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ensure_default_constraints is on by default

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James Hensman 2013-06-17 15:57:19 +01:00
parent 4cc26902e4
commit 8fd8288fb8
22 changed files with 16 additions and 71 deletions
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12
GPy/examples/dimensionality_reduction.py
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@ -37,7 +37,6 @@ def BGPLVM(seed=default_seed):
# m.optimize(messages = 1)
# m.plot()
# pb.title('After optimisation')
m.ensure_default_constraints()
m.randomize()
m.checkgrad(verbose=1)
@ -53,7 +52,6 @@ def GPLVM_oil_100(optimize=True):
m.data_labels = data['Y'].argmax(axis=1)
# optimize
m.ensure_default_constraints()
if optimize:
m.optimize('scg', messages=1)
@ -108,7 +106,6 @@ def swiss_roll(optimize=True, N=1000, num_inducing=15, Q=4, sigma=.2, plot=False
m.data_colors = c
m.data_t = t
m.ensure_default_constraints()
m['rbf_lengthscale'] = 1. # X.var(0).max() / X.var(0)
m['noise_variance'] = Y.var() / 100.
m['bias_variance'] = 0.05
@ -134,7 +131,6 @@ def BGPLVM_oil(optimize=True, N=200, Q=10, num_inducing=15, max_f_eval=50, plot=
m['.*lengt'] = 1. # m.X.var(0).max() / m.X.var(0)
m['noise'] = Yn.var() / 100.
m.ensure_default_constraints()
# optimize
if optimize:
@ -159,7 +155,6 @@ def oil_100():
m = GPy.models.GPLVM(data['X'], 2)
# optimize
m.ensure_default_constraints()
m.optimize(messages=1, max_iters=2)
# plot
@ -239,7 +234,6 @@ def bgplvm_simulation_matlab_compare():
# X=mu,
# X_variance=S,
_debug=False)
m.ensure_default_constraints()
m.auto_scale_factor = True
m['noise'] = Y.var() / 100.
m['linear_variance'] = .01
@ -262,7 +256,6 @@ def bgplvm_simulation(optimize='scg',
k = kern.linear(Q, ARD=True) + kern.bias(Q, np.exp(-2)) + kern.white(Q, np.exp(-2)) # + kern.bias(Q)
m = BayesianGPLVM(Y, Q, init="PCA", num_inducing=num_inducing, kernel=k, _debug=True)
# m.constrain('variance|noise', logexp_clipped())
m.ensure_default_constraints()
m['noise'] = Y.var() / 100.
m['linear_variance'] = .01
@ -291,7 +284,6 @@ def mrd_simulation(optimize=True, plot=True, plot_sim=True, **kw):
for i, Y in enumerate(Ylist):
m['{}_noise'.format(i + 1)] = Y.var() / 100.
m.ensure_default_constraints()
# DEBUG
# np.seterr("raise")
@ -319,7 +311,6 @@ def brendan_faces():
# optimize
m.constrain('rbf|noise|white', GPy.core.transformations.logexp_clipped())
m.ensure_default_constraints()
m.optimize('scg', messages=1, max_f_eval=10000)
ax = m.plot_latent(which_indices=(0, 1))
@ -336,7 +327,6 @@ def stick():
m = GPy.models.GPLVM(data['Y'], 2)
# optimize
m.ensure_default_constraints()
m.optimize(messages=1, max_f_eval=10000)
m._set_params(m._get_params())
@ -359,7 +349,6 @@ def cmu_mocap(subject='35', motion=['01'], in_place=True):
m = GPy.models.GPLVM(data['Y'], 2, normalize_Y=True)
# optimize
m.ensure_default_constraints()
m.optimize(messages=1, max_f_eval=10000)
ax = m.plot_latent()
@ -391,7 +380,6 @@ def cmu_mocap(subject='35', motion=['01'], in_place=True):
# m.set('iip', Z)
# m.set('bias', 1e-4)
# # optimize
# # m.ensure_default_constraints()
#
# import pdb; pdb.set_trace()
# m.optimize('tnc', messages=1)