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 )