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hierarchy edits. adding removing parameters withing hierarchy

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Max Zwiessele 2014-02-28 16:18:47 +00:00
parent c87bda9e49
commit 47e4026141
11 changed files with 106 additions and 64 deletions
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43
GPy/core/parameterization/param.py
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@ -269,7 +269,7 @@ class Param(OptimizationHandlable, ObservableArray, Gradcheckable):
return [t._short() for t in self._tied_to_] or ['']
def __repr__(self, *args, **kwargs):
name = "\033[1m{x:s}\033[0;0m:\n".format(
x=self.hirarchy_name())
x=self.hierarchy_name())
return name + super(Param, self).__repr__(*args, **kwargs)
def _ties_for(self, rav_index):
# size = sum(p.size for p in self._tied_to_)
@ -303,12 +303,12 @@ class Param(OptimizationHandlable, ObservableArray, Gradcheckable):
gen = map(lambda x: " ".join(map(str, x)), gen)
return reduce(lambda a, b:max(a, len(b)), gen, len(header))
def _max_len_values(self):
return reduce(lambda a, b:max(a, len("{x:=.{0}g}".format(__precision__, x=b))), self.flat, len(self.hirarchy_name()))
return reduce(lambda a, b:max(a, len("{x:=.{0}g}".format(__precision__, x=b))), self.flat, len(self.hierarchy_name()))
def _max_len_index(self, ind):
return reduce(lambda a, b:max(a, len(str(b))), ind, len(__index_name__))
def _short(self):
# short string to print
name = self.hirarchy_name()
name = self.hierarchy_name()
if self._realsize_ < 2:
return name
ind = self._indices()
@ -331,8 +331,8 @@ class Param(OptimizationHandlable, ObservableArray, Gradcheckable):
if lp is None: lp = self._max_len_names(prirs, __tie_name__)
sep = '-'
header_format = " {i:{5}^{2}s} | \033[1m{x:{5}^{1}s}\033[0;0m | {c:{5}^{0}s} | {p:{5}^{4}s} | {t:{5}^{3}s}"
if only_name: header = header_format.format(lc, lx, li, lt, lp, ' ', x=self.hirarchy_name(), c=sep*lc, i=sep*li, t=sep*lt, p=sep*lp) # nice header for printing
else: header = header_format.format(lc, lx, li, lt, lp, ' ', x=self.hirarchy_name(), c=__constraints_name__, i=__index_name__, t=__tie_name__, p=__priors_name__) # nice header for printing
if only_name: header = header_format.format(lc, lx, li, lt, lp, ' ', x=self.hierarchy_name(), c=sep*lc, i=sep*li, t=sep*lt, p=sep*lp) # nice header for printing
else: header = header_format.format(lc, lx, li, lt, lp, ' ', x=self.hierarchy_name(), c=__constraints_name__, i=__index_name__, t=__tie_name__, p=__priors_name__) # nice header for printing
if not ties: ties = itertools.cycle([''])
return "\n".join([header] + [" {i!s:^{3}s} | {x: >{1}.{2}g} | {c:^{0}s} | {p:^{5}s} | {t:^{4}s} ".format(lc, lx, __precision__, li, lt, lp, x=x, c=" ".join(map(str, c)), p=" ".join(map(str, p)), t=(t or ''), i=i) for i, x, c, t, p in itertools.izip(indices, vals, constr_matrix, ties, prirs)]) # return all the constraints with right indices
# except: return super(Param, self).__str__()
@ -356,6 +356,21 @@ class ParamConcatenation(object):
self._param_sizes = [p.size for p in self.params]
startstops = numpy.cumsum([0] + self._param_sizes)
self._param_slices_ = [slice(start, stop) for start,stop in zip(startstops, startstops[1:])]
parents = dict()
for p in self.params:
if p.has_parent():
parent = p._direct_parent_
level = 0
while parent is not None:
if parent in parents:
parents[parent] = max(level, parents[parent])
else:
parents[parent] = level
level += 1
parent = parent._direct_parent_
import operator
self.parents = map(lambda x: x[0], sorted(parents.iteritems(), key=operator.itemgetter(1)))
#===========================================================================
# Get/set items, enable broadcasting
#===========================================================================
@ -369,24 +384,26 @@ class ParamConcatenation(object):
val = val._vals()
ind = numpy.zeros(sum(self._param_sizes), dtype=bool); ind[s] = True;
vals = self._vals(); vals[s] = val; del val
[numpy.place(p, ind[ps], vals[ps]) and update and p._notify_observers()
[numpy.place(p, ind[ps], vals[ps])
for p, ps in zip(self.params, self._param_slices_)]
if update:
self.update_all_params()
def _vals(self):
return numpy.hstack([p._get_params() for p in self.params])
#===========================================================================
# parameter operations:
#===========================================================================
def update_all_params(self):
for p in self.params:
p._notify_observers()
for par in self.parents:
par._notify_observers(-numpy.inf)
def constrain(self, constraint, warning=True):
[param.constrain(constraint, update=False) for param in self.params]
[param.constrain(constraint, trigger_parent=False) for param in self.params]
self.update_all_params()
constrain.__doc__ = Param.constrain.__doc__
def constrain_positive(self, warning=True):
[param.constrain_positive(warning, update=False) for param in self.params]
[param.constrain_positive(warning, trigger_parent=False) for param in self.params]
self.update_all_params()
constrain_positive.__doc__ = Param.constrain_positive.__doc__
@ -396,12 +413,12 @@ class ParamConcatenation(object):
fix = constrain_fixed
def constrain_negative(self, warning=True):
[param.constrain_negative(warning, update=False) for param in self.params]
[param.constrain_negative(warning, trigger_parent=False) for param in self.params]
self.update_all_params()
constrain_negative.__doc__ = Param.constrain_negative.__doc__
def constrain_bounded(self, lower, upper, warning=True):
[param.constrain_bounded(lower, upper, warning, update=False) for param in self.params]
[param.constrain_bounded(lower, upper, warning, trigger_parent=False) for param in self.params]
self.update_all_params()
constrain_bounded.__doc__ = Param.constrain_bounded.__doc__