Component Translated Unfinished Unfinished words Unfinished characters Untranslated Checks Suggestions Comments
pgRouting CC-BY-SA-4.0 47% 16,446 122,229 912,109 15,296 181 16,897 0
Glossary index CC-BY-SA-4.0 0 0 0 0 0 0 0

Overview

Project website docs.pgrouting.org/dev/en/index.html
Instructions for translators

TBD
Project maintainers User avatar josekrv User avatar cvvergara User avatar sanak
Translation license CC-BY-SA-4.0 pgRouting index
yesterday

String statistics

Strings percent Hosted strings Words percent Hosted words Characters percent Hosted characters
Total 31,386 229,230 1,702,122
Source 5,231 38,205 283,687
Translated 47% 14,940 46% 107,001 46% 790,013
Needs editing 3% 1,150 2% 5,767 3% 56,114
Read-only 16% 5,231 16% 38,205 16% 283,687
Failing checks 1% 181 1% 1,069 1% 7,529
Strings with suggestions 53% 16,897 54% 125,527 55% 939,316
Untranslated strings 48% 15,296 50% 116,462 50% 855,995
Last 12 months Previous

Activity in last 12 months

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Quick numbers

229 k
Hosted words
31,386
Hosted strings
47%
Translated
3
Contributors
and previous 30 days

Trends of last 30 days

+2%
Hosted words
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User avatar mt:deepl

Suggestion added

  1. pgRouting
  2. pgRouting
  3. Chinese (Simplified)
It is well-known that the shortest paths between a single source and all other vertices can be found using Breadth First Search in :math:`O(|E|)` in an unweighted graph, i.e. the distance is the minimal number of edges that you need to traverse from the source to another vertex. We can interpret such a graph also as a weighted graph, where every edge has the weight :math:`1`. If not all edges in graph have the same weight, that we need a more general algorithm, like Dijkstra's Algorithm which runs in :math:`O(|E|log|V|)` time.
众所周知，在无权重图中，使用广度优先搜索（Breadth First Search）可以在 :math:`O(|E|)` 内找到单个源点与所有其他顶点之间的最短路径，也就是说，距离是指从源点到另一个顶点所需的最少边数。我们也可以把这样的图解释为加权图，其中每条边的权重为 :math:`1`。如果图中不是并非所有边的权重都相同，我们就需要一种更通用的算法，比如 Dijkstra 算法，它的运行时间为 :math:`O(|E|log|V||)` 的 Dijkstra 算法。
yesterday
User avatar mt:deepl

Suggestion added

  1. pgRouting
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  3. Chinese (Simplified)
:doc:`pgr_binaryBreadthFirstSearch` [3]_
:doc:`pgr_binaryBreadthFirstSearch` [3]_
yesterday
User avatar mt:deepl

Suggestion added

  1. pgRouting
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  3. Chinese (Simplified)
`#2908 <https://github.com/pgRouting/pgrouting/issues/2908>`__ pgr_binaryBreadthFirstSearch
`#2683908 <https://github.com/pgRouting/pgrouting/issues/2683908>`__: pgr_trspbinaryBreadthFirstSearch
yesterday
User avatar mt:deepl

Suggestion added

  1. pgRouting
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  3. Korean
It is well-known that the shortest paths between a single source and all other vertices can be found using Breadth First Search in :math:`O(|E|)` in an unweighted graph, i.e. the distance is the minimal number of edges that you need to traverse from the source to another vertex. We can interpret such a graph also as a weighted graph, where every edge has the weight :math:`1`. If not all edges in graph have the same weight, that we need a more general algorithm, like Dijkstra's Algorithm which runs in :math:`O(|E|log|V|)` time.
단일 소스와 다른 모든 정점 사이의 최단 경로는 가중치가 없는 그래프에서 :math:`O(|E|)`의 폭 우선 검색을 사용하여 찾을 수 있다는 것은 잘 알려져 있습니다. 즉, 거리는 소스에서 다른 정점까지 이동하는 데 필요한 최소 에지 수입니다. 이러한 그래프를 가중 그래프로도 해석할 수 있는데, 여기서 모든 에지는 가중치 :math:`1`을 갖습니다. 그래프의 모든 에지가 동일한 가중치를 가지지 않는다면 :math:`O(|E|log|V|)` 시간 내에 실행되는 Dijkstra의 알고리즘과 같은 보다 일반적인 알고리즘이 필요합니다.
yesterday
User avatar mt:deepl

Suggestion added

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  3. Korean
:doc:`pgr_binaryBreadthFirstSearch` [3]_
:doc:`pgr_dijkstraNear`binaryBreadthFirstSearch` [3]_
yesterday
User avatar mt:deepl

Suggestion added

  1. pgRouting
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  3. Korean
`#2908 <https://github.com/pgRouting/pgrouting/issues/2908>`__ pgr_binaryBreadthFirstSearch
`#2908 <https://github.com/pgRouting/pgrouting/issues/2908>`__ pgr_binaryBreadthFirstSearch
yesterday
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Changes pushed

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Changes pushed yesterday
User avatar mt:deepl

Suggestion added

  1. pgRouting
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  3. Japanese
It is well-known that the shortest paths between a single source and all other vertices can be found using Breadth First Search in :math:`O(|E|)` in an unweighted graph, i.e. the distance is the minimal number of edges that you need to traverse from the source to another vertex. We can interpret such a graph also as a weighted graph, where every edge has the weight :math:`1`. If not all edges in graph have the same weight, that we need a more general algorithm, like Dijkstra's Algorithm which runs in :math:`O(|E|log|V|)` time.
すなわち、距離とは、ソースから別の頂点まで辿るのに必要な辺の最小数である。このようなグラフは，すべての辺が :math:`1` の重みを持つ重み付きグラフとしても解釈できる．グラフ内のすべての辺が同じ重みを持つわけではない場合、ダイクストラのアルゴリズムのように :math:`O(|E|log|V||)` 時間で実行されるような、より一般的なアルゴリズムが必要になる。
yesterday
User avatar mt:deepl

Suggestion added

  1. pgRouting
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  3. Japanese
:doc:`pgr_binaryBreadthFirstSearch` [3]_
:doc:`pgr_kruskalBFS`binaryBreadthFirstSearch` [3]_.
yesterday
User avatar mt:deepl

Suggestion added

  1. pgRouting
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  3. Japanese
`#2908 <https://github.com/pgRouting/pgrouting/issues/2908>`__ pgr_binaryBreadthFirstSearch
`#2908 <https://github.com/pgRouting/pgrouting/issues/2908>`__ pgr_binaryBreadthFirstSearch
yesterday
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