I have been trying to update a spreadsheet we currently using to show the most efficient way of ordering items. Items can be ordered in packs of 1, 5, 10 or 20. Can if statements be used to produce a table to show the best way of ordering these?
E.G: 18 - made of 1 x pack of 10; 1 x pack of 5; 3 x pack of 1
Been trying to use IF statements, but as the numbers get larger: more errors seems to creep in. I'm certain there is a simple solution i am missing at the moment.
Packaging
You can handle this easily with INT and MOD.
=INT($A3/B$2)
=INT(MOD($A3,B$2)/C$2)
It was easy when the packaging was convenient. If it isn't, instead of MOD, you could use SUMPRODUCT.
=INT($A3/B$2)
=INT(($A3-SUMPRODUCT($B$2:B$2,$B3:B3))/C$2)
A quick go at this, but I added some prices:
But you may want to consider how you could get the result of ordering 20 and having 2 spare etc...
So, set that up like this, but you nay want to fine tune to control your situation more precisely:
Related
I know it's possible to add an element inside a list AND NOT AS THE FIRST ELEMENT NOR THE LAST by redefining the list and adding three lists:
# I want to add 5 into [1,2,3,4,6,7,8,9,0] between the 4 and the 6
A=[1,2,3,4,6,7,8,9,0]
A=[1,2,3,4]+[5]+[6,7,8,9,0]
but I think this isn't optimal, since I'm creating three lists and re-defining a variable. Someone could show me the best way to do this?
You can use insert method of the list mentioned here.
L = [1,2,3,4,6,7,8,9,0]
L.insert(4,5)
This is the optimized way of python, if you need more optimized insertion operation perhaps use some other data structure depending upon your need.
I really love using total functions. That said, sometimes I'm not sure what the best approach is for guaranteeing that. Lets say that I'm writing a function similar to chunksOf from the split package, where I want to split up a list into sublists of a given size. Now I'd really rather say that the input for sublist size needs to be a positive int (so excluding 0). As I see it I have several options:
1) all-out: make a newtype for PositiveInt, hide the constructor, and only expose safe functions for creating a PositiveInt (perhaps returning a Maybe or some union of Positive | Negative | Zero or what have you). This seems like it could be a huge hassle.
2) what the split package does: just return an infinite list of size-0 sublists if the size <= 0. This seems like you risk bugs not getting caught, and worse: those bugs just infinitely hanging your program with no indication of what went wrong.
3) what most other languages do: error when the input is <= 0. I really prefer total functions though...
4) return an Either or Maybe to cover the case that the input might have been <= 0. Similar to #1, it seems like using this could just be a hassle.
This seems similar to this post, but this has more to do with error conditions than just being as precise about types as possible. I'm looking for thoughts on how to decide what the best approach for a case like this is. I'm probably most inclined towards doing #1, and just dealing with the added overhead, but I'm concerned that I'll be kicking myself down the road. Is this a decision that needs to be made on a case-by-case basis, or is there a general strategy that consistently works best?
Let's say that I have a = '1+2*5/3', there's a specific order to which my machine will evaluate this statement (with eval(a))
I would like to know if there's a line of code (or a function? just an elegant way that could get the job done) that would calculate :
(1+2)*5/3
1+(2*5)/3
1+2*(5/3)
(1+2*5)/3
1+(2*5/3)
(1+2)*(5/3)
1+2*5/3
In this example, I used an operation with 4 factors, so I could just code 1 function for each possibility, but I need to do the same thing with 6 factors and that would just take way too much time and effort since the possibility of different operation order would increase exponentially
It would be also great that it returns everything in a dictionary in this form {operation:result} with the parentheses included, if not i'll find my way around it
edit: as requested, the main goal is to make a program that find the solution to the game " le compte est bon " brute force method, the rules can be found here : https://en.wikipedia.org/wiki/Des_chiffres_et_des_lettres#Le_compte_est_bon_.28.22the_total_is_right.22.29
This is going to be very hard. I recommend you follow these steps:
Create a list to check if the formula has already been calculated
Randomize the order (such as +-*/ and randomly place numbers
Check if rule number`s one is a valid formula. if not try number 1 again
Randomize the order (such as opening and closing parentheses and ^)
Check if the sentence above is a valid formula. if not try number 3 again.
Check the formula through the list and see if it has already been calculated. if it has been calculated then we don't use it and go back to number two. but...
If it is not in the list then we can use it.
Those are the basic steps for common known math symbols, but what about square root?
Another way to do this is by making python move the symbols over like you did with the parentheses, but for EVERYTHING (numbers and symbols(+-/*))
EDIT:
This was before the original question was changed.
There's an algorithm currently driving me crazy.
I've seen quite a few variations of it, so I'll just try to explain the easiest one I can think about.
Let's say I have a project P:
Project P is made up of 4 sub projects.
I can solve each of those 4 in two separate ways, and each of those modes has a specific cost and a specific time requirement:
For example (making it up):
P: 1 + 2 + 3 + 4 + .... n
A(T/C) Ta1/Ca1 Ta2/Ca2 etc
B(T/C) Tb1/Cb1 etc
Basically I have to find the combination that of those four modes which has the lowest cost. And that's kind of easy, the problem is: the combination has to be lower than specific given time.
In order to find the lowest combination I can easily write something like:
for i = 1 to n
aa[i] = min(aa[i-1],ba[i-1]) + value(a[i])
bb[i] = min(bb[i-1],ab[i-1]) + value(b[i])
ba[i] = min(bb[i-1],ab[i-1]) + value(b[i])
ab[i] = min(aa[i-1],ba[i-1]) + value(a[i])
Now something like is really easy and returns the correct value every time, the lowest at the last circle is gonna be the correct one.
Problem is: if min returns modality that takes the last time, in the end I'll have the fastest procedure no matter the cost.
If if min returns the lowest cost, I'll have the cheapest project no matter the amount of time taken to realize it.
However I need to take both into consideration: I can do it easily with a recursive function with O(2^n) but I can't seem to find a solution with dynamic programming.
Can anyone help me?
If there are really just four projects, you should go with the exponential-time solution. There are only 16 different cases, and the code will be short and easy to verify!
Anyway, the I'm pretty sure the problem you describe is the knapsack problem, which is NP-hard. So, there will be no exact solution that's sub-exponential unless P=NP. However, depending on what "n" actually is (is it 4 in your case? or the values of the time and cost?) there may be a pseudo-polynomial time solution. The Wikipedia article contains descriptions of these.
I think the best way to form this question is with an example...so, the actual reason I decided to ask about this is because of because of Problem 55 on Project Euler. In the problem, it asks to find the number of Lychrel numbers below 10,000. In an imperative language, I would get the list of numbers leading up to the final palindrome, and push those numbers to a list outside of my function. I would then check each incoming number to see if it was a part of that list, and if so, simply stop the test and conclude that the number is NOT a Lychrel number. I would do the same thing with non-lychrel numbers and their preceding numbers.
I've done this before and it has worked out nicely. However, it seems like a big hassle to actually implement this in Haskell without adding a bunch of extra arguments to my functions to hold the predecessors, and an absolute parent function to hold all of the numbers that I need to store.
I'm just wondering if there is some kind of tool that I'm missing here, or if there are any standards as a way to do this? I've read that Haskell kind of "naturally caches" (for example, if I wanted to define odd numbers as odds = filter odd [1..], I could refer to that whenever I wanted to, but it seems to get complicated when I need to dynamically add elements to a list.
Any suggestions on how to tackle this?
Thanks.
PS: I'm not asking for an answer to the Project Euler problem, I just want to get to know Haskell a bit better!
I believe you're looking for memoizing. There are a number of ways to do this. One fairly simple way is with the MemoTrie package. Alternatively if you know your input domain is a bounded set of numbers (e.g. [0,10000)) you can create an Array where the values are the results of your computation, and then you can just index into the array with your input. The Array approach won't work for you though because, even though your input numbers are below 10,000, subsequent iterations can trivially grow larger than 10,000.
That said, when I solved Problem 55 in Haskell, I didn't bother doing any memoization whatsoever. It turned out to just be fast enough to run (up to) 50 iterations on all input numbers. In fact, running that right now takes 0.2s to complete on my machine.