En Fri, 10 Jun 2011 07:30:28 -0300, Francesc Segura <[email protected]>
escribió:
Hello all, I'm new to this and I'm having problems on summing two
values at python.
I get the following error:
Traceback (most recent call last):
File "C:\edge-bc (2).py", line 168, in <module>
if (costGG <= cost + T0):
TypeError: unsupported operand type(s) for +: 'float' and 'tuple'
I see Tim Chase already told you about this error. Let me make a few
comments about the rest.
try:
import matplotlib.pyplot as plt
except:
raise
I guess the above try/except was left from some earlier debugging attempt
- such an except clause is useless, just omit it.
T0 = 0.5
RO = 0.99
Perhaps those names make sense in your problem at hand, but usually I try
to use more meaningful ones. 0 and O look very similar in some fonts.
for i in range(len(edges)):
total = 0
cost = 0
factor = 1
liedges = list(edges[i])
linode1 = list(liedges[0])
linode2 = list(liedges[1])
list(something) creates a new list out of the elements from `something`.
You're just iterating here, so there is no need to duplicate those lists.
In addition, Python is not C: the `for` statement iterates over a
collection, you don't have to iterate over the indices and dereference
each item:
for liedges in edges:
linode1 = liedges[0]
linode2 = liedges[1]
distance = (((linode2[0]-linode1[0])%N)^2)+(((linode2[1]-
linode1[1])%N)^2)
That doesn't evaluate what you think it does. ^ is the "bitwise xor"
operator, and I bet you want **, the "power" operator.
total = total + cost
return(total)
return is not a function but a statement; those () are unnecesary and
confusing.
And I think you want to initialize total=0 *before* entering the loop;
also, initializing cost and factor is unnecesary.
def costGeasy(G):
bc = NX.edge_betweenness_centrality(G,normalized=True)
total = 0
for i in range(len(bc)):
total=total+bc.values()[i]
return (total)
bc = NX.edge_betweenness_centrality(G,normalized=True)
values = bc.values()
total = sum(values)
return total
==>
return sum(bc.values())
pos={}
for i in range(NODES):
pos[nod[i]]=(nod[i][0]/(N*1.0),nod[i][1]/(N*1.0))
In Python version 2.x, 1/3 evals to 0, but that's a mistake; it is fixed
in the 3.x version. If you put this line at the top of your script:
from __future__ import division
then 1/3 returns 0.3333...
When you actually want integer division, use //, like 1//3
So we can rewrite the above as:
from __future__ import division
...
for node in nod:
pos[node] = (node[0] / N, node[1] / N)
Another way, not relying on true division:
divisor = float(N)
for node in nod:
pos[node] = (node[0] / divisor, node[1] / divisor)
or even:
pos = dict((node, (node[0] / divisor, node[1] / divisor)) for node in nod)
for y in range(NK):
for x in range(ITERATIONS):
cost = costG(G)
if (cost < (best_cost)):
best_graph = G
best_cost = cost
GG = G
Again, I think this doesn't do what you think it does. GG = G means "let's
use the name GG for the object currently known as G". GG is not a "copy"
of G, just a different name for the very same object. Later operations
like GG.remove_edge(...) modify the object - and you'll see the changes in
G, and in best_graph, because those names all refer to the same object.
I think you'll benefit from reading this:
http://effbot.org/zone/python-objects.htm
a = random.randint(0,NODES-1)
b = random.randint(0,NODES-1)
adj=G.adjacency_list()
while ((nod[b] in adj[a]) or (b == a)):
a = random.randint(0,NODES-1)
b = random.randint(0,NODES-1)
GG.add_edge(nod[a],nod[b])
As above, I'd avoid using indexes, take two random nodes using
random.sample instead, and avoid adjacency_list():
while True:
a, b = random.sample(nod, 2)
if b not in G[a]:
break
GG.add_edge(a, b)
(mmm, I'm unsure of the adjacency test, I've used networkx some time ago
but I don't have it available right now)
--
Gabriel Genellina
--
http://mail.python.org/mailman/listinfo/python-list
