Bug fixes and improvements (#1205)

* Add Ruby code blocks to documents

* Remove Ruby code from en/docs

* Remove "center-table" class in index.md

* Add "data-toc-label" to handle the latex heading during the build process

* Use normal JD link instead.

* Bug fixes

en/docs/chapter_computational_complexity/space_complexity.md

@@ -736,7 +736,7 @@ $$
 
 ![Common Types of Space Complexity](space_complexity.assets/space_complexity_common_types.png)
 
-### Constant Order $O(1)$ {data-toc-label="Constant Order"}
+### Constant Order $O(1)$
 
 Constant order is common in constants, variables, objects that are independent of the size of input data $n$.
 
@@ -746,7 +746,7 @@ Note that memory occupied by initializing variables or calling functions in a lo
 [file]{space_complexity}-[class]{}-[func]{constant}
 ```
 
-### Linear Order $O(n)$ {data-toc-label="Linear Order"}
+### Linear Order $O(n)$
 
 Linear order is common in arrays, linked lists, stacks, queues, etc., where the number of elements is proportional to $n$:
 
@@ -762,7 +762,7 @@ As shown below, this function's recursive depth is $n$, meaning there are $n$ in
 
 ![Recursive Function Generating Linear Order Space Complexity](space_complexity.assets/space_complexity_recursive_linear.png)
 
-### Quadratic Order $O(n^2)$ {data-toc-label="Quadratic Order"}
+### Quadratic Order $O(n^2)$
 
 Quadratic order is common in matrices and graphs, where the number of elements is quadratic to $n$:
 
@@ -778,7 +778,7 @@ As shown below, the recursive depth of this function is $n$, and in each recursi
 
 ![Recursive Function Generating Quadratic Order Space Complexity](space_complexity.assets/space_complexity_recursive_quadratic.png)
 
-### Exponential Order $O(2^n)$ {data-toc-label="Exponential Order"}
+### Exponential Order $O(2^n)$
 
 Exponential order is common in binary trees. Observe the below image, a "full binary tree" with $n$ levels has $2^n - 1$ nodes, occupying $O(2^n)$ space:
 
@@ -788,7 +788,7 @@ Exponential order is common in binary trees. Observe the below image, a "full bi
 
 ![Full Binary Tree Generating Exponential Order Space Complexity](space_complexity.assets/space_complexity_exponential.png)
 
-### Logarithmic Order $O(\log n)$ {data-toc-label="Logarithmic Order"}
+### Logarithmic Order $O(\log n)$
 
 Logarithmic order is common in divide-and-conquer algorithms. For example, in merge sort, an array of length $n$ is recursively divided in half each round, forming a recursion tree of height $\log n$, using $O(\log n)$ stack frame space.