def __init__(self, file, **args):
"""
:Keywords:
- `headerRow` - True/False depending on whether the file contains a
header row that provides feature IDs
- `idColumn` - set to 0 if the data has pattern IDs in the first column
- `labelsColumn` - possible values: if there are no patternIDs
it is either 0 or -1, and if there are patternIDs, 1 or -1
"""
Parser.__init__(self, file, **args)
PyMLobject.__init__(self, None, **args)
if self.labelsColumn == 1:
self.idColumn = 0
if self.idColumn is None and self.labelsColumn is None:
self._first = 0
else:
self._first = max(self.idColumn, self.labelsColumn) + 1
def __init__(self, file, **args):
"""
:Keywords:
- `headerRow` - True/False depending on whether the file contains a
header row that provides feature IDs
- `idColumn` - set to 0 if the data has pattern IDs in the first column
- `labelsColumn` - possible values: if there are no patternIDs
it is either 0 or -1, and if there are patternIDs, 1 or -1
"""
Parser.__init__(self, file, **args)
PyMLobject.__init__(self, None, **args)
if self.labelsColumn == 1:
self.idColumn = 0
if self.idColumn is None and self.labelsColumn is None:
self._first = 0
else:
self._first = max(self.idColumn, self.labelsColumn) + 1
def __init__(self, **args):
PyMLobject.__init__(self, **args)
def __init__(self, arg = None, **args) :
PyMLobject.__init__(self, arg, **args)
if type(arg) == type('') :
self.load(arg)
self.log = misc.Container()
def __init__(self, **args) :
PyMLobject.__init__(self, **args)
def __init__(self, arg=None, **args):
PyMLobject.__init__(self, arg, **args)
if type(arg) == type(''):
self.load(arg)
self.log = misc.Container()
