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merged static

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Max Zwiessele 2014-02-24 14:50:23 +00:00
commit 22403a266f
15 changed files with 623 additions and 1138 deletions
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17
GPy/plotting/matplot_dep/models_plots.py
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@ -20,7 +20,7 @@ def plot_fit(model, plot_limits=None, which_data_rows='all',
- In higher dimensions, use fixed_inputs to plot the GP with some of the inputs fixed.
Can plot only part of the data and part of the posterior functions
using which_data_rowsm which_data_ycols.
using which_data_rowsm which_data_ycols.
:param plot_limits: The limits of the plot. If 1D [xmin,xmax], if 2D [[xmin,ymin],[xmax,ymax]]. Defaluts to data limits
:type plot_limits: np.array
@ -56,10 +56,12 @@ def plot_fit(model, plot_limits=None, which_data_rows='all',
if ax is None:
fig = pb.figure(num=fignum)
ax = fig.add_subplot(111)
X, Y, Z = param_to_array(model.X, model.Y, model.Z)
if model.has_uncertain_inputs(): X_variance = param_to_array(model.q.variance)
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)
@ -68,8 +70,7 @@ def plot_fit(model, plot_limits=None, which_data_rows='all',
if len(free_dims) == 1:
#define the frame on which to plot
resolution = resolution or 200
Xnew, xmin, xmax = x_frame1D(X[:,free_dims], plot_limits=plot_limits)
Xnew, xmin, xmax = x_frame1D(X[:,free_dims], plot_limits=plot_limits, resolution=resolution or 200)
Xgrid = np.empty((Xnew.shape[0],model.input_dim))
Xgrid[:,free_dims] = Xnew
for i,v in fixed_inputs:
@ -95,7 +96,7 @@ def plot_fit(model, plot_limits=None, which_data_rows='all',
ax.plot(Xnew, yi[:,None], Tango.colorsHex['darkBlue'], linewidth=0.25)
#ax.plot(Xnew, yi[:,None], marker='x', linestyle='--',color=Tango.colorsHex['darkBlue']) #TODO apply this line for discrete outputs.
#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(),