Related
def two_sum(nums, target)
for i in 0..3 - 1
for j in 0..3 - 1
if nums[i] + nums[j] == target && i < j && i != j
puts '[' + (i - 1).to_s + ',' + (j - 1).to_s + ']'
end
end
end
return (i - 1), (j - 1)
end
def main()
nums = Array.new()
target = gets().to_i
nums = gets().to_i
two_sum(nums, target)
end
main()
The requirement of the exercise is to print out numbers whose sum is equal to a target number. You need to get an array of integers and the target number at first.
Can anyone debug it for me? Thank you.
I will leave it others to debug your code. Instead I would like to suggest another way that calculation could be made relatively efficiently.
def two_sum(nums, target)
h = nums.each_with_index.with_object(Hash.new { |h,k| h[k] = [] }) do |(n,i),h|
h[n] << i
end
n,i = nums.each_with_index.find { |n,_i| h.key?(target-n) }
return nil if n.nil?
indices = h[target-n]
return [i,indices.first] unless n == target/2
return nil if indices.size == 1
[i, indices.find { |j| j !=i }]
end
two_sum([2,7,11,15], 9) #=> [0, 1]
two_sum([2,7,11,15], 10) #=> nil
two_sum([2,7,11,15], 4) #=> nil
two_sum([2,7,11,2,15], 4) #=> [0, 3]
two_sum([2,11,7,11,2,15,11], 22) #=> [1, 3]
In the last example
h #=> {2=>[0, 4], 11=>[1, 3, 6], 7=>[2], 15=>[5]}
Note that key lookups in hashes are very fast, specifically, the execution of the line
indices = h[target-n]
Building h has a computational complexity of O(n), where n = num.size and the remainder is very close to O(n) ("very close" because key lookups are close to constant-time), the overall computational complexity is close to O(n), whereas a brute-force approach considering each pair of values in num is O(n^2).
If a hash is defined
h = Hash.new { |h,k| h[k] = [] }
executing h[k] when h has no key k causes
h[k] = []
to be executed. For example, if
h #=> { 2=>[0] }
then
h[11] << 1
causes
h[11] = []
to be executed (since h does not have a key 11), after which
h[11] << 1
is executed, resulting in
h #=> { 2=>[0], 11=>[1] }
By contrast, if then
h[2] << 3
is executed we obtain
h #=> { 2=>[0,3], 11=>[1] }
without h[2] = [] being executed because h already has a key 2. See Hash::new.
Expressing block variables as
|(n,i),h|
is a form of array decomposition.
Invoice numbers are numeric only with any number of digits. To format one correctly, group the digits in group of three plus a group of any remainder, but never leave one digit by itself, unless it's a one digit number. Eg these are all correct formatting
123
12-34
6
783-907-23-45
And these are not
123-4
98-456
There's one more catch user input is passed directly to the function and you never know what characters users might type. Ignore any part of the input that is not digit
Invoice.format_number should always return a string
module Invoice
def self.format_number(str)
return ""
end
end
puts Invoice.format_number("ab1234")
What I have tried
1st approach
arr = []
str.chars.each do |elem|
val = elem =~ /\A[-+]?[0-9]*\.?[0-9]+\Z/
arr << elem if val == 0
end
num_of_digits = arr.length
pairs_of_two = 0
pairs_of_three = 0
if num_of_digits > 5
while num_of_digits > 0 do
break if num_of_digits <= 3
if num_of_digits >= 3 && (num_of_digits % 3 == 0 || num_of_digits % 3 == 2)
pairs_of_three += 1
num_of_digits -= 3
elsif num_of_digits % 2 == 0 || num_of_digits % 2 == 1
pairs_of_two += 1
num_of_digits -= 2
end
end
end
2nd approach
arr = []
str.chars.each do |elem|
val = elem =~ /\A[-+]?[0-9]*\.?[0-9]+\Z/
arr << elem if val == 0
end
len = arr.length - 1
if arr.length > 4
str = ""
i = 0
while i < len do
if arr[i..i+3].length == 4
str << arr[i..i+2].join + "-"
i += 3
elsif arr[i..i+2].length == 3
str << arr[i..i+1].join + "-"
i += 2
elsif arr[i..i+1].length == 2
str << arr[i..i+1].join
i += 2
elsif !arr[i].nil?
str << arr[i]
i += 1
end
end
puts str
else
if arr.length <= 3
puts arr.join
else
puts arr[0..1].join + "-" + arr[2..3].join
end
end
But none of them is correct
Here is the function invoice_number in python
def invoice_number(invoice):
s = ''.join(x for x in invoice if x <= '9' and x >= '0')
n = len(s)
if n <= 3:
return s
w = ''
i = 0
while i + 3 <= n:
for j in range(0, 3):
w += s[i + j]
i += 3
w += ('-')
m = n - i
if m == 0: return w[:-1]
if m == 1: return w[:m-3] + '-' + s[-2:]
return w + s[i:]
Testing
print(invoice_number('1234567'))
print(invoice_number('12345678'))
print(invoice_number('abc123456789'))
print(invoice_number('1234abc5678xyz9foobar'))
123-45-67
123-456-78
123-456-789
123-456-789
Eliminating non-digits is easy with re. For your format, the key is to figure our the "right" splitting indices.
Here is a try:
import re
def splits(n, k):
idx = [(i, min(n, i+k)) for i in range(0, n, k)]
if len(idx) > 1:
(a, b), (c, d) = idx[-2:]
if d - c < 2:
idx[-2:] = [(a, b - 1), (c - 1, d)]
return idx
def myformat(s):
s = re.sub(r'[^0-9]+', '', s)
parts = [s[a:b] for a, b in splits(len(s), 3)]
return '-'.join(parts)
Tests:
>>> myformat('123')
123
>>> myformat('1234')
12-34
>>> myformat('6')
6
>>> myformat('7839072345')
783-907-23-45
As the question was asked for ruby, adding solution for ruby. (The inspiration of the code is mostly from #yuri answer)
def format_invoice(invoice)
# only numbers are allowed
invoice = invoice.tr("^0-9","")
#puts invoice
return invoice if(invoice.length <= 3)
formatted_invoice = ''
i = 0
# Loop to divide the invoice in group of 3
while i + 3 <= invoice.length do
for j in 0..2 do
formatted_invoice += invoice[i + j]
end
i += 3
formatted_invoice += ('-')
end
m = invoice.length - i
return formatted_invoice[0..-2] if m == 0
return formatted_invoice[0..m-4] + '-' + invoice[-2..-1] if m == 1
return formatted_invoice + invoice[i..-1]
end
Testing
puts format_invoice('abc1') # 1
puts format_invoice('abc123') # 123
puts format_invoice('abc123A4') # 12-34
puts format_invoice('1234567') # 123-45-67
puts format_invoice('12345678') # 123-456-78
puts format_invoice('abc123456789') # 123-456-789
puts format_invoice('1234a#c5678xyz9foobar') # 123-456-789
I have a unique sorted array: [2,4,6,8,10].
I have a variable called i. If i is 5, I want to return the elements in the array that 5 falls between. In this case [4,6]. If i is 8, then [8,10].
How should I go about this?
I've tried with partition, to some extent. If i happens to be a number directly equal to one of the values in the array. This seems to work:
a=[2,4,6,8,10]
i = 6
a.partition { |v| v < i }.max[0..1] # returns [6,8]
However, if i is a number not directly equal to any of the values in the array. For example 5, it gets a little trickier.
I got it working for the last case:
a=[2,4,6,8,10]
i = 5
partition = a.partition { |v| v < i }
[].tap { |a| a << partition[0].max; a << partition[1].min } # returns [6,8]
While this works, I am looking to see if there is a better way to write this logic.
You could use Enumerable#each_cons.
def mind_the_gap(arr, n)
arr.each_cons(2).find { |l,u| l <= n && n < u }
end
arr = [2,4,6,8,10]
mind_the_gap(arr, 5) #=> [4,6]
mind_the_gap(arr, 8) #=> [8,10]
mind_the_gap(arr, 1) #=> nil
mind_the_gap(arr, 10) #=> nil
If you don't want the last two examples to return nil, you could change the method as follows.
def mind_the_gap(arr, n)
rv = arr.each_cons(2).find { |l,u| l <= n && n < u }
return rv unless rv.nil?
n < arr.first ? :low : :high
end
mind_the_gap(arr, 5) #=> [4,6]
mind_the_gap(arr, 8) #=> [8,10]
mind_the_gap(arr, 1) #=> :low
mind_the_gap(arr, 10) #=> :high
Another way is to use Enumerable#slice_when.
def mind_the_gap(arr, n)
a = arr.slice_when { |l,u| l <= n && n < u }.to_a
return [a.first.last, a.last.first] unless a.size == 1
n < arr.first ? :low : :high
end
mind_the_gap(arr, 5) #=> [4,6]
mind_the_gap(arr, 8) #=> [8,10]
mind_the_gap(arr, 1) #=> :low
mind_the_gap(arr, 10) #=> :high
If you're looking for elements inside a sorted array, the "better way" probably involves bsearch or bsearch_index.
The second element in the pair is the first element in the array that is greater than your variable, so bsearch_index can return it directly. You need to check it isn't nil or 0 before returning the found element and the previous one :
a = [2, 4, 6, 8, 10]
def find_surrounding_pair(array, element)
second_index = array.bsearch_index { |x| x > element }
array[second_index - 1, 2] if second_index && second_index > 0
end
puts find_surrounding_pair(a, 1).nil?
puts find_surrounding_pair(a, 2) == [2, 4]
puts find_surrounding_pair(a, 7) == [6, 8]
puts find_surrounding_pair(a, 8) == [8, 10]
puts find_surrounding_pair(a, 12).nil?
#=> true * 5
The complexity of this method should be O(log n).
what about this
val = 5
a = [2,4,6,8,10] # assuming it's sorted
a.slice(a.rindex {|e| e <= val}, 2)
It doesn't account for the case when the lookup value is equal or bigger the last element of the array. I'd probably append a nil element for this, if that would be appropriate for the problem.
This looks like a good use to check for the inclusion in a range:
a = [2,4,6,8,10]
b = 5
a.each_cons(2).select { |i, j| (i .. j) === b }
# => [[4, 6]]
It's not clear exactly what you mean by "falls between". In the code above 8 would fall between two sets of numbers:
b = 8
a.each_cons(2).select { |i, j| (i .. j) === b }
# => [[6, 8], [8, 10]]
if the test is i <= b <= j. If it's i <= b < j then use ... instead of ..:
a.each_cons(2).select { |i, j| (i ... j) === b }
# => [[8, 10]]
I'm not a big fan of using ... but it simplifies the code.
From the Range documentation:
Ranges constructed using .. run from the beginning to the end inclusively. Those created using ... exclude the end value.
You could change that to:
a.each_cons(2).select { |i, j| i <= b && b <= j }
or:
a.each_cons(2).select { |i, j| i <= b && b < j }
if those work better for your mind. Using a Range is a little slower, but not radically so.
I need to improve the performance of this algorithm. I believe the answer lies in the application of the pisano period.
This algorithm must return the last digit of the sum of fib numbers from f(m) to f(n).
Here is what I have so far:
def fib(n)
a = []
a << 0 << 1
(n+1).times do |i|
a << a[-1] + a[-2]
end
a[n]
end
def fib_partial_sum(m, n)
if n == m
fib(m) % 10
else
m = fib(m + 1) - 1
n = fib(n + 2) - 1
(n - m) % 10
end
end
if __FILE__ == $0
m, n = gets.split().map(&:to_i)
puts "#{fib_partial_sum(m, n)}"
end
The last digit of any fib num repeats every 60 numbers. Therefore, we can do this, n, m = n % 60, m % 60. An improvement, but not quite there yet, fails on input 567717153638 567717153638):
def fib(n)
a = []
a << 0 << 1
(n+1).times do |i|
a << a[-1] + a[-2]
end
a[n]
end
def fib_partial_sum(m, n)
if n == m
fib(m)
else
m = m % 60
n = n % 60
m = fib(m + 1) - 1
n = fib(n + 2) - 1
(n - m) % 10
end
end
if __FILE__ == $0
m, n = gets.split().map(&:to_i)
puts "#{fib_partial_sum(m, n)}"
end
Here is a nice solution to the problem, it passes all time and memory constraints.
This way you never have to calculate a fib num greater that f(60). It can handle very large inputs efficiently.
def fib(n)
a, b = 0, 1
(n-1).times do
a, b = b, (a + b) % 10
end
b
end
def fib_partial_sum(m, n)
if n == m
fib(m % 60)
else
m = m % 60
n = n % 60
m = fib(m + 1) - 1
n = fib(n + 2) - 1
(n - m) % 10
end
end
if __FILE__ == $0
m, n = gets.split().map(&:to_i)
puts "#{fib_partial_sum(m, n)}"
end
(Max time used: 0.05/5.00, max memory used: 8699904/536870912.)
The following requires only a single pass of the numbers between zero and at most [n,m+60].min, where m..n is the range of interest, and has a minimal memory requirement. It makes use of #nloveladyallen's observation that the last digit of Fibonacci numbers has a periodicity of 60.
Code
def fib_last(m,n)
n -= 60*((n-m)/60)
fib_sum(m,n) % 10
end
def fib_sum(m,n)
return nil if m < 0 || m > n
return n if n < 2
next_to_last, last = fib(m-1)
(m..n).reduce(0) do |tot,_|
current = next_to_last + last
next_to_last = last
last = current
tot + current
end
end
def fib(m)
next_to_last, last = -1, 1
0.upto(m).each do |n|
current = next_to_last + last
next_to_last, last = last, current
end
[next_to_last, last]
end
Example
m, n = 6, 12
(n+1).times { |i| puts "#{i}: #{fib(i)}" }
0: [0, 0]
1: [0, 1]
2: [1, 1]
3: [1, 2]
4: [2, 3]
5: [3, 5]
6: [5, 8]
7: [8, 13]
8: [13, 21]
9: [21, 34]
10: [34, 55]
11: [55, 89]
12: [89, 144]
fib_last(6,12) #=> 4 (fib_sum(6,12) #=> 8 + 13 + 21 + 34 + 55 + 89 + 144 = 364)
fib_last(1,2) #=> 2 (fib_sum(1,2) #=> 1 + 1 = 2)
fib_last(1,3) #=> 4 (fib_sum(1,3) #=> 1 + 1 + 2 = 4)
fib_last(1,4) #=> 7 (fib_sum(1,4) #=> 1 + 1 + 2 + 3 = 7)
fib_last(2,3) #=> 3 (fib_sum(2,3) #=> 1 + 2 = 3)
Given two numbers, say (14, 18), the problem is to find the sum of all the numbers in this range, 14, 15, 16, 17, 18 recursively. Now, I have done this using loops but I have trouble doing this recursively.
Here is my recursive solution:
def sum_cumulative_recursive(a,b)
total = 0
#base case is a == b, the stopping condition
if a - b == 0
puts "sum is: "
return total + a
end
if b - a == 0
puts "sum is: "
return total + b
end
#case 1: a > b, start from b, and increment recursively
if a > b
until b > a
puts "case 1"
total = b + sum_cumulative_recursive(a, b+1)
return total
end
end
#case 2: a < b, start from a, and increment recursively
if a < b
until a > b
puts "case 2"
total = a + sum_cumulative_recursive(a+1, b)
return total
end
end
end
Here are some sample test cases:
puts first.sum_cumulative_recursive(4, 2)
puts first.sum_cumulative_recursive(14, 18)
puts first.sum_cumulative_recursive(-2,-2)
My solution works for cases where a > b, and a < b, but it doesn't work for a == b.
How can I fix this code so that it works?
Thank you for your time.
def sum_cumulative_recursive(a,b)
return a if a == b
a, b = [a,b].sort
a + sum_cumulative_recursive(a + 1, b)
end
EDIT
Here is the most efficient solution I could see from some informal benchmarks:
def sum_cumulative_recursive(a,b)
return a if a == b
a, b = b, a if a > b
a + sum_cumulative_recursive(a + 1, b)
end
Using:
Benchmark.measure { sum_cumulative_recursive(14,139) }
Benchmark for my initial response: 0.005733
Benchmark for #Ajedi32's response: 0.000371
Benchmark for my new response: 0.000115
I was also surprised to see that in some cases, the recursive solution approaches or exceeds the efficiency of the more natural inject solution:
Benchmark.measure { 10.times { (1000..5000).inject(:+) } }
# => 0.010000 0.000000 0.010000 ( 0.027827)
Benchmark.measure { 10.times { sum_cumulative_recursive(1000,5000) } }
# => 0.010000 0.010000 0.020000 ( 0.019441)
Though you run into stack level too deep errors if you take it too far...
I'd do it like this:
def sum_cumulative_recursive(a, b)
a, b = a.to_i, b.to_i # Only works with ints
return sum_cumulative_recursive(b, a) if a > b
return a if a == b
return a + sum_cumulative_recursive(a+1, b)
end
Here's one way of doing it. I assume this is just an exercise, as the sum of the elements of a range r is of course just (r.first+r.last)*(f.last-r.first+1)/2.
def sum_range(range)
return nil if range.last < range.first
case range.size
when 1 then range.first
when 2 then range.first + range.last
else
range.first + range.last + sum_range(range.first+1..range.last-1)
end
end
sum_range(14..18) #=> 80
sum_range(14..14) #=> 14
sum_range(14..140) #=> 9779
sum_range(14..139) #=> 9639
Another solution would be to have a front-end invocation that fixes out-of-order arguments, then a private recursive back-end which does the actual work. I find this is useful to avoid repeated checks of arguments once you've established they're clean.
def sum_cumulative_recursive(a, b)
a, b = b, a if b < a
_worker_bee_(a, b)
end
private
def _worker_bee_(a, b)
a < b ? (a + _worker_bee_(a+1,b-1) + b) : a == b ? a : 0
end
This variant would cut the stack requirement in half by summing from both ends.
If you don't like that approach and/or you really want to trim the stack size:
def sum_cumulative_recursive(a, b)
if a < b
mid = (a + b) / 2
sum_cumulative_recursive(a, mid) + sum_cumulative_recursive(mid+1, b)
elsif a == b
a
else
sum_cumulative_recursive(b, a)
end
end
This should keep the stack size to O(log |b-a|).