New translations lsape_based_method.py (French)

lang/fr/gklearn/ged/methods/lsape_based_method.py

@@ -0,0 +1,254 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Thu Jun 18 16:01:24 2020
+
+@author: ljia
+"""
+import numpy as np
+import networkx as nx
+from gklearn.ged.methods import GEDMethod
+from gklearn.ged.util import LSAPESolver, misc
+from gklearn.ged.env import NodeMap
+	
+
+class LSAPEBasedMethod(GEDMethod):
+	
+	
+	def __init__(self, ged_data):
+		super().__init__(ged_data)
+		self._lsape_model = None # @todo: LSAPESolver::ECBP
+		self._greedy_method = None # @todo: LSAPESolver::BASIC
+		self._compute_lower_bound = True
+		self._solve_optimally = True
+		self._num_threads = 1
+		self._centrality_method = 'NODE' # @todo
+		self._centrality_weight = 0.7
+		self._centralities = {}
+		self._max_num_solutions = 1
+		
+		
+	def populate_instance_and_run_as_util(self, g, h): #, lsape_instance):
+		"""
+	/*!
+	 * @brief Runs the method with options specified by set_options() and provides access to constructed LSAPE instance.
+	 * @param[in] g Input graph.
+	 * @param[in] h Input graph.
+	 * @param[out] result Result variable.
+	 * @param[out] lsape_instance LSAPE instance.
+	 */
+		"""
+		result = {'node_maps': [], 'lower_bound': 0, 'upper_bound': np.inf}
+		
+		# Populate the LSAPE instance and set up the solver.
+		nb1, nb2 = nx.number_of_nodes(g), nx.number_of_nodes(h)
+		lsape_instance = np.ones((nb1 + nb2, nb1 + nb2)) * np.inf
+# 		lsape_instance = np.empty((nx.number_of_nodes(g) + 1, nx.number_of_nodes(h) + 1))
+		self.populate_instance(g, h, lsape_instance)
+		
+# 		nb1, nb2 = nx.number_of_nodes(g), nx.number_of_nodes(h)
+# 		lsape_instance_new = np.empty((nb1 + nb2, nb1 + nb2)) * np.inf
+# 		lsape_instance_new[nb1:, nb2:] = 0
+# 		lsape_instance_new[0:nb1, 0:nb2] = lsape_instance[0:nb1, 0:nb2]
+# 		for i in range(nb1): # all u's neighbor
+# 			lsape_instance_new[i, nb2 + i] = lsape_instance[i, nb2]
+# 		for i in range(nb2): # all u's neighbor
+# 			lsape_instance_new[nb1 + i, i] = lsape_instance[nb2, i]
+# 		lsape_solver = LSAPESolver(lsape_instance_new)
+		
+		lsape_solver = LSAPESolver(lsape_instance)
+		
+		# Solve the LSAPE instance.
+		if self._solve_optimally:
+			lsape_solver.set_model(self._lsape_model)
+		else:
+			lsape_solver.set_greedy_method(self._greedy_method)
+		lsape_solver.solve(self._max_num_solutions)
+		
+		# Compute and store lower and upper bound.
+		if self._compute_lower_bound and self._solve_optimally:
+			result['lower_bound'] = lsape_solver.minimal_cost() * self._lsape_lower_bound_scaling_factor(g, h) # @todo: test
+		
+		for solution_id in range(0, lsape_solver.num_solutions()):
+			result['node_maps'].append(NodeMap(nx.number_of_nodes(g), nx.number_of_nodes(h)))
+			misc.construct_node_map_from_solver(lsape_solver, result['node_maps'][-1], solution_id)
+			self._ged_data.compute_induced_cost(g, h, result['node_maps'][-1])
+			
+		# Add centralities and reoptimize.
+		if self._centrality_weight > 0 and self._centrality_method != 'NODE':
+			print('This is not implemented.')
+			pass # @todo
+			
+		# Sort the node maps and set the upper bound.
+		if len(result['node_maps']) > 1 or len(result['node_maps']) > self._max_num_solutions:
+			print('This is not implemented.') # @todo:
+			pass
+		if len(result['node_maps']) == 0:
+			result['upper_bound'] = np.inf
+		else:
+			result['upper_bound'] = result['node_maps'][0].induced_cost()
+					
+		return result
+			
+		
+	
+	def populate_instance(self, g, h, lsape_instance):
+		"""
+	/*!
+	 * @brief Populates the LSAPE instance.
+	 * @param[in] g Input graph.
+	 * @param[in] h Input graph.
+	 * @param[out] lsape_instance LSAPE instance.
+	 */
+		"""
+		if not self._initialized:
+			pass
+		# @todo: if (not this->initialized_) {
+		self._lsape_populate_instance(g, h, lsape_instance)
+		lsape_instance[nx.number_of_nodes(g):, nx.number_of_nodes(h):] = 0
+# 		lsape_instance[nx.number_of_nodes(g), nx.number_of_nodes(h)] = 0
+		
+	
+	###########################################################################
+	# Member functions inherited from GEDMethod.
+	###########################################################################
+	
+	
+	def _ged_init(self):
+		self._lsape_pre_graph_init(False)
+		for graph in self._ged_data._graphs:
+			self._init_graph(graph)
+		self._lsape_init()
+		
+		
+	def _ged_run(self, g, h):
+# 		lsape_instance = np.empty((0, 0))
+		result = self.populate_instance_and_run_as_util(g, h) # , lsape_instance)
+		return result
+		
+		
+	def _ged_parse_option(self, option, arg):
+		is_valid_option = False
+		
+		if option == 'threads': # @todo: try.. catch...
+			self._num_threads = arg
+			is_valid_option = True
+		elif option == 'lsape_model':
+			self._lsape_model = arg # @todo
+			is_valid_option = True
+		elif option == 'greedy_method':
+			self._greedy_method = arg # @todo
+			is_valid_option = True
+		elif option == 'optimal':
+			self._solve_optimally = arg # @todo
+			is_valid_option = True
+		elif option == 'centrality_method':
+			self._centrality_method = arg # @todo
+			is_valid_option = True
+		elif option == 'centrality_weight':
+			self._centrality_weight = arg # @todo
+			is_valid_option = True
+		elif option == 'max_num_solutions':
+			if arg == 'ALL':
+				self._max_num_solutions = -1
+			else:				
+				self._max_num_solutions = arg # @todo
+			is_valid_option = True
+			
+		is_valid_option = is_valid_option or self._lsape_parse_option(option, arg)
+		is_valid_option = True # @todo: this is not in the C++ code.
+		return is_valid_option
+		
+		
+	def _ged_set_default_options(self):
+		self._lsape_model = None # @todo: LSAPESolver::ECBP
+		self._greedy_method = None # @todo: LSAPESolver::BASIC
+		self._solve_optimally = True
+		self._num_threads = 1
+		self._centrality_method = 'NODE' # @todo
+		self._centrality_weight = 0.7
+		self._max_num_solutions = 1
+		
+		
+	###########################################################################
+	# Private helper member functions.
+	###########################################################################
+	
+	
+	def _init_graph(self, graph):
+		if self._centrality_method != 'NODE':
+			self._init_centralities(graph) # @todo
+		self._lsape_init_graph(graph)
+	
+	
+	###########################################################################
+	# Virtual member functions to be overridden by derived classes.
+	###########################################################################
+	
+	
+	def _lsape_init(self):
+		"""
+	/*!
+	 * @brief Initializes the method after initializing the global variables for the graphs.
+	 * @note Must be overridden by derived classes of ged::LSAPEBasedMethod that require custom initialization.
+	 */
+		"""
+		pass
+		
+		
+	def _lsape_parse_option(self, option, arg):
+		"""
+	/*!
+	 * @brief Parses one option that is not among the ones shared by all derived classes of ged::LSAPEBasedMethod.
+	 * @param[in] option The name of the option.
+	 * @param[in] arg The argument of the option.
+	 * @return Returns true if @p option is a valid option name for the method and false otherwise.
+	 * @note Must be overridden by derived classes of ged::LSAPEBasedMethod that have options that are not among the ones shared by all derived classes of ged::LSAPEBasedMethod.
+	 */
+		"""
+		return False
+		
+		
+	def _lsape_set_default_options(self):
+		"""
+	/*!
+	 * @brief Sets all options that are not among the ones shared by all derived classes of ged::LSAPEBasedMethod to default values.
+	 * @note Must be overridden by derived classes of ged::LSAPEBasedMethod that have options that are not among the ones shared by all derived classes of ged::LSAPEBasedMethod.
+	 */
+		"""
+		pass
+	
+	
+	def _lsape_populate_instance(self, g, h, lsape_instance):
+		"""
+	/*!
+	 * @brief Populates the LSAPE instance.
+	 * @param[in] g Input graph.
+	 * @param[in] h Input graph.
+	 * @param[out] lsape_instance LSAPE instance of size (n + 1) x (m + 1), where n and m are the number of nodes in @p g and @p h. The last row and the last column represent insertion and deletion.
+	 * @note Must be overridden by derived classes of ged::LSAPEBasedMethod.
+	 */
+		"""
+		pass
+	
+	
+	def _lsape_init_graph(self, graph):
+		"""
+	/*!
+	 * @brief Initializes global variables for one graph.
+	 * @param[in] graph Graph for which the global variables have to be initialized.
+	 * @note Must be overridden by derived classes of ged::LSAPEBasedMethod that require to initialize custom global variables.
+	 */
+		"""
+		pass
+	
+	
+	def _lsape_pre_graph_init(self, called_at_runtime):
+		"""
+	/*!
+	 * @brief Initializes the method at runtime or during initialization before initializing the global variables for the graphs.
+	 * @param[in] called_at_runtime Equals @p true if called at runtime and @p false if called during initialization.
+	 * @brief Must be overridden by derived classes of ged::LSAPEBasedMethod that require default initialization at runtime before initializing the global variables for the graphs.
+	 */
+		"""
+		pass