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https://github.com/SheffieldML/GPy.git
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fixing now works, removing parameters needs fixing
This commit is contained in:
Max Zwiessele
parent
d2e8807a88
commit
f71af38505
7 changed files with 100 additions and 147 deletions
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@ -8,15 +8,10 @@ import cPickle
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import itertools
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from re import compile, _pattern_type
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from param import ParamConcatenation, Param
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from parameter_core import Constrainable, Pickleable, Observable, adjust_name_for_printing, Gradcheckable, __fixed__
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from parameter_core import Constrainable, Pickleable, Observable, adjust_name_for_printing, Gradcheckable
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from transformations import __fixed__, FIXED, UNFIXED
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from array_core import ParamList
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#===============================================================================
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# constants
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FIXED = False
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UNFIXED = True
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#===============================================================================
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class Parameterized(Constrainable, Pickleable, Observable, Gradcheckable):
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"""
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Parameterized class
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@ -71,37 +66,6 @@ class Parameterized(Constrainable, Pickleable, Observable, Gradcheckable):
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self._added_names_ = set()
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del self._in_init_
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#===========================================================================
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# Parameter connection for model creation:
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#===========================================================================
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# def set_as_parameter(self, name, array, gradient, index=None, gradient_parent=None):
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# """
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# :param name: name of the param (in print and plots), can be callable without parameters
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# :type name: str, callable
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# :param array: array which the param consists of
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# :type array: array-like
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# :param gradient: gradient method of the param
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# :type gradient: callable
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# :param index: (optional) index of the param when printing
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#
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# (:param gradient_parent: connect these parameters to this class, but tell
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# updates to highest_parent, this is needed when parameterized classes
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# contain parameterized classes, but want to access the parameters
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# of their children)
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#
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#
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# Set array (e.g. self.X) as param with name and gradient.
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# I.e: self.set_as_parameter('curvature', self.lengthscale, self.dK_dlengthscale)
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#
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# Note: the order in which parameters are added can be adjusted by
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# giving an index, of where to put this param in printing
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# """
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# if index is None:
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# self._parameters_.append(Param(name, array, gradient))
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# else:
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# self._parameters_.insert(index, Param(name, array, gradient))
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# self._connect_parameters(gradient_parent=gradient_parent)
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def _has_fixes(self):
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return hasattr(self, "_fixes_") and self._fixes_ is not None
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@ -118,53 +82,22 @@ class Parameterized(Constrainable, Pickleable, Observable, Gradcheckable):
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# if param.has_parent():
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# raise AttributeError, "parameter {} already in another model, create new object (or copy) for adding".format(param._short())
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if param in self._parameters_ and index is not None:
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# make sure fixes and constraints are indexed right
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if self._has_fixes():
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param_slice = slice(self._offset_for(param), self._offset_for(param) + param.size)
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dest_index = sum((p.size for p in self._parameters_[:index]))
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dest_slice = slice(dest_index, dest_index + param.size)
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fixes_param = self._fixes_[param_slice].copy()
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self._fixes_[param_slice] = self._fixes_[dest_slice]
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self._fixes_[dest_slice] = fixes_param
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del self._parameters_[param._parent_index_]
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self._parameters_.insert(index, param)
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self.remove_parameter(param)
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self.add_parameter(param, index)
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elif param not in self._parameters_:
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# make sure the size is set
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if not hasattr(self, 'size'):
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self.size = sum(p.size for p in self._parameters_)
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if index is None:
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self._parameters_.append(param)
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# make sure fixes and constraints are indexed right
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if param._has_fixes(): fixes_param = param._fixes_.copy()
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else: fixes_param = numpy.ones(param.size, dtype=bool)
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if self._has_fixes(): self._fixes_ = np.r_[self._fixes_, fixes_param]
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elif param._has_fixes(): self._fixes_ = np.r_[np.ones(self.size, dtype=bool), fixes_param]
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else:
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start = sum(p.size for p in self._parameters_[:index])
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self.constraints.shift(start, param.size)
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self._parameters_.insert(index, param)
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# make sure fixes and constraints are indexed right
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if param._has_fixes(): fixes_param = param._fixes_.copy()
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else: fixes_param = numpy.ones(param.size, dtype=bool)
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ins = sum((p.size for p in self._parameters_[:index]))
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if self._has_fixes(): self._fixes_ = np.r_[self._fixes_[:ins], fixes_param, self._fixes[ins:]]
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elif not np.all(fixes_param):
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self._fixes_ = np.ones(self.size + param.size, dtype=bool)
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self._fixes_[ins:ins + param.size] = fixes_param
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self.size += param.size
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else:
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raise RuntimeError, """Parameter exists already added and no copy made"""
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self._connect_parameters()
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for p in self._parameters_:
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p._parent_changed(self)
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if param._default_constraint_ is not None:
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param.constrain(param._default_constraint_, False)
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if self._has_fixes() and np.all(self._fixes_): # ==UNFIXED
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self._fixes_ = None
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def add_parameters(self, *parameters):
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"""
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@ -173,18 +106,20 @@ class Parameterized(Constrainable, Pickleable, Observable, Gradcheckable):
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"""
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[self.add_parameter(p) for p in parameters]
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def remove_parameter(self, *names_params_indices):
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def remove_parameter(self, param):
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"""
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:param names_params_indices: mix of parameter_names, param objects, or indices
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to remove from being a param of this parameterized object.
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note: if it is a string object it will not (!) be regexp-matched
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automatically.
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:param param: param object to remove from being a parameter of this parameterized object.
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"""
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self._parameters_ = ParamList([p for p in self._parameters_
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if not (p._parent_index_ in names_params_indices
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or p.name in names_params_indices
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or p in names_params_indices)])
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if not param in self._parameters_:
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raise RuntimeError, "Parameter {} does not belong to this object, remove parameters directly from their respective parents".format(param._short())
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del self._parameters_[param._parent_index_]
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self.size -= param.size
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constr = param.constraints.copy()
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param.constraints.clear()
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param.constraints = constr
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param._direct_parent_ = None
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param._parent_index_ = None
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param._connect_fixes()
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self._connect_parameters()
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def _connect_parameters(self):
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@ -214,6 +149,8 @@ class Parameterized(Constrainable, Pickleable, Observable, Gradcheckable):
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elif not (pname in not_unique):
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self.__dict__[pname] = p
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self._added_names_.add(pname)
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self._connect_fixes()
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#===========================================================================
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# Pickling operations
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#===========================================================================
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@ -337,7 +274,7 @@ class Parameterized(Constrainable, Pickleable, Observable, Gradcheckable):
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self._added_names_.add(pname)
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self.__dict__[pname] = param
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#===========================================================================
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# Index Handling
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# Indexable Handling
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#===========================================================================
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def _backtranslate_index(self, param, ind):
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# translate an index in parameterized indexing into the index of param
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@ -373,36 +310,10 @@ class Parameterized(Constrainable, Pickleable, Observable, Gradcheckable):
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#===========================================================================
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# Fixing parameters:
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#===========================================================================
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def _set_fixed(self, param_or_index):
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if not self._has_fixes(): self._fixes_ = numpy.ones(self.size, dtype=bool)
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try:
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param_or_index = self._raveled_index_for(param_or_index)
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except AttributeError:
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pass
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self._fixes_[param_or_index] = FIXED
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if numpy.all(self._fixes_): self._fixes_ = None # ==UNFIXED
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def _set_unfixed(self, param_or_index):
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if not self._has_fixes(): self._fixes_ = numpy.ones(self.size, dtype=bool)
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try:
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param_or_index = self._raveled_index_for(param_or_index)
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except AttributeError:
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pass
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self._fixes_[param_or_index] = UNFIXED
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for constr, ind in self.constraints.iteritems():
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if constr is __fixed__:
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self._fixes_[ind] = FIXED
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if numpy.all(self._fixes_): self._fixes_ = None # ==UNFIXED
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def _fixes_for(self, param):
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if self._has_fixes():
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return self._fixes_[self._raveled_index_for(param)]
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return numpy.ones(self.size, dtype=bool)[self._raveled_index_for(param)]
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# def _fix(self, param, warning=True):
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# f = self._add_constrain(param, __fixed__, warning)
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# self._set_fixed(f)
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# def _unfix(self, param):
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# if self._has_fixes():
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# f = self._remove_constrain(param, __fixed__)
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# self._set_unfixed(f)
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#===========================================================================
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# Convenience for fixed, tied checking of param:
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#===========================================================================
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