I'm doing coursework which involves graphs. I have edge lists E=[('a','b'),('a','c'),('a','d'), ('b','c') etc. ] and I want to a function to convert them into adjacency matrices in the form of dictionaries {'a':['b','c','d'], 'b':['a', etc. } so that I can use a function that only inputs these dictionaries.
My main issue is I can't figure out how to use a loop to add key:values without just overwriting the lists. A previous version of my function would output [] as all values because 'f' has no connections.
I've tried this:
V = ['a','b','c','d','e','f']
E=[('a', 'b'), ('a', 'c'), ('a', 'd'), ('b', 'c'), ('b', 'd'), ('c', 'd')]
def EdgeListtoAdjMat(V,E):
GA={}
conneclist=[]
for v in V:
for i in range(len(V)):
conneclist.append([])
if (v,V[i]) in E:
conneclist[i].append(V[i])
for i in range(len(V)):
GA[V[i]]=conneclist[i]
return(GA)
EdgeListtoAdjMat(V,E) outputs:
{'a': [], 'b': ['b'], 'c': ['c', 'c'], 'd': ['d', 'd', 'd'], 'e': [], 'f': []}
whereas it should output:
{'a':['b','c','d'],
'b':['a','c','d'],
'c':['a','b','d'],
'd':['a','b','c'],
'e':[],
'f':[]
}
The logic of what you're trying to achieve is actually quite simple:
V = ['a','b','c','d','e','f']
E=[('a', 'b'), ('a', 'c'), ('a', 'd'), ('b', 'c'), ('b', 'd'), ('c', 'd')]
result = {}
for elem in V:
tempList = []
for item in E:
if elem in item:
if elem == item[0]:
tempList.append(item[1])
else:
tempList.append(item[0])
result[elem] = tempList
tempList = []
print(result)
Result:
{'a': ['b', 'c', 'd'], 'b': ['a', 'c', 'd'], 'c': ['a', 'b', 'd'], 'd': ['a', 'b', 'c'], 'e': [], 'f': []}
For every element in V
, perform a check to see whether that element exists in any tuple in E
. If it exists, then take the element that together form a pair on that tuple and append to a temporary list. After checking every element in E
, update the result
dictionary and move to the next element of V
until you're done.
To get back to your code, you need to modify it as following:
def EdgeListtoAdjMat(V,E):
GA={}
conneclist=[]
for i in range(len(V)):
for j in range(len(V)):
# Checking if a pair of two different elements exists in either format inside E.
if not i==j and ((V[i],V[j]) in E or (V[j],V[i]) in E):
conneclist.append(V[j])
GA[V[i]]=conneclist
conneclist = []
return(GA)
A more efficient approach is to iterate through the edges and append to the output dict of lists the vertices in both directions. Use dict.setdefault
to initialize each new key with a list. And when the iterations over the edges finish, iterate over the rest of the vertices that are not yet in the output dict to assign to them empty lists:
def EdgeListtoAdjMat(V,E):
GA = {}
for a, b in E:
GA.setdefault(a, []).append(b)
GA.setdefault(b, []).append(a)
for v in V:
if v not in GA:
GA[v] = []
return GA
so that given:
V = ['a', 'b', 'c', 'd', 'e', 'f']
E = [('a', 'b'), ('a', 'c'), ('a', 'd'), ('b', 'c'), ('b', 'd'), ('c', 'd')]
EdgeListtoAdjMat(V, E))
would return:
{'a': ['b', 'c', 'd'], 'b': ['a', 'c', 'd'], 'c': ['a', 'b', 'd'], 'd': ['a', 'b', 'c'], 'e': [], 'f': []}
Since you already have your list of vertices in V, it is easy to prepare a dictionary with an empty list of connections. Then, simply go through the edge list and add to the array on each side:
V = ['a','b','c','d','e','f']
E = [('a', 'b'), ('a', 'c'), ('a', 'd'), ('b', 'c'), ('b', 'd'), ('c', 'd')]
GA = {v:[] for v in V}
for v1,v2 in E:
GA[v1].append(v2)
GA[v2].append(v1)
I think your code is not very pythonic, you could write a more readable code that is simpler to debug and also faster since you are using python's built-in libraries and numpy's indexing.
def EdgeListToAdjMat(V, E):
AdjMat = np.zeros((len(V), len(V))) # the shape of Adjancy Matrix
connectlist = {
# Mapping each character to its index
x: idx for idx, x in enumerate(V)
}
for e in E:
v1, v2 = e
idx_1, idx_2 = connectlist[v1], connectlist[v2]
AdjMat[idx_1, idx_2] = 1
AdjMat[idx_2, idx_1] = 1
return AdjMat
If you'd consider using a library, networkx
is designed for these type of network problems:
import networkx as nx
V = ['a','b','c','d','e','f']
E = [('a', 'b'), ('a', 'c'), ('a', 'd'), ('b', 'c'), ('b', 'd'), ('c', 'd')]
G=nx.Graph(E)
G.add_nodes_from(V)
GA = nx.to_dict_of_lists(G)
print(GA)
# {'a': ['c', 'b', 'd'], 'c': ['a', 'b', 'd'], 'b': ['a', 'c', 'd'], 'e': [], 'd': ['a', 'c', 'b'], 'f': []}
You can convert the edge list to the map using itertools.groupby
from itertools import groupby
from operator import itemgetter
V = ['a','b','c','d','e','f']
E = [('a', 'b'), ('a', 'c'), ('a', 'd'), ('b', 'c'), ('b', 'd'), ('c', 'd')]
# add edge in the other direction. E.g., for a -> b, add b -> a
nondirected_edges = E + [tuple(reversed(pair)) for pair in E]
# extract start and end vertices from an edge
v_start = itemgetter(0)
v_end = itemgetter(1)
# group edges by their starting vertex
groups = groupby(sorted(nondirected_edges), key=v_start)
# make a map from each vertex -> adjacent vertices
mapping = {vertex: list(map(v_end, edges)) for vertex, edges in groups}
# if you don't need all the vertices to be present
# and just want to be able to lookup the connected
# list of vertices to a given vertex at some point
# you can use a defaultdict:
from collections import defaultdict
adj_matrix = defaultdict(list, mapping)
# if you need all vertices present immediately:
adj_matrix = dict(mapping)
adj_matrix.update({vertex: [] for vertex in V if vertex not in mapping})
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