def testPlottingDataNotShow(self):
m = GPy.models.SparseGPRegression(self.X, self.Y)
p = PredictionModelSparse(m)
p.plot_data()
fig, ax1 = plt.subplots()
p.plot(plot_training_data=False, ax=ax1)
ax1.set_ylim(0, 1)
ax1.set_xlim(-2, 2)
#i1 = StringIO()
#fig.savefig(i1, format='svg')
#i1.seek(0)
fig, ax2 = plt.subplots()
p.plot(plot_training_data=True, ax=ax2)
ax2.set_ylim(0, 1)
ax2.set_xlim(-2, 2)
#i2 = StringIO()
#fig.savefig(i2, format='svg')
#i2.seek(0)
cm(fl(ax1), fl(ax2))
m = GPy.models.GPRegression(self.X, self.Y)
p = PredictionModel(m)
p.plot_data()
fig, ax1 = plt.subplots()
p.plot(plot_training_data=False, ax=ax1)
ax1.set_ylim(0, 1)
ax1.set_xlim(-2, 2)
#i1 = StringIO()
#fig.savefig(i1, format='svg')
#i1.seek(0)
fig, ax2 = plt.subplots()
p.plot(plot_training_data=True, ax=ax2)
ax2.set_ylim(0, 1)
ax2.set_xlim(-2, 2)
#i2 = StringIO()
#fig.savefig(i2, format='svg')
#i2.seek(0)
cm(fl(ax1), fl(ax2))
def testPlottingSparseClass(self):
m = GPy.models.SparseGPClassification(self.X, self.Y < 0)
p = PredictionModelSparse(m)
fig, ax1 = plt.subplots()
m.plot(plot_training_data=False, ax=ax1)
ax1.set_ylim(0, 1)
ax1.set_xlim(-2, 2)
#i1 = StringIO()
#fig.savefig(i1, format='svg')
#i1.seek(0)
fig, ax2 = plt.subplots()
p.plot(plot_training_data=False, ax=ax2)
ax2.set_ylim(0, 1)
ax2.set_xlim(-2, 2)
#i2 = StringIO()
#fig.savefig(i2, format='svg')
#i2.seek(0)
#self.assertEqual(i1.read(), i2.read())
cm(fl(ax1), fl(ax2))