def test_plot_graphs(self):
r"""
Plot all graphs which have coordinates.
With and without signal.
With both backends.
"""
# Graphs who are not embedded, i.e., have no coordinates.
COORDS_NO = {
'Graph',
'BarabasiAlbert',
'ErdosRenyi',
'FullConnected',
'RandomRegular',
'StochasticBlockModel',
}
# Coordinates are not in 2D or 3D.
COORDS_WRONG_DIM = {'ImgPatches'}
Gs = []
for classname in set(graphs.__all__) - COORDS_NO - COORDS_WRONG_DIM:
Graph = getattr(graphs, classname)
# Classes who require parameters.
if classname == 'NNGraph':
Xin = np.arange(90).reshape(30, 3)
Gs.append(Graph(Xin))
elif classname in ['ImgPatches', 'Grid2dImgPatches']:
Gs.append(Graph(img=self._img, patch_shape=(3, 3)))
elif classname == 'LineGraph':
Gs.append(Graph(graphs.Sensor(20, seed=42)))
else:
Gs.append(Graph())
# Add more test cases.
if classname == 'TwoMoons':
Gs.append(Graph(moontype='standard'))
Gs.append(Graph(moontype='synthesized'))
elif classname == 'Cube':
Gs.append(Graph(nb_dim=2))
Gs.append(Graph(nb_dim=3))
elif classname == 'DavidSensorNet':
Gs.append(Graph(N=64))
Gs.append(Graph(N=500))
Gs.append(Graph(N=128))
for G in Gs:
self.assertTrue(hasattr(G, 'coords'))
self.assertEqual(G.N, G.coords.shape[0])
signal = np.arange(G.N) + 0.3
G.plot(backend='pyqtgraph')
G.plot(backend='matplotlib')
G.plot(signal, backend='pyqtgraph')
G.plot(signal, backend='matplotlib')
plotting.close_all()
def test_plot_graphs(self):
r"""
Plot all graphs which have coordinates.
With and without signal.
With both backends.
"""
# Graphs who are not embedded, i.e., have no coordinates.
COORDS_NO = {
'Graph',
'BarabasiAlbert',
'ErdosRenyi',
'FullConnected',
'RandomRegular',
'StochasticBlockModel',
}
# Coordinates are not in 2D or 3D.
COORDS_WRONG_DIM = {'ImgPatches'}
Gs = []
for classname in set(graphs.__all__) - COORDS_NO - COORDS_WRONG_DIM:
Graph = getattr(graphs, classname)
# Classes who require parameters.
if classname == 'NNGraph':
Xin = np.arange(90).reshape(30, 3)
Gs.append(Graph(Xin))
elif classname in ['ImgPatches', 'Grid2dImgPatches']:
Gs.append(Graph(img=self._img, patch_shape=(3, 3)))
else:
Gs.append(Graph())
# Add more test cases.
if classname == 'TwoMoons':
Gs.append(Graph(moontype='standard'))
Gs.append(Graph(moontype='synthesized'))
elif classname == 'Cube':
Gs.append(Graph(nb_dim=2))
Gs.append(Graph(nb_dim=3))
elif classname == 'DavidSensorNet':
Gs.append(Graph(N=64))
Gs.append(Graph(N=500))
Gs.append(Graph(N=128))
for G in Gs:
self.assertTrue(hasattr(G, 'coords'))
self.assertEqual(G.N, G.coords.shape[0])
signal = np.arange(G.N) + 0.3
G.plot(backend='pyqtgraph')
G.plot(backend='matplotlib')
G.plot(signal, backend='pyqtgraph')
G.plot(signal, backend='matplotlib')
plotting.close_all()
def test_all_filters(self):
"""Plot all filters."""
for classname in dir(filters):
if not classname[0].isupper():
# Not a Filter class but a submodule or private stuff.
continue
Filter = getattr(filters, classname)
if classname in ['Filter', 'Modulation', 'Gabor']:
g = Filter(self._graph, filters.Heat(self._graph))
else:
g = Filter(self._graph)
g.plot()
plotting.close_all()
def tearDown(cls):
plotting.close_all()
def test_show_close(self):
G = graphs.Sensor()
G.plot()
plotting.show(block=False) # Don't block or the test will halt.
plotting.close()
plotting.close_all()
def test_show_close(self):
G = graphs.Sensor()
G.plot()
plotting.show(block=False) # Don't block or the test will halt.
plotting.close()
plotting.close_all()