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Translate all code to English (#1836)

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* Review the EN heading format.

* Fix pythontutor headings.

* Fix pythontutor headings.

* bug fixes

* Fix headings in **/summary.md

* Revisit the CN-to-EN translation for Python code using Claude-4.5

* Revisit the CN-to-EN translation for Java code using Claude-4.5

* Revisit the CN-to-EN translation for Cpp code using Claude-4.5.

* Fix the dictionary.

* Fix cpp code translation for the multipart strings.

* Translate Go code to English.

* Update workflows to test EN code.

* Add EN translation for C.

* Add EN translation for CSharp.

* Add EN translation for Swift.

* Trigger the CI check.

* Revert.

* Update en/hash_map.md

* Add the EN version of Dart code.

* Add the EN version of Kotlin code.

* Add missing code files.

* Add the EN version of JavaScript code.

* Add the EN version of TypeScript code.

* Fix the workflows.

* Add the EN version of Ruby code.

* Add the EN version of Rust code.

* Update the CI check for the English version  code.

* Update Python CI check.

* Fix cmakelists for en/C code.

* Fix Ruby comments
This commit is contained in:
Yudong Jin
2025-12-31 07:44:52 +08:00
committed by GitHub
parent 45e1295241
commit 2778a6f9c7
1284 changed files with 71557 additions and 3275 deletions
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en/docs/chapter_greedy/max_capacity_problem.md
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# Max capacity problem
# Max Capacity Problem
!!! question
@@ -20,7 +20,7 @@ $$
Let the array length be $n$, then the number of combinations of two partitions (total number of states) is $C_n^2 = \frac{n(n - 1)}{2}$. Most directly, **we can exhaustively enumerate all states** to find the maximum capacity, with time complexity $O(n^2)$.
### Greedy strategy determination
### Greedy Strategy Determination
This problem has a more efficient solution. As shown in the figure below, select a state $[i, j]$ where index $i < j$ and height $ht[i] < ht[j]$, meaning $i$ is the short partition and $j$ is the long partition.
@@ -72,7 +72,7 @@ The figure below shows the execution process of the greedy strategy.
=== "<9>"
![max_capacity_greedy_step9](max_capacity_problem.assets/max_capacity_greedy_step9.png)
### Code implementation
### Code Implementation
The code loops at most $n$ rounds, **therefore the time complexity is $O(n)$**.
@@ -82,7 +82,7 @@ Variables $i$, $j$, and $res$ use a constant amount of extra space, **therefore
[file]{max_capacity}-[class]{}-[func]{max_capacity}
```
### Correctness proof
### Correctness Proof
The reason greedy is faster than exhaustive enumeration is that each round of greedy selection "skips" some states.