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logexp_clipped adjust & mrd error messages

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Max Zwiessele 2013-05-22 17:52:09 +01:00
parent 8f5d577bbb
commit 4ef29e1fea
3 changed files with 6 additions and 5 deletions
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6
GPy/core/transformations.py
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@ -39,7 +39,7 @@ class logexp(transformation):
return '(+ve)' return '(+ve)'
class logexp_clipped(transformation): class logexp_clipped(transformation):
max_bound = 1e300 max_bound = 1e100
min_bound = 1e-10 min_bound = 1e-10
log_max_bound = np.log(max_bound) log_max_bound = np.log(max_bound)
log_min_bound = np.log(min_bound) log_min_bound = np.log(min_bound)
@ -53,11 +53,11 @@ class logexp_clipped(transformation):
# import ipdb;ipdb.set_trace() # import ipdb;ipdb.set_trace()
return np.clip(f, self.min_bound, self.max_bound) return np.clip(f, self.min_bound, self.max_bound)
def finv(self, f): def finv(self, f):
return np.log(np.exp(np.clip(f, self.min_bound, self.max_bound)) - 1.) return np.log(np.exp(f - 1.))
def gradfactor(self, f): def gradfactor(self, f):
ef = np.exp(f) # np.clip(f, self.min_bound, self.max_bound)) ef = np.exp(f) # np.clip(f, self.min_bound, self.max_bound))
gf = (ef - 1.) / ef gf = (ef - 1.) / ef
return np.where(f < self.lower, 0, gf) return gf # np.where(f < self.lower, 0, gf)
def initialize(self, f): def initialize(self, f):
if np.any(f < 0.): if np.any(f < 0.):
print "Warning: changing parameters to satisfy constraints" print "Warning: changing parameters to satisfy constraints"

4
GPy/examples/dimensionality_reduction.py
View file

@ -278,7 +278,7 @@ def bgplvm_simulation(optimize='scg',
return m return m
def mrd_simulation(optimize=True, plot_sim=False, **kw): def mrd_simulation(optimize=True, plot_sim=False, **kw):
D1, D2, D3, N, M, Q = 150, 200, 400, 700, 3, 7 D1, D2, D3, N, M, Q = 150, 200, 400, 300, 3, 7
slist, Slist, Ylist = _simulate_sincos(D1, D2, D3, N, M, Q, plot_sim) slist, Slist, Ylist = _simulate_sincos(D1, D2, D3, N, M, Q, plot_sim)
from GPy.models import mrd from GPy.models import mrd
@ -287,7 +287,7 @@ def mrd_simulation(optimize=True, plot_sim=False, **kw):
reload(mrd); reload(kern) reload(mrd); reload(kern)
k = kern.linear(Q, [0.01] * Q, True) + kern.bias(Q, np.exp(-2)) + kern.white(Q, np.exp(-2)) k = kern.linear(Q, [0.05] * Q, True) + kern.bias(Q, np.exp(-2)) + kern.white(Q, np.exp(-2))
m = mrd.MRD(Ylist, Q=Q, M=M, kernels=k, initx="concat", initz='permute', **kw) m = mrd.MRD(Ylist, Q=Q, M=M, kernels=k, initx="concat", initz='permute', **kw)
for i, Y in enumerate(Ylist): for i, Y in enumerate(Ylist):

1
GPy/models/mrd.py
View file

@ -56,6 +56,7 @@ class MRD(model):
else: else:
assert len(kernels) == len(likelihood_or_Y_list), "need one kernel per output" assert len(kernels) == len(likelihood_or_Y_list), "need one kernel per output"
assert all([isinstance(k, kern) for k in kernels]), "invalid kernel object detected!" assert all([isinstance(k, kern) for k in kernels]), "invalid kernel object detected!"
assert not ('kernel' in kw), "pass kernels through `kernels` argument"
self.Q = Q self.Q = Q
self.M = M self.M = M