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Fixed MRD inducing point gradients

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This commit is contained in:
Alan Saul 2015-09-24 13:44:28 +01:00
parent 76220cd4d2
commit 7b1c35f83f
5 changed files with 8 additions and 7 deletions
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7
GPy/examples/dimensionality_reduction.py
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@ -405,10 +405,8 @@ def mrd_simulation(optimize=True, verbose=True, plot=True, plot_sim=True, **kw):
D1, D2, D3, N, num_inducing, Q = 60, 20, 36, 60, 6, 5
_, _, Ylist = _simulate_sincos(D1, D2, D3, N, num_inducing, plot_sim)
# Ylist = [Ylist[0]]
k = kern.Linear(Q, ARD=True)
k = kern.Linear(Q) + kern.White(Q, variance=1e-4)
m = MRD(Ylist, input_dim=Q, num_inducing=num_inducing, kernel=k, initx="PCA_concat", initz='permute', **kw)
m['.*noise'] = [Y.var() / 40. for Y in Ylist]
@ -428,8 +426,7 @@ def mrd_simulation_missing_data(optimize=True, verbose=True, plot=True, plot_sim
D1, D2, D3, N, num_inducing, Q = 60, 20, 36, 60, 6, 5
_, _, Ylist = _simulate_matern(D1, D2, D3, N, num_inducing, plot_sim)
# Ylist = [Ylist[0]]
k = kern.Linear(Q, ARD=True)
k = kern.Linear(Q) + kern.White(Q, variance=1e-4)
inanlist = []
for Y in Ylist: