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plotting conflict fixed

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This commit is contained in:
James Hensman 2014-02-24 13:55:11 +00:00
commit d3eaef5c99
13 changed files with 196 additions and 158 deletions
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16
GPy/plotting/matplot_dep/models_plots.py
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@ -60,6 +60,8 @@ def plot_fit(model, plot_limits=None, which_data_rows='all',
X, Y = param_to_array(model.X, model.Y)
if hasattr(model, 'has_uncertain_inputs') and model.has_uncertain_inputs(): X_variance = model.X_variance
if hasattr(model, 'Z'): Z = param_to_array(model.Z)
#work out what the inputs are for plotting (1D or 2D)
fixed_dims = np.array([i for i,v in fixed_inputs])
free_dims = np.setdiff1d(np.arange(model.input_dim),fixed_dims)
@ -96,10 +98,10 @@ def plot_fit(model, plot_limits=None, which_data_rows='all',
#add error bars for uncertain (if input uncertainty is being modelled)
if hasattr(model,"has_uncertain_inputs") and model.has_uncertain_inputs():
ax.errorbar(X[which_data_rows, free_dims].flatten(), Y[which_data_rows, which_data_ycols].flatten(),
xerr=2 * np.sqrt(X_variance[which_data_rows, free_dims].flatten()),
ecolor='k', fmt=None, elinewidth=.5, alpha=.5)
#if hasattr(model,"has_uncertain_inputs") and model.has_uncertain_inputs():
# ax.errorbar(X[which_data_rows, free_dims].flatten(), Y[which_data_rows, which_data_ycols].flatten(),
# xerr=2 * np.sqrt(X_variance[which_data_rows, free_dims].flatten()),
# ecolor='k', fmt=None, elinewidth=.5, alpha=.5)
#set the limits of the plot to some sensible values
@ -111,7 +113,7 @@ 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 = param_to_array(model.Z[:,free_dims])
Zu = Z[:,free_dims]
z_height = ax.get_ylim()[0]
ax.plot(Zu, np.zeros_like(Zu) + z_height, 'r|', mew=1.5, markersize=12)
@ -135,7 +137,7 @@ def plot_fit(model, plot_limits=None, which_data_rows='all',
Y = Y
else:
m, _, _, _ = model.predict(Xgrid)
Y = model.data
Y = Y
for d in which_data_ycols:
m_d = m[:,d].reshape(resolution, resolution).T
ax.contour(x, y, m_d, levels, vmin=m.min(), vmax=m.max(), cmap=pb.cm.jet)
@ -151,7 +153,7 @@ 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]
Zu = Z[:,free_dims]
ax.plot(Zu[:,free_dims[0]], Zu[:,free_dims[1]], 'wo')
else: