Alle mercoledì 1 agosto 2007, Jean-Sébastien ha scritto:
http://groups.google.com/group/comp.lang.ruby/browse_thread/thread/3122212f
6db8d7f5/04a7b10da8195cec?lnk=gst&q=array++count&rnum=8#04a7b10da8195cec
If someone could help.
regards
There are two problems in your code:
1- in the inject block, you return elt, which is (or should be, if the
code
worked) the hash containing the id which is being processed. You should
return a, that is the array which contains the hashes. Correcting this
should
give a piece of code which executes without errors, but which returns an
empty array
2- you never insert the hashes you create inside the inject block into
the
array a: you only store them in the local variable elt, which gets
destroyed
after each iteration. The inject block should be:
result = array_of_ids.inject(Array.new){ |a,x|
elt = ( a.find{|h| h[:id] == x} || a[a.size] = {:id => x, :count =>
0} )
elt[:count] += 1
a
}
As you can see, after the || operator a new hash is created and inserted
at
the end of a (corresponding to the index a.size). Since an assignment
always
return the value being assigned (this is why I didn’t use <<, it returns
the
array, not the inserted element), elt is then set to the new hash. Of
course,
all this happens only if find returns nil.
If you can rely in the id to be positive integers, and don’t care if the
resulting array contains the hashes in the same order as the id are
stored in
the array, here’s another approach you can consider:
result = array_of_ids.inject([]) do |res, i|
res[i-1] ||= {:id => i, :count => 0}
res[i-1][:count] += 1
res
end
This code stores the data relative to the id i in the i-1 position in
the
array (the -1 is there to avoid a nil element at the beginning). This
should
make it faster, since you don’t need to iterate all the array to check
whether the data corresponding to an id is already there or not: either
is in
the position id - 1 or it itsn’t there. A quick benchmark, done by
creating
an array of ids of 100_000 elements, with values randomly chosen between
1
and 11 gives:
user system total real
original approach 5.730000 1.490000 7.220000 ( 7.310224)
user system total real
alternative approach 1.250000 0.150000 1.400000 ( 1.416871)
Changing the range of the ids from 11 to 101 gives:
user system total real
alternative approach 1.270000 0.190000 1.460000 ( 1.472353)
user system total real
original approach 37.730000 11.360000 49.090000 ( 51.056527)
Increasing it to 1001 gives
user system total real
alternative approach 1.500000 0.220000 1.720000 ( 1.733568)
The original approach takes much more time (I didn’t have the patience
to wait
for it to complete).
I hope this helps
Stefano