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Added option for plotting with SVGP

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This commit is contained in:
Alan Saul 2015-05-21 16:33:35 +01:00
parent afa0621488
commit d3e79495e7
1 changed files with 9 additions and 3 deletions
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12
GPy/plotting/matplot_dep/models_plots.py
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@ -11,6 +11,7 @@ from base_plots import gpplot, x_frame1D, x_frame2D
from ...models.gp_coregionalized_regression import GPCoregionalizedRegression
from ...models.sparse_gp_coregionalized_regression import SparseGPCoregionalizedRegression
from scipy import sparse
from ...core.parameterization.variational import VariationalPosterior
def plot_fit(model, plot_limits=None, which_data_rows='all',
which_data_ycols='all', fixed_inputs=[],
@ -78,7 +79,7 @@ def plot_fit(model, plot_limits=None, which_data_rows='all',
if predict_kw is None:
predict_kw = {}
#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)
@ -219,7 +220,7 @@ def plot_fit_f(model, *args, **kwargs):
kwargs['plot_raw'] = True
plot_fit(model,*args, **kwargs)
def fixed_inputs(model, non_fixed_inputs, fix_routine='median', as_list=True):
def fixed_inputs(model, non_fixed_inputs, fix_routine='median', as_list=True, X_all=False):
"""
Convenience function for returning back fixed_inputs where the other inputs
are fixed using fix_routine
@ -235,8 +236,13 @@ def fixed_inputs(model, non_fixed_inputs, fix_routine='median', as_list=True):
f_inputs = []
if hasattr(model, 'has_uncertain_inputs') and model.has_uncertain_inputs():
X = model.X.mean.values.copy()
else:
elif isinstance(model.X, VariationalPosterior):
X = model.X.values.copy()
else:
if X_all:
X = model.X_all.copy()
else:
X = model.X.copy()
for i in range(X.shape[1]):
if i not in non_fixed_inputs:
if fix_routine == 'mean':