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sparse GP now working nicely

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James Hensman 2014-01-31 10:15:30 +00:00
parent e0dbfbe148
commit 9f40ab0f83
3 changed files with 24 additions and 12 deletions
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11
GPy/plotting/matplot_dep/models_plots.py
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@ -5,6 +5,7 @@ import pylab as pb
import numpy as np
import Tango
from base_plots import gpplot, x_frame1D, x_frame2D
from ...util.misc import param_to_array
def plot_fit(model, plot_limits=None, which_data_rows='all',
@ -95,8 +96,11 @@ def plot_fit(model, plot_limits=None, which_data_rows='all',
#add inducing inputs (if a sparse model is used)
if hasattr(model,"Z"):
Zu = model.Z[:,free_dims] * model._Xscale[:,free_dims] + model._Xoffset[:,free_dims]
ax.plot(Zu, np.zeros_like(Zu) + ax.get_ylim()[0], 'r|', mew=1.5, markersize=12)
#Zu = model.Z[:,free_dims] * model._Xscale[:,free_dims] + model._Xoffset[:,free_dims]
Zu = param_to_array(model.Z[:,free_dims])
z_height = ax.get_ylim()[0]
ax.plot(Zu, np.zeros_like(Zu) + z_height, 'r|', mew=1.5, markersize=12)
#add error bars for uncertain (if input uncertainty is being modelled)
if hasattr(model,"has_uncertain_inputs"):
@ -144,7 +148,8 @@ def plot_fit(model, plot_limits=None, which_data_rows='all',
#add inducing inputs (if a sparse model is used)
if hasattr(model,"Z"):
Zu = model.Z[:,free_dims] * model._Xscale[:,free_dims] + model._Xoffset[:,free_dims]
#Zu = model.Z[:,free_dims] * model._Xscale[:,free_dims] + model._Xoffset[:,free_dims]
Zu = model.Z[:,free_dims]
ax.plot(Zu[:,free_dims[0]], Zu[:,free_dims[1]], 'wo')
else: