I was doing a quick read up on arrays and some basic methods. And one of the exercise questions at the end of the reading gave me an array and asked to get the following output
=> [10, 8, 4, 2]
Here's the array:
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
solution:1
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
numbers = numbers.select { |number| number.even? }.reverse
numbers.delete(6)
p numbers
But my question to you is why would the above code return the correct output but the following code won't?
solution: 2
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
numbers = numbers.select { |number| number.even? }
numbers.delete(6)
numbers.reverse
p numbers
I understand it's not the most fluent, but when I try to solve these exercises it's easier for me to separate everything and then clean up the code.
I expected it to pull the even numbers delete 6 from them and then print the reversed array.
Instead it pulls the even numbers, deletes 6, and prints the even numbers. Completely skips the .reverse
As max says, .reverse doesn't change the array. Try, instead:
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
numbers = numbers.select { |number| number.even? }
numbers.delete(6)
numbers.reverse!
p numbers
=> [10, 8, 4, 2]
As other commenters have mentioned, .reverse doesn't change the array.
You either have to declare numbers.reverse as a new variable (i.e. reversed_numbers = numbers.reverse) or use numbers.reverse! (as demonstrated by jvillian) to change the value of the numbers variable itself at invocation.
Between the two, the latter method is more suitable.
Hope this helped!
I want to combine the arrays together to add the first column of all arrays, then the second columns, respectively, to the end.
My arrays :
[1,2,3,4,5]
[6,7,8,9,10]
[11,12,13,14,15]
i want result :
[1,6,11 , 2,7,12 , 3,8,13 , 4,9,14 , 5,10,15]
Suppose we have a "simple" case where the three arrays are the same length:
a = [1,2,3,4,5]
b = [6,7,8,9,10]
c = [11,12,13,14,15]
In this case, you can use Array#zip to merge the arrays in your desired way, then flatten the result into a single array:
a.zip(b, c).flatten
#=> [1, 6, 11, 2, 7, 12, 3, 8, 13, 4, 9, 14, 5, 10, 15]
However, what if a.length > b.length or b.length > c.length?
a = [1,2,3,4,5]
b = [6,7,8,9]
c = [10,11,12]
This is a little bit harder, because now Array#zip will leave you with some nil values that you presumably want to remove:
a.zip(b, c).flatten
#=> [1, 6, 10, 2, 7, 11, 3, 8, 12, 4, 9, nil, 5, nil, nil]
a.zip(b, c).flatten.compact
#=> [1, 6, 10, 2, 7, 11, 3, 8, 12, 4, 9, 5]
And finally, what if a.length < b.length or b.length < c.length?
a = [1,2,3]
b = [4,5,6,7]
c = [8,9,10,11,12]
This is again a bit harder. Now, you'll presumably want to pad the arrays with as many nils as needed, and then perform the same operation as above:
max_length = [a,b,c].map(&:length).max
def padded_array(array, size)
array.dup.fill(nil, array.length, size)
end
padded_array(a, max_length).zip(
padded_array(b, max_length), padded_array(c, max_length)
).flatten.compact
So the complexity of your final answer depends on what arrays you are dealing with, and how far you need to go with accounting for edge cases.
a = [1,2,3,4,5]
b = [6,7,8,9,10]
c = [11,12,13,14,15]
((a.zip b).zip c).flatten.compact
=> [1, 6, 11, 2, 7, 12, 3, 8, 13, 4, 9, 14, 5, 10, 15]
I seem to be a little confused on the proper implementation of Quick Sort.
If I wanted to find all of the pivot values of QuickSort, at what point do I stop dividing the subarrays?
QuickSort(A,p,r):
if p < r:
q = Partition(A,p,r)
Quicksort(A,p,q-1)
Quicksort(A,q+1,r)
Partition(A,p,r):
x = A[r]
i = p-1
for j = p to r-1:
if A[j] ≤ x:
i = i + 1
swap(A[i], A[j])
swap(A[i+1], A[r])
return i+1
Meaning, if I have an array:
A = [9, 7, 5, 11, 12, 2, 14, 3, 10, 6]
As Quick Sort breaks this into its constitutive pieces...
A = [2, 5, 3] [12, 7, 14, 9, 10, 11]
One more step to reach the point of confusion...
A = [2, 5] [7, 12, 14, 9, 10, 11]
Does the subArray on the left stop here? Or does it (quickSort) make a final call to quickSort with 5 as the final pivot value?
It would make sense to me that we continue until all subarrays are single items- but one of my peers have been telling me otherwise.
Pivots for your example would be: 6, 3, 11, 10, 9, 12. Regarding
Does the subArray on the left stop here?
It is always best to examine the source code. When your recursive subarray becomes [2, 5, 3], function QuickSort will be invoked with p = 0 and r = 2. Let's proceed: Partition(A,0,2) will return q = 1, so the next two calls will be Quicksort(A,0,0) and Quicksort(A,2,2). Therefore, Quicksort(A,0,1) will never be invoked, so you'll never have a chance to examine the subarray [2, 5] - it has already been sorted!
I have an array of objects of variable length n. Defined by the number of records in my database.
I need a function to grab subsets (keeping the objects in order and always beginning at index 0) of the array of specified length m where m can be any integer I pass in.
e.g. if n = 10 and m = 4
array foo = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
subset a = [0, 1, 2, 3]
subset b = [4, 5, 6, 7]
subset c = [8, 9]
So, I need to programmatically be able to say, "Give me the i-th subset of length m from an array, given the array is length n." Using the previous example: "Give me the second subset of length four from foo" => returns the items at positions [4, 5, 6, 7].
I hope that made sense. Assistance with a ruby solution would be much appreciated! thx!
foo.each_slice(subset_length).to_a[subset_index]
e.g. foo.each_slice(4).to_a[2] returns "the second subset of length four from foo".
You can use Enumerable#each_slice:
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9].each_slice(4).to_a
#=> [[0, 1, 2, 3], [4, 5, 6, 7], [8, 9]]
My friend was asked a question in his interview:
The interviewer gave him an array of unsorted numbers and asked him to sort. The restriction is that the number of writes should be minimized while there is no limitation on the number of reads.
Selection sort is not the right algorithm here. Selection sort will swap values, making up to two writes per selection, giving a maximum of 2n writes per sort.
An algorithm that's twice as good as selection sort is "cycle" sort, which does not swap. Cycle sort will give a maximum of n writes per sort. The number of writes is absolutely minimized. It will only write a number once to its final destination, and only then if it's not already there.
It is based on the idea that all permutations are products of cycles and you can simply cycle through each cycle and write each element to its proper place once.
import java.util.Random;
import java.util.Collections;
import java.util.Arrays;
public class CycleSort {
public static final <T extends Comparable<T>> int cycleSort(final T[] array) {
int writes = 0;
// Loop through the array to find cycles to rotate.
for (int cycleStart = 0; cycleStart < array.length - 1; cycleStart++) {
T item = array[cycleStart];
// Find where to put the item.
int pos = cycleStart;
for (int i = cycleStart + 1; i < array.length; i++)
if (array[i].compareTo(item) < 0) pos++;
// If the item is already there, this is not a cycle.
if (pos == cycleStart) continue;
// Otherwise, put the item there or right after any duplicates.
while (item.equals(array[pos])) pos++;
{
final T temp = array[pos];
array[pos] = item;
item = temp;
}
writes++;
// Rotate the rest of the cycle.
while (pos != cycleStart) {
// Find where to put the item.
pos = cycleStart;
for (int i = cycleStart + 1; i < array.length; i++)
if (array[i].compareTo(item) < 0) pos++;
// Put the item there or right after any duplicates.
while (item.equals(array[pos])) pos++;
{
final T temp = array[pos];
array[pos] = item;
item = temp;
}
writes++;
}
}
return writes;
}
public static final void main(String[] args) {
final Random rand = new Random();
final Integer[] array = new Integer[8];
for (int i = 0; i < array.length; i++) { array[i] = rand.nextInt(8); }
for (int iteration = 0; iteration < 10; iteration++) {
System.out.printf("array: %s ", Arrays.toString(array));
final int writes = cycleSort(array);
System.out.printf("sorted: %s writes: %d\n", Arrays.toString(array), writes);
Collections.shuffle(Arrays.asList(array));
}
}
}
A few example runs :
array: [3, 2, 6, 1, 3, 1, 4, 4] sorted: [1, 1, 2, 3, 3, 4, 4, 6] writes: 6
array: [1, 3, 4, 1, 3, 2, 4, 6] sorted: [1, 1, 2, 3, 3, 4, 4, 6] writes: 4
array: [3, 3, 1, 1, 4, 4, 2, 6] sorted: [1, 1, 2, 3, 3, 4, 4, 6] writes: 6
array: [1, 1, 3, 2, 4, 3, 6, 4] sorted: [1, 1, 2, 3, 3, 4, 4, 6] writes: 6
array: [3, 2, 3, 4, 6, 4, 1, 1] sorted: [1, 1, 2, 3, 3, 4, 4, 6] writes: 7
array: [6, 2, 4, 3, 1, 3, 4, 1] sorted: [1, 1, 2, 3, 3, 4, 4, 6] writes: 6
array: [6, 3, 2, 4, 3, 1, 4, 1] sorted: [1, 1, 2, 3, 3, 4, 4, 6] writes: 5
array: [4, 2, 6, 1, 1, 4, 3, 3] sorted: [1, 1, 2, 3, 3, 4, 4, 6] writes: 7
array: [4, 3, 3, 1, 2, 4, 6, 1] sorted: [1, 1, 2, 3, 3, 4, 4, 6] writes: 7
array: [1, 6, 4, 2, 4, 1, 3, 3] sorted: [1, 1, 2, 3, 3, 4, 4, 6] writes: 7
array: [5, 1, 2, 3, 4, 3, 7, 0] sorted: [0, 1, 2, 3, 3, 4, 5, 7] writes: 5
array: [5, 1, 7, 3, 2, 3, 4, 0] sorted: [0, 1, 2, 3, 3, 4, 5, 7] writes: 6
array: [4, 0, 3, 1, 5, 2, 7, 3] sorted: [0, 1, 2, 3, 3, 4, 5, 7] writes: 8
array: [4, 0, 7, 3, 5, 1, 3, 2] sorted: [0, 1, 2, 3, 3, 4, 5, 7] writes: 7
array: [3, 4, 2, 7, 5, 3, 1, 0] sorted: [0, 1, 2, 3, 3, 4, 5, 7] writes: 7
array: [0, 5, 3, 2, 3, 7, 1, 4] sorted: [0, 1, 2, 3, 3, 4, 5, 7] writes: 6
array: [1, 4, 3, 7, 2, 3, 5, 0] sorted: [0, 1, 2, 3, 3, 4, 5, 7] writes: 7
array: [1, 5, 0, 7, 3, 3, 4, 2] sorted: [0, 1, 2, 3, 3, 4, 5, 7] writes: 7
array: [0, 5, 7, 3, 3, 4, 2, 1] sorted: [0, 1, 2, 3, 3, 4, 5, 7] writes: 4
array: [7, 3, 1, 0, 3, 5, 4, 2] sorted: [0, 1, 2, 3, 3, 4, 5, 7] writes: 7
If the array is shorter (ie less than about 100 elements) a Selection sort is often the best choice if you also want to reduce the number of writes.
From wikipedia:
Another key difference is that
selection sort always performs Θ(n)
swaps, while insertion sort performs
Θ(n2) swaps in the average and worst
cases. Because swaps require writing
to the array, selection sort is
preferable if writing to memory is
significantly more expensive than
reading. This is generally the case if
the items are huge but the keys are
small. Another example where writing
times are crucial is an array stored
in EEPROM or Flash. There is no other
algorithm with less data movement.
For larger arrays/lists Quicksort and friends will provide better performance, but may still likely need more writes than a selection sort.
If you're interested this is a fantastic sort visualization site that allows you to watch specific sort algorithms do their job and also "race" different sort algorithms against each other.
You can use a very naive algorithm that satisfies what you need.
The algorithm should look like this:
i = 0
do
search for the minimum in range [i..n)
swap a[i] with a[minPos]
i = i + 1
repeat until i = n.
The search for the minimum can cost you almost nothing, the swap costs you 3 writes, the i++ costs you 1..
This is named selection sort as stated by ash. (Sorry, I didn't knew it was selection sort :( )
One option for large arrays is as follows (assuming n elements):
Initialize an array with n elements numbered 0..n-1
Sort the array using any sorting algorithm. As the comparison function, compare the elements in the input set with the corresponding numbers (eg, to compare 2 and 4, compare the 2nd and 4th elements in the input set). This turns the array from step 1 into a permutation that represents the sorted order of the input set.
Iterate through the elements in the permutation, writing out the blocks in the order specified by the array. This requires exactly n writes, the minimum.
To sort in-place, in step 3 you should instead identify the cycles in the permutation, and 'rotate' them as necessary to result in sorted order.
The ordering I meant in O(n) is like the selection sort(the previous post) useful when you have a small range of keys (or you are ordering numbers between 2 ranges)
If you have a number array where numbers will be between -10 and 100, then you can create an array of 110 and be sure that all numbers will fit in there, if you consider repeated numbers the idea is the same, but you will have lists instead of numbers in the sorted array
the pseudo-idea is like this
N: max value of your array
tosort //array to be sorted
sorted = int[N]
for i = 0 to length(tosort)
do
sorted[tosort[i]]++;
end
finalarray = int[length(tosort)]
k = 0
for i = 0 to N
do
if ( sorted[i] > 0 )
finalarray[k] = i
k++;
endif
end
finalarray will have the final sorted array and you will have o(N) write operations, where N is the range of the array. Once again, this is useful when using keys inside a specific range, but perhaps its your case.
Best regards and good luck!