问题2017.等边三角形的一侧

由谭雅莫顿

像(20)

解决后

{ “关系”：[{ “关系”： “http://schemas.mathworks.com/matlab/code/2013/relationships/document”， “targetMode”： “”， “relationshipId”： “RID1”，“目标“：” /matlab/document.xml “}，{” 关系 “：” http://schemas.mathworks.com/matlab/code/2013/relationships/output”， “targetMode”： “”， “relationshipId”：“RID2”， “目标”： “/ MATLAB /的Output.xml”}]， “份”：[{ “partUri”： “/ MATLAB / document.xml中”， “关系”：[{ “关系”：“HTTP：//schemas.mathworks.com/matlab/code/2013/relationships/image”， “targetMode”： “”， “relationshipId”： “RID1”， “目标”： “/media/image1.JPEG”}]，“的contentType”： “应用/ vnd.mathworks.matlab.code.document + xml” 的， “内容”： “<XML版本= \” 1.0 \”编码= \ “UTF-8 \”？> \ n <W：文档的xmlns：W = \ “HTTP：//schemas.openxmlformats.org/wordprocessingml/2006/main \”> <W：体> <W：p> <W：PPR> <瓦特：PSTYLE瓦特：VAL = \“文本\”/> </ W：PPR> <W：R> <W：T>如果一个等边三角形具有区域A，那么什么是其每一侧的长度，X </瓦特：T> </ W：R> </ w的：p> <W：p> <W：PPR> <瓦特：PSTYLE瓦特：VAL = \ “文本\”/> </ W：PPR> <瓦特：customXml瓦特：电子字元素= \ “图像\”> <W：customXmlPr> <瓦特：ATTR瓦特：名称= \ “高度\” W：VAL = \ “ -  1 \”/> <瓦特：ATTR瓦特：名称= \“宽度\“W：VAL = \”  -  1 \ “/> <瓦特：ATTR瓦特：名称= \” relationshipId \” W：VAL = \ “RID1 \”/> </ W：customXmlPr> </ W：customXml> </ W：p> <W：p> <W：PPR> <瓦特：PSTYLE瓦特：VAL = \ “文本\”/> </ W：PPR> <W：R> <W：吨>图像的礼貌</ W：T> </ W：R> <W：R> <W：T> </ W：T> </ W：R> <W：超链接瓦特：docLocation = \“HTTP：//upload.wikimedia。org/wikipedia/commons/e/e0/Equilateral-triangle.svg\"><w:r><w:t>Wikipedia</w:t></w:r></w:hyperlink><w:r><w:t>.</w:t></w:r></w:p></w:body></w:document>"},{"partUri":"/matlab/output.xml","contentType":"text/xml","content":"<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\" ?><embeddedOutputs><metaData><evaluationState>manual</evaluationState><layoutState>code</layoutState><outputStatus>ready</outputStatus></metaData><outputArray type=\"array\"/><regionArray type=\"array\"/></embeddedOutputs>"},{"partUri":"/media/image1.JPEG","contentType":"image/JPEG","content":"data:image/JPEG;base64,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"}]}

解决

解决方案统计信息

5814解万博尤文图斯决方案
解决3117

去年解决方案于2021年6月14日提交

最后200解决方案万博尤文图斯

问题的评论

3评论

3评论

加勒特Pesi2018年3月24日

如果你先画一幅画肯定会有帮助。

KINGEN LOPEZ.20月16日10月16日

不错的

亚当•特纳2020年11月25日

第一次和第三次测试是不正确的

解决方案评论

解决方案5674940

1条评论

1条评论

约翰·珀金斯2021年5月4日

好问题

解决方案5086367

1条评论

1条评论

Yashender沙玛2021年3月17日

超级简单

解决方案395861

1条评论

1条评论

李立2018年2月12日

regexp技巧

最近的问题解决者3117

提出问题

问题标签

社区寻宝

在MATLAB中心找到宝藏，并发现社区如何可以帮助你!

开始狩猎!