{"group":{"group":{"id":54228,"name":"Tough Stuff","lockable":false,"created_at":"2022-10-12T11:13:51.000Z","updated_at":"2025-12-14T01:33:56.000Z","description":"Solve Cody problems that I thought were challenging, but not outright unsolvable (without a background in mathematics)! I managed to complete all of these eventually. Can you do it, too?\n(Coconut photograph by horiavarlan on Flickr, who kindly made it available under the CC-BY 2.0 license.)","is_default":false,"created_by":332395,"badge_id":62,"featured":false,"trending":false,"solution_count_in_trending_period":122,"trending_last_calculated":"2025-12-14T00:00:00.000Z","image_id":4813,"published":true,"community_created":true,"status_id":2,"is_default_group_for_player":false,"deleted_by":null,"deleted_at":null,"restored_by":null,"restored_at":null,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSolve Cody problems that I thought were challenging, but not outright unsolvable (without a background in mathematics)! I managed to complete all of these eventually. Can you do it, too?\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e(\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.flickr.com/photos/horiavarlan/4268223207\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eCoconut photograph by horiavarlan on Flickr\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e, who kindly made it available under the \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://creativecommons.org/licenses/by/2.0/\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eCC-BY 2.0 license\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 114px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 289.5px 57px; transform-origin: 289.5px 57px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 266.5px 31.5px; text-align: left; transform-origin: 266.5px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eSolve Cody problems that I thought were challenging, but not outright unsolvable (without a background in mathematics)! I managed to complete all of these eventually. Can you do it, too?\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 266.5px 21px; text-align: left; transform-origin: 266.5px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e(\u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://www.flickr.com/photos/horiavarlan/4268223207\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eCoconut photograph by horiavarlan on Flickr\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e, who kindly made it available under the \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://creativecommons.org/licenses/by/2.0/\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eCC-BY 2.0 license\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e.)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","published_at":"2022-10-12T12:03:13.000Z"},"current_player":null},"problems":[{"id":242,"title":"Make a function that returns its own character count","description":"Write a function that returns a 128 element vector with an accurate inventory of the ASCII characters in its own function file. The test suite uses textscan to verify that your function returns the exact same census.\r\n file = textscan(fid,'%c','CommentStyle','%','Whitespace','')\r\n filetext = file{1};\r\n texthist = histc(filetext,1:128);\r\nNewlines are suppressed by this approach, so you may assume the counts for ASCII 10 and 13 are zero.\r\nSpecial Note: The characters associated with ASCII values 33-41 are not allowed in your function. For clarity, these are\r\n 33 !\r\n 34 \"\r\n 35 #\r\n 36 $\r\n 37 %\r\n 38 \u0026\r\n 39 '\r\n 40 (\r\n 41 )","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 368.2px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 184.1px; transform-origin: 407px 184.1px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 375.5px 8px; transform-origin: 375.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function that returns a 128 element vector with an accurate inventory of the ASCII characters in its own function file. The test suite uses textscan to verify that your function returns the exact same census.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 61.3px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 30.65px; transform-origin: 404px 30.65px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 244px 8.5px; tab-size: 4; transform-origin: 244px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 84px 8.5px; transform-origin: 84px 8.5px; \"\u003e file = textscan(fid,\u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 16px 8.5px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 16px 8.5px; \"\u003e'%c'\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 4px 8.5px; transform-origin: 4px 8.5px; \"\u003e,\u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 56px 8.5px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 56px 8.5px; \"\u003e'CommentStyle'\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 4px 8.5px; transform-origin: 4px 8.5px; \"\u003e,\u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 12px 8.5px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 12px 8.5px; \"\u003e'%'\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 4px 8.5px; transform-origin: 4px 8.5px; \"\u003e,\u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 48px 8.5px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 48px 8.5px; \"\u003e'Whitespace'\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 4px 8.5px; transform-origin: 4px 8.5px; \"\u003e,\u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 8px 8.5px; text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 8px 8.5px; \"\u003e''\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 4px 8.5px; transform-origin: 4px 8.5px; \"\u003e)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 80px 8.5px; tab-size: 4; transform-origin: 80px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e filetext = file{1};\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 136px 8.5px; tab-size: 4; transform-origin: 136px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e texthist = histc(filetext,1:128);\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 328.5px 8px; transform-origin: 328.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNewlines are suppressed by this approach, so you may assume the counts for ASCII 10 and 13 are zero.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 46px 8px; transform-origin: 46px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eSpecial Note:\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 331.5px 8px; transform-origin: 331.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e The characters associated with ASCII values 33-41 are not allowed in your function. For clarity, these are\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 183.9px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 91.95px; transform-origin: 404px 91.95px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 20px 8.5px; tab-size: 4; transform-origin: 20px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 16px 8.5px; transform-origin: 16px 8.5px; \"\u003e 33 \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(178, 140, 0); border-block-start-color: rgb(178, 140, 0); border-bottom-color: rgb(178, 140, 0); border-inline-end-color: rgb(178, 140, 0); border-inline-start-color: rgb(178, 140, 0); border-left-color: rgb(178, 140, 0); border-right-color: rgb(178, 140, 0); border-top-color: rgb(178, 140, 0); caret-color: rgb(178, 140, 0); color: rgb(178, 140, 0); column-rule-color: rgb(178, 140, 0); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(178, 140, 0); perspective-origin: 4px 8.5px; text-decoration: none; text-decoration-color: rgb(178, 140, 0); text-emphasis-color: rgb(178, 140, 0); transform-origin: 4px 8.5px; \"\u003e!\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 20px 8.5px; tab-size: 4; transform-origin: 20px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 16px 8.5px; transform-origin: 16px 8.5px; \"\u003e 34 \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(196, 0, 0); border-block-start-color: rgb(196, 0, 0); border-bottom-color: rgb(196, 0, 0); border-inline-end-color: rgb(196, 0, 0); border-inline-start-color: rgb(196, 0, 0); border-left-color: rgb(196, 0, 0); border-right-color: rgb(196, 0, 0); border-top-color: rgb(196, 0, 0); caret-color: rgb(196, 0, 0); color: rgb(196, 0, 0); column-rule-color: rgb(196, 0, 0); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(196, 0, 0); perspective-origin: 4px 8.5px; text-decoration: none; text-decoration-color: rgb(196, 0, 0); text-emphasis-color: rgb(196, 0, 0); transform-origin: 4px 8.5px; \"\u003e\"\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 20px 8.5px; tab-size: 4; transform-origin: 20px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 16px 8.5px; transform-origin: 16px 8.5px; \"\u003e 35 \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(255, 0, 0); border-block-start-color: rgb(255, 0, 0); border-bottom-color: rgb(255, 0, 0); border-inline-end-color: rgb(255, 0, 0); border-inline-start-color: rgb(255, 0, 0); border-left-color: rgb(255, 0, 0); border-right-color: rgb(255, 0, 0); border-top-color: rgb(255, 0, 0); caret-color: rgb(255, 0, 0); color: rgb(255, 0, 0); column-rule-color: rgb(255, 0, 0); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(255, 0, 0); perspective-origin: 4px 8.5px; text-decoration: none; text-decoration-color: rgb(255, 0, 0); text-emphasis-color: rgb(255, 0, 0); transform-origin: 4px 8.5px; \"\u003e#\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 20px 8.5px; tab-size: 4; transform-origin: 20px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 16px 8.5px; transform-origin: 16px 8.5px; \"\u003e 36 \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(255, 0, 0); border-block-start-color: rgb(255, 0, 0); border-bottom-color: rgb(255, 0, 0); border-inline-end-color: rgb(255, 0, 0); border-inline-start-color: rgb(255, 0, 0); border-left-color: rgb(255, 0, 0); border-right-color: rgb(255, 0, 0); border-top-color: rgb(255, 0, 0); caret-color: rgb(255, 0, 0); color: rgb(255, 0, 0); column-rule-color: rgb(255, 0, 0); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(255, 0, 0); perspective-origin: 4px 8.5px; text-decoration: none; text-decoration-color: rgb(255, 0, 0); text-emphasis-color: rgb(255, 0, 0); transform-origin: 4px 8.5px; \"\u003e$\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 20px 8.5px; tab-size: 4; transform-origin: 20px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 16px 8.5px; transform-origin: 16px 8.5px; \"\u003e 37 \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(2, 128, 9); border-block-start-color: rgb(2, 128, 9); border-bottom-color: rgb(2, 128, 9); border-inline-end-color: rgb(2, 128, 9); border-inline-start-color: rgb(2, 128, 9); border-left-color: rgb(2, 128, 9); border-right-color: rgb(2, 128, 9); border-top-color: rgb(2, 128, 9); caret-color: rgb(2, 128, 9); color: rgb(2, 128, 9); column-rule-color: rgb(2, 128, 9); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(2, 128, 9); perspective-origin: 4px 8.5px; text-decoration: none; text-decoration-color: rgb(2, 128, 9); text-emphasis-color: rgb(2, 128, 9); transform-origin: 4px 8.5px; \"\u003e%\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 20px 8.5px; tab-size: 4; transform-origin: 20px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e 38 \u0026amp;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 20px 8.5px; tab-size: 4; transform-origin: 20px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 16px 8.5px; transform-origin: 16px 8.5px; \"\u003e 39 \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(196, 0, 0); border-block-start-color: rgb(196, 0, 0); border-bottom-color: rgb(196, 0, 0); border-inline-end-color: rgb(196, 0, 0); border-inline-start-color: rgb(196, 0, 0); border-left-color: rgb(196, 0, 0); border-right-color: rgb(196, 0, 0); border-top-color: rgb(196, 0, 0); caret-color: rgb(196, 0, 0); color: rgb(196, 0, 0); column-rule-color: rgb(196, 0, 0); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(196, 0, 0); perspective-origin: 4px 8.5px; text-decoration: none; text-decoration-color: rgb(196, 0, 0); text-emphasis-color: rgb(196, 0, 0); transform-origin: 4px 8.5px; \"\u003e'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 20px 8.5px; tab-size: 4; transform-origin: 20px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e 40 (\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 20px 8.5px; tab-size: 4; transform-origin: 20px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e 41 )\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function x = omphaloskeptic\r\n  x = 0;\r\nend","test_suite":"%%\r\nfname = 'omphaloskeptic.m';\r\nfid = fopen(fname);\r\nfile = textscan(fid,'%c', ...\r\n  'CommentStyle','%', ...\r\n  'Whitespace','');\r\nfclose(fid);\r\n\r\nha = histc(file{1},1:128);\r\nhp = omphaloskeptic;\r\n\r\nassert(~any(ismember(33:41,find(ha))),'Used an illegal character');\r\nassert(isequal(ha,hp),'Actual characters did not match prediction');","published":true,"deleted":false,"likes_count":4,"comments_count":1,"created_by":7,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":34,"test_suite_updated_at":"2021-09-07T15:14:16.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-02-02T22:19:52.000Z","updated_at":"2026-03-21T04:10:51.000Z","published_at":"2012-02-03T15:28:39.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function that returns a 128 element vector with an accurate inventory of the ASCII characters in its own function file. The test suite uses textscan to verify that your function returns the exact same census.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ file = textscan(fid,'%c','CommentStyle','%','Whitespace','')\\n filetext = file{1};\\n texthist = histc(filetext,1:128);]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNewlines are suppressed by this approach, so you may assume the counts for ASCII 10 and 13 are zero.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eSpecial Note:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e The characters associated with ASCII values 33-41 are not allowed in your function. For clarity, these are\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ 33 !\\n 34 \\\"\\n 35 #\\n 36 $\\n 37 %\\n 38 \u0026\\n 39 '\\n 40 (\\n 41 )]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":196,"title":"love is an n-letter word","description":"Given a list of *N words*, return the *N-letter word* (choosing one letter from each word) with the property of having the least distance between each pair of two consecutive letters (if there are multiple optimal solutions return any one of them).\r\n\r\nExample: s1 = {'abcd','bcde','cdef','defg'}; should return s2 = 'dddd'; (with total letter-distance = 0)\r\n\r\nExample: s1={'aldfejk','czoa','vwy','abcde'}; should return s2='love'; (with total letter-distance = 27: _|'l'-'o'|_=3 + _|'o'-'v'|_=7 + _|'v'-'e'|_=17 ; compare for example to the possible word 'aave' which has a total letter-distance of 38)\r\n\r\n\r\n\r\n","description_html":"\u003cp\u003eGiven a list of \u003cb\u003eN words\u003c/b\u003e, return the \u003cb\u003eN-letter word\u003c/b\u003e (choosing one letter from each word) with the property of having the least distance between each pair of two consecutive letters (if there are multiple optimal solutions return any one of them).\u003c/p\u003e\u003cp\u003eExample: s1 = {'abcd','bcde','cdef','defg'}; should return s2 = 'dddd'; (with total letter-distance = 0)\u003c/p\u003e\u003cp\u003eExample: s1={'aldfejk','czoa','vwy','abcde'}; should return s2='love'; (with total letter-distance = 27: \u003ci\u003e\u003ctt\u003e'l'-'o'\u003c/tt\u003e\u003c/i\u003e=3 + \u003ci\u003e\u003ctt\u003e'o'-'v'\u003c/tt\u003e\u003c/i\u003e=7 + \u003ci\u003e\u003ctt\u003e'v'-'e'\u003c/tt\u003e\u003c/i\u003e=17 ; compare for example to the possible word 'aave' which has a total letter-distance of 38)\u003c/p\u003e","function_template":"function s2 = gobbledigook(s1)\r\n  s2 = '';\r\nend","test_suite":"%%\r\ns1 = {'abcd','bcde','cdef','defg'}; \r\nassert(isequal(gobbledigook(s1),'dddd'))\r\ns2_correct = 'dddd';\r\n%%\r\ns1 = {'aldfejk','czoa','vwy','abcde'}; \r\nassert(isequal(gobbledigook(s1),'love'))\r\ns2_correct = 'love';\r\n%%\r\ns1 = {'some','help','check','viterbi','algorithm'}; \r\nassert(isequal(gobbledigook(s1),'eeeeg'))\r\ns2_correct = 'eeeeg';\r\n%%\r\ns1 = {'ldjfac','deamv','fka','idlw','pqmfjavs'}; \r\nassert(isequal(gobbledigook(s1),'lmklm')|isequal(gobbledigook(s1),'aaadf'))\r\ns2_correct = 'lmklm';\r\ns2_correct = 'aaadf';\r\n%% \r\n% avoids look-up table hack\r\ns1 = cellfun(@(x)char('a'-1+randi(26,1,5)),cell(1,7),'uniformoutput',false);\r\nassert(all(any(bsxfun(@eq,gobbledigook(s1),cell2mat(cellfun(@(x)x',s1,'uniformoutput',false)))))\u0026all(sum(abs(diff(double(gobbledigook(s1)))))\u003c=sum(abs(diff(double(cell2mat(cellfun(@(x)x(randi(numel(x),1,1000))',s1,'uniformoutput',false))),1,2)),2)));","published":true,"deleted":false,"likes_count":3,"comments_count":5,"created_by":43,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":55,"test_suite_updated_at":"2012-03-08T02:36:04.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-01-31T08:36:36.000Z","updated_at":"2026-03-20T18:33:59.000Z","published_at":"2012-03-08T03:14:35.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a list of\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eN words\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, return the\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eN-letter word\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e (choosing one letter from each word) with the property of having the least distance between each pair of two consecutive letters (if there are multiple optimal solutions return any one of them).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExample: s1 = {'abcd','bcde','cdef','defg'}; should return s2 = 'dddd'; (with total letter-distance = 0)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExample: s1={'aldfejk','czoa','vwy','abcde'}; should return s2='love'; (with total letter-distance = 27:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e'l'-'o'\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e=3 +\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e'o'-'v'\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e=7 +\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e'v'-'e'\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e=17 ; compare for example to the possible word 'aave' which has a total letter-distance of 38)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":154,"title":"Reverse Boggle","description":"Description\r\nIn the classic Parker Brothers game Boggle, players find words from a 4x4 game board of letters. This exercise is to make sure that a particular solution to a boggle board is actually available on the board.\r\nThe program does not need to check to make sure if the input word is a valid english word. Furthermore, all inputs will be in all uppercase, so the user does not need to check/convert for case differences. The game board will always be 4x4.\r\nNote: This does not perfectly align with the rules of Boggle. Specifically, all solutions in the original game must be 3 or more letters, which this problem is not asking to account for, and the atomic \"Qu\" is present (which I have avoided in the test suite).\r\nHappy MATLABing!\r\nExample\r\n    x = ['TIPE'\r\n         'YECV'\r\n         'LSRA'\r\n         'WOTU'];\r\n    y = 'RACIEST';\r\n    TF = true;","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 387.6px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 193.8px; transform-origin: 407px 193.8px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 40.5px 8px; transform-origin: 40.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eDescription\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 112px 8px; transform-origin: 112px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIn the classic Parker Brothers game\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"/#null\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eBoggle\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 247px 8px; transform-origin: 247px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, players find words from a 4x4 game board of letters. This exercise is to make sure that a particular solution to a boggle board is actually available on the board.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 41px 8px; transform-origin: 41px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe program\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 27.5px 8px; transform-origin: 27.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003edoes not\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 311px 8px; transform-origin: 311px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e need to check to make sure if the input word is a valid english word. Furthermore, all inputs will be in all uppercase, so the user does not need to check/convert for case differences. The game board will always be 4x4.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 370px 8px; transform-origin: 370px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eNote: This does not perfectly align with the rules of Boggle. Specifically, all solutions in the original game must be 3 or more letters, which this problem is not asking to account for, and the atomic \"Qu\" is present (which I have avoided in the test suite).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 61px 8px; transform-origin: 61px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eHappy MATLABing!\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 29.5px 8px; transform-origin: 29.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eExample\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 122.6px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 61.3px; transform-origin: 404px 61.3px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 60px 8.5px; tab-size: 4; transform-origin: 60px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 36px 8.5px; transform-origin: 36px 8.5px; \"\u003e    x = [\u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 24px 8.5px; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 24px 8.5px; \"\u003e'TIPE'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 60px 8.5px; tab-size: 4; transform-origin: 60px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 36px 8.5px; transform-origin: 36px 8.5px; \"\u003e         \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 24px 8.5px; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 24px 8.5px; \"\u003e'YECV'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 60px 8.5px; tab-size: 4; transform-origin: 60px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 36px 8.5px; transform-origin: 36px 8.5px; \"\u003e         \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 24px 8.5px; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 24px 8.5px; \"\u003e'LSRA'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 68px 8.5px; tab-size: 4; transform-origin: 68px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 36px 8.5px; transform-origin: 36px 8.5px; \"\u003e         \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 24px 8.5px; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 24px 8.5px; \"\u003e'WOTU'\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 8px 8.5px; transform-origin: 8px 8.5px; \"\u003e];\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 72px 8.5px; tab-size: 4; transform-origin: 72px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 32px 8.5px; transform-origin: 32px 8.5px; \"\u003e    y = \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 36px 8.5px; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 36px 8.5px; \"\u003e'RACIEST'\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 4px 8.5px; transform-origin: 4px 8.5px; \"\u003e;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 56px 8.5px; tab-size: 4; transform-origin: 56px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    TF = true;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function tf = boggle_checker(x,y)\r\n  tf = true;\r\nend","test_suite":"%%\r\nx = ['TIPE'\r\n     'YECV'\r\n     'LSRA'\r\n     'WOTU'];\r\ny = 'RACIEST';\r\nassert(isequal(boggle_checker(x,y),true))\r\n\r\n%%\r\nx = ['TIPE'\r\n     'YECV'\r\n     'LSRA'\r\n     'WOTU'];\r\ny = 'RACIESTS';\r\nassert(isequal(boggle_checker(x,y),false))\r\n\r\n%%\r\nx = ['TIPE'\r\n     'YECV'\r\n     'LSRA'\r\n     'WOTU'];\r\ny = 'RACIESTW';\r\nassert(isequal(boggle_checker(x,y),false))\r\n\r\n%%\r\nx = ['TIPE'\r\n     'YECV'\r\n     'LSRA'\r\n     'WOTU'];\r\ny = 'AUTOLYTIC';\r\nassert(isequal(boggle_checker(x,y),true))\r\n\r\n%%\r\nx = ['TIPE'\r\n     'YECV'\r\n     'LSRA'\r\n     'WOTU'];\r\ny = 'RESTAR';\r\nassert(isequal(boggle_checker(x,y),false))\r\n\r\n%%\r\nx = ['OCEW'\r\n     'LRIR'\r\n     'GYSI'\r\n     'KREM'];\r\ny = 'SIRI';\r\nassert(isequal(boggle_checker(x,y),true))\r\n\r\n%%\r\nx = ['OCEW'\r\n     'LRIR'\r\n     'GYSI'\r\n     'KREM'];\r\ny = 'SIRIM';\r\nassert(isequal(boggle_checker(x,y),true))\r\n\r\n%%\r\nx = ['OCEW'\r\n     'LRIR'\r\n     'GYSI'\r\n     'KREM'];\r\ny = 'GLORY';\r\nassert(isequal(boggle_checker(x,y),true))\r\n\r\n%%\r\nx = ['OCEW'\r\n     'LRIR'\r\n     'GYSI'\r\n     'KREM'];\r\ny = 'ROME';\r\nassert(isequal(boggle_checker(x,y),false))","published":true,"deleted":false,"likes_count":3,"comments_count":2,"created_by":134,"edited_by":223089,"edited_at":"2023-02-02T11:43:47.000Z","deleted_by":null,"deleted_at":null,"solvers_count":60,"test_suite_updated_at":"2023-02-02T11:43:47.000Z","rescore_all_solutions":false,"group_id":40,"created_at":"2012-01-28T22:27:00.000Z","updated_at":"2026-04-02T08:30:49.000Z","published_at":"2012-02-01T01:02:17.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eDescription\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn the classic Parker Brothers game\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eBoggle\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e, players find words from a 4x4 game board of letters. This exercise is to make sure that a particular solution to a boggle board is actually available on the board.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe program\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003edoes not\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e need to check to make sure if the input word is a valid english word. Furthermore, all inputs will be in all uppercase, so the user does not need to check/convert for case differences. The game board will always be 4x4.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote: This does not perfectly align with the rules of Boggle. Specifically, all solutions in the original game must be 3 or more letters, which this problem is not asking to account for, and the atomic \\\"Qu\\\" is present (which I have avoided in the test suite).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHappy MATLABing!\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eExample\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[    x = ['TIPE'\\n         'YECV'\\n         'LSRA'\\n         'WOTU'];\\n    y = 'RACIEST';\\n    TF = true;]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":42633,"title":"Cumulative maximum of an array","description":"Find the cumulative maximum of an array without using the built-in function cummax (and a few others). Your function should act identically to cummax, allowing the same inputs.\r\nExamples\r\nIf X = [0 4 3\r\n        6 5 2]\r\n\r\ncumax(X,1) is [0 4 3  and cumax(X,2) is [0 4 4\r\n               6 5 3]                    6 6 6]\r\n\r\ncumax(X,1,'reverse') is [6 5 3  and cumax(X,2,'reverse') is [4 4 3\r\n                         6 5 2]                              6 5 2]\r\n\r\nAlso,\r\ncumax([8 9 1 10 6 1 3 6 10 10]) returns [8 9 9 10 10 10 10 10 10 10]\r\n\r\ncumax([8 9 1 10 6 1 3 6 10 10]') returns [8 9 9 10 10 10 10 10 10 10]'\r\nSee also cumin.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 378.633px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 189.317px; transform-origin: 407px 189.317px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 234px 8px; transform-origin: 234px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFind the cumulative maximum of an array without using the built-in function\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"/#null\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003ecummax\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 107px 8px; transform-origin: 107px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e (and a few others). Your function should act identically to cummax, allowing the same inputs.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 33.5px 8px; transform-origin: 33.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eExamples\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 265.633px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 132.817px; transform-origin: 404px 132.817px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 52px 8.5px; tab-size: 4; transform-origin: 52px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 12px 8.5px; transform-origin: 12px 8.5px; \"\u003eIf \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 40px 8.5px; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 40px 8.5px; \"\u003eX = [0 4 3\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 56px 8.5px; tab-size: 4; transform-origin: 56px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e        6 5 2]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 8.5px; tab-size: 4; transform-origin: 0px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 184px 8.5px; tab-size: 4; transform-origin: 184px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 56px 8.5px; transform-origin: 56px 8.5px; \"\u003ecumax(X,1) is \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 128px 8.5px; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 128px 8.5px; \"\u003e[0 4 3  and cumax(X,2) is [0 4 4\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 188px 8.5px; tab-size: 4; transform-origin: 188px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e               6 5 3]                    6 6 6]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 8.5px; tab-size: 4; transform-origin: 0px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 264px 8.5px; tab-size: 4; transform-origin: 264px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 40px 8.5px; transform-origin: 40px 8.5px; \"\u003ecumax(X,1,\u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 36px 8.5px; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 36px 8.5px; \"\u003e'reverse'\u003c/span\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 20px 8.5px; transform-origin: 20px 8.5px; \"\u003e) is \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 168px 8.5px; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 168px 8.5px; \"\u003e[6 5 3  and cumax(X,2,'reverse') is [4 4 3\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 268px 8.5px; tab-size: 4; transform-origin: 268px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e                         6 5 2]                              6 5 2]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 8.5px; tab-size: 4; transform-origin: 0px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 20px 8.5px; tab-size: 4; transform-origin: 20px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eAlso,\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 272px 8.5px; tab-size: 4; transform-origin: 272px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 160px 8.5px; transform-origin: 160px 8.5px; \"\u003ecumax([8 9 1 10 6 1 3 6 10 10]) returns \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 112px 8.5px; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 112px 8.5px; \"\u003e[8 9 9 10 10 10 10 10 10 10]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 8.5px; tab-size: 4; transform-origin: 0px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 280px 8.5px; tab-size: 4; transform-origin: 280px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 164px 8.5px; transform-origin: 164px 8.5px; \"\u003ecumax([8 9 1 10 6 1 3 6 10 10]') returns \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(196, 0, 0); border-block-start-color: rgb(196, 0, 0); border-bottom-color: rgb(196, 0, 0); border-inline-end-color: rgb(196, 0, 0); border-inline-start-color: rgb(196, 0, 0); border-left-color: rgb(196, 0, 0); border-right-color: rgb(196, 0, 0); border-top-color: rgb(196, 0, 0); caret-color: rgb(196, 0, 0); color: rgb(196, 0, 0); column-rule-color: rgb(196, 0, 0); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(196, 0, 0); perspective-origin: 116px 8.5px; text-decoration-color: rgb(196, 0, 0); text-emphasis-color: rgb(196, 0, 0); transform-origin: 116px 8.5px; \"\u003e[8 9 9 10 10 10 10 10 10 10]'\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 27.5px 8px; transform-origin: 27.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eSee also\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"/#null\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003ecumin\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2px 8px; transform-origin: 2px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = cumaX(x,varargin)\r\n  y = x;\r\nend","test_suite":"%%\r\nfiletext = fileread('cumaX.m');\r\nassert(isempty(strfind(filetext,'max')))\r\nassert(isempty(strfind(filetext,'cummin')))\r\nassert(isempty(strfind(filetext,'cummax')))\r\nassert(isempty(strfind(filetext,'feval')))\r\n\r\n%%\r\nx = randi(100);\r\nassert(isequal(cumaX(x),cummax(x)))\r\nassert(isequal(cumaX(x,1),cummax(x,1)))\r\nassert(isequal(cumaX(x,2),cummax(x,2)))\r\nassert(isequal(cumaX(x,1,'reverse'),cummax(x,1,'reverse')))\r\nassert(isequal(cumaX(x,2,'reverse'),cummax(x,2,'reverse')))\r\nassert(isequal(cumaX(x,'reverse'),cummax(x,'reverse')))\r\n\r\n%%\r\nx = randi(100,randi([2 100]),1);\r\nassert(isequal(cumaX(x),cummax(x)))\r\nassert(isequal(cumaX(x,1),cummax(x,1)))\r\nassert(isequal(cumaX(x,2),cummax(x,2)))\r\nassert(isequal(cumaX(x,1,'reverse'),cummax(x,1,'reverse')))\r\nassert(isequal(cumaX(x,2,'reverse'),cummax(x,2,'reverse')))\r\nassert(isequal(cumaX(x,'reverse'),cummax(x,'reverse')))\r\n\r\n%%\r\nx = randi(100,1,randi([2 100]));\r\nassert(isequal(cumaX(x),cummax(x)))\r\nassert(isequal(cumaX(x,1),cummax(x,1)))\r\nassert(isequal(cumaX(x,2),cummax(x,2)))\r\nassert(isequal(cumaX(x,1,'reverse'),cummax(x,1,'reverse')))\r\nassert(isequal(cumaX(x,2,'reverse'),cummax(x,2,'reverse')))\r\nassert(isequal(cumaX(x,'reverse'),cummax(x,'reverse')))\r\n\r\n%%\r\nx = magic(10);\r\nassert(isequal(cumaX(x),cummax(x)))\r\nassert(isequal(cumaX(x,1),cummax(x,1)))\r\nassert(isequal(cumaX(x,2),cummax(x,2)))\r\nassert(isequal(cumaX(x,1,'reverse'),cummax(x,1,'reverse')))\r\nassert(isequal(cumaX(x,2,'reverse'),cummax(x,2,'reverse')))\r\nassert(isequal(cumaX(x,'reverse'),cummax(x,'reverse')))\r\n\r\n%%\r\nx = [];\r\nassert(isequal(cumaX(x),cummax(x)))\r\nassert(isequal(cumaX(x,1),cummax(x,1)))\r\nassert(isequal(cumaX(x,2),cummax(x,2)))\r\nassert(isequal(cumaX(x,1,'reverse'),cummax(x,1,'reverse')))\r\nassert(isequal(cumaX(x,2,'reverse'),cummax(x,2,'reverse')))\r\nassert(isequal(cumaX(x,'reverse'),cummax(x,'reverse')))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":5,"created_by":4793,"edited_by":223089,"edited_at":"2022-10-09T10:09:17.000Z","deleted_by":null,"deleted_at":null,"solvers_count":42,"test_suite_updated_at":"2022-10-09T10:09:17.000Z","rescore_all_solutions":false,"group_id":24,"created_at":"2015-09-23T19:36:49.000Z","updated_at":"2026-03-29T06:57:19.000Z","published_at":"2015-09-23T19:38:39.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFind the cumulative maximum of an array without using the built-in function\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ecummax\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e (and a few others). Your function should act identically to cummax, allowing the same inputs.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eExamples\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[If X = [0 4 3\\n        6 5 2]\\n\\ncumax(X,1) is [0 4 3  and cumax(X,2) is [0 4 4\\n               6 5 3]                    6 6 6]\\n\\ncumax(X,1,'reverse') is [6 5 3  and cumax(X,2,'reverse') is [4 4 3\\n                         6 5 2]                              6 5 2]\\n\\nAlso,\\ncumax([8 9 1 10 6 1 3 6 10 10]) returns [8 9 9 10 10 10 10 10 10 10]\\n\\ncumax([8 9 1 10 6 1 3 6 10 10]') returns [8 9 9 10 10 10 10 10 10 10]']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSee also\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ecumin\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":3070,"title":"Pattern Recognition 3 - Variable Unit and Array Length (including cell arrays)","description":"You will be given various arrays, composed of numbers or strings, including cell arrays of strings. For this problem, the pattern unit length is variable, ranging from three to half the array length (the unit will be completely repeated at least once). Write a function to determine if the supplied array is a strict repeating pattern. The array will not necessarily have a length that is a multiple of the unit length.\r\n\r\nFor example, [1 2 3 4 5 1 2 3 4 5 1 2 3] would return true since the first block (1:5) is strictly repeated through the remainder of the array (including the last [1 2 3]). On the other hand, 'abcabcabcabcabcabea' would return false, since the last complete block is 'abe' rather than 'abc', as indicated by the first block.\r\n\r\nThis problem is a follow-on to \u003chttps://www.mathworks.com/matlabcentral/cody/problems/3068-pattern-recognition-1-known-unit-length Problem 3068\u003e and \u003chttps://www.mathworks.com/matlabcentral/cody/problems/3069-pattern-recognition-2-known-unit-length-various-array-length-including-cell-arrays Problem 3069\u003e.","description_html":"\u003cp\u003eYou will be given various arrays, composed of numbers or strings, including cell arrays of strings. For this problem, the pattern unit length is variable, ranging from three to half the array length (the unit will be completely repeated at least once). Write a function to determine if the supplied array is a strict repeating pattern. The array will not necessarily have a length that is a multiple of the unit length.\u003c/p\u003e\u003cp\u003eFor example, [1 2 3 4 5 1 2 3 4 5 1 2 3] would return true since the first block (1:5) is strictly repeated through the remainder of the array (including the last [1 2 3]). On the other hand, 'abcabcabcabcabcabea' would return false, since the last complete block is 'abe' rather than 'abc', as indicated by the first block.\u003c/p\u003e\u003cp\u003eThis problem is a follow-on to \u003ca href = \"https://www.mathworks.com/matlabcentral/cody/problems/3068-pattern-recognition-1-known-unit-length\"\u003eProblem 3068\u003c/a\u003e and \u003ca href = \"https://www.mathworks.com/matlabcentral/cody/problems/3069-pattern-recognition-2-known-unit-length-various-array-length-including-cell-arrays\"\u003eProblem 3069\u003c/a\u003e.\u003c/p\u003e","function_template":"function [tf] = pattern_recognition3(array)\r\n\r\ntf = 0;\r\n\r\nend\r\n","test_suite":"%%\r\narray = [1 2 3 4 5 1 2 3 4 5 1 2 3];\r\ntf = 1;\r\nassert(isequal(pattern_recognition3(array),tf))\r\n\r\n%%\r\narray = [1 2 2 1 2 1 2 2 1 2 1 2];\r\ntf = 1;\r\nassert(isequal(pattern_recognition3(array),tf))\r\n\r\n%%\r\narray = [1 2 1 2 2 2 1 2];\r\ntf = 0;\r\nassert(isequal(pattern_recognition3(array),tf))\r\n\r\n%%\r\narray = [0.1 1 10 100 1000 10000];\r\narray = repmat(array,[1,5]);\r\ntf = 1;\r\nassert(isequal(pattern_recognition3(array),tf))\r\n\r\n%%\r\narray = {'c3po','r2','d2','c3po','d2','r2','c3po','r2','d2','c3po'};\r\ntf = 0;\r\nassert(isequal(pattern_recognition3(array),tf))\r\n\r\n%%\r\narray = 'hi ho hi ho hi ho hi';\r\ntf = 1;\r\nassert(isequal(pattern_recognition3(array),tf))\r\n\r\n%%\r\narray = 'a':'z';\r\narray = repmat(array,[1,5]);\r\ntf = 1;\r\nassert(isequal(pattern_recognition3(array),tf))\r\n\r\n%%\r\narray = {'c3','po','r2','d2','c3','po','r2','d2','c3','po','r2','d2','c3','po','r2'};\r\ntf = 1;\r\nassert(isequal(pattern_recognition3(array),tf))\r\n\r\n%%\r\narray = [1 2 3 3 2 3 1 2 3 1];\r\ntf = 0;\r\nassert(isequal(pattern_recognition3(array),tf))\r\n\r\n%%\r\narray = {'ab','cde','fg','ab','cbe','fg','ab','edc','fg'};\r\ntf = 0;\r\nassert(isequal(pattern_recognition3(array),tf))\r\n\r\n%%\r\narray = 'abcabcabcabcabcabea';\r\ntf = 0;\r\nassert(isequal(pattern_recognition3(array),tf))\r\n\r\n%%\r\narray = [1 10 100 1 100 10 1 10 100 1 10 100];\r\ntf = 0;\r\nassert(isequal(pattern_recognition3(array),tf))\r\n\r\n%%\r\narray = 'hi hi him';\r\ntf = 0;\r\nassert(isequal(pattern_recognition3(array),tf))\r\n\r\n%%\r\narray = {'ab','cde','fg','ab','cde','fg','ab','cde','fg'};\r\ntf = 1;\r\nassert(isequal(pattern_recognition3(array),tf))\r\n\r\n%%\r\narray = [ones(1,40) zeros(1,20) ones(1,40) zeros(1,20) ones(1,40)];\r\ntf = 1;\r\nassert(isequal(pattern_recognition3(array),tf))\r\n\r\n%%\r\narray = [-1:9 -1:4 -1:2 -1:9 -1:4 -1:2 -1:9 -1:4 -1:2 -1:9];\r\ntf = 1;\r\nassert(isequal(pattern_recognition3(array),tf))\r\n\r\n%%\r\nind = randi(4);\r\nswitch ind\r\n\tcase 1\r\n\t\tarray = {'c3po','r2','d2','c3po','r2','d2','c3po','r2','d2','c3po'};\r\n\t\ttf = 1;\r\n\tcase 2\r\n\t\tarray = 'hi hi him';\r\n\t\ttf = 0;\r\n\tcase 3\r\n\t\tarray = [1 2 3 3 1 2 3 1 2 3];\r\n\t\ttf = 0;\r\n\tcase 4\r\n\t\tarray = [1 2 2 4 1 2 2 4 1];\r\n\t\ttf = 1;\r\nend\r\nassert(isequal(pattern_recognition3(array),tf))\r\n\r\n%%\r\nind = randi(4);\r\nswitch ind\r\n\tcase 1\r\n\t\tarray = [1 2 3 3 2 3 1 2 3 1 2];\r\n\t\ttf = 0;\r\n\tcase 2\r\n\t\tarray = [1 10 100 1 10 1 10 100 1 10 100 1];\r\n\t\ttf = 0;\r\n\tcase 3\r\n\t\tarray = [1 2 2 4 5 1 2 2 4 5 1];\r\n\t\ttf = 1;\r\n\tcase 4\r\n\t\tarray = {'ab','cde','ab','cde','fg','ab','cde','ab','cde','fg','ab','cde','ab','cde','fg'};\r\n\t\ttf = 1;\r\nend\r\nassert(isequal(pattern_recognition3(array),tf))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":3,"created_by":26769,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":58,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":30,"created_at":"2015-03-08T03:41:45.000Z","updated_at":"2026-03-16T14:26:39.000Z","published_at":"2015-03-08T03:41:45.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou will be given various arrays, composed of numbers or strings, including cell arrays of strings. For this problem, the pattern unit length is variable, ranging from three to half the array length (the unit will be completely repeated at least once). Write a function to determine if the supplied array is a strict repeating pattern. The array will not necessarily have a length that is a multiple of the unit length.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example, [1 2 3 4 5 1 2 3 4 5 1 2 3] would return true since the first block (1:5) is strictly repeated through the remainder of the array (including the last [1 2 3]). On the other hand, 'abcabcabcabcabcabea' would return false, since the last complete block is 'abe' rather than 'abc', as indicated by the first block.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis problem is a follow-on to\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.mathworks.com/matlabcentral/cody/problems/3068-pattern-recognition-1-known-unit-length\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eProblem 3068\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e and\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.mathworks.com/matlabcentral/cody/problems/3069-pattern-recognition-2-known-unit-length-various-array-length-including-cell-arrays\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eProblem 3069\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":42631,"title":"Cumulative minimum of an array","description":"Find the cumulative minimum of an array without using the built-in function \u003chttp://www.mathworks.com/help/matlab/ref/cummin.html cummin\u003e (and a few others). Your function should act identically to cummin, allowing the same inputs.\r\n\r\n*Examples*\r\n\r\n  If X = [0 4 3\r\n          6 5 2]\r\n\r\n  cumin(X,1) is [0 4 3  and cumin(X,2) is [0 0 0\r\n                 0 4 2]                    6 5 2]\r\n \r\n  cumin(X,1,'reverse') is [0 4 2  and cumin(X,2,'reverse') is [0 3 3\r\n                           6 5 2]                              2 2 2]\r\n\r\n  Also,\r\n  cumin([8 9 1 10 6 1 3 6 10 10]) returns [8 8 1 1 1 1 1 1 1 1]\r\n\r\n  cumin([8 9 1 10 6 1 3 6 10 10]') returns [8 8 1 1 1 1 1 1 1 1]'\r\n\r\nSee also \u003chttp://www.mathworks.com/matlabcentral/cody/problems/42633-cumulative-maximum-of-an-array cumax\u003e.","description_html":"\u003cp\u003eFind the cumulative minimum of an array without using the built-in function \u003ca href = \"http://www.mathworks.com/help/matlab/ref/cummin.html\"\u003ecummin\u003c/a\u003e (and a few others). Your function should act identically to cummin, allowing the same inputs.\u003c/p\u003e\u003cp\u003e\u003cb\u003eExamples\u003c/b\u003e\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eIf X = [0 4 3\r\n        6 5 2]\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003ecumin(X,1) is [0 4 3  and cumin(X,2) is [0 0 0\r\n               0 4 2]                    6 5 2]\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003ecumin(X,1,'reverse') is [0 4 2  and cumin(X,2,'reverse') is [0 3 3\r\n                         6 5 2]                              2 2 2]\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003eAlso,\r\ncumin([8 9 1 10 6 1 3 6 10 10]) returns [8 8 1 1 1 1 1 1 1 1]\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003ecumin([8 9 1 10 6 1 3 6 10 10]') returns [8 8 1 1 1 1 1 1 1 1]'\r\n\u003c/pre\u003e\u003cp\u003eSee also \u003ca href = \"http://www.mathworks.com/matlabcentral/cody/problems/42633-cumulative-maximum-of-an-array\"\u003ecumax\u003c/a\u003e.\u003c/p\u003e","function_template":"function y = cumin(x,varargin)\r\n  y = [];\r\nend","test_suite":"%%\r\nfiletext = fileread('cumin.m');\r\nassert(isempty(strfind(filetext,'cummin')))\r\nassert(isempty(strfind(filetext,'cummax')))\r\nassert(isempty(strfind(filetext,'feval')))\r\n\r\n%%\r\nx = randi(100);\r\nassert(isequal(cumin(x),cummin(x)))\r\nassert(isequal(cumin(x,1),cummin(x,1)))\r\nassert(isequal(cumin(x,2),cummin(x,2)))\r\nassert(isequal(cumin(x,1,'reverse'),cummin(x,1,'reverse')))\r\nassert(isequal(cumin(x,2,'reverse'),cummin(x,2,'reverse')))\r\nassert(isequal(cumin(x,'reverse'),cummin(x,'reverse')))\r\n\r\n%%\r\nx = randi(100,randi([2 100]),1);\r\nassert(isequal(cumin(x),cummin(x)))\r\nassert(isequal(cumin(x,1),cummin(x,1)))\r\nassert(isequal(cumin(x,2),cummin(x,2)))\r\nassert(isequal(cumin(x,1,'reverse'),cummin(x,1,'reverse')))\r\nassert(isequal(cumin(x,2,'reverse'),cummin(x,2,'reverse')))\r\nassert(isequal(cumin(x,'reverse'),cummin(x,'reverse')))\r\n\r\n%%\r\nx = randi(100,1,randi([2 100]));\r\nassert(isequal(cumin(x),cummin(x)))\r\nassert(isequal(cumin(x,1),cummin(x,1)))\r\nassert(isequal(cumin(x,2),cummin(x,2)))\r\nassert(isequal(cumin(x,1,'reverse'),cummin(x,1,'reverse')))\r\nassert(isequal(cumin(x,2,'reverse'),cummin(x,2,'reverse')))\r\nassert(isequal(cumin(x,'reverse'),cummin(x,'reverse')))\r\n\r\n%%\r\nx = magic(10);\r\nassert(isequal(cumin(x),cummin(x)))\r\nassert(isequal(cumin(x,1),cummin(x,1)))\r\nassert(isequal(cumin(x,2),cummin(x,2)))\r\nassert(isequal(cumin(x,1,'reverse'),cummin(x,1,'reverse')))\r\nassert(isequal(cumin(x,2,'reverse'),cummin(x,2,'reverse')))\r\nassert(isequal(cumin(x,'reverse'),cummin(x,'reverse')))\r\n\r\n%%\r\nx = [];\r\nassert(isequal(cumin(x),cummin(x)))\r\nassert(isequal(cumin(x,1),cummin(x,1)))\r\nassert(isequal(cumin(x,2),cummin(x,2)))\r\nassert(isequal(cumin(x,1,'reverse'),cummin(x,1,'reverse')))\r\nassert(isequal(cumin(x,2,'reverse'),cummin(x,2,'reverse')))\r\nassert(isequal(cumin(x,'reverse'),cummin(x,'reverse')))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":4793,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":42,"test_suite_updated_at":"2015-09-24T04:46:57.000Z","rescore_all_solutions":false,"group_id":24,"created_at":"2015-09-22T21:12:22.000Z","updated_at":"2026-04-01T07:07:43.000Z","published_at":"2015-09-23T19:24:39.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFind the cumulative minimum of an array without using the built-in function\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.mathworks.com/help/matlab/ref/cummin.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ecummin\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e (and a few others). Your function should act identically to cummin, allowing the same inputs.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eExamples\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[If X = [0 4 3\\n        6 5 2]\\n\\ncumin(X,1) is [0 4 3  and cumin(X,2) is [0 0 0\\n               0 4 2]                    6 5 2]\\n\\ncumin(X,1,'reverse') is [0 4 2  and cumin(X,2,'reverse') is [0 3 3\\n                         6 5 2]                              2 2 2]\\n\\nAlso,\\ncumin([8 9 1 10 6 1 3 6 10 10]) returns [8 8 1 1 1 1 1 1 1 1]\\n\\ncumin([8 9 1 10 6 1 3 6 10 10]') returns [8 8 1 1 1 1 1 1 1 1]']]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSee also\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.mathworks.com/matlabcentral/cody/problems/42633-cumulative-maximum-of-an-array\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ecumax\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":42639,"title":"Find the Final State of an Abelian Sandpile","description":"Let us define an \u003chttp://nautil.us/issue/23/dominoes/the-amazing-autotuning-sandpile Abelian sand pile\u003e as a matrix that is only in a stable and final state when all of its elements are less than 4. When any of its elements is greater than 4, distribute four sand grains, one each to the elements above, below, to the left, and to the right of the offending element. Continue doing this until the matrix is stable.\r\n\r\nSo\r\n\r\n 0 0 0 \r\n 0 4 1\r\n 1 0 0\r\n\r\nwould become\r\n\r\n 0 1 0\r\n 1 0 2\r\n 1 1 0\r\n\r\nbecause the 4 in the middle is unstable and gets distributed.\r\n\r\nWhat makes this process Abelian is that the order in which you distribute the \"sand grains\" doesn't matter. This gives you considerable algorithmic freedom.\r\n\r\nSo, given an input matrix A, return the resulting stable Abelian sand pile matrix B.\r\n\r\nNote: you won't have to worry about sand grains \"falling off the edge of the table.\" The given matrix A will always be big enough to handle the resulting stable matrix B.\r\n\r\nExamples\r\n\r\n A = [ 0 0 0 0\r\n       0 4 4 0\r\n       0 0 0 0 ]\r\n\r\n B = [ 0 1 1 0\r\n       1 1 1 1\r\n       0 1 1 0 ]\r\n\r\nand\r\n\r\n A = [ 0 0 0\r\n       0 9 0\r\n       0 0 0 ] \r\n\r\n B = [ 0 2 0\r\n       2 1 2\r\n       0 2 0 ]\r\n\r\n\r\n","description_html":"\u003cp\u003eLet us define an \u003ca href = \"http://nautil.us/issue/23/dominoes/the-amazing-autotuning-sandpile\"\u003eAbelian sand pile\u003c/a\u003e as a matrix that is only in a stable and final state when all of its elements are less than 4. When any of its elements is greater than 4, distribute four sand grains, one each to the elements above, below, to the left, and to the right of the offending element. Continue doing this until the matrix is stable.\u003c/p\u003e\u003cp\u003eSo\u003c/p\u003e\u003cpre\u003e 0 0 0 \r\n 0 4 1\r\n 1 0 0\u003c/pre\u003e\u003cp\u003ewould become\u003c/p\u003e\u003cpre\u003e 0 1 0\r\n 1 0 2\r\n 1 1 0\u003c/pre\u003e\u003cp\u003ebecause the 4 in the middle is unstable and gets distributed.\u003c/p\u003e\u003cp\u003eWhat makes this process Abelian is that the order in which you distribute the \"sand grains\" doesn't matter. This gives you considerable algorithmic freedom.\u003c/p\u003e\u003cp\u003eSo, given an input matrix A, return the resulting stable Abelian sand pile matrix B.\u003c/p\u003e\u003cp\u003eNote: you won't have to worry about sand grains \"falling off the edge of the table.\" The given matrix A will always be big enough to handle the resulting stable matrix B.\u003c/p\u003e\u003cp\u003eExamples\u003c/p\u003e\u003cpre\u003e A = [ 0 0 0 0\r\n       0 4 4 0\r\n       0 0 0 0 ]\u003c/pre\u003e\u003cpre\u003e B = [ 0 1 1 0\r\n       1 1 1 1\r\n       0 1 1 0 ]\u003c/pre\u003e\u003cp\u003eand\u003c/p\u003e\u003cpre\u003e A = [ 0 0 0\r\n       0 9 0\r\n       0 0 0 ] \u003c/pre\u003e\u003cpre\u003e B = [ 0 2 0\r\n       2 1 2\r\n       0 2 0 ]\u003c/pre\u003e","function_template":"function B = sandpile(A)\r\n  B = zeros(size(A));\r\nend","test_suite":"%%\r\nA = 1;\r\nB_correct = 1;\r\nassert(isequal(sandpile(A),B_correct))\r\n\r\n%%\r\nA = [0 0 0;0 4 1;1 0 0];\r\nB_correct  = [0 1 0;1 0 2;1 1 0];\r\nassert(isequal(sandpile(A),B_correct))\r\n\r\n%%\r\nA = [0 0 0 0;0 4 4 0;0 0 0 0];\r\nB_correct = [0 1 1 0;1 1 1 1;0 1 1 0];\r\nassert(isequal(sandpile(A),B_correct))\r\n\r\n%%\r\nA = [0 0 0 0 0;0 0 0 0 0;0 0 17 0 0;0 0 0 7 0;0 0 0 0 0];\r\nB_correct = [0 0 1 0 0;0 2 1 2 0;1 1 1 3 1;0 2 3 1 2;0 0 1 2 0];\r\nassert(isequal(sandpile(A),B_correct))\r\n\r\n%%\r\nA = [0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0;0 0 0 16 2 3 13 0 0 0 0;0 0 0 5 11 10 8 0 0 0 0;0 0 0 9 7 6 12 0 0 0 0;0 0 0 4 14 15 1 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0];\r\nB_correct = [0 0 0 0 0 0 0 0 0 0 0;0 0 1 3 3 3 3 1 0 0 0;0 2 3 2 3 3 2 3 2 0 0;1 1 1 3 2 3 1 1 1 1 0;1 3 1 1 3 3 1 2 3 1 0;1 3 0 3 3 3 3 1 3 1 0;1 0 3 2 2 3 0 3 0 1 0;0 2 2 3 2 2 3 2 2 0 0;0 0 2 0 3 3 0 2 0 0 0;0 0 0 1 1 1 1 0 0 0 0;0 0 0 0 0 0 0 0 0 0 0];\r\nassert(isequal(sandpile(A),B_correct))\r\n\r\n","published":true,"deleted":false,"likes_count":4,"comments_count":1,"created_by":7,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":74,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":24,"created_at":"2015-09-29T20:59:19.000Z","updated_at":"2026-04-01T07:15:49.000Z","published_at":"2015-09-29T23:01:28.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eLet us define an\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://nautil.us/issue/23/dominoes/the-amazing-autotuning-sandpile\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eAbelian sand pile\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e as a matrix that is only in a stable and final state when all of its elements are less than 4. When any of its elements is greater than 4, distribute four sand grains, one each to the elements above, below, to the left, and to the right of the offending element. Continue doing this until the matrix is stable.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSo\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ 0 0 0 \\n 0 4 1\\n 1 0 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ewould become\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ 0 1 0\\n 1 0 2\\n 1 1 0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ebecause the 4 in the middle is unstable and gets distributed.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWhat makes this process Abelian is that the order in which you distribute the \\\"sand grains\\\" doesn't matter. This gives you considerable algorithmic freedom.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSo, given an input matrix A, return the resulting stable Abelian sand pile matrix B.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote: you won't have to worry about sand grains \\\"falling off the edge of the table.\\\" The given matrix A will always be big enough to handle the resulting stable matrix B.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExamples\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ A = [ 0 0 0 0\\n       0 4 4 0\\n       0 0 0 0 ]\\n\\n B = [ 0 1 1 0\\n       1 1 1 1\\n       0 1 1 0 ]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eand\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ A = [ 0 0 0\\n       0 9 0\\n       0 0 0 ] \\n\\n B = [ 0 2 0\\n       2 1 2\\n       0 2 0 ]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1940,"title":"Decimation - Optimized for speed","description":"This problem is similar to http://www.mathworks.com/matlabcentral/cody/problems/1092-decimation, only this time the score will be based on how quickly you can determine which person will survive.\r\n\r\nThe sample sizes (num_prisoners) and number of prisoners killed (num_killed) will be larger than in the original problem, but other than that the problem sets are identical.","description_html":"\u003cp\u003eThis problem is similar to \u003ca href = \"http://www.mathworks.com/matlabcentral/cody/problems/1092-decimation\"\u003ehttp://www.mathworks.com/matlabcentral/cody/problems/1092-decimation\u003c/a\u003e, only this time the score will be based on how quickly you can determine which person will survive.\u003c/p\u003e\u003cp\u003eThe sample sizes (num_prisoners) and number of prisoners killed (num_killed) will be larger than in the original problem, but other than that the problem sets are identical.\u003c/p\u003e","function_template":"function y = speed_decimation(num_prisoners, num_killed)\r\n  y = num_prisoners+num_killed;\r\nend","test_suite":"%%\r\nassert(isequal(speed_decimation(10,3),4))\r\n%%\r\nassert(isequal(speed_decimation(1024,3),676))\r\n%%\r\nassert(isequal(speed_decimation(2012,50),543))\r\n%%\r\nassert(isequal(speed_decimation(30,5),3))\r\n%%\r\nassert(isequal(speed_decimation(10,10),8))\r\n%%\r\nassert(isequal(speed_decimation(2048,2),1))\r\n%%\r\nassert(isequal(speed_decimation(2048,1024),1773))\r\n%%\r\nt_in=clock;\r\nj=1:50;\r\nv=arrayfun(@(x) speed_decimation(100000,x),j);\r\ncorrect=[100000 68929 92620 32942 40333 54212 27152 67341 42610 77328 82991 13252 91717 6850 45758 71249 38339 86953 63331 66903 72606 83990 87828 46101 99979 47141 16871 60389 51549 76409 42868 78390 79590 27573 95835 53636 36954 39891 45943 63811 71589 70886 49313 4069 93694 96031 20739 41403 93714 60023];\r\nassert(all(isequal(v,correct)));\r\nt_out=etime(clock,t_in)*1000;\r\nfprintf('Actual Time = %.0f msec\\n',t_out)\r\nv=[100000:100000:1000000];\r\nv=arrayfun(@(x) speed_decimation(x,17),v);\r\ncorrect=[38339 162859 151602 99465 462955 559860 337009 546467 563784 364193];\r\nassert(all(isequal(v,correct)));\r\nt_out=etime(clock,t_in)*1000;\r\nfprintf('Actual Time = %.0f msec\\n',t_out)\r\nassert(isequal(speed_decimation(2^20,2^9),210856));\r\nt_out=etime(clock,t_in)*1000;\r\nt2=min(100000,t_out);\r\nfprintf('Actual Time = %.0f msec\\n',t_out)\r\nfeval(@assignin,'caller','score',floor(t2));","published":true,"deleted":false,"likes_count":9,"comments_count":2,"created_by":1615,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":221,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":13,"created_at":"2013-10-16T19:58:38.000Z","updated_at":"2026-03-17T13:55:24.000Z","published_at":"2013-10-16T19:58:38.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThis problem is similar to\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.mathworks.com/matlabcentral/cody/problems/1092-decimation\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ehttp://www.mathworks.com/matlabcentral/cody/problems/1092-decimation\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e, only this time the score will be based on how quickly you can determine which person will survive.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe sample sizes (num_prisoners) and number of prisoners killed (num_killed) will be larger than in the original problem, but other than that the problem sets are identical.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":44080,"title":"Construct a \"diagAdiag\" matrix","description":"Construct a matrix whose elements begin from 1 and end at n^2 with the order of arrangement as shown below:\r\n\r\nFor:\r\n\r\n  n = 4\r\n\r\noutput\r\n\r\n  M = \r\n[1   2   6   7;\r\n 3   5   8   13;\r\n 4   9   12  14;\r\n 10  11  15  16]\r\n\r\nNote the elements increase and decrease along alternating diagonals with the last element being always n^2.\r\n","description_html":"\u003cp\u003eConstruct a matrix whose elements begin from 1 and end at n^2 with the order of arrangement as shown below:\u003c/p\u003e\u003cp\u003eFor:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003en = 4\r\n\u003c/pre\u003e\u003cp\u003eoutput\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eM = \r\n[1   2   6   7;\r\n3   5   8   13;\r\n4   9   12  14;\r\n10  11  15  16]\r\n\u003c/pre\u003e\u003cp\u003eNote the elements increase and decrease along alternating diagonals with the last element being always n^2.\u003c/p\u003e","function_template":"function y = diagAdiag(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx = 3;\r\ny_correct = [1 2 6; 3 5 7;4 8 9];\r\nassert(isequal(diagAdiag(x),y_correct))\r\n\r\n%%\r\nx = 4;\r\ny_correct = [1   2   6   7; 3   5   8   13;4   9   12  14;10  11  15  16];\r\nassert(isequal(diagAdiag(x),y_correct))\r\n\r\n%%\r\nx = 5;\r\ny_correct = [1 2 6 7 15;3 5 8 14 16;4 9 13 17 22;10 12 18 21 23;11 19 20 24 25];\r\nassert(isequal(diagAdiag(x),y_correct))\r\n\r\n%%\r\nx = 6;\r\ny_correct = [ 1  2  6  7 15 16;\r\n              3  5  8 14 17 26;\r\n              4  9 13 18 25 27;\r\n             10 12 19 24 28 33;\r\n             11 20 23 29 32 34;\r\n             21 22 30 31 35 36];\r\nassert(isequal(diagAdiag(x),y_correct))\r\n\r\n%%\r\nx = 7;\r\ny_correct = [ 1  2  6  7 15 16 28;\r\n              3  5  8 14 17 27 29;\r\n              4  9 13 18 26 30 39;\r\n             10 12 19 25 31 38 40;\r\n             11 20 24 32 37 41 46;\r\n             21 23 33 36 42 45 47;\r\n             22 34 35 43 44 48 49];\r\nassert(isequal(diagAdiag(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":98103,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":89,"test_suite_updated_at":"2017-04-19T17:09:18.000Z","rescore_all_solutions":false,"group_id":24,"created_at":"2017-03-04T19:12:05.000Z","updated_at":"2026-04-02T22:13:25.000Z","published_at":"2017-03-04T19:15:05.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eConstruct a matrix whose elements begin from 1 and end at n^2 with the order of arrangement as shown below:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[n = 4]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eoutput\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[M = \\n[1   2   6   7;\\n3   5   8   13;\\n4   9   12  14;\\n10  11  15  16]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote the elements increase and decrease along alternating diagonals with the last element being always n^2.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":1826,"title":"Find vampire numbers","description":"A vampire number is a number v that is the product of two numbers x and y such that the following conditions are satisfied:\r\nat most one of x and y are divisible by 10;\r\nx and y have the same number of digits; and\r\nThe digits in v consist of the digits of x and y (including anyrepetitions).\r\nIf these conditions are met, x and y are known as \"fangs\" of v. For example, 1260 is a vampire number because 1260 = 21*60, so 21 and 60 are the fangs.\r\nWrite a function that returns all the vampire numbers in a given array. The output is a vector.\r\nExample: disp(find_vampire(1000:2000) 1260 1395 1435 1530 1827\r\nSee also:  Problem 1825. Find all vampire fangs and Problem 1804. Fangs of a vampire number.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 265.3px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 406.5px 132.65px; transform-origin: 406.5px 132.65px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 21px; text-align: left; transform-origin: 383.5px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 5.025px 7.81667px; transform-origin: 5.025px 7.81667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2.23333px 7.81667px; transform-origin: 2.23333px 7.81667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"/#null\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003evampire number\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 307.642px 7.81667px; transform-origin: 307.642px 7.81667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is a number v that is the product of two numbers x and y such that the following conditions are satisfied:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003col style=\"block-size: 61.3px; counter-reset: list-item 0; font-family: Helvetica, Arial, sans-serif; list-style-type: decimal; margin-block-end: 20px; margin-block-start: 10px; margin-bottom: 20px; margin-top: 10px; perspective-origin: 390.5px 30.65px; transform-origin: 390.5px 30.65px; margin-top: 10px; margin-bottom: 20px; \"\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 362.5px 10.2167px; text-align: left; transform-origin: 362.5px 10.2167px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 134.558px 7.81667px; transform-origin: 134.558px 7.81667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eat most one of x and y are divisible by 10;\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 362.5px 10.2167px; text-align: left; transform-origin: 362.5px 10.2167px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 142.933px 7.81667px; transform-origin: 142.933px 7.81667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ex and y have the same number of digits; and\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli style=\"block-size: 20.4333px; counter-reset: none; display: list-item; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-start: 56px; margin-left: 56px; margin-top: 0px; perspective-origin: 362.5px 10.2167px; text-align: left; transform-origin: 362.5px 10.2167px; white-space-collapse: preserve; margin-left: 56px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-inline-start: 0px; margin-left: 0px; perspective-origin: 228.358px 7.81667px; transform-origin: 228.358px 7.81667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe digits in v consist of the digits of x and y (including anyrepetitions).\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 21px; text-align: left; transform-origin: 383.5px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 383.5px 7.81667px; transform-origin: 383.5px 7.81667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIf these conditions are met, x and y are known as \"fangs\" of v. For example, 1260 is a vampire number because 1260 = 21*60, so 21 and 60 are the fangs.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.5px; text-align: left; transform-origin: 383.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 294.242px 7.81667px; transform-origin: 294.242px 7.81667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function that returns all the vampire numbers in a given array. The output is a vector.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.5px; text-align: left; transform-origin: 383.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 215.517px 7.81667px; transform-origin: 215.517px 7.81667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eExample: disp(find_vampire(1000:2000) 1260 1395 1435 1530 1827\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 383.5px 10.5px; text-align: left; transform-origin: 383.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 32.9417px 7.81667px; transform-origin: 32.9417px 7.81667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eSee also: \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2.23333px 7.81667px; transform-origin: 2.23333px 7.81667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"/#null\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eProblem 1825. Find all vampire fangs\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 13.9583px 7.81667px; transform-origin: 13.9583px 7.81667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2.23333px 7.81667px; transform-origin: 2.23333px 7.81667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"/#null\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eProblem 1804. Fangs of a vampire number\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 2.23333px 7.81667px; transform-origin: 2.23333px 7.81667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y =find_vampire(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nfiletext = fileread('find_vampire.m');\r\nillegal = contains(filetext, 'assignin') || contains(filetext, 'regexp') ...\r\n    || contains(filetext, '1260') || contains(filetext, 'intersect') ;\r\n%test case enhanced on 01-08-2024\r\n%intersect and the elements themselves were used to hard-code the problem\r\nassert(~illegal)\r\n\r\n%%\r\nx = 1000:2000;\r\nv = find_vampire(x);\r\nv_correct = [1260 1395 1435 1530 1827];\r\nassert(isequal(v,v_correct))\r\n\r\n%%\r\nx = 1:999;\r\nv = find_vampire(x);\r\nassert(isempty(v))\r\n\r\n%%\r\nx = reshape(2000:2999,100,[]);\r\nv = find_vampire(x);\r\nv_correct = 2187;\r\nassert(isequal(v,v_correct))\r\n\r\n%%\r\nx = [];\r\nv = find_vampire(x);\r\nassert(isempty(v))\r\n\r\n%%\r\nx = -2000:-1000;\r\nv = find_vampire(x);\r\nassert(isempty(v))\r\n\r\n%%\r\nx = 125000:125501;\r\nv = find_vampire(x);\r\nv_correct = [125248 125433 125460 125500];\r\nassert(isequal(v,v_correct))","published":true,"deleted":false,"likes_count":12,"comments_count":7,"created_by":1011,"edited_by":223089,"edited_at":"2024-08-01T16:28:29.000Z","deleted_by":null,"deleted_at":null,"solvers_count":394,"test_suite_updated_at":"2024-08-01T16:28:29.000Z","rescore_all_solutions":false,"group_id":8,"created_at":"2013-08-14T22:41:30.000Z","updated_at":"2026-02-15T13:30:53.000Z","published_at":"2013-08-14T22:42:12.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"\\\"\u003e\u003cw:r\u003e\u003cw:t\u003evampire number\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e is a number v that is the product of two numbers x and y such that the following conditions are satisfied:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eat most one of x and y are divisible by 10;\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ex and y have the same number of digits; and\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"ListParagraph\\\"/\u003e\u003cw:numPr\u003e\u003cw:numId w:val=\\\"2\\\"/\u003e\u003c/w:numPr\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe digits in v consist of the digits of x and y (including anyrepetitions).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIf these conditions are met, x and y are known as \\\"fangs\\\" of v. For example, 1260 is a vampire number because 1260 = 21*60, so 21 and 60 are the fangs.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function that returns all the vampire numbers in a given array. The output is a vector.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExample: disp(find_vampire(1000:2000) 1260 1395 1435 1530 1827\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eSee also: \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eProblem 1825. Find all vampire fangs\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e and\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eProblem 1804. Fangs of a vampire number\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":227,"title":"Math with Roman Numerals","description":"Given a function R within (+,-,*,/) and two Roman numerals a \u0026 b, compute aRb in Roman numerals.","description_html":"\u003cp\u003eGiven a function R within (+,-,*,/) and two Roman numerals a \u0026 b, compute aRb in Roman numerals.\u003c/p\u003e","function_template":"function y = numeri_romani(fcn,nbA,nbB)\r\n  y = (fcn,nbA,nbB);\r\nend","test_suite":"%%\r\nassert(isequal(numeri_romani('+','I','I'),'II'))\r\n\r\n%%\r\nassert(isequal(numeri_romani('-','X','I'),'IX'))\r\n\r\n%%\r\nassert(isequal(numeri_romani('*','X','X'),'C'))\r\n\r\n%%\r\nassert(isequal(numeri_romani('+',numeri_romani('*','XXV','XX'),numeri_romani('+','IV','V')),'DIX'))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":659,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":99,"test_suite_updated_at":"2014-10-14T14:24:43.000Z","rescore_all_solutions":false,"group_id":38,"created_at":"2012-02-02T09:52:13.000Z","updated_at":"2026-03-31T17:43:38.000Z","published_at":"2012-02-02T09:52:13.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a function R within (+,-,*,/) and two Roman numerals a \u0026amp; b, compute aRb in Roman numerals.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":2640,"title":"Find similar sequences","description":"Another problem inspired by a question on the \u003chttp://www.mathworks.com/matlabcentral/answers answers\u003e forum.\r\n\r\nGiven a matrix of positive integer numbers, find all the rows that are similar to the first rows and return these rows as a new matrix.\r\n\r\nRows are considered similar if the numbers common to both rows are in the exact same order with no other numbers in between. 0s in a row are always ignored and only occur at the end of the row.\r\n\r\nFor example:\r\n\r\n [3 1 5 0 0] and [4 2 1 5 0] are similar (1 5 are the common numbers and occur in the same order)\r\n [3 1 5 0 0] and [3 4 1 5 0] are not similar (3 1 5 are the common numbers, there's a 4 in between)\r\n ","description_html":"\u003cp\u003eAnother problem inspired by a question on the \u003ca href = \"http://www.mathworks.com/matlabcentral/answers\"\u003eanswers\u003c/a\u003e forum.\u003c/p\u003e\u003cp\u003eGiven a matrix of positive integer numbers, find all the rows that are similar to the first rows and return these rows as a new matrix.\u003c/p\u003e\u003cp\u003eRows are considered similar if the numbers common to both rows are in the exact same order with no other numbers in between. 0s in a row are always ignored and only occur at the end of the row.\u003c/p\u003e\u003cp\u003eFor example:\u003c/p\u003e\u003cpre\u003e [3 1 5 0 0] and [4 2 1 5 0] are similar (1 5 are the common numbers and occur in the same order)\r\n [3 1 5 0 0] and [3 4 1 5 0] are not similar (3 1 5 are the common numbers, there's a 4 in between)\u003c/pre\u003e","function_template":"function rows = findsimilar(m)\r\n  rows = [];\r\nend","test_suite":"%%\r\nm = [3 1 5 0 0\r\n     3 4 1 5 0\r\n     4 2 1 5 0];\r\nsrows = [3 1 5 0 0;4 2 1 5 0];\r\nassert(isequal(findsimilar(m),srows))\r\n\r\n%%\r\nm = [3 1 5 0 0\r\n     1 2 5 0 0\r\n     1 3 4 1 5\r\n     2 1 5 0 0];\r\nsrows = [3 1 5 0 0; 2 1 5 0 0];\r\nassert(isequal(findsimilar(m),srows))\r\n\r\n%%\r\nm = [3 1 5 7 0\r\n     3 2 5 7 0\r\n     3 5 7 2 0\r\n     1 5 7 2 0\r\n     4 6 7 8 9\r\n     4 5 7 8 0\r\n     4 5 6 7 8];\r\nsrows = [3 1 5 7 0;1 5 7 2 0;4 6 7 8 9;4 5 7 8 0];\r\nassert(isequal(findsimilar(m),srows))\r\n\r\n%%\r\nm = [3 1 5 0 0\r\n     3 1 6 0 0\r\n     3 2 6 0 0\r\n     2 1 5 6 0];\r\nsrows = m;\r\nassert(isequal(findsimilar(m), srows))","published":true,"deleted":false,"likes_count":1,"comments_count":8,"created_by":999,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":140,"test_suite_updated_at":"2014-10-24T06:14:05.000Z","rescore_all_solutions":false,"group_id":29,"created_at":"2014-10-23T08:06:10.000Z","updated_at":"2026-03-17T14:55:43.000Z","published_at":"2014-10-23T08:06:26.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAnother problem inspired by a question on the\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.mathworks.com/matlabcentral/answers\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eanswers\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e forum.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven a matrix of positive integer numbers, find all the rows that are similar to the first rows and return these rows as a new matrix.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eRows are considered similar if the numbers common to both rows are in the exact same order with no other numbers in between. 0s in a row are always ignored and only occur at the end of the row.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ [3 1 5 0 0] and [4 2 1 5 0] are similar (1 5 are the common numbers and occur in the same order)\\n [3 1 5 0 0] and [3 4 1 5 0] are not similar (3 1 5 are the common numbers, there's a 4 in between)]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":95,"title":"Given two arrays, find the maximum overlap","description":"Given two (integer) arrays s1 and s2, create a new array s3 which is as short as possible and contains both arrays.\r\n#1\r\n s1 = [1 2 3 4 5]\r\n s2 = [5 4 3 2]\r\n s3 = [1 2 3 4 5 4 3 2]\r\nThere is guaranteed to be one best solution.\r\n8/8/22 - New test case added (and solutions have been rescored)\r\n#2\r\n%courtesy of comments\r\n s1 = [-1 -2 -3]\r\n s2 = [-3 -1 -2]\r\n s3 = [-3 -1 -2 -3]","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 305.033px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 152.517px; transform-origin: 407px 152.517px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 361.5px 8px; transform-origin: 361.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"perspective-origin: 33px 8px; transform-origin: 33px 8px; \"\u003eGiven two \u003c/span\u003e\u003cspan style=\"border-block-end-style: solid; border-block-end-width: 1px; border-bottom-style: solid; border-bottom-width: 1px; perspective-origin: 2.5px 8.5px; transform-origin: 2.5px 8.5px; \"\u003e(\u003c/span\u003e\u003cspan style=\"perspective-origin: 22px 8px; transform-origin: 22px 8px; \"\u003einteger\u003c/span\u003e\u003cspan style=\"border-block-end-style: solid; border-block-end-width: 1px; border-bottom-style: solid; border-bottom-width: 1px; perspective-origin: 2.5px 8.5px; transform-origin: 2.5px 8.5px; \"\u003e)\u003c/span\u003e\u003cspan style=\"perspective-origin: 301.5px 8px; transform-origin: 301.5px 8px; \"\u003e arrays s1 and s2, create a new array s3 which is as short as possible and contains both arrays.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 8px 8px; transform-origin: 8px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e#1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 61.3px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 30.65px; transform-origin: 404px 30.65px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 68px 8.5px; tab-size: 4; transform-origin: 68px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e s1 = [1 2 3 4 5]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 60px 8.5px; tab-size: 4; transform-origin: 60px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e s2 = [5 4 3 2]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 92px 8.5px; tab-size: 4; transform-origin: 92px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e s3 = [1 2 3 4 5 4 3 2]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 140.5px 8px; transform-origin: 140.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThere is guaranteed to be one best solution.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 206.5px 8px; transform-origin: 206.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e8/8/22 - New test case added (and solutions have been rescored)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 8px 8px; transform-origin: 8px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e#2\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 81.7333px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 40.8667px; transform-origin: 404px 40.8667px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 84px 8.5px; tab-size: 4; transform-origin: 84px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"border-block-end-color: rgb(2, 128, 9); border-block-start-color: rgb(2, 128, 9); border-bottom-color: rgb(2, 128, 9); border-inline-end-color: rgb(2, 128, 9); border-inline-start-color: rgb(2, 128, 9); border-left-color: rgb(2, 128, 9); border-right-color: rgb(2, 128, 9); border-top-color: rgb(2, 128, 9); caret-color: rgb(2, 128, 9); color: rgb(2, 128, 9); column-rule-color: rgb(2, 128, 9); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(2, 128, 9); text-decoration-color: rgb(2, 128, 9); text-emphasis-color: rgb(2, 128, 9); \"\u003e%courtesy of comments\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 64px 8.5px; tab-size: 4; transform-origin: 64px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e s1 = [-1 -2 -3]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 64px 8.5px; tab-size: 4; transform-origin: 64px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e s2 = [-3 -1 -2]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 76px 8.5px; tab-size: 4; transform-origin: 76px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e s3 = [-3 -1 -2 -3]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function s3 = overlap(s1,s2)\r\n  s3 = '';\r\nend","test_suite":"%%\r\n\r\ns1 = [1 2 3 4 5];\r\ns2 = [5 4 3 2];\r\ns3_correct = [1 2 3 4 5 4 3 2];\r\nassert(isequal(overlap(s1,s2),s3_correct))\r\n\r\n%%\r\n\r\ns1 = [1 0 1 7 7 7 6];\r\ns2 = [1 0 1 0 1];\r\ns3_correct = [1 0 1 0 1 7 7 7 6];\r\nassert(isequal(overlap(s1,s2),s3_correct))\r\n\r\n%%\r\n\r\ns1 = [3 1 4 1 5 9 2 6 5 3 5];\r\ns2 = [9 2 6 5];\r\ns3_correct = [3 1 4 1 5 9 2 6 5 3 5];\r\nassert(isequal(overlap(s1,s2),s3_correct))\r\n\r\n\r\n%%\r\n\r\ns1 = 1:100;\r\ns2 = [50 51];\r\ns3_correct = s1;\r\nassert(isequal(overlap(s1,s2),s3_correct))\r\n\r\n%%\r\n\r\ns1 = 90:10:200;\r\ns2 = 10:10:120;\r\ns3_correct = 10:10:200;\r\nassert(isequal(overlap(s1,s2),s3_correct))\r\n\r\n%%\r\n\r\ns1 = [-1 -2 -3];\r\ns2 = [-3 -1 -2];\r\ns3_correct = [-3 -1 -2 -3];\r\nassert(isequal(overlap(s1,s2),s3_correct))","published":true,"deleted":false,"likes_count":26,"comments_count":14,"created_by":1,"edited_by":223089,"edited_at":"2022-08-08T10:24:04.000Z","deleted_by":null,"deleted_at":null,"solvers_count":1729,"test_suite_updated_at":"2022-08-08T10:18:16.000Z","rescore_all_solutions":false,"group_id":2,"created_at":"2012-01-18T01:00:30.000Z","updated_at":"2026-04-03T07:43:48.000Z","published_at":"2012-01-18T01:00:30.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven two (integer) arrays s1 and s2, create a new array s3 which is as short as possible and contains both arrays.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e#1\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ s1 = [1 2 3 4 5]\\n s2 = [5 4 3 2]\\n s3 = [1 2 3 4 5 4 3 2]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThere is guaranteed to be one best solution.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e8/8/22 - New test case added (and solutions have been rescored)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e#2\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[%courtesy of comments\\n s1 = [-1 -2 -3]\\n s2 = [-3 -1 -2]\\n s3 = [-3 -1 -2 -3]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":782,"title":"Some Assembly Required","description":"The input to this function is a matrix of real numbers.  Your job is to assemble the rows of the matrix into one large row that contains all of the individual rows of the matrix, and to make this output row as short as possible.  You accomplish this by joining the rows together at the points at which they overlap.  To help with the task, you can flip rows if you need to do so.\r\n\r\nFor example:\r\n\r\n  input  = [1 1 2 3 ; 4 5 6 7 ; 5 4 8 3]\r\n\r\n  output = [1 1 2 3 8 4 5 6 7]\r\n\r\nExplanation:\r\nThe [1 1 2 3] is the first row of the input.\r\n\r\n[3 8 4 5] is the third row (flipped) so the 3 at the end of the third row overlaps with the 3 at the end of the first row.\r\n\r\n[4 5 6 7] is the second row, with the [4 5] overlapping with the flipped [5 4] from the third row.\r\n\r\nOther than the mirrored version of the solution ([7 6 5 4 8 3 2 1 1] in the above example), each solution will be unique.  Flipped versions of the entered value of y_correct will be tested for as well, in case your code comes up with that version of the correct answer.\r\n\r\nGood luck, and happy hunting.","description_html":"\u003cp\u003eThe input to this function is a matrix of real numbers.  Your job is to assemble the rows of the matrix into one large row that contains all of the individual rows of the matrix, and to make this output row as short as possible.  You accomplish this by joining the rows together at the points at which they overlap.  To help with the task, you can flip rows if you need to do so.\u003c/p\u003e\u003cp\u003eFor example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003einput  = [1 1 2 3 ; 4 5 6 7 ; 5 4 8 3]\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003eoutput = [1 1 2 3 8 4 5 6 7]\r\n\u003c/pre\u003e\u003cp\u003eExplanation:\r\nThe [1 1 2 3] is the first row of the input.\u003c/p\u003e\u003cp\u003e[3 8 4 5] is the third row (flipped) so the 3 at the end of the third row overlaps with the 3 at the end of the first row.\u003c/p\u003e\u003cp\u003e[4 5 6 7] is the second row, with the [4 5] overlapping with the flipped [5 4] from the third row.\u003c/p\u003e\u003cp\u003eOther than the mirrored version of the solution ([7 6 5 4 8 3 2 1 1] in the above example), each solution will be unique.  Flipped versions of the entered value of y_correct will be tested for as well, in case your code comes up with that version of the correct answer.\u003c/p\u003e\u003cp\u003eGood luck, and happy hunting.\u003c/p\u003e","function_template":"function y = assemble_this(x)\r\n  y = x;\r\nend","test_suite":"%%\r\nx= [1 2 ; 2 3 ; 3 4 ; 4 5];\r\ny_correct=[1 2 3 4 5];\r\nassert(isequal(assemble_this(x),y_correct)||isequal(assemble_this(x),fliplr(y_correct)))\r\n%%\r\nx= [1 1 2 3 ; 4 5 6 7 ; 5 4 8 3];\r\ny_correct=[1 1 2 3 8 4 5 6 7];\r\nassert(isequal(assemble_this(x),y_correct)||isequal(assemble_this(x),fliplr(y_correct)))\r\n%%\r\nx=[2 3 ; 4 2 ; 3 1 ; 1 5 ; 5 9];\r\ny_correct=[9 5 1 3 2 4];\r\nassert(isequal(assemble_this(x),y_correct)||isequal(assemble_this(x),fliplr(y_correct)))\r\n%%\r\nx=[10:-1:6 ; 1:5 ; 5:0.25:6];\r\ny_correct=[1:4 5:0.25:6 7:10];\r\nassert(isequal(assemble_this(x),y_correct)||isequal(assemble_this(x),fliplr(y_correct)))\r\n%%\r\nx=[8 16 24 ; 2 4 8 ; 6 4 2];\r\ny_correct=[6 4 2 4 8 16 24];\r\nassert(isequal(assemble_this(x),y_correct)||isequal(assemble_this(x),fliplr(y_correct)))\r\n%%\r\ny=ceil(rand*7)+5;\r\nry=[rand(1,y) y];\r\nfry=fliplr([y ry(1:end-1)]);\r\natf=assemble_this([fry ; ry]);\r\ny_correct=[y fry];\r\nassert(isequal(atf,y_correct)||isequal(atf,fliplr(y_correct)))\r\n%%\r\nt=rand(1,2);\r\nx=[8 16 24 ; 2 4 8 ; 6 4 2 ; 24 t];\r\nat=assemble_this(x);\r\ny_correct=[fliplr(t) 24 16 8 4 2 4 6];\r\nassert(isequal(at,y_correct)||isequal(at,fliplr(y_correct)))\r\n%%\r\nk=5+ceil(8*rand);\r\nx=randperm(k);\r\ny=randperm(k)+k;\r\nat=assemble_this([x x ; x y]);\r\ny_correct=[x x y];\r\nassert(isequal(at,y_correct)||isequal(at,fliplr(y_correct)))\r\n","published":true,"deleted":false,"likes_count":9,"comments_count":6,"created_by":1615,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":130,"test_suite_updated_at":"2018-01-08T18:23:27.000Z","rescore_all_solutions":true,"group_id":19,"created_at":"2012-06-21T18:36:35.000Z","updated_at":"2026-04-03T20:25:05.000Z","published_at":"2012-06-21T18:43:48.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe input to this function is a matrix of real numbers. Your job is to assemble the rows of the matrix into one large row that contains all of the individual rows of the matrix, and to make this output row as short as possible. You accomplish this by joining the rows together at the points at which they overlap. To help with the task, you can flip rows if you need to do so.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[input  = [1 1 2 3 ; 4 5 6 7 ; 5 4 8 3]\\n\\noutput = [1 1 2 3 8 4 5 6 7]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExplanation: The [1 1 2 3] is the first row of the input.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e[3 8 4 5] is the third row (flipped) so the 3 at the end of the third row overlaps with the 3 at the end of the first row.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e[4 5 6 7] is the second row, with the [4 5] overlapping with the flipped [5 4] from the third row.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOther than the mirrored version of the solution ([7 6 5 4 8 3 2 1 1] in the above example), each solution will be unique. Flipped versions of the entered value of y_correct will be tested for as well, in case your code comes up with that version of the correct answer.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGood luck, and happy hunting.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":375,"title":"N-Dimensional Array Slice","description":"Given an N-dimensional array, _A_, an index, _I_, and a dimension, _d_, return the _I_ th elements of _A_ in the _d_ dimension.\r\n\r\nFor Example,\r\n\r\n    array_slice( A, 5, 3 )\r\n\r\nis equivalent to\r\n\r\n    A(:,:,5)\r\n\r\nNote: |eval| and |str2func| cannot be used. This is a Cody restriction.","description_html":"\u003cp\u003eGiven an N-dimensional array, \u003ci\u003eA\u003c/i\u003e, an index, \u003ci\u003eI\u003c/i\u003e, and a dimension, \u003ci\u003ed\u003c/i\u003e, return the \u003ci\u003eI\u003c/i\u003e th elements of \u003ci\u003eA\u003c/i\u003e in the \u003ci\u003ed\u003c/i\u003e dimension.\u003c/p\u003e\u003cp\u003eFor Example,\u003c/p\u003e\u003cpre\u003e    array_slice( A, 5, 3 )\u003c/pre\u003e\u003cp\u003eis equivalent to\u003c/p\u003e\u003cpre\u003e    A(:,:,5)\u003c/pre\u003e\u003cp\u003eNote: \u003ctt\u003eeval\u003c/tt\u003e and \u003ctt\u003estr2func\u003c/tt\u003e cannot be used. This is a Cody restriction.\u003c/p\u003e","function_template":"function S = arraySlice(A,I,d)\r\n  S = A(:,I);\r\nend","test_suite":"%%\r\nA = randn(5,5);\r\nassert(isequal(arraySlice(A,4,2),A(:,4)))\r\n\r\n%%\r\nA = randn(5,5);\r\nassert(isequal(arraySlice(A,4,1),A(4,:)))\r\n\r\n%%\r\nA = randn(5,5);\r\nassert(isequal(arraySlice(A,1,10),A))\r\n\r\n%%\r\nA = randn(5,5,5,3);\r\nassert(isequal(arraySlice(A,3,4),A(:,:,:,3)))\r\n\r\n%%\r\nA = randn(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2);\r\nassert(isequal(arraySlice(A,2,18),A(:,:,:,:,:,:,:,:,:,:,:,:,:,:,:,:,:,2)))","published":true,"deleted":false,"likes_count":13,"comments_count":7,"created_by":134,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":284,"test_suite_updated_at":"2012-02-21T16:23:06.000Z","rescore_all_solutions":false,"group_id":19,"created_at":"2012-02-21T16:23:06.000Z","updated_at":"2026-04-01T12:13:28.000Z","published_at":"2012-02-21T16:23:06.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven an N-dimensional array,\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eA\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, an index,\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eI\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, and a dimension,\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ed\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, return the\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eI\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e th elements of\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eA\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e in the\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ed\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e dimension.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor Example,\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[    array_slice( A, 5, 3 )]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eis equivalent to\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[    A(:,:,5)]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eNote:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eeval\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003estr2func\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e cannot be used. This is a Cody restriction.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":317,"title":"Find the stride of the longest skip sequence","description":"We define a _skip sequence_ as a regularly-spaced list of integers such as might be generated by MATLAB's \u003chttp://www.mathworks.com/help/matlab/ref/colon.html colon operator\u003e. We will call the inter-element increment the _stride_. So the vector 2:3:17 or [2 5 8 11 14 17] is a six-element skip sequence with stride 3.\r\n\r\nGiven the vector a, your job is to find the stride associated with the longest skip sequence you can assemble using any of the elements of a in any order. You can assume that stride is positive and unique.\r\n\r\nExample:\r\n\r\n input  a = [1 5 3 11 7 2 4 9]\r\n output stride is 2\r\n\r\nsince from the elements of a we can build the six-element sequence [1 3 5 7 9 11].","description_html":"\u003cp\u003eWe define a \u003ci\u003eskip sequence\u003c/i\u003e as a regularly-spaced list of integers such as might be generated by MATLAB's \u003ca href=\"http://www.mathworks.com/help/matlab/ref/colon.html\"\u003ecolon operator\u003c/a\u003e. We will call the inter-element increment the \u003ci\u003estride\u003c/i\u003e. So the vector 2:3:17 or [2 5 8 11 14 17] is a six-element skip sequence with stride 3.\u003c/p\u003e\u003cp\u003eGiven the vector a, your job is to find the stride associated with the longest skip sequence you can assemble using any of the elements of a in any order. You can assume that stride is positive and unique.\u003c/p\u003e\u003cp\u003eExample:\u003c/p\u003e\u003cpre\u003e input  a = [1 5 3 11 7 2 4 9]\r\n output stride is 2\u003c/pre\u003e\u003cp\u003esince from the elements of a we can build the six-element sequence [1 3 5 7 9 11].\u003c/p\u003e","function_template":"function stride = skip_sequence_stride(a)\r\n  stride = 0;\r\nend","test_suite":"%%\r\na = [1 5 3 11 7 2 4 9];\r\nstride = 2;\r\nassert(isequal(skip_sequence_stride(a),stride))\r\n\r\n%%\r\na = [1:5:20 23:3:42 2:9:100];\r\nstride = 9;\r\nassert(isequal(skip_sequence_stride(a),stride))\r\n\r\n%%\r\na = [2:2:22 13:17];\r\na = a(randperm(length(a)));\r\nstride = 2;\r\nassert(isequal(skip_sequence_stride(a),stride))\r\n\r\n%%\r\na = 37:5:120;\r\na = a(randperm(length(a)));\r\nstride = 5;\r\nassert(isequal(skip_sequence_stride(a),stride))\r\n\r\n%%\r\na = [1:5 101:10:171 201:205];\r\na = a(randperm(length(a)));\r\nstride = 10;\r\nassert(isequal(skip_sequence_stride(a),stride))\r\n\r\n%%\r\na = [7:17:302 primes(300)];\r\na = sort(a);\r\nstride = 17;\r\nassert(isequal(skip_sequence_stride(a),stride))\r\n","published":true,"deleted":false,"likes_count":9,"comments_count":6,"created_by":7,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":179,"test_suite_updated_at":"2014-02-13T19:31:00.000Z","rescore_all_solutions":false,"group_id":27,"created_at":"2012-02-13T21:03:00.000Z","updated_at":"2026-03-25T13:01:34.000Z","published_at":"2012-02-14T06:35:51.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWe define a\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eskip sequence\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e as a regularly-spaced list of integers such as might be generated by MATLAB's\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www.mathworks.com/help/matlab/ref/colon.html\\\"\u003e\u003cw:r\u003e\u003cw:t\u003ecolon operator\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. We will call the inter-element increment the\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003estride\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e. So the vector 2:3:17 or [2 5 8 11 14 17] is a six-element skip sequence with stride 3.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eGiven the vector a, your job is to find the stride associated with the longest skip sequence you can assemble using any of the elements of a in any order. You can assume that stride is positive and unique.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExample:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ input  a = [1 5 3 11 7 2 4 9]\\n output stride is 2]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003esince from the elements of a we can build the six-element sequence [1 3 5 7 9 11].\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\"},{\"partUri\":\"/matlab/output.xml\",\"contentType\":\"text/xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\" standalone=\\\"no\\\" ?\u003e\u003cembeddedOutputs\u003e\u003cmetaData\u003e\u003cevaluationState\u003emanual\u003c/evaluationState\u003e\u003clayoutState\u003ecode\u003c/layoutState\u003e\u003coutputStatus\u003eready\u003c/outputStatus\u003e\u003c/metaData\u003e\u003coutputArray type=\\\"array\\\"/\u003e\u003cregionArray type=\\\"array\\\"/\u003e\u003c/embeddedOutputs\u003e\"}]}"},{"id":47623,"title":"Create initial basic feasible solution for transportation problems -Minimum Cost Method","description":null,"description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none solid rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 1208px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 604px; transform-origin: 407px 604px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003ePrevious Problem : \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://www.mathworks.com/matlabcentral/cody/problems/47618\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eProblem 47618\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eConsider following transportation problem:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 359px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 179.5px; text-align: left; transform-origin: 384px 179.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" width=\"808\" height=\"353\" style=\"vertical-align: baseline;width: 808px;height: 353px\" 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\" data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eYou should return the assignment matrix where the total cost is minimum. In this case assignment matrix should be:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 80px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 40px; transform-origin: 404px 40px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10px; transform-origin: 404px 10px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eassignmentMatrix = [\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10px; transform-origin: 404px 10px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    0 0 0 40\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10px; transform-origin: 404px 10px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    10 10 30 0\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10px; transform-origin: 404px 10px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e    0 10 0 0];\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eAnd total cost should be 410.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [assignmentMatrix, totalCost] = minimumCostMethod(x)\r\n\r\nend","test_suite":"%%\r\nx = [1 5 7 1 40;\r\n    9 8 6 10 50;\r\n    4 2 2 3 10;\r\n    10 20 30 40 100];\r\nassignmentMatrix = [\r\n    0 0 0 40\r\n    10 10 30 0\r\n    0 10 0 0];\r\ntotalCost = 410;\r\n[assignmentSolution, totalCostSolution] = minimumCostMethod(x)\r\nassert(isequal(assignmentMatrix, assignmentSolution))\r\nassert(isequal(totalCost, totalCostSolution))\r\n\r\n\t\r\n%%\r\nx = [ 5 1 8 9 50;\r\n    1 2 4 6 40;\r\n    7 9 1 6 90;\r\n    20 35 40 85 180];\r\nassignmentMatrix = [\r\n    0 35 0 15;\r\n    20 0 0 20;\r\n    0 0 40 50];\r\ntotalCost = 650;\r\n[assignmentSolution, totalCostSolution] = minimumCostMethod(x);\r\nassert(isequal(assignmentMatrix, assignmentSolution))\r\nassert(isequal(totalCost, totalCostSolution))\r\n\r\n\t\r\n%%\r\nx = [5 6 25;\r\n    5 8 50 ;\r\n    7 3 25;\r\n    9 3 30;\r\n    90 40 130];\r\nassignmentMatrix = [\r\n    25 0;\r\n    50 0;\r\n    15 10;\r\n    0 30];\r\ntotalCost = 600;\r\n[assignmentSolution, totalCostSolution] = minimumCostMethod(x);\r\nassert(isequal(assignmentMatrix, assignmentSolution))\r\nassert(isequal(totalCost, totalCostSolution))\r\n\r\n\t\r\n%%\r\nx = magic(5);\r\nx(end+1,end+1) = 280;\r\nx(:,end) = [20;60;120;40;40;280];\r\nx(end,:) = [90 50 45 35 60 280];\r\nassignmentMatrix = [\r\n    0 0 20 0 0;\r\n    0 50 10 0 0;\r\n    90 0 15 0 15;\r\n    0 0 0 0 40;\r\n    0 0 0 35 5];\r\ntotalCost = 1460;\r\n[assignmentSolution, totalCostSolution] = minimumCostMethod(x);\r\nassert(isequal(assignmentMatrix, assignmentSolution))\r\nassert(isequal(totalCost, totalCostSolution))\r\n\r\n\r\n\t\r\n%%\r\nx = [1 2 3 4 50;\r\n    4 5 6 7 50;\r\n    8 4 9 4 50;\r\n    10 11 4 12 20;\r\n    40 80 30 20 170];\r\nassignmentMatrix = [\r\n    40 10 0 0;\r\n    0 40 10 0;\r\n    0 30 0 20;\r\n    0 0 20 0];\r\ntotalCost = 600;\r\n[assignmentSolution, totalCostSolution] = minimumCostMethod(x);\r\nassert(isequal(assignmentMatrix, assignmentSolution))\r\nassert(isequal(totalCost, totalCostSolution))\r\n\r\n\r\n%%\r\nx = rand(9);\r\nx(end+1,end+1) = 450;\r\nx(end,1:end-1) = 10:10:90;\r\nx(1:end-1,end) = 10:10:90;\r\n[assignmentSolution, totalCostSolution] = minimumCostMethod(x);\r\nassert(all(sum(assignmentSolution)==(10:10:90)))\r\nassert(all(sum(assignmentSolution,2)==(10:10:90)'))\r\n\r\n\r\n\r\n","published":true,"deleted":false,"likes_count":7,"comments_count":3,"created_by":8703,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":44,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-11-26T09:56:27.000Z","updated_at":"2026-03-19T01:55:24.000Z","published_at":"2020-11-26T11:20:48.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ePrevious Problem : \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.mathworks.com/matlabcentral/cody/problems/47618\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eProblem 47618\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eConsider following transportation problem:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"353\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"808\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"533\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"996\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId2\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou should return the assignment matrix where the total cost is minimum. In this case assignment matrix should be:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[assignmentMatrix = [\\n    0 0 0 40\\n    10 10 30 0\\n    0 10 0 0];]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eAnd total cost should be 410.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc 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e8CRekbilKFolT49NfJ/MfxOQETn7PSx3jYKdpHUWKNE/jD+JzA5jN0B6KP8bBTlKL0CUWpQlEqUBSFolShKBUoikJRqjzvohjj78zVRvPgyrai3LkpdhI71rNtZOwUf7Flsm/866n7ux2Os9jdiXeJ42GH0A/C5g9pLYr75/+7XtqHC/fg7ozn77jWsSju/3a2F8WNkZ207Wz8/Ktz44u6+UUbOUkej/BmPyobPmRDUcIN7/z90szUlSIUZdG9KBun6A6xf79pTCyb/+r+bmOy7UUbSR0P+2Y/CJs/ZH1R9ganKH2Mh52iFKVPKEoVilKBoigUpQpFqUBRFIpShaJUoChKT0UBAACAZ4w7/RZGhCvK9yefm1/58uxD8X7Ll/G5Oz+Jzwn0sCaZPh498IF7+L57+ND83D3tg5nqdKAoPVIUxfI980Vs7Ya7IacJv2RHUXqkUhTLJ+brsbUDtihv3LFIC0XpkXpRLMb8Nra2YYviDhC7K4UoSo+sKYrFmO/G1kbC4ouk9M36okwm3zDmF7HZil33Wk4uw5SgKD3SVhTLz4z5aWxuh6L0yIaiWH5pzI9jcwsbR8ZOLPv/1C3t2tlYlAszuXafottFa9n8R7ugNZNL97CBzeNhNwHcuuZs44isww17bBa0Dsjmolj+aPNICFuL4v4lFSVMzY0Ds/mP7iPuJ5Plxiu6txXFfcfN5hFZx9ohax3crUWx/HCHumwrip+q+Yvi0rLxVduLMg/P+zGTb/dnNq7s82xmH27WD4sWxe0yaR/cb5qvYquFbUW5dQOVXpT2IXRs/GucLFtetb0oy+sORfFf7f73RZFn2/fyNv69TJGUjcNq+Y75OLbWsa0ofpIkFmXqfnx+0+/2bBwFPwTuRws2vmpbUezK5sa5t51SMeTZ/YxC/GuFWlHM9No+3IeThpf1Xyj5tvlWbDXYPDKX/su9JFvZWBQbNGNdsGVybP6j/Yhb9wk3scdaNo+HuQll3TspZm6XVHM3+DEhk8XcD+7aQS4VxY2wmbnl3cIm9MbXpcFvzNdiq8rGkdmJjUXZjbVjuB/p47EFWxTL5iEtJ2VpH9xSM+REdqA0+J35QWyVoCg7UilKS2obiy/XcBc7tBfF0jz8QlF6RIty73+6zC3C5q6Y5nLtZSgFtcMvFKVHiqTsT/nwC0XpkZSiWPTwC0XpkcSiWMLhF4rSI+lFsRjzXYrSI74o/9c8lf/GbuVAb/jSpNPD56RHxc9hafQwHn8cT53vzq/jJ6VCURSKUoGiVKEoCkWpQFGqUBSFolSgKFUoikJRKlCUKhRFoSgVKEoViqJQlAoUpQpFUShKhcMpysWNu6px2z5+iqJsKcq7+KOtG9helHheI0XZle1JMVt+b2mHxZfx96mlKLuyuSif2X89FMVW5Z6i7M7Govh7BqcXZTbxPxpNUXZlY1HcEfgeimLc1S0UZXe2O+Xdll/L32XxtQsURdlelG30W5SUG6LGoqScX+OL4q8C6UwP4zG2oiRMjViUpE/wRblJ+pAexuMZFqXD5YRKb4sviiKExdebhM+IRXkIT52gKFWi6NOLkjIUPYwHRanA4qtKHJmU+7i7otwmndwcipKy9OpjPMZWlCRiUhLoLSlJUJQKFKUKRVEoSgWKUoWiKBSlAkWpQlGUnoryQTrmy2Q+js/d+TA+J9DDePzdP03lH/ripkNSFBZfFShKFYqiUJQKFKUKRVEoSgWKUoWiKBSlAkWpQlEUilKBolShKApFqUBRqlAUhaJUOKCi3Lq7wNxvvBUMRSkxRFFsNVaTi21nw1MUZXNRzOlLf4ndJrYXJVYj/HB+KxRF2VyUI/sv/UouWxU3pLPNJw1SFGXL4su87KMok5W7anvjDWkoSoltTunlmke76HqwZrmM3euhKMoQRTl2d15bbLtmjaIoG4ti3vtfnHgRO9ezy+JrFyiKsi0p2+m1KLeNW6vtgy+K2Xh7ui3EorTeIGkHQlHc47G7yU8XRlaU+8lNwoUdrihpV5GGoiR8QLko7o5xnRhbUiaThOtIY1LcD8F0xBclqSbx3fbR/t9xXEZWFLtCsO4Gnzvii7JlG3UzUpSEzwhvDZ/xPIqSNDlE9Akf0WdR3K0+fXtvxlaUm413G91CdEpC1nxRuk9NhxbFLkafR1G2bPVvwSfF/WBSZ4LoH1J+H8F//YXbKLvcsl+8ldEtvlKIi68EQlGS6GE8KEoFilKFoigUpQJFqUJRFIpSgaJUoSjKiIryF8n8jfjcnX8dnxPoYTz+6Z+l8vfiRE2FpCgsvipQlCoURaEoFShKFYqiUJQKFKUKRVEoSgWKUoWiKBSlAkWpQlEUilKBolShKApFqXBARfEXom479YeiKEMUxV+IOp3MNg8uRVG2FMWEez1uYntR4tVCC6553JHtRUm/kitciHrDlVy7MkhRwoWoWwaXoihDFMUO5vJh61nTFEUZoij+QtSt906kKMr2onAh6n48flF2oOeipIyTL8q2RG7EF2WV9BH+vcf+Zu9dGVtRFqlFSbviJxRlskq4QCV+e8p4PL+kpBfFch+fOxC//RndvW7ZR1ESiEVJuaAsjMBtyniMqyh2NS1leR6KkrI070/0KfeKfH6Lr6Q7Z/ZXlJSwPbuipGXNF8V+QsKPkfhvN0mzxuiKkkJvTkmhh/GgKBUoShWKolCUChSlCkVRKEoFilKFoigjKsqvk/nr+Nyd0/icwDjGI07UVDYeSduNHuaw+JzAOMYjTtRUKIpCUSpQlCoURaEoFShKFYqiUJQKFKUKRVEoSgWKUoWiKBSlAkWpQlEUilKBolShKMpjFcUYs+l83DWnAW0ZmVf239uz0G5j88icn7sH9zntbCmKOXUPod3GtqLYv6eNh8V9x8YPaUmKneqbyrJ3UfxwbBnjjSNjrk78Xd/cdG1lc1FO3PvNlStuO1vG487+PWU87uw/PwgbP6S9KFP779jdnvZmMVksbft4cmF8OcJjlS0jY/8c/t/Atjlsh1vxxec27JvtVHETppXNg7jLQGwtihuEzR/SXpSlm/azS1eIY18HGx1zb5dcZnKTpSjbP2Lb4stcndqkbfyIzYN4bv++bSC2FcUPwuYPaS9KjIV78mfTO83Ytu+boyhH2z9iW1Lenr61Utp4advGz3/n/p40HrYofhA2f8gGp9jJfz+5kKLY/9KKsm0e3VIUJ0b7/o1G2FYUi9m89NoyiO7vSePhvtwNwuYPWV+UG7v69RCuVHuwVbh2izJ36rW5tA+3ZmUaN2PcMjLuz2bz5NhcFPf1dlbd/DWbi2LuPrq6enm6+ecetoyH+3vKeLyWQdj4IS1J2ZttI7MDm5OyCzskZRvjGI84UVOhKApFqUBRqlAUhaJUoChVKIpCUSpQlCoURaEoFShKFYqiUJQKFKUKRVEoSgWKUoWiKBSlAkUBAAAAAACAQ+Lf/1fLEfC//2cf5Ocf//3YyMoyPmfln/xRbGRlFJPiby5DUMx/8TVjzG++EbpyYb6MjZz85EexkZXmidoZ+HQM9RjHpPggDoX5vn/67rdsXL7tm4/H9NpdWuEuEavfNpKgKARFGWNQAr/92MblO7HjcQhBqUNQFIKijDcoga9/Zcwn34wdfSNBMfb7l/72kb6LoAgERRl7UAJfWLl874exoz9iUKYuKDYtsqVEUASCojyNoAR+buPyYZybeyEG5ToG5dL3JCgFBEV5SkHx/PhXNi6f/zJ2pSGrXtc2I9fmxvcjKCUIivLkghL46Q9sXH73s9jVLwRFISjKEw1K4BePctilc1Dmdmgc17H7Yt0+tR3pHhR/E1hLWJE8tq3uQ9F57liGYYhf7X7CpftdwrsHxY28o1hd7z4tdp4UK/eN09X2TYSFX+Pfi65BCfR92KW7Uexw2Ec3pWJnjqDY9Un300E2L3Zd0mbWzaXhL/vT+Y1xUoQnd3twOxSuuwvdg2Lj6iowNSbc49xujD56UG5DLOfbg2ILFVs7kxaUwG97O+ySGhRXGL+rOWtQZGCSBmPvSirx2+3AhM8wM//UheSguIFxYXU/Rfbok+KN/bL4JW7cw1LzwZhb27BS9b6x2D+7oLhOG6n7HT+9j6AE+jjskhwUmTuyB8Uv1S7NrXvqxI71W0OcBG4VzHdbwXW9y3gvQbmYPFjBDhAU7y2LTaYfd/9gB8TWwn+773YZCQ+he9f7pzeD4t9ugxb/sCdph12Sg2JXPv28mT0oodM9dqT7e+O325kmHsd1vyjZjV6C4iZLwP9lf3Z9XzCnXS7EaeAfJCiV7hAU22Mm+1u30haU5USOlneh62GX1KDYeIffF80alDAs7sniVjy6EOvSgfD1dsvEL0RtFboHNjkoYVgcCRXZdfDjOqb7ymP7EFa9JCh2U8l3ewPEoNg+O8+kLUFxv5numlObT/cz6q4d/uZ2Zyy84twrNrL/YZeuQXGDY5m+KXeGyOxP56CErzW3Phu2IB7/lw50faPdSnMchz1dq6mZdZ0Ols5BCQNhruOBZMsAQbE5uTWzsPPgwkxdUKY+KNfut5v9QF0uZn7JYXF9VruueLUF5T4kLX6cH0d/sonv4Vv2+92ftvONfQ67dDdKj3Q3Sp/sOHkfl+5G6ZOkSRGM4omzs7CYTvbYdmtf9fJNvxRoCYp8/y787d0OuxAUJdYlL08/KHY+FZe5VvmjLvZa52gLiid+hd8Y9McG/N+6BCXwL7YddiEoihYhJ8/AKH3RDMqj89v2wy4ERSEoyqEGJTD/ysalftiFoCgERTnsoATcYZevisMuBEUhKApBEdxhl4/dJg9BUQiKMq6g/LuvcvPvbFzMj/Lzz/8yNrIyhinxo8+/io2sjGJS/IkEJTxl5tNRDMaPfhIbOZElWF7GUY/0nz1P59cEpQFBUQiKQFCaEBSFoAgEpQlBUQiKQFCaEBSFoAgEpQlBUQiKQFCaEBSFoAgEpQlBUQiKQFCaEBSFoAgEpQlBUQiKQFCaEBSFoAgEpQlBUQiKQFCaEBSFoAgEpQlBUQiKQFCaEBSFoAh9BMX9tquZh59ISvkZeYJSgqAoqUEx4encvAqNTvQQlPirLfGRoPQDQVHSgnLyzgfFvHAPp67ZiV6CUroDB0HpCYKiJAXl/MQbJaQlPHail20UfwMd+eFXgtILBEVJCYpLhv/nI3LXXSk9BMX/ILjcM4eg9ARBUboH5eWde3QZee2DktcoYb1rHp4ISk8QFKWXjXnz3j2cu2YnegjK0v1m+tT/brlbBev+M/IEpQRBUXoJytXRu/fmxLc60cs2Sm8QFIWgKKlB6YXRBmWZthKXQiko/i4nsT0sRVC8pTMNxTjqQVDqVIwygqDM452JMlAzSrwx0NCMox4Epc7YgvLG3VostgemGpTLTEMxjnoQlDpjC4rjjSnurzYg1aDkKs846kFQ6owxKJMRBOUhz4oXQSkgKE00KP5Ez+MsOakEZZWtOuOoB0GpUwlKNmpGyUNtYz4T46gHQalDUBSCohCUBgRFISgKQWlAUBSCohCUBgRFISgKQWlAUBSCohCUBgRFISjKuIIyEj4YAX/yB7GRk+UoJsU46vHXv87PqQQlPGUGoygYRWHVqwFBUQiKQlAaEBSFoCgEpQFBUQiKQlAaEBSFoCgEpQFBUQiKQlAaEBSFoCgEpQFBUQiKQlAaEBSFoCgEpQFBUQiKQlAaEBSFoCgEpQFBUQiKQlAaEBSFoCgEpQFBUQiKQlAaEBSFoCjPJihmtppc+58e9bfeug59u0BQFIKiJAXlzs2SrvHu/DTzbR+MWbknmw8XkWnKj/USFIWgKClBeSX3ohvBjYQuXGb15kG2K7Y6QFAUgqIkBOXUzZsvbePIW+Uu663p3G+tO0Lb3IbnThAUhaAoqdsobtVLbnbqQtOJHoISkrHwSbkP9wbuCkFRCIqSvDFvQxJuc3qe1ShhG2XhPsGbJcEpBEUhKEpqUO785skL99D57tn9rHr1BkFRCIqSEJSXZz4gjpMj8yo2u0BQmhAU5akHpT/GGhS/sTM7Dh0DUwTFD07+Gwldhx3wGSgGYr6K90c5tk/D3imPoDQogmKW/jFlF1pnSkFx359nLi2Cskq4cX8q5dkiBOXB90o5BrA3BKVBKSihHllu8lRa9ZrFo6nDUwTFzGYXxtzErmEpzxahGKEw0/IfHhuC0qC0jbKczd6EpdfgFEGZP0zmgy48CzQoSy/XNybLbRzL405QHEOOeDvVjfnbTEtzDcqFHxy/43twSka5949+XXRoyqMegjL3vczCPQ4EQWlQDsp9no1oS2GUmTt7Lc+kKW3Mu9Wu2VhWvSY3tt9xwomv+0NQGlSNkovSNko+SkHJyDjqQVDqEBSFoCgEpQFBUQiKQlAaEBSFoCgEpQFBUQiKQlAaEBSFoCgEpQFBUQiKMq6gjIS/GAFf/o3YyMm/HsWkGEc9/umf5efvSVDCU2YwioJRFFa9GhAUhaAoBKUBQVEIikJQGhAUhaAoBKUBQVEIikJQGhAUhaAoBKUBQVEIikJQGhAUhaAoBKUBQVEIikJQGhAUhaAoBKUBQVEIikJQGhAUhaAoBKUBQVEIikJQGhAUhaAoBKUBQVEIivJsglLc7NRfUpJwLyGCohAUJSkob8O9tsZ1s1PHMuUnSAmKQlCUNKPEoIzsZqc3M5PyI7kERSEoSh9BGd/NTucp614ERSEoSh9BGdvNTi1L0/32PwRFIShKH0EZ181OrUwuLxNyQlAKCIrSzzYKNzvtHYKiPPmgnLqNAt/iZqe9Q1CUJx+U3hhzUFJ2NKegQblc+H16sWtYiqCYpdtbkueeSjoQD5cZ60FQ6pSD8ubNMldhKkZZ5ZlHa0ZJ2fJLoDIQq1z1ICh1SkGZuf1nsT0w1aBcZ7nhaiMo8XlgSl/7xoR75A0PQWlQBMXdI3AUQTnOc0+4alAu8/ikPltkWvciKA00KFPHsZlmWZqXgnIz6M0Ky5SDkq841W8ON38dHILSoLoxn90oNzap0+ksy+K8tDHvlxp5pkUxEHaJMc+01CAoDapByUV1GyUTtW2UTIyjHgSlDkFRCIpCUBoQFIWgKASlAUFRCIpCUBoQFIWgKASlAUFRCIpCUBoQFIWgKOMKykj4cgR89XFs5OTDUUyKcdTj7/5pfv6hBCU8ZebT7leg9cgfjmMJFhtZoR7C2Fa94mBlhaAo1EMgKE0IikI9BILShKAo1EMgKE0IikI9BILShKAo1EMgKE0IikI9BILShKAo1EMgKE0IikI9BILShKAo1EMgKE0IikI9BILShKAo1EMgKE0IikI9BILShKAo1EMgKE0IikI9hH2CYoyZXE6NeYjd+6G3r9tAUlBeGXMXG1dXZwk/8Z9QmBNz9NqYt751dXV3FPp2ISUor9/dGX/Pwquzj9Jm9pT3WsIdF3LV4zze8KGYCglDsm9QwlOXn61+9KDYieGD8sJ/iHnnHjuREBQXEX+/wLf+DrRSqQ6kGsW8dg8uqacJn5Q0ECfn/p6J+eoRb9moUyFlSDoEZe6f5zYt7m6NF8a4HubGPbgXTd0LLycTq55j28v9uqD7g20OFJQwdybMo6mqPzqXr0+6uWZsdOPIRfY03Don4V64KQPx2dsw/vnqESZ/MRVShqRDUJbu+d61pzYG/v4httfS/d1GYTF1SbJpsUGJbwnvO5igvLOij1+fLygnbgBOw63Y8gTFvXUkQZGpkDIkHYKycL//72PgqATF5uPYmSZrUM7C5Dhzj51IC0r43o/8QLzuPj7JG/Nu9vA3Lnzb/Va4CUGxRQ9krEdcTulUSBmS/YNi16fcJortmE+OG0Gx8bi0RlmUg3LpVsWuBwuKf0pYlicFxX/tW1uZd7YcboO+KylBcZtHH33mGu5DjDNcRxIGwhGqkK0e8UuLqZAwJPsE5fFJDEpPpBmlJ5KN0gvUQyAoTQiKQj0EgtKEoCjUQyAoTQiKQj0EgtKEoCjUQyAoTQiKQj0EgtKEoCjUQyAoTQiKQj0EgtKEoCjUQyAoTQiKQj0EgtKEoCjUQyAoTQiKQj0EgtKEoCjUQyAoTQiKQj0EgtKEoCjUQ9CgAMAmQlAAAAAAAAAAAAAAAAAAAPbk9+6XI+B//D8+GAHL+JyVf/L3YyMro5gUf/OPYiMrS5+TL+LBeQBYi8/Jp8Yl5Xs/9B3Z+MkoTqIZxUB8+qPYyMooJsUHX8ZGViQn9uE7Niof/9Z3Pyo+noHYJ0JOFHKijC4nlp/beffDsCr2eLjvChmp1YGcKOREGWNOLN+2s/C3vhs7HoW5/Rdycum7FXKikBNlpDmZTH78KzsXf/7L2PU4hJzUICcKOVFGmxPLN35jZ+Sv/SJ2PQKSkwtzeW9ufJOclCAnyphzYvnpD+y8/Lufxa6+iTlZultxqVrIiUJOlJHnxPKz39nZ+Qc/jV29EnPib1FvzLHvR04KyIky/pxYfvE1O0f/5huxqz80JxfaJiclyInyJHJi+eXndkb+1Y9jV0+Qk82QE+Wp5MTy3W/ZefnbsaMXyMlmyInyhHJiWX5oZ+efx450YjYWYfvk3vcjJwXkRHlaObH89mM7d38ndiQiDnFPZuab5KQEOVGeXE4sP/yencG/iB3dsR/icM1rM3PH5z3kRCEnylPMieXrXxnzyTdjR7+QE4WcKE80J5ZvfmLMV1+PHT1CThRyojzdnFge5XKV7jmZhRU5E0+sXC0SKtz5rfM4ENe+a+WaK9/sQPecHPthMCac9e27fKsLnd+59INgzDR2u/Xr2Nib3XMydV+5XMSudi7ty2JzZ8Ib9s6Jpf/LVbrn5MLvYL4O86ifX0P/LnR/a/ja+OVuILoPRvec2FnUzp12GriTHGY3buaJpzvsTw+TIi4pbrpPip1zMvVfNtvhizoUJryhS04sPV+ukpoTpxV/TuWie1XSZw4nksnkwbbs4HSdOKk5cfGIe9uN7k/cm9RJUcyQ2tifnXMSv2KHL+owNOENHXNi6fNyleSc2KWW/wg7k7inbnR/a/x2+xTOgLaDky0nxbyQsPaXPCnsksKndWaHyj13YY+c+DVeNyNsQafN7oQ3dM+JpbfLVZJzIhMgb050TceaxT93oJec+Hzcds5qD5PC1sU9X98MkxNZLtm1zovJg/tKv5VosT1t961tyVWCdiXd9RXrbiMMflJOJpMf93O5Si85cZvyeXMSZ47J5N5dNdCNXnISZ4m4Y6EDyZPCDox9vnlwDd+/AzvnxG2ex6S42SF8pR+AmVv1tN3HLjd26eF7+oedRzG8LjEnlm/0cLlKLzlx02kkOUkYil5y4ieJ26vhnruQPClCTsJM6vt3YOecRHk4l9dyYiviB8HOG37q+J5hrfiNf+d2wuBLTtx4RUKPffi91MtVnsl6l7O7e77pvmHQT07CSkjCVlLypHjjnl1rkJzE+dduHNZyYpuX7sHnxHb7B/+441qXfbF/LHxiZzE7xy07HoD420mXqzyTnCzsirDv3HVZtYYet+NtK1tO7EbAsWt7Og7FPjnxyfTCqOdk2czJvV0H23mXuR+dRk7Cfs1OfND9cpXknNh1DD+P5M1JfDp2mwc7L69qJOfErqzL7uDuE6OPSbFyD57HzokvvY3m2pzEsIRu/+CeFjsb37+hkRMflc78i46XqyTnJI5/3pzYxVTMrMP/YX+Sc+K/+sFnJSw7upA6KewqX/zuMNN2YuechL3x125PjitBOIjmB8SWpMiJXXTFuuwzm4RX1nPi9tPYec/YxZJdhVhNzdQFz/a4mBy7wXnws8IG/qjL5Srdc2I3CRZuQsRF6GyPCdCg+1vtKF+6VQ0nkbhDsuuupu458ZsEN3YK2Io9+GEQr+xP0qRYujnIr4BaBsmJWVza73ST3I+2/0rbcGvC1u1hAVL0dM+76z68oZaTle+0TVdtO+XndukYdjK6bVS7ZWbZ+hW/3ftylc45ccNjuQ0WjV2+3YHEgZiGrZLYFQ447k/nnMTvvQ5nutkF6bT2Y4L70HVS2DnH4dc8A0PkZDW5PA4LdJeMe/uV9jvtw+Vi5lb5bPfy2l0XGKaRe9UeS5Aw+JWcyKfY5sNkems/1nbEB/vJ/q/xJVvY83KV7j7pk1EMRHef9MkoJsV+2/F1ihnV5SQ2hbScXFyGc8ls0z1ZkdtHf9TKr5NFfek7NrPP5SrkRCEnyiPlxO2130O14VPq2ye+M+bErmXaxxiRvXNi2flyFXKikBPlkXIyMxf7bLiFT6nnxG9+9ZUTi7tc5autl6uQE4WcKEk5sfNdnFPd5orsffMs9jqpKHxIPSfSdE92W94++hOnOufE4i5X+cvNl6uQE4WcKGk+6YswKTblxBpqpWHpnhOLu1zlz+vbUiXIiUJOlFHmxO0IltU22ww7f2cz9388J8Af6PX7i7vgLlf5su1yFXKikBNlnD55fNzlKv987eUq5EQhJ8qh5iRernLcvFyFnCjkRDncnFj85So/ql2uQk4UcqIcdE4sP3WXq/zf5ctVyIlCTpRDz4nlZ+5ylb/Sy1XIiUJOFHLi+IW7XOX74XIVcqKQE4WcRP6Ou1zlf7UNcqKQE4WcFPwrd7nKf0pOFHKijCkn/8Z8lZv/6D+3UfmTH+XHxOesfP6XsZGVUUyKP/kqNrIScvL7fzkfAf+fTQrAKPE5+XQUbpuY78dGVkaxtjGKgfjJOOpxNQLISQNyIpAThZw0ICcCOVHISQNyIpAThZw0ICcCOVHISQNyIpAThZw0ICcCOVHISQNyIpAThZw0ICcCOVHISQNyIpAThZw0ICcCOVHISQNyIpAThZw0ICcCOVHISQNyIpAThZw0ICcCOVHISQNyIpAThZw0ICcCOVHISQNyIpAThZw0ICcCOVHISQNyIpAThZw0ICcCOVHISQNyIpAThZw0ICcCOVHISQNyIpAThZw0ICcCOVHISQNyIpAThZw0ICcCOVHISQNyIpAThZw0ICcCOVHISQNyIpATpYecuF+9X0wuXHO1SKovOVHIiZKYk/fh/a/MkX/uSHpOzMw+3Bibk7neJ6Ij5EQhJ0piTox//9E72zrxPTqRnJM3LiGTyaV/XJCTniAnSlpOznxOTt3DXcInJefkwpiVf3YPU3LSE+REScrJq1OfkyAV89I9diI5Jyu/dRIhJ31BTpSknLwOETHnriM8diI5J5Njt1XitlEs5KQvyImSkpMzO4f7nLxwXcEqnUjPiVvzsty4JjnpC3KiJOTko1PJyZ3rzJuTyeTaBcU1yElfkBMlISduV/BIcjL1j3bly3eQk54gJ0rCzO0ffE7Cetdr99iJ9Jz4vV0TctIv5ERJyEnkLibEfOR7dyE9J+ETyEm/jGIgnv52vMX75Nw9+IMoHQn1SMqJuZhczsJBlBk56QlyovSRE38s/uyd79GJ9JxMJvfG3LpmtJzv3QlyopATpZecnJjT8+5HT3rISZ+QE4WcKIk56Qdy0oCcCOREGW9Owg7nDJRmUX8INbaHpfhWvy6bZygqOclXjzirZmWsOUncc5ZC6YvdDHod28OiA3HjU2IeYueglHKSsx5xVs3KWHNiF+WxMTjFF8/9yThZ0IEIZ86F3YlDU/ZJxnrEWTUr5KRB8cXZBqHx1XmGhJwoYezJSQn94qVd31nG9tBUx/4+y2oXOSkgJw2KnFwscm2e1HKSZ7WLnBSQkwaVL55lMkotJ/F5YMiJEsaenJSozaJ5hqPyrfM8q13kpCCMPTkpUf3ieZ7hqHxrptUuclIQxp6clKh9cZ7hqHxrrklBTpQw9uSkRPWL7+exMSzlgci12kVOCshJA/3i6eVksoq/kDE05bHPtdpFTgpGm5OFuY+todEZwp0v4i8YyEAlJ/F5cMo5yViPOKtmZbQ5yUe22bLMKAainJN8kJM65EQhJwo5qUNOFHKikJM65EQhJwo5qUNOFHKikJM65EQhJwo5qUNOFHKikJM65EQhJwo5qUNOFHKikJM65EQhJwo5qUNOFHKikJM65EQhJwo5qUNOFHKikJM65EQhJ8qIcvKFO4V8BPzVByPAxOesjGIg/mAc9fj1CAg5+f0P4zDlxXzvyxFg4nNWRjEQH4+jHn86AljvasB6l8B6l0JOGpATgZwo5KQBORHIiUJOGpATgZwo5KQBORHIiUJOGpATgZwo5KQBORHIiUJOGpATgZwo5KQBORHIiUJOGpATgZwo5KQBORHIiUJOGpATgZwo5KQBORHIiUJOGpATgZwo5KQBORHIiUJOGpATgZwo5KQBORHIiUJOGpATgZwo5KQBORHIiUJOGpATgZwo5KQBORHIiUJOGpATgZwo5KQBORHIiUJOGpATgZwo5KQBORHIiUJOGpATgZwo5KQBORHIiUJOGpATgZwo5KQBORHIidJDTi6PzcNkcmFbq6m5Dv26QU4UcqI8k5xcm/lkaYzNyY2/h0ns3QVyopATJSknbo58YZ9PzPsXR6FXJ5JzsjK37unY5sRcruxQWbd0hZwo5ERJycmr96enp65hTq6uXr/z/TqRnJMLswjPk6V7ShIKOVHIiZKSE3nvO9d4mfBJyTmZGzOLTYcxx7HVAXKikBMlYe4+9etcFuM/xNz5ji4k58QZxMxWscN2XcZWB8iJQk6UFAtYXvvGuX88c4+dSM+J2yYxZhq7KnLZF3KikBMlISd2+/3MhyOYJFilE+k5cXu8LGF1a5FUX3KikBMlKSdXVy+M3ZAfRU4mk1sbFPd8aXQFrAvkRCEnSmJO/DpX/pyEFS678uWezI3v6go5UciJkpqTdy4nYfuk+47h9Jz4wyd2+90+HLuYhO5OkBOFnCjJOXklJjFvfY8upOfEH2dcuQ35udtO4fhJL5ATJXm9y/47dQ+fJXxSek4uL1w4bFjCji9y0gvkROk+d9/Z1a14cPHohZ3XT3yzE8k56RNyopATJcEC78zr97F5l7BxYiEnDciJ8DzWu3qBnDQgJwI5UcaaEzOfJ+5k7kwxix5fTN5kmmErX3tt7mNrWMo5mcYhujHLadJFRntDTuoUOXHHKxMPWnZGZ9Frd2xonico5W9Nu/gtgVJOVnKmhXsaNrbkpI7m5N4PVtK5Yt3RWdTPn0vtHJTSt6acgZ1G2ScXYYhm7imUZyjISR3Nia+Gqn5g9Fv9UFxnDmucFllYk5Nwwqvx1xoNBDmpozkJB2Fy52RlzOomzzAUA3EZrhfNQjMnK3d9tx26hItW94ac1NGcXPsFVu6cuAv+h5whyuhAHJvb6+t4zejQNHOyDCbRyyiGgJzUKW3H2234ecqh/QRK3zrzJxrkQAfCT4Rlnk359pwMuTJKTuoUOZk82CV57u1418oVFB2IsLDIs8jAJ0qY/uPLieUi5RLiBHSWXLiVrtxSC9+fdv1bV9Ztx4ftkyF3DJOTOtWc5NofWsyiYZ7w7aHRbz32rTybauty4ooy7L5yclKnkpNZnrWu0iwaNgqyzKHFt6780dYQ2aFZkxP/dDxoachJnXJOZkOuAlfQWfTSte7zHAzXgZhc2+ZNnmXGmpxMZnMb3dAcCHJSR3Nyke1UDUsxF6ymxl+imYHSrLicZTq9q5wTd2FRWHJdD10bclKnun2Si2GXli2MYiDKPskHOalDThRyopCTOuREIScKOalDThRyopCTOuREIScKOalDThRyopCTOuREIScKOalDThRyopCTOuREIScKOalDThRyopCTOuREIScKOalDThRyopCTOuREIScKOalDThRyoowoJ1/4GzLk5/O/GAEmPmdlFAPxN8ZRjz8bAePyCTkRyIlCTuqw3qWw3qWwfVKHnCjkRCEndciJQk4UclKHnCjkRCEndciJQk4UclKHnCjkRCEndciJQk4UclKHnCjkRCEndciJQk4UclKHnCjkRCEndciJQk4UclKHnCjkRCEndciJQk4UclKHnCjkRCEndciJQk4UclKHnCjkRCEndciJQk4UclKHnCjkRCEndciJQk4UclKHnCjkRCEndciJQk4UclKHnCjkRCEndciJQk4UclKHnCjkRCEndciJQk4UclKHnCjkRCEndciJQk4UclKHnCjkRCEndciJQk6U55KTy2PzMJlc2NbqwRyvQs9OkBOFnCjPJCfXZj5ZGmNzMvf3MEkICjlRyImSlJMX8d0n5v2Lo9DsRHJOVubWPR1fTFaXrstMfe9OkBOFnCgpOXn7Lr7bnFxdvX4X2l1IzsmFWYRn/zgx1i6dIScKOVGSfHIa3u3j8jLhk5JzYle2ZrFpWblNlc6QE4WcKH3kxPgnc+c7upCcE2sQm5S4UXJbCc3ekBOFnCi95OTcP575ji6k58RukljCVonNiUmoMDlRyInSS068SYJVOpGeE7fHy3Ic2uSkH8iJ8mxyEjwSm+SkF8iJ8jxyEla47MqXfyYnPUFOlF5yErZPuu8YTs+JP3zi4jH3m/DkpBfIidJLTvyTees7upCeE3+ccWU35O2618XkIaXA5EQhJ0ofOfFPnyV8UnpOLi/cZrwNiz9tJWW3MDkpICdKHzm5Onph5/WT0O5Cck76hJwo5ERJyYlbdIf33yVsnFjISQNyIjwDn/QFOWlATgRyoow4JylnHqdQzKJO2vH8zqEpBsIdxU3a6utOkZMbNylie2jISZ1KTm6z58TM3XGhZewaFh2IuZ0KD5mCUuTk2O2miadcDA05qVPOyWqaPSc37iHTYlS/1V+1sMgzEJqTnFOCnDQo58SMYL3LkTsnnjd5BqK6fZJyZVEK5KROKScPq7HkJOWCmu5UB2I+gpysMq12kZMGRU5Wdu4cSU7i88BUv3aRZ29COSfXuXYmkJMGRU7cYI0iJ7fh9LXBqeak2jUY5ZzczNg+GV1Opu76yFHkJNtCND575HLRoalunzwYvzk/OOSkjubE7a13ZNknW55FK7PrkJS/+DrP/FnPySTXLvI4q2ZlnDmZOsxsmmUGKc2iuWxSGYh5pv1MzZzk0Ro5qVNsnzjyr3eFmGTZhi4GYn7vHrNsJtVzEp8HhpzUGVlOZsdea7FrWPRb58YPRN6cTM1laZAGhpzUGVdOZnEjKXYOi3yrP7Eq10BoTi4XZpFt7Y+c1KnmJBd55skaoxiI2npXJshJHXKikBOFnNQhJwo5UchJHXKikBOFnNQhJwo5UchJHXKikBOFnNQhJwo5UchJHXKikBOFnNQhJwo5UchJHXKikBOFnNQhJwo5UchJHXKikBOFnNQhJwo5UchJHXKikBNlRDn5Ip69nZvvfTkCTHzOyigG4uNx1ONPR8C4fPK//XoEmPiclVEMxF9TD2FcOfkP0XJZGYfn43NW/ph6COSkATkRyIlCThqQE4GcKOSkATkRyIlCThqQE4GcKOSkATkRyIlCThqQE4GcKOSkATkRyIlCThqQE4GcKOSkATkRyIlCThqQE4GcKOSkATkRyIlCThqQE4GcKOSkATkRyIlCThqQE4GcKOSkATkRyIlCThqQE4GcKOSkATkRyIlCThqQE4GcKOSkATkRyIlCThqQE4GcKOSkATkRyIlCThqQE4GcKOSkATkRyIlCThqQE4GcKOSkATkRyIlCThqQE4GcKOSkATkRyIlCThqQE4GcKDvnJN554eEmdu+He2tsbiAxJ6/j8wvzIrY6kVKXV8a8ktZRaHQjZSBOjsw7bZ2GVidSc3J0559y1eP0PDwXU6H7kOzukzfGTN2DWcUee/H4OXlt4gQ1L69OUmazhPe+NufGnLnWkZ1TzYnv2YmEgTgxd0dhWry0j+cJ82hiTl4an5NM9Tg1JuSkmAoJQ7J7TpYuJzvO8E0G8Ml5mAT+6SwuSrrQcUpa3jqX+IXXqfuQu+6flJIT57Hw1d5tCWlNzInxOclXj5gTnQopQ7J3TqxRZqHHXgyXE/OZfcgzi4ZFt1vpCctzu/zqSsLwe9z7X4WB8H7rRFpOjq58TvLVI+SkmAopQ7J3TmSOvzDHdgXMdpjJg7lw3Q+u9+TamFv7ZPtPJ8fm0vVaLYx980A5eenXRcNjNxJK6jEf2X++RHGB1oXEgXjlvvnMf0h47ERSTk4/8jnJWI8w+XUqJA1Jp5ws7ePCmsWmwAXFMp/ZB+uZuf28qY+EMcfuD7Z1Y197E5pb6CMnd+atewqrxp3oPl8F3PvD9qJsMXUgbSBeeoeEr4+a7UJSTtwC3BYhYz3iwkqmQtKQdMrJhc3CG9fyXf5hNVmE1kJzYlw6XKTCa8M3baSfnPiOfIvyz9w3h2Lkyomd2O79WXPidj6GnPjOHPVo5MQ1Og5JmHv3zMncPvgAxPnfP/h4vDE3E6sW/zL76vgy/+B6bqHPnGRYfgX82/PmxO0AtfNpzpycvrcP5ZxkqEdLTjoNSZh798zJKsz7sSs+BI1Mptfik5gT+74hc/LK2/WlHMboQOe6eMJWc1zvkiM6+5M2EPb99gPCHJJn+ySs+NlZMmM9yjmxUyFpSMLcu2dO3MO17yld9sHHY1Va78qTk7AbMOzk6EbCW6+u3oW9sCEhbou+I0kDYXELz3f+Q8J80onuOTm19fbY789Wj5CTYiqkDEmYe/fIybUx9zLb38SGf/DxcJmo5cQ+6Bu20E9O3PGDhJWNpFn0RdwT7L/fH0TpSMpAOO7euQOOLrQJazxJ2/EW/9X56hFyUkyFlCEJc++OOTmeTC794+TCmNnqzUWc/8s5mTW2T3z3cDlxh19TjlykzKIvvNPdSSOuOGfx7JEuJAyE3+/p3//azigpYe0lJ/nqEbfYdSqkDEmYe3fJid/NawkbJq7LBsHGJoRg5eJw6Vq3tt/UpWrh0uQOqtieso94M0k5OTHGbTtas56dnnVaB410n7FeuLEMJ66cmNPzUKZudB8Iu4rx7i5sJV2d3aWs8PSTk2z1eG/iqQg6FRKGZPecDECaT/oiZc7qjVEMRGpO+mEc9fAzKDkpQU4EcqKQkwbkRCAnCjlpQE4EcqKQkwbkRCAnCjlpQE4EcqKQkwbkRCAnCjlpQE4EcqKQkwbkRCAnCjlpQE4EcqKQkwbkRCAnCjlpQE4EcqKQkwbkRCAnCjlpQE4EcqKQkwbkRCAnCjlpQE4EcqKQkwbkRCAnCjlpQE4EcqKQkwbkRCAnCjlpQE4EcqKQkwbkRCAnCjlpQE4EcqKQkwbkRCAnCjlpQE4EcqKQkwbkRCAnCjlpQE4EcqKQkwbkRCAnCjlpQE4EcqKQkwbkRCAnCjlpQE4EcqKEnHwRbkgAAOvxOQEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgHHANfIAANCdKBPLp8b8D77XV7/54Tdiv0PlJ8aM45ea8vMT86PYOng+ZVIIn5IP4QMmhfBBzSffn0x+8cXXvFTMX/7qtz+Of3niTMMI1Yl/XQs+UfCJgk8UfKLgE2WNTwK//M7nYaH78beXsdfTxfrk4Y19vvBjNLWtG9f0f2sBnyj4RMEnCj5R8InS6pPAd3/+Lb8INh/+/Lux11NkugjPhU8s1/hkN/CJgk8UfKLgE2WLTwLLb3/oF8Tmn3/nl7HX02K6Cs8Vn0yO4/Na8ImCTxR8ouATBZ8oO/nE8+Pf/upjvzg2x1/8IvZ7alR94ri8PTZm9jCPnQX4RMEnCj5R8ImCT5TdfRL4xg9/8z2/UDZf++bPYr+nQ90nt7br0j5fW6fchF4CPlHwiYJPFHyi4BNlX58Efvr1H3zlF82f/IOv/zT2ewrUfLKQjkvXu7qNgk8UfKLgEwWfKPhE6eaTwM+++btP3ILYfPVXT+RylapP3NaJufBN399tqSj4RMEnCj5R8ImCT5QUnwT0cpXvfX/0l6tUfeKvSin5pHJeND5R8ImCTxR8ouATJd0ngeJylf9yxJer4JMu4BMFnyj4RMEnSl8+CRSXq/wvo7xcpeqTN67D+8QfP4nXqETwiYJPFHyi4BMFnyj9+iSgl6t86y9GdrlK7Xi8E4q/CMU1FvEalQg+UfCJgk8UfKLgE+UxfOIpLlf5/A/GcrnKm1kYontVx60VyuXk3tqkdrowPinAJwo+UfCJgk+UR/NJoHS5yv/8tC5XwScKPlHwiYJPFHyiPLJPAsXlKr/7yVO5XAWfKPhEwScKPlHwiTKITwLF5So/+Pfjv1xlcJ/4SSPMptfzyuUwgflUj/0MyOA+iRMhsGZSzB9mxqz5jZzHZ3CfVO+0MH24r+2XfXO9MGZxvWZeeWwG98m2SRFYHRfHR4fiUXyyDJV1J51epJ8yG44clxf2j8OAPgkUl6v85r8b8+UqObZP/AWW7oyzm7m7dF9OZvbcXPs+B+ETS/uksAsM4bh6CsUA5Ng+8achusJfvgmL1AcZ7Zt4PNAx+Fn6ObZP2ieFMA9/H5b+feJm8uM39jmMZx/FDUaJHY/G4D4JFJer/GrwIOxGDp+Ekscl50OpY7W4uAgBOhSftE6KpXmw66XzsCSd+V4DksMnSz+qsfD3pY6HGJ0wZ4T2cOTwSeukiIR1jcEz0rtP3Hi6+zV57FoDPtmJ4nKVb/+r2Gs0ZPdJXEUvwuEXG4NnxZLdJ+VJIVcJhRcMvTKS3SdxFX1WWS93fa5jezCy+6Q5KebGr3kMnpHefeKi/hDblgU+2YPicpWf/53YawTk90k8jHAbuw7ZJ/VJ4fB9ht7hld8ncWukfO8euxA9Xnss4VHJ75PapFgdL1b+BU/fJ2Hf9nFFI2FkXSRCwy23w/Swq1Vzb6Dw+rU9C5/Ezwnh8o0+p9cIfOIpXa7ynVFcrjICn4S5SuvjZ4QD9UltUlh8agY/JD8Cn7gjBJa4mLi8D4eXKqodhBH4pDIp5uY+vuDp+6RY6C9Ks7jv4SIRJoPvF5rmerXyEQk7ydb2FJ/Ih/uedtun3w3bsfgkULpc5YvMl6uMwCehU/fpHLJPapPC4vZslDoHYgQ+iQuLOGnEJ8O7dQQ+KU2K1cL/voXv8wx8MrmRslpkXcF3rPWJN4bf1+fngrU9C5+EtbOwWfem54k1Lp8ESperfPP3Yr/BGY9P5FxQfFK6o4CNxMbbNT8S4/FJSR/xNK+Bd3mNxyd2UtzH6eH7PAefWJa6kRKN4ptrfeJXrIq+a3uWfBIWJe4AzarvM1q2+GQVTqKoEP/02JQuV/l6hstVRuCTMD/pYvOQfVKbFJPjxv00h2EEPolqrRw58ucrDLy1NgKf6KSIjYJhp8Xj+MRxGZ3iheJb23zimmt7hmnk+ln81o/90EXfFy5t3T4JI6TBtuuFsTUMpctVfjjo5Sr5feJ/9Li02nnAPqlNipvh9+5ERuCTsCPkPnZFXK+Bz00YgU90Ujw3nxQnC/uZPY6yH7NtPtG9fvWeFZ+s/Cbt/XXvMdrXJzbasTEkpctVfht7PTb5fRLSUqyGH7BPqpPiWmyymg+84BiBT/y+b6+Tm4W5jg5Z2V5DGza/T4pJofgXDJ6R/n1SFoqLgh9JN24+EuFEaderoQ4/7mt7VnwS19D6P8l8L5/cukEsnRc9MKXLVR5/MZLPJ2Fn6dKvQZQLfoA+WTcpyheFD34MJZ9Pwphe+gv2wu8ChGRe30xWdmLNBv/FlXw+aU4KpVh8Dskj+MTMxJNu+yQsfv2x9eNVGPGmT5xew8U4a3tWfeJfU73jUy/s45Olrg1e+kxPY7adS9/MzGzpkj+LZg3n8l3Ir2PYd4YRSl4ElC5Xecx7dmXwifycfmRW+VWmy7A2Zqdo7DEcGXzSPil8qJThV8oHnxQ3MUGCXlBQEqtspwxJBp+0TgrlufjkehV/X8miZokbZOY4bJ/EZbLj/uHS/zG+cl3PaKFiu8cuoB9hHWRnn6zc7yhp/cK68sO918WbsDvOD519jqtK7hW2YxnN8mCXhEEufaxTli9XeZx7duXYPhkpObZPRkqO7ZORkmP7ZKQ83vH4rZQ2RQrW9mwwLe1T640dfRKp+kRl53bfxt9S8n/wa0uuERwa5ONaYURdqxfKl6v0fREkPlHwiYJPFHyiPEmf3IedyT2zx/4uu3VR9YluaPg9WWEr0//BW8Q11vuk582s8uUq/V0EiU8UfKLgEwWfKE/LJ24n0Xwyf5y9gnsdjy9+UKZQhGNPn2wRZzfKl6v0cc8ufKLgEwWfKPhEyeeT8IMqtYOqa3sWhB9XfZStkz19UtzXpeoTf4Sk5BN/lNQ1BvRJoHy5StpFkPhEwScKPlHwiZJx+2Rs7OWTgqpPwllpvuX6hzOKXWtwnwTKl6t0vQgSnyj4RMEnCj5R8ImS4pPSiVpuC8Vtlcizxb0ik08CaZer4BMFnyj4RMEnCj5RNvokLP6F2NMSrySxxB6Wlb+B4FR22gUNWZb64ougGEd4zSB0vVwFnyj4RMEnCj5R8ImydfvkWdDhchV8ouATBZ8o+ETBJ8ph+CSw1+Uq+ETBJwo+UfCJgk+UQ/JJYMfLVfCJgk8UfKLgEwWfKIfnk8DWy1XwiYJPFHyi4BMFnyiH6pPAhstV8ImCTxR8ouATBZ8oh+2TwNrLVfCJgk8UfKLgEwWfKPhEqF2ugk8UfKLgEwWfKPhEwSdV9HKV/xefCPhEwScKPlHwiVLxyRdhUQoAANCBKBMLqxwl7MbaP/gUPJ+bfxlbh87cmNg6eP4l+RA+N//ob4HjFT5pgZ1/BT8yP4mtQ6eyPX/Y/IR8CD8yf3wFjl/jkxbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCLgkzbwSQE+EfCJgk8UfCKMxCeXt8fGzB7mtrm8CL0C8+k0toYGnxTgEwGfKPhEwSfCKHxybV0yX1mV2IYx4pMb32XwSX7wiYBPFHyi5PXJyZkxsWk73pnz96cvzNFJ7DEsI/DJambMbWxPVsfBJ6vFxcUUn4wEfCLgEwWfKFl98t4tJWP76jNzFkTy2rzzzwMzAp9c2MmxsFsnketif5cXCj7JDz4R8ImCT5ScPnl3dlL45J0x70PrpTHnoTUoI/DJ3FnDzNyxkxr4ZCTgEwGfKPhEyeeTt2efXV3ZpWTo+khbV1fnxtzF5oCM4fiJ20DxzC6KzRQHPhkJ+ETAJwo+UbL55CNzah/tUjJ0HpU2Su6MOYvNARnF8fhVOFLimZaUgk9GAj4R8ImCT5RcPjl/7Q+W2KWk73QN3SaxPtFtleEYhU8sl+FkLsdx7IVPRgM+EfCJgk+UPD55exblYZeS2qj45GVsD8dYfOJY3Tp/lISCT0YCPhHwiYJPlCw+uVNd2KWkNtg+merJwu40YaeQ2IFPxgI+EfCJgk+UHD555xaOZaxJbD89fnJucpwxPAafFFefTCZLO2EeYhufjAV8IuATBZ8oOXzy2blil5L28dXV1VvbkusYbfNtbA7IKHxizG08Cu+2TwqB4JORgE8EfKLgEyXX8fiIXUrG1qkxL0LrM+NP/RqaMfjk+PLyYubU4RCzFIfoaycRDwU+KcAnAj5R8IkyGp9cnRwFoeT6wZUxHY8fF/ikAJ8I+ETBJ8p4fGKNcndkzLtXsWto8Ekb+KQAnwj4RMEnSmafjAh80gY+KcAnAj5R8ImCTwR80kabT5bTfOcI5GK9T9wPQwcuY5/nzzqfHMepEMhztC8DLT45zHzgkwA+aWO9T+ar6iloh8F6nyweloGDWYSu9cn17EJ9emzW/KzpM2WtTw41H/gkgE/aaN3fdYFPPItDmwqOpk/ul7FhuS+unXr+tO3vOsh84JMAPmkDnxSs88nUzKb3h7OjK7Lx+MnlAe3twicl8ImAT9rAJwVrfOKvNXWUftzgANjok0Pa24VPSuATAZ+0gU8K1h8/CcdejbmOXYfAJp8c1N4ufFICnwj4pA18UtDmE8vN7KAmxwafrA5qbxc+KYFPBHzSBj4p2OATv+erdEj6mbPBJw8HtbcLn5TAJwI+aQOfFGz0yQ0+ccwPa28XPimBTwR80gY+Kdjik0VsHQCtPjm0vV34pAQ+EfBJG/ikYJNPVrPiBs3Pn1afHNreLnxSAp8I+KQNfFLQ9Ikxxl0WvprPFjex10HQ5pN5cZfqQwGfKPhEwCdtrPeJDUvgoCKzZvvkwv1q1eFd0Njmk9kB/YZZZK1PDjUf+CSAT9po3T45QDYePzko2o/HHxxt2ycHCD4R8Ekb+KQAnwj4RMEnCj4R8Ekb+KQAnwj4RMEnCj4R8Ekb+KQAnwj4RMEnCj4R8Ekb+KQAnwj4RMEnCj4R8Ekb+KQAnwj4RMEnCj4R8Ekb+KQAnwj4RMEnCj4R8Ekb+KQAnwj4RMEnCj4R8Ekb+KQAnwj4RMEnCj4R8Ekb+KQAnwj4RMEnCj4R8Ekb+KQAnwj4RMEnCj4R8Ekb+KQAnwj4RMEnCj4R8Ekb+KQAnwj4RMEnCj4R8Ekb+KQAnwj4RMEnCj4RKj75Iv7WNAAAwP5EmVjYPinB9kkB2ycC2ycK2ycK2ycC+7vawCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJgE/awCcF+ETAJwo+UfCJMA6f3JrIYj55uAj9bmax323oHhp8UoBPBHyi4BMln09OzuJS8uwk9rl6dW7M0avYMTRj8MmFMbOb0Lw5Nsb7ZCU2cSz93wYGnxTgEwGfKPhEyecT0Yl5G7pPjsw793xnjlQwQzICn7yxUyNuk1guQ3s2913zMLF8e2DwSQE+EfCJgk+UbD557eVRcGrMi9C6M+Y0tAZlBD6xmyfGHK9i12RZuMVyj09GAD4R8ImCT5RcPnl9FBuRt3ZZKZsltvkyNgdkBD5ZeWX4YydN3MZLaetlQPBJAT4R8ImCT5RMPjn3y82zO92z9c6Y89istIdjDMdPJsd+ujjibq6CB9vzOraHBZ8U4BMBnyj4RMnjk7enH91FpcQtEduMu7v8Di8TmwMyCp9MJhfF4Xc5NO9xx0/exPbA4JMCfCLgEwWfKPmOx1tO7JZI3BSxjTvfsDifDH8EZSQ+sVxe2wnguY99/NGTaWwODj4pwCcCPlHwiZLVJ5ajuF1iF54Vn8TmgIzAJ9Nig8SdLmyJXZOpmV3G5vDgkwJ8IuATBZ8ouX1y9TpsoLwu7e+yWy2vY3NAxuCTmZ7bFU8QDs2bme76eshwBQo+KcAnAj5R8ImS3Sd3wSMflRxi3fJRbA7IGHxiTHEU3vkkdOnuL8ux7zMs+KQAnwj4RMEnSnafnEWNnBvzPrROs5zeNRKfGDO7sNsil/OZXIly4z0irDuT+LHBJwX4RMAnCj5Rsvjk5N153AB5ZT4LDbeXK/zwyslZuE5+aMbgE7cza3XvtDK9jcdL3GnCBbPQc1jwSQE+EfCJgk+ULD55K7+18rp8Gpf7wZXT9+fmPMvPrYzBJyMFnxTgEwGfKPhEyb6/azTgkzbwSQE+EfCJgk8UfCLgkzZafLK8XhhzfF86Je0AWO+T+dQd7rrOd0p3Bjb55PLeTZDY8fxp9clyWr1obHVxbEyOUzQHA58I+KSNtT65Ng/uaXVcvYz/ubPGJ6tFPEvCNooLUJ89rT6Zz8zxc15kNlnrk6U/u6bsk5tZmD+mmX43aQjwiYBP2ljjk9VMM3Gd6Vcq87DGJzMd/2X5Fw2eOy0+sbPD811attC2fXJR8YntimdnTk35QrNnBT4R8Ekba3xi1710FdSuheU4izkPTZ/cGF06WJ8czpRY65O5nRgHtdfPs5NP7KSRi8fsfJLlRM0BwCcCPmljjU+sQ3RN3Lol20+LDc6a7RN3uanfQrFmyfSLnTlY5xM7KZ7tmvcGdvLJrLQdX24/L/CJgE/aWOOT49KV+ofuk3B//+PlbHFIB5LW+cTd8u3m8tbOHIuLQ9LKLj6x2yTFxuvzjQw+EfBJG2t8cmnTERPhbgJ22D6xRvG/3nk4+7oca3xip8HMi8QZ9oD2e+3qE91F7A7Vx+YzA58I+KSNNT4Je3nMdGoWrnE4u3nW+mRurt2y47CORDd9Ul5kurniYITSxSdsnzxz8Ekba30iuM2TA1qMrvHJm7jkfON2ex3OibKbfeK2VQ7mtL9dfOK26HUD1s4pzzQz+ETAJ21s8snKRuM2tg+Bpk/sUlQWnO74QWw+f5o+casW5VVwfFLeDHkoHOLc8kyPteETAZ+0scEndt38oC5nXOMTKxFdcN4etE/c8tNf5Oo4franxDbZySduzSuepGD7P1fX4hMBn7TR6pOb2YHZZJ1P7Jq4niN7fEBHktb4pOTWuVkczhleO/nE/XxC6LJbtM/2sld8IuCTNtb6ZHm/MIvDOqPJse54/I1dUFiP3Fwf1J6/dT5xx+FndqaYH9a50y0+ebMw1hwlrdr1r4vlfPGcZxN8IuCTNjYejz8w1vnkMFnvk4OkbfvkAMEnAj5pA58U4BMBnyj4RMEnAj5pA58U4BMBnyj4RMEnAj5pA58U4BMBnyj4RMEnAj5pA58U4BMBnyj4RMEnAj5pA58U4BMBnyj4RMEnAj5pA58U4BMBnyj4RMEnAj5pA58U4BMBnyj4RMEnAj5pA58U4BMBnyj4RMEnAj5pA58U4BMBnyj4RMEnAj5pA58U4BMBnyj4RMEnAj5pA58U4BMBnyj4RMEnAj5pA58U4BMBnyj4RMEnAj5pA58U4BMBnyj4RMEnQsUnv28+/AAic3yi4BMBnyj4RMEnQsUnXxgAAICuRJlY2N9Vgv1dBWyfCGyfKGyfKGyfCBw/aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJwI+aQOfFOATAZ8o+ETBJ8I4fHJrIov55OEi9Hszi/1mN6HHwOCTAnwi4BMFnyg5ffL2hYmtyKtzY45exY6hGYNPLgpn3Bwb433yZnZxOVnNF94ot/5vA4NPCvCJgE8UfKLk8ol1iSN2OU6OzDv3fGeOTnyPgRmBT97YKRK3SSyXob3yHZPJvZteD7FjUPBJAT4R8ImCT5SM2yenFZ/YrhehdWfMaWgNygh8YjdPjDkWgUyWhVss7o/T2B4WfFKATwR8ouATZSw+eWs7ZLPENl/G5oCMwCcrO+aOxTz2KFhNrWkuY8fA4JMCfCLgEwWfKGPxyTtjzmOz0h6OURyPPw5CscxKTlnGfsY0RTMA+KQAnwj4RMEnylh8Yttxd5ff4VU+sDIQo/DJZHIhJ3NVT+da+X1hxlzH7iHBJwX4RMAnCj5RRuSTu9j0Phn+CMpIfGK5vHbmcNzHPh5/QD5HhvFJAT4R8ImCT5Sx+iQ2B2QEPpkWGyTudGFL7ArMG32GAZ8U4BMBnyj4RBmLT16X9ne9M+Z1bA7IGHwy03O71tnDHUapnPI1EPikAJ8I+ETBJ8pYfPJRySHWLR/F5oCMwSflA+7OJ7bLHU6JJ3bZP+fQCT4pgU8EfKLgE2UsPrk6N+Z9aNn+GU7vGolPjJld3Ewml3PrEX8lSnF4vnxpyqDgkwJ8IuATBZ8oo/HJ1Ttz5i9AOTkL18kPzRh8srQPq3unlemtXGxyeesOpSwe7vPIxIJPCvCJgE8UfKLk88lLu0ViXryNXRb3gyun78/NeZafWxmDT0YKPinAJwI+UfCJknH7ZGTgkzbwSQE+EfCJgk8UfCLgkzY2+uQ204+KZWKtTy6vF8YsrjP9HE4m1vtk+eAO/F1k2zebhbU+Wd0fGzN7cLuwDwh8IuCTNjb4ZGUXpIfuk3u72Jj6Uyny3E4gE+t88mC1Og1XTr2JvQ6BNT6xwXi4uPCT4pCmBD5R8Ekb7T5ZGrsEOXCfXMtZd+4E7wOaFmt8spBfA3I/8JDl1PY8NH2ylJnC/UxSaB0G+ETAJ220+uR6tloeuk8ui19Uc7evyXMHzRw0fTIvLp66tdtssXkAbDp+YrfYYusgwCcCPmmjxSer2YO/Zp/jJ8JBLUQ3Ho+3s0WWW7/lYYNP5ocVD3yi4JM21vvkjd8xjE8K7PbJAR193eiTW1P+6aDnTqtPbo5nh3WSBj5R8Ekba33yEBYY+ERZHZRONvrkzUHppMUn4RSNPLeYyAY+EfBJG2t8sprFU5nwiXBjFoe0DN3kk/tD2tllad/ftXJnJhzSARR8IuCTNpo+udc1cXwSuT2s80I3+eTgdvJsOh5/aYVyQJut+ETAJ200feK348scTGJafHJzSKfHBtp8UqxrHAybfOLOGMYnBwg+aWP98fgA2yeWm9lB7SMPrPfJvHTHhYNhi08OaecfPhHwSRv4pGCNT25mxX0E5oezq2edT+bFwefVxeEcNljjk6XMEvcH9aMJ+ETBJ23gk4KGT27KN6ip3fH/WdP0ib+jaMHhXNrZ9MnCTQD3gyuzw5khPPhEwCdtbPLJodF6PP7gaD8ef3Bs3N91WOATAZ+0gU8K8ImATxR8ouATAZ+0gU8K8ImATxR8ouATAZ+0gU8K8ImATxR8ouATAZ+0gU8K8ImATxR8ouATAZ+0gU8K8ImATxR8ouATAZ+0gU8K8ImATxR8ouATAZ+0gU8K8ImATxR8ouATAZ+0gU8K8ImATxR8ouATAZ+0gU8K8ImATxR8ouATAZ+0gU8K8ImATxR8ouATAZ+0gU8K8ImATxR8ouATAZ+0gU8K8ImATxR8ouATAZ+0gU8K8ImATxR8ouAToeKT3zcffgCROT5R8ImATxR8ouAToeKTf2M++RIif+5vZwEAADsTZWJhf1eJT435D1G6B88fsv4VsetfsXXw/DH5EMiHwPGTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyIeCTNvBJAXkR8ImCTxTyITyGT5bHpsJ0Gf8wABf+Gy9iVwo5ffLqtTF3se15f3Z2d2r7vordA5MpL2+PfDWNOXoZ+1xdnbwz5+9PX5ijk9hjWHL55KVMitIcYPu9OH1/bl7E7oHJ7JO7ckQOLR+n58acx7ZnzbyQZZo8yvbJ0s/5U9+e+/bxyncMgP+6J+2Tk1dXL+04lHzy9ix2vTKmWLIOSB6fvDAv3tqnU7colfB8Zs6CSF6bd/55YDL55N2RmxKu/ubI97AcxYny1piPfGNg8vrEzRQSkUPLx6uTE7vCWfZJc17INE0e3SeTydR33ceux8Z/2VPfPrmyqx+FT6xdZCHyzpjT2BySLD75SIVR6NWO/3vfcP0qK2gDkccnL71NLCd2SsTmmTFxE+2jysrHYOT0yUtzV2yfHGI+7NiXZv/mvJBrmgzgk8nMdw4kFP9dz8sndm6RjlM7crE5JHm2Two+M+Yz92zToqNfmUSDkccnivVJ3H1hlxK6QLFTJcNSNKNPPjt7W9rfdYj5qPhkzbyQa5oM4ZNwTMOEXV7zmbleXS7M7MZ1XYaNl7hXzL3lJh58eeNfPXmzmM0nk3vbYxb63Hg7TVfhZbNL39O+zva+tm92r3xmPnlvR0gXF7adYedGbp+8iNvsR6Xg2ESdxeaA5PXJyWs5bOQ2VHQOsXNLhp1/2Xxy8trNBOqTg8xH2Sdr5oVs02QIn4ROY70wubHPt66fffZ/j665XgVBLI6Pl1EuTh8rJw/X8Nrxb4y7z6xdrn3D95ssbMv/OfR8Vj6xs06xDLNt/cNwZPbJWwlHeewrk2UwMvrkvbWqOYtLBrfSqQsMO7cUK6uDkcsnp2HpqD45yHyUfbJmXsg2TQb0iV3IO50Yf7aXs4LbAxZ8UrxK/+idcOkaD9InfKBvLlzLNcIbHrT1DPd31eeNDKuieX3y9uwsHj+wY1+ZLMMffM25ffLyszM7zuEAUn0ZkmFTLZNPPosnZNj6r/fJQeTDjnSrT+y8kG2aDOGTN77TLe/D1oPgXtDuk2vX8swX137jpeQT33QN/wavnYPxyWDrGgVZffK+OAmyPPaVyTIYOX3ieGfH2ln0ULdPTs5k0Wjrv94nB5EPO9IHu30SLHJsW94FlQPz7T4Jb1/derOU+qzxSemtz9An7uwmmV3crJPhjMiMPjk5Kl1pUj7waCdRhjXR3D7Rs3VKB1zdAiPDQYMcPnFZqHKg+Sj7ZM28kG2aDOCTsPUwc4fjrRxsK/QObPGJ2y5xctjsk5W2nqNP3NFof3aTxc5GOa5ey+eTF2flKLy1tRW72KacRTsg2X1i5wA/B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spiral diagonals (Part 2)","description":"Inspired by Project Euler n°28 and 58.\r\nA n x n spiral matrix is obtained by starting with the number 1 and moving to the right in a clockwise direction.\r\nFor example with n=5, the spiral matrix is :\r\n                       21 22 23 24 25\r\n                       20  7  8  9 10\r\n                       19  6  1  2 11\r\n                       18  5  4  3 12\r\n                       17 16 15 14 13\r\nThe sum of the numbers on the diagonals is 101 (See problem 2340) and you have 5 primes (3, 5, 7, 13, 17) out of the 9 numbers lying along both diagonals. So the prime ratio is 5/9 ≈ 55%.\r\nWith a 7x7 spiral matrix, the ratio is 62% (8 primes out of the 13 diagonal numbers).\r\nWhat is the side length (always odd and greater than 1) of the square spiral for which the ratio of primes along both diagonals FIRST falls below p% ? (0\u003cp\u003c1)","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 326.167px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 163.083px; transform-origin: 407px 163.083px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 120px 8px; transform-origin: 120px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eInspired by Project Euler n°28 and 58.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 341px 8px; transform-origin: 341px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA n x n spiral matrix is obtained by starting with the number 1 and moving to the right in a clockwise direction.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 131.5px 8px; transform-origin: 131.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor example with n=5, the spiral matrix is :\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 102.167px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 51.0833px; transform-origin: 404px 51.0833px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 148px 8.5px; tab-size: 4; transform-origin: 148px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e                       21 22 23 24 25\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 148px 8.5px; tab-size: 4; transform-origin: 148px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e                       20  7  8  9 10\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 148px 8.5px; tab-size: 4; transform-origin: 148px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e                       19  6  1  2 11\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 148px 8.5px; tab-size: 4; transform-origin: 148px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e                       18  5  4  3 12\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 148px 8.5px; tab-size: 4; transform-origin: 148px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e                       17 16 15 14 13\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 382.5px 8px; transform-origin: 382.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe sum of the numbers on the diagonals is 101 (See problem 2340) and you have 5 primes (3, 5, 7, 13, 17) out of the 9 numbers lying along both diagonals. So the prime ratio is 5/9 ≈ 55%.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 262px 8px; transform-origin: 262px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWith a 7x7 spiral matrix, the ratio is 62% (8 primes out of the 13 diagonal numbers).\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 364.5px 8px; transform-origin: 364.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"perspective-origin: 74px 8px; transform-origin: 74px 8px; \"\u003eWhat is the side length \u003c/span\u003e\u003cspan style=\"border-block-end-style: solid; border-block-end-width: 1px; border-bottom-style: solid; border-bottom-width: 1px; perspective-origin: 2.5px 8.5px; transform-origin: 2.5px 8.5px; \"\u003e(\u003c/span\u003e\u003cspan style=\"perspective-origin: 96px 8px; transform-origin: 96px 8px; \"\u003ealways odd and greater than 1\u003c/span\u003e\u003cspan style=\"border-block-end-style: solid; border-block-end-width: 1px; border-bottom-style: solid; border-bottom-width: 1px; perspective-origin: 2.5px 8.5px; transform-origin: 2.5px 8.5px; \"\u003e)\u003c/span\u003e\u003cspan style=\"perspective-origin: 189.5px 8px; transform-origin: 189.5px 8px; \"\u003e of the square spiral for which the ratio of primes along both diagonals FIRST falls below p% ? (0\u0026lt;p\u0026lt;1)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function res=spiral_ratio(pourcentage)\r\nres=pourcentage*2;\r\nend","test_suite":"%%\r\nx = 0.8;\r\ny_correct = 3;\r\nassert(isequal(spiral_ratio(x),y_correct))\r\n%%\r\nx = 0.5;\r\ny_correct = 11;\r\nassert(isequal(spiral_ratio(x),y_correct))\r\n%%\r\nx = 0.4;\r\ny_correct = 31;\r\nassert(isequal(spiral_ratio(x),y_correct))\r\n%%\r\nx = 0.3;\r\ny_correct = 49;\r\nassert(isequal(spiral_ratio(x),y_correct))\r\n%%\r\nx = 0.25;\r\ny_correct = 99;\r\nassert(isequal(spiral_ratio(x),y_correct))\r\n%%\r\nx = 0.2;\r\ny_correct = 309;\r\nassert(isequal(spiral_ratio(x),y_correct))\r\n%%\r\nx = 0.15;\r\ny_correct = 981;\r\nassert(isequal(spiral_ratio(x),y_correct))\r\n%%\r\nx = 0.14;\r\ny_correct = 1883;\r\nassert(isequal(spiral_ratio(x),y_correct))\r\n%%\r\nx = 0.13;\r\ny_correct = 3593;\r\nassert(isequal(spiral_ratio(x),y_correct))\r\n%%\r\nx = 0.12;\r\ny_correct = 6523;\r\nassert(isequal(spiral_ratio(x),y_correct))\r\n%%\r\nx = 0.11;\r\ny_correct = 12201;\r\nassert(isequal(spiral_ratio(x),y_correct))","published":true,"deleted":false,"likes_count":7,"comments_count":5,"created_by":5390,"edited_by":223089,"edited_at":"2022-09-26T17:42:20.000Z","deleted_by":null,"deleted_at":null,"solvers_count":196,"test_suite_updated_at":"2022-07-09T19:28:50.000Z","rescore_all_solutions":false,"group_id":31,"created_at":"2014-05-31T18:36:25.000Z","updated_at":"2026-03-04T11:06:42.000Z","published_at":"2014-05-31T18:53:35.000Z","restored_at":null,"restored_by":null,"spam":null,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eInspired by Project Euler n°28 and 58.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eA n x n spiral matrix is obtained by starting with the number 1 and moving to the right in a clockwise direction.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example with n=5, the spiral matrix is :\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[                       21 22 23 24 25\\n                       20  7  8  9 10\\n                       19  6  1  2 11\\n                       18  5  4  3 12\\n                       17 16 15 14 13]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe sum of the numbers on the diagonals is 101 (See problem 2340) and you have 5 primes (3, 5, 7, 13, 17) out of the 9 numbers lying along both diagonals. So the prime ratio is 5/9 ≈ 55%.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWith a 7x7 spiral matrix, the ratio is 62% (8 primes out of the 13 diagonal numbers).\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWhat is the side length (always odd and greater than 1) of the square spiral for which the ratio of primes along both diagonals FIRST falls below p% ? (0\u0026lt;p\u0026lt;1)\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":658,"title":"Find the biggest empty box","description":"You are given a matrix that contains only ones and zeros. Think of the ones as columns in an otherwise empty floor plan. You want to fit a big square into the empty space (denoted by zeros). What is the largest empty square sub-matrix you can find in the given matrix? You will return the row and column extent of the sub-matrix. The answer may not be unique. We will test that your sub-matrix is square, that it is empty, and that it contains the correct number of elements.\r\nExample:\r\n Input a = [ 1 0 0 \r\n             0 0 0 \r\n             0 0 0 ]\r\n\r\n Output si = [ 2 3 2 3 ]\r\nThat is, the square indices are a(2:3,2:3). We verify that sum(sum(a(2:3,2:3))) is zero, and that it has four elements.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.4333px; min-height: 0px; white-space: normal; color: rgb(0, 0, 0); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: rgb(0, 0, 0); white-space: normal; \"\u003e\u003cdiv style=\"block-size: 257.167px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 128.583px; transform-origin: 407px 128.583px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 84px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 42px; text-align: left; transform-origin: 384px 42px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 380.5px 8px; transform-origin: 380.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eYou are given a matrix that contains only ones and zeros. Think of the ones as columns in an otherwise empty floor plan. You want to fit a big square into the empty space (denoted by zeros). What is the largest empty square sub-matrix you can find in the given matrix? You will return the row and column extent of the sub-matrix. The answer may not be unique. We will test that your sub-matrix is \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 24.5px 8px; transform-origin: 24.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003esquare\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 30.5px 8px; transform-origin: 30.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, that it is \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 21px 8px; transform-origin: 21px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eempty\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 166.5px 8px; transform-origin: 166.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, and that it contains the correct number of elements.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 28.5px 8px; transform-origin: 28.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eExample:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 102.167px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 51.0833px; transform-origin: 404px 51.0833px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 76px 8.5px; tab-size: 4; transform-origin: 76px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 28px 8.5px; transform-origin: 28px 8.5px; \"\u003e Input \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 48px 8.5px; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 48px 8.5px; \"\u003ea = [ 1 0 0 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 76px 8.5px; tab-size: 4; transform-origin: 76px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e             0 0 0 \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 80px 8.5px; tab-size: 4; transform-origin: 80px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e             0 0 0 ]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 8.5px; tab-size: 4; transform-origin: 0px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 96px 8.5px; tab-size: 4; transform-origin: 96px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; perspective-origin: 32px 8.5px; transform-origin: 32px 8.5px; \"\u003e Output \u003c/span\u003e\u003cspan style=\"border-block-end-color: rgb(170, 4, 249); border-block-start-color: rgb(170, 4, 249); border-bottom-color: rgb(170, 4, 249); border-inline-end-color: rgb(170, 4, 249); border-inline-start-color: rgb(170, 4, 249); border-left-color: rgb(170, 4, 249); border-right-color: rgb(170, 4, 249); border-top-color: rgb(170, 4, 249); caret-color: rgb(170, 4, 249); color: rgb(170, 4, 249); column-rule-color: rgb(170, 4, 249); margin-inline-end: 0px; margin-right: 0px; outline-color: rgb(170, 4, 249); perspective-origin: 64px 8.5px; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); transform-origin: 64px 8.5px; \"\u003esi = [ 2 3 2 3 ]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 364px 8px; transform-origin: 364px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThat is, the square indices are a(2:3,2:3). We verify that sum(sum(a(2:3,2:3))) is zero, and that it has four elements.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [r1,r2,c1,c2] = biggest_box(a)\r\n  r1 = 1;\r\n  r2 = 1;\r\n  c1 = 1;\r\n  c2 = 1;\r\nend","test_suite":"%%\r\na = [1 0; 0 0];\r\n[r1,r2,c1,c2] = biggest_box(a);\r\nsub = a(r1:r2,c1:c2);\r\n[m,n] = size(sub);\r\nlen = 1;\r\nassert(isequal(sum(sub(:)),0))\r\nassert(isequal(m,len));\r\nassert(isequal(n,len));\r\n\r\n%%\r\na = [1 0 0; 0 0 0; 0 0 0];\r\n[r1,r2,c1,c2] = biggest_box(a);\r\nsub = a(r1:r2,c1:c2);\r\n[m,n] = size(sub);\r\nlen = 2;\r\nassert(isequal(sum(sub(:)),0))\r\nassert(isequal(m,len));\r\nassert(isequal(n,len));\r\n\r\n%%\r\na = triu(ones(6,7));\r\n[r1,r2,c1,c2] = biggest_box(a);\r\nsub = a(r1:r2,c1:c2);\r\n[m,n] = size(sub);\r\nlen = 3;\r\nassert(isequal(sum(sub(:)),0))\r\nassert(isequal(m,len));\r\nassert(isequal(n,len));\r\n\r\n%%\r\na = eye(9);\r\n[r1,r2,c1,c2] = biggest_box(a);\r\nsub = a(r1:r2,c1:c2);\r\n[m,n] = size(sub);\r\nlen = 4;\r\nassert(isequal(sum(sub(:)),0))\r\nassert(isequal(m,len));\r\nassert(isequal(n,len));\r\n\r\n%%\r\na = double(magic(7)\u003c6);\r\n[r1,r2,c1,c2] = biggest_box(a);\r\nsub = a(r1:r2,c1:c2);\r\n[m,n] = size(sub);\r\nlen = 4;\r\nassert(isequal(sum(sub(:)),0))\r\nassert(isequal(m,len));\r\nassert(isequal(n,len));\r\n\r\n%%\r\na=reshape(1:7*9,9,7)\u003e41;\r\n[r1,r2,c1,c2] = biggest_box(a);\r\nsub = a(r1:r2,c1:c2);\r\n[m,n] = size(sub);\r\nlen = 5;\r\nassert(isequal(sum(sub(:)),0))\r\nassert(isequal(m,len));\r\nassert(isequal(n,len));","published":true,"deleted":false,"likes_count":23,"comments_count":9,"created_by":7,"edited_by":223089,"edited_at":"2022-07-09T10:43:47.000Z","deleted_by":null,"deleted_at":null,"solvers_count":501,"test_suite_updated_at":"2022-07-09T10:43:47.000Z","rescore_all_solutions":false,"group_id":6,"created_at":"2012-05-04T19:14:38.000Z","updated_at":"2026-02-19T11:52:57.000Z","published_at":"2012-06-08T19:08:22.000Z","restored_at":null,"restored_by":null,"spam":false,"simulink":false,"admin_reviewed":false,"description_opc":"{\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eYou are given a matrix that contains only ones and zeros. Think of the ones as columns in an otherwise empty floor plan. You want to fit a big square into the empty space (denoted by zeros). What is the largest empty square sub-matrix you can find in the given matrix? You will return the row and column extent of the sub-matrix. The answer may not be unique. We will test that your sub-matrix is \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003esquare\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, that it is \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eempty\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, and that it contains the correct number of elements.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eExample:\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"code\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e\u003c![CDATA[ Input a = [ 1 0 0 \\n             0 0 0 \\n             0 0 0 ]\\n\\n Output si = [ 2 3 2 3 ]]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThat is, the square indices are a(2:3,2:3). We verify that sum(sum(a(2:3,2:3))) is zero, and that it has four elements.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003c/w:body\u003e\u003c/w:document\u003e\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"}],"no_progress_badge":{"id":53,"name":"Unknown","symbol":"unknown","description":"Partially completed groups","description_html":null,"image_location":"/images/responsive/supporting/matlabcentral/cody/badges/problem_groups_unknown_2.png","bonus":null,"players_count":0,"active":false,"created_by":null,"updated_by":null,"deleted_by":null,"deleted_at":null,"restored_by":null,"restored_at":null,"created_at":"2018-01-10T23:20:29.000Z","updated_at":"2018-01-10T23:20:29.000Z","community_badge_id":null,"award_multiples":false}}