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subclassing ndarray almost functional
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Max Zwiessele
parent
2ced667193
commit
738f6a5928
1 changed files with 24 additions and 102 deletions
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@ -48,6 +48,9 @@ class Parameters(object):
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return [x.name for x in self._params]
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@property
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def size(self):
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return sum(self.sizes)
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@property
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def sizes(self):
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return [x.size for x in self._params]
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@property
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@ -76,32 +79,20 @@ class Parameters(object):
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pass
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class Parameter(numpy.ndarray):
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class Param(numpy.ndarray):
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tied_to = [] # list of parameters this parameter is tied to
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fixed = False # if this parameter is fixed
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__array_priority__ = 3.0
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__array_priority__ = -1
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def __new__(cls, name, input_array, info=None):
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def __new__(cls, name, input_array, constraints=None):
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obj = numpy.array(input_array).view(cls)
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obj.name = name
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obj._current_slice = slice(None)
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obj._realshape = input_array.shape
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# def attribute_func(value, name):
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# value_func = self.value.__getattribute__(name)
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# def f(*args, **kwargs):
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# with self.slicing():
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# raise AttributeError("This is a parameter view, use self.value for array view")
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# try:
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# f.__doc__ = value_func.__doc__
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# except AttributeError:
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# # no docstring present
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# pass
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# return f
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#
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# for name in dir(value):
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# if not hasattr(self, name):
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# self.__setattr__(name, attribute_func(value, name))#value.__getattribute__(name))
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obj.constraints = ParameterIndexOperations(obj)
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if constraints is None:
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obj.constraints = ParameterIndexOperations(obj)
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else:
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obj.constraints = constraints
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return obj
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def __array_finalize__(self, obj):
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@ -115,51 +106,10 @@ class Parameter(numpy.ndarray):
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def __array_wrap__(self, out_arr, context=None):
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return numpy.ndarray.__array_wrap__(self, out_arr, context)
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# def __init__(self, name, value, constraint=None, *args, **kwargs):
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# self.constraints = ParameterIndexOperations(self)
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#
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# self._value = value
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# self._current_slice = slice(None)
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# def attribute_func(value, name):
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# value_func = self.value.__getattribute__(name)
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# def f(*args, **kwargs):
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# with self.slicing():
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# raise AttributeError("This is a parameter view, use self.value for array view")
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# try:
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# f.__doc__ = value_func.__doc__
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# except AttributeError:
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# # no docstring present
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# pass
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# return f
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#
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# for name in dir(value):
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# if not hasattr(self, name):
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# self.__setattr__(name, attribute_func(value, name))#value.__getattribute__(name))
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# super(Parameter, self).__init__(value, *args, **kwargs)
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@property
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def value(self):
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return self#self.base[self._current_slice]
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# @value.setter
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# def value(self, value):
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# self.base[self._current_slice] = value
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# @property
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# def value(self):
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# return self._value[self._current_slice]
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# @value.setter
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# def value(self, value):
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# self._value[self._current_slice] = value
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# @property
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# def size(self):
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# return self.value.size
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# @property
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# def shape(self):
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# return self.value.shape
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# @property
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# def realshape(self):
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# return self._value.shape
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@property
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def _desc(self):
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if self.size <= 1:
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@ -171,19 +121,19 @@ class Parameter(numpy.ndarray):
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return ' '.join([str(c) if c else '' for c in self.constraints.keys()])
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def _set_params(self, param):
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with self.slicing():
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#with self.slicing():
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self.value.flat = param
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def _get_params(self):
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with self.slicing():
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#with self.slicing():
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return self.value.flat
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def _get_params_transformed(self):
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with self.slicing():
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#with self.slicing():
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params = self.value.copy()
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def constrain(self, constraint):
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with self.slicing():
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#with self.slicing():
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self.constraints.add(constraint, self._current_slice)
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def constrain_positive(self):
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@ -193,7 +143,7 @@ class Parameter(numpy.ndarray):
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self.constrain(NegativeLogexp())
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def unconstrain(self, constraints=None):
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with self.slicing():
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#with self.slicing():
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if constraints is None:
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constraints = self.constraints.keys()
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elif not isinstance(constraints, (tuple, list, numpy.ndarray)):
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@ -204,37 +154,18 @@ class Parameter(numpy.ndarray):
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def unconstrain_positive(self):
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self.unconstrain(Logexp())
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def __getitem__(self, s, *args, **kwargs):
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#self._current_slice = s
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# import ipdb;ipdb.set_trace()
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new_arr = numpy.ndarray.__getitem__(self, s, *args, **kwargs)
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new_arr = new_arr.view(self.__class__)
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try:
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new_arr._current_slice = s
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except AttributeError:
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# returning 0d array or float, double etc:
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pass
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return new_arr
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# def __getitem__(self, s):
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# try:
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# self.value[s]
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# self._current_slice = s#[s if s else slice(s2) for s,s2 in itertools.izip_longest([s], self.shape, fillvalue=None)]
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# return self
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# except IndexError as i:
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# self._current_slice = slice(None)
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# raise i
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#
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# def __setitem__(self, s, value):
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# try:
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# self.value[s] = value
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# self._current_slice = slice(None)
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# return self
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# except IndexError as i:
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# raise i
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#
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#
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def __repr__(self, *args, **kwargs):
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view = str(self.value)
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return super(Param, self).__repr__(*args, **kwargs)
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view = repr(self.value)
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return view
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def __str__(self, format_spec=None):
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@ -255,22 +186,13 @@ class Parameter(numpy.ndarray):
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header = " {i:^{3}s} | {x:^{1}s} | {c:^{0}s}".format(lc,lx,p,li, x=x_name, c=c_name, i=i_name)
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return "\n".join([header]+[" {i:^{3}s} | {x: >{1}.{2}G} | {c:^{0}s}".format(lc,lx,p,li, x=x, c=constr.next(), i=i) for i,x in itertools.izip(ind,self.value.flat)])
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return format_spec.format(self=self)
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import contextlib
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@contextlib.contextmanager
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def slicing(self, *args, **kwargs):
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try:
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yield
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finally:
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self._current_slice = slice(None)
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del contextlib
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if __name__ == '__main__':
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X = numpy.random.randn(2,4)
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p = Parameter("X", X)
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p2 = Parameter("Y", numpy.random.randn(3,1))
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p3 = Parameter("rbf_variance", numpy.random.rand(1))
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p4 = Parameter("rbf_lengthscale", numpy.random.rand(2))
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p = Param("X", X)
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p2 = Param("Y", numpy.random.randn(3,1))
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p3 = Param("rbf_variance", numpy.random.rand(1))
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p4 = Param("rbf_lengthscale", numpy.random.rand(2))
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params = Parameters([p,p2,p3,p4])
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params.X[1].constrain_positive()
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print params.X
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