string("Invalid argument \"") + option.second + "\" for option max-itrs. Usage: options = \"[--max-itrs ] [...]"); + } + } + else if (option.first == "max-itrs-without-update") { + try { + max_itrs_without_update_ = std::stoi(option.second); + } + catch (...) { + throw Error(std::string("Invalid argument \"") + option.second + "\" for option max-itrs-without-update. Usage: options = \"[--max-itrs-without-update ] [...]"); + } + } + else if (option.first == "seed") { + try { + seed_ = std::stoul(option.second); + } + catch (...) { + throw Error(std::string("Invalid argument \"") + option.second + "\" for option seed. Usage: options = \"[--seed ] [...]"); + } + } + else if (option.first == "epsilon") { + try { + epsilon_ = std::stod(option.second); + } + catch (...) { + throw Error(std::string("Invalid argument \"") + option.second + "\" for option epsilon. Usage: options = \"[--epsilon ] [...]"); + } + if (epsilon_ <= 0) { + throw Error(std::string("Invalid argument \"") + option.second + "\" for option epsilon. Usage: options = \"[--epsilon ] [...]"); + } + } + else if (option.first == "inits-increase-order") { + try { + num_inits_increase_order_ = std::stoul(option.second); + } + catch (...) { + throw Error(std::string("Invalid argument \"") + option.second + "\" for option inits-increase-order. Usage: options = \"[--inits-increase-order ]\""); + } + if (num_inits_increase_order_ <= 0) { + throw Error(std::string("Invalid argument \"") + option.second + "\" for option inits-increase-order. Usage: options = \"[--inits-increase-order ]\""); + } + } + else if (option.first == "init-type-increase-order") { + init_type_increase_order_ = option.second; + if (option.second != "CLUSTERS" and option.second != "K-MEANS++") { + throw ged::Error(std::string("Invalid argument ") + option.second + " for option init-type-increase-order. Usage: options = \"[--init-type-increase-order CLUSTERS|K-MEANS++] [...]\""); + } + } + else if (option.first == "max-itrs-increase-order") { + try { + max_itrs_increase_order_ = std::stoi(option.second); + } + catch (...) { + throw Error(std::string("Invalid argument \"") + option.second + "\" for option max-itrs-increase-order. Usage: options = \"[--max-itrs-increase-order ] [...]"); + } + } + else { + std::string valid_options("[--init-type ] [--random-inits ] [--randomness ] [--seed ] [--stdout ] "); + valid_options += "[--time-limit ] [--max-itrs ] [--epsilon ] "; + valid_options += "[--inits-increase-order ] [--init-type-increase-order ] [--max-itrs-increase-order ]"; + throw Error(std::string("Invalid option \"") + option.first + "\". Usage: options = \"" + valid_options + "\""); + } diff --git a/gklearn/preimage/misc.py b/gklearn/ged/util/misc.py similarity index 100% rename from gklearn/preimage/misc.py rename to gklearn/ged/util/misc.py diff --git a/gklearn/ged/util/util.py b/gklearn/ged/util/util.py new file mode 100644 index 0000000..b58e945 --- /dev/null +++ b/gklearn/ged/util/util.py @@ -0,0 +1,344 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +Created on Tue Mar 31 17:06:22 2020 + +@author: ljia +""" +import numpy as np +from itertools import combinations +import multiprocessing +from multiprocessing import Pool +from functools import partial +import sys +from tqdm import tqdm +import networkx as nx +from gklearn.gedlib import librariesImport, gedlibpy + + +def compute_ged(g1, g2, options): + ged_env = gedlibpy.GEDEnv() + ged_env.set_edit_cost(options['edit_cost'], edit_cost_constant=options['edit_cost_constants']) + ged_env.add_nx_graph(g1, '') + ged_env.add_nx_graph(g2, '') + listID = ged_env.get_all_graph_ids() + ged_env.init() + ged_env.set_method(options['method'], ged_options_to_string(options)) + ged_env.init_method() + + g = listID[0] + h = listID[1] + ged_env.run_method(g, h) + pi_forward = ged_env.get_forward_map(g, h) + pi_backward = ged_env.get_backward_map(g, h) + upper = ged_env.get_upper_bound(g, h) + dis = upper + + # make the map label correct (label remove map as np.inf) + nodes1 = [n for n in g1.nodes()] + nodes2 = [n for n in g2.nodes()] + nb1 = nx.number_of_nodes(g1) + nb2 = nx.number_of_nodes(g2) + pi_forward = [nodes2[pi] if pi < nb2 else np.inf for pi in pi_forward] + pi_backward = [nodes1[pi] if pi < nb1 else np.inf for pi in pi_backward] +# print(pi_forward) + + return dis, pi_forward, pi_backward + + +def compute_geds(graphs, options={}, parallel=False): + # initialize ged env. + ged_env = gedlibpy.GEDEnv() + ged_env.set_edit_cost(options['edit_cost'], edit_cost_constant=options['edit_cost_constants']) + for g in graphs: + ged_env.add_nx_graph(g, '') + listID = ged_env.get_all_graph_ids() + ged_env.init() + ged_env.set_method(options['method'], ged_options_to_string(options)) + ged_env.init_method() + + # compute ged. + ged_mat = np.zeros((len(graphs), len(graphs))) + if parallel: + len_itr = int(len(graphs) * (len(graphs) - 1) / 2) + ged_vec = [0 for i in range(len_itr)] + n_edit_operations = [0 for i in range(len_itr)] + itr = combinations(range(0, len(graphs)), 2) + n_jobs = multiprocessing.cpu_count() + if len_itr < 100 * n_jobs: + chunksize = int(len_itr / n_jobs) + 1 + else: + chunksize = 100 + def init_worker(graphs_toshare, ged_env_toshare, listID_toshare): + global G_graphs, G_ged_env, G_listID + G_graphs = graphs_toshare + G_ged_env = ged_env_toshare + G_listID = listID_toshare + do_partial = partial(_wrapper_compute_ged_parallel, options) + pool = Pool(processes=n_jobs, initializer=init_worker, initargs=(graphs, ged_env, listID)) + iterator = tqdm(pool.imap_unordered(do_partial, itr, chunksize), + desc='computing GEDs', file=sys.stdout) +# iterator = pool.imap_unordered(do_partial, itr, chunksize) + for i, j, dis, n_eo_tmp in iterator: + idx_itr = int(len(graphs) * i + j - (i + 1) * (i + 2) / 2) + ged_vec[idx_itr] = dis + ged_mat[i][j] = dis + ged_mat[j][i] = dis + n_edit_operations[idx_itr] = n_eo_tmp +# print('\n-------------------------------------------') +# print(i, j, idx_itr, dis) + pool.close() + pool.join() + + else: + ged_vec = [] + n_edit_operations = [] + for i in tqdm(range(len(graphs)), desc='computing GEDs', file=sys.stdout): +# for i in range(len(graphs)): + for j in range(i + 1, len(graphs)): + dis, pi_forward, pi_backward = _compute_ged(ged_env, listID[i], listID[j], graphs[i], graphs[j]) + ged_vec.append(dis) + ged_mat[i][j] = dis + ged_mat[j][i] = dis + n_eo_tmp = get_nb_edit_operations(graphs[i], graphs[j], pi_forward, pi_backward, edit_cost=options['edit_cost']) + n_edit_operations.append(n_eo_tmp) + + return ged_vec, ged_mat, n_edit_operations + + +def _wrapper_compute_ged_parallel(options, itr): + i = itr[0] + j = itr[1] + dis, n_eo_tmp = _compute_ged_parallel(G_ged_env, G_listID[i], G_listID[j], G_graphs[i], G_graphs[j], options) + return i, j, dis, n_eo_tmp + + +def _compute_ged_parallel(env, gid1, gid2, g1, g2, options): + dis, pi_forward, pi_backward = _compute_ged(env, gid1, gid2, g1, g2) + n_eo_tmp = get_nb_edit_operations(g1, g2, pi_forward, pi_backward, edit_cost=options['edit_cost']) # [0,0,0,0,0,0] + return dis, n_eo_tmp + + +def _compute_ged(env, gid1, gid2, g1, g2): + env.run_method(gid1, gid2) + pi_forward = env.get_forward_map(gid1, gid2) + pi_backward = env.get_backward_map(gid1, gid2) + upper = env.get_upper_bound(gid1, gid2) + dis = upper + + # make the map label correct (label remove map as np.inf) + nodes1 = [n for n in g1.nodes()] + nodes2 = [n for n in g2.nodes()] + nb1 = nx.number_of_nodes(g1) + nb2 = nx.number_of_nodes(g2) + pi_forward = [nodes2[pi] if pi < nb2 else np.inf for pi in pi_forward] + pi_backward = [nodes1[pi] if pi < nb1 else np.inf for pi in pi_backward] + + return dis, pi_forward, pi_backward + + +def get_nb_edit_operations(g1, g2, forward_map, backward_map, edit_cost=None): + if edit_cost == 'LETTER' or edit_cost == 'LETTER2': + return get_nb_edit_operations_letter(g1, g2, forward_map, backward_map) + elif edit_cost == 'NON_SYMBOLIC': + return get_nb_edit_operations_nonsymbolic(g1, g2, forward_map, backward_map) + else: + return get_nb_edit_operations_symbolic(g1, g2, forward_map, backward_map) + + +def get_nb_edit_operations_symbolic(g1, g2, forward_map, backward_map): + """Compute the number of each edit operations. + """ + n_vi = 0 + n_vr = 0 + n_vs = 0 + n_ei = 0 + n_er = 0 + n_es = 0 + + nodes1 = [n for n in g1.nodes()] + for i, map_i in enumerate(forward_map): + if map_i == np.inf: + n_vr += 1 + elif g1.node[nodes1[i]]['atom'] != g2.node[map_i]['atom']: + n_vs += 1 + for map_i in backward_map: + if map_i == np.inf: + n_vi += 1 + +# idx_nodes1 = range(0, len(node1)) + + edges1 = [e for e in g1.edges()] + nb_edges2_cnted = 0 + for n1, n2 in edges1: + idx1 = nodes1.index(n1) + idx2 = nodes1.index(n2) + # one of the nodes is removed, thus the edge is removed. + if forward_map[idx1] == np.inf or forward_map[idx2] == np.inf: + n_er += 1 + # corresponding edge is in g2. + elif (forward_map[idx1], forward_map[idx2]) in g2.edges(): + nb_edges2_cnted += 1 + # edge labels are different. + if g2.edges[((forward_map[idx1], forward_map[idx2]))]['bond_type'] \ + != g1.edges[(n1, n2)]['bond_type']: + n_es += 1 + elif (forward_map[idx2], forward_map[idx1]) in g2.edges(): + nb_edges2_cnted += 1 + # edge labels are different. + if g2.edges[((forward_map[idx2], forward_map[idx1]))]['bond_type'] \ + != g1.edges[(n1, n2)]['bond_type']: + n_es += 1 + # corresponding nodes are in g2, however the edge is removed. + else: + n_er += 1 + n_ei = nx.number_of_edges(g2) - nb_edges2_cnted + + return n_vi, n_vr, n_vs, n_ei, n_er, n_es + + +def get_nb_edit_operations_letter(g1, g2, forward_map, backward_map): + """Compute the number of each edit operations. + """ + n_vi = 0 + n_vr = 0 + n_vs = 0 + sod_vs = 0 + n_ei = 0 + n_er = 0 + + nodes1 = [n for n in g1.nodes()] + for i, map_i in enumerate(forward_map): + if map_i == np.inf: + n_vr += 1 + else: + n_vs += 1 + diff_x = float(g1.nodes[nodes1[i]]['x']) - float(g2.nodes[map_i]['x']) + diff_y = float(g1.nodes[nodes1[i]]['y']) - float(g2.nodes[map_i]['y']) + sod_vs += np.sqrt(np.square(diff_x) + np.square(diff_y)) + for map_i in backward_map: + if map_i == np.inf: + n_vi += 1 + +# idx_nodes1 = range(0, len(node1)) + + edges1 = [e for e in g1.edges()] + nb_edges2_cnted = 0 + for n1, n2 in edges1: + idx1 = nodes1.index(n1) + idx2 = nodes1.index(n2) + # one of the nodes is removed, thus the edge is removed. + if forward_map[idx1] == np.inf or forward_map[idx2] == np.inf: + n_er += 1 + # corresponding edge is in g2. Edge label is not considered. + elif (forward_map[idx1], forward_map[idx2]) in g2.edges() or \ + (forward_map[idx2], forward_map[idx1]) in g2.edges(): + nb_edges2_cnted += 1 + # corresponding nodes are in g2, however the edge is removed. + else: + n_er += 1 + n_ei = nx.number_of_edges(g2) - nb_edges2_cnted + + return n_vi, n_vr, n_vs, sod_vs, n_ei, n_er + + +def get_nb_edit_operations_nonsymbolic(g1, g2, forward_map, backward_map): + """Compute the number of each edit operations. + """ + n_vi = 0 + n_vr = 0 + n_vs = 0 + sod_vs = 0 + n_ei = 0 + n_er = 0 + n_es = 0 + sod_es = 0 + + nodes1 = [n for n in g1.nodes()] + for i, map_i in enumerate(forward_map): + if map_i == np.inf: + n_vr += 1 + else: + n_vs += 1 + sum_squares = 0 + for a_name in g1.graph['node_attrs']: + diff = float(g1.nodes[nodes1[i]][a_name]) - float(g2.nodes[map_i][a_name]) + sum_squares += np.square(diff) + sod_vs += np.sqrt(sum_squares) + for map_i in backward_map: + if map_i == np.inf: + n_vi += 1 + +# idx_nodes1 = range(0, len(node1)) + + edges1 = [e for e in g1.edges()] + for n1, n2 in edges1: + idx1 = nodes1.index(n1) + idx2 = nodes1.index(n2) + n1_g2 = forward_map[idx1] + n2_g2 = forward_map[idx2] + # one of the nodes is removed, thus the edge is removed. + if n1_g2 == np.inf or n2_g2 == np.inf: + n_er += 1 + # corresponding edge is in g2. + elif (n1_g2, n2_g2) in g2.edges(): + n_es += 1 + sum_squares = 0 + for a_name in g1.graph['edge_attrs']: + diff = float(g1.edges[n1, n2][a_name]) - float(g2.nodes[n1_g2, n2_g2][a_name]) + sum_squares += np.square(diff) + sod_es += np.sqrt(sum_squares) + elif (n2_g2, n1_g2) in g2.edges(): + n_es += 1 + sum_squares = 0 + for a_name in g1.graph['edge_attrs']: + diff = float(g1.edges[n2, n1][a_name]) - float(g2.nodes[n2_g2, n1_g2][a_name]) + sum_squares += np.square(diff) + sod_es += np.sqrt(sum_squares) + # corresponding nodes are in g2, however the edge is removed. + else: + n_er += 1 + n_ei = nx.number_of_edges(g2) - n_es + + return n_vi, n_vr, sod_vs, n_ei, n_er, sod_es + + +def ged_options_to_string(options): + opt_str = ' ' + for key, val in options.items(): + if key == 'initialization_method': + opt_str += '--initial_solutions ' + str(val) + ' ' + elif key == 'initialization_options': + opt_str += '--initialization-options ' + str(val) + ' ' + elif key == 'lower_bound_method': + opt_str += '--lower-bound-method ' + str(val) + ' ' + elif key == 'random_substitution_ratio': + opt_str += '--random-substitution-ratio ' + str(val) + ' ' + elif key == 'initial_solutions': + opt_str += '--initial-solutions ' + str(val) + ' ' + elif key == 'ratio_runs_from_initial_solutions': + opt_str += '--ratio-runs-from-initial-solutions ' + str(val) + ' ' + elif key == 'threads': + opt_str += '--threads ' + str(val) + ' ' + elif key == 'num_randpost_loops': + opt_str += '--num-randpost-loops ' + str(val) + ' ' + elif key == 'max_randpost_retrials': + opt_str += '--maxrandpost-retrials ' + str(val) + ' ' + elif key == 'randpost_penalty': + opt_str += '--randpost-penalty ' + str(val) + ' ' + elif key == 'randpost_decay': + opt_str += '--randpost-decay ' + str(val) + ' ' + elif key == 'log': + opt_str += '--log ' + str(val) + ' ' + elif key == 'randomness': + opt_str += '--randomness ' + str(val) + ' ' + +# if not isinstance(val, list): +# opt_str += '--' + key.replace('_', '-') + ' ' +# if val == False: +# val_str = 'FALSE' +# else: +# val_str = str(val) +# opt_str += val_str + ' ' + + return opt_str \ No newline at end of file diff --git a/gklearn/gedlib/README.rst b/gklearn/gedlib/README.rst new file mode 100644 index 0000000..7a44bbf --- /dev/null +++ b/gklearn/gedlib/README.rst @@ -0,0 +1,97 @@ +GEDLIBPY +==================================== + +Please Read https://dbblumenthal.github.io/gedlib/ before using Python code. +You can also find this module documentation in documentation/build/html folder. + +Make sure you have numpy installed (and Cython if you have to recompile the library). You can use pip for this. + + +Running the script +------------------- + +After donwloading the entire folder, you can run test.py to ensure the library works. + +For your code, you have to make two imports:: + + import librariesImport + import gedlibpy + +You can call each function in the library with this. You can't move any folder or files on the library, please make sure that the architecture remains the same. + +This library is compiled for Python3 only. If you want to use it with Python 2, you have to recompile it with setup.py. You have to use this command on your favorite shell:: + + python setup.py build_ext --inplace + +After this step, you can use the same lines as Python3 for import, it will be ok. Check the documentation inside the documentation/build/html folder before using function. You can also copy the tests examples for basic use. + + +A problem with the library ? +------------------------------- + +If the library isn't found, you can recompile the Python library because your Linux is different to mine. Please delete gedlibpy.so, gedlibpy.cpp and build folder. Then use this command on a linux shell :: + + python3 setup.py build_ext --inplace + +You can make it with Python 2 but make sure you use the same version with your code and the compilation. + +If it's doesn't work, maybe the version of GedLib or another library can be a problem. If it is, you can re-install GedLib for your computer. You can download it on this git : https://dbblumenthal.github.io/gedlib/ + +You have to install Gedlib with the Python installer after that. +Just call:: + + python3 install.py + +Make the links like indicate on the documentation. Use the same architecture like this library, but just change the .so and folders with your installation. You can recompile the Python library with setup command, after that. + +If you use Mac OS, you have to follow all this part, and install the external libraries with this command:: + + install_name_tool -change // + +For an example, you have to write these lines:: + + install_name_tool -change libdoublefann.2.dylib lib/fann/libdoublefann.2.dylib gedlibpy.so + install_name_tool -change libsvm.so lib/libsvm.3.22/libsvm.so gedlibpy.so + install_name_tool -change libnomad.so lib/nomad/libnomad.so gedlibpy.so + install_name_tool -change libsgtelib.so lib/nomad/libsgtelib.so gedlibpy.so + +The name of the library gedlibpy can be different if you use Python 3. + +If your problem is still here, you can contact me on : natacha.lambert@unicaen.fr + +How to use this library +------------------------- + +This library allow to compute edit distance between two graphs. You have to follow these steps to use it : + +- Add your graphs (GXL files, NX Structures or your structure, make sure that the internal type is the same) +- Choose your cost function +- Init your environnment (After that, the cost function and your graphs can't be modified) +- Choose your method computation +- Run the computation with the IDs of the two graphs. You can have the ID when you add the graph or with some functions +- Find the result with differents functions (NodeMap, edit distance, etc) + +Here is an example of code with GXL graphs:: + + gedlibpy.load_GXL_graphs('include/gedlib-master/data/datasets/Mutagenicity/data/', 'collections/MUTA_10.xml') + listID = gedlibpy.get_all_graph_ids() + gedlibpy.set_edit_cost("CHEM_1") + gedlibpy.init() + gedlibpy.set_method("IPFP", "") + gedlibpy.init_method() + g = listID[0] + h = listID[1] + + gedlibpy.run_method(g,h) + + print("Node Map : ", gedlibpy.get_node_map(g,h)) + print ("Upper Bound = " + str(gedlibpy.get_upper_bound(g,h)) + ", Lower Bound = " + str(gedlibpy.get_lower_bound(g,h)) + ", Runtime = " + str(gedlibpy.get_runtime(g,h))) + + +Please read the documentation for more examples and functions. + + +An advice if you don't code in a shell +--------------------------------------- + +Python library don't indicate each C++ error. If you have a restart causing by an error in your code, please use on a linux shell for having C++ errors. diff --git a/gklearn/gedlib/__init__.py b/gklearn/gedlib/__init__.py new file mode 100644 index 0000000..1289a2c --- /dev/null +++ b/gklearn/gedlib/__init__.py @@ -0,0 +1,10 @@ +# -*-coding:utf-8 -*- +""" +gedlib + +""" + +# info +__version__ = "0.1" +__author__ = "Linlin Jia" +__date__ = "March 2020" diff --git a/gklearn/gedlib/documentation/Makefile b/gklearn/gedlib/documentation/Makefile new file mode 100644 index 0000000..d42ba39 --- /dev/null +++ b/gklearn/gedlib/documentation/Makefile @@ -0,0 +1,20 @@ +# Minimal makefile for Sphinx documentation +# + +# You can set these variables from the command line. +SPHINXOPTS = +SPHINXBUILD = sphinx-build +SPHINXPROJ = Cython_GedLib +SOURCEDIR = source +BUILDDIR = build + +# Put it first so that "make" without argument is like "make help". +help: + @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) + +.PHONY: help Makefile + +# Catch-all target: route all unknown targets to Sphinx using the new +# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). +%: Makefile + @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) \ No newline at end of file diff --git a/gklearn/gedlib/documentation/gedlibpy.pdf b/gklearn/gedlib/documentation/gedlibpy.pdf new file mode 100644 index 0000000..5a88fcd Binary files /dev/null and b/gklearn/gedlib/documentation/gedlibpy.pdf differ diff --git a/gklearn/gedlib/documentation/make.bat b/gklearn/gedlib/documentation/make.bat new file mode 100644 index 0000000..16f31bb --- /dev/null +++ b/gklearn/gedlib/documentation/make.bat @@ -0,0 +1,36 @@ +@ECHO OFF + +pushd %~dp0 + +REM Command file for Sphinx documentation + +if "%SPHINXBUILD%" == "" ( + set SPHINXBUILD=sphinx-build +) +set SOURCEDIR=source +set BUILDDIR=build +set SPHINXPROJ=Cython_GedLib + +if "%1" == "" goto help + +%SPHINXBUILD% >NUL 2>NUL +if errorlevel 9009 ( + echo. + echo.The 'sphinx-build' command was not found. Make sure you have Sphinx + echo.installed, then set the SPHINXBUILD environment variable to point + echo.to the full path of the 'sphinx-build' executable. Alternatively you + echo.may add the Sphinx directory to PATH. + echo. + echo.If you don't have Sphinx installed, grab it from + echo.http://sphinx-doc.org/ + exit /b 1 +) + +%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% +goto end + +:help +%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% + +:end +popd diff --git a/gklearn/gedlib/documentation/source/conf.py b/gklearn/gedlib/documentation/source/conf.py new file mode 100644 index 0000000..d1836bc --- /dev/null +++ b/gklearn/gedlib/documentation/source/conf.py @@ -0,0 +1,199 @@ +# -*- coding: utf-8 -*- +# +# Python_GedLib documentation build configuration file, created by +# sphinx-quickstart on Thu Jun 13 16:10:06 2019. +# +# This file is execfile()d with the current directory set to its +# containing dir. +# +# Note that not all possible configuration values are present in this +# autogenerated file. +# +# All configuration values have a default; values that are commented out +# serve to show the default. + +# If extensions (or modules to document with autodoc) are in another directory, +# add these directories to sys.path here. If the directory is relative to the +# documentation root, use os.path.abspath to make it absolute, like shown here. +# +import os +import sys +#sys.path.insert(0, os.path.abspath('.')) +sys.path.insert(0, os.path.abspath('../../')) +sys.path.append("../../lib/fann") +#,"lib/gedlib", "lib/libsvm.3.22","lib/nomad" + + +# -- General configuration ------------------------------------------------ + +# If your documentation needs a minimal Sphinx version, state it here. +# +# needs_sphinx = '1.0' + +# Add any Sphinx extension module names here, as strings. They can be +# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom +# ones. +extensions = ['sphinx.ext.autodoc', + 'sphinx.ext.intersphinx', + 'sphinx.ext.coverage', + 'sphinx.ext.mathjax', + 'sphinx.ext.githubpages'] + +# Add any paths that contain templates here, relative to this directory. +templates_path = ['_templates'] + +# The suffix(es) of source filenames. +# You can specify multiple suffix as a list of string: +# +# source_suffix = ['.rst', '.md'] +source_suffix = '.rst' + +# The master toctree document. +master_doc = 'index' + +# General information about the project. +project = u'GeDLiBPy' +copyright = u'2019, Natacha Lambert' +author = u'Natacha Lambert' + +# The version info for the project you're documenting, acts as replacement for +# |version| and |release|, also used in various other places throughout the +# built documents. +# +# The short X.Y version. +version = u'1.0' +# The full version, including alpha/beta/rc tags. +release = u'1.0' + +# The language for content autogenerated by Sphinx. Refer to documentation +# for a list of supported languages. +# +# This is also used if you do content translation via gettext catalogs. +# Usually you set "language" from the command line for these cases. +language = None + +# List of patterns, relative to source directory, that match files and +# directories to ignore when looking for source files. +# This patterns also effect to html_static_path and html_extra_path +exclude_patterns = [] + +# The name of the Pygments (syntax highlighting) style to use. +pygments_style = 'sphinx' + +# If true, `todo` and `todoList` produce output, else they produce nothing. +todo_include_todos = False + + +# -- Options for HTML output ---------------------------------------------- + +# The theme to use for HTML and HTML Help pages. See the documentation for +# a list of builtin themes. +# +html_theme = 'alabaster' + +# Theme options are theme-specific and customize the look and feel of a theme +# further. For a list of options available for each theme, see the +# documentation. +# +# html_theme_options = {} + +# Add any paths that contain custom static files (such as style sheets) here, +# relative to this directory. They are copied after the builtin static files, +# so a file named "default.css" will overwrite the builtin "default.css". +html_static_path = ['_static'] + +# Custom sidebar templates, must be a dictionary that maps document names +# to template names. +# +# This is required for the alabaster theme +# refs: http://alabaster.readthedocs.io/en/latest/installation.html#sidebars +html_sidebars = { + '**': [ + 'relations.html', # needs 'show_related': True theme option to display + 'searchbox.html', + ] +} + + +# -- Options for HTMLHelp output ------------------------------------------ + +# Output file base name for HTML help builder. +htmlhelp_basename = 'gedlibpydoc' + + +# -- Options for LaTeX output --------------------------------------------- + +latex_elements = { + # The paper size ('letterpaper' or 'a4paper'). + # + # 'papersize': 'letterpaper', + + # The font size ('10pt', '11pt' or '12pt'). + # + # 'pointsize': '10pt', + + # Additional stuff for the LaTeX preamble. + # + # 'preamble': '', + + # Latex figure (float) alignment + # + # 'figure_align': 'htbp', +} + +# Grouping the document tree into LaTeX files. List of tuples +# (source start file, target name, title, +# author, documentclass [howto, manual, or own class]). +latex_documents = [ + (master_doc, 'gedlibpy.tex', u'gedlibpy Documentation', + u'Natacha Lambert', 'manual'), +] + + +# -- Options for manual page output --------------------------------------- + +# One entry per manual page. List of tuples +# (source start file, name, description, authors, manual section). +man_pages = [ + (master_doc, 'gedlibpy', u'gedlibpy Documentation', + [author], 1) +] + + +# -- Options for Texinfo output ------------------------------------------- + +# Grouping the document tree into Texinfo files. List of tuples +# (source start file, target name, title, author, +# dir menu entry, description, category) +texinfo_documents = [ + (master_doc, 'gedlibpy', u'gedlibpy Documentation', + author, 'gedlibpy', 'One line description of project.', + 'Miscellaneous'), +] + + + +# -- Options for Epub output ---------------------------------------------- + +# Bibliographic Dublin Core info. +epub_title = project +epub_author = author +epub_publisher = author +epub_copyright = copyright + +# The unique identifier of the text. This can be a ISBN number +# or the project homepage. +# +# epub_identifier = '' + +# A unique identification for the text. +# +# epub_uid = '' + +# A list of files that should not be packed into the epub file. +epub_exclude_files = ['search.html'] + + + +# Example configuration for intersphinx: refer to the Python standard library. +intersphinx_mapping = {'https://docs.python.org/': None} diff --git a/gklearn/gedlib/documentation/source/doc.rst b/gklearn/gedlib/documentation/source/doc.rst new file mode 100644 index 0000000..07ec991 --- /dev/null +++ b/gklearn/gedlib/documentation/source/doc.rst @@ -0,0 +1,2 @@ +.. automodule:: gedlibpy + :members: diff --git a/gklearn/gedlib/documentation/source/editcost.rst b/gklearn/gedlib/documentation/source/editcost.rst new file mode 100644 index 0000000..ea3d36b --- /dev/null +++ b/gklearn/gedlib/documentation/source/editcost.rst @@ -0,0 +1,42 @@ +How to add your own editCost class +========================================= + +When you choose your cost function, you can decide some parameters to personalize the function. But if you have some graphs which its type doesn't correpond to the choices, you can create your edit cost function. + +For this, you have to write it in C++. + +C++ side +------------- + +You class must inherit to EditCost class, which is an asbtract class. You can find it here : include/gedlib-master/src/edit_costs + +You can inspire you to the others to understand how to use it. You have to override these functions : + +- virtual double node_ins_cost_fun(const UserNodeLabel & node_label) const final; +- virtual double node_del_cost_fun(const UserNodeLabel & node_label) const final; +- virtual double node_rel_cost_fun(const UserNodeLabel & node_label_1, const UserNodeLabel & node_label_2) const final; +- virtual double edge_ins_cost_fun(const UserEdgeLabel & edge_label) const final; +- virtual double edge_del_cost_fun(const UserEdgeLabel & edge_label) const final; +- virtual double edge_rel_cost_fun(const UserEdgeLabel & edge_label_1, const UserEdgeLabel & edge_label_2) const final; + +You can add some attributes for parameters use or more functions, but these are unavoidable. + +When your class is ready, please go to the C++ Bind here : src/GedLibBind.cpp . The function is : + + void setPersonalEditCost(std::vector editCostConstants){env.set_edit_costs(Your EditCost Class(editCostConstants));} + +You have just to initialize your class. Parameters aren't mandatory, empty by default. If your class doesn't have one, you can skip this. After that, you have to recompile the project. + +Python side +---------------- + +For this, use setup.py with this command in a linux shell:: + + python3 setup.py build_ext --inplace + +You can also make it in Python 2. + +Now you can use your edit cost function with the Python function set_personal_edit_cost(edit_cost_constant). + +If you want more informations on C++, you can check the documentation of the original library here : https://github.com/dbblumenthal/gedlib + diff --git a/gklearn/gedlib/documentation/source/examples.rst b/gklearn/gedlib/documentation/source/examples.rst new file mode 100644 index 0000000..c3496b9 --- /dev/null +++ b/gklearn/gedlib/documentation/source/examples.rst @@ -0,0 +1,165 @@ +Examples +============== + +Before using each example, please make sure to put these lines on the beginnig of your code : + +.. code-block:: python + + import librariesImport + import gedlibpy + +Use your path to access it, without changing the library architecture. After that, you are ready to use the library. + +When you want to make new computation, please use this function : + +.. code-block:: python + + gedlibpy.restart_env() + +All the graphs and results will be delete so make sure you don't need it. + +Classique case with GXL graphs +------------------------------------ +.. code-block:: python + + gedlibpy.load_GXL_graphs('include/gedlib-master/data/datasets/Mutagenicity/data/', 'collections/MUTA_10.xml') + listID = gedlibpy.get_all_graph_ids() + gedlibpy.set_edit_cost("CHEM_1") + + gedlibpy.init() + + gedlibpy.set_method("IPFP", "") + gedlibpy.init_method() + + g = listID[0] + h = listID[1] + + gedlibpy.run_method(g,h) + + print("Node Map : ", gedlibpy.get_node_map(g,h)) + print ("Upper Bound = " + str(gedlibpy.get_upper_bound(g,h)) + ", Lower Bound = " + str(gedlibpy.get_lower_bound(g,h)) + ", Runtime = " + str(gedlibpy.get_runtime(g,h))) + + +You can also use this function : + +.. code-block:: python + + compute_edit_distance_on_GXl_graphs(path_folder, path_XML, edit_cost, method, options="", init_option = "EAGER_WITHOUT_SHUFFLED_COPIES") + +This function compute all edit distance between all graphs, even itself. You can see the result with some functions and graphs IDs. Please see the documentation of the function for more informations. + +Classique case with NX graphs +------------------------------------ +.. code-block:: python + + for graph in dataset : + gedlibpy.add_nx_graph(graph, classe) + listID = gedlibpy.get_all_graph_ids() + gedlibpy.set_edit_cost("CHEM_1") + + gedlibpy.init() + + gedlibpy.set_method("IPFP", "") + gedlibpy.init_method() + + g = listID[0] + h = listID[1] + + gedlibpy.run_method(g,h) + + print("Node Map : ", gedlibpy.get_node_map(g,h)) + print ("Upper Bound = " + str(gedlibpy.get_upper_bound(g,h)) + ", Lower Bound = " + str(gedlibpy.get_lower_bound(g,h)) + ", Runtime = " + str(gedlibpy.get_runtime(g,h))) + +You can also use this function : + +.. code-block:: python + + compute_edit_distance_on_nx_graphs(dataset, classes, edit_cost, method, options, init_option = "EAGER_WITHOUT_SHUFFLED_COPIES") + +This function compute all edit distance between all graphs, even itself. You can see the result in the return and with some functions and graphs IDs. Please see the documentation of the function for more informations. + +Or this function : + +.. code-block:: python + + compute_ged_on_two_graphs(g1,g2, edit_cost, method, options, init_option = "EAGER_WITHOUT_SHUFFLED_COPIES") + +This function allow to compute the edit distance just for two graphs. Please see the documentation of the function for more informations. + +Add a graph from scratch +------------------------------------ +.. code-block:: python + + currentID = gedlibpy.add_graph() + gedlibpy.add_node(currentID, "_1", {"chem" : "C"}) + gedlibpy.add_node(currentID, "_2", {"chem" : "O"}) + gedlibpy.add_edge(currentID,"_1", "_2", {"valence": "1"} ) + +Please make sure as the type are the same (string for Ids and a dictionnary for labels). If you want a symmetrical graph, you can use this function to ensure the symmetry : + +.. code-block:: python + + add_symmetrical_edge(graph_id, tail, head, edge_label) + +If you have a Nx structure, you can use directly this function : + +.. code-block:: python + + add_nx_graph(g, classe, ignore_duplicates=True) + +Even if you have another structure, you can use this function : + +.. code-block:: python + + add_random_graph(name, classe, list_of_nodes, list_of_edges, ignore_duplicates=True) + +Please read the documentation before using and respect the types. + +Median computation +------------------------------------ + +An example is available in the Median_Example folder. It contains the necessary to compute a median graph. You can launch xp-letter-gbr.py to compute median graph on all letters in the dataset, or median.py for le letter Z. + +To summarize the use, you can follow this example : + +.. code-block:: python + + import pygraph #Available with the median example + from median import draw_Letter_graph, compute_median, compute_median_set + + gedlibpy.load_GXL_graphs('../include/gedlib-master/data/datasets/Letter/HIGH/', '../include/gedlib-master/data/collections/Letter_Z.xml') + gedlibpy.set_edit_cost("LETTER") + gedlibpy.init() + gedlibpy.set_method("IPFP", "") + gedlibpy.init_method() + listID = gedlibpy.get_all_graph_ids() + + dataset,my_y = pygraph.utils.graphfiles.loadDataset("../include/gedlib-master/data/datasets/Letter/HIGH/Letter_Z.cxl") + median, sod, sods_path,set_median = compute_median(gedlibpy,listID,dataset,verbose=True) + draw_Letter_graph(median) + +Please use the function in the median.py code to simplify your use. You can adapt this example to your case. Also, some function in the PythonGedLib module can make the work easier. Ask Benoît Gauzere if you want more information. + +Hungarian algorithm +------------------------------------ + + +LSAPE +~~~~~~ + +.. code-block:: python + + result = gedlibpy.hungarian_LSAPE(matrixCost) + print("Rho = ", result[0], " Varrho = ", result[1], " u = ", result[2], " v = ", result[3]) + + +LSAP +~~~~~~ + +.. code-block:: python + + result = gedlibpy.hungarian_LSAP(matrixCost) + print("Rho = ", result[0], " Varrho = ", result[1], " u = ", result[2], " v = ", result[3]) + + + diff --git a/gklearn/gedlib/documentation/source/index.rst b/gklearn/gedlib/documentation/source/index.rst new file mode 100644 index 0000000..42b7067 --- /dev/null +++ b/gklearn/gedlib/documentation/source/index.rst @@ -0,0 +1,36 @@ +.. Python_GedLib documentation master file, created by + sphinx-quickstart on Thu Jun 13 16:10:06 2019. + You can adapt this file completely to your liking, but it should at least + contain the root `toctree` directive. + + +Welcome to GEDLIBPY's documentation! +========================================= + +This module allow to use a C++ library for edit distance between graphs (GedLib) with Python. + +Before using, please read the first section to ensure a good start with the library. Then, you can follow some examples or informations about each method. + +.. toctree:: + :maxdepth: 2 + :caption: Contents: + + readme + editcost + examples + doc + +Authors +~~~~~~~~ + +* David Blumenthal for C++ module +* Natacha Lambert for Python module + +Copyright (C) 2019 by all the authors + +Indices and tables +~~~~~~~~~~~~~~~~~~~~~ + +* :ref:`genindex` +* :ref:`modindex` +* :ref:`search` diff --git a/gklearn/gedlib/documentation/source/readme.rst b/gklearn/gedlib/documentation/source/readme.rst new file mode 100644 index 0000000..bafe5ea --- /dev/null +++ b/gklearn/gedlib/documentation/source/readme.rst @@ -0,0 +1,97 @@ +How to install this library +==================================== + +Please Read https://dbblumenthal.github.io/gedlib/ before using Python code. +You can also find this module documentation in documentation/build/html folder. + +Make sure you have numpy installed (and Cython if you have to recompile the library). You can use pip for this. + + +Running the script +------------------- + +After donwloading the entire folder, you can run test.py to ensure the library works. + +For your code, you have to make two imports:: + + import librariesImport + import gedlibpy + +You can call each function in the library with this. You can't move any folder or files on the library, please make sure that the architecture remains the same. + +This library is compiled for Python3 only. If you want to use it with Python 2, you have to recompile it with setup.py. You have to use this command on your favorite shell:: + + python setup.py build_ext --inplace + +After this step, you can use the same lines as Python3 for import, it will be ok. Check the documentation inside the documentation/build/html folder before using function. You can also copy the tests examples for basic use. + + +A problem with the library ? +------------------------------- + +If the library isn't found, you can recompile the Python library because your Linux is different to mine. Please delete gedlibpy.so, gedlibpy.cpp and build folder. Then use this command on a linux shell :: + + python3 setup.py build_ext --inplace + +You can make it with Python 2 but make sure you use the same version with your code and the compilation. + +If it's doesn't work, maybe the version of GedLib or another library can be a problem. If it is, you can re-install GedLib for your computer. You can download it on this git : https://dbblumenthal.github.io/gedlib/ + +You have to install Gedlib with the Python installer after that. +Just call:: + + python3 install.py + +Make the links like indicate on the documentation. Use the same architecture like this library, but just change the .so and folders with your installation. You can recompile the Python library with setup command, after that. + +If you use Mac OS, you have to follow all this part, and install the external libraries with this command:: + + install_name_tool -change // + +For an example, you have to write these lines:: + + install_name_tool -change libdoublefann.2.dylib lib/fann/libdoublefann.2.dylib gedlibpy.so + install_name_tool -change libsvm.so lib/libsvm.3.22/libsvm.so gedlibpy.so + install_name_tool -change libnomad.so lib/nomad/libnomad.so gedlibpy.so + install_name_tool -change libsgtelib.so lib/nomad/libsgtelib.so gedlibpy.so + +The name of the library gedlibpy can be different if you use Python 3. + +If your problem is still here, you can contact me on : natacha.lambert@unicaen.fr + +How to use this library +------------------------- + +This library allow to compute edit distance between two graphs. You have to follow these steps to use it : + +- Add your graphs (GXL files, NX Structures or your structure, make sure that the internal type is the same) +- Choose your cost function +- Init your environnment (After that, the cost function and your graphs can't be modified) +- Choose your method computation +- Run the computation with the IDs of the two graphs. You can have the ID when you add the graph or with some functions +- Find the result with differents functions (NodeMap, edit distance, etc) + +Here is an example of code with GXL graphs:: + + gedlibpy.load_GXL_graphs('include/gedlib-master/data/datasets/Mutagenicity/data/', 'collections/MUTA_10.xml') + listID = gedlibpy.get_all_graph_ids() + gedlibpy.set_edit_cost("CHEM_1") + gedlibpy.init() + gedlibpy.set_method("IPFP", "") + gedlibpy.init_method() + g = listID[0] + h = listID[1] + + gedlibpy.run_method(g,h) + + print("Node Map : ", gedlibpy.get_node_map(g,h)) + print ("Upper Bound = " + str(gedlibpy.get_upper_bound(g,h)) + ", Lower Bound = " + str(gedlibpy.get_lower_bound(g,h)) + ", Runtime = " + str(gedlibpy.get_runtime(g,h))) + + +Please read the documentation for more examples and functions. + + +An advice if you don't code in a shell +--------------------------------------- + +Python library don't indicate each C++ error. 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!defined(_MSC_VER)) +# define CYTHON_UNUSED __attribute__ ((__unused__)) +# else +# define CYTHON_UNUSED +# endif +#endif +#ifndef CYTHON_MAYBE_UNUSED_VAR +# if defined(__cplusplus) + template void CYTHON_MAYBE_UNUSED_VAR( const T& ) { } +# else +# define CYTHON_MAYBE_UNUSED_VAR(x) (void)(x) +# endif +#endif +#ifndef CYTHON_NCP_UNUSED +# if CYTHON_COMPILING_IN_CPYTHON +# define CYTHON_NCP_UNUSED +# else +# define CYTHON_NCP_UNUSED CYTHON_UNUSED +# endif +#endif +#define __Pyx_void_to_None(void_result) ((void)(void_result), Py_INCREF(Py_None), Py_None) +#ifdef _MSC_VER + #ifndef _MSC_STDINT_H_ + #if _MSC_VER < 1300 + typedef unsigned char uint8_t; + typedef unsigned int uint32_t; + #else + typedef unsigned __int8 uint8_t; + typedef unsigned __int32 uint32_t; + #endif + #endif +#else + #include +#endif +#ifndef CYTHON_FALLTHROUGH + #if defined(__cplusplus) && __cplusplus >= 201103L + #if __has_cpp_attribute(fallthrough) + #define CYTHON_FALLTHROUGH [[fallthrough]] + #elif __has_cpp_attribute(clang::fallthrough) + #define CYTHON_FALLTHROUGH [[clang::fallthrough]] + #elif __has_cpp_attribute(gnu::fallthrough) + #define CYTHON_FALLTHROUGH [[gnu::fallthrough]] + #endif + #endif + #ifndef CYTHON_FALLTHROUGH + #if __has_attribute(fallthrough) + #define CYTHON_FALLTHROUGH __attribute__((fallthrough)) + #else + #define CYTHON_FALLTHROUGH + #endif + #endif + #if defined(__clang__ ) && defined(__apple_build_version__) + #if __apple_build_version__ < 7000000 + #undef CYTHON_FALLTHROUGH + #define CYTHON_FALLTHROUGH + #endif + #endif +#endif + +#ifndef __cplusplus + #error "Cython files generated with the C++ option must be compiled with a C++ compiler." +#endif +#ifndef CYTHON_INLINE + #if defined(__clang__) + #define CYTHON_INLINE __inline__ __attribute__ ((__unused__)) + #else + #define CYTHON_INLINE inline + #endif +#endif +template +void __Pyx_call_destructor(T& x) { + x.~T(); +} +template +class __Pyx_FakeReference { + public: + __Pyx_FakeReference() : ptr(NULL) { } + __Pyx_FakeReference(const T& ref) : ptr(const_cast(&ref)) { } + T *operator->() { return ptr; } + T *operator&() { return ptr; } + operator T&() { return *ptr; } + template bool operator ==(U other) { return *ptr == other; } + template bool operator !=(U other) { return *ptr != other; } + private: + T *ptr; +}; + +#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) + #define Py_OptimizeFlag 0 +#endif +#define __PYX_BUILD_PY_SSIZE_T "n" +#define CYTHON_FORMAT_SSIZE_T "z" +#if PY_MAJOR_VERSION < 3 + #define __Pyx_BUILTIN_MODULE_NAME "__builtin__" + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) + #define __Pyx_DefaultClassType PyClass_Type +#else + #define __Pyx_BUILTIN_MODULE_NAME "builtins" +#if PY_VERSION_HEX >= 0x030800A4 && PY_VERSION_HEX < 0x030800B2 + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, 0, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#else + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#endif + #define __Pyx_DefaultClassType PyType_Type +#endif +#ifndef Py_TPFLAGS_CHECKTYPES + #define Py_TPFLAGS_CHECKTYPES 0 +#endif +#ifndef Py_TPFLAGS_HAVE_INDEX + #define Py_TPFLAGS_HAVE_INDEX 0 +#endif +#ifndef Py_TPFLAGS_HAVE_NEWBUFFER + #define Py_TPFLAGS_HAVE_NEWBUFFER 0 +#endif +#ifndef Py_TPFLAGS_HAVE_FINALIZE + #define Py_TPFLAGS_HAVE_FINALIZE 0 +#endif +#ifndef METH_STACKLESS + #define METH_STACKLESS 0 +#endif +#if PY_VERSION_HEX <= 0x030700A3 || !defined(METH_FASTCALL) + #ifndef METH_FASTCALL + #define METH_FASTCALL 0x80 + #endif + typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject *const *args, Py_ssize_t nargs); + typedef PyObject *(*__Pyx_PyCFunctionFastWithKeywords) (PyObject *self, PyObject *const *args, + Py_ssize_t nargs, PyObject *kwnames); +#else + #define __Pyx_PyCFunctionFast _PyCFunctionFast + #define __Pyx_PyCFunctionFastWithKeywords _PyCFunctionFastWithKeywords +#endif +#if CYTHON_FAST_PYCCALL +#define __Pyx_PyFastCFunction_Check(func)\ + ((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))))) +#else +#define __Pyx_PyFastCFunction_Check(func) 0 +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) + #define PyObject_Malloc(s) PyMem_Malloc(s) + #define PyObject_Free(p) PyMem_Free(p) + #define PyObject_Realloc(p) PyMem_Realloc(p) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030400A1 + #define PyMem_RawMalloc(n) PyMem_Malloc(n) + #define PyMem_RawRealloc(p, n) PyMem_Realloc(p, n) + #define PyMem_RawFree(p) PyMem_Free(p) +#endif +#if CYTHON_COMPILING_IN_PYSTON + #define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno) +#else + #define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno) +#endif +#if !CYTHON_FAST_THREAD_STATE || PY_VERSION_HEX < 0x02070000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#elif PY_VERSION_HEX >= 0x03060000 + #define __Pyx_PyThreadState_Current _PyThreadState_UncheckedGet() +#elif PY_VERSION_HEX >= 0x03000000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#else + #define __Pyx_PyThreadState_Current _PyThreadState_Current +#endif +#if PY_VERSION_HEX < 0x030700A2 && !defined(PyThread_tss_create) && !defined(Py_tss_NEEDS_INIT) +#include "pythread.h" +#define Py_tss_NEEDS_INIT 0 +typedef int Py_tss_t; +static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { + *key = PyThread_create_key(); + return 0; +} +static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { + Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); + *key = Py_tss_NEEDS_INIT; + return key; +} +static CYTHON_INLINE void PyThread_tss_free(Py_tss_t *key) { + PyObject_Free(key); +} +static CYTHON_INLINE int PyThread_tss_is_created(Py_tss_t *key) { + return *key != Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE void PyThread_tss_delete(Py_tss_t *key) { + PyThread_delete_key(*key); + *key = Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { + return PyThread_set_key_value(*key, value); +} +static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { + return PyThread_get_key_value(*key); +} +#endif +#if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) +#define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) +#else +#define __Pyx_PyDict_NewPresized(n) PyDict_New() +#endif +#if PY_MAJOR_VERSION >= 3 || CYTHON_FUTURE_DIVISION + #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) +#else + #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 && CYTHON_USE_UNICODE_INTERNALS +#define __Pyx_PyDict_GetItemStr(dict, name) _PyDict_GetItem_KnownHash(dict, name, ((PyASCIIObject *) name)->hash) +#else +#define __Pyx_PyDict_GetItemStr(dict, name) PyDict_GetItem(dict, name) +#endif +#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) + #define CYTHON_PEP393_ENABLED 1 + #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ + 0 : _PyUnicode_Ready((PyObject *)(op))) + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u) + #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u) + #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) + #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) +#else + #define CYTHON_PEP393_ENABLED 0 + #define PyUnicode_1BYTE_KIND 1 + #define PyUnicode_2BYTE_KIND 2 + #define PyUnicode_4BYTE_KIND 4 + #define __Pyx_PyUnicode_READY(op) (0) + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111) + #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE)) + #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u)) + #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i])) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch) + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u)) +#endif +#if CYTHON_COMPILING_IN_PYPY + #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) +#else + #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ + PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) + #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check) + #define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format) + #define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, "__format__", "O", fmt) +#endif +#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyString_Check(b) && !PyString_CheckExact(b)))) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) +#define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyUnicode_Check(b) && !PyUnicode_CheckExact(b)))) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b) +#else + #define __Pyx_PyString_Format(a, b) PyString_Format(a, b) +#endif +#if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII) + #define PyObject_ASCII(o) PyObject_Repr(o) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBaseString_Type PyUnicode_Type + #define PyStringObject PyUnicodeObject + #define PyString_Type PyUnicode_Type + #define PyString_Check PyUnicode_Check + #define PyString_CheckExact PyUnicode_CheckExact + #define PyObject_Unicode PyObject_Str +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) + #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) +#else + #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj)) + #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj)) +#endif +#ifndef PySet_CheckExact + #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) +#endif +#if CYTHON_ASSUME_SAFE_MACROS + #define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq) +#else + #define __Pyx_PySequence_SIZE(seq) PySequence_Size(seq) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyIntObject PyLongObject + #define PyInt_Type PyLong_Type + #define PyInt_Check(op) PyLong_Check(op) + #define PyInt_CheckExact(op) PyLong_CheckExact(op) + #define PyInt_FromString PyLong_FromString + #define PyInt_FromUnicode PyLong_FromUnicode + #define PyInt_FromLong PyLong_FromLong + #define PyInt_FromSize_t PyLong_FromSize_t + #define PyInt_FromSsize_t PyLong_FromSsize_t + #define PyInt_AsLong PyLong_AsLong + #define PyInt_AS_LONG PyLong_AS_LONG + #define PyInt_AsSsize_t PyLong_AsSsize_t + #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask + #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask + #define PyNumber_Int PyNumber_Long +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBoolObject PyLongObject +#endif +#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY + #ifndef PyUnicode_InternFromString + #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) + #endif +#endif +#if PY_VERSION_HEX < 0x030200A4 + typedef long Py_hash_t; + #define __Pyx_PyInt_FromHash_t PyInt_FromLong + #define __Pyx_PyInt_AsHash_t PyInt_AsLong +#else + #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t + #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : (Py_INCREF(func), func)) +#else + #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) +#endif +#if CYTHON_USE_ASYNC_SLOTS + #if PY_VERSION_HEX >= 0x030500B1 + #define __Pyx_PyAsyncMethodsStruct PyAsyncMethods + #define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async) + #else + #define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved)) + #endif +#else + #define __Pyx_PyType_AsAsync(obj) NULL +#endif +#ifndef __Pyx_PyAsyncMethodsStruct + typedef struct { + unaryfunc am_await; + unaryfunc am_aiter; + unaryfunc am_anext; + } __Pyx_PyAsyncMethodsStruct; +#endif + +#if defined(WIN32) || defined(MS_WINDOWS) + #define _USE_MATH_DEFINES +#endif +#include +#ifdef NAN +#define __PYX_NAN() ((float) NAN) +#else +static CYTHON_INLINE float __PYX_NAN() { + float value; + memset(&value, 0xFF, sizeof(value)); + return value; +} +#endif +#if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL) +#define __Pyx_truncl trunc +#else +#define __Pyx_truncl truncl +#endif + + +#define __PYX_ERR(f_index, lineno, Ln_error) \ +{ \ + __pyx_filename = __pyx_f[f_index]; __pyx_lineno = lineno; __pyx_clineno = __LINE__; goto Ln_error; \ +} + +#ifndef __PYX_EXTERN_C + #ifdef __cplusplus + #define __PYX_EXTERN_C extern "C" + #else + #define __PYX_EXTERN_C extern + #endif +#endif + +#define __PYX_HAVE__gedlibpy +#define __PYX_HAVE_API__gedlibpy +/* Early includes */ +#include "ios" +#include "new" +#include "stdexcept" +#include "typeinfo" +#include +#include +#include +#include +#include +#include +#include +#include "numpy/arrayobject.h" +#include "numpy/ufuncobject.h" +#include "pythread.h" +#include "src/GedLibBind.hpp" +#ifdef _OPENMP +#include +#endif /* _OPENMP */ + +#if defined(PYREX_WITHOUT_ASSERTIONS) && !defined(CYTHON_WITHOUT_ASSERTIONS) +#define CYTHON_WITHOUT_ASSERTIONS +#endif + +typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding; + const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; + +#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8) +#define __PYX_DEFAULT_STRING_ENCODING "" +#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString +#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#define __Pyx_uchar_cast(c) ((unsigned char)c) +#define __Pyx_long_cast(x) ((long)x) +#define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\ + (sizeof(type) < sizeof(Py_ssize_t)) ||\ + (sizeof(type) > sizeof(Py_ssize_t) &&\ + likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX) &&\ + (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\ + v == (type)PY_SSIZE_T_MIN))) ||\ + (sizeof(type) == sizeof(Py_ssize_t) &&\ + (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX))) ) +static CYTHON_INLINE int __Pyx_is_valid_index(Py_ssize_t i, Py_ssize_t limit) { + return (size_t) i < (size_t) limit; +} +#if defined (__cplusplus) && __cplusplus >= 201103L + #include + #define __Pyx_sst_abs(value) std::abs(value) +#elif SIZEOF_INT >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) abs(value) +#elif SIZEOF_LONG >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) labs(value) +#elif defined (_MSC_VER) + #define __Pyx_sst_abs(value) ((Py_ssize_t)_abs64(value)) +#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define __Pyx_sst_abs(value) llabs(value) +#elif defined (__GNUC__) + #define __Pyx_sst_abs(value) __builtin_llabs(value) +#else + #define __Pyx_sst_abs(value) ((value<0) ? -value : value) +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject*); +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); +#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) +#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l) +#define __Pyx_PyBytes_FromString PyBytes_FromString +#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); +#if PY_MAJOR_VERSION < 3 + #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#else + #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize +#endif +#define __Pyx_PyBytes_AsWritableString(s) ((char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableSString(s) ((signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableUString(s) ((unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsString(s) ((const char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsSString(s) ((const signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsUString(s) ((const unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyObject_AsWritableString(s) ((char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsSString(s) ((const signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsUString(s) ((const unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) +#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) +#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) +#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) +#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) +static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { + const Py_UNICODE *u_end = u; + while (*u_end++) ; + return (size_t)(u_end - u - 1); +} +#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) +#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode +#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode +#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) +#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b); +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*); +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject*); +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x); +#define __Pyx_PySequence_Tuple(obj)\ + (likely(PyTuple_CheckExact(obj)) ? __Pyx_NewRef(obj) : PySequence_Tuple(obj)) +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t); +#if CYTHON_ASSUME_SAFE_MACROS +#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x)) +#else +#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x) +#endif +#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x)) +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x)) +#else +#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x)) +#endif +#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x)) +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII +static int __Pyx_sys_getdefaultencoding_not_ascii; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + PyObject* ascii_chars_u = NULL; + PyObject* ascii_chars_b = NULL; + const char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + if (strcmp(default_encoding_c, "ascii") == 0) { + __Pyx_sys_getdefaultencoding_not_ascii = 0; + } else { + char ascii_chars[128]; + int c; + for (c = 0; c < 128; c++) { + ascii_chars[c] = c; + } + __Pyx_sys_getdefaultencoding_not_ascii = 1; + ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL); + if (!ascii_chars_u) goto bad; + ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL); + if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) { + PyErr_Format( + PyExc_ValueError, + "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.", + default_encoding_c); + goto bad; + } + Py_DECREF(ascii_chars_u); + Py_DECREF(ascii_chars_b); + } + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + Py_XDECREF(ascii_chars_u); + Py_XDECREF(ascii_chars_b); + return -1; +} +#endif +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3 +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL) +#else +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL) +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +static char* __PYX_DEFAULT_STRING_ENCODING; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c) + 1); + if (!__PYX_DEFAULT_STRING_ENCODING) goto bad; + strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c); + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + return -1; +} +#endif +#endif + + +/* Test for GCC > 2.95 */ +#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95))) + #define likely(x) __builtin_expect(!!(x), 1) + #define unlikely(x) __builtin_expect(!!(x), 0) +#else /* !__GNUC__ or GCC < 2.95 */ + #define likely(x) (x) + #define unlikely(x) (x) +#endif /* __GNUC__ */ +static CYTHON_INLINE void __Pyx_pretend_to_initialize(void* ptr) { (void)ptr; } + +static PyObject *__pyx_m = NULL; +static PyObject *__pyx_d; +static PyObject *__pyx_b; +static PyObject *__pyx_cython_runtime = NULL; +static PyObject *__pyx_empty_tuple; +static PyObject *__pyx_empty_bytes; +static PyObject *__pyx_empty_unicode; +static int __pyx_lineno; +static int __pyx_clineno = 0; +static const char * __pyx_cfilenm= __FILE__; +static const char *__pyx_filename; + +/* Header.proto */ +#if !defined(CYTHON_CCOMPLEX) + #if defined(__cplusplus) + #define CYTHON_CCOMPLEX 1 + #elif defined(_Complex_I) + #define CYTHON_CCOMPLEX 1 + #else + #define CYTHON_CCOMPLEX 0 + #endif +#endif +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #include + #else + #include + #endif +#endif +#if CYTHON_CCOMPLEX && !defined(__cplusplus) && defined(__sun__) && defined(__GNUC__) + #undef _Complex_I + #define _Complex_I 1.0fj +#endif + + +static const char *__pyx_f[] = { + "gedlibpy.pyx", + "stringsource", + "__init__.pxd", + "array.pxd", + "type.pxd", + "bool.pxd", + "complex.pxd", +}; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":776 + * # in Cython to enable them only on the right systems. + * + * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + */ +typedef npy_int8 __pyx_t_5numpy_int8_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":777 + * + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t + */ +typedef npy_int16 __pyx_t_5numpy_int16_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":778 + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< + * ctypedef npy_int64 int64_t + * #ctypedef npy_int96 int96_t + */ +typedef npy_int32 __pyx_t_5numpy_int32_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":779 + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< + * #ctypedef npy_int96 int96_t + * #ctypedef npy_int128 int128_t + */ +typedef npy_int64 __pyx_t_5numpy_int64_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":783 + * #ctypedef npy_int128 int128_t + * + * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + */ +typedef npy_uint8 __pyx_t_5numpy_uint8_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":784 + * + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t + */ +typedef npy_uint16 __pyx_t_5numpy_uint16_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":785 + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< + * ctypedef npy_uint64 uint64_t + * #ctypedef npy_uint96 uint96_t + */ +typedef npy_uint32 __pyx_t_5numpy_uint32_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":786 + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< + * #ctypedef npy_uint96 uint96_t + * #ctypedef npy_uint128 uint128_t + */ +typedef npy_uint64 __pyx_t_5numpy_uint64_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":790 + * #ctypedef npy_uint128 uint128_t + * + * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< + * ctypedef npy_float64 float64_t + * #ctypedef npy_float80 float80_t + */ +typedef npy_float32 __pyx_t_5numpy_float32_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":791 + * + * ctypedef npy_float32 float32_t + * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< + * #ctypedef npy_float80 float80_t + * #ctypedef npy_float128 float128_t + */ +typedef npy_float64 __pyx_t_5numpy_float64_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":800 + * # The int types are mapped a bit surprising -- + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t + */ +typedef npy_long __pyx_t_5numpy_int_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":801 + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong longlong_t + * + */ +typedef npy_longlong __pyx_t_5numpy_long_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":802 + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_ulong uint_t + */ +typedef npy_longlong __pyx_t_5numpy_longlong_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":804 + * ctypedef npy_longlong longlong_t + * + * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t + */ +typedef npy_ulong __pyx_t_5numpy_uint_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":805 + * + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulonglong_t + * + */ +typedef npy_ulonglong __pyx_t_5numpy_ulong_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":806 + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_intp intp_t + */ +typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":808 + * ctypedef npy_ulonglong ulonglong_t + * + * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< + * ctypedef npy_uintp uintp_t + * + */ +typedef npy_intp __pyx_t_5numpy_intp_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":809 + * + * ctypedef npy_intp intp_t + * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< + * + * ctypedef npy_double float_t + */ +typedef npy_uintp __pyx_t_5numpy_uintp_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":811 + * ctypedef npy_uintp uintp_t + * + * ctypedef npy_double float_t # <<<<<<<<<<<<<< + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t + */ +typedef npy_double __pyx_t_5numpy_float_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":812 + * + * ctypedef npy_double float_t + * ctypedef npy_double double_t # <<<<<<<<<<<<<< + * ctypedef npy_longdouble longdouble_t + * + */ +typedef npy_double __pyx_t_5numpy_double_t; + +/* "../../../../../../../../../home/ljia/.local/lib/python3.6/site-packages/Cython/Includes/numpy/__init__.pxd":813 + * ctypedef npy_double float_t + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< + * + * ctypedef npy_cfloat cfloat_t + */ +typedef npy_longdouble __pyx_t_5numpy_longdouble_t; + +/* "gedlibpy.pyx":39 + * #Long unsigned int equivalent + * cimport numpy as np + * ctypedef np.npy_uint32 UINT32_t # <<<<<<<<<<<<<< + * from cpython cimport array + * + */ +typedef npy_uint32 __pyx_t_8gedlibpy_UINT32_t; +/* Declarations.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< float > __pyx_t_float_complex; + #else + typedef float _Complex __pyx_t_float_complex; 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+ return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16LE(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = -1; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16BE(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = 1; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} + +/* decode_c_bytes.proto */ +static CYTHON_INLINE PyObject* __Pyx_decode_c_bytes( + const char* cstring, Py_ssize_t length, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)); + +/* decode_cpp_string.proto */ +static CYTHON_INLINE PyObject* __Pyx_decode_cpp_string( + std::string cppstring, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) { + return __Pyx_decode_c_bytes( + cppstring.data(), cppstring.size(), start, stop, encoding, errors, decode_func); +} + +/* RaiseArgTupleInvalid.proto */ +static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact, + Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found); + +/* KeywordStringCheck.proto */ +static int __Pyx_CheckKeywordStrings(PyObject *kwdict, const char* function_name, int kw_allowed); + +/* RaiseDoubleKeywords.proto */ +static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name); + +/* ParseKeywords.proto */ +static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[],\ + PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args,\ + const char* function_name); + +/* PyCFunctionFastCall.proto */ +#if CYTHON_FAST_PYCCALL +static CYTHON_INLINE PyObject *__Pyx_PyCFunction_FastCall(PyObject *func, PyObject **args, Py_ssize_t nargs); +#else +#define __Pyx_PyCFunction_FastCall(func, args, nargs) (assert(0), NULL) +#endif + +/* PyFunctionFastCall.proto */ +#if CYTHON_FAST_PYCALL +#define __Pyx_PyFunction_FastCall(func, args, nargs)\ + __Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL) +#if 1 || PY_VERSION_HEX < 0x030600B1 +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs); +#else +#define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs) +#endif +#define __Pyx_BUILD_ASSERT_EXPR(cond)\ + (sizeof(char [1 - 2*!(cond)]) - 1) +#ifndef Py_MEMBER_SIZE +#define Py_MEMBER_SIZE(type, member) sizeof(((type *)0)->member) +#endif + static size_t __pyx_pyframe_localsplus_offset = 0; + #include "frameobject.h" + #define __Pxy_PyFrame_Initialize_Offsets()\ + ((void)__Pyx_BUILD_ASSERT_EXPR(sizeof(PyFrameObject) == offsetof(PyFrameObject, f_localsplus) + Py_MEMBER_SIZE(PyFrameObject, f_localsplus)),\ + (void)(__pyx_pyframe_localsplus_offset = ((size_t)PyFrame_Type.tp_basicsize) - Py_MEMBER_SIZE(PyFrameObject, f_localsplus))) + #define __Pyx_PyFrame_GetLocalsplus(frame)\ + (assert(__pyx_pyframe_localsplus_offset), (PyObject **)(((char *)(frame)) + __pyx_pyframe_localsplus_offset)) +#endif + +/* PyObjectCall.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw); +#else +#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw) +#endif + +/* PyObjectCall2Args.proto */ +static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2); + +/* PyObjectCallMethO.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg); +#endif + +/* PyObjectCallOneArg.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); + +/* PyDictVersioning.proto */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +#define __PYX_DICT_VERSION_INIT ((PY_UINT64_T) -1) +#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\ + (version_var) = __PYX_GET_DICT_VERSION(dict);\ + (cache_var) = (value); +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ + (VAR) = __pyx_dict_cached_value;\ + } else {\ + (VAR) = __pyx_dict_cached_value = (LOOKUP);\ + __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ + }\ +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj); +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj); +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version); +#else +#define __PYX_GET_DICT_VERSION(dict) (0) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var) +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) (VAR) = (LOOKUP); +#endif + +/* GetModuleGlobalName.proto */ +#if CYTHON_USE_DICT_VERSIONS +#define __Pyx_GetModuleGlobalName(var, name) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + (var) = (likely(__pyx_dict_version == __PYX_GET_DICT_VERSION(__pyx_d))) ?\ + (likely(__pyx_dict_cached_value) ? __Pyx_NewRef(__pyx_dict_cached_value) : __Pyx_GetBuiltinName(name)) :\ + __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ +} +#define __Pyx_GetModuleGlobalNameUncached(var, name) {\ + PY_UINT64_T __pyx_dict_version;\ + PyObject *__pyx_dict_cached_value;\ + (var) = __Pyx__GetModuleGlobalName(name, &__pyx_dict_version, &__pyx_dict_cached_value);\ +} +static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value); +#else +#define __Pyx_GetModuleGlobalName(var, name) (var) = __Pyx__GetModuleGlobalName(name) +#define __Pyx_GetModuleGlobalNameUncached(var, name) (var) = __Pyx__GetModuleGlobalName(name) +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name); +#endif + +/* PySequenceContains.proto */ +static CYTHON_INLINE int __Pyx_PySequence_ContainsTF(PyObject* item, PyObject* seq, int eq) { + int result = PySequence_Contains(seq, item); + return unlikely(result < 0) ? result : (result == (eq == Py_EQ)); +} + +/* PyThreadStateGet.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyThreadState_declare PyThreadState *__pyx_tstate; +#define __Pyx_PyThreadState_assign __pyx_tstate = __Pyx_PyThreadState_Current; +#define __Pyx_PyErr_Occurred() __pyx_tstate->curexc_type +#else +#define __Pyx_PyThreadState_declare +#define __Pyx_PyThreadState_assign +#define __Pyx_PyErr_Occurred() PyErr_Occurred() +#endif + +/* PyErrFetchRestore.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyErr_Clear() __Pyx_ErrRestore(NULL, NULL, NULL) +#define __Pyx_ErrRestoreWithState(type, value, tb) __Pyx_ErrRestoreInState(PyThreadState_GET(), type, value, tb) +#define __Pyx_ErrFetchWithState(type, value, tb) __Pyx_ErrFetchInState(PyThreadState_GET(), type, value, tb) +#define __Pyx_ErrRestore(type, value, tb) __Pyx_ErrRestoreInState(__pyx_tstate, type, value, tb) +#define __Pyx_ErrFetch(type, value, tb) __Pyx_ErrFetchInState(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#if CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_PyErr_SetNone(exc) (Py_INCREF(exc), __Pyx_ErrRestore((exc), NULL, NULL)) +#else +#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) +#endif +#else +#define __Pyx_PyErr_Clear() PyErr_Clear() +#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) +#define __Pyx_ErrRestoreWithState(type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetchWithState(type, value, tb) PyErr_Fetch(type, value, tb) +#define __Pyx_ErrRestoreInState(tstate, type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetchInState(tstate, type, value, tb) PyErr_Fetch(type, value, tb) +#define __Pyx_ErrRestore(type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetch(type, value, tb) PyErr_Fetch(type, value, tb) +#endif + +/* RaiseException.proto */ +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); + +/* GetItemInt.proto */ +#define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\ + (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\ + __Pyx_GetItemInt_Generic(o, to_py_func(i)))) +#define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ + (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +#define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ + (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ + __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ + (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL)) +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + int wraparound, int boundscheck); +static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j); +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, + int is_list, int wraparound, int boundscheck); + +/* ObjectGetItem.proto */ +#if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key); +#else +#define __Pyx_PyObject_GetItem(obj, key) PyObject_GetItem(obj, key) +#endif + +/* PyObjectCallNoArg.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func); +#else +#define __Pyx_PyObject_CallNoArg(func) __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL) +#endif + +/* IterFinish.proto */ +static CYTHON_INLINE int __Pyx_IterFinish(void); + +/* PyObjectGetMethod.proto */ +static int __Pyx_PyObject_GetMethod(PyObject *obj, PyObject *name, PyObject **method); + +/* PyObjectCallMethod0.proto */ +static PyObject* __Pyx_PyObject_CallMethod0(PyObject* obj, PyObject* method_name); + +/* RaiseNeedMoreValuesToUnpack.proto */ +static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); + +/* RaiseTooManyValuesToUnpack.proto */ +static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); + +/* UnpackItemEndCheck.proto */ +static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected); + +/* RaiseNoneIterError.proto */ +static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); + +/* UnpackTupleError.proto */ +static void __Pyx_UnpackTupleError(PyObject *, Py_ssize_t index); + +/* UnpackTuple2.proto */ +#define __Pyx_unpack_tuple2(tuple, value1, value2, is_tuple, has_known_size, decref_tuple)\ + (likely(is_tuple || PyTuple_Check(tuple)) ?\ + (likely(has_known_size || PyTuple_GET_SIZE(tuple) == 2) ?\ + __Pyx_unpack_tuple2_exact(tuple, value1, value2, decref_tuple) :\ + (__Pyx_UnpackTupleError(tuple, 2), -1)) :\ + __Pyx_unpack_tuple2_generic(tuple, value1, value2, has_known_size, decref_tuple)) +static CYTHON_INLINE int __Pyx_unpack_tuple2_exact( + PyObject* tuple, PyObject** value1, PyObject** value2, int decref_tuple); +static int __Pyx_unpack_tuple2_generic( + PyObject* tuple, PyObject** value1, PyObject** value2, int has_known_size, int decref_tuple); + +/* dict_iter.proto */ +static CYTHON_INLINE PyObject* __Pyx_dict_iterator(PyObject* dict, int is_dict, PyObject* method_name, + Py_ssize_t* p_orig_length, int* p_is_dict); +static CYTHON_INLINE int __Pyx_dict_iter_next(PyObject* dict_or_iter, Py_ssize_t orig_length, Py_ssize_t* ppos, + PyObject** pkey, PyObject** pvalue, PyObject** pitem, int is_dict); + +/* PyObjectSetAttrStr.proto */ +#if CYTHON_USE_TYPE_SLOTS +#define __Pyx_PyObject_DelAttrStr(o,n) __Pyx_PyObject_SetAttrStr(o, n, NULL) +static CYTHON_INLINE int __Pyx_PyObject_SetAttrStr(PyObject* obj, PyObject* attr_name, PyObject* value); +#else +#define __Pyx_PyObject_DelAttrStr(o,n) PyObject_DelAttr(o,n) +#define __Pyx_PyObject_SetAttrStr(o,n,v) PyObject_SetAttr(o,n,v) +#endif + +/* DictGetItem.proto */ +#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY +static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key); +#define __Pyx_PyObject_Dict_GetItem(obj, name)\ + (likely(PyDict_CheckExact(obj)) ?\ + __Pyx_PyDict_GetItem(obj, name) : PyObject_GetItem(obj, name)) +#else +#define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key) +#define __Pyx_PyObject_Dict_GetItem(obj, name) PyObject_GetItem(obj, name) +#endif + +/* ExtTypeTest.proto */ +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); + +/* GetTopmostException.proto */ +#if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate); +#endif + +/* SaveResetException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_ExceptionSave(type, value, tb) __Pyx__ExceptionSave(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#define __Pyx_ExceptionReset(type, value, tb) __Pyx__ExceptionReset(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); +#else +#define __Pyx_ExceptionSave(type, value, tb) PyErr_GetExcInfo(type, value, tb) +#define __Pyx_ExceptionReset(type, value, tb) PyErr_SetExcInfo(type, value, tb) +#endif + +/* PyErrExceptionMatches.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyErr_ExceptionMatches(err) __Pyx_PyErr_ExceptionMatchesInState(__pyx_tstate, err) +static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err); +#else +#define __Pyx_PyErr_ExceptionMatches(err) PyErr_ExceptionMatches(err) +#endif + +/* GetException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_GetException(type, value, tb) __Pyx__GetException(__pyx_tstate, type, value, tb) +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); +#endif + +/* PyObject_GenericGetAttrNoDict.proto */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name); +#else +#define __Pyx_PyObject_GenericGetAttrNoDict PyObject_GenericGetAttr +#endif + +/* PyObject_GenericGetAttr.proto */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name); +#else +#define __Pyx_PyObject_GenericGetAttr PyObject_GenericGetAttr +#endif + +/* SetupReduce.proto */ +static int __Pyx_setup_reduce(PyObject* type_obj); + +/* TypeImport.proto */ +#ifndef __PYX_HAVE_RT_ImportType_proto +#define __PYX_HAVE_RT_ImportType_proto +enum __Pyx_ImportType_CheckSize { + __Pyx_ImportType_CheckSize_Error = 0, + __Pyx_ImportType_CheckSize_Warn = 1, + __Pyx_ImportType_CheckSize_Ignore = 2 +}; +static PyTypeObject *__Pyx_ImportType(PyObject* module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size); +#endif + +/* Import.proto */ +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); + +/* CalculateMetaclass.proto */ +static PyObject *__Pyx_CalculateMetaclass(PyTypeObject *metaclass, PyObject *bases); + +/* Py3ClassCreate.proto */ +static PyObject *__Pyx_Py3MetaclassPrepare(PyObject *metaclass, PyObject *bases, PyObject *name, PyObject *qualname, + PyObject *mkw, PyObject *modname, PyObject *doc); +static PyObject *__Pyx_Py3ClassCreate(PyObject *metaclass, PyObject *name, PyObject *bases, PyObject *dict, + PyObject *mkw, int calculate_metaclass, int allow_py2_metaclass); + +/* FetchCommonType.proto */ +static PyTypeObject* __Pyx_FetchCommonType(PyTypeObject* type); + +/* CythonFunction.proto */ +#define __Pyx_CyFunction_USED 1 +#define __Pyx_CYFUNCTION_STATICMETHOD 0x01 +#define __Pyx_CYFUNCTION_CLASSMETHOD 0x02 +#define __Pyx_CYFUNCTION_CCLASS 0x04 +#define __Pyx_CyFunction_GetClosure(f)\ + (((__pyx_CyFunctionObject *) (f))->func_closure) +#define __Pyx_CyFunction_GetClassObj(f)\ + (((__pyx_CyFunctionObject *) (f))->func_classobj) +#define __Pyx_CyFunction_Defaults(type, f)\ + ((type *)(((__pyx_CyFunctionObject *) (f))->defaults)) +#define __Pyx_CyFunction_SetDefaultsGetter(f, g)\ + ((__pyx_CyFunctionObject *) (f))->defaults_getter = (g) +typedef struct { + PyCFunctionObject func; +#if PY_VERSION_HEX < 0x030500A0 + PyObject *func_weakreflist; +#endif + PyObject *func_dict; + PyObject *func_name; + PyObject *func_qualname; + PyObject *func_doc; + PyObject *func_globals; + PyObject *func_code; + PyObject *func_closure; + PyObject *func_classobj; + void *defaults; + int defaults_pyobjects; + int flags; + PyObject *defaults_tuple; + PyObject *defaults_kwdict; + PyObject *(*defaults_getter)(PyObject *); + PyObject *func_annotations; +} __pyx_CyFunctionObject; +static PyTypeObject *__pyx_CyFunctionType = 0; +#define __Pyx_CyFunction_Check(obj) (__Pyx_TypeCheck(obj, __pyx_CyFunctionType)) +#define __Pyx_CyFunction_NewEx(ml, flags, qualname, self, module, globals, code)\ + __Pyx_CyFunction_New(__pyx_CyFunctionType, ml, flags, qualname, self, module, globals, code) +static PyObject *__Pyx_CyFunction_New(PyTypeObject *, PyMethodDef *ml, + int flags, PyObject* qualname, + PyObject *self, + PyObject *module, PyObject *globals, + PyObject* code); +static CYTHON_INLINE void *__Pyx_CyFunction_InitDefaults(PyObject *m, + size_t size, + int pyobjects); +static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsTuple(PyObject *m, + PyObject *tuple); +static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsKwDict(PyObject *m, + PyObject *dict); +static CYTHON_INLINE void __Pyx_CyFunction_SetAnnotationsDict(PyObject *m, + PyObject *dict); +static int __pyx_CyFunction_init(void); + +/* SetNameInClass.proto */ +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 +#define __Pyx_SetNameInClass(ns, name, value)\ + (likely(PyDict_CheckExact(ns)) ? _PyDict_SetItem_KnownHash(ns, name, value, ((PyASCIIObject *) name)->hash) : PyObject_SetItem(ns, name, value)) +#elif CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_SetNameInClass(ns, name, value)\ + (likely(PyDict_CheckExact(ns)) ? PyDict_SetItem(ns, name, value) : PyObject_SetItem(ns, name, value)) +#else +#define __Pyx_SetNameInClass(ns, name, value) PyObject_SetItem(ns, name, value) +#endif + +/* CLineInTraceback.proto */ +#ifdef CYTHON_CLINE_IN_TRACEBACK +#define __Pyx_CLineForTraceback(tstate, c_line) (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0) +#else +static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line); +#endif + +/* CodeObjectCache.proto */ +typedef struct { + PyCodeObject* code_object; + int code_line; +} __Pyx_CodeObjectCacheEntry; +struct __Pyx_CodeObjectCache { + int count; + int max_count; + __Pyx_CodeObjectCacheEntry* entries; +}; +static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL}; +static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line); +static PyCodeObject *__pyx_find_code_object(int code_line); +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object); + +/* AddTraceback.proto */ +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename); + +/* ArrayAPI.proto */ +#ifndef _ARRAYARRAY_H +#define _ARRAYARRAY_H +typedef struct arraydescr { + int typecode; + int itemsize; + PyObject * (*getitem)(struct arrayobject *, Py_ssize_t); + int (*setitem)(struct arrayobject *, Py_ssize_t, PyObject *); +#if PY_MAJOR_VERSION >= 3 + char *formats; +#endif +} arraydescr; +struct arrayobject { + PyObject_HEAD + Py_ssize_t ob_size; + union { + char *ob_item; + float *as_floats; + double *as_doubles; + int *as_ints; + unsigned int *as_uints; + unsigned char *as_uchars; + signed char *as_schars; + char *as_chars; + unsigned long *as_ulongs; + long *as_longs; +#if PY_MAJOR_VERSION >= 3 + unsigned long long *as_ulonglongs; + long long *as_longlongs; +#endif + short *as_shorts; + unsigned short *as_ushorts; + Py_UNICODE *as_pyunicodes; + void *as_voidptr; + } data; + Py_ssize_t allocated; + struct arraydescr *ob_descr; + PyObject *weakreflist; +#if PY_MAJOR_VERSION >= 3 + int ob_exports; +#endif +}; +#ifndef NO_NEWARRAY_INLINE +static CYTHON_INLINE PyObject * newarrayobject(PyTypeObject *type, Py_ssize_t size, + struct arraydescr *descr) { + arrayobject *op; + size_t nbytes; + if (size < 0) { + PyErr_BadInternalCall(); + return NULL; + } + nbytes = size * descr->itemsize; + if (nbytes / descr->itemsize != (size_t)size) { + return PyErr_NoMemory(); + } + op = (arrayobject *) type->tp_alloc(type, 0); + if (op == NULL) { + return NULL; + } + op->ob_descr = descr; + op->allocated = size; + op->weakreflist = NULL; + op->ob_size = size; + if (size <= 0) { + op->data.ob_item = NULL; + } + else { + op->data.ob_item = PyMem_NEW(char, nbytes); + if (op->data.ob_item == NULL) { + Py_DECREF(op); + return PyErr_NoMemory(); + } + } + return (PyObject *) op; +} +#else +PyObject* newarrayobject(PyTypeObject *type, Py_ssize_t size, + struct arraydescr *descr); +#endif +static CYTHON_INLINE int resize(arrayobject *self, Py_ssize_t n) { + void *items = (void*) self->data.ob_item; + PyMem_Resize(items, char, (size_t)(n * self->ob_descr->itemsize)); + if (items == NULL) { + PyErr_NoMemory(); + return -1; + } + self->data.ob_item = (char*) items; + self->ob_size = n; + self->allocated = n; + return 0; +} +static CYTHON_INLINE int resize_smart(arrayobject *self, Py_ssize_t n) { + void *items = (void*) self->data.ob_item; + Py_ssize_t newsize; + if (n < self->allocated && n*4 > self->allocated) { + self->ob_size = n; + return 0; + } + newsize = n + (n / 2) + 1; + if (newsize <= n) { + PyErr_NoMemory(); + return -1; + } + PyMem_Resize(items, char, (size_t)(newsize * self->ob_descr->itemsize)); + if (items == NULL) { + PyErr_NoMemory(); + return -1; + } + self->data.ob_item = (char*) items; + self->ob_size = n; + self->allocated = newsize; + return 0; +} +#endif + +/* CppExceptionConversion.proto */ +#ifndef __Pyx_CppExn2PyErr +#include +#include +#include +#include +static void __Pyx_CppExn2PyErr() { + try { + if (PyErr_Occurred()) + ; // let the latest Python exn pass through and ignore the current one + else + throw; + } catch (const std::bad_alloc& exn) { + PyErr_SetString(PyExc_MemoryError, exn.what()); + } catch (const std::bad_cast& exn) { + PyErr_SetString(PyExc_TypeError, exn.what()); + } catch (const std::bad_typeid& exn) { + PyErr_SetString(PyExc_TypeError, exn.what()); + } catch (const std::domain_error& exn) { + PyErr_SetString(PyExc_ValueError, exn.what()); + } catch (const std::invalid_argument& exn) { + PyErr_SetString(PyExc_ValueError, exn.what()); + } catch (const std::ios_base::failure& exn) { + PyErr_SetString(PyExc_IOError, exn.what()); + } catch (const std::out_of_range& exn) { + PyErr_SetString(PyExc_IndexError, exn.what()); + } catch (const std::overflow_error& exn) { + PyErr_SetString(PyExc_OverflowError, exn.what()); + } catch (const std::range_error& exn) { + PyErr_SetString(PyExc_ArithmeticError, exn.what()); + } catch (const std::underflow_error& exn) { + PyErr_SetString(PyExc_ArithmeticError, exn.what()); + } catch (const std::exception& exn) { + PyErr_SetString(PyExc_RuntimeError, exn.what()); + } + catch (...) + { + PyErr_SetString(PyExc_RuntimeError, "Unknown exception"); + } +} +#endif + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_npy_uint64(npy_uint64 value); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); + +/* RealImag.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #define __Pyx_CREAL(z) ((z).real()) + #define __Pyx_CIMAG(z) ((z).imag()) + #else + #define __Pyx_CREAL(z) (__real__(z)) + #define __Pyx_CIMAG(z) (__imag__(z)) + #endif +#else + #define __Pyx_CREAL(z) ((z).real) + #define __Pyx_CIMAG(z) ((z).imag) +#endif +#if defined(__cplusplus) && CYTHON_CCOMPLEX\ + && (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103) + #define __Pyx_SET_CREAL(z,x) ((z).real(x)) + #define __Pyx_SET_CIMAG(z,y) ((z).imag(y)) +#else + #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x) + #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y) +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_float(a, b) ((a)==(b)) + #define __Pyx_c_sum_float(a, b) ((a)+(b)) + #define __Pyx_c_diff_float(a, b) ((a)-(b)) + #define __Pyx_c_prod_float(a, b) ((a)*(b)) + #define __Pyx_c_quot_float(a, b) ((a)/(b)) + #define __Pyx_c_neg_float(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_float(z) ((z)==(float)0) + #define __Pyx_c_conj_float(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_float(z) (::std::abs(z)) + #define __Pyx_c_pow_float(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_float(z) ((z)==0) + #define __Pyx_c_conj_float(z) (conjf(z)) + #if 1 + #define __Pyx_c_abs_float(z) (cabsf(z)) + #define __Pyx_c_pow_float(a, b) (cpowf(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex); + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex, __pyx_t_float_complex); + #endif +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_double(a, b) ((a)==(b)) + #define __Pyx_c_sum_double(a, b) ((a)+(b)) + #define __Pyx_c_diff_double(a, b) ((a)-(b)) + #define __Pyx_c_prod_double(a, b) ((a)*(b)) + #define __Pyx_c_quot_double(a, b) ((a)/(b)) + #define __Pyx_c_neg_double(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_double(z) ((z)==(double)0) + #define __Pyx_c_conj_double(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (::std::abs(z)) + #define __Pyx_c_pow_double(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_double(z) ((z)==0) + #define __Pyx_c_conj_double(z) (conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (cabs(z)) + #define __Pyx_c_pow_double(a, b) (cpow(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex); + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex, __pyx_t_double_complex); + #endif +#endif + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value); + +/* CIntFromPy.proto */ +static CYTHON_INLINE size_t __Pyx_PyInt_As_size_t(PyObject *); + +/* CIntFromPy.proto */ +static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); + +/* CIntFromPy.proto */ +static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); + +/* FastTypeChecks.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_TypeCheck(obj, type) __Pyx_IsSubtype(Py_TYPE(obj), (PyTypeObject *)type) +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject *type); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2); +#else +#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) +#define __Pyx_PyErr_GivenExceptionMatches(err, type) PyErr_GivenExceptionMatches(err, type) +#define __Pyx_PyErr_GivenExceptionMatches2(err, type1, type2) (PyErr_GivenExceptionMatches(err, type1) || PyErr_GivenExceptionMatches(err, type2)) +#endif +#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception) + +/* CStringEquals.proto */ +static CYTHON_INLINE int __Pyx_StrEq(const char *, const char *); + +/* CheckBinaryVersion.proto */ +static int __Pyx_check_binary_version(void); + +/* InitStrings.proto */ +static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); + + +/* Module declarations from 'libcpp.vector' */ + +/* Module declarations from 'libc.string' */ + +/* Module declarations from 'libcpp.string' */ + +/* Module declarations from 'libcpp.utility' */ + +/* Module declarations from 'libcpp.map' */ + +/* Module declarations from 'libcpp' */ + +/* Module declarations from 'libcpp.pair' */ + +/* Module declarations from 'libcpp.list' */ + +/* Module declarations from 'cpython.buffer' */ + +/* Module declarations from 'libc.stdio' */ + +/* Module declarations from '__builtin__' */ + +/* Module declarations from 'cpython.type' */ +static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; + +/* Module declarations from 'cpython.version' */ + +/* Module declarations from 'cpython.exc' */ + +/* Module declarations from 'cpython.module' */ + +/* Module declarations from 'cpython.mem' */ + +/* Module declarations from 'cpython.tuple' */ + +/* Module declarations from 'cpython.list' */ + +/* Module declarations from 'cpython.sequence' */ + +/* Module declarations from 'cpython.mapping' */ + +/* Module declarations from 'cpython.iterator' */ + +/* Module declarations from 'cpython.number' */ + +/* Module declarations from 'cpython.int' */ + +/* Module declarations from '__builtin__' */ + +/* Module declarations from 'cpython.bool' */ +static PyTypeObject *__pyx_ptype_7cpython_4bool_bool = 0; + +/* Module declarations from 'cpython.long' */ + +/* Module declarations from 'cpython.float' */ + +/* Module declarations from '__builtin__' */ + +/* Module declarations from 'cpython.complex' */ +static PyTypeObject *__pyx_ptype_7cpython_7complex_complex = 0; + +/* Module declarations from 'cpython.string' */ + +/* Module declarations from 'cpython.unicode' */ + +/* Module declarations from 'cpython.dict' */ + +/* Module declarations from 'cpython.instance' */ + +/* Module declarations from 'cpython.function' */ + +/* Module declarations from 'cpython.method' */ + +/* Module declarations from 'cpython.weakref' */ + +/* Module declarations from 'cpython.getargs' */ + +/* Module declarations from 'cpython.pythread' */ + +/* Module declarations from 'cpython.pystate' */ + +/* Module declarations from 'cpython.cobject' */ + +/* Module declarations from 'cpython.oldbuffer' */ + +/* Module declarations from 'cpython.set' */ + +/* Module declarations from 'cpython.bytes' */ + +/* Module declarations from 'cpython.pycapsule' */ + +/* Module declarations from 'cpython' */ + +/* Module declarations from 'cpython.object' */ + +/* Module declarations from 'cpython.ref' */ + +/* Module declarations from 'numpy' */ + +/* Module declarations from 'numpy' */ +static PyTypeObject *__pyx_ptype_5numpy_dtype = 0; +static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0; +static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0; +static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; +static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; +static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *, char *, char *, int *); /*proto*/ + +/* Module declarations from 'array' */ + +/* Module declarations from 'cpython.array' */ +static PyTypeObject *__pyx_ptype_7cpython_5array_array = 0; +static CYTHON_INLINE int __pyx_f_7cpython_5array_extend_buffer(arrayobject *, char *, Py_ssize_t); /*proto*/ + +/* Module declarations from 'gedlibpy' */ +static PyTypeObject *__pyx_ptype_8gedlibpy_GEDEnv = 0; +static CYTHON_INLINE PyObject *__pyx_convert_PyObject_string_to_py_std__in_string(std::string const &); /*proto*/ +static CYTHON_INLINE PyObject *__pyx_convert_PyUnicode_string_to_py_std__in_string(std::string const &); /*proto*/ +static CYTHON_INLINE PyObject *__pyx_convert_PyStr_string_to_py_std__in_string(std::string const &); /*proto*/ +static CYTHON_INLINE PyObject *__pyx_convert_PyBytes_string_to_py_std__in_string(std::string const &); /*proto*/ +static CYTHON_INLINE PyObject *__pyx_convert_PyByteArray_string_to_py_std__in_string(std::string const &); /*proto*/ +static std::string __pyx_convert_string_from_py_std__in_string(PyObject *); /*proto*/ +static PyObject *__pyx_convert_pair_to_py_size_t____size_t(std::pair const &); /*proto*/ +static PyObject *__pyx_convert_vector_to_py_size_t(const std::vector &); /*proto*/ +static std::map __pyx_convert_map_from_py_std_3a__3a_string__and_std_3a__3a_string(PyObject *); /*proto*/ +static PyObject *__pyx_convert_map_to_py_std_3a__3a_string____std_3a__3a_string(std::map const &); /*proto*/ +static PyObject *__pyx_convert_map_to_py_std_3a__3a_pair_3c_size_t_2c_size_t_3e_______std_3a__3a_map_3c_std_3a__3a_string_2c_std_3a__3a_string_3e___(std::map ,std::map > const &); /*proto*/ +static PyObject *__pyx_convert_vector_to_py_std_3a__3a_vector_3c_size_t_3e___(const std::vector > &); /*proto*/ +static std::vector __pyx_convert_vector_from_py_double(PyObject *); /*proto*/ +static PyObject *__pyx_convert_vector_to_py_npy_uint64(const std::vector &); /*proto*/ +static PyObject *__pyx_convert_vector_to_py_std_3a__3a_pair_3c_size_t_2c_size_t_3e___(const std::vector > &); /*proto*/ +static PyObject *__pyx_convert_vector_to_py_int(const std::vector &); /*proto*/ +static PyObject *__pyx_convert_vector_to_py_std_3a__3a_vector_3c_int_3e___(const std::vector > &); /*proto*/ +static PyObject *__pyx_convert_vector_to_py_std_3a__3a_vector_3c_npy_uint64_3e___(const std::vector > &); /*proto*/ +static std::vector __pyx_convert_vector_from_py_size_t(PyObject *); /*proto*/ +static std::vector > __pyx_convert_vector_from_py_std_3a__3a_vector_3c_size_t_3e___(PyObject *); /*proto*/ +static std::vector > __pyx_convert_vector_from_py_std_3a__3a_vector_3c_double_3e___(PyObject *); /*proto*/ +static PyObject *__pyx_convert_vector_to_py_double(const std::vector &); /*proto*/ +static PyObject *__pyx_convert_vector_to_py_std_3a__3a_vector_3c_double_3e___(const std::vector > &); /*proto*/ +static std::vector > __pyx_convert_vector_from_py_std_3a__3a_map_3c_std_3a__3a_string_2c_std_3a__3a_string_3e___(PyObject *); /*proto*/ +#define __Pyx_MODULE_NAME "gedlibpy" +extern int __pyx_module_is_main_gedlibpy; +int __pyx_module_is_main_gedlibpy = 0; + +/* Implementation of 'gedlibpy' */ +static PyObject *__pyx_builtin_print; +static PyObject *__pyx_builtin_range; +static PyObject *__pyx_builtin_TypeError; +static PyObject *__pyx_builtin_ValueError; +static PyObject *__pyx_builtin_RuntimeError; +static PyObject *__pyx_builtin_ImportError; +static PyObject *__pyx_builtin_MemoryError; +static const char __pyx_k_[] = ""; +static const char __pyx_k_g[] = "g"; +static const char __pyx_k_h[] = "h"; +static const char __pyx_k_g1[] = "g1"; +static const char __pyx_k_g2[] = "g2"; +static const char __pyx_k_id[] = "id"; +static const char __pyx_k_nx[] = "nx"; +static const char __pyx_k_os[] = "os"; +static const char __pyx_k__20[] = "*"; +static const char __pyx_k_doc[] = "__doc__"; +static const char __pyx_k_key[] = "key"; +static const char __pyx_k_res[] = "res"; +static const char __pyx_k_cdll[] = "cdll"; +static const char __pyx_k_file[] = "__file__"; +static const char __pyx_k_g_id[] = "g_id"; +static const char __pyx_k_h_id[] = "h_id"; +static const char __pyx_k_head[] = "head"; +static const char __pyx_k_init[] = "init"; +static const char __pyx_k_lib1[] = "lib1"; +static const char __pyx_k_lib2[] = "lib2"; +static const char __pyx_k_lib3[] = "lib3"; +static const char __pyx_k_lib4[] = "lib4"; +static const char __pyx_k_main[] = "__main__"; +static const char __pyx_k_name[] = "name"; +static const char __pyx_k_path[] = "path"; +static const char __pyx_k_self[] = "self"; +static const char __pyx_k_tail[] = "tail"; +static const char __pyx_k_test[] = "__test__"; +static const char __pyx_k_Error[] = "Error"; +static const char __pyx_k_Graph[] = "Graph"; +static const char __pyx_k_edges[] = "edges"; +static const char __pyx_k_graph[] = "graph"; +static const char __pyx_k_items[] = "items"; +static const char __pyx_k_map_b[] = "map_b"; +static const char __pyx_k_map_u[] = "map_u"; +static const char __pyx_k_nodes[] = "nodes"; +static const char __pyx_k_print[] = "print"; +static const char __pyx_k_range[] = "range"; +static const char __pyx_k_utf_8[] = "utf-8"; +static const char __pyx_k_value[] = "value"; +static const char __pyx_k_GEDEnv[] = "GEDEnv"; +static const char __pyx_k_classe[] = "classe"; +static const char __pyx_k_ctypes[] = "ctypes"; +static const char __pyx_k_decode[] = "decode"; +static const char __pyx_k_encode[] = "encode"; +static const char __pyx_k_import[] = "__import__"; +static const char __pyx_k_init_2[] = "__init__"; +static const char __pyx_k_method[] = "method"; +static const char __pyx_k_module[] = "__module__"; +static const char __pyx_k_name_2[] = "__name__"; +static const char __pyx_k_option[] = "option"; +static const char __pyx_k_reduce[] = "__reduce__"; +static const char __pyx_k_classes[] = "classes"; +static const char __pyx_k_dataset[] = "dataset"; +static const char __pyx_k_dirname[] = "dirname"; +static const char __pyx_k_message[] = "message"; +static const char __pyx_k_node_id[] = "node_id"; +static const char __pyx_k_options[] = "options"; +static const char __pyx_k_prepare[] = "__prepare__"; +static const char __pyx_k_add_edge[] = "add_edge"; +static const char __pyx_k_add_node[] = "add_node"; +static const char __pyx_k_gedlibpy[] = "gedlibpy"; +static const char __pyx_k_getstate[] = "__getstate__"; +static const char __pyx_k_graph_id[] = "graph_id"; +static const char __pyx_k_networkx[] = "networkx"; +static const char __pyx_k_nx_graph[] = "nx_graph"; +static const char __pyx_k_path_XML[] = "path_XML"; +static const char __pyx_k_qualname[] = "__qualname__"; +static const char __pyx_k_realpath[] = "realpath"; +static const char __pyx_k_setstate[] = "__setstate__"; +static const char __pyx_k_InitError[] = "InitError"; +static const char __pyx_k_TypeError[] = "TypeError"; +static const char __pyx_k_add_graph[] = "add_graph"; +static const char __pyx_k_adj_lists[] = "adj_lists"; +static const char __pyx_k_edge_list[] = "edge_list"; +static const char __pyx_k_edge_type[] = "edge_type"; +static const char __pyx_k_edit_cost[] = "edit_cost"; +static const char __pyx_k_graph_ids[] = "graph_ids"; +static const char __pyx_k_iteritems[] = "iteritems"; +static const char __pyx_k_map_edges[] = "map_edges"; +static const char __pyx_k_metaclass[] = "__metaclass__"; +static const char __pyx_k_node_type[] = "node_type"; +static const char __pyx_k_reduce_ex[] = "__reduce_ex__"; +static const char __pyx_k_ValueError[] = "ValueError"; +static const char __pyx_k_adj_matrix[] = "adj_matrix"; +static const char __pyx_k_edge_label[] = "edge_label"; +static const char __pyx_k_graph_name[] = "graph_name"; +static const char __pyx_k_map_edge_b[] = "map_edge_b"; +static const char __pyx_k_node_label[] = "node_label"; +static const char __pyx_k_run_method[] = "run_method"; +static const char __pyx_k_set_method[] = "set_method"; +static const char __pyx_k_ImportError[] = "ImportError"; +static const char __pyx_k_LoadLibrary[] = "LoadLibrary"; +static const char __pyx_k_MemoryError[] = "MemoryError"; +static const char __pyx_k_MethodError[] = "MethodError"; +static const char __pyx_k_clear_graph[] = "clear_graph"; +static const char __pyx_k_graph_class[] = "graph_class"; +static const char __pyx_k_init_method[] = "init_method"; +static const char __pyx_k_init_option[] = "init_option"; +static const char __pyx_k_path_folder[] = "path_folder"; +static const char __pyx_k_restart_env[] = "restart_env"; +static const char __pyx_k_RuntimeError[] = "RuntimeError"; +static const char __pyx_k_add_nx_graph[] = "add_nx_graph"; +static const char __pyx_k_edge_label_1[] = "edge_label_1"; +static const char __pyx_k_edge_label_2[] = "edge_label_2"; +static const char __pyx_k_edge_label_b[] = "edge_label_b"; +static const char __pyx_k_gedlibpy_pyx[] = "gedlibpy.pyx"; +static const char __pyx_k_get_node_map[] = "get_node_map"; +static const char __pyx_k_node_label_1[] = "node_label_1"; +static const char __pyx_k_node_label_2[] = "node_label_2"; +static const char __pyx_k_EditCostError[] = "EditCostError"; +static const char __pyx_k_Graphs_loaded[] = "Graphs loaded ! "; +static const char __pyx_k_get_edge_data[] = "get_edge_data"; +static const char __pyx_k_list_of_edges[] = "list_of_edges"; +static const char __pyx_k_list_of_nodes[] = "list_of_nodes"; +static const char __pyx_k_reduce_cython[] = "__reduce_cython__"; +static const char __pyx_k_set_edit_cost[] = "set_edit_cost"; +static const char __pyx_k_get_dummy_node[] = "get_dummy_node"; +static const char __pyx_k_is_initialized[] = "is_initialized"; +static const char __pyx_k_decode_your_map[] = "decode_your_map"; +static const char __pyx_k_encode_your_map[] = "encode_your_map"; +static const char __pyx_k_get_graph_edges[] = "get_graph_edges"; +static const char __pyx_k_get_upper_bound[] = "get_upper_bound"; +static const char __pyx_k_load_GXL_graphs[] = "load_GXL_graphs"; +static const char __pyx_k_print_to_stdout[] = "print_to_stdout"; +static const char __pyx_k_setstate_cython[] = "__setstate_cython__"; +static const char __pyx_k_InitError___init[] = "InitError.__init__"; +static const char __pyx_k_Number_of_graphs[] = "Number of graphs = "; +static const char __pyx_k_get_init_options[] = "get_init_options"; +static const char __pyx_k_ignore_duplicates[] = "ignore_duplicates"; +static const char __pyx_k_original_node_ids[] = "original_node_ids"; +static const char __pyx_k_MethodError___init[] = "MethodError.__init__"; +static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback"; +static const char __pyx_k_decode_graph_edges[] = "decode_graph_edges"; +static const char __pyx_k_edit_cost_constant[] = "edit_cost_constant"; +static const char __pyx_k_get_method_options[] = "get_method_options"; +static const char __pyx_k_get_graph_num_nodes[] = "get_graph_num_nodes"; +static const char __pyx_k_EditCostError___init[] = "EditCostError.__init__"; +static const char __pyx_k_list_of_init_options[] = "list_of_init_options"; +static const char __pyx_k_get_edit_cost_options[] = "get_edit_cost_options"; +static const char __pyx_k_get_graph_node_labels[] = "get_graph_node_labels"; +static const char __pyx_k_get_original_node_ids[] = "get_original_node_ids"; +static const char __pyx_k_lib_nomad_libnomad_so[] = "/lib/nomad/libnomad.so"; +static const char __pyx_k_list_of_method_options[] = "list_of_method_options"; +static const char __pyx_k_lib_nomad_libsgtelib_so[] = "/lib/nomad/libsgtelib.so"; +static const char __pyx_k_Computation_between_graph[] = "Computation between graph "; +static const char __pyx_k_Initialization_terminated[] = "Initialization terminated !"; +static const char __pyx_k_lib_fann_libdoublefann_so[] = "/lib/fann/libdoublefann.so"; +static const char __pyx_k_lib_libsvm_3_22_libsvm_so[] = "/lib/libsvm.3.22/libsvm.so"; +static const char __pyx_k_list_of_edit_cost_options[] = "list_of_edit_cost_options"; +static const char __pyx_k_Initialization_in_progress[] = "Initialization in progress..."; +static const char __pyx_k_Loading_graphs_in_progress[] = "Loading graphs in progress..."; +static const char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous"; +static const char __pyx_k_EAGER_WITHOUT_SHUFFLED_COPIES[] = "EAGER_WITHOUT_SHUFFLED_COPIES"; +static const char __pyx_k_Class_for_Edit_Cost_Error_Raise[] = "\n\t\tClass for Edit Cost Error. Raise an error if an edit cost function doesn't exist in the library (not in list_of_edit_cost_options).\n\n\t\t:attribute message: The message to print when an error is detected.\n\t\t:type message: string\n\t"; +static const char __pyx_k_Class_for_Init_Error_Raise_an_e[] = "\n\t\tClass for Init Error. Raise an error if an init option doesn't exist in the library (not in list_of_init_options).\n\n\t\t:attribute message: The message to print when an error is detected.\n\t\t:type message: string\n\t"; +static const char __pyx_k_Class_for_Method_Error_Raise_an[] = "\n\t\tClass for Method Error. Raise an error if a computation method doesn't exist in the library (not in list_of_method_options).\n\n\t\t:attribute message: The message to print when an error is detected.\n\t\t:type message: string\n\t"; +static const char __pyx_k_Class_for_error_s_management_Th[] = "\n\t\tClass for error's management. This one is general. \n\t"; +static const char __pyx_k_Finish_The_return_contains_edit[] = "Finish ! The return contains edit distances and NodeMap but you can check the result with graphs'ID until you restart the environment"; +static const char __pyx_k_Finish_You_can_check_the_result[] = "Finish ! You can check the result with each ID of graphs ! There are in the return"; +static const char __pyx_k_Python_GedLib_module_This_modul[] = "\n\tPython GedLib module\n\t======================\n\t\n\tThis module allow to use a C++ library for edit distance between graphs (GedLib) with Python.\n\n\t\n\tAuthors\n\t-------------------\n \n\tDavid Blumenthal\n\tNatacha Lambert\n\tLinlin Jia\n\n\tCopyright (C) 2019-2020 by all the authors\n\n\tClasses & Functions\n\t-------------------\n \n"; +static const char __pyx_k_This_edit_cost_function_doesn_t[] = "This edit cost function doesn't exist, please see list_of_edit_cost_options for selecting a edit cost function"; +static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import"; +static const char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)"; +static const char __pyx_k_with_all_the_others_including_h[] = " with all the others including himself."; +static const char __pyx_k_Format_string_allocated_too_shor[] = "Format string allocated too short, see comment in numpy.pxd"; +static const char __pyx_k_Non_native_byte_order_not_suppor[] = "Non-native byte order not supported"; +static const char __pyx_k_Please_don_t_restart_the_environ[] = "Please don't restart the environment or recall this function, you will lose your results !"; +static const char __pyx_k_This_init_option_doesn_t_exist_p[] = "This init option doesn't exist, please see list_of_init_options for selecting an option. You can choose any options."; +static const char __pyx_k_This_method_doesn_t_exist_please[] = "This method doesn't exist, please see list_of_method_options for selecting a method"; +static const char __pyx_k_ndarray_is_not_Fortran_contiguou[] = "ndarray is not Fortran contiguous"; +static const char __pyx_k_no_default___reduce___due_to_non[] = "no default __reduce__ due to non-trivial __cinit__"; +static const char __pyx_k_numpy_core_umath_failed_to_impor[] = "numpy.core.umath failed to import"; +static const char __pyx_k_Format_string_allocated_too_shor_2[] = "Format string allocated too short."; +static PyObject *__pyx_kp_u_; +static PyObject *__pyx_kp_s_Class_for_Edit_Cost_Error_Raise; +static PyObject *__pyx_kp_s_Class_for_Init_Error_Raise_an_e; +static PyObject *__pyx_kp_s_Class_for_Method_Error_Raise_an; +static PyObject *__pyx_kp_s_Class_for_error_s_management_Th; +static PyObject *__pyx_kp_u_Computation_between_graph; +static PyObject *__pyx_n_u_EAGER_WITHOUT_SHUFFLED_COPIES; +static PyObject *__pyx_n_s_EditCostError; +static PyObject *__pyx_n_s_EditCostError___init; +static PyObject *__pyx_n_s_Error; +static PyObject *__pyx_kp_u_Finish_The_return_contains_edit; +static PyObject *__pyx_kp_u_Finish_You_can_check_the_result; +static PyObject *__pyx_kp_u_Format_string_allocated_too_shor; +static PyObject *__pyx_kp_u_Format_string_allocated_too_shor_2; +static PyObject *__pyx_n_s_GEDEnv; +static PyObject *__pyx_n_s_Graph; +static PyObject *__pyx_kp_u_Graphs_loaded; +static PyObject *__pyx_n_s_ImportError; +static PyObject *__pyx_n_s_InitError; +static PyObject *__pyx_n_s_InitError___init; +static PyObject *__pyx_kp_u_Initialization_in_progress; +static PyObject *__pyx_kp_u_Initialization_terminated; +static PyObject *__pyx_n_s_LoadLibrary; +static PyObject *__pyx_kp_u_Loading_graphs_in_progress; +static PyObject *__pyx_n_s_MemoryError; +static PyObject *__pyx_n_s_MethodError; +static PyObject *__pyx_n_s_MethodError___init; +static PyObject *__pyx_kp_u_Non_native_byte_order_not_suppor; +static PyObject *__pyx_kp_u_Number_of_graphs; +static PyObject *__pyx_kp_u_Please_don_t_restart_the_environ; +static PyObject *__pyx_n_s_RuntimeError; +static PyObject *__pyx_kp_u_This_edit_cost_function_doesn_t; +static PyObject *__pyx_kp_u_This_init_option_doesn_t_exist_p; +static PyObject *__pyx_kp_u_This_method_doesn_t_exist_please; +static PyObject *__pyx_n_s_TypeError; +static PyObject *__pyx_n_s_ValueError; +static PyObject *__pyx_n_s__20; +static PyObject *__pyx_n_s_add_edge; +static PyObject *__pyx_n_s_add_graph; +static PyObject *__pyx_n_s_add_node; +static PyObject *__pyx_n_s_add_nx_graph; +static PyObject *__pyx_n_s_adj_lists; +static PyObject *__pyx_n_s_adj_matrix; +static PyObject *__pyx_n_s_cdll; +static PyObject *__pyx_n_s_classe; +static PyObject *__pyx_n_s_classes; +static PyObject *__pyx_n_s_clear_graph; +static PyObject *__pyx_n_s_cline_in_traceback; +static PyObject *__pyx_n_s_ctypes; +static PyObject *__pyx_n_s_dataset; +static PyObject *__pyx_n_s_decode; +static PyObject *__pyx_n_s_decode_graph_edges; +static PyObject *__pyx_n_s_decode_your_map; +static PyObject *__pyx_n_s_dirname; +static PyObject *__pyx_n_s_doc; +static PyObject *__pyx_n_s_edge_label; +static PyObject *__pyx_n_s_edge_label_1; +static PyObject *__pyx_n_s_edge_label_2; +static PyObject *__pyx_n_s_edge_label_b; +static PyObject *__pyx_n_s_edge_list; +static PyObject *__pyx_n_s_edge_type; +static PyObject *__pyx_n_s_edges; +static PyObject *__pyx_n_s_edit_cost; +static PyObject *__pyx_n_s_edit_cost_constant; +static PyObject *__pyx_n_s_encode; +static PyObject *__pyx_n_s_encode_your_map; +static PyObject *__pyx_n_s_file; +static PyObject *__pyx_n_s_g; +static PyObject *__pyx_n_s_g1; +static PyObject *__pyx_n_s_g2; +static PyObject *__pyx_n_s_g_id; +static PyObject *__pyx_n_s_gedlibpy; +static PyObject *__pyx_kp_s_gedlibpy_pyx; +static PyObject *__pyx_n_s_get_dummy_node; +static PyObject *__pyx_n_s_get_edge_data; +static PyObject *__pyx_n_s_get_edit_cost_options; +static PyObject *__pyx_n_s_get_graph_edges; +static PyObject *__pyx_n_s_get_graph_node_labels; +static PyObject *__pyx_n_s_get_graph_num_nodes; +static PyObject *__pyx_n_s_get_init_options; +static PyObject *__pyx_n_s_get_method_options; +static PyObject *__pyx_n_s_get_node_map; +static PyObject *__pyx_n_s_get_original_node_ids; +static PyObject *__pyx_n_s_get_upper_bound; +static PyObject *__pyx_n_s_getstate; +static PyObject *__pyx_n_s_graph; +static PyObject *__pyx_n_s_graph_class; +static PyObject *__pyx_n_s_graph_id; +static PyObject *__pyx_n_s_graph_ids; +static PyObject *__pyx_n_s_graph_name; +static PyObject *__pyx_n_s_h; +static PyObject *__pyx_n_s_h_id; +static PyObject *__pyx_n_s_head; +static PyObject *__pyx_n_u_id; +static PyObject *__pyx_n_s_ignore_duplicates; +static PyObject *__pyx_n_s_import; +static PyObject *__pyx_n_s_init; +static PyObject *__pyx_n_s_init_2; +static PyObject *__pyx_n_s_init_method; +static PyObject *__pyx_n_s_init_option; +static PyObject *__pyx_n_s_is_initialized; +static PyObject *__pyx_n_s_items; +static PyObject *__pyx_n_s_iteritems; +static PyObject *__pyx_n_s_key; +static PyObject *__pyx_n_s_lib1; +static PyObject *__pyx_n_s_lib2; +static PyObject *__pyx_n_s_lib3; +static PyObject *__pyx_n_s_lib4; +static PyObject *__pyx_kp_u_lib_fann_libdoublefann_so; +static PyObject *__pyx_kp_u_lib_libsvm_3_22_libsvm_so; +static PyObject *__pyx_kp_u_lib_nomad_libnomad_so; +static PyObject *__pyx_kp_u_lib_nomad_libsgtelib_so; +static PyObject *__pyx_n_s_list_of_edges; +static PyObject *__pyx_n_s_list_of_edit_cost_options; +static PyObject *__pyx_n_s_list_of_init_options; +static PyObject *__pyx_n_s_list_of_method_options; +static PyObject *__pyx_n_s_list_of_nodes; +static PyObject *__pyx_n_s_load_GXL_graphs; +static PyObject *__pyx_n_s_main; +static PyObject *__pyx_n_s_map_b; +static PyObject *__pyx_n_s_map_edge_b; +static PyObject *__pyx_n_s_map_edges; +static PyObject *__pyx_n_s_map_u; +static PyObject *__pyx_n_s_message; +static PyObject *__pyx_n_s_metaclass; +static PyObject *__pyx_n_s_method; +static PyObject *__pyx_n_s_module; +static PyObject *__pyx_n_s_name; +static PyObject *__pyx_n_s_name_2; +static PyObject *__pyx_kp_u_ndarray_is_not_C_contiguous; +static PyObject *__pyx_kp_u_ndarray_is_not_Fortran_contiguou; +static PyObject *__pyx_n_s_networkx; +static PyObject *__pyx_kp_s_no_default___reduce___due_to_non; +static PyObject *__pyx_n_s_node_id; +static PyObject *__pyx_n_s_node_label; +static PyObject *__pyx_n_s_node_label_1; +static PyObject *__pyx_n_s_node_label_2; +static PyObject *__pyx_n_s_node_type; +static PyObject *__pyx_n_s_nodes; +static PyObject *__pyx_kp_u_numpy_core_multiarray_failed_to; +static PyObject *__pyx_kp_u_numpy_core_umath_failed_to_impor; +static PyObject *__pyx_n_s_nx; +static PyObject *__pyx_n_s_nx_graph; +static PyObject *__pyx_n_s_option; +static PyObject *__pyx_n_s_options; +static PyObject *__pyx_n_u_original_node_ids; +static PyObject *__pyx_n_s_os; +static PyObject *__pyx_n_s_path; +static PyObject *__pyx_n_s_path_XML; +static PyObject *__pyx_n_s_path_folder; +static PyObject *__pyx_n_s_prepare; +static PyObject *__pyx_n_s_print; +static PyObject *__pyx_n_s_print_to_stdout; +static PyObject *__pyx_n_s_qualname; +static PyObject *__pyx_n_s_range; +static PyObject *__pyx_n_s_realpath; +static PyObject *__pyx_n_s_reduce; +static PyObject *__pyx_n_s_reduce_cython; +static PyObject *__pyx_n_s_reduce_ex; +static PyObject *__pyx_n_s_res; +static PyObject *__pyx_n_s_restart_env; +static PyObject *__pyx_n_s_run_method; +static PyObject *__pyx_n_s_self; +static PyObject *__pyx_n_s_set_edit_cost; +static PyObject *__pyx_n_s_set_method; +static PyObject *__pyx_n_s_setstate; +static PyObject *__pyx_n_s_setstate_cython; +static PyObject *__pyx_n_s_tail; +static PyObject *__pyx_n_s_test; +static PyObject *__pyx_kp_u_unknown_dtype_code_in_numpy_pxd; +static PyObject *__pyx_kp_u_utf_8; +static PyObject *__pyx_n_s_value; +static PyObject *__pyx_kp_u_with_all_the_others_including_h; +static PyObject *__pyx_pf_8gedlibpy_get_edit_cost_options(CYTHON_UNUSED PyObject *__pyx_self); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_2get_method_options(CYTHON_UNUSED PyObject *__pyx_self); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_4get_init_options(CYTHON_UNUSED PyObject *__pyx_self); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6get_dummy_node(CYTHON_UNUSED PyObject *__pyx_self); /* proto */ +static int __pyx_pf_8gedlibpy_6GEDEnv___cinit__(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self); /* proto */ +static void __pyx_pf_8gedlibpy_6GEDEnv_2__dealloc__(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_4is_initialized(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_6restart_env(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_8load_GXL_graphs(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_path_folder, PyObject *__pyx_v_path_XML, PyObject *__pyx_v_node_type, PyObject *__pyx_v_edge_type); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_10graph_ids(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_12get_all_graph_ids(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_14get_graph_class(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_id); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_16get_graph_name(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_id); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_18add_graph(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_name, PyObject *__pyx_v_classe); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_20add_node(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_graph_id, PyObject *__pyx_v_node_id, PyObject *__pyx_v_node_label); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_22add_edge(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_graph_id, PyObject *__pyx_v_tail, PyObject *__pyx_v_head, PyObject *__pyx_v_edge_label, PyObject *__pyx_v_ignore_duplicates); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_24add_symmetrical_edge(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_graph_id, PyObject *__pyx_v_tail, PyObject *__pyx_v_head, PyObject *__pyx_v_edge_label); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_26clear_graph(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_graph_id); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_28get_graph_internal_id(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_graph_id); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_30get_graph_num_nodes(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_graph_id); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_32get_graph_num_edges(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_graph_id); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_34get_original_node_ids(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_graph_id); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_36get_graph_node_labels(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_graph_id); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_38get_graph_edges(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_graph_id); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_40get_graph_adjacence_matrix(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_graph_id); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_42set_edit_cost(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_edit_cost, PyObject *__pyx_v_edit_cost_constant); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_44set_personal_edit_cost(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_edit_cost_constant); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_46init(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_init_option, PyObject *__pyx_v_print_to_stdout); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_48set_method(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_method, PyObject *__pyx_v_options); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_50init_method(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_52get_init_time(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_54run_method(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_g, PyObject *__pyx_v_h); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_56get_upper_bound(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_g, PyObject *__pyx_v_h); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_58get_lower_bound(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_g, PyObject *__pyx_v_h); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_60get_forward_map(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_g, PyObject *__pyx_v_h); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_62get_backward_map(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_g, PyObject *__pyx_v_h); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_64get_node_image(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_g, PyObject *__pyx_v_h, PyObject *__pyx_v_node_id); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_66get_node_pre_image(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_g, PyObject *__pyx_v_h, PyObject *__pyx_v_node_id); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_68get_induced_cost(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_g, PyObject *__pyx_v_h); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_70get_node_map(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_g, PyObject *__pyx_v_h); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_72get_assignment_matrix(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_g, PyObject *__pyx_v_h); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_74get_all_map(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_g, PyObject *__pyx_v_h); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_76get_runtime(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_g, PyObject *__pyx_v_h); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_78quasimetric_cost(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_80hungarian_LSAP(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_matrix_cost); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_82hungarian_LSAPE(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_matrix_cost); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_84add_random_graph(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_name, PyObject *__pyx_v_classe, PyObject *__pyx_v_list_of_nodes, PyObject *__pyx_v_list_of_edges, PyObject *__pyx_v_ignore_duplicates); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_86add_nx_graph(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_g, PyObject *__pyx_v_classe, PyObject *__pyx_v_ignore_duplicates); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_88compute_ged_on_two_graphs(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_g1, PyObject *__pyx_v_g2, PyObject *__pyx_v_edit_cost, PyObject *__pyx_v_method, PyObject *__pyx_v_options, PyObject *__pyx_v_init_option); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_90compute_edit_distance_on_nx_graphs(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_dataset, PyObject *__pyx_v_classes, PyObject *__pyx_v_edit_cost, PyObject *__pyx_v_method, PyObject *__pyx_v_options, PyObject *__pyx_v_init_option); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_92compute_edit_distance_on_GXl_graphs(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_path_folder, PyObject *__pyx_v_path_XML, PyObject *__pyx_v_edit_cost, PyObject *__pyx_v_method, PyObject *__pyx_v_options, PyObject *__pyx_v_init_option); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_94get_num_node_labels(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_96get_node_label(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_label_id); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_98get_num_edge_labels(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_100get_edge_label(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_label_id); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_102get_avg_num_nodes(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_104get_node_rel_cost(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_node_label_1, PyObject *__pyx_v_node_label_2); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_106get_node_del_cost(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_node_label); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_108get_node_ins_cost(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_node_label); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_110get_median_node_label(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_node_labels); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_112get_edge_rel_cost(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_edge_label_1, PyObject *__pyx_v_edge_label_2); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_114get_edge_del_cost(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_edge_label); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_116get_edge_ins_cost(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_edge_label); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_118get_median_edge_label(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_edge_labels); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_120get_nx_graph(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_graph_id, CYTHON_UNUSED PyObject *__pyx_v_adj_matrix, CYTHON_UNUSED PyObject *__pyx_v_adj_lists, CYTHON_UNUSED PyObject *__pyx_v_edge_list); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_122get_init_type(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_124load_nx_graph(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_nx_graph, PyObject *__pyx_v_graph_id, PyObject *__pyx_v_graph_name, PyObject *__pyx_v_graph_class); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_126compute_induced_cost(struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, PyObject *__pyx_v_g_id, PyObject *__pyx_v_h_id); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_128__reduce_cython__(CYTHON_UNUSED struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_6GEDEnv_130__setstate_cython__(CYTHON_UNUSED struct __pyx_obj_8gedlibpy_GEDEnv *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_13EditCostError___init__(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self, PyObject *__pyx_v_message); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_11MethodError___init__(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self, PyObject *__pyx_v_message); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_9InitError___init__(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self, PyObject *__pyx_v_message); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_8encode_your_map(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_map_u); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_10decode_your_map(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_map_b); /* proto */ +static PyObject *__pyx_pf_8gedlibpy_12decode_graph_edges(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_map_edge_b); /* proto */ +static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ +static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */ +static int __pyx_pf_7cpython_5array_5array___getbuffer__(arrayobject *__pyx_v_self, Py_buffer *__pyx_v_info, CYTHON_UNUSED int __pyx_v_flags); /* proto */ +static void __pyx_pf_7cpython_5array_5array_2__releasebuffer__(CYTHON_UNUSED arrayobject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */ +static PyObject *__pyx_tp_new_8gedlibpy_GEDEnv(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ +static PyObject *__pyx_int_0; +static PyObject *__pyx_k__2; +static PyObject *__pyx_k__3; +static PyObject *__pyx_tuple__4; +static PyObject *__pyx_tuple__5; +static PyObject *__pyx_tuple__6; +static PyObject *__pyx_tuple__7; +static PyObject *__pyx_tuple__8; +static PyObject *__pyx_tuple__9; +static PyObject *__pyx_tuple__10; +static PyObject *__pyx_tuple__11; +static PyObject *__pyx_tuple__12; +static PyObject *__pyx_tuple__13; +static PyObject *__pyx_tuple__14; +static PyObject *__pyx_tuple__15; +static PyObject *__pyx_tuple__16; +static PyObject *__pyx_tuple__17; +static PyObject *__pyx_tuple__18; +static PyObject *__pyx_tuple__19; +static PyObject *__pyx_tuple__21; +static PyObject *__pyx_tuple__23; +static PyObject *__pyx_tuple__25; 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Please use directly list_of_edit_cost_options. \n\t\t.. note:: Prefer the list_of_edit_cost_options attribute of this module.\n\t"; +static PyMethodDef __pyx_mdef_8gedlibpy_1get_edit_cost_options = {"get_edit_cost_options", (PyCFunction)__pyx_pw_8gedlibpy_1get_edit_cost_options, METH_NOARGS, __pyx_doc_8gedlibpy_get_edit_cost_options}; +static PyObject *__pyx_pw_8gedlibpy_1get_edit_cost_options(PyObject *__pyx_self, CYTHON_UNUSED PyObject *unused) { + PyObject *__pyx_r = 0; + __Pyx_RefNannyDeclarations + __Pyx_RefNannySetupContext("get_edit_cost_options (wrapper)", 0); + __pyx_r = __pyx_pf_8gedlibpy_get_edit_cost_options(__pyx_self); + + /* function exit code */ + __Pyx_RefNannyFinishContext(); + return __pyx_r; +} + +static PyObject *__pyx_pf_8gedlibpy_get_edit_cost_options(CYTHON_UNUSED PyObject *__pyx_self) { + std::string __pyx_7genexpr__pyx_v_option; + PyObject *__pyx_r = NULL; + __Pyx_RefNannyDeclarations + PyObject *__pyx_t_1 = NULL; + std::vector __pyx_t_2; + std::vector ::iterator __pyx_t_3; + std::vector *__pyx_t_4; + std::string __pyx_t_5; + PyObject *__pyx_t_6 = NULL; + __Pyx_RefNannySetupContext("get_edit_cost_options", 0); + + /* "gedlibpy.pyx":137 + * """ + * + * return [option.decode('utf-8') for option in getEditCostStringOptions()] # <<<<<<<<<<<<<< + * + * + */ + __Pyx_XDECREF(__pyx_r); + { /* enter inner scope */ + __pyx_t_1 = PyList_New(0); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 137, __pyx_L1_error) + __Pyx_GOTREF(__pyx_t_1); + try { + __pyx_t_2 = pyged::getEditCostStringOptions(); + } catch(...) { + __Pyx_CppExn2PyErr(); + __PYX_ERR(0, 137, __pyx_L1_error) + } + __pyx_t_4 = &__pyx_t_2; + __pyx_t_3 = __pyx_t_4->begin(); + for (;;) { + if (!(__pyx_t_3 != __pyx_t_4->end())) break; + __pyx_t_5 = *__pyx_t_3; + ++__pyx_t_3; + __pyx_7genexpr__pyx_v_option = __pyx_t_5; + __pyx_t_6 = __Pyx_decode_cpp_string(__pyx_7genexpr__pyx_v_option, 0, PY_SSIZE_T_MAX, NULL, NULL, PyUnicode_DecodeUTF8); if (unlikely(!__pyx_t_6)) __PYX_ERR(0, 137, __pyx_L1_error) + __Pyx_GOTREF(__pyx_t_6); + if (unlikely(__Pyx_ListComp_Append(__pyx_t_1, (PyObject*)__pyx_t_6))) __PYX_ERR(0, 137, __pyx_L1_error) + __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0; + } + } /* exit inner scope */ + __pyx_r = __pyx_t_1; + __pyx_t_1 = 0; + goto __pyx_L0; + + /* "gedlibpy.pyx":126 + * + * + * def get_edit_cost_options() : # <<<<<<<<<<<<<< + * """ + * Searchs the differents edit cost functions and returns the result. + */ + + /* function exit code */ + __pyx_L1_error:; + __Pyx_XDECREF(__pyx_t_1); + __Pyx_XDECREF(__pyx_t_6); + __Pyx_AddTraceback("gedlibpy.get_edit_cost_options", __pyx_clineno, __pyx_lineno, __pyx_filename); + __pyx_r = NULL; + __pyx_L0:; + __Pyx_XGIVEREF(__pyx_r); + __Pyx_RefNannyFinishContext(); + return __pyx_r; +} + +/* "gedlibpy.pyx":140 + * + * + * def get_method_options() : # <<<<<<<<<<<<<< + * """ + * Searchs the differents method for edit distance computation between graphs and returns the result. + */ + +/* Python wrapper */ +static PyObject *__pyx_pw_8gedlibpy_3get_method_options(PyObject *__pyx_self, CYTHON_UNUSED PyObject *unused); /*proto*/ +static char __pyx_doc_8gedlibpy_2get_method_options[] = "\n\t\tSearchs the differents method for edit distance computation between graphs and returns the result.\n \n\t\t:return: The list of method to compute the edit distance between graphs\n\t\t:rtype: list[string]\n \n\t\t.. warning:: This function is useless for an external use. 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__pyx_filename); + __Pyx_pretend_to_initialize(&__pyx_r); + __pyx_L0:; + __Pyx_XDECREF(__pyx_v_item); + __Pyx_RefNannyFinishContext(); + return __pyx_r; +} + +static PyObject *__pyx_tp_new_8gedlibpy_GEDEnv(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { + PyObject *o; + if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { + o = (*t->tp_alloc)(t, 0); + } else { + o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); + } + if (unlikely(!o)) return 0; + if (unlikely(__pyx_pw_8gedlibpy_6GEDEnv_1__cinit__(o, __pyx_empty_tuple, NULL) < 0)) goto bad; + return o; + bad: + Py_DECREF(o); o = 0; + return NULL; +} + +static void __pyx_tp_dealloc_8gedlibpy_GEDEnv(PyObject *o) { + #if CYTHON_USE_TP_FINALIZE + if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && (!PyType_IS_GC(Py_TYPE(o)) || !_PyGC_FINALIZED(o))) { + if (PyObject_CallFinalizerFromDealloc(o)) return; + } + #endif + { + PyObject *etype, *eval, 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(PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_15get_graph_class, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_14get_graph_class}, + {"get_graph_name", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_17get_graph_name, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_16get_graph_name}, + {"add_graph", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_19add_graph, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_18add_graph}, + {"add_node", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_21add_node, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_20add_node}, + {"add_edge", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_23add_edge, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_22add_edge}, + {"add_symmetrical_edge", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_25add_symmetrical_edge, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_24add_symmetrical_edge}, + {"clear_graph", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_27clear_graph, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_26clear_graph}, + {"get_graph_internal_id", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_29get_graph_internal_id, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_28get_graph_internal_id}, + {"get_graph_num_nodes", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_31get_graph_num_nodes, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_30get_graph_num_nodes}, + {"get_graph_num_edges", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_33get_graph_num_edges, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_32get_graph_num_edges}, + {"get_original_node_ids", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_35get_original_node_ids, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_34get_original_node_ids}, + {"get_graph_node_labels", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_37get_graph_node_labels, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_36get_graph_node_labels}, + {"get_graph_edges", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_39get_graph_edges, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_38get_graph_edges}, + {"get_graph_adjacence_matrix", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_41get_graph_adjacence_matrix, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_40get_graph_adjacence_matrix}, + {"set_edit_cost", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_43set_edit_cost, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_42set_edit_cost}, + {"set_personal_edit_cost", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_45set_personal_edit_cost, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_44set_personal_edit_cost}, + {"init", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_47init, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_46init}, + {"set_method", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_49set_method, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_48set_method}, + {"init_method", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_51init_method, METH_NOARGS, __pyx_doc_8gedlibpy_6GEDEnv_50init_method}, + {"get_init_time", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_53get_init_time, METH_NOARGS, __pyx_doc_8gedlibpy_6GEDEnv_52get_init_time}, + {"run_method", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_55run_method, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_54run_method}, + {"get_upper_bound", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_57get_upper_bound, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_56get_upper_bound}, + {"get_lower_bound", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_59get_lower_bound, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_58get_lower_bound}, + {"get_forward_map", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_61get_forward_map, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_60get_forward_map}, + {"get_backward_map", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_63get_backward_map, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_62get_backward_map}, + {"get_node_image", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_65get_node_image, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_64get_node_image}, + {"get_node_pre_image", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_67get_node_pre_image, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_66get_node_pre_image}, + {"get_induced_cost", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_69get_induced_cost, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_68get_induced_cost}, + {"get_node_map", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_71get_node_map, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_70get_node_map}, + {"get_assignment_matrix", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_73get_assignment_matrix, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_72get_assignment_matrix}, + {"get_all_map", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_75get_all_map, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_74get_all_map}, + {"get_runtime", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_77get_runtime, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_76get_runtime}, + {"quasimetric_cost", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_79quasimetric_cost, METH_NOARGS, __pyx_doc_8gedlibpy_6GEDEnv_78quasimetric_cost}, + {"hungarian_LSAP", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_81hungarian_LSAP, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_80hungarian_LSAP}, + {"hungarian_LSAPE", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_83hungarian_LSAPE, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_82hungarian_LSAPE}, + {"add_random_graph", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_85add_random_graph, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_84add_random_graph}, + {"add_nx_graph", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_87add_nx_graph, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_86add_nx_graph}, + {"compute_ged_on_two_graphs", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_89compute_ged_on_two_graphs, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_88compute_ged_on_two_graphs}, + {"compute_edit_distance_on_nx_graphs", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_91compute_edit_distance_on_nx_graphs, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_90compute_edit_distance_on_nx_graphs}, + {"compute_edit_distance_on_GXl_graphs", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_93compute_edit_distance_on_GXl_graphs, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_92compute_edit_distance_on_GXl_graphs}, + {"get_num_node_labels", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_95get_num_node_labels, METH_NOARGS, __pyx_doc_8gedlibpy_6GEDEnv_94get_num_node_labels}, + {"get_node_label", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_97get_node_label, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_96get_node_label}, + {"get_num_edge_labels", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_99get_num_edge_labels, METH_NOARGS, __pyx_doc_8gedlibpy_6GEDEnv_98get_num_edge_labels}, + {"get_edge_label", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_101get_edge_label, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_100get_edge_label}, + {"get_avg_num_nodes", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_103get_avg_num_nodes, METH_NOARGS, __pyx_doc_8gedlibpy_6GEDEnv_102get_avg_num_nodes}, + {"get_node_rel_cost", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_105get_node_rel_cost, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_104get_node_rel_cost}, + {"get_node_del_cost", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_107get_node_del_cost, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_106get_node_del_cost}, + {"get_node_ins_cost", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_109get_node_ins_cost, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_108get_node_ins_cost}, + {"get_median_node_label", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_111get_median_node_label, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_110get_median_node_label}, + {"get_edge_rel_cost", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_113get_edge_rel_cost, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_112get_edge_rel_cost}, + {"get_edge_del_cost", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_115get_edge_del_cost, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_114get_edge_del_cost}, + {"get_edge_ins_cost", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_117get_edge_ins_cost, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_116get_edge_ins_cost}, + {"get_median_edge_label", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_119get_median_edge_label, METH_O, __pyx_doc_8gedlibpy_6GEDEnv_118get_median_edge_label}, + {"get_nx_graph", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_121get_nx_graph, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_120get_nx_graph}, + {"get_init_type", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_123get_init_type, METH_NOARGS, __pyx_doc_8gedlibpy_6GEDEnv_122get_init_type}, + {"load_nx_graph", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_125load_nx_graph, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_124load_nx_graph}, + {"compute_induced_cost", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_8gedlibpy_6GEDEnv_127compute_induced_cost, METH_VARARGS|METH_KEYWORDS, __pyx_doc_8gedlibpy_6GEDEnv_126compute_induced_cost}, + {"__reduce_cython__", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_129__reduce_cython__, METH_NOARGS, 0}, + {"__setstate_cython__", (PyCFunction)__pyx_pw_8gedlibpy_6GEDEnv_131__setstate_cython__, METH_O, 0}, + {0, 0, 0, 0} +}; + +static PyTypeObject __pyx_type_8gedlibpy_GEDEnv = { + PyVarObject_HEAD_INIT(0, 0) + "gedlibpy.GEDEnv", /*tp_name*/ + sizeof(struct __pyx_obj_8gedlibpy_GEDEnv), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_8gedlibpy_GEDEnv, /*tp_dealloc*/ + #if PY_VERSION_HEX < 0x030800b4 + 0, /*tp_print*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 + 0, /*tp_vectorcall_offset*/ + #endif + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + #if PY_MAJOR_VERSION < 3 + 0, /*tp_compare*/ + #endif + #if PY_MAJOR_VERSION >= 3 + 0, /*tp_as_async*/ + #endif + 0, /*tp_repr*/ + 0, /*tp_as_number*/ + 0, /*tp_as_sequence*/ + 0, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + 0, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ + "Cython wrapper class for C++ class PyGEDEnv\n\t", /*tp_doc*/ + 0, /*tp_traverse*/ + 0, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_8gedlibpy_GEDEnv, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + 0, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_8gedlibpy_GEDEnv, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ + 0, /*tp_del*/ + 0, /*tp_version_tag*/ + #if PY_VERSION_HEX >= 0x030400a1 + 0, /*tp_finalize*/ + #endif + #if PY_VERSION_HEX >= 0x030800b1 + 0, /*tp_vectorcall*/ + #endif + #if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, /*tp_print*/ + #endif +}; + +static PyMethodDef __pyx_methods[] = { + {0, 0, 0, 0} +}; + +static int __pyx_import_star_set(PyObject *o, PyObject* py_name, char *name) { + static const char* internal_type_names[] = { + "GEDEnv", + "PyGEDEnv", + "UINT32_t", + "X", + "Y", + "__pyx_ctuple_dbc1b__c5621__std__in_map__lAngstd__in_pair__lAngsize_t__comma_size_t__rAng__comma_std__in_map__lAngstd__in_string__comma_std__in_string__rAng__rAng__etc__etc", + "__pyx_ctuple_dbc1b__c5621__std__in_map__lAngstd__in_pair__lAngsize_t__comma_size_t__rAng__comma_std__in_map__lAngstd__in_string__comma_std__in_string__rAng__rAng__etc__etc_struct", + "__pyx_ctuple_size_t", + "__pyx_ctuple_size_t__space___const___and_size_t__space___const_", + "__pyx_ctuple_size_t__space___const___and_size_t__space___const__struct", + "__pyx_ctuple_size_t_struct", + "__pyx_ctuple_std__in_map__lAngstd__in_string__comma_std__in_string__rAng", + "__pyx_ctuple_std__in_map__lAngstd__in_string__comma_std__in_string__rAng_struct", + "bool", + "list", + "map", + "pair", + "string", + "vector", + 0 + }; + const char** type_name = internal_type_names; + while (*type_name) { + if (__Pyx_StrEq(name, *type_name)) { + PyErr_Format(PyExc_TypeError, "Cannot overwrite C type %s", name); + goto bad; + } + type_name++; + } + if (0); + else { + if (PyObject_SetAttr(__pyx_m, py_name, o) < 0) goto bad; + } + return 0; + bad: + return -1; +} + +static int +__Pyx_import_all_from(PyObject *locals, PyObject *v) +{ + PyObject *all = PyObject_GetAttrString(v, "__all__"); + PyObject *dict, *name, *value; + int skip_leading_underscores = 0; + int pos, err; + if (all == NULL) { + if (!PyErr_ExceptionMatches(PyExc_AttributeError)) + return -1; + PyErr_Clear(); + dict = PyObject_GetAttrString(v, "__dict__"); + if (dict == NULL) { + if (!PyErr_ExceptionMatches(PyExc_AttributeError)) + return -1; + PyErr_SetString(PyExc_ImportError, + "from-import-* object has no __dict__ and no __all__"); + return -1; + } +#if PY_MAJOR_VERSION < 3 + all = PyObject_CallMethod(dict, (char *)"keys", NULL); +#else + all = PyMapping_Keys(dict); +#endif + Py_DECREF(dict); + if (all == NULL) + return -1; + skip_leading_underscores = 1; + } + for (pos = 0, err = 0; ; pos++) { + name = PySequence_GetItem(all, pos); + if (name == NULL) { + if (!PyErr_ExceptionMatches(PyExc_IndexError)) + err = -1; + else + PyErr_Clear(); + break; + } + if (skip_leading_underscores && +#if PY_MAJOR_VERSION < 3 + PyString_Check(name) && + PyString_AS_STRING(name)[0] == '_') +#else + PyUnicode_Check(name) && + PyUnicode_AS_UNICODE(name)[0] == '_') +#endif + { + Py_DECREF(name); + continue; + } + value = PyObject_GetAttr(v, name); + if (value == NULL) + err = -1; + else if (PyDict_CheckExact(locals)) + err = PyDict_SetItem(locals, name, value); + else + err = PyObject_SetItem(locals, name, value); + Py_DECREF(name); + Py_XDECREF(value); + if (err != 0) + break; + } + Py_DECREF(all); + return err; +} +static int __pyx_import_star(PyObject* m) { + int i; + int ret = -1; + char* s; + PyObject *locals = 0; + PyObject *list = 0; +#if PY_MAJOR_VERSION >= 3 + PyObject *utf8_name = 0; +#endif + PyObject *name; + PyObject *item; + locals = PyDict_New(); if (!locals) goto bad; + if (__Pyx_import_all_from(locals, m) < 0) goto bad; + list = PyDict_Items(locals); if (!list) goto bad; + for(i=0; i= 3 + utf8_name = PyUnicode_AsUTF8String(name); + if (!utf8_name) goto bad; + s = PyBytes_AS_STRING(utf8_name); + if (__pyx_import_star_set(item, name, s) < 0) goto bad; + Py_DECREF(utf8_name); utf8_name = 0; +#else + s = PyString_AsString(name); + if (!s) goto bad; + if (__pyx_import_star_set(item, name, s) < 0) goto bad; +#endif + } + ret = 0; +bad: + Py_XDECREF(locals); + Py_XDECREF(list); +#if PY_MAJOR_VERSION >= 3 + Py_XDECREF(utf8_name); +#endif + return ret; +} + + + +#if PY_MAJOR_VERSION >= 3 +#if CYTHON_PEP489_MULTI_PHASE_INIT +static PyObject* __pyx_pymod_create(PyObject *spec, PyModuleDef *def); /*proto*/ +static int __pyx_pymod_exec_gedlibpy(PyObject* module); /*proto*/ +static PyModuleDef_Slot __pyx_moduledef_slots[] = { + {Py_mod_create, (void*)__pyx_pymod_create}, + {Py_mod_exec, (void*)__pyx_pymod_exec_gedlibpy}, + {0, NULL} +}; +#endif + +static struct PyModuleDef __pyx_moduledef = { + PyModuleDef_HEAD_INIT, + "gedlibpy", + __pyx_k_Python_GedLib_module_This_modul, /* m_doc */ + #if CYTHON_PEP489_MULTI_PHASE_INIT + 0, /* m_size */ + #else + -1, /* m_size */ + #endif + __pyx_methods /* m_methods */, + #if CYTHON_PEP489_MULTI_PHASE_INIT + __pyx_moduledef_slots, /* m_slots */ + #else + NULL, /* m_reload */ + #endif + NULL, /* m_traverse */ + NULL, /* m_clear */ + NULL /* m_free */ +}; +#endif +#ifndef CYTHON_SMALL_CODE +#if defined(__clang__) + #define CYTHON_SMALL_CODE +#elif defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 3)) + #define CYTHON_SMALL_CODE __attribute__((cold)) +#else + #define CYTHON_SMALL_CODE +#endif +#endif + +static __Pyx_StringTabEntry __pyx_string_tab[] = { + {&__pyx_kp_u_, __pyx_k_, sizeof(__pyx_k_), 0, 1, 0, 0}, + {&__pyx_kp_s_Class_for_Edit_Cost_Error_Raise, __pyx_k_Class_for_Edit_Cost_Error_Raise, sizeof(__pyx_k_Class_for_Edit_Cost_Error_Raise), 0, 0, 1, 0}, + {&__pyx_kp_s_Class_for_Init_Error_Raise_an_e, __pyx_k_Class_for_Init_Error_Raise_an_e, sizeof(__pyx_k_Class_for_Init_Error_Raise_an_e), 0, 0, 1, 0}, + {&__pyx_kp_s_Class_for_Method_Error_Raise_an, __pyx_k_Class_for_Method_Error_Raise_an, sizeof(__pyx_k_Class_for_Method_Error_Raise_an), 0, 0, 1, 0}, + {&__pyx_kp_s_Class_for_error_s_management_Th, __pyx_k_Class_for_error_s_management_Th, sizeof(__pyx_k_Class_for_error_s_management_Th), 0, 0, 1, 0}, + {&__pyx_kp_u_Computation_between_graph, __pyx_k_Computation_between_graph, sizeof(__pyx_k_Computation_between_graph), 0, 1, 0, 0}, + {&__pyx_n_u_EAGER_WITHOUT_SHUFFLED_COPIES, __pyx_k_EAGER_WITHOUT_SHUFFLED_COPIES, sizeof(__pyx_k_EAGER_WITHOUT_SHUFFLED_COPIES), 0, 1, 0, 1}, + {&__pyx_n_s_EditCostError, __pyx_k_EditCostError, sizeof(__pyx_k_EditCostError), 0, 0, 1, 1}, + {&__pyx_n_s_EditCostError___init, __pyx_k_EditCostError___init, sizeof(__pyx_k_EditCostError___init), 0, 0, 1, 1}, + {&__pyx_n_s_Error, __pyx_k_Error, sizeof(__pyx_k_Error), 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__pyx_k_InitError, sizeof(__pyx_k_InitError), 0, 0, 1, 1}, + {&__pyx_n_s_InitError___init, __pyx_k_InitError___init, sizeof(__pyx_k_InitError___init), 0, 0, 1, 1}, + {&__pyx_kp_u_Initialization_in_progress, __pyx_k_Initialization_in_progress, sizeof(__pyx_k_Initialization_in_progress), 0, 1, 0, 0}, + {&__pyx_kp_u_Initialization_terminated, __pyx_k_Initialization_terminated, sizeof(__pyx_k_Initialization_terminated), 0, 1, 0, 0}, + {&__pyx_n_s_LoadLibrary, __pyx_k_LoadLibrary, sizeof(__pyx_k_LoadLibrary), 0, 0, 1, 1}, + {&__pyx_kp_u_Loading_graphs_in_progress, __pyx_k_Loading_graphs_in_progress, sizeof(__pyx_k_Loading_graphs_in_progress), 0, 1, 0, 0}, + {&__pyx_n_s_MemoryError, __pyx_k_MemoryError, sizeof(__pyx_k_MemoryError), 0, 0, 1, 1}, + {&__pyx_n_s_MethodError, __pyx_k_MethodError, sizeof(__pyx_k_MethodError), 0, 0, 1, 1}, + {&__pyx_n_s_MethodError___init, __pyx_k_MethodError___init, sizeof(__pyx_k_MethodError___init), 0, 0, 1, 1}, + {&__pyx_kp_u_Non_native_byte_order_not_suppor, 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{&__pyx_n_s_cline_in_traceback, __pyx_k_cline_in_traceback, sizeof(__pyx_k_cline_in_traceback), 0, 0, 1, 1}, + {&__pyx_n_s_ctypes, __pyx_k_ctypes, sizeof(__pyx_k_ctypes), 0, 0, 1, 1}, + {&__pyx_n_s_dataset, __pyx_k_dataset, sizeof(__pyx_k_dataset), 0, 0, 1, 1}, + {&__pyx_n_s_decode, __pyx_k_decode, sizeof(__pyx_k_decode), 0, 0, 1, 1}, + {&__pyx_n_s_decode_graph_edges, __pyx_k_decode_graph_edges, sizeof(__pyx_k_decode_graph_edges), 0, 0, 1, 1}, + {&__pyx_n_s_decode_your_map, __pyx_k_decode_your_map, sizeof(__pyx_k_decode_your_map), 0, 0, 1, 1}, + {&__pyx_n_s_dirname, __pyx_k_dirname, sizeof(__pyx_k_dirname), 0, 0, 1, 1}, + {&__pyx_n_s_doc, __pyx_k_doc, sizeof(__pyx_k_doc), 0, 0, 1, 1}, + {&__pyx_n_s_edge_label, __pyx_k_edge_label, sizeof(__pyx_k_edge_label), 0, 0, 1, 1}, + {&__pyx_n_s_edge_label_1, __pyx_k_edge_label_1, sizeof(__pyx_k_edge_label_1), 0, 0, 1, 1}, + {&__pyx_n_s_edge_label_2, __pyx_k_edge_label_2, sizeof(__pyx_k_edge_label_2), 0, 0, 1, 1}, + {&__pyx_n_s_edge_label_b, 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0 : -1; + #elif PY_MAJOR_VERSION >= 3 + return __pyx_m; + #else + return; + #endif +} + +/* --- Runtime support code --- */ +/* Refnanny */ +#if CYTHON_REFNANNY +static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname) { + PyObject *m = NULL, *p = NULL; + void *r = NULL; + m = PyImport_ImportModule(modname); + if (!m) goto end; + p = PyObject_GetAttrString(m, "RefNannyAPI"); + if (!p) goto end; + r = PyLong_AsVoidPtr(p); +end: + Py_XDECREF(p); + Py_XDECREF(m); + return (__Pyx_RefNannyAPIStruct *)r; +} +#endif + +/* PyObjectGetAttrStr */ +#if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name) { + PyTypeObject* tp = Py_TYPE(obj); + if (likely(tp->tp_getattro)) + return tp->tp_getattro(obj, attr_name); +#if PY_MAJOR_VERSION < 3 + if (likely(tp->tp_getattr)) + return tp->tp_getattr(obj, PyString_AS_STRING(attr_name)); +#endif + return PyObject_GetAttr(obj, attr_name); +} +#endif + +/* GetBuiltinName */ +static PyObject *__Pyx_GetBuiltinName(PyObject *name) { + PyObject* result = __Pyx_PyObject_GetAttrStr(__pyx_b, name); + if (unlikely(!result)) { + PyErr_Format(PyExc_NameError, +#if PY_MAJOR_VERSION >= 3 + "name '%U' is not defined", name); +#else + "name '%.200s' is not defined", PyString_AS_STRING(name)); +#endif + } + return result; +} + +/* decode_c_bytes */ +static CYTHON_INLINE PyObject* __Pyx_decode_c_bytes( + const char* cstring, Py_ssize_t length, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) { + if (unlikely((start < 0) | (stop < 0))) { + if (start < 0) { + start += length; + if (start < 0) + start = 0; + } + if (stop < 0) + stop += length; + } + if (stop > length) + stop = length; + length = stop - start; + if (unlikely(length <= 0)) + return PyUnicode_FromUnicode(NULL, 0); + cstring += start; + if (decode_func) { + return decode_func(cstring, length, errors); + } else { + return PyUnicode_Decode(cstring, length, encoding, errors); + } +} + +/* RaiseArgTupleInvalid */ +static void __Pyx_RaiseArgtupleInvalid( + const char* func_name, + int exact, + Py_ssize_t num_min, + Py_ssize_t num_max, + Py_ssize_t num_found) +{ + Py_ssize_t num_expected; + const char *more_or_less; + if (num_found < num_min) { + num_expected = num_min; + more_or_less = "at least"; + } else { + num_expected = num_max; + more_or_less = "at most"; + } + if (exact) { + more_or_less = "exactly"; + } + PyErr_Format(PyExc_TypeError, + "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)", + func_name, more_or_less, num_expected, + (num_expected == 1) ? "" : "s", num_found); +} + +/* KeywordStringCheck */ +static int __Pyx_CheckKeywordStrings( + PyObject *kwdict, + const char* function_name, + int kw_allowed) +{ + PyObject* key = 0; + Py_ssize_t pos = 0; +#if CYTHON_COMPILING_IN_PYPY + if (!kw_allowed && PyDict_Next(kwdict, &pos, &key, 0)) + goto invalid_keyword; + return 1; +#else + while (PyDict_Next(kwdict, &pos, &key, 0)) { + #if PY_MAJOR_VERSION < 3 + if (unlikely(!PyString_Check(key))) + #endif + if (unlikely(!PyUnicode_Check(key))) + goto invalid_keyword_type; + } + if ((!kw_allowed) && unlikely(key)) + goto invalid_keyword; + return 1; +invalid_keyword_type: + PyErr_Format(PyExc_TypeError, + "%.200s() keywords must be strings", function_name); + return 0; +#endif +invalid_keyword: + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION < 3 + "%.200s() got an unexpected keyword argument '%.200s'", + function_name, PyString_AsString(key)); + #else + "%s() got an unexpected keyword argument '%U'", + function_name, key); + #endif + return 0; +} + +/* RaiseDoubleKeywords */ +static void __Pyx_RaiseDoubleKeywordsError( + const char* func_name, + PyObject* kw_name) +{ + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION >= 3 + "%s() got multiple values for keyword argument '%U'", func_name, kw_name); + #else + "%s() got multiple values for keyword argument '%s'", func_name, + PyString_AsString(kw_name)); + #endif +} + +/* ParseKeywords */ +static int __Pyx_ParseOptionalKeywords( + PyObject *kwds, + PyObject **argnames[], + PyObject *kwds2, + PyObject *values[], + Py_ssize_t num_pos_args, + const char* function_name) +{ + PyObject *key = 0, *value = 0; + Py_ssize_t pos = 0; + PyObject*** name; + PyObject*** first_kw_arg = argnames + num_pos_args; + while (PyDict_Next(kwds, &pos, &key, &value)) { + name = first_kw_arg; + while (*name && (**name != key)) name++; + if (*name) { + values[name-argnames] = value; + continue; + } + name = first_kw_arg; + #if PY_MAJOR_VERSION < 3 + if (likely(PyString_CheckExact(key)) || likely(PyString_Check(key))) { + while (*name) { + if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) + && _PyString_Eq(**name, key)) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + if ((**argname == key) || ( + (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key)) + && _PyString_Eq(**argname, key))) { + goto arg_passed_twice; + } + argname++; + } + } + } else + #endif + if (likely(PyUnicode_Check(key))) { + while (*name) { + int cmp = (**name == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 : + #endif + PyUnicode_Compare(**name, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + int cmp = (**argname == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 : + #endif + PyUnicode_Compare(**argname, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) goto arg_passed_twice; + argname++; + } + } + } else + goto invalid_keyword_type; + if (kwds2) { + if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad; + } else { + goto invalid_keyword; + } + } + return 0; +arg_passed_twice: + __Pyx_RaiseDoubleKeywordsError(function_name, key); + goto bad; +invalid_keyword_type: + PyErr_Format(PyExc_TypeError, + "%.200s() keywords must be strings", function_name); + goto bad; +invalid_keyword: + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION < 3 + "%.200s() got an unexpected keyword argument '%.200s'", + function_name, PyString_AsString(key)); + #else + "%s() got an unexpected keyword argument '%U'", + function_name, key); + #endif +bad: + return -1; +} + +/* PyCFunctionFastCall */ +#if CYTHON_FAST_PYCCALL +static CYTHON_INLINE PyObject * __Pyx_PyCFunction_FastCall(PyObject *func_obj, PyObject **args, Py_ssize_t nargs) { + PyCFunctionObject *func = (PyCFunctionObject*)func_obj; + PyCFunction meth = PyCFunction_GET_FUNCTION(func); + PyObject *self = PyCFunction_GET_SELF(func); + int flags = PyCFunction_GET_FLAGS(func); + assert(PyCFunction_Check(func)); + assert(METH_FASTCALL == (flags & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))); + assert(nargs >= 0); + assert(nargs == 0 || args != NULL); + /* _PyCFunction_FastCallDict() must not be called with an exception set, + because it may clear it (directly or indirectly) and so the + caller loses its exception */ + assert(!PyErr_Occurred()); + if ((PY_VERSION_HEX < 0x030700A0) || unlikely(flags & METH_KEYWORDS)) { + return (*((__Pyx_PyCFunctionFastWithKeywords)(void*)meth)) (self, args, nargs, NULL); + } else { + return (*((__Pyx_PyCFunctionFast)(void*)meth)) (self, args, nargs); + } +} +#endif + +/* PyFunctionFastCall */ +#if CYTHON_FAST_PYCALL +static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args, Py_ssize_t na, + PyObject *globals) { + PyFrameObject *f; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject **fastlocals; + Py_ssize_t i; + PyObject *result; + assert(globals != NULL); + /* XXX Perhaps we should create a specialized + PyFrame_New() that doesn't take locals, but does + take builtins without sanity checking them. + */ + assert(tstate != NULL); + f = PyFrame_New(tstate, co, globals, NULL); + if (f == NULL) { + return NULL; + } + fastlocals = __Pyx_PyFrame_GetLocalsplus(f); + for (i = 0; i < na; i++) { + Py_INCREF(*args); + fastlocals[i] = *args++; + } + result = PyEval_EvalFrameEx(f,0); + ++tstate->recursion_depth; + Py_DECREF(f); + --tstate->recursion_depth; + return result; +} +#if 1 || PY_VERSION_HEX < 0x030600B1 +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs) { + PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func); + PyObject *globals = PyFunction_GET_GLOBALS(func); + PyObject *argdefs = PyFunction_GET_DEFAULTS(func); + PyObject *closure; +#if PY_MAJOR_VERSION >= 3 + PyObject *kwdefs; +#endif + PyObject *kwtuple, **k; + PyObject **d; + Py_ssize_t nd; + Py_ssize_t nk; + PyObject *result; + assert(kwargs == NULL || PyDict_Check(kwargs)); + nk = kwargs ? PyDict_Size(kwargs) : 0; + if (Py_EnterRecursiveCall((char*)" while calling a Python object")) { + return NULL; + } + if ( +#if PY_MAJOR_VERSION >= 3 + co->co_kwonlyargcount == 0 && +#endif + likely(kwargs == NULL || nk == 0) && + co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) { + if (argdefs == NULL && co->co_argcount == nargs) { + result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals); + goto done; + } + else if (nargs == 0 && argdefs != NULL + && co->co_argcount == Py_SIZE(argdefs)) { + /* function called with no arguments, but all parameters have + a default value: use default values as arguments .*/ + args = &PyTuple_GET_ITEM(argdefs, 0); + result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals); + goto done; + } + } + if (kwargs != NULL) { + Py_ssize_t pos, i; + kwtuple = PyTuple_New(2 * nk); + if (kwtuple == NULL) { + result = NULL; + goto done; + } + k = &PyTuple_GET_ITEM(kwtuple, 0); + pos = i = 0; + while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) { + Py_INCREF(k[i]); + Py_INCREF(k[i+1]); + i += 2; + } + nk = i / 2; + } + else { + kwtuple = NULL; + k = NULL; + } + closure = PyFunction_GET_CLOSURE(func); +#if PY_MAJOR_VERSION >= 3 + kwdefs = PyFunction_GET_KW_DEFAULTS(func); +#endif + if (argdefs != NULL) { + d = &PyTuple_GET_ITEM(argdefs, 0); + nd = Py_SIZE(argdefs); + } + else { + d = NULL; + nd = 0; + } +#if PY_MAJOR_VERSION >= 3 + result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, kwdefs, closure); +#else + result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, closure); +#endif + Py_XDECREF(kwtuple); +done: + Py_LeaveRecursiveCall(); + return result; +} +#endif +#endif + +/* PyObjectCall */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { + PyObject *result; + ternaryfunc call = func->ob_type->tp_call; + if (unlikely(!call)) + return PyObject_Call(func, arg, kw); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = (*call)(func, arg, kw); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* PyObjectCall2Args */ +static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) { + PyObject *args, *result = NULL; + #if CYTHON_FAST_PYCALL + if (PyFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyFunction_FastCall(function, args, 2); + } + #endif + #if CYTHON_FAST_PYCCALL + if (__Pyx_PyFastCFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyCFunction_FastCall(function, args, 2); + } + #endif + args = PyTuple_New(2); + if (unlikely(!args)) goto done; + Py_INCREF(arg1); + PyTuple_SET_ITEM(args, 0, arg1); + Py_INCREF(arg2); + PyTuple_SET_ITEM(args, 1, arg2); + Py_INCREF(function); + result = __Pyx_PyObject_Call(function, args, NULL); + Py_DECREF(args); + Py_DECREF(function); +done: + return result; +} + +/* PyObjectCallMethO */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { + PyObject *self, *result; + PyCFunction cfunc; + cfunc = PyCFunction_GET_FUNCTION(func); + self = PyCFunction_GET_SELF(func); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = cfunc(self, arg); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* PyObjectCallOneArg */ +#if CYTHON_COMPILING_IN_CPYTHON +static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_New(1); + if (unlikely(!args)) return NULL; + Py_INCREF(arg); + PyTuple_SET_ITEM(args, 0, arg); + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { +#if CYTHON_FAST_PYCALL + if (PyFunction_Check(func)) { + return __Pyx_PyFunction_FastCall(func, &arg, 1); + } +#endif + if (likely(PyCFunction_Check(func))) { + if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { + return __Pyx_PyObject_CallMethO(func, arg); +#if CYTHON_FAST_PYCCALL + } else if (PyCFunction_GET_FLAGS(func) & METH_FASTCALL) { + return __Pyx_PyCFunction_FastCall(func, &arg, 1); +#endif + } + } + return __Pyx__PyObject_CallOneArg(func, arg); +} +#else +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_Pack(1, arg); + if (unlikely(!args)) return NULL; + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +#endif + +/* PyDictVersioning */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + return likely(dict) ? __PYX_GET_DICT_VERSION(dict) : 0; +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj) { + PyObject **dictptr = NULL; + Py_ssize_t offset = Py_TYPE(obj)->tp_dictoffset; + if (offset) { +#if CYTHON_COMPILING_IN_CPYTHON + dictptr = (likely(offset > 0)) ? (PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); +#else + dictptr = _PyObject_GetDictPtr(obj); +#endif + } + return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; +} +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) + return 0; + return obj_dict_version == __Pyx_get_object_dict_version(obj); +} +#endif + +/* GetModuleGlobalName */ +#if CYTHON_USE_DICT_VERSIONS +static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value) +#else +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name) +#endif +{ + PyObject *result; +#if !CYTHON_AVOID_BORROWED_REFS +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 + result = _PyDict_GetItem_KnownHash(__pyx_d, name, ((PyASCIIObject *) name)->hash); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } else if (unlikely(PyErr_Occurred())) { + return NULL; + } +#else + result = PyDict_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } +#endif +#else + result = PyObject_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } + PyErr_Clear(); +#endif + return __Pyx_GetBuiltinName(name); +} + +/* PyErrFetchRestore */ +#if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + tmp_type = tstate->curexc_type; + tmp_value = tstate->curexc_value; + tmp_tb = tstate->curexc_traceback; + tstate->curexc_type = type; + tstate->curexc_value = value; + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + *type = tstate->curexc_type; + *value = tstate->curexc_value; + *tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +} +#endif + +/* RaiseException */ +#if PY_MAJOR_VERSION < 3 +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, + CYTHON_UNUSED PyObject *cause) { + __Pyx_PyThreadState_declare + Py_XINCREF(type); + if (!value || value == Py_None) + value = NULL; + else + Py_INCREF(value); + if (!tb || tb == Py_None) + tb = NULL; + else { + Py_INCREF(tb); + if (!PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto raise_error; + } + } + if (PyType_Check(type)) { +#if CYTHON_COMPILING_IN_PYPY + if (!value) { + Py_INCREF(Py_None); + value = Py_None; + } +#endif + PyErr_NormalizeException(&type, &value, &tb); + } else { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto raise_error; + } + value = type; + type = (PyObject*) Py_TYPE(type); + Py_INCREF(type); + if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto raise_error; + } + } + __Pyx_PyThreadState_assign + __Pyx_ErrRestore(type, value, tb); + return; +raise_error: + Py_XDECREF(value); + Py_XDECREF(type); + Py_XDECREF(tb); + return; +} +#else +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { + PyObject* owned_instance = NULL; + if (tb == Py_None) { + tb = 0; + } else if (tb && !PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto bad; + } + if (value == Py_None) + value = 0; + if (PyExceptionInstance_Check(type)) { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto bad; + } + value = type; + type = (PyObject*) Py_TYPE(value); + } else if (PyExceptionClass_Check(type)) { + PyObject *instance_class = NULL; + if (value && PyExceptionInstance_Check(value)) { + instance_class = (PyObject*) Py_TYPE(value); + if (instance_class != type) { + int is_subclass = PyObject_IsSubclass(instance_class, type); + if (!is_subclass) { + instance_class = NULL; + } else if (unlikely(is_subclass == -1)) { + goto bad; + } else { + type = instance_class; + } + } + } + if (!instance_class) { + PyObject *args; + if (!value) + args = PyTuple_New(0); + else if (PyTuple_Check(value)) { + Py_INCREF(value); + args = value; + } else + args = PyTuple_Pack(1, value); + if (!args) + goto bad; + owned_instance = PyObject_Call(type, args, NULL); + Py_DECREF(args); + if (!owned_instance) + goto bad; + value = owned_instance; + if (!PyExceptionInstance_Check(value)) { + PyErr_Format(PyExc_TypeError, + "calling %R should have returned an instance of " + "BaseException, not %R", + type, Py_TYPE(value)); + goto bad; + } + } + } else { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto bad; + } + if (cause) { + PyObject *fixed_cause; + if (cause == Py_None) { + fixed_cause = NULL; + } else if (PyExceptionClass_Check(cause)) { + fixed_cause = PyObject_CallObject(cause, NULL); + if (fixed_cause == NULL) + goto bad; + } else if (PyExceptionInstance_Check(cause)) { + fixed_cause = cause; + Py_INCREF(fixed_cause); + } else { + PyErr_SetString(PyExc_TypeError, + "exception causes must derive from " + "BaseException"); + goto bad; + } + PyException_SetCause(value, fixed_cause); + } + PyErr_SetObject(type, value); + if (tb) { +#if CYTHON_COMPILING_IN_PYPY + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); + Py_INCREF(tb); + PyErr_Restore(tmp_type, tmp_value, tb); + Py_XDECREF(tmp_tb); +#else + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject* tmp_tb = tstate->curexc_traceback; + if (tb != tmp_tb) { + Py_INCREF(tb); + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_tb); + } +#endif + } +bad: + Py_XDECREF(owned_instance); + return; +} +#endif + +/* GetItemInt */ +static PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { + PyObject *r; + if (!j) return NULL; + r = PyObject_GetItem(o, j); + Py_DECREF(j); + return r; +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + Py_ssize_t wrapped_i = i; + if (wraparound & unlikely(i < 0)) { + wrapped_i += PyList_GET_SIZE(o); + } + if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyList_GET_SIZE(o)))) { + PyObject *r = PyList_GET_ITEM(o, wrapped_i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + Py_ssize_t wrapped_i = i; + if (wraparound & unlikely(i < 0)) { + wrapped_i += PyTuple_GET_SIZE(o); + } + if ((!boundscheck) || likely(__Pyx_is_valid_index(wrapped_i, PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, wrapped_i); + Py_INCREF(r); + return r; + } + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +#else + return PySequence_GetItem(o, i); +#endif +} +static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, + CYTHON_NCP_UNUSED int wraparound, + CYTHON_NCP_UNUSED int boundscheck) { +#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS + if (is_list || PyList_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); + if ((!boundscheck) || (likely(__Pyx_is_valid_index(n, PyList_GET_SIZE(o))))) { + PyObject *r = PyList_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } + else if (PyTuple_CheckExact(o)) { + Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); + if ((!boundscheck) || likely(__Pyx_is_valid_index(n, PyTuple_GET_SIZE(o)))) { + PyObject *r = PyTuple_GET_ITEM(o, n); + Py_INCREF(r); + return r; + } + } else { + PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; + if (likely(m && m->sq_item)) { + if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { + Py_ssize_t l = m->sq_length(o); + if (likely(l >= 0)) { + i += l; + } else { + if (!PyErr_ExceptionMatches(PyExc_OverflowError)) + return NULL; + PyErr_Clear(); + } + } + return m->sq_item(o, i); + } + } +#else + if (is_list || PySequence_Check(o)) { + return PySequence_GetItem(o, i); + } +#endif + return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); +} + +/* ObjectGetItem */ +#if CYTHON_USE_TYPE_SLOTS +static PyObject *__Pyx_PyObject_GetIndex(PyObject *obj, PyObject* index) { + PyObject *runerr; + Py_ssize_t key_value; + PySequenceMethods *m = Py_TYPE(obj)->tp_as_sequence; + if (unlikely(!(m && m->sq_item))) { + PyErr_Format(PyExc_TypeError, "'%.200s' object is not subscriptable", Py_TYPE(obj)->tp_name); + return NULL; + } + key_value = __Pyx_PyIndex_AsSsize_t(index); + if (likely(key_value != -1 || !(runerr = PyErr_Occurred()))) { + return __Pyx_GetItemInt_Fast(obj, key_value, 0, 1, 1); + } + if (PyErr_GivenExceptionMatches(runerr, PyExc_OverflowError)) { + PyErr_Clear(); + PyErr_Format(PyExc_IndexError, "cannot fit '%.200s' into an index-sized integer", Py_TYPE(index)->tp_name); + } + return NULL; +} +static PyObject *__Pyx_PyObject_GetItem(PyObject *obj, PyObject* key) { + PyMappingMethods *m = Py_TYPE(obj)->tp_as_mapping; + if (likely(m && m->mp_subscript)) { + return m->mp_subscript(obj, key); + } + return __Pyx_PyObject_GetIndex(obj, key); +} +#endif + +/* PyObjectCallNoArg */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) { +#if CYTHON_FAST_PYCALL + if (PyFunction_Check(func)) { + return __Pyx_PyFunction_FastCall(func, NULL, 0); + } +#endif +#ifdef __Pyx_CyFunction_USED + if (likely(PyCFunction_Check(func) || __Pyx_CyFunction_Check(func))) +#else + if (likely(PyCFunction_Check(func))) +#endif + { + if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) { + return __Pyx_PyObject_CallMethO(func, NULL); + } + } + return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL); +} +#endif + +/* IterFinish */ +static CYTHON_INLINE int __Pyx_IterFinish(void) { +#if CYTHON_FAST_THREAD_STATE + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject* exc_type = tstate->curexc_type; + if (unlikely(exc_type)) { + if (likely(__Pyx_PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration))) { + PyObject *exc_value, *exc_tb; + exc_value = tstate->curexc_value; + exc_tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; + Py_DECREF(exc_type); + Py_XDECREF(exc_value); + Py_XDECREF(exc_tb); + return 0; + } else { + return -1; + } + } + return 0; +#else + if (unlikely(PyErr_Occurred())) { + if (likely(PyErr_ExceptionMatches(PyExc_StopIteration))) { + PyErr_Clear(); + return 0; + } else { + return -1; + } + } + return 0; +#endif +} + +/* PyObjectGetMethod */ +static int __Pyx_PyObject_GetMethod(PyObject *obj, PyObject *name, PyObject **method) { + PyObject *attr; +#if CYTHON_UNPACK_METHODS && CYTHON_COMPILING_IN_CPYTHON && CYTHON_USE_PYTYPE_LOOKUP + PyTypeObject *tp = Py_TYPE(obj); + PyObject *descr; + descrgetfunc f = NULL; + PyObject **dictptr, *dict; + int meth_found = 0; + assert (*method == NULL); + if (unlikely(tp->tp_getattro != PyObject_GenericGetAttr)) { + attr = __Pyx_PyObject_GetAttrStr(obj, name); + goto try_unpack; + } + if (unlikely(tp->tp_dict == NULL) && unlikely(PyType_Ready(tp) < 0)) { + return 0; + } + descr = _PyType_Lookup(tp, name); + if (likely(descr != NULL)) { + Py_INCREF(descr); +#if PY_MAJOR_VERSION >= 3 + #ifdef __Pyx_CyFunction_USED + if (likely(PyFunction_Check(descr) || (Py_TYPE(descr) == &PyMethodDescr_Type) || __Pyx_CyFunction_Check(descr))) + #else + if (likely(PyFunction_Check(descr) || (Py_TYPE(descr) == &PyMethodDescr_Type))) + #endif +#else + #ifdef __Pyx_CyFunction_USED + if (likely(PyFunction_Check(descr) || __Pyx_CyFunction_Check(descr))) + #else + if (likely(PyFunction_Check(descr))) + #endif +#endif + { + meth_found = 1; + } else { + f = Py_TYPE(descr)->tp_descr_get; + if (f != NULL && PyDescr_IsData(descr)) { + attr = f(descr, obj, (PyObject *)Py_TYPE(obj)); + Py_DECREF(descr); + goto try_unpack; + } + } + } + dictptr = _PyObject_GetDictPtr(obj); + if (dictptr != NULL && (dict = *dictptr) != NULL) { + Py_INCREF(dict); + attr = __Pyx_PyDict_GetItemStr(dict, name); + if (attr != NULL) { + Py_INCREF(attr); + Py_DECREF(dict); + Py_XDECREF(descr); + goto try_unpack; + } + Py_DECREF(dict); + } + if (meth_found) { + *method = descr; + return 1; + } + if (f != NULL) { + attr = f(descr, obj, (PyObject *)Py_TYPE(obj)); + Py_DECREF(descr); + goto try_unpack; + } + if (descr != NULL) { + *method = descr; + return 0; + } + PyErr_Format(PyExc_AttributeError, +#if PY_MAJOR_VERSION >= 3 + "'%.50s' object has no attribute '%U'", + tp->tp_name, name); +#else + "'%.50s' object has no attribute '%.400s'", + tp->tp_name, PyString_AS_STRING(name)); +#endif + return 0; +#else + attr = __Pyx_PyObject_GetAttrStr(obj, name); + goto try_unpack; +#endif +try_unpack: +#if CYTHON_UNPACK_METHODS + if (likely(attr) && PyMethod_Check(attr) && likely(PyMethod_GET_SELF(attr) == obj)) { + PyObject *function = PyMethod_GET_FUNCTION(attr); + Py_INCREF(function); + Py_DECREF(attr); + *method = function; + return 1; + } +#endif + *method = attr; + return 0; +} + +/* PyObjectCallMethod0 */ +static PyObject* __Pyx_PyObject_CallMethod0(PyObject* obj, PyObject* method_name) { + PyObject *method = NULL, *result = NULL; + int is_method = __Pyx_PyObject_GetMethod(obj, method_name, &method); + if (likely(is_method)) { + result = __Pyx_PyObject_CallOneArg(method, obj); + Py_DECREF(method); + return result; + } + if (unlikely(!method)) goto bad; + result = __Pyx_PyObject_CallNoArg(method); + Py_DECREF(method); +bad: + return result; +} + +/* RaiseNeedMoreValuesToUnpack */ +static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { + PyErr_Format(PyExc_ValueError, + "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", + index, (index == 1) ? "" : "s"); +} + +/* RaiseTooManyValuesToUnpack */ +static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { + PyErr_Format(PyExc_ValueError, + "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); +} + +/* UnpackItemEndCheck */ +static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected) { + if (unlikely(retval)) { + Py_DECREF(retval); + __Pyx_RaiseTooManyValuesError(expected); + return -1; + } else { + return __Pyx_IterFinish(); + } + return 0; +} + +/* RaiseNoneIterError */ +static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { + PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); +} + +/* UnpackTupleError */ +static void __Pyx_UnpackTupleError(PyObject *t, Py_ssize_t index) { + if (t == Py_None) { + __Pyx_RaiseNoneNotIterableError(); + } else if (PyTuple_GET_SIZE(t) < index) { + __Pyx_RaiseNeedMoreValuesError(PyTuple_GET_SIZE(t)); + } else { + __Pyx_RaiseTooManyValuesError(index); + } +} + +/* UnpackTuple2 */ +static CYTHON_INLINE int __Pyx_unpack_tuple2_exact( + PyObject* tuple, PyObject** pvalue1, PyObject** pvalue2, int decref_tuple) { + PyObject *value1 = NULL, *value2 = NULL; +#if CYTHON_COMPILING_IN_PYPY + value1 = PySequence_ITEM(tuple, 0); if (unlikely(!value1)) goto bad; + value2 = PySequence_ITEM(tuple, 1); if (unlikely(!value2)) goto bad; +#else + value1 = PyTuple_GET_ITEM(tuple, 0); Py_INCREF(value1); + value2 = PyTuple_GET_ITEM(tuple, 1); Py_INCREF(value2); +#endif + if (decref_tuple) { + Py_DECREF(tuple); + } + *pvalue1 = value1; + *pvalue2 = value2; + return 0; +#if CYTHON_COMPILING_IN_PYPY +bad: + Py_XDECREF(value1); + Py_XDECREF(value2); + if (decref_tuple) { Py_XDECREF(tuple); } + return -1; +#endif +} +static int __Pyx_unpack_tuple2_generic(PyObject* tuple, PyObject** pvalue1, PyObject** pvalue2, + int has_known_size, int decref_tuple) { + Py_ssize_t index; + PyObject *value1 = NULL, *value2 = NULL, *iter = NULL; + iternextfunc iternext; + iter = PyObject_GetIter(tuple); + if (unlikely(!iter)) goto bad; + if (decref_tuple) { Py_DECREF(tuple); tuple = NULL; } + iternext = Py_TYPE(iter)->tp_iternext; + value1 = iternext(iter); if (unlikely(!value1)) { index = 0; goto unpacking_failed; } + value2 = iternext(iter); if (unlikely(!value2)) { index = 1; goto unpacking_failed; } + if (!has_known_size && unlikely(__Pyx_IternextUnpackEndCheck(iternext(iter), 2))) goto bad; + Py_DECREF(iter); + *pvalue1 = value1; + *pvalue2 = value2; + return 0; +unpacking_failed: + if (!has_known_size && __Pyx_IterFinish() == 0) + __Pyx_RaiseNeedMoreValuesError(index); +bad: + Py_XDECREF(iter); + Py_XDECREF(value1); + Py_XDECREF(value2); + if (decref_tuple) { Py_XDECREF(tuple); } + return -1; +} + +/* dict_iter */ +static CYTHON_INLINE PyObject* __Pyx_dict_iterator(PyObject* iterable, int is_dict, PyObject* method_name, + Py_ssize_t* p_orig_length, int* p_source_is_dict) { + is_dict = is_dict || likely(PyDict_CheckExact(iterable)); + *p_source_is_dict = is_dict; + if (is_dict) { +#if !CYTHON_COMPILING_IN_PYPY + *p_orig_length = PyDict_Size(iterable); + Py_INCREF(iterable); + return iterable; +#elif PY_MAJOR_VERSION >= 3 + static PyObject *py_items = NULL, *py_keys = NULL, *py_values = NULL; + PyObject **pp = NULL; + if (method_name) { + const char *name = PyUnicode_AsUTF8(method_name); + if (strcmp(name, "iteritems") == 0) pp = &py_items; + else if (strcmp(name, "iterkeys") == 0) pp = &py_keys; + else if (strcmp(name, "itervalues") == 0) pp = &py_values; + if (pp) { + if (!*pp) { + *pp = PyUnicode_FromString(name + 4); + if (!*pp) + return NULL; + } + method_name = *pp; + } + } +#endif + } + *p_orig_length = 0; + if (method_name) { + PyObject* iter; + iterable = __Pyx_PyObject_CallMethod0(iterable, method_name); + if (!iterable) + return NULL; +#if !CYTHON_COMPILING_IN_PYPY + if (PyTuple_CheckExact(iterable) || PyList_CheckExact(iterable)) + return iterable; +#endif + iter = PyObject_GetIter(iterable); + Py_DECREF(iterable); + return iter; + } + return PyObject_GetIter(iterable); +} +static CYTHON_INLINE int __Pyx_dict_iter_next( + PyObject* iter_obj, CYTHON_NCP_UNUSED Py_ssize_t orig_length, CYTHON_NCP_UNUSED Py_ssize_t* ppos, + PyObject** pkey, PyObject** pvalue, PyObject** pitem, int source_is_dict) { + PyObject* next_item; +#if !CYTHON_COMPILING_IN_PYPY + if (source_is_dict) { + PyObject *key, *value; + if (unlikely(orig_length != PyDict_Size(iter_obj))) { + PyErr_SetString(PyExc_RuntimeError, "dictionary changed size during iteration"); + return -1; + } + if (unlikely(!PyDict_Next(iter_obj, ppos, &key, &value))) { + return 0; + } + if (pitem) { + PyObject* tuple = PyTuple_New(2); + if (unlikely(!tuple)) { + return -1; + } + Py_INCREF(key); + Py_INCREF(value); + PyTuple_SET_ITEM(tuple, 0, key); + PyTuple_SET_ITEM(tuple, 1, value); + *pitem = tuple; + } else { + if (pkey) { + Py_INCREF(key); + *pkey = key; + } + if (pvalue) { + Py_INCREF(value); + *pvalue = value; + } + } + return 1; + } else if (PyTuple_CheckExact(iter_obj)) { + Py_ssize_t pos = *ppos; + if (unlikely(pos >= PyTuple_GET_SIZE(iter_obj))) return 0; + *ppos = pos + 1; + next_item = PyTuple_GET_ITEM(iter_obj, pos); + Py_INCREF(next_item); + } else if (PyList_CheckExact(iter_obj)) { + Py_ssize_t pos = *ppos; + if (unlikely(pos >= PyList_GET_SIZE(iter_obj))) return 0; + *ppos = pos + 1; + next_item = PyList_GET_ITEM(iter_obj, pos); + Py_INCREF(next_item); + } else +#endif + { + next_item = PyIter_Next(iter_obj); + if (unlikely(!next_item)) { + return __Pyx_IterFinish(); + } + } + if (pitem) { + *pitem = next_item; + } else if (pkey && pvalue) { + if (__Pyx_unpack_tuple2(next_item, pkey, pvalue, source_is_dict, source_is_dict, 1)) + return -1; + } else if (pkey) { + *pkey = next_item; + } else { + *pvalue = next_item; + } + return 1; +} + +/* PyObjectSetAttrStr */ +#if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE int __Pyx_PyObject_SetAttrStr(PyObject* obj, PyObject* attr_name, PyObject* value) { + PyTypeObject* tp = Py_TYPE(obj); + if (likely(tp->tp_setattro)) + return tp->tp_setattro(obj, attr_name, value); +#if PY_MAJOR_VERSION < 3 + if (likely(tp->tp_setattr)) + return tp->tp_setattr(obj, PyString_AS_STRING(attr_name), value); +#endif + return PyObject_SetAttr(obj, attr_name, value); +} +#endif + +/* DictGetItem */ +#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY +static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key) { + PyObject *value; + value = PyDict_GetItemWithError(d, key); + if (unlikely(!value)) { + if (!PyErr_Occurred()) { + if (unlikely(PyTuple_Check(key))) { + PyObject* args = PyTuple_Pack(1, key); + if (likely(args)) { + PyErr_SetObject(PyExc_KeyError, args); + Py_DECREF(args); + } + } else { + PyErr_SetObject(PyExc_KeyError, key); + } + } + return NULL; + } + Py_INCREF(value); + return value; +} +#endif + +/* ExtTypeTest */ +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + if (likely(__Pyx_TypeCheck(obj, type))) + return 1; + PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", + Py_TYPE(obj)->tp_name, type->tp_name); + return 0; +} + +/* GetTopmostException */ +#if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * +__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) +{ + _PyErr_StackItem *exc_info = tstate->exc_info; + while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && + exc_info->previous_item != NULL) + { + exc_info = exc_info->previous_item; + } + return exc_info; +} +#endif + +/* SaveResetException */ +#if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); + *type = exc_info->exc_type; + *value = exc_info->exc_value; + *tb = exc_info->exc_traceback; + #else + *type = tstate->exc_type; + *value = tstate->exc_value; + *tb = tstate->exc_traceback; + #endif + Py_XINCREF(*type); + Py_XINCREF(*value); + Py_XINCREF(*tb); +} +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = type; + exc_info->exc_value = value; + exc_info->exc_traceback = tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = type; + tstate->exc_value = value; + tstate->exc_traceback = tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +#endif + +/* PyErrExceptionMatches */ +#if CYTHON_FAST_THREAD_STATE +static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; icurexc_type; + if (exc_type == err) return 1; + if (unlikely(!exc_type)) return 0; + if (unlikely(PyTuple_Check(err))) + return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); + return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); +} +#endif + +/* GetException */ +#if CYTHON_FAST_THREAD_STATE +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) +#endif +{ + PyObject *local_type, *local_value, *local_tb; +#if CYTHON_FAST_THREAD_STATE + PyObject *tmp_type, *tmp_value, *tmp_tb; + local_type = tstate->curexc_type; + local_value = tstate->curexc_value; + local_tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +#else + PyErr_Fetch(&local_type, &local_value, &local_tb); +#endif + PyErr_NormalizeException(&local_type, &local_value, &local_tb); +#if CYTHON_FAST_THREAD_STATE + if (unlikely(tstate->curexc_type)) +#else + if (unlikely(PyErr_Occurred())) +#endif + goto bad; + #if PY_MAJOR_VERSION >= 3 + if (local_tb) { + if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) + goto bad; + } + #endif + Py_XINCREF(local_tb); + Py_XINCREF(local_type); + Py_XINCREF(local_value); + *type = local_type; + *value = local_value; + *tb = local_tb; +#if CYTHON_FAST_THREAD_STATE + #if CYTHON_USE_EXC_INFO_STACK + { + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = local_type; + exc_info->exc_value = local_value; + exc_info->exc_traceback = local_tb; + } + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = local_type; + tstate->exc_value = local_value; + tstate->exc_traceback = local_tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(local_type, local_value, local_tb); +#endif + return 0; +bad: + *type = 0; + *value = 0; + *tb = 0; + Py_XDECREF(local_type); + Py_XDECREF(local_value); + Py_XDECREF(local_tb); + return -1; +} + +/* PyObject_GenericGetAttrNoDict */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static PyObject *__Pyx_RaiseGenericGetAttributeError(PyTypeObject *tp, PyObject *attr_name) { + PyErr_Format(PyExc_AttributeError, +#if PY_MAJOR_VERSION >= 3 + "'%.50s' object has no attribute '%U'", + tp->tp_name, attr_name); +#else + "'%.50s' object has no attribute '%.400s'", + tp->tp_name, PyString_AS_STRING(attr_name)); +#endif + return NULL; +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_GenericGetAttrNoDict(PyObject* obj, PyObject* attr_name) { + PyObject *descr; + PyTypeObject *tp = Py_TYPE(obj); + if (unlikely(!PyString_Check(attr_name))) { + return PyObject_GenericGetAttr(obj, attr_name); + } + assert(!tp->tp_dictoffset); + descr = _PyType_Lookup(tp, attr_name); + if (unlikely(!descr)) { + return __Pyx_RaiseGenericGetAttributeError(tp, attr_name); + } + Py_INCREF(descr); + #if PY_MAJOR_VERSION < 3 + if (likely(PyType_HasFeature(Py_TYPE(descr), Py_TPFLAGS_HAVE_CLASS))) + #endif + { + descrgetfunc f = Py_TYPE(descr)->tp_descr_get; + if (unlikely(f)) { + PyObject *res = f(descr, obj, (PyObject *)tp); + Py_DECREF(descr); + return res; + } + } + return descr; +} +#endif + +/* PyObject_GenericGetAttr */ +#if CYTHON_USE_TYPE_SLOTS && CYTHON_USE_PYTYPE_LOOKUP && PY_VERSION_HEX < 0x03070000 +static PyObject* __Pyx_PyObject_GenericGetAttr(PyObject* obj, PyObject* attr_name) { + if (unlikely(Py_TYPE(obj)->tp_dictoffset)) { + return PyObject_GenericGetAttr(obj, attr_name); + } + return __Pyx_PyObject_GenericGetAttrNoDict(obj, attr_name); +} +#endif + +/* SetupReduce */ +static int __Pyx_setup_reduce_is_named(PyObject* meth, PyObject* name) { + int ret; + PyObject *name_attr; + name_attr = __Pyx_PyObject_GetAttrStr(meth, __pyx_n_s_name_2); + if (likely(name_attr)) { + ret = PyObject_RichCompareBool(name_attr, name, Py_EQ); + } else { + ret = -1; + } + if (unlikely(ret < 0)) { + PyErr_Clear(); + ret = 0; + } + Py_XDECREF(name_attr); + return ret; +} +static int __Pyx_setup_reduce(PyObject* type_obj) { + int ret = 0; + PyObject *object_reduce = NULL; + PyObject *object_reduce_ex = NULL; + PyObject *reduce = NULL; + PyObject *reduce_ex = NULL; + PyObject *reduce_cython = NULL; + PyObject *setstate = NULL; + PyObject *setstate_cython = NULL; +#if CYTHON_USE_PYTYPE_LOOKUP + if (_PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; +#else + if (PyObject_HasAttr(type_obj, __pyx_n_s_getstate)) goto __PYX_GOOD; +#endif +#if CYTHON_USE_PYTYPE_LOOKUP + object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; +#else + object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto __PYX_BAD; +#endif + reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto __PYX_BAD; + if (reduce_ex == object_reduce_ex) { +#if CYTHON_USE_PYTYPE_LOOKUP + object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; +#else + object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto __PYX_BAD; +#endif + reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto __PYX_BAD; + if (reduce == object_reduce || __Pyx_setup_reduce_is_named(reduce, __pyx_n_s_reduce_cython)) { + reduce_cython = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_cython); if (unlikely(!reduce_cython)) goto __PYX_BAD; + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + setstate = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate); + if (!setstate) PyErr_Clear(); + if (!setstate || __Pyx_setup_reduce_is_named(setstate, __pyx_n_s_setstate_cython)) { + setstate_cython = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate_cython); if (unlikely(!setstate_cython)) goto __PYX_BAD; + ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto __PYX_BAD; + } + PyType_Modified((PyTypeObject*)type_obj); + } + } + goto __PYX_GOOD; +__PYX_BAD: + if (!PyErr_Occurred()) + PyErr_Format(PyExc_RuntimeError, "Unable to initialize pickling for %s", ((PyTypeObject*)type_obj)->tp_name); + ret = -1; +__PYX_GOOD: +#if !CYTHON_USE_PYTYPE_LOOKUP + Py_XDECREF(object_reduce); + Py_XDECREF(object_reduce_ex); +#endif + Py_XDECREF(reduce); + Py_XDECREF(reduce_ex); + Py_XDECREF(reduce_cython); + Py_XDECREF(setstate); + Py_XDECREF(setstate_cython); + return ret; +} + +/* TypeImport */ +#ifndef __PYX_HAVE_RT_ImportType +#define __PYX_HAVE_RT_ImportType +static PyTypeObject *__Pyx_ImportType(PyObject *module, const char *module_name, const char *class_name, + size_t size, enum __Pyx_ImportType_CheckSize check_size) +{ + PyObject *result = 0; + char warning[200]; + Py_ssize_t basicsize; +#ifdef Py_LIMITED_API + PyObject *py_basicsize; +#endif + result = PyObject_GetAttrString(module, class_name); + if (!result) + goto bad; + if (!PyType_Check(result)) { + PyErr_Format(PyExc_TypeError, + "%.200s.%.200s is not a type object", + module_name, class_name); + goto bad; + } +#ifndef Py_LIMITED_API + basicsize = ((PyTypeObject *)result)->tp_basicsize; +#else + py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); + if (!py_basicsize) + goto bad; + basicsize = PyLong_AsSsize_t(py_basicsize); + Py_DECREF(py_basicsize); + py_basicsize = 0; + if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) + goto bad; +#endif + if ((size_t)basicsize < size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + if (check_size == __Pyx_ImportType_CheckSize_Error && (size_t)basicsize != size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + else if (check_size == __Pyx_ImportType_CheckSize_Warn && (size_t)basicsize > size) { + PyOS_snprintf(warning, sizeof(warning), + "%s.%s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; + } + return (PyTypeObject *)result; +bad: + Py_XDECREF(result); + return NULL; +} +#endif + +/* Import */ +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { + PyObject *empty_list = 0; + PyObject *module = 0; + PyObject *global_dict = 0; + PyObject *empty_dict = 0; + PyObject *list; + #if PY_MAJOR_VERSION < 3 + PyObject *py_import; + py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); + if (!py_import) + goto bad; + #endif + if (from_list) + list = from_list; + else { + empty_list = PyList_New(0); + if (!empty_list) + goto bad; + list = empty_list; + } + global_dict = PyModule_GetDict(__pyx_m); + if (!global_dict) + goto bad; + empty_dict = PyDict_New(); + if (!empty_dict) + goto bad; + { + #if PY_MAJOR_VERSION >= 3 + if (level == -1) { + if (strchr(__Pyx_MODULE_NAME, '.')) { + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, 1); + if (!module) { + if (!PyErr_ExceptionMatches(PyExc_ImportError)) + goto bad; + PyErr_Clear(); + } + } + level = 0; + } + #endif + if (!module) { + #if PY_MAJOR_VERSION < 3 + PyObject *py_level = PyInt_FromLong(level); + if (!py_level) + goto bad; + module = PyObject_CallFunctionObjArgs(py_import, + name, global_dict, empty_dict, list, py_level, (PyObject *)NULL); + Py_DECREF(py_level); + #else + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, level); + #endif + } + } +bad: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(py_import); + #endif + Py_XDECREF(empty_list); + Py_XDECREF(empty_dict); + return module; +} + +/* CalculateMetaclass */ +static PyObject *__Pyx_CalculateMetaclass(PyTypeObject *metaclass, PyObject *bases) { + Py_ssize_t i, nbases = PyTuple_GET_SIZE(bases); + for (i=0; i < nbases; i++) { + PyTypeObject *tmptype; + PyObject *tmp = PyTuple_GET_ITEM(bases, i); + tmptype = Py_TYPE(tmp); +#if PY_MAJOR_VERSION < 3 + if (tmptype == &PyClass_Type) + continue; +#endif + if (!metaclass) { + metaclass = tmptype; + continue; + } + if (PyType_IsSubtype(metaclass, tmptype)) + continue; + if (PyType_IsSubtype(tmptype, metaclass)) { + metaclass = tmptype; + continue; + } + PyErr_SetString(PyExc_TypeError, + "metaclass conflict: " + "the metaclass of a derived class " + "must be a (non-strict) subclass " + "of the metaclasses of all its bases"); + return NULL; + } + if (!metaclass) { +#if PY_MAJOR_VERSION < 3 + metaclass = &PyClass_Type; +#else + metaclass = &PyType_Type; +#endif + } + Py_INCREF((PyObject*) metaclass); + return (PyObject*) metaclass; +} + +/* Py3ClassCreate */ +static PyObject *__Pyx_Py3MetaclassPrepare(PyObject *metaclass, PyObject *bases, PyObject *name, + PyObject *qualname, PyObject *mkw, PyObject *modname, PyObject *doc) { + PyObject *ns; + if (metaclass) { + PyObject *prep = __Pyx_PyObject_GetAttrStr(metaclass, __pyx_n_s_prepare); + if (prep) { + PyObject *pargs = PyTuple_Pack(2, name, bases); + if (unlikely(!pargs)) { + Py_DECREF(prep); + return NULL; + } + ns = PyObject_Call(prep, pargs, mkw); + Py_DECREF(prep); + Py_DECREF(pargs); + } else { + if (unlikely(!PyErr_ExceptionMatches(PyExc_AttributeError))) + return NULL; + PyErr_Clear(); + ns = PyDict_New(); + } + } else { + ns = PyDict_New(); + } + if (unlikely(!ns)) + return NULL; + if (unlikely(PyObject_SetItem(ns, __pyx_n_s_module, modname) < 0)) goto bad; + if (unlikely(PyObject_SetItem(ns, __pyx_n_s_qualname, qualname) < 0)) goto bad; + if (unlikely(doc && PyObject_SetItem(ns, __pyx_n_s_doc, doc) < 0)) goto bad; + return ns; +bad: + Py_DECREF(ns); + return NULL; +} +static PyObject *__Pyx_Py3ClassCreate(PyObject *metaclass, PyObject *name, PyObject *bases, + PyObject *dict, PyObject *mkw, + int calculate_metaclass, int allow_py2_metaclass) { + PyObject *result, *margs; + PyObject *owned_metaclass = NULL; + if (allow_py2_metaclass) { + owned_metaclass = PyObject_GetItem(dict, __pyx_n_s_metaclass); + if (owned_metaclass) { + metaclass = owned_metaclass; + } else if (likely(PyErr_ExceptionMatches(PyExc_KeyError))) { + PyErr_Clear(); + } else { + return NULL; + } + } + if (calculate_metaclass && (!metaclass || PyType_Check(metaclass))) { + metaclass = __Pyx_CalculateMetaclass((PyTypeObject*) metaclass, bases); + Py_XDECREF(owned_metaclass); + if (unlikely(!metaclass)) + return NULL; + owned_metaclass = metaclass; + } + margs = PyTuple_Pack(3, name, bases, dict); + if (unlikely(!margs)) { + result = NULL; + } else { + result = PyObject_Call(metaclass, margs, mkw); + Py_DECREF(margs); + } + Py_XDECREF(owned_metaclass); + return result; +} + +/* FetchCommonType */ +static PyTypeObject* __Pyx_FetchCommonType(PyTypeObject* type) { + PyObject* fake_module; + PyTypeObject* cached_type = NULL; + fake_module = PyImport_AddModule((char*) "_cython_" CYTHON_ABI); + if (!fake_module) return NULL; + Py_INCREF(fake_module); + cached_type = (PyTypeObject*) PyObject_GetAttrString(fake_module, type->tp_name); + if (cached_type) { + if (!PyType_Check((PyObject*)cached_type)) { + PyErr_Format(PyExc_TypeError, + "Shared Cython type %.200s is not a type object", + type->tp_name); + goto bad; + } + if (cached_type->tp_basicsize != type->tp_basicsize) { + PyErr_Format(PyExc_TypeError, + "Shared Cython type %.200s has the wrong size, try recompiling", + type->tp_name); + goto bad; + } + } else { + if (!PyErr_ExceptionMatches(PyExc_AttributeError)) goto bad; + PyErr_Clear(); + if (PyType_Ready(type) < 0) goto bad; + if (PyObject_SetAttrString(fake_module, type->tp_name, (PyObject*) type) < 0) + goto bad; + Py_INCREF(type); + cached_type = type; + } +done: + Py_DECREF(fake_module); + return cached_type; +bad: + Py_XDECREF(cached_type); + cached_type = NULL; + goto done; +} + +/* CythonFunction */ +#include +static PyObject * +__Pyx_CyFunction_get_doc(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *closure) +{ + if (unlikely(op->func_doc == NULL)) { + if (op->func.m_ml->ml_doc) { +#if PY_MAJOR_VERSION >= 3 + op->func_doc = PyUnicode_FromString(op->func.m_ml->ml_doc); +#else + op->func_doc = PyString_FromString(op->func.m_ml->ml_doc); +#endif + if (unlikely(op->func_doc == NULL)) + return NULL; + } else { + Py_INCREF(Py_None); + return Py_None; + } + } + Py_INCREF(op->func_doc); + return op->func_doc; +} +static int +__Pyx_CyFunction_set_doc(__pyx_CyFunctionObject *op, PyObject *value, CYTHON_UNUSED void *context) +{ + PyObject *tmp = op->func_doc; + if (value == NULL) { + value = Py_None; + } + Py_INCREF(value); + op->func_doc = value; + Py_XDECREF(tmp); + return 0; +} +static PyObject * +__Pyx_CyFunction_get_name(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *context) +{ + if (unlikely(op->func_name == NULL)) { +#if PY_MAJOR_VERSION >= 3 + op->func_name = PyUnicode_InternFromString(op->func.m_ml->ml_name); +#else + op->func_name = PyString_InternFromString(op->func.m_ml->ml_name); +#endif + if (unlikely(op->func_name == NULL)) + return NULL; + } + Py_INCREF(op->func_name); + return op->func_name; +} +static int +__Pyx_CyFunction_set_name(__pyx_CyFunctionObject *op, PyObject *value, CYTHON_UNUSED void *context) +{ + PyObject *tmp; +#if PY_MAJOR_VERSION >= 3 + if (unlikely(value == NULL || !PyUnicode_Check(value))) +#else + if (unlikely(value == NULL || !PyString_Check(value))) +#endif + { + PyErr_SetString(PyExc_TypeError, + "__name__ must be set to a string object"); + return -1; + } + tmp = op->func_name; + Py_INCREF(value); + op->func_name = value; + Py_XDECREF(tmp); + return 0; +} +static PyObject * +__Pyx_CyFunction_get_qualname(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *context) +{ + Py_INCREF(op->func_qualname); + return op->func_qualname; +} +static int +__Pyx_CyFunction_set_qualname(__pyx_CyFunctionObject *op, PyObject *value, CYTHON_UNUSED void *context) +{ + PyObject *tmp; +#if PY_MAJOR_VERSION >= 3 + if (unlikely(value == NULL || !PyUnicode_Check(value))) +#else + if (unlikely(value == NULL || !PyString_Check(value))) +#endif + { + PyErr_SetString(PyExc_TypeError, + "__qualname__ must be set to a string object"); + return -1; + } + tmp = op->func_qualname; + Py_INCREF(value); + op->func_qualname = value; + Py_XDECREF(tmp); + return 0; +} +static PyObject * +__Pyx_CyFunction_get_self(__pyx_CyFunctionObject *m, CYTHON_UNUSED void *closure) +{ + PyObject *self; + self = m->func_closure; + if (self == NULL) + self = Py_None; + Py_INCREF(self); + return self; +} +static PyObject * +__Pyx_CyFunction_get_dict(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *context) +{ + if (unlikely(op->func_dict == NULL)) { + op->func_dict = PyDict_New(); + if (unlikely(op->func_dict == NULL)) + return NULL; + } + Py_INCREF(op->func_dict); + return op->func_dict; +} +static int +__Pyx_CyFunction_set_dict(__pyx_CyFunctionObject *op, PyObject *value, CYTHON_UNUSED void *context) +{ + PyObject *tmp; + if (unlikely(value == NULL)) { + PyErr_SetString(PyExc_TypeError, + "function's dictionary may not be deleted"); + return -1; + } + if (unlikely(!PyDict_Check(value))) { + PyErr_SetString(PyExc_TypeError, + "setting function's dictionary to a non-dict"); + return -1; + } + tmp = op->func_dict; + Py_INCREF(value); + op->func_dict = value; + Py_XDECREF(tmp); + return 0; +} +static PyObject * +__Pyx_CyFunction_get_globals(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *context) +{ + Py_INCREF(op->func_globals); + return op->func_globals; +} +static PyObject * +__Pyx_CyFunction_get_closure(CYTHON_UNUSED __pyx_CyFunctionObject *op, CYTHON_UNUSED void *context) +{ + Py_INCREF(Py_None); + return Py_None; +} +static PyObject * +__Pyx_CyFunction_get_code(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *context) +{ + PyObject* result = (op->func_code) ? op->func_code : Py_None; + Py_INCREF(result); + return result; +} +static int +__Pyx_CyFunction_init_defaults(__pyx_CyFunctionObject *op) { + int result = 0; + PyObject *res = op->defaults_getter((PyObject *) op); + if (unlikely(!res)) + return -1; + #if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + op->defaults_tuple = PyTuple_GET_ITEM(res, 0); + Py_INCREF(op->defaults_tuple); + op->defaults_kwdict = PyTuple_GET_ITEM(res, 1); + Py_INCREF(op->defaults_kwdict); + #else + op->defaults_tuple = PySequence_ITEM(res, 0); + if (unlikely(!op->defaults_tuple)) result = -1; + else { + op->defaults_kwdict = PySequence_ITEM(res, 1); + if (unlikely(!op->defaults_kwdict)) result = -1; + } + #endif + Py_DECREF(res); + return result; +} +static int +__Pyx_CyFunction_set_defaults(__pyx_CyFunctionObject *op, PyObject* value, CYTHON_UNUSED void *context) { + PyObject* tmp; + if (!value) { + value = Py_None; + } else if (value != Py_None && !PyTuple_Check(value)) { + PyErr_SetString(PyExc_TypeError, + "__defaults__ must be set to a tuple object"); + return -1; + } + Py_INCREF(value); + tmp = op->defaults_tuple; + op->defaults_tuple = value; + Py_XDECREF(tmp); + return 0; +} +static PyObject * +__Pyx_CyFunction_get_defaults(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *context) { + PyObject* result = op->defaults_tuple; + if (unlikely(!result)) { + if (op->defaults_getter) { + if (__Pyx_CyFunction_init_defaults(op) < 0) return NULL; + result = op->defaults_tuple; + } else { + result = Py_None; + } + } + Py_INCREF(result); + return result; +} +static int +__Pyx_CyFunction_set_kwdefaults(__pyx_CyFunctionObject *op, PyObject* value, CYTHON_UNUSED void *context) { + PyObject* tmp; + if (!value) { + value = Py_None; + } else if (value != Py_None && !PyDict_Check(value)) { + PyErr_SetString(PyExc_TypeError, + "__kwdefaults__ must be set to a dict object"); + return -1; + } + Py_INCREF(value); + tmp = op->defaults_kwdict; + op->defaults_kwdict = value; + Py_XDECREF(tmp); + return 0; +} +static PyObject * +__Pyx_CyFunction_get_kwdefaults(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *context) { + PyObject* result = op->defaults_kwdict; + if (unlikely(!result)) { + if (op->defaults_getter) { + if (__Pyx_CyFunction_init_defaults(op) < 0) return NULL; + result = op->defaults_kwdict; + } else { + result = Py_None; + } + } + Py_INCREF(result); + return result; +} +static int +__Pyx_CyFunction_set_annotations(__pyx_CyFunctionObject *op, PyObject* value, CYTHON_UNUSED void *context) { + PyObject* tmp; + if (!value || value == Py_None) { + value = NULL; + } else if (!PyDict_Check(value)) { + PyErr_SetString(PyExc_TypeError, + "__annotations__ must be set to a dict object"); + return -1; + } + Py_XINCREF(value); + tmp = op->func_annotations; + op->func_annotations = value; + Py_XDECREF(tmp); + return 0; +} +static PyObject * +__Pyx_CyFunction_get_annotations(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *context) { + PyObject* result = op->func_annotations; + if (unlikely(!result)) { + result = PyDict_New(); + if (unlikely(!result)) return NULL; + op->func_annotations = result; + } + Py_INCREF(result); + return result; +} +static PyGetSetDef __pyx_CyFunction_getsets[] = { + {(char *) "func_doc", (getter)__Pyx_CyFunction_get_doc, (setter)__Pyx_CyFunction_set_doc, 0, 0}, + {(char *) "__doc__", (getter)__Pyx_CyFunction_get_doc, (setter)__Pyx_CyFunction_set_doc, 0, 0}, + {(char *) "func_name", (getter)__Pyx_CyFunction_get_name, (setter)__Pyx_CyFunction_set_name, 0, 0}, + {(char *) "__name__", (getter)__Pyx_CyFunction_get_name, (setter)__Pyx_CyFunction_set_name, 0, 0}, + {(char *) "__qualname__", (getter)__Pyx_CyFunction_get_qualname, (setter)__Pyx_CyFunction_set_qualname, 0, 0}, + {(char *) "__self__", (getter)__Pyx_CyFunction_get_self, 0, 0, 0}, + {(char *) "func_dict", (getter)__Pyx_CyFunction_get_dict, (setter)__Pyx_CyFunction_set_dict, 0, 0}, + {(char *) "__dict__", (getter)__Pyx_CyFunction_get_dict, (setter)__Pyx_CyFunction_set_dict, 0, 0}, + {(char *) "func_globals", (getter)__Pyx_CyFunction_get_globals, 0, 0, 0}, + {(char *) "__globals__", (getter)__Pyx_CyFunction_get_globals, 0, 0, 0}, + {(char *) "func_closure", (getter)__Pyx_CyFunction_get_closure, 0, 0, 0}, + {(char *) "__closure__", (getter)__Pyx_CyFunction_get_closure, 0, 0, 0}, + {(char *) "func_code", (getter)__Pyx_CyFunction_get_code, 0, 0, 0}, + {(char *) "__code__", (getter)__Pyx_CyFunction_get_code, 0, 0, 0}, + {(char *) "func_defaults", (getter)__Pyx_CyFunction_get_defaults, (setter)__Pyx_CyFunction_set_defaults, 0, 0}, + {(char *) "__defaults__", (getter)__Pyx_CyFunction_get_defaults, (setter)__Pyx_CyFunction_set_defaults, 0, 0}, + {(char *) "__kwdefaults__", (getter)__Pyx_CyFunction_get_kwdefaults, (setter)__Pyx_CyFunction_set_kwdefaults, 0, 0}, + {(char *) "__annotations__", (getter)__Pyx_CyFunction_get_annotations, (setter)__Pyx_CyFunction_set_annotations, 0, 0}, + {0, 0, 0, 0, 0} +}; +static PyMemberDef __pyx_CyFunction_members[] = { + {(char *) "__module__", T_OBJECT, offsetof(PyCFunctionObject, m_module), PY_WRITE_RESTRICTED, 0}, + {0, 0, 0, 0, 0} +}; +static PyObject * +__Pyx_CyFunction_reduce(__pyx_CyFunctionObject *m, CYTHON_UNUSED PyObject *args) +{ +#if PY_MAJOR_VERSION >= 3 + return PyUnicode_FromString(m->func.m_ml->ml_name); +#else + return PyString_FromString(m->func.m_ml->ml_name); +#endif +} +static PyMethodDef __pyx_CyFunction_methods[] = { + {"__reduce__", (PyCFunction)__Pyx_CyFunction_reduce, METH_VARARGS, 0}, + {0, 0, 0, 0} +}; +#if PY_VERSION_HEX < 0x030500A0 +#define __Pyx_CyFunction_weakreflist(cyfunc) ((cyfunc)->func_weakreflist) +#else +#define __Pyx_CyFunction_weakreflist(cyfunc) ((cyfunc)->func.m_weakreflist) +#endif +static PyObject *__Pyx_CyFunction_New(PyTypeObject *type, PyMethodDef *ml, int flags, PyObject* qualname, + PyObject *closure, PyObject *module, PyObject* globals, PyObject* code) { + __pyx_CyFunctionObject *op = PyObject_GC_New(__pyx_CyFunctionObject, type); + if (op == NULL) + return NULL; + op->flags = flags; + __Pyx_CyFunction_weakreflist(op) = NULL; + op->func.m_ml = ml; + op->func.m_self = (PyObject *) op; + Py_XINCREF(closure); + op->func_closure = closure; + Py_XINCREF(module); + op->func.m_module = module; + op->func_dict = NULL; + op->func_name = NULL; + Py_INCREF(qualname); + op->func_qualname = qualname; + op->func_doc = NULL; + op->func_classobj = NULL; + op->func_globals = globals; + Py_INCREF(op->func_globals); + Py_XINCREF(code); + op->func_code = code; + op->defaults_pyobjects = 0; + op->defaults = NULL; + op->defaults_tuple = NULL; + op->defaults_kwdict = NULL; + op->defaults_getter = NULL; + op->func_annotations = NULL; + PyObject_GC_Track(op); + return (PyObject *) op; +} +static int +__Pyx_CyFunction_clear(__pyx_CyFunctionObject *m) +{ + Py_CLEAR(m->func_closure); + Py_CLEAR(m->func.m_module); + Py_CLEAR(m->func_dict); + Py_CLEAR(m->func_name); + Py_CLEAR(m->func_qualname); + Py_CLEAR(m->func_doc); + Py_CLEAR(m->func_globals); + Py_CLEAR(m->func_code); + Py_CLEAR(m->func_classobj); + Py_CLEAR(m->defaults_tuple); + Py_CLEAR(m->defaults_kwdict); + Py_CLEAR(m->func_annotations); + if (m->defaults) { + PyObject **pydefaults = __Pyx_CyFunction_Defaults(PyObject *, m); + int i; + for (i = 0; i < m->defaults_pyobjects; i++) + Py_XDECREF(pydefaults[i]); + PyObject_Free(m->defaults); + m->defaults = NULL; + } + return 0; +} +static void __Pyx__CyFunction_dealloc(__pyx_CyFunctionObject *m) +{ + if (__Pyx_CyFunction_weakreflist(m) != NULL) + PyObject_ClearWeakRefs((PyObject *) m); + __Pyx_CyFunction_clear(m); + PyObject_GC_Del(m); +} +static void __Pyx_CyFunction_dealloc(__pyx_CyFunctionObject *m) +{ + PyObject_GC_UnTrack(m); + __Pyx__CyFunction_dealloc(m); +} +static int __Pyx_CyFunction_traverse(__pyx_CyFunctionObject *m, visitproc visit, void *arg) +{ + Py_VISIT(m->func_closure); + Py_VISIT(m->func.m_module); + Py_VISIT(m->func_dict); + Py_VISIT(m->func_name); + Py_VISIT(m->func_qualname); + Py_VISIT(m->func_doc); + Py_VISIT(m->func_globals); + Py_VISIT(m->func_code); + Py_VISIT(m->func_classobj); + Py_VISIT(m->defaults_tuple); + Py_VISIT(m->defaults_kwdict); + if (m->defaults) { + PyObject **pydefaults = __Pyx_CyFunction_Defaults(PyObject *, m); + int i; + for (i = 0; i < m->defaults_pyobjects; i++) + Py_VISIT(pydefaults[i]); + } + return 0; +} +static PyObject *__Pyx_CyFunction_descr_get(PyObject *func, PyObject *obj, PyObject *type) +{ + __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; + if (m->flags & __Pyx_CYFUNCTION_STATICMETHOD) { + Py_INCREF(func); + return func; + } + if (m->flags & __Pyx_CYFUNCTION_CLASSMETHOD) { + if (type == NULL) + type = (PyObject *)(Py_TYPE(obj)); + return __Pyx_PyMethod_New(func, type, (PyObject *)(Py_TYPE(type))); + } + if (obj == Py_None) + obj = NULL; + return __Pyx_PyMethod_New(func, obj, type); +} +static PyObject* +__Pyx_CyFunction_repr(__pyx_CyFunctionObject *op) +{ +#if PY_MAJOR_VERSION >= 3 + return PyUnicode_FromFormat("", + op->func_qualname, (void *)op); +#else + return PyString_FromFormat("", + PyString_AsString(op->func_qualname), (void *)op); +#endif +} +static PyObject * __Pyx_CyFunction_CallMethod(PyObject *func, PyObject *self, PyObject *arg, PyObject *kw) { + PyCFunctionObject* f = (PyCFunctionObject*)func; + PyCFunction meth = f->m_ml->ml_meth; + Py_ssize_t size; + switch (f->m_ml->ml_flags & (METH_VARARGS | METH_KEYWORDS | METH_NOARGS | METH_O)) { + case METH_VARARGS: + if (likely(kw == NULL || PyDict_Size(kw) == 0)) + return (*meth)(self, arg); + break; + case METH_VARARGS | METH_KEYWORDS: + return (*(PyCFunctionWithKeywords)(void*)meth)(self, arg, kw); + case METH_NOARGS: + if (likely(kw == NULL || PyDict_Size(kw) == 0)) { + size = PyTuple_GET_SIZE(arg); + if (likely(size == 0)) + return (*meth)(self, NULL); + PyErr_Format(PyExc_TypeError, + "%.200s() takes no arguments (%" CYTHON_FORMAT_SSIZE_T "d given)", + f->m_ml->ml_name, size); + return NULL; + } + break; + case METH_O: + if (likely(kw == NULL || PyDict_Size(kw) == 0)) { + size = PyTuple_GET_SIZE(arg); + if (likely(size == 1)) { + PyObject *result, *arg0; + #if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS + arg0 = PyTuple_GET_ITEM(arg, 0); + #else + arg0 = PySequence_ITEM(arg, 0); if (unlikely(!arg0)) return NULL; + #endif + result = (*meth)(self, arg0); + #if !(CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS) + Py_DECREF(arg0); + #endif + return result; + } + PyErr_Format(PyExc_TypeError, + "%.200s() takes exactly one argument (%" CYTHON_FORMAT_SSIZE_T "d given)", + f->m_ml->ml_name, size); + return NULL; + } + break; + default: + PyErr_SetString(PyExc_SystemError, "Bad call flags in " + "__Pyx_CyFunction_Call. METH_OLDARGS is no " + "longer supported!"); + return NULL; + } + PyErr_Format(PyExc_TypeError, "%.200s() takes no keyword arguments", + f->m_ml->ml_name); + return NULL; +} +static CYTHON_INLINE PyObject *__Pyx_CyFunction_Call(PyObject *func, PyObject *arg, PyObject *kw) { + return __Pyx_CyFunction_CallMethod(func, ((PyCFunctionObject*)func)->m_self, arg, kw); +} +static PyObject *__Pyx_CyFunction_CallAsMethod(PyObject *func, PyObject *args, PyObject *kw) { + PyObject *result; + __pyx_CyFunctionObject *cyfunc = (__pyx_CyFunctionObject *) func; + if ((cyfunc->flags & __Pyx_CYFUNCTION_CCLASS) && !(cyfunc->flags & __Pyx_CYFUNCTION_STATICMETHOD)) { + Py_ssize_t argc; + PyObject *new_args; + PyObject *self; + argc = PyTuple_GET_SIZE(args); + new_args = PyTuple_GetSlice(args, 1, argc); + if (unlikely(!new_args)) + return NULL; + self = PyTuple_GetItem(args, 0); + if (unlikely(!self)) { + Py_DECREF(new_args); + return NULL; + } + result = __Pyx_CyFunction_CallMethod(func, self, new_args, kw); + Py_DECREF(new_args); + } else { + result = __Pyx_CyFunction_Call(func, args, kw); + } + return result; +} +static PyTypeObject __pyx_CyFunctionType_type = { + PyVarObject_HEAD_INIT(0, 0) + "cython_function_or_method", + sizeof(__pyx_CyFunctionObject), + 0, + (destructor) __Pyx_CyFunction_dealloc, + 0, + 0, + 0, +#if PY_MAJOR_VERSION < 3 + 0, +#else + 0, +#endif + (reprfunc) __Pyx_CyFunction_repr, + 0, + 0, + 0, + 0, + __Pyx_CyFunction_CallAsMethod, + 0, + 0, + 0, + 0, + Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC, + 0, + (traverseproc) __Pyx_CyFunction_traverse, + (inquiry) __Pyx_CyFunction_clear, + 0, +#if PY_VERSION_HEX < 0x030500A0 + offsetof(__pyx_CyFunctionObject, func_weakreflist), +#else + offsetof(PyCFunctionObject, m_weakreflist), +#endif + 0, + 0, + __pyx_CyFunction_methods, + __pyx_CyFunction_members, + __pyx_CyFunction_getsets, + 0, + 0, + __Pyx_CyFunction_descr_get, + 0, + offsetof(__pyx_CyFunctionObject, func_dict), + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, +#if PY_VERSION_HEX >= 0x030400a1 + 0, +#endif +#if PY_VERSION_HEX >= 0x030800b1 + 0, +#endif +#if PY_VERSION_HEX >= 0x030800b4 && PY_VERSION_HEX < 0x03090000 + 0, +#endif +}; +static int __pyx_CyFunction_init(void) { + __pyx_CyFunctionType = __Pyx_FetchCommonType(&__pyx_CyFunctionType_type); + if (unlikely(__pyx_CyFunctionType == NULL)) { + return -1; + } + return 0; +} +static CYTHON_INLINE void *__Pyx_CyFunction_InitDefaults(PyObject *func, size_t size, int pyobjects) { + __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; + m->defaults = PyObject_Malloc(size); + if (unlikely(!m->defaults)) + return PyErr_NoMemory(); + memset(m->defaults, 0, size); + m->defaults_pyobjects = pyobjects; + return m->defaults; +} +static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsTuple(PyObject *func, PyObject *tuple) { + __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; + m->defaults_tuple = tuple; + Py_INCREF(tuple); +} +static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsKwDict(PyObject *func, PyObject *dict) { + __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; + m->defaults_kwdict = dict; + Py_INCREF(dict); +} +static CYTHON_INLINE void __Pyx_CyFunction_SetAnnotationsDict(PyObject *func, PyObject *dict) { + __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; + m->func_annotations = dict; + Py_INCREF(dict); +} + +/* CLineInTraceback */ +#ifndef CYTHON_CLINE_IN_TRACEBACK +static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line) { + PyObject *use_cline; + PyObject *ptype, *pvalue, *ptraceback; +#if CYTHON_COMPILING_IN_CPYTHON + PyObject **cython_runtime_dict; +#endif + if (unlikely(!__pyx_cython_runtime)) { + return c_line; + } + __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); +#if CYTHON_COMPILING_IN_CPYTHON + cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime); + if (likely(cython_runtime_dict)) { + __PYX_PY_DICT_LOOKUP_IF_MODIFIED( + use_cline, *cython_runtime_dict, + __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback)) + } else +#endif + { + PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback); + if (use_cline_obj) { + use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True; + Py_DECREF(use_cline_obj); + } else { + PyErr_Clear(); + use_cline = NULL; + } + } + if (!use_cline) { + c_line = 0; + PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False); + } + else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) { + c_line = 0; + } + __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); + return c_line; +} +#endif + +/* CodeObjectCache */ +static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { + int start = 0, mid = 0, end = count - 1; + if (end >= 0 && code_line > entries[end].code_line) { + return count; + } + while (start < end) { + mid = start + (end - start) / 2; + if (code_line < entries[mid].code_line) { + end = mid; + } else if (code_line > entries[mid].code_line) { + start = mid + 1; + } else { + return mid; + } + } + if (code_line <= entries[mid].code_line) { + return mid; + } else { + return mid + 1; + } +} +static PyCodeObject *__pyx_find_code_object(int code_line) { + PyCodeObject* code_object; + int pos; + if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { + return NULL; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { + return NULL; + } + code_object = __pyx_code_cache.entries[pos].code_object; + Py_INCREF(code_object); + return code_object; +} +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { + int pos, i; + __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; + if (unlikely(!code_line)) { + return; + } + if (unlikely(!entries)) { + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); + if (likely(entries)) { + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = 64; + __pyx_code_cache.count = 1; + entries[0].code_line = code_line; + entries[0].code_object = code_object; + Py_INCREF(code_object); + } + return; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { + PyCodeObject* tmp = entries[pos].code_object; + entries[pos].code_object = code_object; + Py_DECREF(tmp); + return; + } + if (__pyx_code_cache.count == __pyx_code_cache.max_count) { + int new_max = __pyx_code_cache.max_count + 64; + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( + __pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry)); + if (unlikely(!entries)) { + return; + } + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = new_max; + } + for (i=__pyx_code_cache.count; i>pos; i--) { + entries[i] = entries[i-1]; + } + entries[pos].code_line = code_line; + entries[pos].code_object = code_object; + __pyx_code_cache.count++; + Py_INCREF(code_object); +} + +/* AddTraceback */ +#include "compile.h" +#include "frameobject.h" +#include "traceback.h" +static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( + const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyObject *py_srcfile = 0; + PyObject *py_funcname = 0; + #if PY_MAJOR_VERSION < 3 + py_srcfile = PyString_FromString(filename); + #else + py_srcfile = PyUnicode_FromString(filename); + #endif + if (!py_srcfile) goto bad; + if (c_line) { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + #else + py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + #endif + } + else { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromString(funcname); + #else + py_funcname = PyUnicode_FromString(funcname); + #endif + } + if (!py_funcname) goto bad; + py_code = __Pyx_PyCode_New( + 0, + 0, + 0, + 0, + 0, + __pyx_empty_bytes, /*PyObject *code,*/ + __pyx_empty_tuple, /*PyObject *consts,*/ + __pyx_empty_tuple, /*PyObject *names,*/ + __pyx_empty_tuple, /*PyObject *varnames,*/ + __pyx_empty_tuple, /*PyObject *freevars,*/ + __pyx_empty_tuple, /*PyObject *cellvars,*/ + py_srcfile, /*PyObject *filename,*/ + py_funcname, /*PyObject *name,*/ + py_line, + __pyx_empty_bytes /*PyObject *lnotab*/ + ); + Py_DECREF(py_srcfile); + Py_DECREF(py_funcname); + return py_code; +bad: + Py_XDECREF(py_srcfile); + Py_XDECREF(py_funcname); + return NULL; +} +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyFrameObject *py_frame = 0; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + if (c_line) { + c_line = __Pyx_CLineForTraceback(tstate, c_line); + } + py_code = __pyx_find_code_object(c_line ? -c_line : py_line); + if (!py_code) { + py_code = __Pyx_CreateCodeObjectForTraceback( + funcname, c_line, py_line, filename); + if (!py_code) goto bad; + __pyx_insert_code_object(c_line ? -c_line : py_line, py_code); + } + py_frame = PyFrame_New( + tstate, /*PyThreadState *tstate,*/ + py_code, /*PyCodeObject *code,*/ + __pyx_d, /*PyObject *globals,*/ + 0 /*PyObject *locals*/ + ); + if (!py_frame) goto bad; + __Pyx_PyFrame_SetLineNumber(py_frame, py_line); + PyTraceBack_Here(py_frame); +bad: + Py_XDECREF(py_code); + Py_XDECREF(py_frame); +} + +/* CIntFromPyVerify */ +#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) +#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) +#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ + {\ + func_type value = func_value;\ + if (sizeof(target_type) < sizeof(func_type)) {\ + if (unlikely(value != (func_type) (target_type) value)) {\ + func_type zero = 0;\ + if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ + return (target_type) -1;\ + if (is_unsigned && unlikely(value < zero))\ + goto raise_neg_overflow;\ + else\ + goto raise_overflow;\ + }\ + }\ + return (target_type) value;\ + } + +/* CIntToPy */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_npy_uint64(npy_uint64 value) { + const npy_uint64 neg_one = (npy_uint64) ((npy_uint64) 0 - (npy_uint64) 1), const_zero = (npy_uint64) 0; + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(npy_uint64) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(npy_uint64) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(npy_uint64) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(npy_uint64) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(npy_uint64) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(npy_uint64), + little, !is_unsigned); + } +} + +/* CIntToPy */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { + const int neg_one = (int) ((int) 0 - (int) 1), const_zero = (int) 0; + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(int) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(int) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(int) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(int), + little, !is_unsigned); + } +} + +/* CIntToPy */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { + const long neg_one = (long) ((long) 0 - (long) 1), const_zero = (long) 0; + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(long) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(long) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(long) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(long), + little, !is_unsigned); + } +} + +/* Declarations */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return ::std::complex< float >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return x + y*(__pyx_t_float_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + __pyx_t_float_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ +#if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabsf(b.real) >= fabsf(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + float r = b.imag / b.real; + float s = (float)(1.0) / (b.real + b.imag * r); + return __pyx_t_float_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + float r = b.real / b.imag; + float s = (float)(1.0) / (b.imag + b.real * r); + return __pyx_t_float_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + float denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_float_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrtf(z.real*z.real + z.imag*z.imag); + #else + return hypotf(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + float r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + float denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_float(a, a); + case 3: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, a); + case 4: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = powf(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2f(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_float(a); + theta = atan2f(a.imag, a.real); + } + lnr = logf(r); + z_r = expf(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cosf(z_theta); + z.imag = z_r * sinf(z_theta); + return z; + } + #endif +#endif + +/* Declarations */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return ::std::complex< double >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return x + y*(__pyx_t_double_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + __pyx_t_double_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ +#if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabs(b.real) >= fabs(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + double r = b.imag / b.real; + double s = (double)(1.0) / (b.real + b.imag * r); + return __pyx_t_double_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + double r = b.real / b.imag; + double s = (double)(1.0) / (b.imag + b.real * r); + return __pyx_t_double_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + double denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_double_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrt(z.real*z.real + z.imag*z.imag); + #else + return hypot(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + double r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + double denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_double(a, a); + case 3: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, a); + case 4: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = pow(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_double(a); + theta = atan2(a.imag, a.real); + } + lnr = log(r); + z_r = exp(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cos(z_theta); + z.imag = z_r * sin(z_theta); + return z; + } + #endif +#endif + +/* CIntToPy */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value) { + const enum NPY_TYPES neg_one = (enum NPY_TYPES) ((enum NPY_TYPES) 0 - (enum NPY_TYPES) 1), const_zero = (enum NPY_TYPES) 0; + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(enum NPY_TYPES) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(enum NPY_TYPES) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(enum NPY_TYPES) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(enum NPY_TYPES), + little, !is_unsigned); + } +} + +/* CIntFromPy */ +static CYTHON_INLINE size_t __Pyx_PyInt_As_size_t(PyObject *x) { + const size_t neg_one = (size_t) ((size_t) 0 - (size_t) 1), const_zero = (size_t) 0; + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(size_t) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(size_t, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (size_t) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (size_t) 0; + case 1: __PYX_VERIFY_RETURN_INT(size_t, digit, digits[0]) + case 2: + if (8 * sizeof(size_t) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) >= 2 * PyLong_SHIFT) { + return (size_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(size_t) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) >= 3 * PyLong_SHIFT) { + return (size_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(size_t) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) >= 4 * PyLong_SHIFT) { + return (size_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (size_t) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(size_t) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(size_t, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(size_t) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(size_t, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (size_t) 0; + case -1: __PYX_VERIFY_RETURN_INT(size_t, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(size_t, digit, +digits[0]) + case -2: + if (8 * sizeof(size_t) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) - 1 > 2 * PyLong_SHIFT) { + return (size_t) (((size_t)-1)*(((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(size_t) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) - 1 > 2 * PyLong_SHIFT) { + return (size_t) ((((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(size_t) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) - 1 > 3 * PyLong_SHIFT) { + return (size_t) (((size_t)-1)*(((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(size_t) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) - 1 > 3 * PyLong_SHIFT) { + return (size_t) ((((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(size_t) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) - 1 > 4 * PyLong_SHIFT) { + return (size_t) (((size_t)-1)*(((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(size_t) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(size_t) - 1 > 4 * PyLong_SHIFT) { + return (size_t) ((((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); + } + } + break; + } +#endif + if (sizeof(size_t) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(size_t, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(size_t) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(size_t, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + size_t val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (size_t) -1; + } + } else { + size_t val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (size_t) -1; + val = __Pyx_PyInt_As_size_t(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to size_t"); + return (size_t) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to size_t"); + return (size_t) -1; +} + +/* CIntFromPy */ +static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { + const int neg_one = (int) ((int) 0 - (int) 1), const_zero = (int) 0; + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(int) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (int) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { + return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { + return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { + return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (int) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(int) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) + case -2: + if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + } +#endif + if (sizeof(int) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + int val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (int) -1; + } + } else { + int val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (int) -1; + val = __Pyx_PyInt_As_int(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to int"); + return (int) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to int"); + return (int) -1; +} + +/* CIntFromPy */ +static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { + const long neg_one = (long) ((long) 0 - (long) 1), const_zero = (long) 0; + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(long) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (long) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { + return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { + return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { + return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (long) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(long) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) + case -2: + if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + } +#endif + if (sizeof(long) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + long val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (long) -1; + } + } else { + long val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (long) -1; + val = __Pyx_PyInt_As_long(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to long"); + return (long) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to long"); + return (long) -1; +} + +/* FastTypeChecks */ +#if CYTHON_COMPILING_IN_CPYTHON +static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) { + while (a) { + a = a->tp_base; + if (a == b) + return 1; + } + return b == &PyBaseObject_Type; +} +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) { + PyObject *mro; + if (a == b) return 1; + mro = a->tp_mro; + if (likely(mro)) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(mro); + for (i = 0; i < n; i++) { + if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b) + return 1; + } + return 0; + } + return __Pyx_InBases(a, b); +} +#if PY_MAJOR_VERSION == 2 +static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) { + PyObject *exception, *value, *tb; + int res; + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + __Pyx_ErrFetch(&exception, &value, &tb); + res = exc_type1 ? PyObject_IsSubclass(err, exc_type1) : 0; + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + if (!res) { + res = PyObject_IsSubclass(err, exc_type2); + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + } + __Pyx_ErrRestore(exception, value, tb); + return res; +} +#else +static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) { + int res = exc_type1 ? __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type1) : 0; + if (!res) { + res = __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2); + } + return res; +} +#endif +static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + assert(PyExceptionClass_Check(exc_type)); + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; ip) { + #if PY_MAJOR_VERSION < 3 + if (t->is_unicode) { + *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); + } else if (t->intern) { + *t->p = PyString_InternFromString(t->s); + } else { + *t->p = PyString_FromStringAndSize(t->s, t->n - 1); + } + #else + if (t->is_unicode | t->is_str) { + if (t->intern) { + *t->p = PyUnicode_InternFromString(t->s); + } else if (t->encoding) { + *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); + } else { + *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); + } + } else { + *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); + } + #endif + if (!*t->p) + return -1; + if (PyObject_Hash(*t->p) == -1) + return -1; + ++t; + } + return 0; +} + +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { + return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); +} +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) { + Py_ssize_t ignore; + return __Pyx_PyObject_AsStringAndSize(o, &ignore); +} +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +#if !CYTHON_PEP393_ENABLED +static const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + char* defenc_c; + PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); + if (!defenc) return NULL; + defenc_c = PyBytes_AS_STRING(defenc); +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + { + char* end = defenc_c + PyBytes_GET_SIZE(defenc); + char* c; + for (c = defenc_c; c < end; c++) { + if ((unsigned char) (*c) >= 128) { + PyUnicode_AsASCIIString(o); + return NULL; + } + } + } +#endif + *length = PyBytes_GET_SIZE(defenc); + return defenc_c; +} +#else +static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL; +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + if (likely(PyUnicode_IS_ASCII(o))) { + *length = PyUnicode_GET_LENGTH(o); + return PyUnicode_AsUTF8(o); + } else { + PyUnicode_AsASCIIString(o); + return NULL; + } +#else + return PyUnicode_AsUTF8AndSize(o, length); +#endif +} +#endif +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT + if ( +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + __Pyx_sys_getdefaultencoding_not_ascii && +#endif + PyUnicode_Check(o)) { + return __Pyx_PyUnicode_AsStringAndSize(o, length); + } else +#endif +#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) + if (PyByteArray_Check(o)) { + *length = PyByteArray_GET_SIZE(o); + return PyByteArray_AS_STRING(o); + } else +#endif + { + char* result; + int r = PyBytes_AsStringAndSize(o, &result, length); + if (unlikely(r < 0)) { + return NULL; + } else { + return result; + } + } +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { + int is_true = x == Py_True; + if (is_true | (x == Py_False) | (x == Py_None)) return is_true; + else return PyObject_IsTrue(x); +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject* x) { + int retval; + if (unlikely(!x)) return -1; + retval = __Pyx_PyObject_IsTrue(x); + Py_DECREF(x); + return retval; +} +static PyObject* __Pyx_PyNumber_IntOrLongWrongResultType(PyObject* result, const char* type_name) { +#if PY_MAJOR_VERSION >= 3 + if (PyLong_Check(result)) { + if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1, + "__int__ returned non-int (type %.200s). " + "The ability to return an instance of a strict subclass of int " + "is deprecated, and may be removed in a future version of Python.", + Py_TYPE(result)->tp_name)) { + Py_DECREF(result); + return NULL; + } + return result; + } +#endif + PyErr_Format(PyExc_TypeError, + "__%.4s__ returned non-%.4s (type %.200s)", + type_name, type_name, Py_TYPE(result)->tp_name); + Py_DECREF(result); + return NULL; +} +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { +#if CYTHON_USE_TYPE_SLOTS + PyNumberMethods *m; +#endif + const char *name = NULL; + PyObject *res = NULL; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x) || PyLong_Check(x))) +#else + if (likely(PyLong_Check(x))) +#endif + return __Pyx_NewRef(x); +#if CYTHON_USE_TYPE_SLOTS + m = Py_TYPE(x)->tp_as_number; + #if PY_MAJOR_VERSION < 3 + if (m && m->nb_int) { + name = "int"; + res = m->nb_int(x); + } + else if (m && m->nb_long) { + name = "long"; + res = m->nb_long(x); + } + #else + if (likely(m && m->nb_int)) { + name = "int"; + res = m->nb_int(x); + } + #endif +#else + if (!PyBytes_CheckExact(x) && !PyUnicode_CheckExact(x)) { + res = PyNumber_Int(x); + } +#endif + if (likely(res)) { +#if PY_MAJOR_VERSION < 3 + if (unlikely(!PyInt_Check(res) && !PyLong_Check(res))) { +#else + if (unlikely(!PyLong_CheckExact(res))) { +#endif + return __Pyx_PyNumber_IntOrLongWrongResultType(res, name); + } + } + else if (!PyErr_Occurred()) { + PyErr_SetString(PyExc_TypeError, + "an integer is required"); + } + return res; +} +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { + Py_ssize_t ival; + PyObject *x; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(b))) { + if (sizeof(Py_ssize_t) >= sizeof(long)) + return PyInt_AS_LONG(b); + else + return PyInt_AsSsize_t(b); + } +#endif + if (likely(PyLong_CheckExact(b))) { + #if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)b)->ob_digit; + const Py_ssize_t size = Py_SIZE(b); + if (likely(__Pyx_sst_abs(size) <= 1)) { + ival = likely(size) ? digits[0] : 0; + if (size == -1) ival = -ival; + return ival; + } else { + switch (size) { + case 2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + } + } + #endif + return PyLong_AsSsize_t(b); + } + x = PyNumber_Index(b); + if (!x) return -1; + ival = PyInt_AsSsize_t(x); + Py_DECREF(x); + return ival; +} +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b) { + return b ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False); +} +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { + return PyInt_FromSize_t(ival); +} + + +#endif /* Py_PYTHON_H */ diff --git a/gklearn/gedlib/gedlibpy.cpython-36m-x86_64-linux-gnu.so b/gklearn/gedlib/gedlibpy.cpython-36m-x86_64-linux-gnu.so new file mode 100644 index 0000000..e950062 Binary files /dev/null and b/gklearn/gedlib/gedlibpy.cpython-36m-x86_64-linux-gnu.so differ diff --git a/gklearn/gedlib/gedlibpy.pyx b/gklearn/gedlib/gedlibpy.pyx new file mode 100644 index 0000000..288a056 --- /dev/null +++ b/gklearn/gedlib/gedlibpy.pyx @@ -0,0 +1,1548 @@ +# distutils: language = c++ + +""" + Python GedLib module + ====================== + + This module allow to use a C++ library for edit distance between graphs (GedLib) with Python. + + + Authors + ------------------- + + David Blumenthal + Natacha Lambert + Linlin Jia + + Copyright (C) 2019-2020 by all the authors + + Classes & Functions + ------------------- + +""" + +################################# +##DECLARATION OF C++ INTERFACES## +################################# + + +#Types imports for C++ compatibility +from libcpp.vector cimport vector +from libcpp.string cimport string +from libcpp.map cimport map +from libcpp cimport bool +from libcpp.pair cimport pair +from libcpp.list cimport list + +#Long unsigned int equivalent +cimport numpy as np +ctypedef np.npy_uint32 UINT32_t +from cpython cimport array + + +cdef extern from "src/GedLibBind.hpp" namespace "pyged": + + cdef vector[string] getEditCostStringOptions() except + + cdef vector[string] getMethodStringOptions() except + + cdef vector[string] getInitStringOptions() except + + cdef size_t getDummyNode() except + + + cdef cppclass PyGEDEnv: + PyGEDEnv() except + + bool isInitialized() except + + void restartEnv() except + + void loadGXLGraph(string pathFolder, string pathXML, bool node_type, bool edge_type) except + + pair[size_t,size_t] getGraphIds() except + + vector[size_t] getAllGraphIds() except + + string getGraphClass(size_t id) except + + string getGraphName(size_t id) except + + size_t addGraph(string name, string classe) except + + void addNode(size_t graphId, string nodeId, map[string, string] nodeLabel) except + + void addEdge(size_t graphId, string tail, string head, map[string, string] edgeLabel, bool ignoreDuplicates) except + + void clearGraph(size_t graphId) except + + size_t getGraphInternalId(size_t graphId) except + + size_t getGraphNumNodes(size_t graphId) except + + size_t getGraphNumEdges(size_t graphId) except + + vector[string] getGraphOriginalNodeIds(size_t graphId) except + + vector[map[string, string]] getGraphNodeLabels(size_t graphId) except + + map[pair[size_t, size_t], map[string, string]] getGraphEdges(size_t graphId) except + + vector[vector[size_t]] getGraphAdjacenceMatrix(size_t graphId) except + + void setEditCost(string editCost, vector[double] editCostConstant) except + + void setPersonalEditCost(vector[double] editCostConstant) except + + void initEnv(string initOption, bool print_to_stdout) except + + void setMethod(string method, string options) except + + void initMethod() except + + double getInitime() except + + void runMethod(size_t g, size_t h) except + + double getUpperBound(size_t g, size_t h) except + + double getLowerBound(size_t g, size_t h) except + + vector[np.npy_uint64] getForwardMap(size_t g, size_t h) except + + vector[np.npy_uint64] getBackwardMap(size_t g, size_t h) except + + size_t getNodeImage(size_t g, size_t h, size_t nodeId) except + + size_t getNodePreImage(size_t g, size_t h, size_t nodeId) except + + double getInducedCost(size_t g, size_t h) except + + vector[pair[size_t,size_t]] getNodeMap(size_t g, size_t h) except + + vector[vector[int]] getAssignmentMatrix(size_t g, size_t h) except + + vector[vector[np.npy_uint64]] getAllMap(size_t g, size_t h) except + + double getRuntime(size_t g, size_t h) except + + bool quasimetricCosts() except + + vector[vector[size_t]] hungarianLSAP(vector[vector[size_t]] matrixCost) except + + vector[vector[double]] hungarianLSAPE(vector[vector[double]] matrixCost) except + + # added by Linlin Jia. + size_t getNumNodeLabels() except + + map[string, string] getNodeLabel(size_t label_id) except + + size_t getNumEdgeLabels() except + + map[string, string] getEdgeLabel(size_t label_id) except + +# size_t getNumNodes(size_t graph_id) except + + double getAvgNumNodes() except + + double getNodeRelCost(map[string, string] & node_label_1, map[string, string] & node_label_2) except + + double getNodeDelCost(map[string, string] & node_label) except + + double getNodeInsCost(map[string, string] & node_label) except + + map[string, string] getMedianNodeLabel(vector[map[string, string]] & node_labels) except + + double getEdgeRelCost(map[string, string] & edge_label_1, map[string, string] & edge_label_2) except + + double getEdgeDelCost(map[string, string] & edge_label) except + + double getEdgeInsCost(map[string, string] & edge_label) except + + map[string, string] getMedianEdgeLabel(vector[map[string, string]] & edge_labels) except + + string getInitType() except + +# double getNodeCost(size_t label1, size_t label2) except + + void computeInducedCost(size_t g_id, size_t h_id) except + + + +############################# +##CYTHON WRAPPER INTERFACES## +############################# + +import networkx as nx + +# import librariesImport +from ctypes import * +import os +lib1 = cdll.LoadLibrary(os.path.dirname(os.path.realpath(__file__)) + '/lib/fann/libdoublefann.so') +lib2 = cdll.LoadLibrary(os.path.dirname(os.path.realpath(__file__)) + '/lib/libsvm.3.22/libsvm.so') +lib3 = cdll.LoadLibrary(os.path.dirname(os.path.realpath(__file__)) + '/lib/nomad/libnomad.so') +lib4 = cdll.LoadLibrary(os.path.dirname(os.path.realpath(__file__)) + '/lib/nomad/libsgtelib.so') + + +def get_edit_cost_options() : + """ + Searchs the differents edit cost functions and returns the result. + + :return: The list of edit cost functions + :rtype: list[string] + + .. warning:: This function is useless for an external use. Please use directly list_of_edit_cost_options. + .. note:: Prefer the list_of_edit_cost_options attribute of this module. + """ + + return [option.decode('utf-8') for option in getEditCostStringOptions()] + + +def get_method_options() : + """ + Searchs the differents method for edit distance computation between graphs and returns the result. + + :return: The list of method to compute the edit distance between graphs + :rtype: list[string] + + .. warning:: This function is useless for an external use. Please use directly list_of_method_options. + .. note:: Prefer the list_of_method_options attribute of this module. + """ + return [option.decode('utf-8') for option in getMethodStringOptions()] + + +def get_init_options() : + """ + Searchs the differents initialization parameters for the environment computation for graphs and returns the result. + + :return: The list of options to initialize the computation environment + :rtype: list[string] + + .. warning:: This function is useless for an external use. Please use directly list_of_init_options. + .. note:: Prefer the list_of_init_options attribute of this module. + """ + return [option.decode('utf-8') for option in getInitStringOptions()] + + +def get_dummy_node() : + """ + Returns the ID of a dummy node. + + :return: The ID of the dummy node (18446744073709551614 for my computer, the hugest number possible) + :rtype: size_t + + .. note:: A dummy node is used when a node isn't associated to an other node. + """ + return getDummyNode() + + +cdef class GEDEnv: + """Cython wrapper class for C++ class PyGEDEnv + """ + # cdef PyGEDEnv c_env # Hold a C++ instance which we're wrapping + cdef PyGEDEnv* c_env # hold a pointer to the C++ instance which we're wrapping + + + def __cinit__(self): + self.c_env = new PyGEDEnv() + + + def __dealloc__(self): + del self.c_env + + + def is_initialized(self) : + """ + Checks and returns if the computation environment is initialized or not. + + :return: True if it's initialized, False otherwise + :rtype: bool + + .. note:: This function exists for internals verifications but you can use it for your code. + """ + return self.c_env.isInitialized() + + + def restart_env(self) : + """ + Restarts the environment variable. All data related to it will be delete. + + .. warning:: This function deletes all graphs, computations and more so make sure you don't need anymore your environment. + .. note:: You can now delete and add somes graphs after initialization so you can avoid this function. + """ + self.c_env.restartEnv() + + + def load_GXL_graphs(self, path_folder, path_XML, node_type, edge_type) : + """ + Loads some GXL graphes on the environment which is in a same folder, and present in the XMLfile. + + :param path_folder: The folder's path which contains GXL graphs + :param path_XML: The XML's path which indicates which graphes you want to load + :param node_type: Select if nodes are labeled or unlabeled + :param edge_type: Select if edges are labeled or unlabeled + :type path_folder: string + :type path_XML: string + :type node_type: bool + :type edge_type: bool + + + .. note:: You can call this function multiple times if you want, but not after an init call. + """ + self.c_env.loadGXLGraph(path_folder.encode('utf-8'), path_XML.encode('utf-8'), node_type, edge_type) + + + def graph_ids(self) : + """ + Searchs the first and last IDs of the loaded graphs in the environment. + + :return: The pair of the first and the last graphs Ids + :rtype: tuple(size_t, size_t) + + .. note:: Prefer this function if you have huges structures with lots of graphs. + """ + return self.c_env.getGraphIds() + + + def get_all_graph_ids(self) : + """ + Searchs all the IDs of the loaded graphs in the environment. + + :return: The list of all graphs's Ids + :rtype: list[size_t] + + .. note:: The last ID is equal to (number of graphs - 1). The order correspond to the loading order. + """ + return self.c_env.getAllGraphIds() + + + def get_graph_class(self, id) : + """ + Returns the class of a graph with its ID. + + :param id: The ID of the wanted graph + :type id: size_t + :return: The class of the graph which correpond to the ID + :rtype: string + + .. seealso:: get_graph_class() + .. note:: An empty string can be a class. + """ + return self.c_env.getGraphClass(id) + + + def get_graph_name(self, id) : + """ + Returns the name of a graph with its ID. + + :param id: The ID of the wanted graph + :type id: size_t + :return: The name of the graph which correpond to the ID + :rtype: string + + .. seealso:: get_graph_class() + .. note:: An empty string can be a name. + """ + return self.c_env.getGraphName(id).decode('utf-8') + + + def add_graph(self, name="", classe="") : + """ + Adds a empty graph on the environment, with its name and its class. Nodes and edges will be add in a second time. + + :param name: The name of the new graph, an empty string by default + :param classe: The class of the new graph, an empty string by default + :type name: string + :type classe: string + :return: The ID of the newly graphe + :rtype: size_t + + .. seealso::add_node(), add_edge() , add_symmetrical_edge() + .. note:: You can call this function without parameters. You can also use this function after initialization, call init() after you're finished your modifications. + """ + return self.c_env.addGraph(name.encode('utf-8'), classe.encode('utf-8')) + + + def add_node(self, graph_id, node_id, node_label): + """ + Adds a node on a graph selected by its ID. A ID and a label for the node is required. + + :param graph_id: The ID of the wanted graph + :param node_id: The ID of the new node + :param node_label: The label of the new node + :type graph_id: size_t + :type node_id: string + :type node_label: dict{string : string} + + .. seealso:: add_graph(), add_edge(), add_symmetrical_edge() + .. note:: You can also use this function after initialization, but only on a newly added graph. Call init() after you're finished your modifications. + """ + self.c_env.addNode(graph_id, node_id.encode('utf-8'), encode_your_map(node_label)) + + + def add_edge(self, graph_id, tail, head, edge_label, ignore_duplicates=True) : + """ + Adds an edge on a graph selected by its ID. + + :param graph_id: The ID of the wanted graph + :param tail: The ID of the tail node for the new edge + :param head: The ID of the head node for the new edge + :param edge_label: The label of the new edge + :param ignore_duplicates: If True, duplicate edges are ignored, otherwise it's raise an error if an existing edge is added. True by default + :type graph_id: size_t + :type tail: string + :type head: string + :type edge_label: dict{string : string} + :type ignore_duplicates: bool + + .. seealso:: add_graph(), add_node(), add_symmetrical_edge() + .. note:: You can also use this function after initialization, but only on a newly added graph. Call init() after you're finished your modifications. + """ + self.c_env.addEdge(graph_id, tail.encode('utf-8'), head.encode('utf-8'), encode_your_map(edge_label), ignore_duplicates) + + + def add_symmetrical_edge(self, graph_id, tail, head, edge_label) : + """ + Adds a symmetrical edge on a graph selected by its ID. + + :param graph_id: The ID of the wanted graph + :param tail: The ID of the tail node for the new edge + :param head: The ID of the head node for the new edge + :param edge_label: The label of the new edge + :type graph_id: size_t + :type tail: string + :type head: string + :type edge_label: dict{string : string} + + .. seealso:: add_graph(), add_node(), add_edge() + .. note:: You can also use this function after initialization, but only on a newly added graph. Call init() after you're finished your modifications. + """ + tailB = tail.encode('utf-8') + headB = head.encode('utf-8') + edgeLabelB = encode_your_map(edge_label) + self.c_env.addEdge(graph_id, tailB, headB, edgeLabelB, True) + self.c_env.addEdge(graph_id, headB, tailB, edgeLabelB, True) + + + def clear_graph(self, graph_id) : + """ + Deletes a graph, selected by its ID, to the environment. + + :param graph_id: The ID of the wanted graph + :type graph_id: size_t + + .. note:: Call init() after you're finished your modifications. + """ + self.c_env.clearGraph(graph_id) + + + def get_graph_internal_id(self, graph_id) : + """ + Searchs and returns the internal Id of a graph, selected by its ID. + + :param graph_id: The ID of the wanted graph + :type graph_id: size_t + :return: The internal ID of the selected graph + :rtype: size_t + + .. seealso:: get_graph_num_nodes(), get_graph_num_edges(), get_original_node_ids(), get_graph_node_labels(), get_graph_edges(), get_graph_adjacence_matrix() + .. note:: These functions allow to collect all the graph's informations. + """ + return self.c_env.getGraphInternalId(graph_id) + + + def get_graph_num_nodes(self, graph_id) : + """ + Searchs and returns the number of nodes on a graph, selected by its ID. + + :param graph_id: The ID of the wanted graph + :type graph_id: size_t + :return: The number of nodes on the selected graph + :rtype: size_t + + .. seealso:: get_graph_internal_id(), get_graph_num_edges(), get_original_node_ids(), get_graph_node_labels(), get_graph_edges(), get_graph_adjacence_matrix() + .. note:: These functions allow to collect all the graph's informations. + """ + return self.c_env.getGraphNumNodes(graph_id) + + + def get_graph_num_edges(self, graph_id) : + """ + Searchs and returns the number of edges on a graph, selected by its ID. + + :param graph_id: The ID of the wanted graph + :type graph_id: size_t + :return: The number of edges on the selected graph + :rtype: size_t + + .. seealso:: get_graph_internal_id(), get_graph_num_nodes(), get_original_node_ids(), get_graph_node_labels(), get_graph_edges(), get_graph_adjacence_matrix() + .. note:: These functions allow to collect all the graph's informations. + """ + return self.c_env.getGraphNumEdges(graph_id) + + + def get_original_node_ids(self, graph_id) : + """ + Searchs and returns all th Ids of nodes on a graph, selected by its ID. + + :param graph_id: The ID of the wanted graph + :type graph_id: size_t + :return: The list of IDs's nodes on the selected graph + :rtype: list[string] + + .. seealso::get_graph_internal_id(), get_graph_num_nodes(), get_graph_num_edges(), get_graph_node_labels(), get_graph_edges(), get_graph_adjacence_matrix() + .. note:: These functions allow to collect all the graph's informations. + """ + return [gid.decode('utf-8') for gid in self.c_env.getGraphOriginalNodeIds(graph_id)] + + + def get_graph_node_labels(self, graph_id) : + """ + Searchs and returns all the labels of nodes on a graph, selected by its ID. + + :param graph_id: The ID of the wanted graph + :type graph_id: size_t + :return: The list of nodes' labels on the selected graph + :rtype: list[dict{string : string}] + + .. seealso:: get_graph_internal_id(), get_graph_num_nodes(), get_graph_num_edges(), get_original_node_ids(), get_graph_edges(), get_graph_adjacence_matrix() + .. note:: These functions allow to collect all the graph's informations. + """ + return [decode_your_map(node_label) for node_label in self.c_env.getGraphNodeLabels(graph_id)] + + + def get_graph_edges(self, graph_id) : + """ + Searchs and returns all the edges on a graph, selected by its ID. + + :param graph_id: The ID of the wanted graph + :type graph_id: size_t + :return: The list of edges on the selected graph + :rtype: dict{tuple(size_t, size_t) : dict{string : string}} + + .. seealso::get_graph_internal_id(), get_graph_num_nodes(), get_graph_num_edges(), get_original_node_ids(), get_graph_node_labels(), get_graph_adjacence_matrix() + .. note:: These functions allow to collect all the graph's informations. + """ + return decode_graph_edges(self.c_env.getGraphEdges(graph_id)) + + + def get_graph_adjacence_matrix(self, graph_id) : + """ + Searchs and returns the adjacence list of a graph, selected by its ID. + + :param graph_id: The ID of the wanted graph + :type graph_id: size_t + :return: The adjacence list of the selected graph + :rtype: list[list[size_t]] + + .. seealso:: get_graph_internal_id(), get_graph_num_nodes(), get_graph_num_edges(), get_original_node_ids(), get_graph_node_labels(), get_graph_edges() + .. note:: These functions allow to collect all the graph's informations. + """ + return self.c_env.getGraphAdjacenceMatrix(graph_id) + + + def set_edit_cost(self, edit_cost, edit_cost_constant = []) : + """ + Sets an edit cost function to the environment, if it exists. + + :param edit_cost: The name of the edit cost function + :type edit_cost: string + :param edi_cost_constant: The parameters you will add to the editCost, empty by default + :type edit_cost_constant: list + + .. seealso:: list_of_edit_cost_options + .. note:: Try to make sure the edit cost function exists with list_of_edit_cost_options, raise an error otherwise. + """ + if edit_cost in list_of_edit_cost_options: + edit_cost_b = edit_cost.encode('utf-8') + self.c_env.setEditCost(edit_cost_b, edit_cost_constant) + else: + raise EditCostError("This edit cost function doesn't exist, please see list_of_edit_cost_options for selecting a edit cost function") + + + def set_personal_edit_cost(self, edit_cost_constant = []) : + """ + Sets an personal edit cost function to the environment. + + :param edit_cost_constant: The parameters you will add to the editCost, empty by default + :type edit_cost_constant: list + + .. seealso:: list_of_edit_cost_options, set_edit_cost() + .. note::You have to modify the C++ function to use it. Please see the documentation to add your Edit Cost function. + """ + self.c_env.setPersonalEditCost(edit_cost_constant) + + + def init(self, init_option='EAGER_WITHOUT_SHUFFLED_COPIES', print_to_stdout=False) : + """ + Initializes the environment with the chosen edit cost function and graphs. + + :param init_option: The name of the init option, "EAGER_WITHOUT_SHUFFLED_COPIES" by default + :type init_option: string + + .. seealso:: list_of_init_options + .. warning:: No modification were allowed after initialization. Try to make sure your choices is correct. You can though clear or add a graph, but recall init() after that. + .. note:: Try to make sure the option exists with list_of_init_options or choose no options, raise an error otherwise. + """ + if init_option in list_of_init_options: + init_option_b = init_option.encode('utf-8') + self.c_env.initEnv(init_option_b, print_to_stdout) + else: + raise InitError("This init option doesn't exist, please see list_of_init_options for selecting an option. You can choose any options.") + + + def set_method(self, method, options="") : + """ + Sets a computation method to the environment, if its exists. + + :param method: The name of the computation method + :param options: The options of the method (like bash options), an empty string by default + :type method: string + :type options: string + + .. seealso:: init_method(), list_of_method_options + .. note:: Try to make sure the edit cost function exists with list_of_method_options, raise an error otherwise. Call init_method() after your set. + """ + if method in list_of_method_options: + method_b = method.encode('utf-8') + self.c_env.setMethod(method_b, options.encode('utf-8')) + else: + raise MethodError("This method doesn't exist, please see list_of_method_options for selecting a method") + + + def init_method(self) : + """ + Inits the environment with the set method. + + .. seealso:: set_method(), list_of_method_options + .. note:: Call this function after set the method. You can't launch computation or change the method after that. + """ + self.c_env.initMethod() + + + def get_init_time(self) : + """ + Returns the initialization time. + + :return: The initialization time + :rtype: double + """ + return self.c_env.getInitime() + + + def run_method(self, g, h) : + """ + Computes the edit distance between two graphs g and h, with the edit cost function and method computation selected. + + :param g: The Id of the first graph to compare + :param h: The Id of the second graph to compare + :type g: size_t + :type h: size_t + + .. seealso:: get_upper_bound(), get_lower_bound(), get_forward_map(), get_backward_map(), get_runtime(), quasimetric_cost() + .. note:: This function only compute the distance between two graphs, without returning a result. Use the differents function to see the result between the two graphs. + """ + self.c_env.runMethod(g, h) + + + def get_upper_bound(self, g, h) : + """ + Returns the upper bound of the edit distance cost between two graphs g and h. + + :param g: The Id of the first compared graph + :param h: The Id of the second compared graph + :type g: size_t + :type h: size_t + :return: The upper bound of the edit distance cost + :rtype: double + + .. seealso:: run_method(), get_lower_bound(), get_forward_map(), get_backward_map(), get_runtime(), quasimetric_cost() + .. warning:: run_method() between the same two graph must be called before this function. + .. note:: The upper bound is equivalent to the result of the pessimist edit distance cost. Methods are heuristics so the library can't compute the real perfect result because it's NP-Hard problem. + """ + return self.c_env.getUpperBound(g, h) + + + def get_lower_bound(self, g, h) : + """ + Returns the lower bound of the edit distance cost between two graphs g and h. + + :param g: The Id of the first compared graph + :param h: The Id of the second compared graph + :type g: size_t + :type h: size_t + :return: The lower bound of the edit distance cost + :rtype: double + + .. seealso:: run_method(), get_upper_bound(), get_forward_map(), get_backward_map(), get_runtime(), quasimetric_cost() + .. warning:: run_method() between the same two graph must be called before this function. + .. note:: This function can be ignored, because lower bound doesn't have a crucial utility. + """ + return self.c_env.getLowerBound(g, h) + + + def get_forward_map(self, g, h) : + """ + Returns the forward map (or the half of the adjacence matrix) between nodes of the two indicated graphs. + + :param g: The Id of the first compared graph + :param h: The Id of the second compared graph + :type g: size_t + :type h: size_t + :return: The forward map to the adjacence matrix between nodes of the two graphs + :rtype: list[npy_uint32] + + .. seealso:: run_method(), get_upper_bound(), get_lower_bound(), get_backward_map(), get_runtime(), quasimetric_cost(), get_node_map(), get_assignment_matrix() + .. warning:: run_method() between the same two graph must be called before this function. + .. note:: I don't know how to connect the two map to reconstruct the adjacence matrix. Please come back when I know how it's work ! + """ + return self.c_env.getForwardMap(g, h) + + + def get_backward_map(self, g, h) : + """ + Returns the backward map (or the half of the adjacence matrix) between nodes of the two indicated graphs. + + :param g: The Id of the first compared graph + :param h: The Id of the second compared graph + :type g: size_t + :type h: size_t + :return: The backward map to the adjacence matrix between nodes of the two graphs + :rtype: list[npy_uint32] + + .. seealso:: run_method(), get_upper_bound(), get_lower_bound(), get_forward_map(), get_runtime(), quasimetric_cost(), get_node_map(), get_assignment_matrix() + .. warning:: run_method() between the same two graph must be called before this function. + .. note:: I don't know how to connect the two map to reconstruct the adjacence matrix. Please come back when I know how it's work ! + """ + return self.c_env.getBackwardMap(g, h) + + + def get_node_image(self, g, h, node_id) : + """ + Returns the node's image in the adjacence matrix, if it exists. + + :param g: The Id of the first compared graph + :param h: The Id of the second compared graph + :param node_id: The ID of the node which you want to see the image + :type g: size_t + :type h: size_t + :type node_id: size_t + :return: The ID of the image node + :rtype: size_t + + .. seealso:: run_method(), get_forward_map(), get_backward_map(), get_node_pre_image(), get_node_map(), get_assignment_matrix() + .. warning:: run_method() between the same two graph must be called before this function. + .. note:: Use BackwardMap's Node to find its images ! You can also use get_forward_map() and get_backward_map(). + + """ + return self.c_env.getNodeImage(g, h, node_id) + + + def get_node_pre_image(self, g, h, node_id) : + """ + Returns the node's preimage in the adjacence matrix, if it exists. + + :param g: The Id of the first compared graph + :param h: The Id of the second compared graph + :param node_id: The ID of the node which you want to see the preimage + :type g: size_t + :type h: size_t + :type node_id: size_t + :return: The ID of the preimage node + :rtype: size_t + + .. seealso:: run_method(), get_forward_map(), get_backward_map(), get_node_image(), get_node_map(), get_assignment_matrix() + .. warning:: run_method() between the same two graph must be called before this function. + .. note:: Use ForwardMap's Node to find its images ! You can also use get_forward_map() and get_backward_map(). + + """ + return self.c_env.getNodePreImage(g, h, node_id) + + + def get_induced_cost(self, g, h) : + """ + Returns the induced cost between the two indicated graphs. + + :param g: The Id of the first compared graph + :param h: The Id of the second compared graph + :type g: size_t + :type h: size_t + :return: The induced cost between the two indicated graphs + :rtype: double + + .. seealso:: run_method(), get_forward_map(), get_backward_map(), get_node_image(), get_node_map(), get_assignment_matrix() + .. warning:: run_method() between the same two graph must be called before this function. + .. note:: Use ForwardMap's Node to find its images ! You can also use get_forward_map() and get_backward_map(). + + """ + return self.c_env.getInducedCost(g, h) + + + def get_node_map(self, g, h) : + """ + Returns the Node Map, like C++ NodeMap. + + :param g: The Id of the first compared graph + :param h: The Id of the second compared graph + :type g: size_t + :type h: size_t + :return: The Node Map between the two selected graph. + :rtype: list[tuple(size_t, size_t)] + + .. seealso:: run_method(), get_forward_map(), get_backward_map(), get_node_image(), get_node_pre_image(), get_assignment_matrix() + .. warning:: run_method() between the same two graph must be called before this function. + .. note:: This function creates datas so use it if necessary, however you can understand how assignement works with this example. + """ + return self.c_env.getNodeMap(g, h) + + + def get_assignment_matrix(self, g, h) : + """ + Returns the Assignment Matrix between two selected graphs g and h. + + :param g: The Id of the first compared graph + :param h: The Id of the second compared graph + :type g: size_t + :type h: size_t + :return: The Assignment Matrix between the two selected graph. + :rtype: list[list[int]] + + .. seealso:: run_method(), get_forward_map(), get_backward_map(), get_node_image(), get_node_pre_image(), get_node_map() + .. warning:: run_method() between the same two graph must be called before this function. + .. note:: This function creates datas so use it if necessary. + """ + return self.c_env.getAssignmentMatrix(g, h) + + + def get_all_map(self, g, h) : + """ + Returns a vector which contains the forward and the backward maps between nodes of the two indicated graphs. + + :param g: The Id of the first compared graph + :param h: The Id of the second compared graph + :type g: size_t + :type h: size_t + :return: The forward and backward maps to the adjacence matrix between nodes of the two graphs + :rtype: list[list[npy_uint32]] + + .. seealso:: run_method(), get_upper_bound(), get_lower_bound(), get_forward_map(), get_backward_map(), get_runtime(), quasimetric_cost() + .. warning:: run_method() between the same two graph must be called before this function. + .. note:: This function duplicates data so please don't use it. I also don't know how to connect the two map to reconstruct the adjacence matrix. Please come back when I know how it's work ! + """ + return self.c_env.getAllMap(g, h) + + + def get_runtime(self, g, h) : + """ + Returns the runtime to compute the edit distance cost between two graphs g and h + + :param g: The Id of the first compared graph + :param h: The Id of the second compared graph + :type g: size_t + :type h: size_t + :return: The runtime of the computation of edit distance cost between the two selected graphs + :rtype: double + + .. seealso:: run_method(), get_upper_bound(), get_lower_bound(), get_forward_map(), get_backward_map(), quasimetric_cost() + .. warning:: run_method() between the same two graph must be called before this function. + .. note:: Python is a bit longer than C++ due to the functions's encapsulate. + """ + return self.c_env.getRuntime(g,h) + + + def quasimetric_cost(self) : + """ + Checks and returns if the edit costs are quasimetric. + + :param g: The Id of the first compared graph + :param h: The Id of the second compared graph + :type g: size_t + :type h: size_t + :return: True if it's verified, False otherwise + :rtype: bool + + .. seealso:: run_method(), get_upper_bound(), get_lower_bound(), get_forward_map(), get_backward_map(), get_runtime() + .. warning:: run_method() between the same two graph must be called before this function. + """ + return self.c_env.quasimetricCosts() + + + def hungarian_LSAP(self, matrix_cost) : + """ + Applies the hungarian algorithm (LSAP) on a matrix Cost. + + :param matrix_cost: The matrix Cost + :type matrix_cost: vector[vector[size_t]] + :return: The values of rho, varrho, u and v, in this order + :rtype: vector[vector[size_t]] + + .. seealso:: hungarian_LSAPE() + """ + return self.c_env.hungarianLSAP(matrix_cost) + + + def hungarian_LSAPE(self, matrix_cost) : + """ + Applies the hungarian algorithm (LSAPE) on a matrix Cost. + + :param matrix_cost: The matrix Cost + :type matrix_cost: vector[vector[double]] + :return: The values of rho, varrho, u and v, in this order + :rtype: vector[vector[double]] + + .. seealso:: hungarian_LSAP() + """ + return self.c_env.hungarianLSAPE(matrix_cost) + + + def add_random_graph(self, name, classe, list_of_nodes, list_of_edges, ignore_duplicates=True) : + """ + Add a Graph (not GXL) on the environment. Be careful to respect the same format as GXL graphs for labelling nodes and edges. + + :param name: The name of the graph to add, can be an empty string + :param classe: The classe of the graph to add, can be an empty string + :param list_of_nodes: The list of nodes to add + :param list_of_edges: The list of edges to add + :param ignore_duplicates: If True, duplicate edges are ignored, otherwise it's raise an error if an existing edge is added. True by default + :type name: string + :type classe: string + :type list_of_nodes: list[tuple(size_t, dict{string : string})] + :type list_of_edges: list[tuple(tuple(size_t,size_t), dict{string : string})] + :type ignore_duplicates: bool + :return: The ID of the newly added graphe + :rtype: size_t + + .. note:: The graph must respect the GXL structure. Please see how a GXL graph is construct. + + """ + id = self.add_graph(name, classe) + for node in list_of_nodes: + self.add_node(id, node[0], node[1]) + for edge in list_of_edges: + self.add_edge(id, edge[0], edge[1], edge[2], ignore_duplicates) + return id + + + def add_nx_graph(self, g, classe, ignore_duplicates=True) : + """ + Add a Graph (made by networkx) on the environment. Be careful to respect the same format as GXL graphs for labelling nodes and edges. + + :param g: The graph to add (networkx graph) + :param ignore_duplicates: If True, duplicate edges are ignored, otherwise it's raise an error if an existing edge is added. True by default + :type g: networkx.graph + :type ignore_duplicates: bool + :return: The ID of the newly added graphe + :rtype: size_t + + .. note:: The NX graph must respect the GXL structure. Please see how a GXL graph is construct. + + """ + id = self.add_graph(g.name, classe) + for node in g.nodes: + self.add_node(id, str(node), g.nodes[node]) + for edge in g.edges: + self.add_edge(id, str(edge[0]), str(edge[1]), g.get_edge_data(edge[0], edge[1]), ignore_duplicates) + return id + + + def compute_ged_on_two_graphs(self, g1, g2, edit_cost, method, options, init_option="EAGER_WITHOUT_SHUFFLED_COPIES") : + """ + Computes the edit distance between two NX graphs. + + :param g1: The first graph to add and compute + :param g2: The second graph to add and compute + :param edit_cost: The name of the edit cost function + :param method: The name of the computation method + :param options: The options of the method (like bash options), an empty string by default + :param init_option: The name of the init option, "EAGER_WITHOUT_SHUFFLED_COPIES" by default + :type g1: networksx.graph + :type g2: networksx.graph + :type edit_cost: string + :type method: string + :type options: string + :type init_option: string + :return: The edit distance between the two graphs and the nodeMap between them. + :rtype: double, list[tuple(size_t, size_t)] + + .. seealso:: list_of_edit_cost_options, list_of_method_options, list_of_init_options + .. note:: Make sure each parameter exists with your architecture and these lists : list_of_edit_cost_options, list_of_method_options, list_of_init_options. The structure of graphs must be similar as GXL. + + """ + if self.is_initialized() : + self.restart_env() + + g = self.add_nx_graph(g1, "") + h = self.add_nx_graph(g2, "") + + self.set_edit_cost(edit_cost) + self.init(init_option) + + self.set_method(method, options) + self.init_method() + + resDistance = 0 + resMapping = [] + self.run_method(g, h) + resDistance = self.get_upper_bound(g, h) + resMapping = self.get_node_map(g, h) + + return resDistance, resMapping + + + def compute_edit_distance_on_nx_graphs(self, dataset, classes, edit_cost, method, options, init_option="EAGER_WITHOUT_SHUFFLED_COPIES") : + """ + + Computes all the edit distance between each NX graphs on the dataset. + + :param dataset: The list of graphs to add and compute + :param classes: The classe of all the graph, can be an empty string + :param edit_cost: The name of the edit cost function + :param method: The name of the computation method + :param options: The options of the method (like bash options), an empty string by default + :param init_option: The name of the init option, "EAGER_WITHOUT_SHUFFLED_COPIES" by default + :type dataset: list[networksx.graph] + :type classes: string + :type edit_cost: string + :type method: string + :type options: string + :type init_option: string + :return: Two matrix, the first with edit distances between graphs and the second the nodeMap between graphs. The result between g and h is one the [g][h] coordinates. + :rtype: list[list[double]], list[list[list[tuple(size_t, size_t)]]] + + .. seealso:: list_of_edit_cost_options, list_of_method_options, list_of_init_options + .. note:: Make sure each parameter exists with your architecture and these lists : list_of_edit_cost_options, list_of_method_options, list_of_init_options. The structure of graphs must be similar as GXL. + + """ + if self.is_initialized() : + self.restart_env() + + print("Loading graphs in progress...") + for graph in dataset : + self.add_nx_graph(graph, classes) + listID = self.graph_ids() + print("Graphs loaded ! ") + print("Number of graphs = " + str(listID[1])) + + self.set_edit_cost(edit_cost) + print("Initialization in progress...") + self.init(init_option) + print("Initialization terminated !") + + self.set_method(method, options) + self.init_method() + + resDistance = [[]] + resMapping = [[]] + for g in range(listID[0], listID[1]) : + print("Computation between graph " + str(g) + " with all the others including himself.") + for h in range(listID[0], listID[1]) : + #print("Computation between graph " + str(g) + " and graph " + str(h)) + self.run_method(g, h) + resDistance[g][h] = self.get_upper_bound(g, h) + resMapping[g][h] = self.get_node_map(g, h) + + print("Finish ! The return contains edit distances and NodeMap but you can check the result with graphs'ID until you restart the environment") + return resDistance, resMapping + + + def compute_edit_distance_on_GXl_graphs(self, path_folder, path_XML, edit_cost, method, options="", init_option="EAGER_WITHOUT_SHUFFLED_COPIES") : + """ + Computes all the edit distance between each GXL graphs on the folder and the XMl file. + + :param path_folder: The folder's path which contains GXL graphs + :param path_XML: The XML's path which indicates which graphes you want to load + :param edit_cost: The name of the edit cost function + :param method: The name of the computation method + :param options: The options of the method (like bash options), an empty string by default + :param init_option: The name of the init option, "EAGER_WITHOUT_SHUFFLED_COPIES" by default + :type path_folder: string + :type path_XML: string + :type edit_cost: string + :type method: string + :type options: string + :type init_option: string + :return: The list of the first and last-1 ID of graphs + :rtype: tuple(size_t, size_t) + + .. seealso:: list_of_edit_cost_options, list_of_method_options, list_of_init_options + .. note:: Make sure each parameter exists with your architecture and these lists : list_of_edit_cost_options, list_of_method_options, list_of_init_options. + + """ + + if self.is_initialized() : + self.restart_env() + + print("Loading graphs in progress...") + self.load_GXL_graphs(path_folder, path_XML) + listID = self.graph_ids() + print("Graphs loaded ! ") + print("Number of graphs = " + str(listID[1])) + + self.set_edit_cost(edit_cost) + print("Initialization in progress...") + self.init(init_option) + print("Initialization terminated !") + + self.set_method(method, options) + self.init_method() + + #res = [] + for g in range(listID[0], listID[1]) : + print("Computation between graph " + str(g) + " with all the others including himself.") + for h in range(listID[0], listID[1]) : + #print("Computation between graph " + str(g) + " and graph " + str(h)) + self.run_method(g,h) + #res.append((get_upper_bound(g,h), get_node_map(g,h), get_runtime(g,h))) + + #return res + + print ("Finish ! You can check the result with each ID of graphs ! There are in the return") + print ("Please don't restart the environment or recall this function, you will lose your results !") + return listID + + + def get_num_node_labels(self): + """ + Returns the number of node labels. + + :return: Number of pairwise different node labels contained in the environment. + :rtype: size_t + + .. note:: If 1 is returned, the nodes are unlabeled. + """ + return self.c_env.getNumNodeLabels() + + + def get_node_label(self, label_id): + """ + Returns node label. + + :param label_id: ID of node label that should be returned. Must be between 1 and get_num_node_labels(). + :type label_id: size_t + :return: Node label for selected label ID. + :rtype: dict{string : string} + """ + return decode_your_map(self.c_env.getNodeLabel(label_id)) + + + def get_num_edge_labels(self): + """ + Returns the number of edge labels. + + :return: Number of pairwise different edge labels contained in the environment. + :rtype: size_t + + .. note:: If 1 is returned, the edges are unlabeled. + """ + return self.c_env.getNumEdgeLabels() + + + def get_edge_label(self, label_id): + """ + Returns edge label. + + :param label_id: ID of edge label that should be returned. Must be between 1 and get_num_edge_labels(). + :type label_id: size_t + :return: Edge label for selected label ID. + :rtype: dict{string : string} + """ + return decode_your_map(self.c_env.getEdgeLabel(label_id)) + + +# def get_num_nodes(self, graph_id): +# """ +# Returns the number of nodes. +# +# :param graph_id: ID of an input graph that has been added to the environment. +# :type graph_id: size_t +# :return: Number of nodes in the graph. +# :rtype: size_t +# """ +# return self.c_env.getNumNodes(graph_id) + + def get_avg_num_nodes(self): + """ + Returns average number of nodes. + + :return: Average number of nodes of the graphs contained in the environment. + :rtype: double + """ + return self.c_env.getAvgNumNodes() + + def get_node_rel_cost(self, node_label_1, node_label_2): + """ + Returns node relabeling cost. + + :param node_label_1: First node label. + :param node_label_2: Second node label. + :type node_label_1: dict{string : string} + :type node_label_2: dict{string : string} + :return: Node relabeling cost for the given node labels. + :rtype: double + """ + return self.c_env.getNodeRelCost(encode_your_map(node_label_1), encode_your_map(node_label_2)) + + + def get_node_del_cost(self, node_label): + """ + Returns node deletion cost. + + :param node_label: Node label. + :type node_label: dict{string : string} + :return: Cost of deleting node with given label. + :rtype: double + """ + return self.c_env.getNodeDelCost(encode_your_map(node_label)) + + + def get_node_ins_cost(self, node_label): + """ + Returns node insertion cost. + + :param node_label: Node label. + :type node_label: dict{string : string} + :return: Cost of inserting node with given label. + :rtype: double + """ + return self.c_env.getNodeInsCost(encode_your_map(node_label)) + + + def get_median_node_label(self, node_labels): + """ + Computes median node label. + + :param node_labels: The node labels whose median should be computed. + :type node_labels: list[dict{string : string}] + :return: Median of the given node labels. + :rtype: dict{string : string} + """ + node_labels_b = [encode_your_map(node_label) for node_label in node_labels] + return decode_your_map(self.c_env.getMedianNodeLabel(node_labels_b)) + + + def get_edge_rel_cost(self, edge_label_1, edge_label_2): + """ + Returns edge relabeling cost. + + :param edge_label_1: First edge label. + :param edge_label_2: Second edge label. + :type edge_label_1: dict{string : string} + :type edge_label_2: dict{string : string} + :return: Edge relabeling cost for the given edge labels. + :rtype: double + """ + return self.c_env.getEdgeRelCost(encode_your_map(edge_label_1), encode_your_map(edge_label_2)) + + + def get_edge_del_cost(self, edge_label): + """ + Returns edge deletion cost. + + :param edge_label: Edge label. + :type edge_label: dict{string : string} + :return: Cost of deleting edge with given label. + :rtype: double + """ + return self.c_env.getEdgeDelCost(encode_your_map(edge_label)) + + + def get_edge_ins_cost(self, edge_label): + """ + Returns edge insertion cost. + + :param edge_label: Edge label. + :type edge_label: dict{string : string} + :return: Cost of inserting edge with given label. + :rtype: double + """ + return self.c_env.getEdgeInsCost(encode_your_map(edge_label)) + + + def get_median_edge_label(self, edge_labels): + """ + Computes median edge label. + + :param edge_labels: The edge labels whose median should be computed. + :type edge_labels: list[dict{string : string}] + :return: Median of the given edge labels. + :rtype: dict{string : string} + """ + edge_labels_b = [encode_your_map(edge_label) for edge_label in edge_labels] + return decode_your_map(self.c_env.getMedianEdgeLabel(edge_label_b)) + + + def get_nx_graph(self, graph_id, adj_matrix=True, adj_lists=False, edge_list=False): # @todo + """ + Get graph with id `graph_id` in the form of the NetworkX Graph. + + Parameters + ---------- + graph_id : int + ID of the selected graph. + + adj_matrix : bool + Set to `True` to construct an adjacency matrix `adj_matrix` and a hash-map `edge_labels`, which has a key for each pair `(i,j)` such that `adj_matrix[i][j]` equals 1. No effect for now. + + adj_lists : bool + No effect for now. + + edge_list : bool + No effect for now. + + Returns + ------- + NetworkX Graph object + The obtained graph. + """ + graph = nx.Graph() + graph.graph['id'] = graph_id + + nb_nodes = self.get_graph_num_nodes(graph_id) + original_node_ids = self.get_original_node_ids(graph_id) + node_labels = self.get_graph_node_labels(graph_id) +# print(original_node_ids) +# print(node_labels) + graph.graph['original_node_ids'] = original_node_ids + + for node_id in range(0, nb_nodes): + graph.add_node(node_id, **node_labels[node_id]) +# graph.nodes[node_id]['original_node_id'] = original_node_ids[node_id] + + edges = self.get_graph_edges(graph_id) + for (head, tail), labels in edges.items(): + graph.add_edge(head, tail, **labels) +# print(edges) + + return graph + + + def get_init_type(self): + """ + Returns the initialization type of the last initialization in string. + + Returns + ------- + string + Initialization type in string. + """ + return self.c_env.getInitType().decode('utf-8') + + +# def get_node_cost(self, label1, label2): +# """ +# Returns node relabeling, insertion, or deletion cost. + +# Parameters +# ---------- +# label1 : int +# First node label. +# +# label2 : int +# Second node label. +# +# Returns +# ------- +# Node relabeling cost if `label1` and `label2` are both different from `ged::dummy_label()`, node insertion cost if `label1` equals `ged::dummy_label` and `label2` does not, node deletion cost if `label1` does not equal `ged::dummy_label` and `label2` does, and 0 otherwise. +# """ +# return self.c_env.getNodeCost(label1, label2) + + + def load_nx_graph(self, nx_graph, graph_id, graph_name='', graph_class=''): + """ + Loads NetworkX Graph into the GED environment. + + Parameters + ---------- + nx_graph : NetworkX Graph object + The graph that should be loaded. + + graph_id : int or None + The ID of a graph contained the environment (overwrite existing graph) or add new graph if `None`. + + graph_name : string, optional + The name of newly added graph. The default is ''. Has no effect unless `graph_id` equals `None`. + + graph_class : string, optional + The class of newly added graph. The default is ''. Has no effect unless `graph_id` equals `None`. + + Returns + ------- + int + The ID of the newly loaded graph. + """ + if graph_id is None: + graph_id = self.add_graph(graph_name, graph_class) + else: + self.clear_graph(graph_id) + for node in nx_graph.nodes: + self.add_node(graph_id, str(node), nx_graph.nodes[node]) + for edge in nx_graph.edges: + self.add_edge(graph_id, str(edge[0]), str(edge[1]), nx_graph.get_edge_data(edge[0], edge[1])) + return graph_id + + + def compute_induced_cost(self, g_id, h_id): + """ + Computes the edit cost between two graphs induced by a node map. + + Parameters + ---------- + g_id : int + ID of input graph. + h_id : int + ID of input graph. + + Returns + ------- + None. + + Notes + ----- + The induced edit cost of the node map between `g_id` and `h_id` is implictly computed and stored in `GEDEnv::node_maps_`. + + """ + + cost = 0.0 + self.c_env.computeInducedCost(g_id, h_id) + + +##################################################################### +##LISTS OF EDIT COST FUNCTIONS, METHOD COMPUTATION AND INIT OPTIONS## +##################################################################### + +list_of_edit_cost_options = get_edit_cost_options() +list_of_method_options = get_method_options() +list_of_init_options = get_init_options() + + +##################### +##ERRORS MANAGEMENT## +##################### + +class Error(Exception): + """ + Class for error's management. This one is general. + """ + pass + + +class EditCostError(Error) : + """ + Class for Edit Cost Error. Raise an error if an edit cost function doesn't exist in the library (not in list_of_edit_cost_options). + + :attribute message: The message to print when an error is detected. + :type message: string + """ + def __init__(self, message): + """ + Inits the error with its message. + + :param message: The message to print when the error is detected + :type message: string + """ + self.message = message + + +class MethodError(Error) : + """ + Class for Method Error. Raise an error if a computation method doesn't exist in the library (not in list_of_method_options). + + :attribute message: The message to print when an error is detected. + :type message: string + """ + def __init__(self, message): + """ + Inits the error with its message. + + :param message: The message to print when the error is detected + :type message: string + """ + self.message = message + + +class InitError(Error) : + """ + Class for Init Error. Raise an error if an init option doesn't exist in the library (not in list_of_init_options). + + :attribute message: The message to print when an error is detected. + :type message: string + """ + def __init__(self, message): + """ + Inits the error with its message. + + :param message: The message to print when the error is detected + :type message: string + """ + self.message = message + + +######################################### +##PYTHON FUNCTIONS FOR SOME COMPUTATION## +######################################### + +def encode_your_map(map_u): + """ + Encodes Python unicode strings in dictionnary `map` to utf-8 byte strings for C++ functions. + + :param map_b: The map to encode + :type map_b: dict{string : string} + :return: The encoded map + :rtype: dict{'b'string : 'b'string} + + .. note:: This function is used for type connection. + + """ + res = {} + for key, value in map_u.items(): + res[key.encode('utf-8')] = value.encode('utf-8') + return res + + +def decode_your_map(map_b): + """ + Decodes utf-8 byte strings in `map` from C++ functions to Python unicode strings. + + :param map_b: The map to decode + :type map_b: dict{'b'string : 'b'string} + :return: The decoded map + :rtype: dict{string : string} + + .. note:: This function is used for type connection. + + """ + res = {} + for key, value in map_b.items(): + res[key.decode('utf-8')] = value.decode('utf-8') + return res + + +def decode_graph_edges(map_edge_b): + """ + Decode utf-8 byte strings in graph edges `map` from C++ functions to Python unicode strings. + + Parameters + ---------- + map_edge_b : dict{tuple(size_t, size_t) : dict{'b'string : 'b'string}} + The map to decode. + + Returns + ------- + dict{tuple(size_t, size_t) : dict{string : string}} + The decoded map. + + Notes + ----- + This is a helper function for function `GEDEnv.get_graph_edges()`. + """ + map_edges = {} + for key, value in map_edge_b.items(): + map_edges[key] = decode_your_map(value) + return map_edges + + + + + + + +# cdef extern from "src/GedLibBind.h" namespace "shapes": +# cdef cppclass Rectangle: +# Rectangle() except + +# Rectangle(int, int, int, int) except + +# int x0, y0, x1, y1 +# int getArea() +# void getSize(int* width, int* height) +# void move(int, int) + + +# # Create a Cython extension type which holds a C++ instance +# # as an attribute and create a bunch of forwarding methods +# # Python extension type. +# cdef class PyRectangle: +# cdef Rectangle c_rect # Hold a C++ instance which we're wrapping + +# def __cinit__(self, int x0, int y0, int x1, int y1): +# self.c_rect = Rectangle(x0, y0, x1, y1) + +# def get_area(self): +# return self.c_rect.getArea() + +# def get_size(self): +# cdef int width, height +# self.c_rect.getSize(&width, &height) +# return width, height + +# def move(self, dx, dy): +# self.c_rect.move(dx, dy) + +# # Attribute access +# @property +# def x0(self): +# return self.c_rect.x0 +# @x0.setter +# def x0(self, x0): +# self.c_rect.x0 = x0 + +# # Attribute access +# @property +# def x1(self): +# return self.c_rect.x1 +# @x1.setter +# def x1(self, x1): +# self.c_rect.x1 = x1 + +# # Attribute access +# @property +# def y0(self): +# return self.c_rect.y0 +# @y0.setter +# def y0(self, y0): +# self.c_rect.y0 = y0 + +# # Attribute access +# @property +# def y1(self): +# return self.c_rect.y1 +# @y1.setter +# def y1(self, y1): +# self.c_rect.y1 = y1 \ No newline at end of file diff --git a/gklearn/gedlib/lib/fann/libdoublefann.so b/gklearn/gedlib/lib/fann/libdoublefann.so new file mode 120000 index 0000000..ad9e2a8 --- /dev/null +++ b/gklearn/gedlib/lib/fann/libdoublefann.so @@ -0,0 +1 @@ +libdoublefann.so.2 \ No newline at end of file diff --git a/gklearn/gedlib/lib/fann/libdoublefann.so.2 b/gklearn/gedlib/lib/fann/libdoublefann.so.2 new file mode 120000 index 0000000..8257493 --- /dev/null +++ b/gklearn/gedlib/lib/fann/libdoublefann.so.2 @@ -0,0 +1 @@ +libdoublefann.so.2.2.0 \ No newline at end of file diff --git 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b/gklearn/gedlib/lib/fann/libfixedfann.so new file mode 120000 index 0000000..fe31b6a --- /dev/null +++ b/gklearn/gedlib/lib/fann/libfixedfann.so @@ -0,0 +1 @@ +libfixedfann.so.2 \ No newline at end of file diff --git a/gklearn/gedlib/lib/fann/libfixedfann.so.2 b/gklearn/gedlib/lib/fann/libfixedfann.so.2 new file mode 120000 index 0000000..ab2489f --- /dev/null +++ b/gklearn/gedlib/lib/fann/libfixedfann.so.2 @@ -0,0 +1 @@ +libfixedfann.so.2.2.0 \ No newline at end of file diff --git a/gklearn/gedlib/lib/fann/libfixedfann.so.2.2.0 b/gklearn/gedlib/lib/fann/libfixedfann.so.2.2.0 new file mode 100644 index 0000000..ce43dd3 Binary files /dev/null and b/gklearn/gedlib/lib/fann/libfixedfann.so.2.2.0 differ diff --git a/gklearn/gedlib/lib/fann/libfloatfann.so b/gklearn/gedlib/lib/fann/libfloatfann.so new file mode 120000 index 0000000..936f681 --- /dev/null +++ b/gklearn/gedlib/lib/fann/libfloatfann.so @@ -0,0 +1 @@ +libfloatfann.so.2 \ No newline at end of file diff --git a/gklearn/gedlib/lib/fann/libfloatfann.so.2 b/gklearn/gedlib/lib/fann/libfloatfann.so.2 new file mode 120000 index 0000000..c1b50c7 --- /dev/null +++ b/gklearn/gedlib/lib/fann/libfloatfann.so.2 @@ -0,0 +1 @@ +libfloatfann.so.2.2.0 \ No newline at end of file diff --git a/gklearn/gedlib/lib/fann/libfloatfann.so.2.2.0 b/gklearn/gedlib/lib/fann/libfloatfann.so.2.2.0 new file mode 100644 index 0000000..42af143 Binary files /dev/null and b/gklearn/gedlib/lib/fann/libfloatfann.so.2.2.0 differ diff --git a/gklearn/gedlib/lib/fann/pkgconfig/fann.pc b/gklearn/gedlib/lib/fann/pkgconfig/fann.pc new file mode 100644 index 0000000..a105358 --- /dev/null +++ b/gklearn/gedlib/lib/fann/pkgconfig/fann.pc @@ -0,0 +1,10 @@ +prefix=/export/home/lambertn/Documents/Python_GedLib/include/gedlib-master/ext/fann.2.2.0 +exec_prefix=/export/home/lambertn/Documents/Python_GedLib/include/gedlib-master/ext/fann.2.2.0/bin +libdir=/export/home/lambertn/Documents/Python_GedLib/include/gedlib-master/ext/fann.2.2.0/lib +includedir=/export/home/lambertn/Documents/Python_GedLib/include/gedlib-master/ext/fann.2.2.0/include + +Name: fann +Description: Fast Artificial Neural Network Library +Version: 2.2.0 +Libs: -L${libdir} -lm -lfann +Cflags: -I${includedir} diff --git a/gklearn/gedlib/lib/libsvm.3.22/COPYRIGHT b/gklearn/gedlib/lib/libsvm.3.22/COPYRIGHT new file mode 100644 index 0000000..5fe2f22 --- /dev/null +++ b/gklearn/gedlib/lib/libsvm.3.22/COPYRIGHT @@ -0,0 +1,31 @@ + +Copyright (c) 2000-2014 Chih-Chung Chang and Chih-Jen Lin +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions +are met: + +1. Redistributions of source code must retain the above copyright +notice, this list of conditions and the following disclaimer. + +2. Redistributions in binary form must reproduce the above copyright +notice, this list of conditions and the following disclaimer in the +documentation and/or other materials provided with the distribution. + +3. Neither name of copyright holders nor the names of its contributors +may be used to endorse or promote products derived from this software +without specific prior written permission. + + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS +``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT +LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR +A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR +CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, +EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, +PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR +PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF +LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING +NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS +SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. diff --git a/gklearn/gedlib/lib/libsvm.3.22/FAQ.html b/gklearn/gedlib/lib/libsvm.3.22/FAQ.html new file mode 100644 index 0000000..42a175a --- /dev/null +++ b/gklearn/gedlib/lib/libsvm.3.22/FAQ.html @@ -0,0 +1,2166 @@ + + + + +LIBSVM FAQ + + + +

LIBSVM FAQ

+last modified : +Tue, 20 Oct 2015 13:43:40 GMT + +
  • All Questions(84)
    • + + + + + + +
    +

    + + +Q: Some courses which have used libsvm as a tool +
    +

    +

    +[Go Top] +

    + +Q: Some applications/tools which have used libsvm +
    +(and maybe liblinear). + +

    +[Go Top] +

    + +Q: Where can I find documents/videos of libsvm ? +
    +

    + +

      +
    • +Official implementation document: +
      +C.-C. Chang and +C.-J. Lin. +LIBSVM +: a library for support vector machines. +ACM Transactions on Intelligent +Systems and Technology, 2:27:1--27:27, 2011. +pdf, ps.gz, +ACM digital lib. + + +
    • Instructions for using LIBSVM are in the README files in the main directory and some sub-directories. +
      +README in the main directory: details all options, data format, and library calls. +
      +tools/README: parameter selection and other tools +
    • +A guide for beginners: +
      +C.-W. Hsu, C.-C. Chang, and +C.-J. Lin. + +A practical guide to support vector classification + +
    • An introductory video +for windows users. + +
    +

    +[Go Top] +

    + +Q: Where are change log and earlier versions? +
    +

    See the change log. + +

    You can download earlier versions +here. +

    +[Go Top] +

    + +Q: How to cite LIBSVM? +
    +

    +Please cite the following paper: +

    +Chih-Chung Chang and Chih-Jen Lin, LIBSVM +: a library for support vector machines. +ACM Transactions on Intelligent Systems and Technology, 2:27:1--27:27, 2011. +Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm +

    +The bibtex format is +

    +@article{CC01a,
+ author = {Chang, Chih-Chung and Lin, Chih-Jen},
+ title = {{LIBSVM}: A library for support vector machines},
+ journal = {ACM Transactions on Intelligent Systems and Technology},
+ volume = {2},
+ issue = {3},
+ year = {2011},
+ pages = {27:1--27:27},
+ note =	 {Software available at \url{http://www.csie.ntu.edu.tw/~cjlin/libsvm}}
+}
+
    +

    +[Go Top] +

    + +Q: I would like to use libsvm in my software. Is there any license problem? +
    +

    +We have "the modified BSD license," +so it is very easy to +use libsvm in your software. +Please check the COPYRIGHT file in detail. Basically +you need to +

      +
    1. +Clearly indicate that LIBSVM is used. +
      2. +
    2. +Retain the LIBSVM COPYRIGHT file in your software. +
      3. +
    +It can also be used in commercial products. +

    +[Go Top] +

    + +Q: Is there a repository of additional tools based on libsvm? +
    +

    +Yes, see libsvm +tools +

    +[Go Top] +

    + +Q: On unix machines, I got "error in loading shared libraries" or "cannot open shared object file." What happened ? +
    + +

    +This usually happens if you compile the code +on one machine and run it on another which has incompatible +libraries. +Try to recompile the program on that machine or use static linking. +

    +[Go Top] +

    + +Q: I have modified the source and would like to build the graphic interface "svm-toy" on MS windows. How should I do it ? +
    + +

    +Build it as a project by choosing "Win32 Project." +On the other hand, for "svm-train" and "svm-predict" +you want to choose "Win32 Console Project." +After libsvm 2.5, you can also use the file Makefile.win. +See details in README. + + +

    +If you are not using Makefile.win and see the following +link error +

    +LIBCMTD.lib(wwincrt0.obj) : error LNK2001: unresolved external symbol
+_wWinMain@16
+
    +you may have selected a wrong project type. +

    +[Go Top] +

    + +Q: I am an MS windows user but why only one (svm-toy) of those precompiled .exe actually runs ? +
    + +

    +You need to open a command window +and type svmtrain.exe to see all options. +Some examples are in README file. +

    +[Go Top] +

    + +Q: What is the difference between "." and "*" outputed during training? +
    + +

    +"." means every 1,000 iterations (or every #data +iterations is your #data is less than 1,000). +"*" means that after iterations of using +a smaller shrunk problem, +we reset to use the whole set. See the +implementation document for details. +

    +[Go Top] +

    + +Q: Why occasionally the program (including MATLAB or other interfaces) crashes and gives a segmentation fault? +
    + +

    +Very likely the program consumes too much memory than what the +operating system can provide. Try a smaller data and see if the +program still crashes. +

    +[Go Top] +

    + +Q: How to build a dynamic library (.dll file) on MS windows? +
    +

    + +The easiest way is to use Makefile.win. +See details in README. + +Alternatively, you can use Visual C++. Here is +the example using Visual Studio 2013: +

      +
    1. Create a Win32 empty DLL project and set (in Project->$Project_Name +Properties...->Configuration) to "Release." + About how to create a new dynamic link library, please refer to +http://msdn2.microsoft.com/en-us/library/ms235636(VS.80).aspx + +
    2. Add svm.cpp, svm.h to your project. +
    3. Add __WIN32__ and _CRT_SECURE_NO_DEPRECATE to Preprocessor definitions (in +Project->$Project_Name Properties...->C/C++->Preprocessor) +
    4. Set Create/Use Precompiled Header to Not Using Precompiled Headers +(in Project->$Project_Name Properties...->C/C++->Precompiled Headers) +
    5. Set the path for the Modulation Definition File svm.def (in +Project->$Project_Name Properties...->Linker->input +
    6. Build the DLL. +
    7. Rename the dll file to libsvm.dll and move it to the correct path. +
    + + +

    +[Go Top] +

    + +Q: On some systems (e.g., Ubuntu), compiling LIBSVM gives many warning messages. Is this a problem and how to disable the warning message? +
    + +

    +If you are using a version before 3.18, probably you see +a warning message like +

    +svm.cpp:2730: warning: ignoring return value of int fscanf(FILE*, const char*, ...), declared with attribute warn_unused_result
+
    +This is not a problem; see this page for more +details of ubuntu systems. +To disable the warning message you can replace +
    +CFLAGS = -Wall -Wconversion -O3 -fPIC
+
    +with +
    +CFLAGS = -Wall -Wconversion -O3 -fPIC -U_FORTIFY_SOURCE
+
    +in Makefile. +

    After version 3.18, we have a better setting so that such warning messages do not appear. +

    +[Go Top] +

    + +Q: In LIBSVM, why you don't use certain C/C++ library functions to make the code shorter? +
    + +

    +For portability, we use only features defined in ISO C89. Note that features in ISO C99 may not be available everywhere. +Even the newest gcc lacks some features in C99 (see http://gcc.gnu.org/c99status.html for details). +If the situation changes in the future, +we might consider using these newer features. +

    +[Go Top] +

    + +Q: Why sometimes not all attributes of a data appear in the training/model files ? +
    +

    +libsvm uses the so called "sparse" format where zero +values do not need to be stored. Hence a data with attributes +

    +1 0 2 0
+
    +is represented as +
    +1:1 3:2
+
    +

    +[Go Top] +

    + +Q: What if my data are non-numerical ? +
    +

    +Currently libsvm supports only numerical data. +You may have to change non-numerical data to +numerical. For example, you can use several +binary attributes to represent a categorical +attribute. +

    +[Go Top] +

    + +Q: Why do you consider sparse format ? Will the training of dense data be much slower ? +
    +

    +This is a controversial issue. The kernel +evaluation (i.e. inner product) of sparse vectors is slower +so the total training time can be at least twice or three times +of that using the dense format. +However, we cannot support only dense format as then we CANNOT +handle extremely sparse cases. Simplicity of the code is another +concern. Right now we decide to support +the sparse format only. +

    +[Go Top] +

    + +Q: Why sometimes the last line of my data is not read by svm-train? +
    + +

    +We assume that you have '\n' in the end of +each line. So please press enter in the end +of your last line. +

    +[Go Top] +

    + +Q: Is there a program to check if my data are in the correct format? +
    + +

    +The svm-train program in libsvm conducts only a simple check of the input data. To do a +detailed check, after libsvm 2.85, you can use the python script tools/checkdata.py. See tools/README for details. +

    +[Go Top] +

    + +Q: May I put comments in data files? +
    + +

    +We don't officially support this. But, currently LIBSVM +is able to process data in the following +format: +

    +1 1:2 2:1 # your comments
+
    +Note that the character ":" should not appear in your +comments. + +

    +[Go Top] +

    + +Q: How to convert other data formats to LIBSVM format? +
    + +

    +It depends on your data format. A simple way is to use +libsvmwrite in the libsvm matlab/octave interface. + +Take a CSV (comma-separated values) file +in UCI machine learning repository as an example. +We download SPECTF.train. +Labels are in the first column. The following steps produce +a file in the libsvm format. +

    +matlab> SPECTF = csvread('SPECTF.train'); % read a csv file
+matlab> labels = SPECTF(:, 1); % labels from the 1st column
+matlab> features = SPECTF(:, 2:end); 
+matlab> features_sparse = sparse(features); % features must be in a sparse matrix
+matlab> libsvmwrite('SPECTFlibsvm.train', labels, features_sparse);
+
    +The tranformed data are stored in SPECTFlibsvm.train. + +

    +Alternatively, you can use convert.c +to convert CSV format to libsvm format. +

    +[Go Top] +

    + +Q: The output of training C-SVM is like the following. What do they mean? +
    +
    optimization finished, #iter = 219 +
    nu = 0.431030 +
    obj = -100.877286, rho = 0.424632 +
    nSV = 132, nBSV = 107 +
    Total nSV = 132 +

    +obj is the optimal objective value of the dual SVM problem. +rho is the bias term in the decision function +sgn(w^Tx - rho). +nSV and nBSV are number of support vectors and bounded support +vectors (i.e., alpha_i = C). nu-svm is a somewhat equivalent +form of C-SVM where C is replaced by nu. nu simply shows the +corresponding parameter. More details are in + +libsvm document. +

    +[Go Top] +

    + +Q: Can you explain more about the model file? +
    + +

    +In the model file, after parameters and other informations such as labels , each line represents a support vector. +Support vectors are listed in the order of "labels" shown earlier. +(i.e., those from the first class in the "labels" list are +grouped first, and so on.) +If k is the total number of classes, +in front of a support vector in class j, there are +k-1 coefficients +y*alpha where alpha are dual solution of the +following two class problems: +
    +1 vs j, 2 vs j, ..., j-1 vs j, j vs j+1, j vs j+2, ..., j vs k +
    +and y=1 in first j-1 coefficients, y=-1 in the remaining +k-j coefficients. + +For example, if there are 4 classes, the file looks like: + +

    ++-+-+-+--------------------+
+|1|1|1|                    |
+|v|v|v|  SVs from class 1  |
+|2|3|4|                    |
++-+-+-+--------------------+
+|1|2|2|                    |
+|v|v|v|  SVs from class 2  |
+|2|3|4|                    |
++-+-+-+--------------------+
+|1|2|3|                    |
+|v|v|v|  SVs from class 3  |
+|3|3|4|                    |
++-+-+-+--------------------+
+|1|2|3|                    |
+|v|v|v|  SVs from class 4  |
+|4|4|4|                    |
++-+-+-+--------------------+
+
    +See also + an illustration using +MATLAB/OCTAVE. +

    +[Go Top] +

    + +Q: Should I use float or double to store numbers in the cache ? +
    + +

    +We have float as the default as you can store more numbers +in the cache. +In general this is good enough but for few difficult +cases (e.g. C very very large) where solutions are huge +numbers, it might be possible that the numerical precision is not +enough using only float. +

    +[Go Top] +

    + +Q: Does libsvm have special treatments for linear SVM? +
    + +

    + +No, libsvm solves linear/nonlinear SVMs by the +same way. +Some tricks may save training/testing time if the +linear kernel is used, +so libsvm is NOT particularly efficient for linear SVM, +especially when +C is large and +the number of data is much larger +than the number of attributes. +You can either +

    + +

    Please also see our SVM guide +on the discussion of using RBF and linear +kernels. +

    +[Go Top] +

    + +Q: The number of free support vectors is large. What should I do? +
    +

    +This usually happens when the data are overfitted. +If attributes of your data are in large ranges, +try to scale them. Then the region +of appropriate parameters may be larger. +Note that there is a scale program +in libsvm. +

    +[Go Top] +

    + +Q: Should I scale training and testing data in a similar way? +
    +

    +Yes, you can do the following: +

    +> svm-scale -s scaling_parameters train_data > scaled_train_data
+> svm-scale -r scaling_parameters test_data > scaled_test_data
+
    +

    +[Go Top] +

    + +Q: On windows sometimes svm-scale.exe generates some non-ASCII data not good for training/prediction? +
    +

    +In general this does not happen, but we have observed in some rare +situations, the output of svm-scale.exe directed to a file (by ">") +has wrong encoding. That is, the file is not an ASCII file, so cannot be +used for training/prediction. Please let us know if this happens as at this moment +we don't clearly see how to fix the problem. +

    +[Go Top] +

    + +Q: Does it make a big difference if I scale each attribute to [0,1] instead of [-1,1]? +
    + +

    +For the linear scaling method, if the RBF kernel is +used and parameter selection is conducted, there +is no difference. Assume Mi and mi are +respectively the maximal and minimal values of the +ith attribute. Scaling to [0,1] means +

    +                x'=(x-mi)/(Mi-mi)
+
    +For [-1,1], +
    +                x''=2(x-mi)/(Mi-mi)-1.
+
    +In the RBF kernel, +
    +                x'-y'=(x-y)/(Mi-mi), x''-y''=2(x-y)/(Mi-mi).
+
    +Hence, using (C,g) on the [0,1]-scaled data is the +same as (C,g/2) on the [-1,1]-scaled data. + +

    Though the performance is the same, the computational +time may be different. For data with many zero entries, +[0,1]-scaling keeps the sparsity of input data and hence +may save the time. +

    +[Go Top] +

    + +Q: The prediction rate is low. How could I improve it? +
    +

    +Try to use the model selection tool grid.py in the tools +directory find +out good parameters. To see the importance of model selection, +please +see our guide for beginners: + +A practical guide to support vector +classification + +

    +[Go Top] +

    + +Q: My data are unbalanced. Could libsvm handle such problems? +
    +

    +Yes, there is a -wi options. For example, if you use +

    +> svm-train -s 0 -c 10 -w1 1 -w-1 5 data_file
+
    +

    +the penalty for class "-1" is larger. +Note that this -w option is for C-SVC only. +

    +[Go Top] +

    + +Q: What is the difference between nu-SVC and C-SVC? +
    +

    +Basically they are the same thing but with different +parameters. The range of C is from zero to infinity +but nu is always between [0,1]. A nice property +of nu is that it is related to the ratio of +support vectors and the ratio of the training +error. +

    +[Go Top] +

    + +Q: The program keeps running (without showing any output). What should I do? +
    +

    +You may want to check your data. Each training/testing +data must be in one line. It cannot be separated. +In addition, you have to remove empty lines. +

    +[Go Top] +

    + +Q: The program keeps running (with output, i.e. many dots). What should I do? +
    +

    +In theory libsvm guarantees to converge. +Therefore, this means you are +handling ill-conditioned situations +(e.g. too large/small parameters) so numerical +difficulties occur. +

    +You may get better numerical stability by replacing +

    +typedef float Qfloat;
+
    +in svm.cpp with +
    +typedef double Qfloat;
+
    +That is, elements in the kernel cache are stored +in double instead of single. However, this means fewer elements +can be put in the kernel cache. +

    +[Go Top] +

    + +Q: The training time is too long. What should I do? +
    +

    +For large problems, please specify enough cache size (i.e., +-m). +Slow convergence may happen for some difficult cases (e.g. -c is large). +You can try to use a looser stopping tolerance with -e. +If that still doesn't work, you may train only a subset of the data. +You can use the program subset.py in the directory "tools" +to obtain a random subset. + +

    +If you have extremely large data and face this difficulty, please +contact us. We will be happy to discuss possible solutions. + +

    When using large -e, you may want to check if -h 0 (no shrinking) or -h 1 (shrinking) is faster. +See a related question below. + +

    +[Go Top] +

    + +Q: Does shrinking always help? +
    +

    +If the number of iterations is high, then shrinking +often helps. +However, if the number of iterations is small +(e.g., you specify a large -e), then +probably using -h 0 (no shrinking) is better. +See the +implementation document for details. +

    +[Go Top] +

    + +Q: How do I get the decision value(s)? +
    +

    +We print out decision values for regression. For classification, +we solve several binary SVMs for multi-class cases. You +can obtain values by easily calling the subroutine +svm_predict_values. Their corresponding labels +can be obtained from svm_get_labels. +Details are in +README of libsvm package. + +

    +If you are using MATLAB/OCTAVE interface, svmpredict can directly +give you decision values. Please see matlab/README for details. + +

    +We do not recommend the following. But if you would +like to get values for +TWO-class classification with labels +1 and -1 +(note: +1 and -1 but not things like 5 and 10) +in the easiest way, simply add +

    +		printf("%f\n", dec_values[0]*model->label[0]);
+
    +after the line +
    +		svm_predict_values(model, x, dec_values);
+
    +of the file svm.cpp. +Positive (negative) +decision values correspond to data predicted as +1 (-1). + + +

    +[Go Top] +

    + +Q: How do I get the distance between a point and the hyperplane? +
    +

    +The distance is |decision_value| / |w|. +We have |w|^2 = w^Tw = alpha^T Q alpha = 2*(dual_obj + sum alpha_i). +Thus in svm.cpp please find the place +where we calculate the dual objective value +(i.e., the subroutine Solve()) +and add a statement to print w^Tw. + +More precisely, here is what you need to do +

      +
    1. Search for "calculate objective value" in svm.cpp +
      2. +
    2. In that place, si->obj is the variable for the objective value +
      3. +
    3. Add a for loop to calculate the sum of alpha +
      4. +
    4. Calculate 2*(si->obj + sum of alpha) and print the square root of it. You now get |w|. You +need to recompile the code +
      5. +
    5. Check an earlier FAQ on printing decision values. You +need to recompile the code +
      6. +
    6. +Then print decision value divided by the |w| value obtained earlier. +
      7. +
    +

    +[Go Top] +

    + +Q: On 32-bit machines, if I use a large cache (i.e. large -m) on a linux machine, why sometimes I get "segmentation fault ?" +
    +

    + +On 32-bit machines, the maximum addressable +memory is 4GB. The Linux kernel uses 3:1 +split which means user space is 3G and +kernel space is 1G. Although there are +3G user space, the maximum dynamic allocation +memory is 2G. So, if you specify -m near 2G, +the memory will be exhausted. And svm-train +will fail when it asks more memory. +For more details, please read + +this article. +

    +The easiest solution is to switch to a + 64-bit machine. +Otherwise, there are two ways to solve this. If your +machine supports Intel's PAE (Physical Address +Extension), you can turn on the option HIGHMEM64G +in Linux kernel which uses 4G:4G split for +kernel and user space. If you don't, you can +try a software `tub' which can eliminate the 2G +boundary for dynamic allocated memory. The `tub' +is available at +http://www.bitwagon.com/tub.html. + + + +

    +[Go Top] +

    + +Q: How do I disable screen output of svm-train? +
    +

    +For commend-line users, use the -q option: +

    +> ./svm-train -q heart_scale
+
    +

    +For library users, set the global variable +

    +extern void (*svm_print_string) (const char *);
+
    +to specify the output format. You can disable the output by the following steps: +
      +
    1. +Declare a function to output nothing: +
      +void print_null(const char *s) {}
+
      +
      2. +
    2. +Assign the output function of libsvm by +
      +svm_print_string = &print_null;
+
      +
      3. +
    +Finally, a way used in earlier libsvm +is by updating svm.cpp from +
    +#if 1
+void info(const char *fmt,...)
+
    +to +
    +#if 0
+void info(const char *fmt,...)
+
    +

    +[Go Top] +

    + +Q: I would like to use my own kernel. Any example? In svm.cpp, there are two subroutines for kernel evaluations: k_function() and kernel_function(). Which one should I modify ? +
    +

    +An example is "LIBSVM for string data" in LIBSVM Tools. +

    +The reason why we have two functions is as follows. +For the RBF kernel exp(-g |xi - xj|^2), if we calculate +xi - xj first and then the norm square, there are 3n operations. +Thus we consider exp(-g (|xi|^2 - 2dot(xi,xj) +|xj|^2)) +and by calculating all |xi|^2 in the beginning, +the number of operations is reduced to 2n. +This is for the training. For prediction we cannot +do this so a regular subroutine using that 3n operations is +needed. + +The easiest way to have your own kernel is +to put the same code in these two +subroutines by replacing any kernel. +

    +[Go Top] +

    + +Q: What method does libsvm use for multi-class SVM ? Why don't you use the "1-against-the rest" method? +
    +

    +It is one-against-one. We chose it after doing the following +comparison: +C.-W. Hsu and C.-J. Lin. + +A comparison of methods +for multi-class support vector machines +, +IEEE Transactions on Neural Networks, 13(2002), 415-425. + +

    +"1-against-the rest" is a good method whose performance +is comparable to "1-against-1." We do the latter +simply because its training time is shorter. +

    +[Go Top] +

    + +Q: I would like to solve L2-loss SVM (i.e., error term is quadratic). How should I modify the code ? +
    +

    +It is extremely easy. Taking c-svc for example, to solve +

    +min_w w^Tw/2 + C \sum max(0, 1- (y_i w^Tx_i+b))^2, +

    +only two +places of svm.cpp have to be changed. +First, modify the following line of +solve_c_svc from +

    +	s.Solve(l, SVC_Q(*prob,*param,y), minus_ones, y,
+		alpha, Cp, Cn, param->eps, si, param->shrinking);
+
    +to +
    +	s.Solve(l, SVC_Q(*prob,*param,y), minus_ones, y,
+		alpha, INF, INF, param->eps, si, param->shrinking);
+
    +Second, in the class of SVC_Q, declare C as +a private variable: +
    +	double C;
+
    +In the constructor replace +
    +	for(int i=0;i<prob.l;i++)
+		QD[i]= (Qfloat)(this->*kernel_function)(i,i);
+
    +with +
    +        this->C = param.C;
+	for(int i=0;i<prob.l;i++)
+		QD[i]= (Qfloat)(this->*kernel_function)(i,i)+0.5/C;
+
    +Then in the subroutine get_Q, after the for loop, add +
    +        if(i >= start && i < len) 
+		data[i] += 0.5/C;
+
    + +

    +For one-class svm, the modification is exactly the same. For SVR, you don't need an if statement like the above. Instead, you only need a simple assignment: +

    +	data[real_i] += 0.5/C;
+
    + + +

    +For large linear L2-loss SVM, please use +LIBLINEAR. +

    +[Go Top] +

    + +Q: In one-class SVM, parameter nu should be an upper bound of the training error rate. Why sometimes I get a training error rate bigger than nu? +
    + +

    +At optimum, some training instances should satisfy +w^Tx - rho = 0. However, numerically they may be slightly +smaller than zero +Then they are wrongly counted +as training errors. You can use a smaller stopping tolerance +(by the -e option) to make this problem less serious. + +

    +This issue does not occur for nu-SVC for +two-class classification. +We have that +

      +
    1. nu is an upper bound on the ratio of training points +on the wrong side of the hyperplane, and +
    2. therefore, nu is also an upper bound on the training error rate. +
    +Numerical issues occur in calculating the first case +because some training points satisfying y(w^Tx + b) - rho = 0 +become negative. +However, we have no numerical problems for the second case because +we compare y(w^Tx + b) and 0 for counting training errors. +

    +[Go Top] +

    + +Q: Why the code gives NaN (not a number) results? +
    +

    +This rarely happens, but few users reported the problem. +It seems that their +computers for training libsvm have the VPN client +running. The VPN software has some bugs and causes this +problem. Please try to close or disconnect the VPN client. +

    +[Go Top] +

    + +Q: Why the sign of predicted labels and decision values are sometimes reversed? +
    +

    + +This situation may occur before version 3.17. +Nothing is wrong. Very likely you have two labels +1/-1 and the first instance in your data +has -1. We give the following explanation. + +

    +Internally class labels are ordered by their first occurrence in the training set. For a k-class data, internally labels +are 0, ..., k-1, and each two-class SVM considers pair +(i, j) with i < j. Then class i is treated as positive (+1) +and j as negative (-1). +For example, if the data set has labels +5/+10 and +10 appears +first, then internally the +5 versus +10 SVM problem +has +10 as positive (+1) and +5 as negative (-1). + +

    +By this setting, if you have labels +1 and -1, +it's possible that internally they correspond to -1 and +1, +respectively. Some new users have been confused about +this, so after version 3.17, if the data set has only +two labels +1 and -1, +internally we ensure +1 to be before -1. Then class +1 +is always treated as positive in the SVM problem. +Note that this is for two-class data only. +

    +[Go Top] +

    + +Q: I don't know class labels of test data. What should I put in the first column of the test file? +
    +

    Any value is ok. In this situation, what you will use is the output file of svm-predict, which gives predicted class labels. + + +

    +[Go Top] +

    + +Q: How can I use OpenMP to parallelize LIBSVM on a multicore/shared-memory computer? +
    + +

    It is very easy if you are using GCC 4.2 +or after. + +

    In Makefile, add -fopenmp to CFLAGS. + +

    In class SVC_Q of svm.cpp, modify the for loop +of get_Q to: +

    +#pragma omp parallel for private(j) schedule(guided)
+			for(j=start;j<len;j++)
+
    +

    In the subroutine svm_predict_values of svm.cpp, add one line to the for loop: +

    +#pragma omp parallel for private(i) schedule(guided) 
+		for(i=0;i<l;i++)
+			kvalue[i] = Kernel::k_function(x,model->SV[i],model->param);
+
    +For regression, you need to modify +class SVR_Q instead. The loop in svm_predict_values +is also different because you need +a reduction clause for the variable sum: +
    +#pragma omp parallel for private(i) reduction(+:sum) schedule(guided)
+		for(i=0;i<model->l;i++)
+			sum += sv_coef[i] * Kernel::k_function(x,model->SV[i],model->param);
+
    + +

    Then rebuild the package. Kernel evaluations in training/testing will be parallelized. An example of running this modification on +an 8-core machine using the data set +real-sim: + +

    8 cores: +

    +%setenv OMP_NUM_THREADS 8
+%time svm-train -c 8 -g 0.5 -m 1000 real-sim
+175.90sec
+
    +1 core: +
    +%setenv OMP_NUM_THREADS 1
+%time svm-train -c 8 -g 0.5 -m 1000 real-sim
+588.89sec
+
    +For this data, kernel evaluations take 91% of training time. In the above example, we assume you use csh. For bash, use +
    +export OMP_NUM_THREADS=8
+
    +instead. + +

    For Python interface, you need to add the -lgomp link option: +

    +$(CXX) -lgomp -shared -dynamiclib svm.o -o libsvm.so.$(SHVER)
+
    + +

    For MS Windows, you need to add /openmp in CFLAGS of Makefile.win + +

    +[Go Top] +

    + +Q: How could I know which training instances are support vectors? +
    + +

    +It's very simple. Since version 3.13, you can use the function +

    +void svm_get_sv_indices(const struct svm_model *model, int *sv_indices)
+
    +to get indices of support vectors. For example, in svm-train.c, after +
    +		model = svm_train(&prob, &param);
+
    +you can add +
    +		int nr_sv = svm_get_nr_sv(model);
+		int *sv_indices = Malloc(int, nr_sv);
+		svm_get_sv_indices(model, sv_indices);
+		for (int i=0; i<nr_sv; i++)
+			printf("instance %d is a support vector\n", sv_indices[i]);
+
    + +

    If you use matlab interface, you can directly check +

    +model.sv_indices
+
    +

    +[Go Top] +

    + +Q: Why sv_indices (indices of support vectors) are not stored in the saved model file? +
    + +

    +Although sv_indices is a member of the model structure +to +indicate support vectors in the training set, +we do not store its contents in the model file. +The model file is mainly used in the future for +prediction, so it is basically independent +from training data. Thus +storing sv_indices is not necessary. +Users should find support vectors right after +the training process. See the previous FAQ. +

    +[Go Top] +

    + +Q: After doing cross validation, why there is no model file outputted ? +
    +

    +Cross validation is used for selecting good parameters. +After finding them, you want to re-train the whole +data without the -v option. +

    +[Go Top] +

    + +Q: Why my cross-validation results are different from those in the Practical Guide? +
    +

    + +Due to random partitions of +the data, on different systems CV accuracy values +may be different. +

    +[Go Top] +

    + +Q: On some systems CV accuracy is the same in several runs. How could I use different data partitions? In other words, how do I set random seed in LIBSVM? +
    +

    +If you use GNU C library, +the default seed 1 is considered. Thus you always +get the same result of running svm-train -v. +To have different seeds, you can add the following code +in svm-train.c: +

    +#include <time.h>
+
    +and in the beginning of main(), +
    +srand(time(0));
+
    +Alternatively, if you are not using GNU C library +and would like to use a fixed seed, you can have +
    +srand(1);
+
    + +

    +For Java, the random number generator +is initialized using the time information. +So results of two CV runs are different. +To fix the seed, after version 3.1 (released +in mid 2011), you can add +

    +svm.rand.setSeed(0);
+
    +in the main() function of svm_train.java. + +

    +If you use CV to select parameters, it is recommended to use identical folds +under different parameters. In this case, you can consider fixing the seed. +

    +[Go Top] +

    + +Q: Why on windows sometimes grid.py fails? +
    +

    + +This problem shouldn't happen after version +2.85. If you are using earlier versions, +please download the latest one. + + +

    +[Go Top] +

    + +Q: Why grid.py/easy.py sometimes generates the following warning message? +
    +
    +Warning: empty z range [62.5:62.5], adjusting to [61.875:63.125]
+Notice: cannot contour non grid data!
+
    +

    Nothing is wrong and please disregard the +message. It is from gnuplot when drawing +the contour. +

    +[Go Top] +

    + +Q: How do I choose the kernel? +
    + +

    +In general we suggest you to try the RBF kernel first. +A recent result by Keerthi and Lin +( +download paper here) +shows that if RBF is used with model selection, +then there is no need to consider the linear kernel. +The kernel matrix using sigmoid may not be positive definite +and in general it's accuracy is not better than RBF. +(see the paper by Lin and Lin +( +download paper here). +Polynomial kernels are ok but if a high degree is used, +numerical difficulties tend to happen +(thinking about dth power of (<1) goes to 0 +and (>1) goes to infinity). +

    +[Go Top] +

    + +Q: How does LIBSVM perform parameter selection for multi-class problems? +
    + +

    +LIBSVM implements "one-against-one" multi-class method, so there are +k(k-1)/2 binary models, where k is the number of classes. + +

    +We can consider two ways to conduct parameter selection. + +

      +
    1. +For any two classes of data, a parameter selection procedure is conducted. Finally, +each decision function has its own optimal parameters. +
      2. +
    2. +The same parameters are used for all k(k-1)/2 binary classification problems. +We select parameters that achieve the highest overall performance. +
      3. +
    + +Each has its own advantages. A +single parameter set may not be uniformly good for all k(k-1)/2 decision functions. +However, as the overall accuracy is the final consideration, one parameter set +for one decision function may lead to over-fitting. In the paper +

    +Chen, Lin, and Schölkopf, + +A tutorial on nu-support vector machines. + +Applied Stochastic Models in Business and Industry, 21(2005), 111-136, + +

    +they have experimentally +shown that the two methods give similar performance. +Therefore, currently the parameter selection in LIBSVM +takes the second approach by considering the same parameters for +all k(k-1)/2 models. +

    +[Go Top] +

    + +Q: How do I choose parameters for one-class SVM as training data are in only one class? +
    +

    +You have pre-specified true positive rate in mind and then search for +parameters which achieve similar cross-validation accuracy. +

    +[Go Top] +

    + +Q: Instead of grid.py, what if I would like to conduct parameter selection using other programmin languages? +
    +

    +For MATLAB, please see another question in FAQ. + +

    +For using shell scripts, please check the code written by Bjarte Johansen +

    +[Go Top] +

    + +Q: Why training a probability model (i.e., -b 1) takes a longer time? +
    +

    +To construct this probability model, we internally conduct a +cross validation, which is more time consuming than +a regular training. +Hence, in general you do parameter selection first without +-b 1. You only use -b 1 when good parameters have been +selected. In other words, you avoid using -b 1 and -v +together. +

    +[Go Top] +

    + +Q: Why using the -b option does not give me better accuracy? +
    +

    +There is absolutely no reason the probability outputs guarantee +you better accuracy. The main purpose of this option is +to provide you the probability estimates, but not to boost +prediction accuracy. From our experience, +after proper parameter selections, in general with +and without -b have similar accuracy. Occasionally there +are some differences. +It is not recommended to compare the two under +just a fixed parameter +set as more differences will be observed. +

    +[Go Top] +

    + +Q: Why using svm-predict -b 0 and -b 1 gives different accuracy values? +
    +

    +Let's just consider two-class classification here. After probability information is obtained in training, +we do not have +

    +prob > = 0.5 if and only if decision value >= 0. +

    +So predictions may be different with -b 0 and 1. +

    +[Go Top] +

    + +Q: How can I save images drawn by svm-toy? +
    +

    +For Microsoft windows, first press the "print screen" key on the keyboard. +Open "Microsoft Paint" +(included in Windows) +and press "ctrl-v." Then you can clip +the part of picture which you want. +For X windows, you can +use the program "xv" or "import" to grab the picture of the svm-toy window. +

    +[Go Top] +

    + +Q: I press the "load" button to load data points but why svm-toy does not draw them ? +
    +

    +The program svm-toy assumes both attributes (i.e. x-axis and y-axis +values) are in (0,1). Hence you want to scale your +data to between a small positive number and +a number less than but very close to 1. +Moreover, class labels must be 1, 2, or 3 +(not 1.0, 2.0 or anything else). +

    +[Go Top] +

    + +Q: I would like svm-toy to handle more than three classes of data, what should I do ? +
    +

    +Taking windows/svm-toy.cpp as an example, you need to +modify it and the difference +from the original file is as the following: (for five classes of +data) +

    +30,32c30
+< 	RGB(200,0,200),
+< 	RGB(0,160,0),
+< 	RGB(160,0,0)
+---
+> 	RGB(200,0,200)
+39c37
+< HBRUSH brush1, brush2, brush3, brush4, brush5;
+---
+> HBRUSH brush1, brush2, brush3;
+113,114d110
+< 	brush4 = CreateSolidBrush(colors[7]);
+< 	brush5 = CreateSolidBrush(colors[8]);
+155,157c151
+< 	else if(v==3) return brush3;
+< 	else if(v==4) return brush4;
+< 	else return brush5;
+---
+> 	else return brush3;
+325d318
+< 	  int colornum = 5;
+327c320
+< 		svm_node *x_space = new svm_node[colornum * prob.l];
+---
+> 		svm_node *x_space = new svm_node[3 * prob.l];
+333,338c326,331
+< 			x_space[colornum * i].index = 1;
+< 			x_space[colornum * i].value = q->x;
+< 			x_space[colornum * i + 1].index = 2;
+< 			x_space[colornum * i + 1].value = q->y;
+< 			x_space[colornum * i + 2].index = -1;
+< 			prob.x[i] = &x_space[colornum * i];
+---
+> 			x_space[3 * i].index = 1;
+> 			x_space[3 * i].value = q->x;
+> 			x_space[3 * i + 1].index = 2;
+> 			x_space[3 * i + 1].value = q->y;
+> 			x_space[3 * i + 2].index = -1;
+> 			prob.x[i] = &x_space[3 * i];
+397c390
+< 				if(current_value > 5) current_value = 1;
+---
+> 				if(current_value > 3) current_value = 1;
+
    +

    +[Go Top] +

    + +Q: What is the difference between Java version and C++ version of libsvm? +
    +

    +They are the same thing. We just rewrote the C++ code +in Java. +

    +[Go Top] +

    + +Q: Is the Java version significantly slower than the C++ version? +
    +

    +This depends on the VM you used. We have seen good +VM which leads the Java version to be quite competitive with +the C++ code. (though still slower) +

    +[Go Top] +

    + +Q: While training I get the following error message: java.lang.OutOfMemoryError. What is wrong? +
    +

    +You should try to increase the maximum Java heap size. +For example, +

    +java -Xmx2048m -classpath libsvm.jar svm_train ...
+
    +sets the maximum heap size to 2048M. +

    +[Go Top] +

    + +Q: Why you have the main source file svm.m4 and then transform it to svm.java? +
    +

    +Unlike C, Java does not have a preprocessor built-in. +However, we need some macros (see first 3 lines of svm.m4). + + +

    +[Go Top] +

    + +Q: Except the python-C++ interface provided, could I use Jython to call libsvm ? +
    +

    Yes, here are some examples: + +

    +$ export CLASSPATH=$CLASSPATH:~/libsvm-2.91/java/libsvm.jar
+$ ./jython
+Jython 2.1a3 on java1.3.0 (JIT: jitc)
+Type "copyright", "credits" or "license" for more information.
+>>> from libsvm import *
+>>> dir()
+['__doc__', '__name__', 'svm', 'svm_model', 'svm_node', 'svm_parameter',
+'svm_problem']
+>>> x1 = [svm_node(index=1,value=1)]
+>>> x2 = [svm_node(index=1,value=-1)]
+>>> param = svm_parameter(svm_type=0,kernel_type=2,gamma=1,cache_size=40,eps=0.001,C=1,nr_weight=0,shrinking=1)
+>>> prob = svm_problem(l=2,y=[1,-1],x=[x1,x2])
+>>> model = svm.svm_train(prob,param)
+*
+optimization finished, #iter = 1
+nu = 1.0
+obj = -1.018315639346838, rho = 0.0
+nSV = 2, nBSV = 2
+Total nSV = 2
+>>> svm.svm_predict(model,x1)
+1.0
+>>> svm.svm_predict(model,x2)
+-1.0
+>>> svm.svm_save_model("test.model",model)
+
+
    + +

    +[Go Top] +

    + +Q: I compile the MATLAB interface without problem, but why errors occur while running it? +
    +

    +Your compiler version may not be supported/compatible for MATLAB. +Please check this MATLAB page first and then specify the version +number. For example, if g++ X.Y is supported, replace +

    +CXX = g++
+
    +in the Makefile with +
    +CXX = g++-X.Y
+
    +

    +[Go Top] +

    + +Q: On 64bit Windows I compile the MATLAB interface without problem, but why errors occur while running it? +
    +

    + + +Please make sure that you use +the -largeArrayDims option in make.m. For example, +

    +mex -largeArrayDims -O -c svm.cpp
+
    + +Moreover, if you use Microsoft Visual Studio, +probabally it is not properly installed. +See the explanation +here. +

    +[Go Top] +

    + +Q: Does the MATLAB interface provide a function to do scaling? +
    +

    +It is extremely easy to do scaling under MATLAB. +The following one-line code scale each feature to the range +of [0,1]: +

    +(data - repmat(min(data,[],1),size(data,1),1))*spdiags(1./(max(data,[],1)-min(data,[],1))',0,size(data,2),size(data,2))
+
    +

    +[Go Top] +

    + +Q: How could I use MATLAB interface for parameter selection? +
    +

    +One can do this by a simple loop. +See the following example: +

    +bestcv = 0;
+for log2c = -1:3,
+  for log2g = -4:1,
+    cmd = ['-v 5 -c ', num2str(2^log2c), ' -g ', num2str(2^log2g)];
+    cv = svmtrain(heart_scale_label, heart_scale_inst, cmd);
+    if (cv >= bestcv),
+      bestcv = cv; bestc = 2^log2c; bestg = 2^log2g;
+    end
+    fprintf('%g %g %g (best c=%g, g=%g, rate=%g)\n', log2c, log2g, cv, bestc, bestg, bestcv);
+  end
+end
+
    +You may adjust the parameter range in the above loops. +

    +[Go Top] +

    + +Q: I use MATLAB parallel programming toolbox on a multi-core environment for parameter selection. Why the program is even slower? +
    +

    +Fabrizio Lacalandra of University of Pisa reported this issue. +It seems the problem is caused by the screen output. +If you disable the info function +using 

    #if 0,
    then the problem +may be solved. +

    +[Go Top] +

    + +Q: How to use LIBSVM with OpenMP under MATLAB/Octave? +
    + +

    +First, you must modify svm.cpp. Check the following faq, + +How can I use OpenMP to parallelize LIBSVM on a multicore/shared-memory computer? + +

    +To build the MATLAB/Octave interface, we recommend using make.m. +You must append '-fopenmp' to CXXFLAGS and add '-lgomp' to mex options in make.m. +See details below. + +

    +For MATLAB users, the modified code is: +

    +mex CFLAGS="\$CFLAGS -std=c99" CXXFLAGS="\$CXXFLAGS -fopenmp" -largeArrayDims -I.. -lgomp svmtrain.c ../svm.cpp svm_model_matlab.c
+mex CFLAGS="\$CFLAGS -std=c99" CXXFLAGS="\$CXXFLAGS -fopenmp" -largeArrayDims -I.. -lgomp svmpredict.c ../svm.cpp svm_model_matlab.c
+
    + +

    +For Octave users, the modified code is: +

    +setenv('CXXFLAGS', '-fopenmp') 
+mex -I.. -lgomp svmtrain.c ../svm.cpp svm_model_matlab.c
+mex -I.. -lgomp svmpredict.c ../svm.cpp svm_model_matlab.c
+
    + +

    +If make.m fails under matlab and you use Makefile to compile the codes, +you must modify two files: + +

    +You must append '-fopenmp' to CFLAGS in ../Makefile for C/C++ codes: +

    +CFLAGS = -Wall -Wconversion -O3 -fPIC -fopenmp -I$(MATLABDIR)/extern/include -I..
+
    +and add '-lgomp' to MEX_OPTION in Makefile for the matlab/octave interface: +
    +MEX_OPTION += -lgomp
+
    + +

    + To run the code, you must specify the number of threads. For + example, before executing matlab/octave, you run +

    +> export OMP_NUM_THREADS=8
+> matlab
+
    +Here we assume Bash is used. Unfortunately, we do not know yet +how to specify the number of threads within MATLAB/Octave. Our +experiments show that +
    +>> setenv('OMP_NUM_THREADS', '8');
+
    +does not work. Please contact us if you +see how to solve this problem. On the other hand, you can +specify the number of threads in the source code (thanks +to comments from Ricardo Santiago-mozos): +
    +#pragma omp parallel  for private(i) num_threads(8)
+
    +

    +[Go Top] +

    + +Q: How could I generate the primal variable w of linear SVM? +
    +

    +Let's start from the binary class and +assume you have two labels -1 and +1. +After obtaining the model from calling svmtrain, +do the following to have w and b: +

    +w = model.SVs' * model.sv_coef;
+b = -model.rho;
+
+if model.Label(1) == -1
+  w = -w;
+  b = -b;
+end
+
    +If you do regression or one-class SVM, then the if statement is not needed. + +

    For multi-class SVM, we illustrate the setting +in the following example of running the iris +data, which have 3 classes +

      
+> [y, x] = libsvmread('../../htdocs/libsvmtools/datasets/multiclass/iris.scale');
+> m = svmtrain(y, x, '-t 0')
+
+m = 
+
+    Parameters: [5x1 double]
+      nr_class: 3
+       totalSV: 42
+           rho: [3x1 double]
+         Label: [3x1 double]
+         ProbA: []
+         ProbB: []
+           nSV: [3x1 double]
+       sv_coef: [42x2 double]
+           SVs: [42x4 double]
+
    +sv_coef is like: +
    ++-+-+--------------------+
+|1|1|                    |
+|v|v|  SVs from class 1  |
+|2|3|                    |
++-+-+--------------------+
+|1|2|                    |
+|v|v|  SVs from class 2  |
+|2|3|                    |
++-+-+--------------------+
+|1|2|                    |
+|v|v|  SVs from class 3  |
+|3|3|                    |
++-+-+--------------------+
+
    +so we need to see nSV of each classes. +
      
+> m.nSV
+
+ans =
+
+     3
+    21
+    18
+
    +Suppose the goal is to find the vector w of classes +1 vs 3. Then +y_i alpha_i of training 1 vs 3 are +
      
+> coef = [m.sv_coef(1:3,2); m.sv_coef(25:42,1)];
+
    +and SVs are: +
      
+> SVs = [m.SVs(1:3,:); m.SVs(25:42,:)];
+
    +Hence, w is +
    +> w = SVs'*coef;
+
    +For rho, +
    +> m.rho
+
+ans =
+
+    1.1465
+    0.3682
+   -1.9969
+> b = -m.rho(2);
+
    +because rho is arranged by 1vs2 1vs3 2vs3. + + + +

    +[Go Top] +

    + +Q: Is there an OCTAVE interface for libsvm? +
    +

    +Yes, after libsvm 2.86, the matlab interface +works on OCTAVE as well. Please use make.m by typing +

    +>> make 
+
    +under OCTAVE. +

    +[Go Top] +

    + +Q: How to handle the name conflict between svmtrain in the libsvm matlab interface and that in MATLAB bioinformatics toolbox? +
    +

    +The easiest way is to rename the svmtrain binary +file (e.g., svmtrain.mexw32 on 32-bit windows) +to a different +name (e.g., svmtrain2.mexw32). +

    +[Go Top] +

    + +Q: On Windows I got an error message "Invalid MEX-file: Specific module not found" when running the pre-built MATLAB interface in the windows sub-directory. What should I do? +
    +

    + +The error usually happens +when there are missing runtime components +such as MSVCR100.dll on your Windows platform. +You can use tools such as +Dependency +Walker to find missing library files. + +

    +For example, if the pre-built MEX files are compiled by +Visual C++ 2010, +you must have installed +Microsoft Visual C++ Redistributable Package 2010 +(vcredist_x86.exe). You can easily find the freely +available file from Microsoft's web site. + +

    +For 64bit Windows, the situation is similar. If +the pre-built files are by +Visual C++ 2008, then you must have +Microsoft Visual C++ Redistributable Package 2008 +(vcredist_x64.exe). +

    +[Go Top] +

    + +Q: LIBSVM supports 1-vs-1 multi-class classification. If instead I would like to use 1-vs-rest, how to implement it using MATLAB interface? +
    + +

    +Please use code in the following directory. The following example shows how to +train and test the problem dna (training and testing). + +

    Load, train and predict data: +

    +[trainY trainX] = libsvmread('./dna.scale');
+[testY testX] = libsvmread('./dna.scale.t');
+model = ovrtrain(trainY, trainX, '-c 8 -g 4');
+[pred ac decv] = ovrpredict(testY, testX, model);
+fprintf('Accuracy = %g%%\n', ac * 100);
+
    +Conduct CV on a grid of parameters +
    +bestcv = 0;
+for log2c = -1:2:3,
+  for log2g = -4:2:1,
+    cmd = ['-q -c ', num2str(2^log2c), ' -g ', num2str(2^log2g)];
+    cv = get_cv_ac(trainY, trainX, cmd, 3);
+    if (cv >= bestcv),
+      bestcv = cv; bestc = 2^log2c; bestg = 2^log2g;
+    end
+    fprintf('%g %g %g (best c=%g, g=%g, rate=%g)\n', log2c, log2g, cv, bestc, bestg, bestcv);
+  end
+end
+
    +

    +[Go Top] +

    + +Q: I tried to install matlab interface on mac, but failed. What should I do? +
    + +

    +We assume that in a matlab command window you change directory to libsvm/matlab and type +

    +>> make
+
    +We discuss the following situations. + +
      +
    1. An error message like "libsvmread.c:1:19: fatal error: +stdio.h: No such file or directory" appears. + +

      +Reason: "make" looks for a C++ compiler, but +no compiler is found. To get one, you can +

        +
      • Install XCode offered by Apple Inc. +
      • Install XCode Command Line Tools. +
      + +

      +

    2. On OS X with Xcode 4.2+, I got an error message like "llvm-gcc-4.2: +command not found." + +

      +Reason: Since Apple Inc. only ships llsvm-gcc instead of gcc-4.2, +llvm-gcc-4.2 cannot be found. + +

      +If you are using Xcode 4.2-4.6, +a related solution is offered at +http://www.mathworks.com/matlabcentral/answers/94092. + +

      +On the other hand, for Xcode 5 (including Xcode 4.2-4.6), in a Matlab command window, enter +

        +
      • cd (matlabroot) +
      • cd bin +
      • Backup your mexopts.sh first +
      • edit mexopts.sh +
      • Scroll down to "maci64" section. Change +
        +		CC='llvm-gcc-4.2'
+		CXX='llvm-g++-4.2'
+
        +to +
        +		CC='llvm-gcc'
+		CXX='llvm-g++'
+
        +
      + +Please also ensure that SDKROOT corresponds to the SDK version you are using. + +

      +

    3. Other errors: you may check http://www.mathworks.com/matlabcentral/answers/94092. + +
    +

    +[Go Top] +

    + +Q: I tried to install octave interface on windows, but failed. What should I do? +
    + +

    +This may be due to +that Octave's math.h file does not +refer to the correct location of Visual Studio's math.h. +Please see this nice page for detailed +instructions. +

    +[Go Top] +

    +

    +LIBSVM home page +

    + + diff --git a/gklearn/gedlib/lib/libsvm.3.22/Makefile b/gklearn/gedlib/lib/libsvm.3.22/Makefile new file mode 100644 index 0000000..6289cb7 --- /dev/null +++ b/gklearn/gedlib/lib/libsvm.3.22/Makefile @@ -0,0 +1,24 @@ +CXX ?= g++ +CFLAGS = -Wall -Wconversion -O3 -fPIC +OS = $(shell uname) + +all: svm-train svm-predict svm-scale + +lib: svm.o + if [ "$(OS)" = "Darwin" ]; then \ + SHARED_LIB_FLAG="-dynamiclib -Wl,-install_name,libsvm.so"; \ + else \ + SHARED_LIB_FLAG="-shared -Wl,-soname,libsvm.so"; \ + fi; \ + $(CXX) $${SHARED_LIB_FLAG} svm.o -o libsvm.so + +svm-predict: svm-predict.c svm.o + $(CXX) $(CFLAGS) svm-predict.c svm.o -o svm-predict -lm +svm-train: svm-train.c svm.o + $(CXX) $(CFLAGS) svm-train.c svm.o -o svm-train -lm +svm-scale: svm-scale.c + $(CXX) $(CFLAGS) svm-scale.c -o svm-scale +svm.o: svm.cpp svm.h + $(CXX) $(CFLAGS) -c svm.cpp +clean: + rm -f *~ svm.o svm-train svm-predict svm-scale libsvm.so diff --git a/gklearn/gedlib/lib/libsvm.3.22/Makefile.win b/gklearn/gedlib/lib/libsvm.3.22/Makefile.win new file mode 100644 index 0000000..b1d3570 --- /dev/null +++ b/gklearn/gedlib/lib/libsvm.3.22/Makefile.win @@ -0,0 +1,33 @@ +#You must ensure nmake.exe, cl.exe, link.exe are in system path. +#VCVARS64.bat +#Under dosbox prompt +#nmake -f Makefile.win + +########################################## +CXX = cl.exe +CFLAGS = /nologo /O2 /EHsc /I. /D _WIN64 /D _CRT_SECURE_NO_DEPRECATE +TARGET = windows + +all: $(TARGET)\svm-train.exe $(TARGET)\svm-predict.exe $(TARGET)\svm-scale.exe $(TARGET)\svm-toy.exe lib + +$(TARGET)\svm-predict.exe: svm.h svm-predict.c svm.obj + $(CXX) $(CFLAGS) svm-predict.c svm.obj -Fe$(TARGET)\svm-predict.exe + +$(TARGET)\svm-train.exe: svm.h svm-train.c svm.obj + $(CXX) $(CFLAGS) svm-train.c svm.obj -Fe$(TARGET)\svm-train.exe + +$(TARGET)\svm-scale.exe: svm.h svm-scale.c + $(CXX) $(CFLAGS) svm-scale.c -Fe$(TARGET)\svm-scale.exe + +$(TARGET)\svm-toy.exe: svm.h svm.obj svm-toy\windows\svm-toy.cpp + $(CXX) $(CFLAGS) svm-toy\windows\svm-toy.cpp svm.obj user32.lib gdi32.lib comdlg32.lib -Fe$(TARGET)\svm-toy.exe + +svm.obj: svm.cpp svm.h + $(CXX) $(CFLAGS) -c svm.cpp + +lib: svm.cpp svm.h svm.def + $(CXX) $(CFLAGS) -LD svm.cpp -Fe$(TARGET)\libsvm -link -DEF:svm.def + +clean: + -erase /Q *.obj $(TARGET)\*.exe $(TARGET)\*.dll $(TARGET)\*.exp $(TARGET)\*.lib + diff --git a/gklearn/gedlib/lib/libsvm.3.22/README b/gklearn/gedlib/lib/libsvm.3.22/README new file mode 100644 index 0000000..5b32236 --- /dev/null +++ b/gklearn/gedlib/lib/libsvm.3.22/README @@ -0,0 +1,769 @@ +Libsvm is a simple, easy-to-use, and efficient software for SVM +classification and regression. It solves C-SVM classification, nu-SVM +classification, one-class-SVM, epsilon-SVM regression, and nu-SVM +regression. It also provides an automatic model selection tool for +C-SVM classification. This document explains the use of libsvm. + +Libsvm is available at +http://www.csie.ntu.edu.tw/~cjlin/libsvm +Please read the COPYRIGHT file before using libsvm. + +Table of Contents +================= + +- Quick Start +- Installation and Data Format +- `svm-train' Usage +- `svm-predict' Usage +- `svm-scale' Usage +- Tips on Practical Use +- Examples +- Precomputed Kernels +- Library Usage +- Java Version +- Building Windows Binaries +- Additional Tools: Sub-sampling, Parameter Selection, Format checking, etc. +- MATLAB/OCTAVE Interface +- Python Interface +- Additional Information + +Quick Start +=========== + +If you are new to SVM and if the data is not large, please go to +`tools' directory and use easy.py after installation. It does +everything automatic -- from data scaling to parameter selection. + +Usage: easy.py training_file [testing_file] + +More information about parameter selection can be found in +`tools/README.' + +Installation and Data Format +============================ + +On Unix systems, type `make' to build the `svm-train' and `svm-predict' +programs. Run them without arguments to show the usages of them. + +On other systems, consult `Makefile' to build them (e.g., see +'Building Windows binaries' in this file) or use the pre-built +binaries (Windows binaries are in the directory `windows'). + +The format of training and testing data file is: + +