vault backup: 2023-04-01 23:36:27

Author: noodleslove

Algorithms/Searching.md

@@ -5,13 +5,13 @@
 
 The following steps are followed to search for an element `k = 1` in the list below.
 
-![./Algorithms/Attachments/Array to be searched for](linear-search-initial-array.webp)
+![Array to be searched for](Attachments/linear-search-initial-array.webp)
 1. Start from the first element, compare `k` with each element `x`.
 
-![./Algorithms/Attachments/Compare with each element](linear-search-comparisons.webp)
+![Compare with each element](Attachments/linear-search-comparisons.webp)
 2. If `x == k`, return the index.
 
-![Algorithms/Attachments/Element found](linear-search-found.webp)
+![Element found](Attachments/linear-search-found.webp)
 3.  Else, return `not found`.
 
 ```Python
@@ -36,11 +36,11 @@ def linearSearch(array, n, x):
 
 ## How Binary Search Works?
 
-![Algorithms/Attachments/Initial array](binary-search-initial-array.webp)
-![Setting pointers](binary-search-set-pointers.webp)
-![Algorithms/Attachments/Finding mid element](binary-search-mid.webp)
-![Algorithms/Attachments/Mid element](binary-search-find-mid.webp)
-![Algorithms/Attachments/Found](binary-search-mid-again.webp)
+![Initial array](Attachments/binary-search-initial-array.webp)
+![Setting pointers](Attachments/binary-search-set-pointers.webp)
+![Finding mid element](Attachments/binary-search-mid.webp)
+![Mid element](Attachments/binary-search-find-mid.webp)
+![Found](Attachments/binary-search-mid-again.webp)
 
 ```Python
 # Binary Search in python

Algorithms/Sorting.md

@@ -64,7 +64,7 @@ def insertionSort(array):
 
 # Merge Sort
 
-![Algorithms/Attachments/Merge Sort example](merge-sort-example_0.png)
+![Merge Sort example](Attachments/merge-sort-example_0.png)
 
 ```Python
 # MergeSort in Python
@@ -186,7 +186,7 @@ def quickSort(array, low, high):
 
 # Heap Sort
 
-![Algorithms/Attachments/Max Heap and Min Heap](max-heap-min-heap.png)
+![Max Heap and Min Heap](Attachments/max-heap-min-heap.png)
 
 ```Python
 # Heap Sort in python

Algorithms/Two Pointers.md

@@ -29,15 +29,15 @@ def hasCycle(head: Optional[Node]) -> bool:
 
 To help illustrate this algorithm, I'll use some very relevant clipart. We'll start with the linked list. The `tortoise` begins at the `head`, while the `hare` begins at `head.next`.
 
-![Algorithms/Attachments/Example 0](tortoise-and-hare-example_0.png)
+![Example 0](Attachments/tortoise-and-hare-example_0.png)
 
 Since `hare` and `hare.next` are both not `null`, we'll enter the while loop. `tortoise` and `hare` are not equal to each other, so we will move them both over. `tortoise` gets moved over one spot, and `hare` gets moved over two spots.
 
-![Algorithms/Attachments/Example 0](tortoise-and-hare-example_1.png)
+![Example 0](Attachments/tortoise-and-hare-example_1.png)
 
 The while loop is still true. Again, `tortoise` and `hare` are not equal to each other. We'll move the `tortoise` over one, and the `hare` over two nodes.
 
-![Algorithms/Attachments/Example 0](tortoise-and-hare-example_2.png)
+![Example 0](Attachments/tortoise-and-hare-example_2.png)
 
 The while loop is still true, but this time, `tortoise` and `hare` are equal to each other. This means that a cycle was found, so we will return true.
 

Data Structures/Hash Table.md

@@ -5,7 +5,7 @@ In chaining, if a hash function produces the same index for multiple elements, t
 
 If `j` is the slot for multiple elements, it contains a pointer to the head of the list of elements. If no element is present, `j` contains `NIL`.
 
-![Data\ Strutures/Attachments/Collision Resolution using chaining](Hash-3_1.webp)
+![Collision Resolution using chaining](Attachments/Hash-3_1.webp)
 
 
 ## 2. Open Addressing