I've been using networkx to simply create a graph and check the connected components. The bottleneck of the operation is the creation of the edges. I've heard that graph-tool is very efficient so I've replaces the code with a graph-tool graph. To my surprise, the creation of a graph-tool graph is MUCH slower than that of a networkx graph. Am I doing something wrong? I've created a small sample program (at the bottom of this message) to test this speed... it creates a graph in a very natural way: pairs of objects that should be connected by an edge are iterated through. We happen to give every possible pair of objects in this example so the complete graph is created. Here is runsnake image of where the running-time is going: <http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/file/n4026108/runsnake_compare.png> The Code: #!/usr/bin/python """ Create graphs in networkx and graph-tool. """ import networkx as nx from graph_tool.all import * from itertools import combinations def graph_tool_create(): """ Create a graph_tool graph given a list of pairs. """ G = Graph(directed=False) objectset = set() for o1,o2 in get_pairs_of_objects(): if(o1 not in objectset): u = G.add_vertex() objectset.add(o1) if(o2 not in objectset): v = G.add_vertex() objectset.add(o2) G.add_edge(u,v) def nx_create(): """ Create a graph_tool graph given a list of pairs. """ G = nx.Graph() for o1,o2 in get_pairs_of_objects(): G.add_edge(o1,o2) def get_pairs_of_objects(): """ Generate pairs of objects. """ n = 5000 for a,b in combinations(range(n),2): yield a,b graph_tool_create() nx_create() -- View this message in context: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/... Sent from the Main discussion list for the graph-tool project mailing list archive at Nabble.com.
I posted code with missing lines... here is the good code: #!/usr/bin/python """ Create graphs in networkx and graph-tool. """ import networkx as nx from graph_tool.all import * import igraph from itertools import combinations def graph_tool_create(): """ Create a graph_tool graph given a list of pairs. """ G = Graph(directed=False) objectTOv = {} for o1,o2 in get_pairs_of_objects(): if(o1 in objectTOv): u = objectTOv[o1] else: u = G.add_vertex() objectTOv[o1] = u if(o2 in objectTOv): v = objectTOv[o2] else: v = G.add_vertex() objectTOv[o2] G.add_edge(u,v) def nx_create(): """ Create a graph_tool graph given a list of pairs. """ G = nx.Graph() for o1,o2 in get_pairs_of_objects(): G.add_edge(o1,o2) def get_pairs_of_objects(): """ Generate pairs of objects. """ n = 3000 for a,b in combinations(range(n),2): yield a,b graph_tool_create() nx_create() -- View this message in context: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/... Sent from the Main discussion list for the graph-tool project mailing list archive at Nabble.com.
On 27.04.2015 14:29, thekswenson wrote:
I've been using networkx to simply create a graph and check the connected components. The bottleneck of the operation is the creation of the edges.
I've heard that graph-tool is very efficient so I've replaces the code with a graph-tool graph. To my surprise, the creation of a graph-tool graph is MUCH slower than that of a networkx graph.
Am I doing something wrong?
How does the performance change if you create the necessary edges beforehand? In graph-tool things are faster than in networkx when they are delegated to C++, otherwise this should be comparable in speed. In the case of adding many edges, this is done by using the Graph.add_edge_list() function, which runs in C++ internally. In your example, this should provide a massive speed-up. Best, Tiago -- Tiago de Paula Peixoto <tiago@skewed.de>
Thanks for the quick response Thiago! In this code all the edges and vertices are created by graph-tool and the result is something much faster... is this the best I can do? It's somewhat annoying to have to keep track of the vertices that will be created like this: def graph_tool_create_all_at_once(): """ Create a graph_tool graph given a list of pairs. """ G = Graph(directed=False) objectTOi = {} vertexpairs = [] counter = 0 for o1,o2 in get_pairs_of_ints(): if(o1 in objectTOi): u = objectTOi[o1] else: u = counter counter += 1 objectTOi[o1] = u if(o2 in objectTOi): v = objectTOi[o2] else: v = counter counter += 1 objectTOi[o2] = v vertexpairs.append((u,v)) G.add_edge_list(vertexpairs) On 27 April 2015 at 16:39, Tiago de Paula Peixoto <tiago@skewed.de> wrote:
On 27.04.2015 14:29, thekswenson wrote:
I've been using networkx to simply create a graph and check the connected components. The bottleneck of the operation is the creation of the edges.
I've heard that graph-tool is very efficient so I've replaces the code with a graph-tool graph. To my surprise, the creation of a graph-tool graph is MUCH slower than that of a networkx graph.
Am I doing something wrong?
How does the performance change if you create the necessary edges beforehand?
In graph-tool things are faster than in networkx when they are delegated to C++, otherwise this should be comparable in speed. In the case of adding many edges, this is done by using the Graph.add_edge_list() function, which runs in C++ internally. In your example, this should provide a massive speed-up.
Best, Tiago
-- Tiago de Paula Peixoto <tiago@skewed.de>
_______________________________________________ graph-tool mailing list graph-tool@skewed.de http://lists.skewed.de/mailman/listinfo/graph-tool
I solved this once by making a NoDupesGraph where you could add edges with just the names of vertices . class NoDupesGraph(Graph): '''Add nodes without worrying if it is a duplicate. Add edges without worrying if nodes exist ''' def __init__(self,*args,**kwargs): Graph.__init__(self,*args,**kwargs) self._nodes = {} def add_nodupe_vertex(self,label,*args,**kwargs): '''Return a node with label. Create node if label is new''' try: n = self._nodes[label] except KeyError: n = self.add_vertex() self._nodes[label]=n return n def add_nodupe_edge(self, n1_label, n2_label,directed=False): """ Get or create edges using get_or_create_node """ #there may be two if graph is directed but edge isn't edges = [] n1 = self.add_nodupe_vertex(n1_label) n2 = self.add_nodupe_vertex(n2_label) edges.append(self.add_edge(n1,n2)) if self.is_directed() and not directed: edges.append(self.add_edge(n2,n1)) return edges def flush_empty_nodes(self): '''not implemented''' pass def condense_edges(self): '''if a node connects to only two edges, combine those edges and delete the node. not implemented ''' pass This could be easily modified to suit your need. On Mon, Apr 27, 2015 at 3:23 PM, Krister <thekswenson@gmail.com> wrote:
Thanks for the quick response Thiago!
In this code all the edges and vertices are created by graph-tool and the result is something much faster... is this the best I can do?
It's somewhat annoying to have to keep track of the vertices that will be created like this:
def graph_tool_create_all_at_once(): """ Create a graph_tool graph given a list of pairs. """ G = Graph(directed=False) objectTOi = {} vertexpairs = [] counter = 0 for o1,o2 in get_pairs_of_ints(): if(o1 in objectTOi): u = objectTOi[o1] else: u = counter counter += 1 objectTOi[o1] = u if(o2 in objectTOi): v = objectTOi[o2] else: v = counter counter += 1 objectTOi[o2] = v
vertexpairs.append((u,v))
G.add_edge_list(vertexpairs)
On 27 April 2015 at 16:39, Tiago de Paula Peixoto <tiago@skewed.de> wrote:
On 27.04.2015 14:29, thekswenson wrote:
I've been using networkx to simply create a graph and check the connected components. The bottleneck of the operation is the creation of the edges.
I've heard that graph-tool is very efficient so I've replaces the code with a graph-tool graph. To my surprise, the creation of a graph-tool graph is MUCH slower than that of a networkx graph.
Am I doing something wrong?
How does the performance change if you create the necessary edges beforehand?
In graph-tool things are faster than in networkx when they are delegated to C++, otherwise this should be comparable in speed. In the case of adding many edges, this is done by using the Graph.add_edge_list() function, which runs in C++ internally. In your example, this should provide a massive speed-up.
Best, Tiago
-- Tiago de Paula Peixoto <tiago@skewed.de>
_______________________________________________ graph-tool mailing list graph-tool@skewed.de http://lists.skewed.de/mailman/listinfo/graph-tool
_______________________________________________ graph-tool mailing list graph-tool@skewed.de http://lists.skewed.de/mailman/listinfo/graph-tool
Hi offonoffon... won't the creation of the vertices and edges one at a time end up dramatically affecting the performance of graph creation (see my original question at the top of the thread)? I've found that creating the edges one at a time is MUCH slower than creating them all at once and that creating the vertices one at a time is a little slower. What I have is not pretty though. On 28 April 2015 at 01:11, ... <offonoffoffonoff@gmail.com> wrote:
I solved this once by making a NoDupesGraph where you could add edges with just the names of vertices .
class NoDupesGraph(Graph): '''Add nodes without worrying if it is a duplicate. Add edges without worrying if nodes exist '''
def __init__(self,*args,**kwargs): Graph.__init__(self,*args,**kwargs) self._nodes = {}
def add_nodupe_vertex(self,label,*args,**kwargs): '''Return a node with label. Create node if label is new''' try: n = self._nodes[label] except KeyError: n = self.add_vertex() self._nodes[label]=n return n
def add_nodupe_edge(self, n1_label, n2_label,directed=False): """ Get or create edges using get_or_create_node """ #there may be two if graph is directed but edge isn't edges = []
n1 = self.add_nodupe_vertex(n1_label) n2 = self.add_nodupe_vertex(n2_label) edges.append(self.add_edge(n1,n2)) if self.is_directed() and not directed: edges.append(self.add_edge(n2,n1)) return edges
def flush_empty_nodes(self): '''not implemented''' pass
def condense_edges(self): '''if a node connects to only two edges, combine those edges and delete the node.
not implemented ''' pass
This could be easily modified to suit your need.
On Mon, Apr 27, 2015 at 3:23 PM, Krister <thekswenson@gmail.com> wrote:
Thanks for the quick response Thiago!
In this code all the edges and vertices are created by graph-tool and the result is something much faster... is this the best I can do?
It's somewhat annoying to have to keep track of the vertices that will be created like this:
def graph_tool_create_all_at_once(): """ Create a graph_tool graph given a list of pairs. """ G = Graph(directed=False) objectTOi = {} vertexpairs = [] counter = 0 for o1,o2 in get_pairs_of_ints(): if(o1 in objectTOi): u = objectTOi[o1] else: u = counter counter += 1 objectTOi[o1] = u if(o2 in objectTOi): v = objectTOi[o2] else: v = counter counter += 1 objectTOi[o2] = v
vertexpairs.append((u,v))
G.add_edge_list(vertexpairs)
On 27 April 2015 at 16:39, Tiago de Paula Peixoto <tiago@skewed.de> wrote:
On 27.04.2015 14:29, thekswenson wrote:
I've been using networkx to simply create a graph and check the connected components. The bottleneck of the operation is the creation of the edges.
I've heard that graph-tool is very efficient so I've replaces the code with a graph-tool graph. To my surprise, the creation of a graph-tool graph is MUCH slower than that of a networkx graph.
Am I doing something wrong?
How does the performance change if you create the necessary edges beforehand?
In graph-tool things are faster than in networkx when they are delegated to C++, otherwise this should be comparable in speed. In the case of adding many edges, this is done by using the Graph.add_edge_list() function, which runs in C++ internally. In your example, this should provide a massive speed-up.
Best, Tiago
-- Tiago de Paula Peixoto <tiago@skewed.de>
_______________________________________________ graph-tool mailing list graph-tool@skewed.de http://lists.skewed.de/mailman/listinfo/graph-tool
_______________________________________________ graph-tool mailing list graph-tool@skewed.de http://lists.skewed.de/mailman/listinfo/graph-tool
_______________________________________________ graph-tool mailing list graph-tool@skewed.de http://lists.skewed.de/mailman/listinfo/graph-tool
Hi offonoffon... won't the creation of the vertices and edges one at a time end up dramatically affecting the performance of graph creation (see my original question at the top of the thread)?
Yes, and that has been solved already. I was responding to "It's somewhat annoying to have to keep track of the vertices that will be created like this", and to the observation that your code is maybe not as flexible/reuseable as it could be. And as I said, my code could be easily modified to add the edges as a batch instead of one at a time. -Elliot
I agree that hiding the mess inside a class could make the view from outside much nicer. On 28 April 2015 at 17:45, ... <offonoffoffonoff@gmail.com> wrote:
Hi offonoffon...
won't the creation of the vertices and edges one at a time end up dramatically affecting the performance of graph creation (see my original question at the top of the thread)?
Yes, and that has been solved already. I was responding to "It's somewhat annoying to have to keep track of the vertices that will be created like this", and to the observation that your code is maybe not as flexible/reuseable as it could be. And as I said, my code could be easily modified to add the edges as a batch instead of one at a time.
-Elliot
_______________________________________________ graph-tool mailing list graph-tool@skewed.de http://lists.skewed.de/mailman/listinfo/graph-tool
On 27.04.2015 22:23, Krister wrote:
Thanks for the quick response Thiago!
In this code all the edges and vertices are created by graph-tool and the result is something much faster... is this the best I can do?
It's somewhat annoying to have to keep track of the vertices that will be created like this:
def graph_tool_create_all_at_once(): """ Create a graph_tool graph given a list of pairs. """ G = Graph(directed=False) objectTOi = {} vertexpairs = [] counter = 0 for o1,o2 in get_pairs_of_ints(): if(o1 in objectTOi): u = objectTOi[o1] else: u = counter counter += 1 objectTOi[o1] = u if(o2 in objectTOi): v = objectTOi[o2] else: v = counter counter += 1 objectTOi[o2] = v
vertexpairs.append((u,v))
G.add_edge_list(vertexpairs)
Yes, it is possible to improve this. If your o1 and o2 objects are always ints (as I gather from get_pairs_of_ints()), then you don't need these dictionaries at all. The G.add_edge_list() will create missing nodes as necessary. So you only need to do: G.add_edge_list(list(get_pairs_of_ints())) This will be much faster. However it requires your ints to be within some reasonable range, since missing ints without edges will also be created. But you are better off guaranteeing this is the case when you generate the ints in the first place. Best, Tiago -- Tiago de Paula Peixoto <tiago@skewed.de>
Sorry Thiago... I accidentally left the get_pairs_of_ints where get_pairs_of_objects should be. The code that creates all edges using integer indices is indeed very fast. On 29 April 2015 at 12:16, Tiago de Paula Peixoto <tiago@skewed.de> wrote:
On 27.04.2015 22:23, Krister wrote:
Thanks for the quick response Thiago!
In this code all the edges and vertices are created by graph-tool and the result is something much faster... is this the best I can do?
It's somewhat annoying to have to keep track of the vertices that will be created like this:
def graph_tool_create_all_at_once(): """ Create a graph_tool graph given a list of pairs. """ G = Graph(directed=False) objectTOi = {} vertexpairs = [] counter = 0 for o1,o2 in get_pairs_of_ints(): if(o1 in objectTOi): u = objectTOi[o1] else: u = counter counter += 1 objectTOi[o1] = u if(o2 in objectTOi): v = objectTOi[o2] else: v = counter counter += 1 objectTOi[o2] = v
vertexpairs.append((u,v))
G.add_edge_list(vertexpairs)
Yes, it is possible to improve this. If your o1 and o2 objects are always ints (as I gather from get_pairs_of_ints()), then you don't need these dictionaries at all. The G.add_edge_list() will create missing nodes as necessary. So you only need to do:
G.add_edge_list(list(get_pairs_of_ints()))
This will be much faster. However it requires your ints to be within some reasonable range, since missing ints without edges will also be created. But you are better off guaranteeing this is the case when you generate the ints in the first place.
Best, Tiago
-- Tiago de Paula Peixoto <tiago@skewed.de>
_______________________________________________ graph-tool mailing list graph-tool@skewed.de http://lists.skewed.de/mailman/listinfo/graph-tool
On 29.04.2015 18:12, Krister wrote:
Sorry Thiago... I accidentally left the get_pairs_of_ints where get_pairs_of_objects should be.
The code that creates all edges using integer indices is indeed very fast.
Ok. Still, the best option would be not to iterate over all pairs to construct the mapping to ints, but to iterate only through the individual objects. Best, Tiago -- Tiago de Paula Peixoto <tiago@skewed.de>
participants (4)
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