How do I find two elements in an array that have the smallest difference?
In other words, how to find two elements that have a the smallest standard deviation.
For instance, if I have an array like:
arr = [158,2,15,38,17,91]
the result would be 15 and 17.
I assume the question is, "for which two elements of the array is the absolute value of their difference minimum?".
arr.combination(2).min_by { |a,b| (a-b).abs }
#=> [15, 17]
See Array#combination and Enumerable#min_by.
Related
I am not understanding the following question. I mean I want to know the sample input output for this problem question: "The pigeonhole principle states that if a function f has n distinct inputs but less than n distinct outputs,then there exist two inputs a and b such that a!=b and f(a)=f(b). Present an algorithm to find a and b such that f(a)=f(b). Assume that the function inputs are 1,2,......,and n.?"
I am unable to solve this problem as I am not understanding the question clearly. looking for your help.
The pigeonhole principle says that if you have more items than boxes, at least one of the boxes must have multiple items in it.
If you want to find which items a != b have the property f(a) == f(b), a straightforward approach is to use a hashmap data structure. Use the function value f(x) as key to store the item value x. Iterate through the items, x=1,...,n. If there is no entry at f(x), store x. If there is, the current value of x and the value stored at f(x) are a pair of the type you're seeking.
In pseudocode:
h = {} # initialize an empty hashmap
for x in 1,...,n
if h[f(x)] is empty
h[f(x)] <- x # store x in the hashmap indexed by f(x)
else
(x, h[f(x)]) qualify as a match # do what you want with them
If you want to identify all pigeons who have roommates, initialize the hashmap with empty sets. Then iterate through the values and append the current value x to the set indexed by f(x). Finally, iterate through the hashmap and pick out all sets with more than one element.
Since you didn't specify a language, for the fun of it I decided to implement the latter algorithm in Ruby:
N = 10 # number of pigeons
# Create an array of value/function pairs.
# Using N-1 for range of rand guarantees at least one duplicate random
# number, and with the nature of randomness, quite likely more.
value_and_f = Array.new(N) { |index| [index, rand(N-1)]}
h = {} # new hash
puts "Value/function pairs..."
p value_and_f # print the value/function pairs
value_and_f.each do |x, key|
h[key] = [] unless h[key] # create an array if none exists for this key
h[key] << x # append the x to the array associated with this key
end
puts "\nConfirm which values share function mapping"
h.keys.each { |key| p h[key] if h[key].length > 1 }
Which produces the following output, for example:
Value/function pairs...
[[0, 0], [1, 3], [2, 1], [3, 6], [4, 7], [5, 4], [6, 0], [7, 1], [8, 0], [9, 3]]
Confirm which values share function mapping
[0, 6, 8]
[1, 9]
[2, 7]
Since this implementation uses randomness, it will produce different results each time you run it.
Well let's go step by step.
I have 2 boxes. My father gave me 3 chocolates....
And I want to put those chocolates in 2 boxes. For our benefit let's name the chocolate a,b,c.
So how many ways we can put them?
[ab][c]
[abc][]
[a][bc]
And you see something strange? There is atleast one box with more than 1 chocolate.
So what do you think?
You can try this with any number of boxes and chocolates ( more than number of boxes) and try this. You will see that it's right.
Well let's make it more easy:
I have 5 friends 3 rooms. We are having a party. And now let's see what happens. (All my friends will sit in any of the room)
I am claiming that there will be atleast one room where there will be more than 1 friend.
My friends are quite mischievious and knowing this they tried to prove me wrong.
Friend-1 selects room-1.
Friend-2 thinks why room-1? Then I will be correct so he selects room-2
Friend-3 also thinks same...he avoids 1 and 2 room and get into room-3
Friend-4 now comes and he understands that there is no other empty room and so he has to enter some room. And thus I become correct.
So you understand the situation?
There n friends (funtions) but unfortunately or (fortunately) their rooms (output values) are less than n. So ofcourse one of the there exists 2 friend of mine a and b who shares the same room.( same value f(a)=f(b))
Continuing what https://stackoverflow.com/a/42254627/7256243 said.
Lets say that you map an array A of length N to an array B with length N-1.
Than the result could be an array B; were for 1 index you would have 2 elements.
A = {1,2,3,4,5,6}
map A -> B
Were a possible solution could be.
B= {1,2,{3,4},5,6}
The mapping of A -> could be done in any number of ways.
Here in this example both input index of 3 and 4 in Array A have the same index in array B.
I hope this usefull.
Suppose I have an input array where all objects are non-equivalent - e.g. [13,2,36]. I want the output array to be [1,0,2], since 13 is greater than 2 so "1", 2 is greater than no element so "0", 36 is greater than both 13 and 2 so "2". How do I get the output array with efficiency better than O(n2)?
Edit 1 : I also want to print the output in same ordering. Give a c/c++ code if possible.
Seems like a dynamic programming.
May be this can help
Here is an O(n) algorithm
1.Declare an array of say max size say 1000001;
2.Traverse through all the elements and make arr[input[n]]=1 where input[n] is the element
3.Traverse through the arr and add with the previous index(To keep record of arr[i] is greater than how many elements) like this
arr[i]+=arr[i-1]
Example: if input[]={12,3,36}
After step 2
arr[12]=1,arr[3]=1,arr[36]=1;
After step 3
arr[3]=1,arr[4]=arr[3]+arr[4]=1(arr[4]=0,arr[3]=1),
arr[11]=arr[10]=arr[9]=arr[8]=arr[7]arr[6]=arr[5]=arr[4]=1
arr[12]=arr[11]+arr[12]=2(arr[11]=1,arr[12]=1)
arr[36]=arr[35]+arr[36]=3(because arr[13],arr[14],...arr[35]=2 and arr[36]=1)
4.Traverse through the input array an print arr[input[i]]-1 where i is the index.
So arr[3]=1,arr[12]=2,arr[36]=3;
If you print arr[input[i]] then output will be {2,1,3} so we need to subtract 1 from each element then the output becomes {1,0,2} which is your desired output.
//pseude code
int arr[1000001];
int input[size];//size is the size of the input array
for(i=0;i<size;i++)
input[i]=take input;//take input
arr[input[i]]=1;//setting the index of input[i]=1;
for(i=1;i<1000001;i++)
arr[i]+=arr[i-1];
for(i=0;i<size;i++)
print arr[input[i]]-1;//since arr[i] was initialized with 1 but you want the input as 0 for first element(so subtracting 1 from each element)
To understand the algorithm better,take paper and pen and do the dry run.It will help to understand better.
Hope it helps
Happy Coding!!
Clone original array (and keep original indexes of elements somewhere) and quicksort it. Value of the element in quicksorted array should be quicksorted.length - i, where i is index of element in the new quicksorted array.
[13, 2, 36] - original
[36(2), 13(1), 2(0)] - sorted
[1, 0, 2] - substituted
def sort(array):
temp = sorted(array)
indexDict = {temp[i]: i for i in xrange(len(temp))}
return [indexDict[i] for i in array]
I realize it's in python, but nevertheless should still help you
Schwartzian transform: decorate, sort, undecorate.
Create a structure holding an object as well as an index. Create a new list of these structures from your list. Sort by the objects as planned. Create a list of the indices from the sorted list.
Algorithm question here.
I have an unordered array containing product weights, e.g. [3, 2, 5, 5, 8] which need to be divided up into smaller arrays.
Rules:
REQUIRED: Should return 1 or more arrays.
REQUIRED: No array should sum to more than 12.
REQUIRED: Return minimum possible number of arrays, ex. total weight of example above is 23, which can fit into two arrays.
IDEALLY: Arrays should be weighted as evenly as possible.
In the example above, the ideal return would be [ [3, 8], [2, 5, 5] ]
My current thoughts:
Number of arrays to return will be (sum(input_array) / 12).ceil
A greedy algorithm could work well enough?
This is a combination of the bin packing problem and multiprocessor scheduling problem. Both are NP-hard.
Your three requirements constitute the bin packing problem: find the minimal number of bins of a fixed size (12) that fit all the numbers.
Once you solve that, you have the multiprocessor scheduling problem: given a fixed number of bins, what is the most even way to distribute the numbers among them.
There are number of well-known approximate algorithms for both problems.
How about something with an entirely different take on it. Something really simple. Like this, which is based on common horse sense:
module Splitter
def self.split(values, max_length = 12)
# if the sum of all values is lower than the max_length there
# is no point in continuing
return values unless self.sum(values) > max_length
optimized = []
current = []
# start off by ordering the values. perhaps it's a good idea
# to start off with the smallest values first; this will result
# in gathering as much values as possible in the first array. This
# in order to conform to the rule "Should return minimum possible
# number of arrays"
ordered_values = values.sort
ordered_values.each do |v|
if self.sum(current) + v > max_length
# finish up the current iteration if we've got an optimized pair
optimized.push(current)
# reset for the next iteration
current = []
end
current.push(v)
end
# push the last iteration
optimized.push(current)
return optimized
end
# calculates the sum of a collection of numbers
def self.sum(numbers)
if numbers.empty?
return 0
else
return numbers.inject{|sum,x| sum + x }
end
end
end
Which can be used like so:
product_weights = [3, 2, 5, 5, 8]
p Splitter.split(product_weights)
The output will be:
[[2, 3, 5], [5], [8]]
Now, as said before, this is a really simple sample. And I've excluded the validations for empty or non-numeric values in the array for brevity. But it does seem to conform to your primary requirements:
Splitting the (expected: all numeric) values into arrays
With a ceiling per array, defaulting in the sample to 12
Return minimum amount of arrays by collection the smallest numbers first EDIT: after the edit from the comments, this indeed doesn't work
I do have some doubts regarding the comment on "returning minimum possible number of arrays, and balance the weights throughout those as evenly as possible". I'm sure someone else will come up with an implementation of a better and math-proven algorithm that conforms to that requirement, but perhaps this is at least a suitable example for the discussion?
If I have an array:
a = [1,2,3]
How do I randomly select subsets of the array, such that the elements of each subset are unique? That is, for a the possible subsets would be:
[]
[1]
[2]
[3]
[1,2]
[2,3]
[1,2,3]
I can't generate all of the possible subsets as the real size of a is very big so there are many, many subsets. At the moment, I am using a 'random walk' idea - for each element of a, I 'flip a coin' and include it if the coin comes up heads - but I am not sure if this actually uniformly samples the space. It feels like it biases towards the middle, but this might just be my mind doing pattern-matching, as there will be more middle sized possiblities.
Am I using the right approach, or how should I be randomly sampling?
(I am aware that this is more of a language agnostic and 'mathsy' question, but I felt it wasn't really Mathoverflow material - I just need a practical answer.)
Just go ahead with your original "coin flipping" idea. It uniformly samples the space of possibilities.
It feels to you like it's biased towards the "middle", but that's because the number of possibilities is largest in the "middle". Think about it: there is only 1 possibility with no elements, and only 1 with all elements. There are N possibilities with 1 element, and N possibilities with (N-1) elements. As the number of elements chosen gets closer to (N/2), the number of possibilities grows very quickly.
You could generate random numbers, convert them to binary and choose the elements from your original array where the bits were 1. Here is an implementation of this as a monkey-patch for the Array class:
class Array
def random_subset(n=1)
raise ArgumentError, "negative argument" if n < 0
(1..n).map do
r = rand(2**self.size)
self.select.with_index { |el, i| r[i] == 1 }
end
end
end
Usage:
a.random_subset(3)
#=> [[3, 6, 9], [4, 5, 7, 8, 10], [1, 2, 3, 4, 6, 9]]
Generally this doesn't perform so bad, it's O(n*m) where n is the number of subsets you want and m is the length of the array.
I think the coin flipping is fine.
ar = ('a'..'j').to_a
p ar.select{ rand(2) == 0 }
An array with 10 elements has 2**10 possible combinations (including [ ] and all 10 elements) which is nothing more then 10 times (1 or 0). It does output more arrays of four, five and six elements, because there are a lot more of those in the powerset.
A way to select a random element from the power set is the following:
my_array = ('a'..'z').to_a
power_set_size = 2 ** my_array.length
random_subset = rand(power_set_size)
subset = []
random_subset.to_i(2).chars.each_with_index do |bit, corresponding_element|
subset << my_array[corresponding_element] if bit == "1"
end
This makes use of strings functions instead than working with real "bits" and bitwise operations just for my convenience. You can turn it into a faster (I guess) algorithm by using real bits.
What it does, is to encode the powerset of array as an integer between 0 and 2 ** array.length and then picks one of those integers at random (uniformly random, indeed). Then it decodes back the integer into a particular subset of array using a bitmask (1 = the element is in the subset, 0 = it is not).
In this way you have an uniform distribution over the power set of your array.
a.select {|element| rand(2) == 0 }
For each element, a coin is flipped. If heads ( == 0), then it is selected.
i've seen a lot of other questions touch on the subject but nothing as on topic as to provide an answer for my particular problem. Is there a way to search an array and return values within a given range...
for clarity I have one array = [0,5,12]
I would like to compare array to another array (array2) using a range of numbers.
Using array[0] as a starting point how would I return all values from array2 +/- 4 of array[0].
In this particular case the returned numbers from array2 will be within the range of -4 and 4.
Thanks for the help ninjas.
Build a Range that is your target ±4 and then use Enumerable#select (remember that Array includes Enumerable) and Range#include?.
For example, let us look for 11±4 in an array that contains the integers between 1 and 100 (inclusive):
a = (1..100).to_a
r = 11-4 .. 11+4
a.select { |i| r.include?(i) }
# [7, 8, 9, 10, 11, 12, 13, 14, 15]
If you don't care about preserving order in your output and you don't have any duplicates in your array you could do it this way:
a & (c-w .. c+w).to_a
Where c is the center of your interval and w is the interval's width. Using Array#& treats the arrays as sets so it will remove duplicates and is not guaranteed to preserver order.