126 lines
3.7 KiB
Python
126 lines
3.7 KiB
Python
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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import logging
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import multiprocessing as mp
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import os
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import threading
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import time
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import types
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from inspect import getmembers, isfunction, signature
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import networkx as nx
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from torch_geometric.data import Data
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from torch_geometric.utils import to_networkx
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with open("mapping_nx.txt", "r") as file:
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BLACK_LIST = [line.rstrip() for line in file]
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class GraphStat(object):
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def __init__(self):
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self.maps = {
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"networkx": self.available_map_networkx(),
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"torch_geometric": self.available_map_torch_geometric(),
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}
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def available_map_networkx(self):
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functions_list = getmembers(nx.algorithms, isfunction)
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MANUALLY_ADDED = [
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"algebraic_connectivity",
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"adjacency_spectrum",
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"degree",
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"density",
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"laplacian_spectrum",
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"normalized_laplacian_spectrum",
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"number_of_selfloops",
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"number_of_edges",
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"number_of_nodes",
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]
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MANUALLY_ADDED_LIST = [
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item for item in getmembers(nx, isfunction) if item[0] in MANUALLY_ADDED
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]
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functions_list = functions_list + MANUALLY_ADDED_LIST
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maps = {}
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for func in functions_list:
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name, f = func
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if (
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name in BLACK_LIST
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or name == "recursive_simple_cycles"
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or "triad" in name
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or "weisfeiler" in name
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or "dfs" in name
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or "trophic" in name
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or "recursive" in name
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or "scipy" in name
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or "numpy" in name
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or "sigma" in name
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or "omega" in name
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or "all_" in name
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):
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continue
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else:
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maps[name] = f
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return maps
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def available_map_torch_geometric(self):
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names = [
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"num_nodes",
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"num_edges",
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"has_self_loops",
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"has_isolated_nodes",
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"num_nodes_features",
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"y",
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]
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maps = {
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name: lambda x, name=name: x.__getattr__(name) if hasattr(x, name) else None
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for name in names
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}
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return maps
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def __call__(self, data):
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data_ = data.__copy__()
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stats = {}
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for k, v in self.maps.items():
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if k == "networkx":
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_data_ = to_networkx(data)
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_data_ = _data_.to_undirected()
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elif k == "torch_geometric":
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_data_ = data.__copy__()
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for name, f in v.items():
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if f is None:
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stats[name] = None
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continue
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else:
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try:
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t0 = time.time()
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val = f(_data_)
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t1 = time.time()
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delta = t1 - t0
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except Exception as e:
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print(name, e)
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with open(f"{name}.txt", "w") as f:
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f.write(str(e))
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# print(name, round(delta, 4))
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# if callable(val) and k == "torch_geometric":
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# val = val()
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# if isinstance(val, types.GeneratorType):
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# val = list(val)
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# stats[name] = val
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return stats
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from torch_geometric.datasets import KarateClub, Planetoid
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d = Planetoid(root="/tmp/", name="Cora")
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# d = KarateClub()
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a = d[0]
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st = GraphStat()
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stat = st(a)
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for k, v in stat.items():
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print("---------")
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print("Name:", k)
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print("Type:", type(v))
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print("Val:", v)
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print("---------")
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