added heatmap

[Schefflera-Arboricola]

heatmap task

[MridulS]

Hmm, interesting. It seems like there is no speedups on your machine while running the timing task. Maybe something you can investigate? @Schefflera-Arboricola

[Schefflera-Arboricola]

@MridulS sir,

1. In the CPU core utilization window, the work was not distributed uniformly among all the 8 cores, most of the work was on one core at a time while the script was running.

2. The CPU% was around 100, and the number of threads for the process was 17(rarely become 18 or 20). It was the same when I executed currFun for the standard and the parallel graph separately.

3. I even tried it for 1000 nodes graphs but I was still getting most of the values in the heatmap around 1.

4. I recently pulled some new changes and I was getting this error:

betweenness = dict.fromkeys(G, 0.0)  # b[v]=0 for v in G
                  ^^^^^^^^^^^^^^^^^^^^^
TypeError: 'ParallelGraph' object is not iterable

So I added this code to interface.py:

class ParallelGraph:
    __networkx_plugin__ = "parallel"

    def __init__(self, graph_object):
        self.graph_object = graph_object

    def is_multigraph(self):
        return self.graph_object.is_multigraph()

    def is_directed(self):
        return self.graph_object.is_directed()
    
+    def __getitem__(self, node):
+       if node in self.graph_object:
+            return list(self.graph_object.neighbors(node))  
+        else:
+           raise KeyError(f"Node {node} not found in the graph.")

+    def __iter__(self):
+        return iter(self.graph_object.nodes())
+    
+    def __len__(self):
+        return len(self.graph_object)

but I am still getting a similar heatmap.

Running on: MacBook Air(macOS: 13.3.1(a))

Could you please help me figure out what might be the issue here, or redirect me to some resource where I could learn more about it(parallel algorithms and their benchmarking, etc.)?

Also, if a cell in the heatmap corresponds to a graph with a particular number of nodes and a particular edge probability, then why have we used 0.5 instead of p here?

Thank you very much for your patience :)

[Schefflera-Arboricola]

@MridulS sir, I think it was happening because I didn't run pip install -e ".[developer]" after setting up the environment, and I also didn't get that TypeError now. The additional code in interface.py was not required. I have updated the heat map.

But I am still doubtful about this :

Also, if a cell in the heatmap corresponds to a graph with a particular number of nodes and a particular edge probability, then why have we used 0.5 instead of p here?

I got this map for p

and this for 0.5

Thank you :)

[MridulS]

Also, if a cell in the heatmap corresponds to a graph with a particular number of nodes and a particular edge probability, then why have we used 0.5 instead of p here?

Yes that looks like a bug, it should be using p to create the random graph. Good catch!

Could you send a PR to the nx-parallel repo to fix it?

[Schefflera-Arboricola]

@MridulS done.
see here

[MridulS]

thanks!