At 10:09 2014-06-13, Malcolm Greene wrote:
Looking for an algorthim for the following use case (highly
simplified):
1. I have buckets (probably 3-5)
2. I have 1 million records with a quantity field containing values in
the range 1 to 1000
I would like to optimally shuffle my 1 million recor
[mailto:profox-boun...@leafe.com] On Behalf Of Jerry Wolper
Sent: 19 June 2014 00:06
To: ProFox Email List
Subject: RE: [NF] Looking for name of algorithm
> Malcolm,
> It is very closely linked with something called the "Monte Carlo
> Method" of sampling (even though you are distributi
uns will be alike.
Dan
> From: jwol...@swanzoco.com
> To: profoxt...@leafe.com
> Date: Wed, 18 Jun 2014 19:06:15 -0400
> Subject: RE: [NF] Looking for name of algorithm
>
> > Malcolm,
> > It is very closely linked with something called the "Monte Carlo
> &g
> Malcolm,
> It is very closely linked with something called the "Monte Carlo
> Method" of sampling (even though you are distributing no sampling)
> but the concepts are the same.
Now I'm confused. I thought Monte Carlo was estimating a distribution
by running (or simulating) the function many ti
Thank you all for you ideas, Paul for the executable pseudo code, and
Dave for the algorithm name which is exactly what I was looking for.
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OT-
it is a distant memory but it will hopefully
point you in the right direction.
Dave
-Original Message-
From: ProFox [mailto:profox-boun...@leafe.com] On Behalf Of Malcolm Greene
Sent: 13 June 2014 18:10
To: profox@leafe.com
Subject: [NF] Looking for name of algorithm
Looking for an al
Did this years ago (1998?) and called it an "Nth" program. Wrote this
in ASSEMBLER!!! Basically, you take your total count, divide by the
number of buckets, and of that answer, the whole part we'll call Nth and
the remainder we'll call LeftoverFraction. As I start to cycle through
the data,
Hi Malcolm,
I would consider something like the following (pseudocode):
from random import shuffle
buckets = []
bucket_count = 3
class Bucket:
tot_qty = 0
items = []
for i in range(bucket_count):
buckets.append(Bucket())
# Sort the input_table by qty
On Fri, Jun 13, 2014 at 12:09 PM, Malcolm Greene wrote:
> Looking for an algorthim for the following use case (highly
> simplified):
>
>
>
> 1. I have buckets (probably 3-5)
>
> -
Round Robin Distribution is the term you are looking for I believe.
You sort the value column
On Fri, Jun 13, 2014 at 10:45 AM, Malcolm Greene wrote:
> Matt,
>
> Good questions. I don't care how many records are in each bucket as long
> as the sum total of all quantity fields in each bucket are balanced as
> much as possible.
>
On the phone so not giving this full CPU power so bear with m
Matt,
Good questions. I don't care how many records are in each bucket as long
as the sum total of all quantity fields in each bucket are balanced as
much as possible.
Taking the extreme case, if I had 999,999 records with a quantity value
of 1, one record with a quantity value of 1,000,000 and t
>
> I would like to optimally shuffle my 1 million records across my
> buckets so that the total quantity (based on the sum of each record's
> quantity field) in each bucket is balanced (as much as possible) across
> buckets.
>
>
>
> This sounds like the type of problem that has been solved before
Looking for an algorthim for the following use case (highly
simplified):
1. I have buckets (probably 3-5)
2. I have 1 million records with a quantity field containing values in
the range 1 to 1000
I would like to optimally shuffle my 1 million records across my
buckets so that the total
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