apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-05-07 19:12:40 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

[visualize] vector show again

Browse source
This commit is contained in:
Max Zwiessele 2014-05-12 14:41:02 +01:00
parent ead4f6787a
commit e9260b248c
2 changed files with 4 additions and 5 deletions
Download patch file Download diff file Expand all files Collapse all files

4
GPy/examples/dimensionality_reduction.py
View file

@ -177,7 +177,7 @@ def bgplvm_oil(optimize=True, verbose=1, plot=True, N=200, Q=7, num_inducing=40,
if plot: if plot:
fig, (latent_axes, sense_axes) = plt.subplots(1, 2) fig, (latent_axes, sense_axes) = plt.subplots(1, 2)
m.plot_latent(ax=latent_axes, labels=m.data_labels) m.plot_latent(ax=latent_axes, labels=m.data_labels)
data_show = GPy.plotting.matplot_dep.visualize.vector_show(np.zeros((m.Y.shape[1], 1))) data_show = GPy.plotting.matplot_dep.visualize.vector_show((m.Y[0,:]))
lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm_dimselect(param_to_array(m.X.mean)[0:1,:], # @UnusedVariable lvm_visualizer = GPy.plotting.matplot_dep.visualize.lvm_dimselect(param_to_array(m.X.mean)[0:1,:], # @UnusedVariable
m, data_show, latent_axes=latent_axes, sense_axes=sense_axes) m, data_show, latent_axes=latent_axes, sense_axes=sense_axes)
raw_input('Press enter to finish') raw_input('Press enter to finish')
@ -186,7 +186,7 @@ def bgplvm_oil(optimize=True, verbose=1, plot=True, N=200, Q=7, num_inducing=40,
def _simulate_sincos(D1, D2, D3, N, num_inducing, Q, plot_sim=False): def _simulate_sincos(D1, D2, D3, N, num_inducing, Q, plot_sim=False):
_np.random.seed(1234) _np.random.seed(1234)
x = _np.linspace(0, 4 * _np.pi, N)[:, None] x = _np.linspace(0, 4 * _np.pi, N)[:, None]
s1 = _np.vectorize(lambda x: _np.sin(x)) s1 = _np.vectorize(lambda x: _np.sin(x))
s2 = _np.vectorize(lambda x: _np.cos(x)**2) s2 = _np.vectorize(lambda x: _np.cos(x)**2)

5
GPy/plotting/matplot_dep/visualize.py
View file

@ -77,13 +77,12 @@ class vector_show(matplotlib_show):
#assert vals.ndim == 2, "Please give a vector in [n x 1] to plot" #assert vals.ndim == 2, "Please give a vector in [n x 1] to plot"
#assert vals.shape[1] == 1, "only showing a vector in one dimension" #assert vals.shape[1] == 1, "only showing a vector in one dimension"
self.size = vals.size self.size = vals.size
self.handle = self.axes.plot(np.arange(0, vals.size)[:, None], vals)[0]
self.handle = self.axes.plot(np.arange(0, vals.size)[:, None], self.vals)[0]
def modify(self, vals): def modify(self, vals):
self.vals = vals.copy() self.vals = vals.copy()
xdata, ydata = self.handle.get_data() xdata, ydata = self.handle.get_data()
assert vals.size == self.size, "values passed into modify changed size! vals:{} != in:{}".format(vals.size, self.size) assert vals.size == self.size, "values passed into modify changed size! vals.size:{} != in.size:{}".format(vals.size, self.size)
self.handle.set_data(xdata, self.vals) self.handle.set_data(xdata, self.vals)
self.axes.figure.canvas.draw() self.axes.figure.canvas.draw()