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Source code for galaxy.datatypes.graph

"""
Graph content classes.
"""

import data
import tabular
import xml

import dataproviders
from galaxy.util import simplegraph

import logging
log = logging.getLogger( __name__ )


[docs]@dataproviders.decorators.has_dataproviders class Xgmml( xml.GenericXml ): """ XGMML graph format (http://wiki.cytoscape.org/Cytoscape_User_Manual/Network_Formats). """ file_ext = "xgmml"
[docs] def set_peek( self, dataset, is_multi_byte=False ): """ Set the peek and blurb text """ if not dataset.dataset.purged: dataset.peek = data.get_file_peek( dataset.file_name, is_multi_byte=is_multi_byte ) dataset.blurb = 'XGMML data' else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def sniff( self, filename ): """ Returns false and the user must manually set. """ return False
[docs] @staticmethod def merge( split_files, output_file ): """ Merging multiple XML files is non-trivial and must be done in subclasses. """ if len( split_files ) > 1: raise NotImplementedError( "Merging multiple XML files is non-trivial " + "and must be implemented for each XML type" ) # For one file only, use base class method (move/copy) data.Text.merge( split_files, output_file )
[docs] @dataproviders.decorators.dataprovider_factory( 'node-edge', dataproviders.hierarchy.XMLDataProvider.settings ) def node_edge_dataprovider( self, dataset, **settings ): dataset_source = dataproviders.dataset.DatasetDataProvider( dataset ) return XGMMLGraphDataProvider( dataset_source, **settings )
[docs]@dataproviders.decorators.has_dataproviders class Sif( tabular.Tabular ): """ SIF graph format (http://wiki.cytoscape.org/Cytoscape_User_Manual/Network_Formats). First column: node id Second column: relationship type Third to Nth column: target ids for link """ file_ext = "sif"
[docs] def set_peek( self, dataset, is_multi_byte=False ): """ Set the peek and blurb text """ if not dataset.dataset.purged: dataset.peek = data.get_file_peek( dataset.file_name, is_multi_byte=is_multi_byte ) dataset.blurb = 'SIF data' else: dataset.peek = 'file does not exist' dataset.blurb = 'file purged from disk'
[docs] def sniff( self, filename ): """ Returns false and the user must manually set. """ return False
[docs] @staticmethod def merge( split_files, output_file ): data.Text.merge( split_files, output_file )
[docs] @dataproviders.decorators.dataprovider_factory( 'node-edge', dataproviders.column.ColumnarDataProvider.settings ) def node_edge_dataprovider( self, dataset, **settings ): dataset_source = dataproviders.dataset.DatasetDataProvider( dataset ) return SIFGraphDataProvider( dataset_source, **settings )
# ----------------------------------------------------------------------------- graph specific data providers
[docs]class XGMMLGraphDataProvider( dataproviders.hierarchy.XMLDataProvider ): """ Provide two lists: nodes, edges:: 'nodes': contains objects of the form: { 'id' : <some string id>, 'data': <any extra data> } 'edges': contains objects of the form: { 'source' : <an index into nodes>, 'target': <an index into nodes>, 'data': <any extra data> } """ def __iter__( self ): # use simple graph to store nodes and links, later providing them as a dict # essentially this is a form of aggregation graph = simplegraph.SimpleGraph() parent_gen = super( XGMMLGraphDataProvider, self ).__iter__() for graph_elem in parent_gen: if 'children' not in graph_elem: continue for elem in graph_elem[ 'children' ]: # use endswith to work around Elementtree namespaces if elem[ 'tag' ].endswith( 'node' ): node_id = elem[ 'attrib' ][ 'id' ] # pass the entire, parsed xml element as the data graph.add_node( node_id, **elem ) elif elem[ 'tag' ].endswith( 'edge' ): source_id = elem[ 'attrib' ][ 'source' ] target_id = elem[ 'attrib' ][ 'target' ] graph.add_edge( source_id, target_id, **elem ) yield graph.as_dict()
[docs]class SIFGraphDataProvider( dataproviders.column.ColumnarDataProvider ): """ Provide two lists: nodes, edges:: 'nodes': contains objects of the form: { 'id' : <some string id>, 'data': <any extra data> } 'edges': contains objects of the form: { 'source' : <an index into nodes>, 'target': <an index into nodes>, 'data': <any extra data> } """ def __iter__( self ): # use simple graph to store nodes and links, later providing them as a dict # essentially this is a form of aggregation graph = simplegraph.SimpleGraph() # SIF is tabular with the source, link-type, and all targets in the columns parent_gen = super( SIFGraphDataProvider, self ).__iter__() for columns in parent_gen: if columns: source_id = columns[0] # there's no extra data for nodes (or links) in the examples I've seen graph.add_node( source_id ) # targets are the (variadic) remaining columns if len( columns ) >= 3: relation = columns[1] targets = columns[2:] for target_id in targets: graph.add_node( target_id ) graph.add_edge( source_id, target_id, type=relation ) yield graph.as_dict()