def plearn_repr(self, indent_level=0, inner_repr=plearn_repr):
"""PLearn representation of this python object.
Are considered as elements any non-None attributes.
"""
elem_format = lambda elem: inner_repr( elem, indent_level+1 )
return '[%s]' % format_list_elements([optval for optval in iter(self)],
elem_format, indent_level+1)
def plearn_repr(self, indent_level=0, inner_repr=plearn_repr):
"""PLearn representation of this python object.
Are considered as elements any non-None attributes.
"""
elem_format = lambda elem: inner_repr(elem, indent_level + 1)
return '[%s]' % format_list_elements([optval for optval in iter(self)],
elem_format, indent_level + 1)
def plearn_repr(self, indent_level=0, inner_repr=plearn_repr):
"""PLearn representation of this python object.
Are considered as options any 'public' instance attributes.
"""
options = format_list_elements(
[(optname, optval) for (optname, optval) in self.iteritems()],
lambda opt_pair: self._optionFormat(opt_pair, indent_level,
inner_repr), indent_level + 1)
return "%s(%s)" % (self.classname(), options)
def plearn_repr(self, indent_level=0, inner_repr=plearn_repr):
"""PLearn representation of this python object.
Are considered as options any 'public' instance attributes.
"""
options = format_list_elements(
[ (optname,optval) for (optname,optval) in self.iteritems() ],
lambda opt_pair: self._optionFormat(opt_pair, indent_level, inner_repr),
indent_level+1
)
return "%s(%s)" % (self.classname(), options)
def plearn_repr( self, indent_level=0, inner_repr=plearn_repr ):
# asking for plearn_repr could be to send specification over
# to another prg so that will open the .pmat
# So we make sure data is flushed to disk.
self.flush()
def elem_format( elem ):
k, v = elem
return '%s = %s' % ( k, inner_repr(v, indent_level+1) )
options = [ ( 'filename', self.fname ),
( 'inputsize', self.inputsize ),
( 'targetsize', self.targetsize ),
( 'weightsize', self.weightsize ) ]
return 'FileVMatrix(%s)' % format_list_elements( options, elem_format, indent_level+1 )
