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I have written the following program to find the permutation of all the elements in an array. The values are created properly but the problem occurs when I try to assign the generated sequence into a new array. The old values will get cleared and the new values are copied as per the array size
def find_perm(nums, answer, set)
if nums.empty?
p set
answer.push(set)
p answer.object_id
p answer
return true
end
for i in (0..nums.length - 1) do
new_nums = nums.clone
new_nums.delete_at(i)
set.push(nums[i])
find_perm(new_nums, answer, set)
set.pop
end
end
def permute(nums)
answer = []
set = []
element = find_perm(nums, answer, set)
return element
end
permute([1,2,3])
This are the observations that I have found out while debugging:
[1, 2, 3]
47167191669680
[[1, 2, 3]]
[1, 3, 2]
47167191669680
[[1, 3, 2], [1, 3, 2]]
[2, 1, 3]
47167191669680
[[2, 1, 3], [2, 1, 3], [2, 1, 3]]
[2, 3, 1]
47167191669680
[[2, 3, 1], [2, 3, 1], [2, 3, 1], [2, 3, 1]]
[3, 1, 2]
47167191669680
[[3, 1, 2], [3, 1, 2], [3, 1, 2], [3, 1, 2], [3, 1, 2]]
[3, 2, 1]
47167191669680
[[3, 2, 1], [3, 2, 1], [3, 2, 1], [3, 2, 1], [3, 2, 1], [3, 2, 1]]
The problem was each time I was pushing the same set array into the answer array so each element in the answer array will have same reference (same object_id).
Solution: Is to clone the set array during the each push to the answer array so that each element have different reference.
The solution:
def fact(n)
return 1 if n == 1
n*fact(n-1)
end
def find_perm(nums, answer, set)
if nums.empty?
answer.push(set.clone)
end
for i in (0..nums.length - 1) do
new_nums = nums.clone
new_nums.delete_at(i)
set.push(nums[i])
find_perm(new_nums, answer, set)
set.pop
return answer if fact(nums.count) == answer.count
end
end
def permute(nums)
answer = []
set = []
element = find_perm(nums, answer, set)
return element
end
p permute([1,2,3])
I believe the approach you are taking is similar to the following.
Suppose we wish to obtain the permutations of the elements of the array
arr = [1, 2, 3, 4]
Begin with the array
[4]
This array has only a single perumutation:
perms3 = [[4]]
(3 in perms3 denotes the index of 4 in arr.) Now obtain the permuations of
[3, 4]
We see that is
perms2 = [[3, 4], [4, 3]]
We simply take each element of perms3 ([4] is the only one) and create two permuations by inserting 3 before 4 and then 3 after 4;
Now suppose the array were
[2, 3, 4]
Then
perms1 = [[2, 3, 4], [3, 2, 4], [3, 4, 2], [2, 4, 3], [4, 2, 3], [4, 3, 2]]
We create three 3-element arrays from [3, 4], one by inserting 2 before 3, one by inserting 2 between 3 and 4 and one by inserting 2 after 4. Simlarly, three 3-element arrays are generated from [4, 3] in a simlar way. This generates six arrays. (Indeed, 3! #=> 6).
Lastly we generating the 4! #=> 24 permuations of [1, 2, 3, 4] by inserting 1 in four locations of each element of perm1, the first four derived from perms1[0] #=> [2, 3, 4]:
[[1, 2, 3, 4], [2, 1, 3, 4], [2, 3, 1, 4], [2, 3, 4, 1]]
We can do this in code as follows.
def my_permutations(arr)
perms = [[arr.last]]
(arr.size-2).downto(0) do |i|
x = arr[i]
perms = perms.flat_map do |perm|
(0..(perm.size)).map { |i| perm.dup.insert(i, x) }
end
end
perms
end
my_permutations(arr)
#=> [[1, 2, 3, 4], [2, 1, 3, 4], [2, 3, 1, 4], [2, 3, 4, 1], [1, 3, 2, 4],
# [3, 1, 2, 4], [3, 2, 1, 4], [3, 2, 4, 1], [1, 3, 4, 2], [3, 1, 4, 2],
# [3, 4, 1, 2], [3, 4, 2, 1], [1, 2, 4, 3], [2, 1, 4, 3], [2, 4, 1, 3],
# [2, 4, 3, 1], [1, 4, 2, 3], [4, 1, 2, 3], [4, 2, 1, 3], [4, 2, 3, 1],
# [1, 4, 3, 2], [4, 1, 3, 2], [4, 3, 1, 2], [4, 3, 2, 1]]
See Enumerable#flat_map and Array#insert. Note that we need to make a copy of the array perm before invoking insert.
We could of course have gone "forward" in arr (starting with [[1]]), rather than "backward", though the elements of the array of permutations would be ordered differently.
I'm trying to create a program that takes a given sum and a given range of allowed addends and outputs the unique configurations of those addends which add up to the sum.
The use case is determining the possible combinations of different-sized multi-member districts to divide the members of a legislature into.
In a trivial example, given 15 legislators, and districts of minimum 3 and maximum 5 seats per district, the possible combinations are:
[3, 3, 3, 3, 3]
[4, 4, 4, 3]
[5, 4, 3, 3]
[5, 5, 5]
My initial thought was to start with the largest group of minimum-sized districts possible in a nested array, and add more entries by copying and modifying the previous entry. I don't know how to implement that approach, but I'm also not sure if it's even the right approach to this problem and I'm looking for suggestions.
def multi_member_districts
reps = 19
min = 3
max = 6
quomin, modmin = reps.divmod(min)
quomax, modmax = reps.divmod(max)
groups = Array.new(1) {Array.new}
(quomin - 1).times do groups[0].push(min) end
groups[0].unshift(min + modmin)
# PSEUDOCODE
# copy groups[i], insert copy at groups[i+1]
# remove the smallest element of groups[i+1] and spread it out across the other
# numbers in groups[i+1] in all configurations in which no element exceeds max
# check that there are no duplicate configurations
# repeat
puts "\nThe possible groups of districts are as follows:"
groups.each_index do |i|
(min..max).each do |j|
unless groups[i].count(j) == 0
puts ">> #{groups[i].count(j)} #{j}-member districts"
end
end
puts
puts "o-o-o-o-o-o-o-o-o-o-o-o-o-o"
end
end
multi_member_districts
EDIT_1:
A less trivial example, 19 legislators, 3-6 seats per district --
[4, 3, 3, 3, 3, 3]
[4, 4, 4, 4, 3]
[5, 5, 5, 4]
[5, 4, 4, 3, 3]
[5, 5, 3, 3, 3]
[6, 5, 5, 3]
[6, 4, 3, 3, 3]
[6, 5, 4, 4]
[6, 6, 4, 3]
EDIT_2: Clarified my question, cut down the code, hopefully more suitable
Let's first compute the combinations where each combination corresponds to an array arr where arr[i] equals the number of legislators assigned to district i. If, for example, there are 15 legislators and there must be between 3 and 5 assigned to each district, [3,3,4,5] and [5,3,4,3] would be distinct combinations. We can solve that problem using recursion.
def doit(nbr, rng)
return nil if nbr < rng.begin
recurse(nbr, rng)
end
def recurse(nbr, rng)
(rng.begin..[rng.end, nbr].min).each_with_object([]) do |n,arr|
if n == nbr
arr << [n]
elsif nbr-n >= rng.begin
recurse(nbr-n, rng).each { |a| arr << a.unshift(n) }
end
end
end
doit(15, 3..5)
#=> [[3, 3, 3, 3, 3], [3, 3, 4, 5], [3, 3, 5, 4], [3, 4, 3, 5],
# [3, 4, 4, 4], [3, 4, 5, 3], [3, 5, 3, 4], [3, 5, 4, 3], [4, 3, 3, 5],
# [4, 3, 4, 4], [4, 3, 5, 3], [4, 4, 3, 4], [4, 4, 4, 3], [4, 5, 3, 3],
# [5, 3, 3, 4], [5, 3, 4, 3], [5, 4, 3, 3], [5, 5, 5]]
doit(19, 3..6)
#=> [[3, 3, 3, 3, 3, 4], [3, 3, 3, 3, 4, 3], [3, 3, 3, 4, 3, 3],
# [3, 3, 3, 4, 6], [3, 3, 3, 5, 5], [3, 3, 3, 6, 4], [3, 3, 4, 3, 3, 3],
# ...
# [6, 5, 3, 5], [6, 5, 4, 4], [6, 5, 5, 3], [6, 6, 3, 4], [6, 6, 4, 3]]
doit(19, 3..6).size
#=> 111
The question is not concerned, however, with allocations to specific districts. To obtain the combinations of interest we may therefore write the following.
require 'set'
def really_doit(nbr, rng)
doit(nbr, rng).map(&:tally).uniq.map do |h|
h.flat_map { |k,v| [k]*v }.sort.reverse
end
end
really_doit(15, 3..5)
#=> [[3, 3, 3, 3, 3], [5, 4, 3, 3], [4, 4, 4, 3], [5, 5, 5]]
really_doit(19, 3..6)
#=> [[4, 3, 3, 3, 3, 3], [6, 4, 3, 3, 3], [5, 5, 3, 3, 3],
# [5, 4, 4, 3, 3], [4, 4, 4, 4, 3], [6, 6, 4, 3], [6, 5, 5, 3],
# [6, 5, 4, 4], [5, 5, 5, 4]]
Enumerable#tally made its debut in Ruby v2.7. To support earlier versions replace map(&:tally) with map { |a| a.each_with_object(Hash.new(0)) { |n,h| h[n] += 1 }.
Note that doit(nbr, rng).map(&:tally).uniq in returns
[{3=>5}, {3=>2, 4=>1, 5=>1}, {3=>1, 4=>3}, {5=>3}]
in really_doit(15, 3..5) and
[{3=>5, 4=>1}, {3=>3, 4=>1, 6=>1}, {3=>3, 5=>2}, {3=>2, 4=>2, 5=>1},
{3=>1, 4=>4}, {3=>1, 4=>1, 6=>2}, {3=>1, 5=>2, 6=>1}, {4=>2, 5=>1, 6=>1},
{4=>1, 5=>3}]
in really_doit(19, 3..6).
We can improve on this by constructing sets of hashes (rather than arrays of arrays) in recurse:
require 'set'
def doit(nbr, rng)
return nil if nbr < rng.begin
recurse(nbr, rng).map { |h| h.flat_map { |k,v| [k]*v }.sort.reverse }
end
def recurse(nbr, rng)
(rng.begin..[rng.end, nbr].min).each_with_object(Set.new) do |n,st|
if n == nbr
st << { n=>1 }
elsif nbr-n >= rng.begin
recurse(nbr-n, rng).each { |h| st << h.merge(n=>h[n].to_i+1 ) }
end
end
end
doit(15, 3..5)
#=> [[3, 3, 3, 3, 3], [5, 4, 3, 3], [4, 4, 4, 3], [5, 5, 5]]
doit(19, 3..6)
#=> [[4, 3, 3, 3, 3, 3], [6, 4, 3, 3, 3], [5, 5, 3, 3, 3],
# [5, 4, 4, 3, 3], [4, 4, 4, 4, 3], [6, 6, 4, 3], [6, 5, 5, 3],
# [6, 5, 4, 4], [5, 5, 5, 4]]
Note that here recurse(nbr, rng) in doit returns:
#<Set: {{3=>5}, {5=>1, 4=>1, 3=>2}, {4=>3, 3=>1}, {5=>3}}>
When executing doit(19, 3..6) recurse(nbr, rng) in doit returns:
#<Set: {{4=>1, 3=>5}, {6=>1, 4=>1, 3=>3}, {5=>2, 3=>3},
# {5=>1, 4=>2, 3=>2}, {4=>4, 3=>1}, {6=>2, 4=>1, 3=>1},
# {6=>1, 5=>2, 3=>1}, {6=>1, 5=>1, 4=>2}, {5=>3, 4=>1}}>
So what Im trying to accomplish is write a (shorter) condition that makes sure each element is different from the other array. This is confusing but I hope this example clears it up.
array = [1, 2, 3]
new_array = array.shuffle
until array[0] != new_array[0] &&
array[1] != new_array[1] &&
array[2] != new_array[2]
new_array = array.shuffle
end
So what Im doing is making sure that every single element/index pair does not match in the other array.
# [1, 2, 3] => [3, 1, 2] yayyyy
# [1, 2, 3] => [3, 2, 1] not what I want because the 2 didnt move
Is there a better way to do what I want to do? Ive looked up the .any? and .none? but I cant seem to figure out how to implement them. Thanks!
I would do this:
array.zip(new_array).all? { |left, right| left != right }
Here are two approaches that do not involve repeated sampling until a valid sample is obtained:
Sample from the population of valid permutations
Construct the population from which you are sampling:
array = [1, 2, 3, 4]
population = array.permutation(array.size).reject do |a|
a.zip(array).any? { |e,f| e==f }
end
#=> [[2, 1, 4, 3], [2, 3, 4, 1], [2, 4, 1, 3], [3, 1, 4, 2], [3, 4, 1, 2],
# [3, 4, 2, 1], [4, 1, 2, 3], [4, 3, 1, 2], [4, 3, 2, 1]]
Then just choose one at random:
10.times { p population.sample }
# [4, 3, 1, 2]
# [3, 4, 1, 2]
# [3, 4, 1, 2]
# [4, 3, 1, 2]
# [2, 1, 4, 3]
# [2, 1, 4, 3]
# [4, 1, 2, 3]
# [2, 1, 4, 3]
# [4, 3, 1, 2]
# [3, 4, 1, 2]
Sequentially sample for each position in the array
def sample_no_match(array)
a = array.each_index.to_a.shuffle
last_ndx = a[-1]
a.dup.map do |i|
if a.size == 2 && a[-1] == last_ndx
select = a[-1]
else
select = (a-[i]).sample
end
a.delete(select)
array[select]
end
end
10.times.each { p sample_no_match(array) }
# [2, 4, 3, 1]
# [4, 3, 1, 2]
# [2, 1, 3, 4]
# [1, 3, 4, 2]
# [1, 3, 2, 4]
# [1, 3, 2, 4]
# [1, 4, 3, 2]
# [3, 4, 2, 1]
# [1, 3, 4, 2]
# [1, 3, 4, 2]
I have been unable to prove or disprove that the second method produces a random sample. We can, however, determine relative frequencies of outcomes:
n = 500_000
h = n.times.with_object(Hash.new(0)) { |_,h| h[sample_no_match(array)] += 1 }
h.keys.each { |k| h[k] = (h[k]/(n.to_f)).round(4) }
h #=> {[1, 2, 3, 4]=>0.0418, [2, 1, 3, 4]=>0.0414, [1, 4, 2, 3]=>0.0418,
# [3, 4, 2, 1]=>0.0417, [4, 3, 2, 1]=>0.0415, [3, 1, 4, 2]=>0.0419,
# [2, 3, 1, 4]=>0.0420, [4, 2, 3, 1]=>0.0417, [3, 2, 1, 4]=>0.0413,
# [4, 2, 1, 3]=>0.0417, [2, 1, 4, 3]=>0.0419, [1, 3, 2, 4]=>0.0415,
# [1, 2, 4, 3]=>0.0418, [1, 3, 4, 2]=>0.0417, [2, 4, 1, 3]=>0.0414,
# [3, 4, 1, 2]=>0.0412, [1, 4, 3, 2]=>0.0423, [4, 1, 3, 2]=>0.0411,
# [3, 2, 4, 1]=>0.0411, [2, 4, 3, 1]=>0.0418, [3, 1, 2, 4]=>0.0419,
# [4, 3, 1, 2]=>0.0412, [4, 1, 2, 3]=>0.0421, [2, 3, 4, 1]=>0.0421}
avg = (h.values.reduce(:+)/h.size.to_f).round(4)
#=> 0.0417
mn, mx = h.values.minmax
#=> [0.0411, 0.0423]
([avg-mn,mx-avg].max/avg).round(6)
#=> 0.014388
which means that the maximum deviation from the average was only 1.4% percent of the average.
This suggests that the second method is a reasonable way of producing pseudo-random samples.
Initially, the first line of this method was:
a = array.each_index.to_a
By looking at the frequency distribution for outcomes, however, it was clear that that method did not produce a pseudo-random sample; hence, the need to shuffle a.
Here's one possibility:
until array.zip(new_array).reject{ |x, y| x == y }.size == array.size
new_array = array.shuffle
end
Note, though, that it will break for arrays like [1] or [1, 1, 1, 2, 3], where the number of instances of 1 exceeds half the size of the array. Recommend Array#uniq or similar, along with checking for arrays of sizes 0 or 1, depending on how trustworthy your input is!
Let i have lazy sequences: s1, s2, s3, ..., sN, with non-descending numbers, for example:
s1 = [1, 1, 2, 3, 3, 3, 4, .....]
s2 = [1, 2, 2, 2, 2, 2, 3, 3, 4, ....]
s3 = [1, 2, 3, 3, 3, 3, 4, 4, 4, ....]
what I'd like to do - is to merge it, grouping by similar items and processing it with some function, for example generate list of tuples (number, count)
for my case:
merge(s1, s2, s3) should generate [ [1, 4], [2, 6], [3, 9], [4, 5], .... ]
Are any gems, etc., to process such sequences
If you want to do it lazily, here is some code which would do that:
def merge(*args)
args.map!(&:lazy)
Enumerator.new do |yielder|
while num = args.map(&:peek).min
count = 0
while list = args.find { |l| l.peek == num }
list.next
list.peek rescue args.delete list
count += 1
end
yielder.yield [num, count]
end
end
end
s1 = [1, 1, 2, 3, 3, 3, 4]
s2 = [1, 2, 2, 2, 2, 2, 3, 3, 4]
s3 = [1, 2, 3, 3, 3, 3, 4, 4, 4]
s4 = (0..1.0/0)
merge(s1, s2, s3, s4).take(20)
# => [[0, 1], [1, 5], [2, 8], [3, 10], [4, 6], [5, 1], [6, 1], [7, 1], [8, 1], [9, 1], [10, 1], [11, 1], [12, 1], [13, 1], [14, 1], [15, 1], [16, 1], [17, 1], [18, 1], [19, 1]]
I have three Ruby arrays:
[1, 2, 3, 4]
[2, 3, 4, 5]
[3, 4, 5, 6]
How can I take the average of all three numbers in position 0, then position 1, etc. and store them in a new array called 'Average'?
a = [1, 2, 3, 4]
b = [2, 3, 4, 5]
c = [3, 4, 5, 6]
a.zip(b,c)
# [[1, 2, 3], [2, 3, 4], [3, 4, 5], [4, 5, 6]]
.map {|array| array.reduce(:+) / array.size }
# => [ 2,3,4,5]
Try this:
arr = ([1, 2, 3, 4] + [3, 4, 5, 6] + [2, 3, 4, 5])
arr.inject(0.0) { |sum, el| sum + el } / arr.size
The concatenation could be done in several ways, depends on how you store your arrays.
As a syntactic sugar, you could do it like this too:
arr.inject(:+).to_f / arr.size