translation: Update binary_search_insertion.md #1554
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| - The given array does not contain decimals, meaning we do not need to worry about how to handle equal situations. | ||
| - Since this method introduces decimals, the variable `target` in the function needs to be changed to a floating point type (no change needed in Python). | ||
| - Since the given array does not contain decimals, this means we do not need to worry about handling equal cases. | ||
| - Because this method introduces decimals, the variable `target` in the function needs to be changed to a floating point type (no change needed in Python). |
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Since has a slightly more formal tone than Because, Consider choosing one for consistency throughout the document."
| @@ -21,27 +21,27 @@ In these cases, simply return $-1$. The code is as follows: | |||
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| ## Find the right boundary | |||
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| So how do we find the rightmost `target`? The most straightforward way is to modify the code, replacing the pointer contraction operation in the case of `nums[m] == target`. The code is omitted here, but interested readers can implement it on their own. | |||
| How do we find the rightmost occurrence of `target`? The most straightforward way is to modify the traditional binary search logic by changing how we adjust the search boundaries in the case of `nums[m] == target`. The code is omitted here. If you are interested, try to implement the code on your own. | |||
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"the traditional binary search logic --> the traditional binary search algorithm " may be better
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The logic of the code changes under the condition 'nums[m] == target', so I chose "logic" rather than "algorithm. " It's more precise while the other word is more general.
| @@ -21,27 +21,27 @@ In these cases, simply return $-1$. The code is as follows: | |||
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| ## Find the right boundary | |||
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| So how do we find the rightmost `target`? The most straightforward way is to modify the code, replacing the pointer contraction operation in the case of `nums[m] == target`. The code is omitted here, but interested readers can implement it on their own. | |||
| How do we find the rightmost occurrence of `target`? The most straightforward way is to modify the traditional binary search logic by changing how we adjust the search boundaries in the case of `nums[m] == target`. The code is omitted here. If you are interested, try to implement the code on your own. | |||
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You can directly use "try implementing the code on your own"
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Just respect the author's original text.
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OK, just use your statement
| 1. Perform a binary search, get an arbitrary index of `target`, denoted as $k$. | ||
| 2. Start from index $k$, and perform a linear search to the left until the leftmost `target` is found and return. | ||
| 1. Perform a binary search to find any `target`'s index, say $k$. | ||
| 2. Starting from index $k$, perform a linear search to the left until the leftmost `target` is found and return. |
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The tenses of the two paragraphs are inconsistent. Perform and Starting
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"Starting from index
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| The requirement to insert `target` to the left of equal elements means that the newly inserted `target` replaces the original `target` position. Thus, **when the array contains `target`, the insertion point index is the index of that `target`**. | ||
| The requirement to insert `target` to the left of equal elements means that the newly inserted `target` will replace the original `target` position. In other words, **when the array contains `target`, the insertion point is indeed the index of that `target`**. |
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"In other words" may be some colloquialisms
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The phrase 'in other words' is common in many documents.
Examples:
https://react.dev/learn/updating-objects-in-state#treat-state-as-read-only
https://python.langchain.com/docs/versions/release_policy/#what-is-a-api-stability
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