Merge pull request #57 from jajupmochi/v0.2.x

V0.2.x

.github/workflows/github-actions-ubuntu.yml

@@ -91,22 +91,22 @@ jobs:
           #          python setup.py bdist_wheel
           python setup.py install
           #          pytest -v --cov-config=.coveragerc --cov-report term --cov=gklearn gklearn/tests/ged/
-          pytest -v --cov-config=.coveragerc --cov-report term --cov=gklearn gklearn/tests/ --ignore=gklearn/tests/test_median_preimage_generator.py --ignore=gklearn/tests/test_graphkernels.py
+          pytest -v --cov-config=.coveragerc --cov-report term --cov=gklearn gklearn/tests/ --ignore=gklearn/tests/test_median_preimage_generator.py --ignore=gklearn/tests/test_graphkernels.py --ignore=gklearn/tests/ged/test_gedlib.py
 
       - name: Run code coverage
         run: |
           codecov
 
-      - name: Publish distribution 📦 to Test PyPI
-        if: matrix.python-version == '3.8' && matrix.os == 'ubuntu-latest'
-        uses: pypa/gh-action-pypi-publish@release/v1
-        with:
-          password: ${{ secrets.TEST_PYPI_API_TOKEN }}
-          repository-url: https://test.pypi.org/legacy/
-
-      - name: Publish distribution 📦 to PyPI
-        if: matrix.python-version == '3.8' && matrix.os == 'ubuntu-latest'
-        uses: pypa/gh-action-pypi-publish@release/v1
-        with:
-          user: __token__
-          password: ${{ secrets.PYPI_API_TOKEN }}
+#      - name: Publish distribution 📦 to Test PyPI
+#        if: matrix.python-version == '3.8' && matrix.os == 'ubuntu-latest'
+#        uses: pypa/gh-action-pypi-publish@release/v1
+#        with:
+#          password: ${{ secrets.TEST_PYPI_API_TOKEN }}
+#          repository-url: https://test.pypi.org/legacy/
+
+#      - name: Publish distribution 📦 to PyPI
+#        if: matrix.python-version == '3.8' && matrix.os == 'ubuntu-latest'
+#        uses: pypa/gh-action-pypi-publish@release/v1
+#        with:
+#          user: __token__
+#          password: ${{ secrets.PYPI_API_TOKEN }}

README.md

@@ -1,6 +1,6 @@
 # graphkit-learn
 
-![GitHub Actions](https://github.com/jajupmochi/graphkit-learn/actions/workflows/github-actions.yml/badge.svg)
+![GitHub Actions](https://github.com/jajupmochi/graphkit-learn/actions/workflows/github-actions-ubuntu.yml/badge.svg)
 [![Build status](https://ci.appveyor.com/api/projects/status/bdxsolk0t1uji9rd?svg=true)](https://ci.appveyor.com/project/jajupmochi/graphkit-learn)
 [![codecov](https://codecov.io/gh/jajupmochi/graphkit-learn/branch/master/graph/badge.svg)](https://codecov.io/gh/jajupmochi/graphkit-learn)
 [![Documentation Status](https://readthedocs.org/projects/graphkit-learn/badge/?version=master)](https://graphkit-learn.readthedocs.io/en/master/?badge=master)

gklearn/ged/model/ged_model.py

@@ -258,6 +258,8 @@ def clear_attributes(self):  # @todo: update
 			delattr(self, '_Y')
 		if hasattr(self, '_run_time'):
 			delattr(self, '_run_time')
+		if hasattr(self, '_test_run_time'):
+			delattr(self, '_test_run_time')
 
 
 	def validate_parameters(self):
@@ -330,24 +332,26 @@ def compute_distance_matrix(self, Y=None, **kwargs):
 
 		else:
 			# Compute kernel matrix between Y and self._graphs (X).
+			Y_copy = ([g.copy() for g in Y] if self.copy_graphs else Y)
+			graphs_copy = ([g.copy() for g in
+			                self._graphs] if self.copy_graphs else self._graphs)
+
 			start_time = time.time()
 
 			if self.parallel == 'imap_unordered':
 				dis_matrix = self._compute_distance_matrix_imap_unordered(Y)
 
 			elif self.parallel is None:
-				Y_copy = ([g.copy() for g in Y] if self.copy_graphs else Y)
-				graphs_copy = ([g.copy() for g in
-				                self._graphs] if self.copy_graphs else self._graphs)
 				dis_matrix = self._compute_distance_matrix_series(
 					Y_copy, graphs_copy, **kwargs
 				)
 
-			self._run_time = time.time() - start_time
+			self._test_run_time = time.time() - start_time
+
 			if self.verbose:
 				print(
 					'Distance matrix of size (%d, %d) built in %s seconds.'
-					% (len(Y), len(self._graphs), self._run_time)
+					% (len(Y), len(self._graphs), self._test_run_time)
 				)
 
 		return dis_matrix
@@ -620,10 +624,11 @@ def compute_edit_costs(self, Y=None, Y_targets=None, **kwargs):
 	#		return dis_mat, dis_max, dis_min, dis_mean
 
 	def _compute_X_distance_matrix(self, **kwargs):
-		start_time = time.time()
-
 		graphs = ([g.copy() for g in
 		           self._graphs] if self.copy_graphs else self._graphs)
+
+		start_time = time.time()
+
 		if self.parallel == 'imap_unordered':
 			dis_matrix = self._compute_X_dm_imap_unordered(graphs, **kwargs)
 		elif self.parallel is None:
@@ -632,6 +637,7 @@ def _compute_X_distance_matrix(self, **kwargs):
 			raise Exception('Parallel mode is not set correctly.')
 
 		self._run_time = time.time() - start_time
+
 		if self.verbose:
 			print(
 				'Distance matrix of size %d built in %s seconds.'
@@ -646,7 +652,7 @@ def _compute_X_dm_series(self, graphs, **kwargs):
 		dis_matrix = np.zeros((n, n))
 
 		iterator = combinations(range(n), 2)
-		len_itr = int(n * (n + 1) / 2)
+		len_itr = int(n * (n - 1) / 2)
 		if self.verbose:
 			print('Graphs in total: %d.' % len(graphs))
 			print('The total # of pairs is %d.' % len_itr)
@@ -780,6 +786,26 @@ def is_graph(self, graph):
 		if isinstance(graph, nx.MultiDiGraph):
 			return True
 		return False
+
+
+	def __repr__(self):
+		return (
+			f"{self.__class__.__name__}("
+			f"optim_method={self.optim_method}, "
+			f"ed_method={self.ed_method}, "
+			f"edit_cost_fun={self.edit_cost_fun}, "
+			f"node_labels={self.node_labels}, "
+			f"edge_labels={self.edge_labels}, "
+			f"optim_options={self.optim_options}, "
+			f"init_edit_cost_constants={self.init_edit_cost_constants}, "
+			f"copy_graphs={self.copy_graphs}, "
+			f"parallel={self.parallel}, "
+			f"n_jobs={self.n_jobs}, "
+			f"verbose={self.verbose}, "
+			f"normalize={self.normalize}, "
+			f"run_time={self.run_time}"
+			f")"
+		)
 
 
 	@property
@@ -807,15 +833,18 @@ def graphs(self):
 	def run_time(self):
 		return self._run_time
 
+	@property
+	def test_run_time(self):
+		return self._test_run_time
 
 	@property
 	def dis_matrix(self):
-		return self._dis_matrix
+		return self._dm_train
 
 
 	@dis_matrix.setter
 	def dis_matrix(self, value):
-		self._dis_matrix = value
+		self._dm_train = value
 
 
 	@property