mirror of
https://github.com/SheffieldML/GPy.git
synced 2026-06-02 14:45:15 +02:00
merged array_core
This commit is contained in:
commit
643c90010b
7 changed files with 22 additions and 26 deletions
|
|
@ -13,7 +13,7 @@ class ParamList(list):
|
|||
if el is other:
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
pass
|
||||
|
||||
class ObservableArray(np.ndarray, Observable):
|
||||
|
|
@ -33,7 +33,7 @@ class ObservableArray(np.ndarray, Observable):
|
|||
# see InfoArray.__array_finalize__ for comments
|
||||
if obj is None: return
|
||||
self._observers_ = getattr(obj, '_observers_', None)
|
||||
|
||||
|
||||
def __setitem__(self, s, val, update=True):
|
||||
super(ObservableArray, self).__setitem__(s, val)
|
||||
if update:
|
||||
|
|
@ -41,10 +41,11 @@ class ObservableArray(np.ndarray, Observable):
|
|||
def __getslice__(self, start, stop):
|
||||
return self.__getitem__(slice(start, stop))
|
||||
def __setslice__(self, start, stop, val):
|
||||
return self.__setitem__(slice(start, stop), val)
|
||||
return self.__setitem__(slice(start, stop), val)
|
||||
|
||||
def __copy__(self, *args):
|
||||
return ObservableArray(self.base.base.copy(*args))
|
||||
return ObservableArray(self.view(np.ndarray).copy())
|
||||
|
||||
def copy(self, *args):
|
||||
return self.__copy__(*args)
|
||||
|
||||
|
|
@ -52,32 +53,27 @@ class ObservableArray(np.ndarray, Observable):
|
|||
r = np.ndarray.__ror__(self, *args, **kwargs)
|
||||
self._notify_observers()
|
||||
return r
|
||||
|
||||
|
||||
def __ilshift__(self, *args, **kwargs):
|
||||
r = np.ndarray.__ilshift__(self, *args, **kwargs)
|
||||
self._notify_observers()
|
||||
return r
|
||||
|
||||
|
||||
def __irshift__(self, *args, **kwargs):
|
||||
r = np.ndarray.__irshift__(self, *args, **kwargs)
|
||||
self._notify_observers()
|
||||
return r
|
||||
|
||||
|
||||
def __rrshift__(self, *args, **kwargs):
|
||||
r = np.ndarray.__rrshift__(self, *args, **kwargs)
|
||||
self._notify_observers()
|
||||
return r
|
||||
|
||||
|
||||
def __ixor__(self, *args, **kwargs):
|
||||
r = np.ndarray.__ixor__(self, *args, **kwargs)
|
||||
self._notify_observers()
|
||||
return r
|
||||
|
||||
|
||||
def __rxor__(self, *args, **kwargs):
|
||||
r = np.ndarray.__rxor__(self, *args, **kwargs)
|
||||
self._notify_observers()
|
||||
|
|
|
|||
|
|
@ -152,14 +152,14 @@ class Param(ObservableArray, Constrainable, Gradcheckable):
|
|||
#===========================================================================
|
||||
def tie_to(self, param):
|
||||
"""
|
||||
:param param: the parameter object to tie this parameter to.
|
||||
:param param: the parameter object to tie this parameter to.
|
||||
Can be ParamConcatenation (retrieved by regexp search)
|
||||
|
||||
|
||||
Tie this parameter to the given parameter.
|
||||
Broadcasting is not allowed, but you can tie a whole dimension to
|
||||
one parameter: self[:,0].tie_to(other), where other is a one-value
|
||||
parameter.
|
||||
|
||||
|
||||
Note: For now only one parameter can have ties, so all of a parameter
|
||||
will be removed, when re-tieing!
|
||||
"""
|
||||
|
|
@ -529,7 +529,7 @@ class ParamConcatenation(object):
|
|||
def checkgrad(self, verbose=0, step=1e-6, tolerance=1e-3):
|
||||
return self.params[0]._highest_parent_._checkgrad(self, verbose, step, tolerance)
|
||||
#checkgrad.__doc__ = Gradcheckable.checkgrad.__doc__
|
||||
|
||||
|
||||
__lt__ = lambda self, val: self._vals() < val
|
||||
__le__ = lambda self, val: self._vals() <= val
|
||||
__eq__ = lambda self, val: self._vals() == val
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue