def __init__(self, arg, *opt, **args) :
BaseDataSet.__init__(self)
if arg.__class__ == self.__class__ :
other = arg
self.datas = [other.datas[i].__class__(other.datas[i], *opt, **args)
for i in range(len(other.datas))]
elif type(arg) == type([]) :
self.datas = arg
else :
raise ValueError, 'wrong type of input for DataAggregate'
self.labels = self.datas[0].labels
def __init__(self, arg, **args) :
"""
:Parameters:
- `arg` - a file name or another PairDataSet object.
if a file name is supplied the constructor expects a dataset
object as a keyword argument 'data'
:Keywords:
- `data` - a dataset object from which the kernel between the pairs
of patterns is derived.
- `patterns` - patterns to copy when performing copy construction
"""
BaseDataSet.__init__(self, arg, **args)
def __init__(self, arg, **args):
"""
:Parameters:
- `arg` - a file name or another PairDataSet object.
if a file name is supplied the constructor expects a dataset
object as a keyword argument 'data'
:Keywords:
- `data` - a dataset object from which the kernel between the pairs
of patterns is derived.
- `patterns` - patterns to copy when performing copy construction
"""
BaseDataSet.__init__(self, arg, **args)
def __init__(self, arg, **args) :
"""
:Parameters:
- `arg` - either an Aggregate object (for copy construction) or a list
of C++ dataset objects
:Keywords:
- `weights` - a list of weights used for computing the dot product
element i is the weight for dataset i in the aggregate
"""
BaseDataSet.__init__(self, arg, **args)
self._trainingFunc = self.aggregate_train
self._testingFunc = self.aggregate_test
def __init__(self, arg, **args):
"""
:Parameters:
- `arg` - a file name or another PairDataSet object.
if a file name is supplied the constructor expects a dataset
object as a keyword argument 'data'
:Keywords:
- `data` - a dataset object from which the kernel between the pairs
of patterns is derived.
- `patterns` - patterns to copy when performing copy construction
"""
BaseDataSet.__init__(self)
if arg.__class__ == self.__class__:
self.copyConstruct(arg, **args)
elif type(arg) == type(''):
if 'data' not in args:
raise ValueError, 'missing data object'
self._data = args['data']
self.constructFromFile(arg)
self.attachKernel('linear')
def __init__(self, arg, **args):
"""
:Parameters:
- `arg` - a file name or another PairDataSet object.
if a file name is supplied the constructor expects a dataset
object as a keyword argument 'data'
:Keywords:
- `data` - a dataset object from which the kernel between the pairs
of patterns is derived.
- `patterns` - patterns to copy when performing copy construction
"""
BaseDataSet.__init__(self)
if arg.__class__ == self.__class__:
self.copyConstruct(arg, **args)
elif type(arg) == type(""):
if "data" not in args:
raise ValueError, "missing data object"
self._data = args["data"]
self.constructFromFile(arg)
self.attachKernel("linear")
def __init__(self, arg, **args) :
"""
:Parameters:
- `arg` - a file name or another PairDataSet object.
if a file name is supplied the constructor expects a dataset
object as a keyword argument 'data'
:Keywords:
- `data` - a dataset object from which the kernel between the pairs
of patterns is derived.
- `patterns` - patterns to copy when performing copy construction
"""
BaseDataSet.__init__(self)
if arg.__class__ == self.__class__ :
if 'patterns' in args :
patterns = args['patterns']
else :
patterns = range(len(arg))
self.copyConstruct(arg, patterns)
elif type(arg) == type('') :
if 'data' not in args :
raise ValueError, 'missing data object'
self.data = args['data']
self.constructFromFile(arg)
def __init__(self, arg=None, **args) :
self.container = csequencedata.SequenceData
BaseDataSet.__init__(self, arg, **args)
self.initialize(**args)
def __init__(self, arg=None, **args):
self.container = csequencedata.SequenceData
BaseDataSet.__init__(self, arg, **args)
self.initialize(**args)
