def __init__(self, value=None, N=1, proposal=numpy.eye(1)):
#print numpy.array([0.0]*N), [prposal
if value is None:
value = numpy.random.multivariate_normal(numpy.array([0.0] * N),
proposal)
Hypothesis.__init__(self, value=value)
self.__dict__.update(locals())
def __init__(self, value=None, n=1, proposal=None):
if proposal is None:
proposal = numpy.eye(n)
if value is None:
value = numpy.random.multivariate_normal(numpy.array([0.0]*n), proposal)
Hypothesis.__init__(self, value=value)
self.n = n
self.proposal = proposal
self.__dict__.update(locals())
def __init__(self, value=None, f=None, args=['x']): """ value - the value of this hypothesis f - defaultly None, in which case this uses self.value2function args - the argumetns to the function """ self.args = args # must come first since below calls value2function Hypothesis.__init__(self,value) # this initializes prior and likleihood variables, so keep it here! self.set_value(value,f)
def __init__(self, value=None, n=1, proposal=None, propose_scale=1.0, propose_n=1):
self.n = n
self.propose_n = propose_n
if value is None:
value = np.random.multivariate_normal(np.array([0.0] * n), proposal)
if proposal is None:
proposal = np.eye(n) * propose_scale
propose_mask = self.get_propose_mask()
proposal = proposal * propose_mask
self.proposal = proposal
Hypothesis.__init__(self, value=value)
self_update(self, locals())
def __init__(self, value=None, f=None, args=['x'], **kwargs):
"""
*value* - the value of this hypothesis
*f* - defaultly None, in which case this uses self.value2function
*args* - the arguments to the function
"""
self.args = args # must come first since below calls value2function
Hypothesis.__init__(
self, value, **kwargs
) # this initializes prior and likleihood variables, so keep it here!
self.set_value(value, f)
def __init__(self, value=None, f=None, display="lambda x: %s", **kwargs):
"""
*value* - the value of this hypothesis
*f* - defaultly None, in which case this uses self.value2function
*args* - the arguments to the function
"""
# this initializes prior and likleihood variables, so keep it here!
# However, don't give it value, since then it calls set_value with no f argument!
Hypothesis.__init__(self, None, display=display, **kwargs)
# And set our value
self.set_value(value, f=f)
def __init__(self, value=None, f=None, args=['x'], **kwargs):
"""
*value* - the value of this hypothesis
*f* - defaultly None, in which case this uses self.value2function
*args* - the arguments to the function
"""
self.args = args # must come first since below calls value2function
# this initializes prior and likleihood variables, so keep it here!
# However, don't give it value, since then it calls set_value with no f argument!
Hypothesis.__init__(self, None, **kwargs)
# And set our value
self.set_value(value, f=f)
def __init__(self, value=None, f=None, args=['x'], **kwargs):
"""
*value* - the value of this hypothesis
*f* - defaultly None, in which case this uses self.value2function
*args* - the arguments to the function
"""
self.args = args # must come first since below calls value2function
# this initializes prior and likleihood variables, so keep it here!
# However, don't give it value, since then it calls set_value with no f argument!
Hypothesis.__init__(self, None, **kwargs)
# And set our value
self.set_value(value, f=f)
def __init__(self,
value=None,
n=1,
proposal=None,
propose_scale=1.0,
propose_n=1):
self.n = n
self.propose_n = propose_n
if value is None:
value = np.random.multivariate_normal(np.array([0.0] * n),
proposal)
if proposal is None:
proposal = np.eye(n) * propose_scale
propose_mask = self.get_propose_mask()
proposal = proposal * propose_mask
self.proposal = proposal
Hypothesis.__init__(self, value=value)
self_update(self, locals())
def __init__(self,value=None, N=1, proposal=numpy.eye(1)):
#print numpy.array([0.0]*N), [prposal
if value is None: value = numpy.random.multivariate_normal(numpy.array([0.0]*N), proposal)
Hypothesis.__init__(self, value=value)
self.__dict__.update(locals())
