On Mon, 28 Jul 2008 16:48:28 +0200, Suresh Pillai wrote:
Okay, please consider this my one absolutely stupid post for the year.
I'd like to pretend it never happened but unfortunately the web doesn't
allow that. Having never used sets, I unfort read something that lead
to it, but ...
Okay,
Suresh Pillai wrote:
On Mon, 28 Jul 2008 16:48:28 +0200, Suresh Pillai wrote:
Okay, please consider this my one absolutely stupid post for the year.
I'd like to pretend it never happened but unfortunately the web doesn't
allow that. Having never used sets, I unfort read something that lead
Diez B. Roggisch wrote:
For sets, I presume they are built on top of or like dicts, and
there is nothing crazy in the low level implementation so that I can
be guaranteed that if I don't alter the set, then the order,
although arbitrary, will be maintained in successive iterations over
the
On Fri, 25 Jul 2008 08:08:57 -0700, Iain King wrote:
On Jul 25, 3:39 pm, Suresh Pillai [EMAIL PROTECTED] wrote:
That's a good comparison for the general question I posed. Thanks.
Although I do believe lists are less than ideal here and a different
data structure should be used.
To be more
On Fri, 25 Jul 2008 05:46:56 -0700, Iain King wrote:
or 3. build a new list every iteration intead of deleting from the old
one:
while processing:
new_off_list = []
for x in off_list:
if goes_on(x):
on_list.append(x)
else:
Suresh Pillai:
Or 4, since the order of my nodes doesn't matter: swap the node to be
deleted with the last node in the list and then remove the last node of
the list. This is the fastest to date, if using native structures, for
low number nodes being deleted per cycle (def if only deleting
On Mon, 28 Jul 2008 10:44:18 +0200, Suresh Pillai wrote:
Since I am doing A LOT of loops over the nodes and the number of nodes
is also huge, my concern using sets is that in order to iterate over the
set in each step of my simulation, the set items need to be converted to
a list every time.
Suresh Pillai [EMAIL PROTECTED] wrote:
[ ... ] is
there any way to iterate over the items in a set other than converting to
a list or using the pop() method.
Er, how about directly iterating over the set?
--
\S -- [EMAIL PROTECTED] -- http://www.chaos.org.uk/~sion/
Frankly I have no
On Mon, 28 Jul 2008 15:04:43 +0200, Suresh Pillai wrote:
I could of course use the old trick of using a dictionary with 'None'
values and then using iterkeys(). But I thought sets were supposed to
replace this. So maybe I should be asking a more basic question: is
there any way to iterate
On Mon, 28 Jul 2008 15:04:43 +0200, Suresh Pillai wrote:
On Mon, 28 Jul 2008 10:44:18 +0200, Suresh Pillai wrote:
Since I am doing A LOT of loops over the nodes and the number of nodes
is also huge, my concern using sets is that in order to iterate over
the set in each step of my
The number of nodes is very large: millions for sure, maybe tens
of millions. If considering (2), take note of my BOLD text above, which
means I can't remove nodes as I iterate through them in the main loop.
Since your use of 'node' is pretty vague and I don't have a good sense
of what tests
I am performing simulations on networks (graphs). I have a question on
speed of execution (assuming very ample memory for now). I simplify the
details of my simulation below, as the question I ask applies more
generally than my specific case. I would greatly appreciate general
feedback in
On Jul 25, 7:57 pm, Suresh Pillai [EMAIL PROTECTED] wrote:
The nodes in my network may be ON or OFF. The network starts off with
all nodes in the OFF state. I loop through the nodes. For each node
that is OFF, I consider some probability of it turning ON based on the
states of its
I'd recommend using 'filter' and list comprehensions.
Look at using reduce(). You can collect information about all of the
nodes without necessarily building a large, intermediate list in the
process.
You might get some ideas from here [http://en.wikipedia.org/wiki/
Antiobjects].
--
On Jul 25, 10:57 am, Suresh Pillai [EMAIL PROTECTED] wrote:
I am performing simulations on networks (graphs). I have a question on
speed of execution (assuming very ample memory for now). I simplify the
details of my simulation below, as the question I ask applies more
generally than my
On Jul 25, 1:46 pm, Iain King [EMAIL PROTECTED] wrote:
On Jul 25, 10:57 am, Suresh Pillai [EMAIL PROTECTED] wrote:
I am performing simulations on networks (graphs). I have a question on
speed of execution (assuming very ample memory for now). I simplify the
details of my simulation
On Jul 25, 9:54 pm, Jeff [EMAIL PROTECTED] wrote:
Look at using reduce(). You can collect information about all of the
nodes without necessarily building a large, intermediate list in the
process.
From the OP's description, I assumed there'd be a list of all nodes,
from which he wishes to
That's a good comparison for the general question I posed. Thanks.
Although I do believe lists are less than ideal here and a different data
structure should be used.
To be more specific to my case:
As mentioned in my original post, I also have the specific condition that
one does not know
Iain King wrote:
I think (2)'s poor performance is being amplified by how python
handles lists and list deletions; the effect may be stymied in other
languages
Delete is O(n) (or O(n/2) on average, if you prefer), while append is
amortized O(1).
Unless I'm missing something, your example
On Fri, 25 Jul 2008 16:51:42 +0200, Fredrik Lundh wrote:
Unless I'm missing something, your example keeps going until it's
flagged *all* nodes as on, which, obviously, kills performance for the
first version as the probability goes down. The OP's question was about
a single pass (but he did
On Jul 25, 3:39 pm, Suresh Pillai [EMAIL PROTECTED] wrote:
That's a good comparison for the general question I posed. Thanks.
Although I do believe lists are less than ideal here and a different data
structure should be used.
To be more specific to my case:
As mentioned in my original post,
Suresh Pillai wrote:
That's a good comparison for the general question I posed. Thanks.
Although I do believe lists are less than ideal here and a different data
structure should be used.
To be more specific to my case:
As mentioned in my original post, I also have the specific condition
On Jul 25, 4:22 pm, Matthew Fitzgibbons [EMAIL PROTECTED] wrote:
It seems like the probability calculation applies to all three equally,
and can therefore be ignored for the simulations.
The probability affects (1) more. My reasoning for this being: as
probability gets lower the number of
2008/7/25 Suresh Pillai [EMAIL PROTECTED]:
...
I naturally started coding with (2), but couldn't decide on the best data
structure for python. A set seemed ideal for speedy removal, but then I
can't iterate through them with out popping. An ordered list? Some
creative solution with
Iain King wrote:
On Jul 25, 4:22 pm, Matthew Fitzgibbons [EMAIL PROTECTED] wrote:
It seems like the probability calculation applies to all three equally,
and can therefore be ignored for the simulations.
The probability affects (1) more. My reasoning for this being: as
probability gets
Suresh Pillai wrote:
I am performing simulations on networks (graphs). I have a question on
speed of execution (assuming very ample memory for now). I simplify the
details of my simulation below, as the question I ask applies more
generally than my specific case. I would greatly
26 matches
Mail list logo
