{"group":{"id":1,"name":"Community","lockable":false,"created_at":"2012-01-18T18:02:15.000Z","updated_at":"2025-12-14T01:33:56.000Z","description":"Problems submitted by members of the MATLAB Central community.","is_default":true,"created_by":161519,"badge_id":null,"featured":false,"trending":false,"solution_count_in_trending_period":0,"trending_last_calculated":"2025-12-14T00:00:00.000Z","image_id":null,"published":true,"community_created":false,"status_id":2,"is_default_group_for_player":false,"deleted_by":null,"deleted_at":null,"restored_by":null,"restored_at":null,"description_opc":null,"description_html":null,"published_at":null},"problems":[{"id":42714,"title":"Throw common elements of two vector arrays","description":"\r\nThrow common elements as output of two given input vector arrays","description_html":"\u003cp\u003eThrow common elements as output of two given input vector arrays\u003c/p\u003e","function_template":"function y = common(A,B)\r\n %y = common(A,B);\r\nend","test_suite":"%%\r\nA = [1 2 3 4 5 6 7 8];\r\nB = [4 5 6 6 7 0 12 34];\r\ny_correct = [4 5 6 7];\r\nassert(isequal(common(A,B),y_correct))\r\n\r\n%%\r\nA = [11 34 23 09 1];\r\nB = [12 33 21 8 1];\r\ny_correct = 1;\r\nassert(isequal(common(A,B),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":46868,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":87,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-01-15T10:05:41.000Z","updated_at":"2026-04-02T18:54:02.000Z","published_at":"2016-01-15T10:05:41.000Z","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\u003eThrow common elements as output of two given input vector arrays\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":45260,"title":"Alternate elements!","description":"Write a function that combines two lists by alternating the elements, e.g. ['a','b','c'], ['1','2','3'] → 'a1b2c3'.","description_html":"\u003cp\u003eWrite a function that combines two lists by alternating the elements, e.g. ['a','b','c'], ['1','2','3'] → 'a1b2c3'.\u003c/p\u003e","function_template":"function z = your_fcn_name(x,y)\r\n z...;\r\nend","test_suite":"%%\r\nx = ['a', 'b', 'c'];\r\ny = ['1', '2', '3'];\r\nz_correct = 'a1b2c3';\r\nassert(isequal(your_fcn_name(x,y),z_correct))\r\n\r\n%%\r\nx = ['c', 'a', 'b', 'f'];\r\ny = ['3', '1', '2', '0'];\r\nz_correct = 'c3a1b2f0';\r\nassert(isequal(your_fcn_name(x,y),z_correct))\r\n\r\n%%\r\nx = ['c', '1', 'b', 'f'];\r\ny = ['3', '1', '2', '0'];\r\nz_correct = 'c311b2f0';\r\nassert(isequal(your_fcn_name(x,y),z_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":274816,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":57,"test_suite_updated_at":"2020-01-08T20:39:30.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-01-08T20:38:52.000Z","updated_at":"2026-02-15T08:30:42.000Z","published_at":"2020-01-08T20:38:52.000Z","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\u003eWrite a function that combines two lists by alternating the elements, e.g. ['a','b','c'], ['1','2','3'] → 'a1b2c3'.\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":60689,"title":"Sum All Positive Elements","description":"Output a scalar that is equal to the sum of all positive elements in a given vector/matrix.\r\nFor Example:\r\nThe sum of all positive elements in [1 2 -4 -8] should be 3...\r\nThe sum of all positive elements in [1 2; 5 -6; 2 -10] should be 10...","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: 111px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 55.5px; transform-origin: 407px 55.5px; 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-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: 270.317px 8px; transform-origin: 270.317px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOutput a scalar that is equal to the sum of all positive elements in a given vector/matrix.\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-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: 41.6167px 8px; transform-origin: 41.6167px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor Example:\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-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: 183.192px 8px; transform-origin: 183.192px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe sum of all positive elements in [1 2 -4 -8] should be 3...\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-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: 206.525px 8px; transform-origin: 206.525px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe sum of all positive elements in [1 2; 5 -6; 2 -10] should be 10...\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = pos_sum(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = [1 2 3 -4];\r\ny_correct = 6;\r\nassert(isequal(pos_sum(x),y_correct))\r\n%%\r\nx = -105;\r\ny_correct = 0;\r\nassert(isequal(pos_sum(x),y_correct))\r\n%%\r\nx = ones(3);\r\ny_correct = 9;\r\nassert(isequal(pos_sum(x),y_correct))\r\n%%\r\nx = [4 -10 -8; -7 -9 100; -25 3 2];\r\ny_correct = 109;\r\nassert(isequal(pos_sum(x),y_correct))\r\n%%\r\nx = [-1 -2 -3 -4; -5 -6 -7 -8; -9 -10 -11 -12;...\r\n -13 -14 -15 -16];\r\ny_correct = 0;\r\nassert(isequal(pos_sum(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":4585291,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":40,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2024-08-06T23:02:55.000Z","updated_at":"2026-03-23T02:39:40.000Z","published_at":"2024-08-06T23:02:55.000Z","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\u003eOutput a scalar that is equal to the sum of all positive elements in a given vector/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\u003cw:jc w:val=\\\"left\\\"/\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=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe sum of all positive elements in [1 2 -4 -8] should be 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\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe sum of all positive elements in [1 2; 5 -6; 2 -10] should be 10...\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":42715,"title":" Throw common elements of two vector arrays in sorted manner","description":"\r\nThrow common elements as output in sorted manner (acending order) of two given input vector arrays","description_html":"\u003cp\u003eThrow common elements as output in sorted manner (acending order) of two given input vector arrays\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n y = x;\r\nend","test_suite":"%%\r\nA = [1 2 3 4 5 6 7 8];\r\nB = [4 5 6 6 7 0 12 34];\r\ny_correct = [7 6 5 4];\r\nassert(isequal(your_fcn_name(A,B),y_correct))\r\n\r\n%%\r\nA = [1 2 3 4 5 6 71 8];\r\nB = [4 5 6 6 7 0 12 34];\r\ny_correct = [6 5 4];\r\nassert(isequal(your_fcn_name(A,B),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":2,"created_by":46868,"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":1,"created_at":"2016-01-15T10:10:48.000Z","updated_at":"2026-02-28T08:11:04.000Z","published_at":"2016-01-15T10:17:09.000Z","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\u003eThrow common elements as output in sorted manner (acending order) of two given input vector arrays\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":52000,"title":"Vector creation using linspace","description":"Create a vector y containing n uniformly spaced values between a and b, with a \u003c b. Use linspace. ","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: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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: 91px 8px; transform-origin: 91px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCreate a vector y containing \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: 4.5px 8px; transform-origin: 4.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003en\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: 108.5px 8px; transform-origin: 108.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e uniformly spaced values between \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: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\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: 16px 8px; transform-origin: 16px 8px; 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: 4.5px 8px; transform-origin: 4.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eb\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: 52px 8px; transform-origin: 52px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, with a \u0026lt; b. Use \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: 26px 8px; transform-origin: 26px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"text-decoration: underline; text-decoration-line: underline; \"\u003elinspace\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: 4px 8px; transform-origin: 4px 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 = your_fcn_name(a,b,n) %% Do not change this line\r\n y = 1;\r\nend %% Do not change this line","test_suite":"%%\r\na = 2; b = 12; n = 6;\r\ny_correct = [2 4 6 8 10 12];\r\nassert(isequal(your_fcn_name(a,b,n),y_correct))\r\n%%\r\na = 10; b = 100; n = 11;\r\ny_correct = [ 10 19 28 37 46 55 64 73 82 91 100];\r\nassert(isequal(your_fcn_name(a,b,n),y_correct))\r\n%%\r\nfiletext = fileread('your_fcn_name.m');\r\nassert(isempty(strfind(filetext, ':')),'colon (:) forbidden')\r\n%%\r\nfiletext = fileread('your_fcn_name.m');\r\nassert(isempty(strfind(filetext, 'linspace'))==0,'use linspace')","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":428668,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":60,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2021-06-06T02:00:45.000Z","updated_at":"2026-02-11T18:34:00.000Z","published_at":"2021-06-06T02:00:45.000Z","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\u003eCreate a vector y containing \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e uniformly spaced values between \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ea\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:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eb\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, with a \u0026lt; b. Use \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:u/\u003e\u003c/w:rPr\u003e\u003cw:t\u003elinspace\u003c/w:t\u003e\u003c/w:r\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":54860,"title":"Create a column vector of n elements between a and b (both included)","description":"Given lower limit a and an upper limit b, create a column vector of n elements inclusive of a and b.\r\nFor example: a = 1, b = 4, n = 4 \r\n y = [1;2;3;4];","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: 81px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 40.5px; transform-origin: 407px 40.5px; 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=\"\"\u003eGiven lower limit a and an upper limit b, create a \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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003ecolumn\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e vector of n elements inclusive of a and b.\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=\"\"\u003eFor example: a = 1, b = 4, n = 4 \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 y = [1;2;3;4];\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(a, b, n)\r\n \r\nend","test_suite":"%%\r\na = 1;\r\nb = 1;\r\nn = 1;\r\ny_correct = 1;\r\nassert(isequal(your_fcn_name(a, b, n),y_correct))\r\n\r\n%%\r\na = 1;\r\nb = 10;\r\nn = 3;\r\ny_correct = [1; 5.5; 10];\r\nassert(isequal(your_fcn_name(a, b, n),y_correct))\r\n\r\n%%\r\na = 2;\r\nb = 10;\r\nn = 5;\r\ny_correct = [2;4;6;8;10];\r\nassert(isequal(your_fcn_name(a, b, n),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":2436220,"edited_by":2436220,"edited_at":"2022-07-12T14:26:21.000Z","deleted_by":null,"deleted_at":null,"solvers_count":27,"test_suite_updated_at":"2022-07-12T14:26:21.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2022-07-12T14:20:07.000Z","updated_at":"2026-03-09T18:48:18.000Z","published_at":"2022-07-12T14:26:21.000Z","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\u003eGiven lower limit a and an upper limit b, create a \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ecolumn\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e vector of n elements inclusive of a and 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\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example: a = 1, b = 4, n = 4 \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 y = [1;2;3;4];\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":58683,"title":"Find sum of alternate numbers in a vector","description":"Find sum of alternate numbers in a vector starting from index 1","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: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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-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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFind sum of alternate numbers in a vector starting from index 1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = sum_alternate(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = [1 2 3 4 5];\r\ny_correct = 9;\r\nassert(isequal(sum_alternate(x),y_correct))\r\n\r\n%%\r\nx = [1 2 3 4 5 0 1];\r\ny_correct = 10;\r\nassert(isequal(sum_alternate(x),y_correct))\r\n\r\n%%\r\nx = [1 2 0];\r\ny_correct = 1;\r\nassert(isequal(sum_alternate(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3494818,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":35,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-07-18T15:55:48.000Z","updated_at":"2026-02-05T16:30:51.000Z","published_at":"2023-07-18T15:55:48.000Z","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 sum of alternate numbers in a vector starting from index 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":54975,"title":"Find Min and Max Differences in a Vector","description":"Given an array of integers, return the absolute largest and smallest (non zero) difference between any two numbers in the array.","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: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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: 384px 8px; transform-origin: 384px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven an array of integers, return the absolute largest and smallest (non zero) difference between any two numbers in the array.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function minThenMax = your_fcn_name(x)\r\n minThenMax = x;\r\nend","test_suite":"%%\r\nx = [1 2 3 4];\r\ny_correct = [1 3];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = [1 1 2 3];\r\ny_correct = [1 2]\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = primes(20);\r\ny_correct = [1 17]\r\nassert(isequal(your_fcn_name(x),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2434420,"edited_by":223089,"edited_at":"2022-10-29T10:18:06.000Z","deleted_by":null,"deleted_at":null,"solvers_count":50,"test_suite_updated_at":"2022-10-29T10:18:06.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2022-07-12T16:41:10.000Z","updated_at":"2026-02-28T08:18:38.000Z","published_at":"2022-07-12T16:41:10.000Z","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\u003eGiven an array of integers, return the absolute largest and smallest (non zero) difference between any two numbers in the array.\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":42347,"title":"Create a Standard Size Vector","description":"Given an input x, create a row vector y from 1 to x with 5 elements.","description_html":"\u003cp\u003eGiven an input x, create a row vector y from 1 to x with 5 elements.\u003c/p\u003e","function_template":"function y = standard_vector(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = 220;\r\ny_correct = [1.0000 55.7500 110.5000 165.2500 220.0000];\r\nassert(isequal(standard_vector(x),y_correct))\r\n\r\n%%\r\nx = 801;\r\ny_correct = [ 1 201 401 601 801];\r\nassert(isequal(standard_vector(x),y_correct))\r\n\r\n%%\r\nx = 4;\r\ny_correct = [ 1.0000 1.7500 2.5000 3.2500 4.000];\r\nassert(isequal(standard_vector(x),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":44605,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":150,"test_suite_updated_at":"2015-06-17T17:59:34.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2015-06-01T01:19:15.000Z","updated_at":"2026-02-17T17:52:43.000Z","published_at":"2015-06-01T01:19:15.000Z","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 an input x, create a row vector y from 1 to x with 5 elements.\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":43104,"title":"Magnitude of a vector","description":"Given a vector x, what is its magnitude?","description_html":"\u003cp\u003eGiven a vector x, what is its magnitude?\u003c/p\u003e","function_template":"function y = magnitude(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = 1;\r\nassert(isequal(magnitude(x),y_correct))\r\n%%\r\nx = [1 1];\r\ny_correct = sqrt(2);\r\nassert(isequal(magnitude(x),y_correct))\r\n%%\r\nx = [1 2];\r\ny_correct = sqrt(5);\r\nassert(isequal(magnitude(x),y_correct))\r\n%%\r\nx = [1 1 1];\r\ny_correct = sqrt(3);\r\nassert(isequal(magnitude(x),y_correct))\r\n%%\r\nx = [1 1 1 1];\r\ny_correct = sqrt(4);\r\nassert(isequal(magnitude(x),y_correct))\r\n%%\r\nx = [1 1 1 2];\r\ny_correct = sqrt(7);\r\nassert(isequal(magnitude(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":94929,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":99,"test_suite_updated_at":"2016-10-19T11:39:56.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-06T07:39:55.000Z","updated_at":"2026-02-13T18:50:52.000Z","published_at":"2016-10-06T07:39:55.000Z","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 vector x, what is its magnitude?\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":54665,"title":"Find the slope of a line that passes through two vectors","description":"Given two vectors p1 and p2, return the slope of a line that passes through p1 and p2.\r\nExamples:\r\nInput [p1,p2] = deal([0,1],[1,3])\r\nOutput m = 2\r\n\r\nInput [p1,p2] = deal([-2,0],[0,1])\r\nOutput m = 0.5","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: 183.75px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 91.875px; transform-origin: 407px 91.875px; 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=\"\"\u003eGiven two vectors \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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ep1\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: 0px 0px; transform-origin: 0px 0px; \"\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ep2\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e, return the slope of a line that passes through \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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ep1\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: 0px 0px; transform-origin: 0px 0px; \"\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ep2\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: 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=\"\"\u003eExamples:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 40.875px; 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 20.4375px; transform-origin: 404px 20.4375px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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 10.2188px; transform-origin: 404px 10.2188px; 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; \"\u003eInput \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); text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); \"\u003e[p1,p2] = deal([0,1],[1,3])\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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 10.2188px; transform-origin: 404px 10.2188px; 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; \"\u003eOutput \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); text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); \"\u003em = 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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 40.875px; 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 20.4375px; transform-origin: 404px 20.4375px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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 10.2188px; transform-origin: 404px 10.2188px; 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; \"\u003eInput \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); text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); \"\u003e[p1,p2] = deal([-2,0],[0,1])\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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 10.2188px; transform-origin: 404px 10.2188px; 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; \"\u003eOutput \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); text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); \"\u003em = 0.5\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function m = slope(p1,p2)\r\n m = [p1 p2];\r\nend","test_suite":"%%\r\n[p1,p2] = deal([0,1],[1,3]);\r\nm_correct = 2;\r\nassert(isequal(slope(p1,p2),m_correct))\r\n%%\r\n[p1,p2] = deal([-2,0],[0,1]);\r\nm_correct = 0.5;\r\nassert(isequal(slope(p1,p2),m_correct))\r\n%%\r\n[p1,p2] = deal([-3,4],[6,-2])\r\nm_correct = -(2/3);\r\nassert(isequal(slope(p1,p2),m_correct))\r\n%%\r\n[p1,p2] = deal([-1,1],[1,1])\r\nm_correct = 0;\r\nassert(isequal(slope(p1,p2),m_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":792819,"edited_by":792819,"edited_at":"2022-05-21T21:29:59.000Z","deleted_by":null,"deleted_at":null,"solvers_count":53,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-05-21T21:26:40.000Z","updated_at":"2026-02-10T08:28:11.000Z","published_at":"2022-05-21T21:29:59.000Z","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\u003eGiven two vectors \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ep1\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003e and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ep2\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003e, return the slope of a line that passes through \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ep1\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003e and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ep2\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr/\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: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[Input [p1,p2] = deal([0,1],[1,3])\\nOutput m = 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\u003e\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 [p1,p2] = deal([-2,0],[0,1])\\nOutput m = 0.5]]\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":44298,"title":"Simple Vector Addition","description":"Take two incoming vectors and output the sum of the two vectors","description_html":"\u003cp\u003eTake two incoming vectors and output the sum of the two vectors\u003c/p\u003e","function_template":"function added_vec = your_fcn_name(x,y)\r\n added_vec = ...;\r\nend","test_suite":"%%\r\nx = [1 2 3 4 5];\r\ny = [1 2 3 4 5];\r\nadded_vec = [2 4 6 8 10];\r\nassert(isequal(your_fcn_name(x,y),added_vec))\r\n\r\n%%\r\nx = 1:20;\r\ny = 1:20;\r\nadded_vec = 2:2:40;\r\nassert(isequal(your_fcn_name(x,y),added_vec))\r\n\r\n%%\r\nx = ones(1,100);\r\ny = ones(1,100);\r\nadded_vec = 2*ones(1,100);\r\nassert(isequal(your_fcn_name(x,y),added_vec))\r\n\r\n%%\r\nx = 42*ones(1,42);\r\ny = -42*ones(1,42);\r\nadded_vec = zeros(1,42);\r\nassert(isequal(your_fcn_name(x,y),added_vec))\r\n\r\n%%\r\nx = 5:5:100;\r\ny = ones(1,20);\r\nadded_vec = 6:5:101;\r\nassert(isequal(your_fcn_name(x,y),added_vec))\r\n\r\n%%\r\nx = mod(1:100,2);\r\ny = mod([2:100,1],2);\r\nadded_vec = ones(1,100);\r\nassert(isequal(your_fcn_name(x,y),added_vec))","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":12852,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":173,"test_suite_updated_at":"2017-09-08T19:31:29.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2017-09-06T01:06:15.000Z","updated_at":"2026-02-11T18:34:14.000Z","published_at":"2017-09-06T01:06:15.000Z","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\u003eTake two incoming vectors and output the sum of the two vectors\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":58643,"title":"Sum of Squares","description":"Given a vector v of length n, write a MATLAB function to calculate the sum of the squares of its elements.","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: 21.6667px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407.5px 10.8333px; transform-origin: 407.5px 10.8333px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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: 384.5px 10.8333px; text-align: left; transform-origin: 384.5px 10.8333px; 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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eGiven a vector \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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ev\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e of length \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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003en\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e, write a MATLAB function to calculate the sum of the squares of its elements.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = [2, 3, 5];\r\ny_correct = 38;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3495653,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":45,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-07-18T14:38:04.000Z","updated_at":"2026-02-13T19:05:22.000Z","published_at":"2023-07-18T14:38:04.000Z","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\u003eGiven a vector \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\u003ev\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e of length \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\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, write a MATLAB function to calculate the sum of the squares of its 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\"}]}"},{"id":44299,"title":"Vector Element Multiplication","description":"Take two incoming vectors, and output the element wise multiplication of the vectors.","description_html":"\u003cp\u003eTake two incoming vectors, and output the element wise multiplication of the vectors.\u003c/p\u003e","function_template":"function ele_mult_vec = your_fcn_name(x,y)\r\n ele_mult_vec = ...;\r\nend","test_suite":"%%\r\nx = [1 2 3 4 5];\r\ny = [1 2 3 4 5];\r\nele_mult_vec = [1 4 9 16 25];\r\nassert(isequal(your_fcn_name(x,y),ele_mult_vec))\r\n\r\n%%\r\nx = ones(1,10);\r\ny = ones(1,10);\r\nele_mult_vec = ones(1,10);\r\nassert(isequal(your_fcn_name(x,y),ele_mult_vec))\r\n\r\n%%\r\nx = ones(1,10);\r\ny = 10:10:100;\r\nele_mult_vec = 10:10:100;\r\nassert(isequal(your_fcn_name(x,y),ele_mult_vec))\r\n\r\n%%\r\nx = 10:10:100;\r\ny = 0.1*ones(1,10);\r\nele_mult_vec = 1:10;\r\nassert(isequal(your_fcn_name(x,y),ele_mult_vec))\r\n\r\n%%\r\nx = 1:3;\r\ny = 4:6;\r\nele_mult_vec = [4 10 18];\r\nassert(isequal(your_fcn_name(x,y),ele_mult_vec))\r\n\r\n%%\r\nx = mod(1:100,2);\r\ny = mod([2:100,1],2);\r\nele_mult_vec = zeros(1,100);\r\nassert(isequal(your_fcn_name(x,y),ele_mult_vec))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":12852,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":124,"test_suite_updated_at":"2017-09-08T19:34:56.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2017-09-06T01:08:51.000Z","updated_at":"2026-02-11T18:34:27.000Z","published_at":"2017-09-06T01:08:51.000Z","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\",\"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\u003eTake two incoming vectors, and output the element wise multiplication of the vectors.\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":47538,"title":"Summy's even sum","description":null,"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: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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=\"\"\u003eSummy wants to sum the elements of the vector x which are present at even indices. Can you help Summy by making a function which returns the required sum?\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(x)\r\n \r\nend","test_suite":"%%\r\nx = [1 2 3 4 5 6];\r\ny_correct = 12;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [1];\r\ny_correct = 0;\r\nassert(isequal(your_fcn_name(x),y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":731238,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":77,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-11-17T12:09:49.000Z","updated_at":"2026-02-09T14:04:03.000Z","published_at":"2020-11-17T12:10:41.000Z","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\u003eSummy wants to sum the elements of the vector x which are present at even indices. Can you help Summy by making a function which returns the required sum?\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":58593,"title":" findPositiveEvenNumbers ","description":"Write a MATLAB function findPositiveEvenNumbers that takes an array of integers as input and returns a new array containing only the positive even numbers from the input array. The output array should be sorted in ascending order.","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: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407.5px 21px; transform-origin: 407.5px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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: 384.5px 21px; text-align: left; transform-origin: 384.5px 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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eWrite a MATLAB function findPositiveEvenNumbers that takes an array of integers as input and returns a new array containing only the positive even numbers from the input array. The output array should be sorted in ascending order.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(inputArray)\r\n y = inputArray;\r\nend","test_suite":"%%\r\nx = [3, -2, 8, 0, -5, 12, -10, 7];\r\ny_correct = [8, 12];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":10,"comments_count":0,"created_by":3495653,"edited_by":3495653,"edited_at":"2023-07-18T13:35:17.000Z","deleted_by":null,"deleted_at":null,"solvers_count":58,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-07-17T23:19:52.000Z","updated_at":"2026-02-27T14:12:15.000Z","published_at":"2023-07-17T23:19:52.000Z","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\u003eWrite a MATLAB function findPositiveEvenNumbers that takes an array of integers as input and returns a new array containing only the positive even numbers from the input array. The output array should be sorted in ascending order.\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":43303,"title":"Pointwise multiplication of vectors.","description":"Pointwise multiplication of vectors x and y. \r\nExample x= [1 3 5 7 9 11 13 15 17 19]\r\ny=[ 1 4 7 10 13 16 19 22 25 28]\r\nresult= [ 1 12 35 70 117 176 247 330 425 532]","description_html":"\u003cp\u003ePointwise multiplication of vectors x and y. \r\nExample x= [1 3 5 7 9 11 13 15 17 19]\r\ny=[ 1 4 7 10 13 16 19 22 25 28]\r\nresult= [ 1 12 35 70 117 176 247 330 425 532]\u003c/p\u003e","function_template":"function z = your_fcn_name(x,y)\r\n z = x;\r\nend","test_suite":"%%\r\nx = [1 3 5 7 9 11 13 15 17 19];\r\ny=[ 1 4 7 10 13 16 19 22 25 28];\r\ny_correct = [ 1 12 35 70 117 176 247 330 425 532];\r\nassert(isequal(your_fcn_name(x,y),y_correct))\r\n%%\r\nx = [1 12 23 34 45 56 67 78 89 100];\r\ny=[ 1 -10 -21 -32 -43 -54 -65 -76 -87 -98];\r\ny_correct = [ 1 -120 -483 -1088 -1935 -3024 -4355 -5928 -7743 -9800];\r\nassert(isequal(your_fcn_name(x,y),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":90467,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":112,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-10T09:58:16.000Z","updated_at":"2026-02-11T18:41:17.000Z","published_at":"2016-10-10T09:58:16.000Z","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\u003ePointwise multiplication of vectors x and y. Example x= [1 3 5 7 9 11 13 15 17 19] y=[ 1 4 7 10 13 16 19 22 25 28] result= [ 1 12 35 70 117 176 247 330 425 532]\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":44301,"title":"Find the mean of two vectors","description":"Take two vectors, and output the mean of them (bonus if you don't use the in-built mean function)","description_html":"\u003cp\u003eTake two vectors, and output the mean of them (bonus if you don't use the in-built mean function)\u003c/p\u003e","function_template":"function out_mean = your_fcn_name(x,y)\r\n out_mean = ...;\r\nend","test_suite":"%%\r\nx = [1 2 3 4 5];\r\ny = [6 7 8 9 10];\r\nout_mean = [3.5000 4.5000 5.5000 6.5000 7.5000];\r\nassert(isequal(your_fcn_name(x,y),out_mean))\r\n\r\n%%\r\nx = [1 1 2 3 5 8 13 21];\r\ny = ones(1,8);\r\nout_mean = [1 1 1.5 2 3 4.5 7 11];\r\nassert(isequal(your_fcn_name(x,y),out_mean))\r\n\r\n%%\r\nx = ones(1,100);\r\ny = 7*ones(1,100);\r\nout_mean = 4*ones(1,100);\r\nassert(isequal(your_fcn_name(x,y),out_mean))\r\n\r\n%%\r\nx = [5 3 8 1 6 7 9 4 2];\r\ny = [3 7 5 6 1 2 9 8 4];\r\nout_mean = [4 5 6.5 3.5 3.5 4.5 9 6 3];\r\nassert(isequal(your_fcn_name(x,y),out_mean))\r\n\r\n%%\r\nx = 5:-1:1;\r\ny = 1:5;\r\nout_mean = 3*ones(1,5);\r\nassert(isequal(your_fcn_name(x,y),out_mean))\r\n\r\n%%\r\nx = 42;\r\ny = -42;\r\nout_mean = 0;\r\nassert(isequal(your_fcn_name(x,y),out_mean))","published":true,"deleted":false,"likes_count":0,"comments_count":2,"created_by":12852,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":116,"test_suite_updated_at":"2017-09-08T19:42:49.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2017-09-06T01:16:44.000Z","updated_at":"2026-02-11T18:35:03.000Z","published_at":"2017-09-06T01:16:46.000Z","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\u003eTake two vectors, and output the mean of them (bonus if you don't use the in-built mean function)\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":61126,"title":"Sum of even numbers in a vector","description":"Write a function that takes a vector of numbers and returns the sum of all the even numbers in the vector.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 408.5px 10.5px; transform-origin: 408.5px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function that takes a vector of numbers and returns the sum of all the even numbers in the vector.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = sumEven(x)\r\n y = x;\r\nend","test_suite":"%% Test 1: Single even number\r\nx = 2;\r\ny_correct = 2;\r\nassert(isequal(sumEven(x),y_correct))\r\n\r\n%% Test 2: Mix of even and odd\r\nx = [1 2 3 4 5 6];\r\ny_correct = 12; % 2+4+6\r\nassert(isequal(sumEven(x),y_correct))\r\n\r\n%% Test 3: All odd numbers\r\nx = [1 3 5 7];\r\ny_correct = 0;\r\nassert(isequal(sumEven(x),y_correct))\r\n\r\n%% Test 4: Empty vector\r\nx = [];\r\ny_correct = 0;\r\nassert(isequal(sumEven(x),y_correct))\r\n\r\n%% Test 5: Negative numbers included\r\nx = [-2 -3 -4 5];\r\ny_correct = -6; % -2 + -4\r\nassert(isequal(sumEven(x),y_correct))\r\n\r\n%% Test 6: Large vector\r\nx = 1:100;\r\ny_correct = sum(2:2:100); % sum of evens up to 100\r\nassert(isequal(sumEven(x),y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5016520,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":16,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2025-12-14T03:56:27.000Z","updated_at":"2026-02-26T11:08:17.000Z","published_at":"2025-12-14T03:56:27.000Z","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\u003eWrite a function that takes a vector of numbers and returns the sum of all the even numbers in the vector.\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":2928,"title":"Find the product of a Vector","description":"How would you find the product of the vector [1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0] times 2?;\r\n\r\nx = [1 : 0.5 : 6];\r\n\r\ny = x;\r\n\r\n","description_html":"\u003cp\u003eHow would you find the product of the vector [1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0] times 2?;\u003c/p\u003e\u003cp\u003ex = [1 : 0.5 : 6];\u003c/p\u003e\u003cp\u003ey = x;\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = [1:0.5:6];\r\ny_correct = [2:12];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":34004,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":348,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2015-02-02T15:58:19.000Z","updated_at":"2026-02-10T21:50:52.000Z","published_at":"2015-02-02T15:58:19.000Z","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\u003eHow would you find the product of the vector [1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0] times 2?;\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\u003ex = [1 : 0.5 : 6];\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\u003ey = x;\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":45174,"title":"Given a vector x, return vector y with all negative elements from the vector x.","description":"Given a vector x, return vector y with all negative elements from the vector x if x has negative elements. Otherwise return 0.\r\nfor example: x=[1 2 3 4 -5 -2] y=[-5 -2]\r\n x=[1 2 3] y=0\r\n ","description_html":"\u003cp\u003eGiven a vector x, return vector y with all negative elements from the vector x if x has negative elements. Otherwise return 0.\r\nfor example: x=[1 2 3 4 -5 -2] y=[-5 -2]\r\n x=[1 2 3] y=0\u003c/p\u003e","function_template":"function y = vector(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = [1 2 2 -4 -5 -2];\r\ny_correct =[-4 -5 -2];\r\nassert(isequal(vector(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":346141,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":67,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2019-10-12T09:02:51.000Z","updated_at":"2026-03-14T13:28:45.000Z","published_at":"2019-10-12T09:07:50.000Z","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 vector x, return vector y with all negative elements from the vector x if x has negative elements. Otherwise return 0. for example: x=[1 2 3 4 -5 -2] y=[-5 -2] x=[1 2 3] y=0\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":44740,"title":"New Matrix with vector addition on diagonal","description":"consider 2 vectors \r\n\r\n x=[1 2 3]\r\n y=[4 5 6]\r\n\r\nthen generate a new Matrix, where Addition of x \u0026 y will be diagonal Elements of the new Matrix. i.e. new Matrix will have x+y=[5 7 9] as diagonal Elements\r\n\r\n Output =[5 6 7\r\n 6 7 8\r\n 7 8 9]","description_html":"\u003cp\u003econsider 2 vectors\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ex=[1 2 3]\r\ny=[4 5 6]\r\n\u003c/pre\u003e\u003cp\u003ethen generate a new Matrix, where Addition of x \u0026 y will be diagonal Elements of the new Matrix. i.e. new Matrix will have x+y=[5 7 9] as diagonal Elements\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eOutput =[5 6 7\r\n 6 7 8\r\n 7 8 9]\r\n\u003c/pre\u003e","function_template":"function z = addmat(x,y)\r\n z = x+y;\r\nend","test_suite":"%%\r\nx=[1 2 3];\r\ny=[4 5 6];\r\nz_correct = [5 6 7;6 7 8;7 8 9]\r\nassert(isequal(addmat(x,y),z_correct))\r\n\r\n%%\r\nx=[10 20 30 40];\r\ny=[-10 -20 -30 -40];\r\nz_correct = [0 10 20 30;-10 0 10 20;-20 -10 0 10;-30 -20 -10 0]\r\nassert(isequal(addmat(x,y),z_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":136465,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":47,"test_suite_updated_at":"2018-10-02T13:28:44.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2018-10-02T13:24:35.000Z","updated_at":"2026-02-27T14:16:57.000Z","published_at":"2018-10-02T13:24:35.000Z","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\u003econsider 2 vectors\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=[1 2 3]\\ny=[4 5 6]]]\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\u003ethen generate a new Matrix, where Addition of x \u0026amp; y will be diagonal Elements of the new Matrix. i.e. new Matrix will have x+y=[5 7 9] as diagonal Elements\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[Output =[5 6 7\\n 6 7 8\\n 7 8 9]]]\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":2311,"title":"Vector Magnitude Calculator","description":"'a' is a vector that starts at the origin and ends at (x, y). Find ||a||.\r\n\r\nHint: It is as simple as \"ABC\".","description_html":"\u003cp\u003e'a' is a vector that starts at the origin and ends at (x, y). Find \u003ctt\u003e|a|\u003c/tt\u003e.\u003c/p\u003e\u003cp\u003eHint: It is as simple as \"ABC\".\u003c/p\u003e","function_template":"function m = vector_magnitude(x, y)\r\n m = x;\r\nend","test_suite":"%%\r\nx = 5;\r\ny = 12;\r\nmm = 13;\r\nassert(isequal(vector_magnitude(x, y),mm))\r\n\r\n%%\r\nx = 3;\r\ny = 4;\r\nmm = 5;\r\nassert(isequal(vector_magnitude(x, y),mm))\r\n\r\n%%\r\nx = 12;\r\ny = 35;\r\nmm = 37;\r\nassert(isequal(vector_magnitude(x, y),mm))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":26349,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":167,"test_suite_updated_at":"2014-06-05T15:55:43.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2014-05-07T19:54:35.000Z","updated_at":"2026-02-18T09:28:19.000Z","published_at":"2014-05-07T19:54:35.000Z","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\u003e'a' is a vector that starts at the origin and ends at (x, y). Find\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\u003e|a\u003c/w:t\u003e\u003c/w:r\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\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHint: It is as simple as \\\"ABC\\\".\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":46105,"title":"Find sum of numbers on the cornice of a matrix.","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=\"display: block; min-width: 0px; padding-top: 0px; vertical-align: baseline; perspective-origin: 407px 85.5px; transform-origin: 407px 85.5px; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; white-space: pre-wrap; perspective-origin: 384px 10.5px; transform-origin: 384px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eGiven a matrix of random integers, calculate the sum of all the integers in the cornice of the matrix.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; white-space: pre-wrap; perspective-origin: 384px 10.5px; transform-origin: 384px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFor example if MTX = [ \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e1 3 5 6;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; white-space: pre-wrap; perspective-origin: 384px 10.5px; transform-origin: 384px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 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\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e4\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e 7 9 \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e2;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; white-space: pre-wrap; perspective-origin: 384px 10.5px; transform-origin: 384px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 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\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e5\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e 6 1 \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e3;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; white-space: pre-wrap; perspective-origin: 384px 10.5px; transform-origin: 384px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 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\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e 7 9 2 1\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 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=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; white-space: pre-wrap; perspective-origin: 384px 10.5px; transform-origin: 384px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eoutput = 1 + 3 + 5 + 6 + 4 + 2 + 5 + 3 + 7 + 9 + 2 + 1 = 48\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = sumCornice(MTX)\r\n y = MTX;\r\nend","test_suite":"%% Test 1\r\nMTX = [ 1 3 5 6;\r\n 4 7 9 2;\r\n 5 6 1 3;\r\n 7 9 2 1];\r\ny_correct = 48;\r\nassert(isequal(sumCornice(MTX),y_correct))\r\n\r\n%% Test 2\r\nMTX = [ 7 1 7 4 5\r\n 4 3 3 7 6\r\n 6 1 9 8 7\r\n 2 1 1 2 7\r\n 7 8 4 5 3];\r\ny_correct = 83;\r\nassert(isequal(sumCornice(MTX),y_correct))\r\n\r\n%% Test 3\r\nMTX = [ 7 2\r\n 6 2];\r\ny_correct = 17;\r\nassert(isequal(sumCornice(MTX),y_correct))\r\n\r\n%% Test 4\r\nMTX = [ 5 7 3 5 7 2 5 1\r\n 9 9 8 4 4 6 2 3\r\n 4 9 3 8 6 5 6 9\r\n 6 5 9 6 1 1 3 2\r\n 3 2 4 5 1 4 6 8\r\n 7 2 2 9 5 2 7 5\r\n 3 3 3 3 8 8 7 9\r\n 5 8 6 7 9 3 5 1];\r\ny_correct = 147;\r\nassert(isequal(sumCornice(MTX),y_correct))\r\n\r\n%% Test 5\r\nMTX = [ 4 8 9 6 5 3\r\n 1 1 2 5 4 4\r\n 9 4 3 2 1 1\r\n 1 3 2 8 3 9\r\n 7 8 2 6 2 9\r\n 8 4 8 4 2 5];\r\ny_correct = 107;\r\nassert(isequal(sumCornice(MTX),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":522328,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":57,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-08-05T18:20:14.000Z","updated_at":"2026-02-18T21:40:33.000Z","published_at":"2020-08-05T18:20:14.000Z","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 a matrix of random integers, calculate the sum of all the integers in the cornice of the 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\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example if MTX = [ \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e1 3 5 6;\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:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e4\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e 7 9 \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e2;\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:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e5\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e 6 1 \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e3;\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:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e 7 9 2 1\u003c/w:t\u003e\u003c/w:r\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\u003eoutput = 1 + 3 + 5 + 6 + 4 + 2 + 5 + 3 + 7 + 9 + 2 + 1 = 48\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":61087,"title":"How tall will my cactus be?","description":"\r\nMy Barbed Wire Cactus is a desert cactus that relies on just the right amount of rainfall to stay healthy. Given a 1×12 vector of monthly rainfall values (in mm), the cactus will die if any month has less than 10 mm of rain (too dry) or more than 150 mm (too wet). If it survives the year, the change in the average height of the cactus follows a realistic saturation model: \r\ng = Gmax * (1 - exp(-r ./ k))\r\nwhere Gmax⁡ = 5 cm is the maximum monthly growth and k = 40 mm controls how strongly rainfall influences growth. Find the final height if the initial height of my cactus is 140 mm. If my cactus dies, the height should be reported as 0.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 863.667px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 408.5px 431.833px; transform-origin: 408.5px 431.833px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 711.667px; 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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384.5px 355.833px; 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\" data-image-state=\"image-loaded\"\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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384.5px 31.5px; text-align: left; transform-origin: 384.5px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMy Barbed Wire Cactus\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: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\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: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eis a desert cactus that relies on just the right amount of rainfall to stay healthy. Given a 1×12 vector of monthly rainfall values (in mm), the cactus will die if any month has less than 10 mm of rain (too dry) or more than 150 mm (too wet). If it survives the year, the change in the average height of the cactus follows a realistic saturation model: \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 18px; 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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 404.5px 9px; transform-origin: 404.5px 9px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; line-height: 18.004px; 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; padding-inline-start: 4px; padding-left: 4px; text-wrap-mode: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(33, 33, 33); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(33, 33, 33); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(33, 33, 33); border-left-style: none; border-left-width: 0px; border-right-color: rgb(33, 33, 33); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eg = Gmax * (1 - exp(-r ./ k))\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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384.5px 21px; text-align: left; transform-origin: 384.5px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ewhere Gmax⁡ = 5 cm is the maximum monthly growth and k = 40 mm controls how strongly rainfall influences growth. Find the final height if the initial height of my cactus is 140 mm. If my cactus dies, the height should be reported as 0.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function final_height = cactusGrowth(rain)\r\n \r\nend","test_suite":"%% Test 1: Healthy cactus with moderate rainfall\r\nrain = [20 30 40 50 60 70 80 90 60 40 30 20];\r\nassert(abs(cactusGrowth(rain) - 179.7959) \u003c 1e-4 )\r\n\r\n%% Test 2: Dies from drought\r\nrain = [12 20 30 40 50 60 70 80 90 100 70 5];\r\nassert(cactusGrowth(rain) == 0 )\r\n\r\n%% Test 3: Dies from overwatering\r\nrain = [20 30 40 50 60 70 80 90 100 110 120 200];\r\nassert(cactusGrowth(rain) == 0 )\r\n\r\n%% Test 4: Boundary case - exactly 10 mm (survives)\r\nrain = [10 15 20 25 30 35 40 45 50 55 60 65];\r\nassert(abs(cactusGrowth(rain) - 174.2549) \u003c 1e-4 )\r\n\r\n%% Test 5: Boundary case - exactly 150 mm (survives)\r\nrain = [150 100 80 60 40 20 20 40 60 80 100 150];\r\nassert(abs(cactusGrowth(rain) - 185.6152) \u003c 1e-4 )\r\n\r\n%% Test 6: Uniform rainfall\r\nrain = ones(1,12)*50;\r\nassert(abs(cactusGrowth(rain) - 182.8097) \u003c 1e-4 )\r\n\r\n%% Test 7: Random valid rainfall \r\nrain = [68 111 10 52 30 23 36 58 65 85 69 106];\r\nassert( abs(cactusGrowth(rain) - 182.3113) \u003c 1e-4 )\r\n\r\n%% Test 8: Random invalid rainfall\r\nrain = [15 20 30 40 50 60 70 80 90 100 70 9];\r\nassert(cactusGrowth(rain) == 0 )","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":5012276,"edited_by":5012276,"edited_at":"2025-11-29T12:13:14.000Z","deleted_by":null,"deleted_at":null,"solvers_count":13,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2025-11-29T11:59:27.000Z","updated_at":"2026-02-26T20:57:42.000Z","published_at":"2025-11-29T12:13:14.000Z","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:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"706\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"1024\\\"/\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:rPr/\u003e\u003cw:t\u003eMy Barbed Wire Cactus\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:t\u003eis a desert cactus that relies on just the right amount of rainfall to stay healthy. Given a 1×12 vector of monthly rainfall values (in mm), the cactus will die if any month has less than 10 mm of rain (too dry) or more than 150 mm (too wet). If it survives the year, the change in the average height of the cactus follows a realistic saturation model: \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[g = Gmax * (1 - exp(-r ./ k))]]\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\u003ewhere Gmax⁡ = 5 cm is the maximum monthly growth and k = 40 mm controls how strongly rainfall influences growth. Find the final height if the initial height of my cactus is 140 mm. If my cactus dies, the height should be reported as 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\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":45875,"title":"Replicate elements in vectors (★★★)","description":"(copy of Prob 867)\r\n\r\n\r\n\r\nReplicate each element of a row vector (with NaN) a constant number of times. Examples\r\n\r\n n=2, A=[1 2 3] -\u003e [1 1 2 2 3 3]\r\n\r\n n=0, A=[2 1] -\u003e []\r\n\r\n","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: 153.3px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 76.65px; transform-origin: 407px 76.65px; 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: 57.4583px 10.5px; transform-origin: 57.4583px 10.5px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e(copy of Prob 867)\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: 276.375px 10.5px; transform-origin: 276.375px 10.5px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eReplicate each element of a row vector (with NaN) a constant number of times. Examples\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: 134.933px 8.5px; transform-origin: 134.933px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e n=2, A=[1 2 3] -\u0026gt; [1 1 2 2 3 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: 0px 8.5px; 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: 88.55px 8.5px; transform-origin: 88.55px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e n=0, A=[2 1] -\u0026gt; []\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: 84.4167px 10.5px; transform-origin: 84.4167px 10.5px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAvoid using for/while loops.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = replicate_times(x,n)\r\n y = x*n;\r\nend","test_suite":"%%\r\nx = [1 2 3];\r\nn=1;\r\ny_correct = [1 2 3];\r\nassert(isequal(replicate_times(x,n),y_correct))\r\n%%\r\nx = [NaN 1 1];\r\nn=2;\r\ny_correct = [NaN NaN 1 1 1 1];\r\nassert(isequalwithequalnans(replicate_times(x,n),y_correct))\r\n%%\r\nx = [1 0 1 0];\r\nn=0;\r\nassert(isempty(replicate_times(x,n)))\r\n%%\r\nx = [-1 0 1 11];\r\nn=2;\r\ny_correct = [-1 -1 0 0 1 1 11 11];\r\nassert(isequal(replicate_times(x,n),y_correct))\r\n%%\r\nfiletext = fileread('replicate_times.m');\r\nassert(isempty(strfind(filetext, 'for')),'for forbidden')\r\nassert(isempty(strfind(filetext, 'while')),'while forbidden')\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":428668,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":62,"test_suite_updated_at":"2020-10-17T01:00:55.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-06-10T18:45:29.000Z","updated_at":"2026-03-31T14:54:59.000Z","published_at":"2020-06-10T18:45:29.000Z","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\u003e(copy of Prob 867)\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\u003eReplicate each element of a row vector (with NaN) a constant number of times. Examples\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=2, A=[1 2 3] -\u003e [1 1 2 2 3 3]\\n\\n n=0, A=[2 1] -\u003e []]]\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\u003eAvoid using for/while loops.\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":43688,"title":"Increment up an input vector","description":"Increment up an input vector by adding the indices to the vector values. For example, if an input vector is [3, 2, 6, 1, 6], the output vector is [3, 2, 6, 1, 6] + [1, 2, 3, 4, 5] = [4, 4, 9, 5, 11].","description_html":"\u003cp\u003eIncrement up an input vector by adding the indices to the vector values. For example, if an input vector is [3, 2, 6, 1, 6], the output vector is [3, 2, 6, 1, 6] + [1, 2, 3, 4, 5] = [4, 4, 9, 5, 11].\u003c/p\u003e","function_template":"function y = f(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = 1:10;\r\ny_correct = 2:2:20;\r\nassert(isequal(f(x),y_correct))\r\n%%\r\nx = [0.2400 0.4173 0.0497 0.9027 0.9448 0.4909 0.4893];\r\ny_correct = [1.2400 2.4173 3.0497 4.9027 5.9448 6.4909 7.4893];\r\nassert(isequal(f(x),y_correct))\r\n%%\r\nx = [4124 52351 pi i -242];\r\ny_correct = [4125 52353 pi+3 4+i -237];\r\nassert(isequal(f(x),y_correct))\r\n%%\r\nx = [7 4 1 5 8 6 9 2 3];\r\ny_correct = [8 6 4 9 13 12 16 10 12];\r\nassert(isequal(f(x),y_correct))\r\n%%\r\nx = -3:3;\r\ny_correct = -2:2:10;\r\nassert(isequal(f(x),y_correct))\r\n%%\r\nx = 10:-1:1;\r\ny_correct = 11*ones(1,10);\r\nassert(isequal(f(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":88423,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":84,"test_suite_updated_at":"2016-12-21T21:12:09.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-11-28T02:16:11.000Z","updated_at":"2026-02-17T14:46:42.000Z","published_at":"2016-11-28T02:16:11.000Z","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\u003eIncrement up an input vector by adding the indices to the vector values. For example, if an input vector is [3, 2, 6, 1, 6], the output vector is [3, 2, 6, 1, 6] + [1, 2, 3, 4, 5] = [4, 4, 9, 5, 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":46823,"title":"Create a vector of n alternating ones and minus ones (★★)","description":null,"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: 102px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 51px; transform-origin: 407px 51px; 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: 377.783px 10.5px; transform-origin: 377.783px 10.5px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven n, your output should be a vector y of numbers such that the first number is 1 and the numbers following it alternate between -1 and 1. Thus,\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: 128.075px 10.5px; transform-origin: 128.075px 10.5px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eif n = 10, then y = [1 -1 1 -1 1 -1 1 -1 1 -1]\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: 87.975px 10.5px; transform-origin: 87.975px 10.5px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eif n = 5, then y = [1 -1 1 -1 1]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = alternating1_1(n)\r\n y = n;\r\nend","test_suite":"%%\r\nn = 5;\r\ny_correct = [1 -1 1 -1 1];\r\nassert(isequal(alternating1_1(n),y_correct))\r\n%%\r\nn = 8;\r\ny_correct = [1 -1 1 -1 1 -1 1 -1];\r\nassert(isequal(alternating1_1(n),y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":428668,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":63,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-10-17T00:50:28.000Z","updated_at":"2026-03-31T15:10:26.000Z","published_at":"2020-10-17T00:50:28.000Z","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 n, your output should be a vector y of numbers such that the first number is 1 and the numbers following it alternate between -1 and 1. Thus,\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 n = 10, then y = [1 -1 1 -1 1 -1 1 -1 1 -1]\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 n = 5, then y = [1 -1 1 -1 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":58678,"title":"Find cross product of 2 vectors","description":"Find cross product of 2 vectors","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: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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-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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFind cross product of 2 vectors\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function ans = cross_prod(x,y)\r\n ans = x.*y;\r\nend","test_suite":"%%\r\nx = [1 2 3];\r\ny = [-1 2 3];\r\ny_correct = [0 -6 4];\r\nassert(isequal(cross_prod(x,y),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3494818,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":38,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-07-18T15:36:20.000Z","updated_at":"2026-02-17T15:58:40.000Z","published_at":"2023-07-18T15:36:20.000Z","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 cross product of 2 vectors\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":2138,"title":"union without repitition","description":"Let \r\n\r\n a = [9 9 9 9 9 9 8 8 8 8 7 7 7 6 6 6 5 5 4 2 1]\r\n b = [1 1 1 3 3 3 3 3 4 4 4 4 4 10 10 10]\r\n\r\nOutput should be\r\n\r\n [9 8 7 6 5 4 2 1 3 10]\r\n\r\n","description_html":"\u003cp\u003eLet\u003c/p\u003e\u003cpre\u003e a = [9 9 9 9 9 9 8 8 8 8 7 7 7 6 6 6 5 5 4 2 1]\r\n b = [1 1 1 3 3 3 3 3 4 4 4 4 4 10 10 10]\u003c/pre\u003e\u003cp\u003eOutput should be\u003c/p\u003e\u003cpre\u003e [9 8 7 6 5 4 2 1 3 10]\u003c/pre\u003e","function_template":"function y = union_without_repitition(a,b)\r\n y = x;\r\nend","test_suite":"%%\r\na = [9 9 9 9 9 97 7 76 6 6 5 54 2 1];\r\n b = [1 1 13 3 3 44 4 10 110];\r\ny_correct = [9 97 7 76 6 5 54 2 1 13 3 44 4 10 110];\r\nassert(isequal(union_without_repitition(a,b),y_correct))\r\n\r\n%%\r\na = [96 6 65 54 2 1];\r\n b = [1 13 3 3 3 44 4 4 410 10 10];\r\n y_correct =[96 6 65 54 2 1 13 3 44 4 410 10];\r\nassert(isequal(union_without_repitition(a,b),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":1690,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":110,"test_suite_updated_at":"2014-01-31T02:35:48.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2014-01-31T02:32:32.000Z","updated_at":"2026-02-18T11:01:35.000Z","published_at":"2014-01-31T02:32:32.000Z","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\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 = [9 9 9 9 9 9 8 8 8 8 7 7 7 6 6 6 5 5 4 2 1]\\n b = [1 1 1 3 3 3 3 3 4 4 4 4 4 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\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput 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[ [9 8 7 6 5 4 2 1 3 10]]]\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":2689,"title":"vector to string","description":"Determine what the ASCII characters spell out. \r\n\r\nExample:\r\n\r\n input = [ 72 73 71 72] \r\n output = 'HIGH'","description_html":"\u003cp\u003eDetermine what the ASCII characters spell out.\u003c/p\u003e\u003cp\u003eExample:\u003c/p\u003e\u003cpre\u003e input = [ 72 73 71 72] \r\n output = 'HIGH'\u003c/pre\u003e","function_template":"function y = vector(x)\r\n y = x;\r\nend","test_suite":"%%\r\nvector = [70 73 86 69];\r\ny_correct = 'FIVE';\r\nassert(isequal(vector,y_correct))\r\n\r\n%%\r\nvector = [109 97 116 104 101 109 97 116 105 99 115];\r\ny_correct = 'mathematics';\r\nassert(isequal(vector,y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":29473,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":138,"test_suite_updated_at":"2014-11-25T15:17:13.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2014-11-24T21:45:26.000Z","updated_at":"2026-02-18T11:13:43.000Z","published_at":"2014-11-24T21:52:18.000Z","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\u003eDetermine what the ASCII characters spell out.\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 = [ 72 73 71 72] \\n output = 'HIGH']]\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":44886,"title":"Given a Vector v1, create v2 which is the sum of each two adjacent elements in v1. {length(v2)=length(v1)-1}","description":"if v1 is [1 2 3 4 5 6 7 8] then v2 should be [3 5 7 9 11 13 15].\r\n\r\nif v1 is [1;\r\n 3;\r\n 5;\r\n 7] \r\nthen v2 should be [4;\r\n 8;\r\n 12].","description_html":"\u003cp\u003eif v1 is [1 2 3 4 5 6 7 8] then v2 should be [3 5 7 9 11 13 15].\u003c/p\u003e\u003cp\u003eif v1 is [1;\r\n 3;\r\n 5;\r\n 7] \r\nthen v2 should be [4;\r\n 8;\r\n 12].\u003c/p\u003e","function_template":"function v2 = sumEachPair(v1)\r\n v2 = v1;\r\nend","test_suite":"%%\r\nx = 1:10;\r\ny_correct = 3:2:19;\r\nassert(isequal(sumEachPair(x),y_correct))\r\n%%\r\nx = [1:100]';\r\ny_correct = [3:2:199]';\r\nassert(isequal(sumEachPair(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":278101,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":162,"test_suite_updated_at":"2019-04-21T12:59:23.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2019-04-21T12:50:42.000Z","updated_at":"2026-03-11T08:21:25.000Z","published_at":"2019-04-21T12:54:44.000Z","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\u003eif v1 is [1 2 3 4 5 6 7 8] then v2 should be [3 5 7 9 11 13 15].\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 v1 is [1; 3; 5; 7] then v2 should be [4; 8; 12].\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":45313,"title":"Find the shortest distance between a point and a straight line.","description":"Given the Cartesian coordinates of three points A, B and C (in a flat Euclidean space),\r\nfind the shortest distance between the straight line through A and B, and the point C.\r\n\r\nAssumption:\r\n\r\nA and B do not coincide.","description_html":"\u003cp\u003eGiven the Cartesian coordinates of three points A, B and C (in a flat Euclidean space),\r\nfind the shortest distance between the straight line through A and B, and the point C.\u003c/p\u003e\u003cp\u003eAssumption:\u003c/p\u003e\u003cp\u003eA and B do not coincide.\u003c/p\u003e","function_template":"function y = shortest_distance(x1,x2,x3)\r\n y = 0;\r\nend","test_suite":"%%\r\nx1 = [0 0 0];\r\nx2 = [1 1 1];\r\nx3 = [2 2 2];\r\n\r\ny_correct = 0; \r\neps = 4.999 * 10^(-7);\r\nassert(abs(shortest_distance(x1,x2,x3)-y_correct)\u003ceps)\r\n\r\n%%\r\nx1 = [0 0 0];\r\nx2 = [0 0 1];\r\nx3 = [1 0 0];\r\n\r\ny_correct = 1;\r\neps = 4.999 * 10^(-7);\r\nassert(abs(shortest_distance(x1,x2,x3)-y_correct)\u003ceps)\r\n\r\n%%\r\nx1 = [1 0 0];\r\nx2 = [0 1 0];\r\nx3 = [0 0 0];\r\n\r\ny_correct = sqrt(1/2);\r\neps = 4.999 * 10^(-7);\r\nassert(abs(shortest_distance(x1,x2,x3)-y_correct)\u003ceps)\r\n\r\n%%\r\ntheta = 0.5;\r\npsi = -0.2;\r\nphi = 1.1;\r\nR3=[cos(psi) sin(psi) 0.0; -sin(psi) cos(psi) 0.0; 0.0 0.0 1.0];\r\nR2=[cos(theta) 0.0 -sin(theta); 0.0 1.0 0.0; sin(theta) 0.0 cos(theta)];\r\nR1=[1.0 0.0 0.0; 0.0 cos(phi) sin(phi); 0.0 -sin(phi) cos(phi)];\r\n\r\nR = R3*R2*R1;\r\nx1 = [1 0 0]*R;\r\nx2 = [0 1 0]*R;\r\nx3 = [0 0 0]*R;\r\n\r\ny_correct = sqrt(1/2);\r\neps = 4.999 * 10^(-7);\r\nassert(abs(shortest_distance(x1,x2,x3)-y_correct)\u003ceps)\r\n\r\n%%\r\nx1 = [0 0 0];\r\nx2 = [0 0 1];\r\nx3 = x2;\r\n\r\ny_correct = 0;\r\neps = 4.999 * 10^(-7);\r\nassert(abs(shortest_distance(x1,x2,x3)-y_correct)\u003ceps)","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":393995,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":17,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-02-04T14:23:13.000Z","updated_at":"2026-03-19T07:20:29.000Z","published_at":"2020-02-18T12:21:57.000Z","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 the Cartesian coordinates of three points A, B and C (in a flat Euclidean space), find the shortest distance between the straight line through A and B, and the point C.\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\u003eAssumption:\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 and B do not coincide.\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":1988,"title":"Remove the middle element from a vector","description":"Remove the middle element of a vector?\r\n\r\n*Example:*\r\n\r\n[1,2,3] should return 2\r\n\r\n[1,2,3,4] should return 2\r\n\r\n[] should return empty vector","description_html":"\u003cp\u003eRemove the middle element of a vector?\u003c/p\u003e\u003cp\u003e\u003cb\u003eExample:\u003c/b\u003e\u003c/p\u003e\u003cp\u003e[1,2,3] should return 2\u003c/p\u003e\u003cp\u003e[1,2,3,4] should return 2\u003c/p\u003e\u003cp\u003e[] should return empty vector\u003c/p\u003e","function_template":"function y = remove_middle(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = [1,2,3];\r\ny_correct = 2;\r\nassert(isequal(remove_middle(x),y_correct))\r\n%%\r\nx = [1,2,3,4];\r\ny_correct = 2;\r\nassert(isequal(remove_middle(x),y_correct))\r\n%%\r\nx = [];\r\ny_correct = [];\r\nassert(isequal(remove_middle(x),y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":2,"created_by":19016,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":93,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-11-14T00:47:38.000Z","updated_at":"2026-02-18T14:46:19.000Z","published_at":"2013-11-14T00:47:38.000Z","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\u003eRemove the middle element of 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\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=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e[1,2,3] should return 2\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[1,2,3,4] should return 2\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[] should return empty vector\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":60704,"title":"Convert RGB to Grayscale","description":"Convert a 3 element RGB array to its correspoding grayscale pixel (a scalar)\r\n*Hint: a formula exists!","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: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 25.5px; transform-origin: 407px 25.5px; 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-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: 236.5px 8px; transform-origin: 236.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eConvert a 3 element RGB array to its correspoding grayscale pixel (a scalar)\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-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: 70.0083px 8px; transform-origin: 70.0083px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e*Hint: a formula exists!\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function g = RGB_to_gray(x)\r\n g = 0;\r\nend","test_suite":"%%\r\nx = [0,0,0];\r\ng = 0;\r\nassert(abs(RGB_to_gray(x)-g) \u003c 1e-1)\r\n%assert(isequal(RGB_to_gray(x),g))\r\n%%\r\nx = [255,255,255];\r\ng = 255;\r\nassert(abs(RGB_to_gray(x)-g) \u003c 1e-1)\r\n%%\r\nx = [200,220,240];\r\ng = 216.3;\r\nassert(abs(RGB_to_gray(x)-g) \u003c 1e-1)\r\n%%\r\nx = [0,255,0];\r\ng = 149.7;\r\nassert(abs(RGB_to_gray(x)-g) \u003c 1e-1)\r\n%%\r\nx = [0,0,255];\r\ng = 29.1;\r\nassert(abs(RGB_to_gray(x)-g) \u003c 1e-1)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":1,"created_by":4585291,"edited_by":4585291,"edited_at":"2024-08-07T19:08:12.000Z","deleted_by":null,"deleted_at":null,"solvers_count":26,"test_suite_updated_at":"2024-08-07T19:08:12.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2024-08-07T16:17:39.000Z","updated_at":"2026-02-18T14:54:19.000Z","published_at":"2024-08-07T16:17:39.000Z","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\u003eConvert a 3 element RGB array to its correspoding grayscale pixel (a scalar)\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*Hint: a formula exists!\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":44842,"title":"Double the next!","description":"Given two numbers, m and n, find a matrix [m,n] where each element value is twice the value of the previous element. Starting from the position (1,1) with value equal to 1, until the position (m,n), following the direction from left to right and from top to bottom.\r\nFor example, for m=2 and n=3, you should get:\r\ny = [1 2 4; 8 16 32].","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: 123.438px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 332px 61.7188px; transform-origin: 332px 61.7188px; 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: 309px 31.5px; text-align: left; transform-origin: 309px 31.5px; 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: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven two numbers, m and n, find a matrix \u003c/span\u003e\u003cspan style=\"border-block-end-style: solid; border-block-end-width: 1px; border-bottom-style: solid; border-bottom-width: 1px; \"\u003e[\u003c/span\u003e\u003cspan style=\"\"\u003em,n\u003c/span\u003e\u003cspan style=\"border-block-end-style: solid; border-block-end-width: 1px; border-bottom-style: solid; border-bottom-width: 1px; \"\u003e]\u003c/span\u003e\u003cspan style=\"\"\u003e where each element value is twice the value of the previous element. Starting from the position (1,1) with value equal to 1, until the position (m,n), following the direction from left to right and from top to bottom.\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: 309px 10.5px; text-align: left; transform-origin: 309px 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: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor example, for m=2 and n=3, you should get:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 20.4375px; 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: 329px 10.2188px; transform-origin: 329px 10.2188px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); 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; text-wrap: 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; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003ey = [1 2 4; 8 16 32].\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(m,n)\r\n y = [];\r\nend","test_suite":"%%\r\nm = 3;\r\nn = 2; \r\ny_correct = [1 2; 4 8; 16 32];\r\nassert(isequal(your_fcn_name(m,n),y_correct))\r\n\r\n%%\r\nm = 1;\r\nn = 1; \r\ny_correct = [1];\r\nassert(isequal(your_fcn_name(m,n),y_correct))\r\n\r\n%%\r\nm = 1;\r\nn = 5; \r\ny_correct = [1 2 4 8 16];\r\nassert(isequal(your_fcn_name(m,n),y_correct))\r\n\r\n%%\r\nm = 3;\r\nn = 1; \r\ny_correct = [1; 2; 4];\r\nassert(isequal(your_fcn_name(m,n),y_correct))\r\n\r\n%%\r\nm = 4;\r\nn = 2; \r\ny_correct = [1 2; 4 8; 16 32; 64 128];\r\nassert(isequal(your_fcn_name(m,n),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":274816,"edited_by":274816,"edited_at":"2024-07-03T13:09:32.000Z","deleted_by":null,"deleted_at":null,"solvers_count":54,"test_suite_updated_at":"2019-03-23T22:36:07.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2019-01-29T11:50:39.000Z","updated_at":"2026-03-04T14:52:41.000Z","published_at":"2019-01-29T11:50:39.000Z","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\u003eGiven two numbers, m and n, find a matrix [m,n] where each element value is twice the value of the previous element. Starting from the position (1,1) with value equal to 1, until the position (m,n), following the direction from left to right and from top to bottom.\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, for m=2 and n=3, you should get:\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[y = [1 2 4; 8 16 32].]]\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":52005,"title":"Vector creation using colon operator","description":"Create a vector y containing n uniformly spaced values between a and b, with a \u003c b. Use the colon (:) operator.","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: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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: 91px 8px; transform-origin: 91px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCreate a vector y containing \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: 4.5px 8px; transform-origin: 4.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003en\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: 108.5px 8px; transform-origin: 108.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e uniformly spaced values between \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: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\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: 16px 8px; transform-origin: 16px 8px; 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: 4.5px 8px; transform-origin: 4.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eb\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: 120.5px 8px; transform-origin: 120.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, with a \u0026lt; b. Use the colon (:) operator.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(a,b,n) %% Do not change this line\r\n y = 1;\r\nend %% Do not change this line","test_suite":"%%\r\na = 2; b = 12; n = 6;\r\ny_correct = [2 4 6 8 10 12];\r\nassert(isequal(your_fcn_name(a,b,n),y_correct))\r\n%%\r\na = 10; b = 100; n = 11;\r\ny_correct = [ 10 19 28 37 46 55 64 73 82 91 100];\r\nassert(isequal(your_fcn_name(a,b,n),y_correct))\r\n%%\r\nfiletext = fileread('your_fcn_name.m');\r\nassert(isempty(strfind(filetext, 'linspace')),'linspace forbidden')\r\n%%\r\nfiletext = fileread('your_fcn_name.m');\r\nassert(isempty(strfind(filetext, ':'))==0,'use colon (:) operator')","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":428668,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":41,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2021-06-06T02:04:54.000Z","updated_at":"2026-03-05T16:12:30.000Z","published_at":"2021-06-06T02:04:54.000Z","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\u003eCreate a vector y containing \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e uniformly spaced values between \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ea\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:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eb\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, with a \u0026lt; b. Use the colon (:) operator.\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":44156,"title":"Weighted average","description":"Compute the weighted average Y, of the vector A, given the weight vector W.\r\n\r\nThe weighted average is the sum of the dot product of A and W, normalized by the sum of W.\r\n\r\nExample 1:\r\n\r\n A = [10 15 20 10];\r\n W = [ 1 1 1 1];\r\n Y = 13.75\r\n\r\nExample 2:\r\n\r\n A = [ 10 15 20 10];\r\n W = [0.25 0.25 0.25 0.25];\r\n Y = 13.75\r\n\r\nExample 3:\r\n\r\n A = [10 15 20 10];\r\n W = [ 2 4 4 2];\r\n Y = 15","description_html":"\u003cp\u003eCompute the weighted average Y, of the vector A, given the weight vector W.\u003c/p\u003e\u003cp\u003eThe weighted average is the sum of the dot product of A and W, normalized by the sum of W.\u003c/p\u003e\u003cp\u003eExample 1:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eA = [10 15 20 10];\r\nW = [ 1 1 1 1];\r\nY = 13.75\r\n\u003c/pre\u003e\u003cp\u003eExample 2:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eA = [ 10 15 20 10];\r\nW = [0.25 0.25 0.25 0.25];\r\nY = 13.75\r\n\u003c/pre\u003e\u003cp\u003eExample 3:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eA = [10 15 20 10];\r\nW = [ 2 4 4 2];\r\nY = 15\r\n\u003c/pre\u003e","function_template":"function Y = weighted_average(A,W)\r\n Y = A;\r\nend","test_suite":"%%\r\nA = [10 15 20 10];\r\nW = [ 1 1 1 1];\r\nY = 13.75\r\nassert(isequal(weighted_average(A,W),Y))\r\n\r\n%%\r\nA = [ 10 15 20 10];\r\nW = [0.25 0.25 0.25 0.25];\r\nY = 13.75\r\nassert(isequal(weighted_average(A,W),Y))\r\n\r\n%%\r\nA = [10 15 20 10];\r\nW = [ 2 4 4 2];\r\nY = 15\r\nassert(isequal(weighted_average(A,W),Y))\r\n\r\n%%\r\nassert(~any(strfind(lower(fileread('weighted_average.m')),'regexp')))\r\n\r\n%%\r\nassert(~any(strfind(lower(fileread('weighted_average.m')),'feval')))\r\n\r\n%%\r\nassert(~any(strfind(lower(fileread('weighted_average.m')),'eval')))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":130819,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":118,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-05-04T14:38:26.000Z","updated_at":"2026-04-03T03:15:25.000Z","published_at":"2017-05-04T14:38:26.000Z","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\u003eCompute the weighted average Y, of the vector A, given the weight vector W.\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 weighted average is the sum of the dot product of A and W, normalized by the sum of W.\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 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[A = [10 15 20 10];\\nW = [ 1 1 1 1];\\nY = 13.75]]\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\u003eExample 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[A = [ 10 15 20 10];\\nW = [0.25 0.25 0.25 0.25];\\nY = 13.75]]\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\u003eExample 3:\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 = [10 15 20 10];\\nW = [ 2 4 4 2];\\nY = 15]]\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":43047,"title":"Wrap-around effect","description":"In vector x of length n we define (n+1) position as going back to the first position (so called wrap-around effect). Can you return the value of x at a given position, taking into account the above rule?\r\n\r\nExample: x = [1 2 3] -\u003e x(1) yields 1, x(5) should yield 2; and so on.","description_html":"\u003cp\u003eIn vector x of length n we define (n+1) position as going back to the first position (so called wrap-around effect). Can you return the value of x at a given position, taking into account the above rule?\u003c/p\u003e\u003cp\u003eExample: x = [1 2 3] -\u0026gt; x(1) yields 1, x(5) should yield 2; and so on.\u003c/p\u003e","function_template":"function y = wrapAround(x,pos)\r\n y = x;\r\nend","test_suite":"%%\r\nx = 1;\r\npos = 1;\r\ny_correct = 1;\r\nassert(isequal(wrapAround(x,pos),y_correct))\r\n\r\n%%\r\nx = [1 2 3 4 5];\r\npos = 99;\r\ny_correct = 4;\r\nassert(isequal(wrapAround(x,pos),y_correct))\r\n\r\n%%\r\nx = 7:101;\r\npos = 909;\r\ny_correct = 60;\r\nassert(isequal(wrapAround(x,pos),y_correct))\r\n\r\n%%\r\nx = 5:5:100;\r\npos = 101;\r\ny_correct = 5;\r\nassert(isequal(wrapAround(x,pos),y_correct))\r\n\r\n%%\r\nx = -17:3:99;\r\npos = 1001;\r\ny_correct = 58;\r\nassert(isequal(wrapAround(x,pos),y_correct))\r\n\r\n%%\r\nx = 1:3:777;\r\npos = 789;\r\ny_correct = 34;\r\nassert(isequal(wrapAround(x,pos),y_correct))\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":1,"created_by":29461,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":53,"test_suite_updated_at":"2016-10-17T18:00:48.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-05T11:23:52.000Z","updated_at":"2026-03-24T13:32:26.000Z","published_at":"2016-10-05T11:23:52.000Z","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\u003eIn vector x of length n we define (n+1) position as going back to the first position (so called wrap-around effect). Can you return the value of x at a given position, taking into account the above rule?\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: x = [1 2 3] -\u0026gt; x(1) yields 1, x(5) should yield 2; and so on.\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":760,"title":"Duplicate each element of a vector.","description":"for an n-dimensional vector x, the function should return another vector 2n-dimension which each element is repeated twice.\r\nExample :\r\nin-\u003e[2 3 NaN 5] and out-\u003e[2 2 3 3 NaN NaN 5 5]","description_html":"\u003cp\u003efor an n-dimensional vector x, the function should return another vector 2n-dimension which each element is repeated twice.\r\nExample :\r\nin-\u003e[2 3 NaN 5] and out-\u003e[2 2 3 3 NaN NaN 5 5]\u003c/p\u003e","function_template":"function y = duplicate(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = [2,3,5];\r\ny_correct = [2,2,3,3,5,5];\r\nassert(isequal(duplicate(x),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":1309,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":636,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-06-13T03:45:03.000Z","updated_at":"2026-03-11T12:03:40.000Z","published_at":"2012-06-13T03:58:24.000Z","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\u003efor an n-dimensional vector x, the function should return another vector 2n-dimension which each element is repeated twice. Example : in-\u003e[2 3 NaN 5] and out-\u003e[2 2 3 3 NaN NaN 5 5]\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":44737,"title":"Get the combinations","description":"Consider\r\np,q = 2 vectors of same or different length.\r\nGet a Output Array which has all the possible combinations of Elements of vectors p and q\r\nfor example: \r\n\r\n p = [1 2 3], q = [10 12]\r\nthen \r\n\r\n Output = [1 10;2 10;3 10;1 12;2 12;3 12]\r\n","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: 133.733px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 66.8667px; transform-origin: 407px 66.8667px; 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: 362px 8px; transform-origin: 362px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eConsider p,q = 2 vectors of same or different length. Get a Output Array which has all the possible combinations of Elements of vectors p and q for example:\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: 96px 8.5px; transform-origin: 96px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003ep = [1 2 3], q = [10 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: 20px 8.5px; transform-origin: 20px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003ethen \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; 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: 160px 8.5px; transform-origin: 160px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eOutput = [1 10;2 10;3 10;1 12;2 12;3 12]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = combineit(p,q)\r\n y = {p.*q};\r\nend","test_suite":"%%\r\np=[10:15]\r\nq=[2:5]\r\ny_correct = [10 2;\r\n 11 2;\r\n 12 2;\r\n 13 2;\r\n 14 2;\r\n 15 2;\r\n 10 3;\r\n 11 3;\r\n 12 3;\r\n 13 3;\r\n 14 3;\r\n 15 3;\r\n 10 4;\r\n 11 4;\r\n 12 4;\r\n 13 4;\r\n 14 4;\r\n 15 4;\r\n 10 5;\r\n 11 5;\r\n 12 5;\r\n 13 5;\r\n 14 5;\r\n 15 5]\r\nassert(isequal(combineit(p,q),y_correct))\r\n\r\n%%\r\np=[-2:2];\r\nq=[-1 0 1];\r\ny_correct = [-2 -1 0 1 2 -2 -1 0 1 2 -2 -1 0 1 2\r\n -1 -1 -1 -1 -1 0 0 0 0 0 1 1 1 1 1]'; \r\nassert(isequal(combineit(p,q),y_correct))\r\n\r\n%%\r\np=[1 1 2 3 5 8 13];\r\nq=[1.618];\r\ny_correct = [1 1.618; 1 1.618; 2 1.618; 3 1.618; 5 1.618; 8 1.618; 13 1.618]; \r\nassert(isequal(combineit(p,q),y_correct))\r\n\r\n%%\r\np=[0 0.5 1];\r\nq=[exp(1) pi];\r\ny_correct = [0 exp(1); 0.5 exp(1); 1 exp(1); 0 pi; 0.5 pi; 1 pi]\r\nassert(isequal(combineit(p,q),y_correct))\r\n\r\n%%\r\np=[];\r\nq=[];\r\nassert(isempty(combineit(p,q)))","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":136465,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":43,"test_suite_updated_at":"2021-05-09T10:37:16.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2018-09-11T12:58:36.000Z","updated_at":"2026-04-03T07:15:22.000Z","published_at":"2018-09-11T12:58:36.000Z","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\u003eConsider p,q = 2 vectors of same or different length. Get a Output Array which has all the possible combinations of Elements of vectors p and q for 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[p = [1 2 3], q = [10 12]\\nthen \\n\\nOutput = [1 10;2 10;3 10;1 12;2 12;3 12]]]\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":341,"title":"count to vector","description":"Return a matrix of numbers of dimension K by N, where K = prod(v), and N=length(v). The rows count from a vector of ones up to v, where the nth element of a row can take on the values 1:v(n).\r\n","description_html":"\u003cp\u003eReturn a matrix of numbers of dimension K by N, where K = prod(v), and N=length(v). The rows count from a vector of ones up to v, where the nth element of a row can take on the values 1:v(n).\u003c/p\u003e","function_template":"function y = count_to_v(v)\r\n y = x;\r\nend","test_suite":"%%\r\nv = [1 2];\r\ny_correct = [1 1; 1 2];\r\nassert(isequal(count_to_v(v),y_correct))\r\n%%\r\nv = [3 2];\r\ny_correct = [1 1; 1 2; 2 1; 2 2; 3 1; 3 2];\r\nassert(isequal(count_to_v(v),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":2,"created_by":153,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":92,"test_suite_updated_at":"2012-02-19T04:04:35.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-02-19T04:02:49.000Z","updated_at":"2026-03-11T12:09:55.000Z","published_at":"2012-02-19T04:10:20.000Z","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\u003eReturn a matrix of numbers of dimension K by N, where K = prod(v), and N=length(v). The rows count from a vector of ones up to v, where the nth element of a row can take on the values 1:v(n).\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":1737,"title":"The sum of individual numbers...","description":"Well this one is taking a number and then summing the individual parts till you reach a value of 1, 2, 3, 4, 5, 6, 7, 8, 9, or 0 (only if the original is 0 the answer will be 0). For example:\r\n \r\n x = [103]; So ---\u003e 1+0+3 = 4\r\n output = 4;\r\n\r\nanother example:\r\n\r\n x = [99]; So ---\u003e 9+9 = 18 ---\u003e 1+8 = 9\r\n output = 9;\r\n\r\nanother example:\r\n \r\n x = [1199]; So ---\u003e 1+1+9+9 = 20 ---\u003e 2+0 = 2\r\n output = 2;\r\n\r\n\r\nanother example:\r\n\r\n x = [11 3]; So ---\u003e 1+1 = 2 and 3 = 3\r\n output = [2 3];\r\n","description_html":"\u003cp\u003eWell this one is taking a number and then summing the individual parts till you reach a value of 1, 2, 3, 4, 5, 6, 7, 8, 9, or 0 (only if the original is 0 the answer will be 0). For example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ex = [103]; So ---\u003e 1+0+3 = 4\r\noutput = 4;\r\n\u003c/pre\u003e\u003cp\u003eanother example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ex = [99]; So ---\u003e 9+9 = 18 ---\u003e 1+8 = 9\r\noutput = 9;\r\n\u003c/pre\u003e\u003cp\u003eanother example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ex = [1199]; So ---\u003e 1+1+9+9 = 20 ---\u003e 2+0 = 2\r\noutput = 2;\r\n\u003c/pre\u003e\u003cp\u003eanother example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ex = [11 3]; So ---\u003e 1+1 = 2 and 3 = 3\r\noutput = [2 3];\r\n\u003c/pre\u003e","function_template":"function y = individualNumSum(x)\r\ny = x;\r\nend","test_suite":"%%\r\nx = [1];\r\ny = [1];\r\nassert(isequal(individualNumSum(x),y))\r\n%%\r\nx = [103];\r\ny = [4];\r\nassert(isequal(individualNumSum(x),y))\r\n%%\r\nx=[189 22 39 88 55 485 769 215 3685 4589];\r\ny = [9 4 3 7 1 8 4 8 4 8];\r\nassert(isequal(individualNumSum(x),y))\r\n%%\r\nx=[1111 2222 3333 4444 5555 6666 7777 8888 9999 0];\r\ny = [4 8 3 7 2 6 1 5 9 0];\r\nassert(isequal(individualNumSum(x),y))\r\n%%\r\nx=[111 222 333 444 555 666 777 888 999 0];\r\ny = [3 6 9 3 6 9 3 6 9 0];\r\nassert(isequal(individualNumSum(x),y))\r\n%%\r\nx=[11 3];\r\ny = [2 3];\r\nassert(isequal(individualNumSum(x),y))","published":true,"deleted":false,"likes_count":3,"comments_count":0,"created_by":15013,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":85,"test_suite_updated_at":"2013-07-22T18:34:35.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-07-22T18:22:26.000Z","updated_at":"2026-04-02T15:51:44.000Z","published_at":"2013-07-22T18:34:35.000Z","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\u003eWell this one is taking a number and then summing the individual parts till you reach a value of 1, 2, 3, 4, 5, 6, 7, 8, 9, or 0 (only if the original is 0 the answer will be 0). For 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[x = [103]; So ---\u003e 1+0+3 = 4\\noutput = 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\u003eanother 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[x = [99]; So ---\u003e 9+9 = 18 ---\u003e 1+8 = 9\\noutput = 9;]]\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\u003eanother 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[x = [1199]; So ---\u003e 1+1+9+9 = 20 ---\u003e 2+0 = 2\\noutput = 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\u003eanother 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[x = [11 3]; So ---\u003e 1+1 = 2 and 3 = 3\\noutput = [2 3];]]\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":2530,"title":"Powers Of","description":"Fill the vector with powers of 2, so that vector(1) is 2^1, vector(2) is 2^2, etc. Stop with vector(10). Complete the function using a *for* loop.","description_html":"\u003cp\u003eFill the vector with powers of 2, so that vector(1) is 2^1, vector(2) is 2^2, etc. Stop with vector(10). Complete the function using a \u003cb\u003efor\u003c/b\u003e loop.\u003c/p\u003e","function_template":"function vector = PowersOf(vector)\r\n for ?\r\n ?\r\n end\r\nend","test_suite":"%%\r\nvector1 = [0 0 0 0 0 0 0 0 0 0];\r\nvector1_correct = [2 4 8 16 32 64 128 256 512 1024];\r\ncode = textread('PowersOf.m', '%s');\r\nassert(isequal(PowersOf(vector1), vector1_correct) \u0026\u0026 ...\r\n strcmp(code(5), 'for') \u0026\u0026 ...\r\n strcmp(code(end-7), 'end') \u0026\u0026 ...\r\n strcmp(code(end-6), 'end'));","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":24594,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":108,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2014-08-26T12:47:32.000Z","updated_at":"2026-03-22T17:55:53.000Z","published_at":"2014-08-26T13:56:12.000Z","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\u003eFill the vector with powers of 2, so that vector(1) is 2^1, vector(2) is 2^2, etc. Stop with vector(10). Complete the function using 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:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efor\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e loop.\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":763,"title":"Find the elements of a matrix according to a defined property.","description":"From A = [5,2,3] and B = [1,2,3,4,5,6,7,8,9,10] produce a vector C where :\r\n\r\nC(1) is the sum of the first A(1) elements of B,\r\n\r\nC(2) is the sum of the next A(2) elements of B, etc.\r\n\r\nc(i) = 0 if A(i) = 0.\r\n\r\nout-\u003e [15 13 27];","description_html":"\u003cp\u003eFrom A = [5,2,3] and B = [1,2,3,4,5,6,7,8,9,10] produce a vector C where :\u003c/p\u003e\u003cp\u003eC(1) is the sum of the first A(1) elements of B,\u003c/p\u003e\u003cp\u003eC(2) is the sum of the next A(2) elements of B, etc.\u003c/p\u003e\u003cp\u003ec(i) = 0 if A(i) = 0.\u003c/p\u003e\u003cp\u003eout-\u003e [15 13 27];\u003c/p\u003e","function_template":"function C = your_fcn_name(A,B)\r\n C = A;\r\nend","test_suite":"%%\r\nA = [4,1,2,3];B = [1,2,3,4,5,6,7,8,9,10];\r\ny_correct = [10 5 13 27];\r\nassert(isequal(your_fcn_name(A,B),y_correct))\r\n\r\n%%\r\nA = [5,2,0,3];B = [1,2,3,4,5,6,7,8,9,10];\r\ny_correct = [15 13 0 27];\r\nassert(isequal(your_fcn_name(A,B),y_correct))","published":true,"deleted":false,"likes_count":3,"comments_count":0,"created_by":1309,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":91,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-06-13T05:06:25.000Z","updated_at":"2025-12-07T18:47:04.000Z","published_at":"2012-06-13T05:08:34.000Z","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\u003eFrom A = [5,2,3] and B = [1,2,3,4,5,6,7,8,9,10] produce a vector C where :\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\u003eC(1) is the sum of the first A(1) elements of 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\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eC(2) is the sum of the next A(2) elements of B, etc.\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\u003ec(i) = 0 if A(i) = 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\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eout-\u003e [15 13 27];\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":44439,"title":"Remove the air bubbles from a vector","description":"_*A reduced version of Problem 112*_\r\n\r\nGiven a column vector v, return a vector w in which all the zeros have \"bubbled\" to the top. The order of the remaining nonzero numbers in the vector should be preserved.\r\n\r\nExample:\r\n\r\n Input v = [1\r\n 3\r\n 0\r\n 5\r\n 0\r\n -1]\r\n\r\n Output w = [0\r\n 0\r\n 1\r\n 3\r\n 5\r\n -1]","description_html":"\u003cp\u003e\u003ci\u003e\u003cb\u003eA reduced version of Problem 112\u003c/b\u003e\u003c/i\u003e\u003c/p\u003e\u003cp\u003eGiven a column vector v, return a vector w in which all the zeros have \"bubbled\" to the top. The order of the remaining nonzero numbers in the vector should be preserved.\u003c/p\u003e\u003cp\u003eExample:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eInput v = [1\r\n 3\r\n 0\r\n 5\r\n 0\r\n -1]\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003eOutput w = [0\r\n 0\r\n 1\r\n 3\r\n 5\r\n -1]\r\n\u003c/pre\u003e","function_template":"function w = bubbles(v)\r\n w = v;\r\nend","test_suite":"%%\r\nfiletext = fileread('bubbles.m');\r\nassert(isempty(strfind(filetext, 'regexp')),'regexp hacks are forbidden')\r\n\r\n%%\r\nv = [1 3 0 5 0 -1]';\r\nw_correct = [0 0 1 3 5 -1]';\r\nassert(isequal(bubbles(v),w_correct))\r\n\r\n%%\r\nv = [0 0 9 2 6]';\r\nw_correct = v;\r\nassert(isequal(bubbles(v),w_correct))\r\n\r\n%%\r\nv = [1 3 5 -1]';\r\nw_correct = v;\r\nassert(isequal(bubbles(v),w_correct))\r\n\r\n%%\r\nv = [0 1 0 1 1 1 0]';\r\nw_correct = [0 0 0 1 1 1 1]';\r\nassert(isequal(bubbles(v),w_correct))\r\n","published":true,"deleted":false,"likes_count":4,"comments_count":1,"created_by":140356,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":193,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-12-03T21:41:30.000Z","updated_at":"2026-03-30T19:08:33.000Z","published_at":"2017-12-03T21:41:30.000Z","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: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:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eA reduced version of Problem 112\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 column vector v, return a vector w in which all the zeros have \\\"bubbled\\\" to the top. The order of the remaining nonzero numbers in the vector should be preserved.\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 v = [1\\n 3\\n 0\\n 5\\n 0\\n -1]\\n\\nOutput w = [0\\n 0\\n 1\\n 3\\n 5\\n -1]]]\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":42581,"title":"Create sequnce 1 4 9 16 25.........","description":"Create sequnce 1 4 9 16 25......... upto entered input value using matlab scripting commands. Let y be output and x be input","description_html":"\u003cp\u003eCreate sequnce 1 4 9 16 25......... upto entered input value using matlab scripting commands. Let y be output and x be input\u003c/p\u003e","function_template":"function y = prntseq(x)\r\n% Enter code\r\nend","test_suite":"%%\r\nx = 25;\r\ny_correct = [1 4 9 16 25];\r\nassert(isequal(prntseq(x),y_correct))\r\n%%\r\nx = 100;\r\ny_correct = [1 4 9 16 25 36 49 64 81 100];\r\nassert(isequal(prntseq(x),y_correct))\r\n%%\r\nx = 9;\r\ny_correct = [1 4 9];\r\nassert(isequal(prntseq(x),y_correct))\r\n%%\r\nx = 36;\r\ny_correct = [1 4 9 16 25 36];\r\nassert(isequal(prntseq(x),y_correct))","published":true,"deleted":false,"likes_count":4,"comments_count":0,"created_by":46868,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":414,"test_suite_updated_at":"2015-08-28T11:26:07.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2015-08-28T11:17:32.000Z","updated_at":"2026-02-08T06:17:39.000Z","published_at":"2015-08-28T11:26:07.000Z","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\u003eCreate sequnce 1 4 9 16 25......... upto entered input value using matlab scripting commands. Let y be output and x be input\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":43109,"title":"How many complete pizzas (number 2)","description":"x is a vector with numbers of pizza slices. A corresponding vector n indicates in how many slices the pizza slices of x were cut and t is a vector indicating the type of pizza (e.g. 1 is a margarita, 2 is a peperoni, etc.). How many complete pizzas do we have, when we cannot join 2 different pizzas?\r\n\r\nExample:\r\n\r\n x = [1 3 12];\r\n n = [2 6 8];\r\n t = [1 2 1];\r\n\r\nin the first column we have on slice (x=1) from a pizza margarita (t=1) cut in half (n=2) -\u003e half a pizza margarita. in the second column we have 3 slices (x=3) from a peperoni pizza (t=2) cut in 6 slices (n=6) -\u003e so half a peperoni pizza. in the third column we have 12 slices of a margarita pizzas (t=1) cut in 8 slices -\u003e1.5 slices margarita pizza.\r\n\r\nso we can combine this to 2 pizza margaritas and 0.5 peperoni pizza. So in total we can combine 2 pizzas.","description_html":"\u003cp\u003ex is a vector with numbers of pizza slices. A corresponding vector n indicates in how many slices the pizza slices of x were cut and t is a vector indicating the type of pizza (e.g. 1 is a margarita, 2 is a peperoni, etc.). How many complete pizzas do we have, when we cannot join 2 different pizzas?\u003c/p\u003e\u003cp\u003eExample:\u003c/p\u003e\u003cpre\u003e x = [1 3 12];\r\n n = [2 6 8];\r\n t = [1 2 1];\u003c/pre\u003e\u003cp\u003ein the first column we have on slice (x=1) from a pizza margarita (t=1) cut in half (n=2) -\u0026gt; half a pizza margarita. in the second column we have 3 slices (x=3) from a peperoni pizza (t=2) cut in 6 slices (n=6) -\u0026gt; so half a peperoni pizza. in the third column we have 12 slices of a margarita pizzas (t=1) cut in 8 slices -\u0026gt;1.5 slices margarita pizza.\u003c/p\u003e\u003cp\u003eso we can combine this to 2 pizza margaritas and 0.5 peperoni pizza. So in total we can combine 2 pizzas.\u003c/p\u003e","function_template":"function y = completePizzas(x,n,t)\r\n y = x;\r\nend","test_suite":"%%%%\r\n x = [1 3 12];\r\n n = [2 6 8];\r\n t = [1 2 1];\r\ny_correct = 2;\r\nassert(isequal(completePizzas(x,n,t),y_correct))\r\n%%\r\n x = [1 3 12];\r\n n = [2 6 8];\r\n t = [1 1 1];\r\ny_correct = 2;\r\nassert(isequal(completePizzas(x,n,t),y_correct))\r\n%%\r\n x = [1 3 12];\r\n n = [2 6 8];\r\n t = [1 1 2];\r\ny_correct = 2;\r\nassert(isequal(completePizzas(x,n,t),y_correct))\r\n%%\r\n x = [1 3 12];\r\n n = [2 6 8];\r\n t = [1 2 3];\r\ny_correct = 1;\r\nassert(isequal(completePizzas(x,n,t),y_correct))\r\n%%\r\n x = [1 3 58 41 24 7 5];\r\n n = [2 6 8 50 5 4 3];\r\n t = [1 2 3 1 4 2 3];\r\ny_correct = 15;\r\nassert(isequal(completePizzas(x,n,t),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":1,"created_by":94929,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":22,"test_suite_updated_at":"2016-10-21T17:41:02.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-06T08:13:26.000Z","updated_at":"2026-01-20T12:37:21.000Z","published_at":"2016-10-06T08:13:26.000Z","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\u003ex is a vector with numbers of pizza slices. A corresponding vector n indicates in how many slices the pizza slices of x were cut and t is a vector indicating the type of pizza (e.g. 1 is a margarita, 2 is a peperoni, etc.). How many complete pizzas do we have, when we cannot join 2 different pizzas?\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[ x = [1 3 12];\\n n = [2 6 8];\\n t = [1 2 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\u003ein the first column we have on slice (x=1) from a pizza margarita (t=1) cut in half (n=2) -\u0026gt; half a pizza margarita. in the second column we have 3 slices (x=3) from a peperoni pizza (t=2) cut in 6 slices (n=6) -\u0026gt; so half a peperoni pizza. in the third column we have 12 slices of a margarita pizzas (t=1) cut in 8 slices -\u0026gt;1.5 slices margarita pizza.\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 we can combine this to 2 pizza margaritas and 0.5 peperoni pizza. So in total we can combine 2 pizzas.\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":44398,"title":"ベクトルの値が増加しているかを調べよう","description":"ベクトルの値が増加している場合 (ベクトルの各要素が前の要素よりも大きい場合) には true を、そうでない場合には false を返すようなコードを書いてみましょう。\r\n\r\n例:\r\n\r\n 入力が x = [-3 0 7] のとき、\r\n 関数の出力 tf は true を返します。\r\n\r\n 入力が x = [2 2] のとき、\r\n 関数の出力 tf は false を返します。\r\n\r\n* (英語版) Problem 10. Determine whether a vector is monotonically increasing\r\n\u003chttps://www.mathworks.com/matlabcentral/cody/problems/10-determine-whether-a-vector-is-monotonically-increasing\u003e","description_html":"\u003cp\u003eベクトルの値が増加している場合 (ベクトルの各要素が前の要素よりも大きい場合) には true を、そうでない場合には false を返すようなコードを書いてみましょう。\u003c/p\u003e\u003cp\u003e例:\u003c/p\u003e\u003cpre\u003e 入力が x = [-3 0 7] のとき、\r\n 関数の出力 tf は true を返します。\u003c/pre\u003e\u003cpre\u003e 入力が x = [2 2] のとき、\r\n 関数の出力 tf は false を返します。\u003c/pre\u003e\u003cul\u003e\u003cli\u003e(英語版) Problem 10. Determine whether a vector is monotonically increasing \u003ca href = \"https://www.mathworks.com/matlabcentral/cody/problems/10-determine-whether-a-vector-is-monotonically-increasing\"\u003ehttps://www.mathworks.com/matlabcentral/cody/problems/10-determine-whether-a-vector-is-monotonically-increasing\u003c/a\u003e\u003c/li\u003e\u003c/ul\u003e","function_template":"function tf = mono_increase(x)\r\n tf = false;\r\nend","test_suite":"%%\r\nx = [0 1 2 3 4];\r\nassert(isequal(mono_increase(x),true));\r\n%%\r\nx = [0];\r\nassert(isequal(mono_increase(x),true));\r\n%%\t\r\nx = [0 0 0 0 0];\r\nassert(isequal(mono_increase(x),false));\r\n%%\t\r\nx = [0 1 2 3 -4];\r\nassert(isequal(mono_increase(x),false));\r\n%%\t\r\nx = [-3 -4 2 3 4];\r\nassert(isequal(mono_increase(x),false));\r\n%%\r\nx = 1:.1:10;\r\nassert(isequal(mono_increase(x),true));\r\n%%\t\r\nx = cumsum(rand(1,100));\r\nx(5) = -1;\r\nassert(isequal(mono_increase(x),false));\r\n%%\t\r\nx = cumsum(rand(1,50));\r\nassert(isequal(mono_increase(x),true));","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":11824,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":367,"test_suite_updated_at":"2017-11-05T23:19:13.000Z","rescore_all_solutions":false,"group_id":36,"created_at":"2017-11-05T23:15:41.000Z","updated_at":"2026-03-17T03:46:51.000Z","published_at":"2017-11-05T23:19:13.000Z","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\",\"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\u003eベクトルの値が増加している場合 (ベクトルの各要素が前の要素よりも大きい場合) には true を、そうでない場合には false を返すようなコードを書いてみましょう。\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例:\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[ 入力が x = [-3 0 7] のとき、\\n 関数の出力 tf は true を返します。\\n\\n 入力が x = [2 2] のとき、\\n 関数の出力 tf は false を返します。]]\u003e\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=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e(英語版) Problem 10. Determine whether a vector is monotonically increasing\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/10-determine-whether-a-vector-is-monotonically-increasing\\\"\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026lt;https://www.mathworks.com/matlabcentral/cody/problems/10-determine-whether-a-vector-is-monotonically-increasing\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026gt;\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":1038,"title":"Change the sign of even index entries of the reversed vector","description":"change the signs of the even index entries of the reversed vector\r\n\r\nexample 1\r\nvec = [4 -1 -2 9]\r\nans = [9 2 -1 -4]\r\n\r\nexample2\r\nvec = [-4 -1 -2 -9]\r\nans = [-9 2 -1 4]","description_html":"\u003cp\u003echange the signs of the even index entries of the reversed vector\u003c/p\u003e\u003cp\u003eexample 1\r\nvec = [4 -1 -2 9]\r\nans = [9 2 -1 -4]\u003c/p\u003e\u003cp\u003eexample2\r\nvec = [-4 -1 -2 -9]\r\nans = [-9 2 -1 4]\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = [4 -5 -2 9];\r\ny_correct = [9 2 -5 -4];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = ones(1,4);\r\ny_correct = [1 -1 1 -1];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = 1:10;\r\ny_correct = [10 -9 8 -7 6 -5 4 -3 2 -1];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = 2:2:12;\r\ny_correct = [12 -10 8 -6 4 -2];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = -3:3;\r\ny_correct = [3 -2 1 0 -1 2 -3];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = [1 1 2 3 5 8 13 21 34 55 89 144];\r\ny_correct = [144 -89 55 -34 21 -13 8 -5 3 -2 1 -1];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = [1 0 1 0 1 0 1 0 1 0 1 0];\r\ny_correct = [0 -1 0 -1 0 -1 0 -1 0 -1 0 -1];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = [0 1 0 2 0 3 0 4 0 5 0 6];\r\ny_correct = [6 0 5 0 4 0 3 0 2 0 1 0];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = [0 1 0 1 0 1 0 1 0 1 0 1];\r\ny_correct = [x(2:end) x(1)];\r\nassert(isequal(your_fcn_name(x),y_correct))","published":true,"deleted":false,"likes_count":5,"comments_count":1,"created_by":1023,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":646,"test_suite_updated_at":"2016-11-18T03:05:04.000Z","rescore_all_solutions":false,"group_id":13,"created_at":"2012-11-19T03:18:07.000Z","updated_at":"2026-04-02T19:22:10.000Z","published_at":"2012-11-19T03:18:34.000Z","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\u003echange the signs of the even index entries of the reversed 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 1 vec = [4 -1 -2 9] ans = [9 2 -1 -4]\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\u003eexample2 vec = [-4 -1 -2 -9] ans = [-9 2 -1 4]\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\"}]}"}],"problem_search":{"errors":[],"problems":[{"id":42714,"title":"Throw common elements of two vector arrays","description":"\r\nThrow common elements as output of two given input vector arrays","description_html":"\u003cp\u003eThrow common elements as output of two given input vector arrays\u003c/p\u003e","function_template":"function y = common(A,B)\r\n %y = common(A,B);\r\nend","test_suite":"%%\r\nA = [1 2 3 4 5 6 7 8];\r\nB = [4 5 6 6 7 0 12 34];\r\ny_correct = [4 5 6 7];\r\nassert(isequal(common(A,B),y_correct))\r\n\r\n%%\r\nA = [11 34 23 09 1];\r\nB = [12 33 21 8 1];\r\ny_correct = 1;\r\nassert(isequal(common(A,B),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":46868,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":87,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-01-15T10:05:41.000Z","updated_at":"2026-04-02T18:54:02.000Z","published_at":"2016-01-15T10:05:41.000Z","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\u003eThrow common elements as output of two given input vector arrays\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":45260,"title":"Alternate elements!","description":"Write a function that combines two lists by alternating the elements, e.g. ['a','b','c'], ['1','2','3'] → 'a1b2c3'.","description_html":"\u003cp\u003eWrite a function that combines two lists by alternating the elements, e.g. ['a','b','c'], ['1','2','3'] → 'a1b2c3'.\u003c/p\u003e","function_template":"function z = your_fcn_name(x,y)\r\n z...;\r\nend","test_suite":"%%\r\nx = ['a', 'b', 'c'];\r\ny = ['1', '2', '3'];\r\nz_correct = 'a1b2c3';\r\nassert(isequal(your_fcn_name(x,y),z_correct))\r\n\r\n%%\r\nx = ['c', 'a', 'b', 'f'];\r\ny = ['3', '1', '2', '0'];\r\nz_correct = 'c3a1b2f0';\r\nassert(isequal(your_fcn_name(x,y),z_correct))\r\n\r\n%%\r\nx = ['c', '1', 'b', 'f'];\r\ny = ['3', '1', '2', '0'];\r\nz_correct = 'c311b2f0';\r\nassert(isequal(your_fcn_name(x,y),z_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":274816,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":57,"test_suite_updated_at":"2020-01-08T20:39:30.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-01-08T20:38:52.000Z","updated_at":"2026-02-15T08:30:42.000Z","published_at":"2020-01-08T20:38:52.000Z","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\u003eWrite a function that combines two lists by alternating the elements, e.g. ['a','b','c'], ['1','2','3'] → 'a1b2c3'.\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":60689,"title":"Sum All Positive Elements","description":"Output a scalar that is equal to the sum of all positive elements in a given vector/matrix.\r\nFor Example:\r\nThe sum of all positive elements in [1 2 -4 -8] should be 3...\r\nThe sum of all positive elements in [1 2; 5 -6; 2 -10] should be 10...","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: 111px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 55.5px; transform-origin: 407px 55.5px; 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-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: 270.317px 8px; transform-origin: 270.317px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eOutput a scalar that is equal to the sum of all positive elements in a given vector/matrix.\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-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: 41.6167px 8px; transform-origin: 41.6167px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor Example:\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-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: 183.192px 8px; transform-origin: 183.192px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe sum of all positive elements in [1 2 -4 -8] should be 3...\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-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: 206.525px 8px; transform-origin: 206.525px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThe sum of all positive elements in [1 2; 5 -6; 2 -10] should be 10...\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = pos_sum(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = [1 2 3 -4];\r\ny_correct = 6;\r\nassert(isequal(pos_sum(x),y_correct))\r\n%%\r\nx = -105;\r\ny_correct = 0;\r\nassert(isequal(pos_sum(x),y_correct))\r\n%%\r\nx = ones(3);\r\ny_correct = 9;\r\nassert(isequal(pos_sum(x),y_correct))\r\n%%\r\nx = [4 -10 -8; -7 -9 100; -25 3 2];\r\ny_correct = 109;\r\nassert(isequal(pos_sum(x),y_correct))\r\n%%\r\nx = [-1 -2 -3 -4; -5 -6 -7 -8; -9 -10 -11 -12;...\r\n -13 -14 -15 -16];\r\ny_correct = 0;\r\nassert(isequal(pos_sum(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":4585291,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":40,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2024-08-06T23:02:55.000Z","updated_at":"2026-03-23T02:39:40.000Z","published_at":"2024-08-06T23:02:55.000Z","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\u003eOutput a scalar that is equal to the sum of all positive elements in a given vector/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\u003cw:jc w:val=\\\"left\\\"/\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=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe sum of all positive elements in [1 2 -4 -8] should be 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\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe sum of all positive elements in [1 2; 5 -6; 2 -10] should be 10...\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":42715,"title":" Throw common elements of two vector arrays in sorted manner","description":"\r\nThrow common elements as output in sorted manner (acending order) of two given input vector arrays","description_html":"\u003cp\u003eThrow common elements as output in sorted manner (acending order) of two given input vector arrays\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n y = x;\r\nend","test_suite":"%%\r\nA = [1 2 3 4 5 6 7 8];\r\nB = [4 5 6 6 7 0 12 34];\r\ny_correct = [7 6 5 4];\r\nassert(isequal(your_fcn_name(A,B),y_correct))\r\n\r\n%%\r\nA = [1 2 3 4 5 6 71 8];\r\nB = [4 5 6 6 7 0 12 34];\r\ny_correct = [6 5 4];\r\nassert(isequal(your_fcn_name(A,B),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":2,"created_by":46868,"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":1,"created_at":"2016-01-15T10:10:48.000Z","updated_at":"2026-02-28T08:11:04.000Z","published_at":"2016-01-15T10:17:09.000Z","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\u003eThrow common elements as output in sorted manner (acending order) of two given input vector arrays\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":52000,"title":"Vector creation using linspace","description":"Create a vector y containing n uniformly spaced values between a and b, with a \u003c b. Use linspace. ","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: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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: 91px 8px; transform-origin: 91px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCreate a vector y containing \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: 4.5px 8px; transform-origin: 4.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003en\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: 108.5px 8px; transform-origin: 108.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e uniformly spaced values between \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: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\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: 16px 8px; transform-origin: 16px 8px; 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: 4.5px 8px; transform-origin: 4.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eb\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: 52px 8px; transform-origin: 52px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, with a \u0026lt; b. Use \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: 26px 8px; transform-origin: 26px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"text-decoration: underline; text-decoration-line: underline; \"\u003elinspace\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: 4px 8px; transform-origin: 4px 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 = your_fcn_name(a,b,n) %% Do not change this line\r\n y = 1;\r\nend %% Do not change this line","test_suite":"%%\r\na = 2; b = 12; n = 6;\r\ny_correct = [2 4 6 8 10 12];\r\nassert(isequal(your_fcn_name(a,b,n),y_correct))\r\n%%\r\na = 10; b = 100; n = 11;\r\ny_correct = [ 10 19 28 37 46 55 64 73 82 91 100];\r\nassert(isequal(your_fcn_name(a,b,n),y_correct))\r\n%%\r\nfiletext = fileread('your_fcn_name.m');\r\nassert(isempty(strfind(filetext, ':')),'colon (:) forbidden')\r\n%%\r\nfiletext = fileread('your_fcn_name.m');\r\nassert(isempty(strfind(filetext, 'linspace'))==0,'use linspace')","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":428668,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":60,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2021-06-06T02:00:45.000Z","updated_at":"2026-02-11T18:34:00.000Z","published_at":"2021-06-06T02:00:45.000Z","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\u003eCreate a vector y containing \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e uniformly spaced values between \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ea\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:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eb\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, with a \u0026lt; b. Use \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:u/\u003e\u003c/w:rPr\u003e\u003cw:t\u003elinspace\u003c/w:t\u003e\u003c/w:r\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":54860,"title":"Create a column vector of n elements between a and b (both included)","description":"Given lower limit a and an upper limit b, create a column vector of n elements inclusive of a and b.\r\nFor example: a = 1, b = 4, n = 4 \r\n y = [1;2;3;4];","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: 81px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 40.5px; transform-origin: 407px 40.5px; 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=\"\"\u003eGiven lower limit a and an upper limit b, create a \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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003ecolumn\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e vector of n elements inclusive of a and b.\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=\"\"\u003eFor example: a = 1, b = 4, n = 4 \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 y = [1;2;3;4];\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(a, b, n)\r\n \r\nend","test_suite":"%%\r\na = 1;\r\nb = 1;\r\nn = 1;\r\ny_correct = 1;\r\nassert(isequal(your_fcn_name(a, b, n),y_correct))\r\n\r\n%%\r\na = 1;\r\nb = 10;\r\nn = 3;\r\ny_correct = [1; 5.5; 10];\r\nassert(isequal(your_fcn_name(a, b, n),y_correct))\r\n\r\n%%\r\na = 2;\r\nb = 10;\r\nn = 5;\r\ny_correct = [2;4;6;8;10];\r\nassert(isequal(your_fcn_name(a, b, n),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":2436220,"edited_by":2436220,"edited_at":"2022-07-12T14:26:21.000Z","deleted_by":null,"deleted_at":null,"solvers_count":27,"test_suite_updated_at":"2022-07-12T14:26:21.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2022-07-12T14:20:07.000Z","updated_at":"2026-03-09T18:48:18.000Z","published_at":"2022-07-12T14:26:21.000Z","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\u003eGiven lower limit a and an upper limit b, create a \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ecolumn\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e vector of n elements inclusive of a and 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\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example: a = 1, b = 4, n = 4 \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 y = [1;2;3;4];\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":58683,"title":"Find sum of alternate numbers in a vector","description":"Find sum of alternate numbers in a vector starting from index 1","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: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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-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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFind sum of alternate numbers in a vector starting from index 1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = sum_alternate(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = [1 2 3 4 5];\r\ny_correct = 9;\r\nassert(isequal(sum_alternate(x),y_correct))\r\n\r\n%%\r\nx = [1 2 3 4 5 0 1];\r\ny_correct = 10;\r\nassert(isequal(sum_alternate(x),y_correct))\r\n\r\n%%\r\nx = [1 2 0];\r\ny_correct = 1;\r\nassert(isequal(sum_alternate(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3494818,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":35,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-07-18T15:55:48.000Z","updated_at":"2026-02-05T16:30:51.000Z","published_at":"2023-07-18T15:55:48.000Z","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 sum of alternate numbers in a vector starting from index 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":54975,"title":"Find Min and Max Differences in a Vector","description":"Given an array of integers, return the absolute largest and smallest (non zero) difference between any two numbers in the array.","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: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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: 384px 8px; transform-origin: 384px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven an array of integers, return the absolute largest and smallest (non zero) difference between any two numbers in the array.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function minThenMax = your_fcn_name(x)\r\n minThenMax = x;\r\nend","test_suite":"%%\r\nx = [1 2 3 4];\r\ny_correct = [1 3];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = [1 1 2 3];\r\ny_correct = [1 2]\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = primes(20);\r\ny_correct = [1 17]\r\nassert(isequal(your_fcn_name(x),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":2434420,"edited_by":223089,"edited_at":"2022-10-29T10:18:06.000Z","deleted_by":null,"deleted_at":null,"solvers_count":50,"test_suite_updated_at":"2022-10-29T10:18:06.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2022-07-12T16:41:10.000Z","updated_at":"2026-02-28T08:18:38.000Z","published_at":"2022-07-12T16:41:10.000Z","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\u003eGiven an array of integers, return the absolute largest and smallest (non zero) difference between any two numbers in the array.\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":42347,"title":"Create a Standard Size Vector","description":"Given an input x, create a row vector y from 1 to x with 5 elements.","description_html":"\u003cp\u003eGiven an input x, create a row vector y from 1 to x with 5 elements.\u003c/p\u003e","function_template":"function y = standard_vector(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = 220;\r\ny_correct = [1.0000 55.7500 110.5000 165.2500 220.0000];\r\nassert(isequal(standard_vector(x),y_correct))\r\n\r\n%%\r\nx = 801;\r\ny_correct = [ 1 201 401 601 801];\r\nassert(isequal(standard_vector(x),y_correct))\r\n\r\n%%\r\nx = 4;\r\ny_correct = [ 1.0000 1.7500 2.5000 3.2500 4.000];\r\nassert(isequal(standard_vector(x),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":44605,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":150,"test_suite_updated_at":"2015-06-17T17:59:34.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2015-06-01T01:19:15.000Z","updated_at":"2026-02-17T17:52:43.000Z","published_at":"2015-06-01T01:19:15.000Z","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 an input x, create a row vector y from 1 to x with 5 elements.\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":43104,"title":"Magnitude of a vector","description":"Given a vector x, what is its magnitude?","description_html":"\u003cp\u003eGiven a vector x, what is its magnitude?\u003c/p\u003e","function_template":"function y = magnitude(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = 1;\r\ny_correct = 1;\r\nassert(isequal(magnitude(x),y_correct))\r\n%%\r\nx = [1 1];\r\ny_correct = sqrt(2);\r\nassert(isequal(magnitude(x),y_correct))\r\n%%\r\nx = [1 2];\r\ny_correct = sqrt(5);\r\nassert(isequal(magnitude(x),y_correct))\r\n%%\r\nx = [1 1 1];\r\ny_correct = sqrt(3);\r\nassert(isequal(magnitude(x),y_correct))\r\n%%\r\nx = [1 1 1 1];\r\ny_correct = sqrt(4);\r\nassert(isequal(magnitude(x),y_correct))\r\n%%\r\nx = [1 1 1 2];\r\ny_correct = sqrt(7);\r\nassert(isequal(magnitude(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":94929,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":99,"test_suite_updated_at":"2016-10-19T11:39:56.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-06T07:39:55.000Z","updated_at":"2026-02-13T18:50:52.000Z","published_at":"2016-10-06T07:39:55.000Z","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 vector x, what is its magnitude?\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":54665,"title":"Find the slope of a line that passes through two vectors","description":"Given two vectors p1 and p2, return the slope of a line that passes through p1 and p2.\r\nExamples:\r\nInput [p1,p2] = deal([0,1],[1,3])\r\nOutput m = 2\r\n\r\nInput [p1,p2] = deal([-2,0],[0,1])\r\nOutput m = 0.5","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: 183.75px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 91.875px; transform-origin: 407px 91.875px; 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=\"\"\u003eGiven two vectors \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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ep1\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: 0px 0px; transform-origin: 0px 0px; \"\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ep2\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e, return the slope of a line that passes through \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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ep1\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: 0px 0px; transform-origin: 0px 0px; \"\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-style: italic; \"\u003ep2\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: 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=\"\"\u003eExamples:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 40.875px; 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 20.4375px; transform-origin: 404px 20.4375px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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 10.2188px; transform-origin: 404px 10.2188px; 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; \"\u003eInput \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); text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); \"\u003e[p1,p2] = deal([0,1],[1,3])\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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 10.2188px; transform-origin: 404px 10.2188px; 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; \"\u003eOutput \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); text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); \"\u003em = 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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 40.875px; 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 20.4375px; transform-origin: 404px 20.4375px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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 10.2188px; transform-origin: 404px 10.2188px; 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; \"\u003eInput \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); text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); \"\u003e[p1,p2] = deal([-2,0],[0,1])\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4375px; 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 10.2188px; transform-origin: 404px 10.2188px; 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; \"\u003eOutput \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); text-decoration: none; text-decoration-color: rgb(170, 4, 249); text-emphasis-color: rgb(170, 4, 249); \"\u003em = 0.5\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function m = slope(p1,p2)\r\n m = [p1 p2];\r\nend","test_suite":"%%\r\n[p1,p2] = deal([0,1],[1,3]);\r\nm_correct = 2;\r\nassert(isequal(slope(p1,p2),m_correct))\r\n%%\r\n[p1,p2] = deal([-2,0],[0,1]);\r\nm_correct = 0.5;\r\nassert(isequal(slope(p1,p2),m_correct))\r\n%%\r\n[p1,p2] = deal([-3,4],[6,-2])\r\nm_correct = -(2/3);\r\nassert(isequal(slope(p1,p2),m_correct))\r\n%%\r\n[p1,p2] = deal([-1,1],[1,1])\r\nm_correct = 0;\r\nassert(isequal(slope(p1,p2),m_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":3,"created_by":792819,"edited_by":792819,"edited_at":"2022-05-21T21:29:59.000Z","deleted_by":null,"deleted_at":null,"solvers_count":53,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2022-05-21T21:26:40.000Z","updated_at":"2026-02-10T08:28:11.000Z","published_at":"2022-05-21T21:29:59.000Z","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\u003eGiven two vectors \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ep1\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003e and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ep2\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003e, return the slope of a line that passes through \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ep1\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr/\u003e\u003cw:t\u003e and \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ep2\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr/\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: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[Input [p1,p2] = deal([0,1],[1,3])\\nOutput m = 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\u003e\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 [p1,p2] = deal([-2,0],[0,1])\\nOutput m = 0.5]]\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":44298,"title":"Simple Vector Addition","description":"Take two incoming vectors and output the sum of the two vectors","description_html":"\u003cp\u003eTake two incoming vectors and output the sum of the two vectors\u003c/p\u003e","function_template":"function added_vec = your_fcn_name(x,y)\r\n added_vec = ...;\r\nend","test_suite":"%%\r\nx = [1 2 3 4 5];\r\ny = [1 2 3 4 5];\r\nadded_vec = [2 4 6 8 10];\r\nassert(isequal(your_fcn_name(x,y),added_vec))\r\n\r\n%%\r\nx = 1:20;\r\ny = 1:20;\r\nadded_vec = 2:2:40;\r\nassert(isequal(your_fcn_name(x,y),added_vec))\r\n\r\n%%\r\nx = ones(1,100);\r\ny = ones(1,100);\r\nadded_vec = 2*ones(1,100);\r\nassert(isequal(your_fcn_name(x,y),added_vec))\r\n\r\n%%\r\nx = 42*ones(1,42);\r\ny = -42*ones(1,42);\r\nadded_vec = zeros(1,42);\r\nassert(isequal(your_fcn_name(x,y),added_vec))\r\n\r\n%%\r\nx = 5:5:100;\r\ny = ones(1,20);\r\nadded_vec = 6:5:101;\r\nassert(isequal(your_fcn_name(x,y),added_vec))\r\n\r\n%%\r\nx = mod(1:100,2);\r\ny = mod([2:100,1],2);\r\nadded_vec = ones(1,100);\r\nassert(isequal(your_fcn_name(x,y),added_vec))","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":12852,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":173,"test_suite_updated_at":"2017-09-08T19:31:29.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2017-09-06T01:06:15.000Z","updated_at":"2026-02-11T18:34:14.000Z","published_at":"2017-09-06T01:06:15.000Z","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\u003eTake two incoming vectors and output the sum of the two vectors\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":58643,"title":"Sum of Squares","description":"Given a vector v of length n, write a MATLAB function to calculate the sum of the squares of its elements.","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: 21.6667px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407.5px 10.8333px; transform-origin: 407.5px 10.8333px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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: 384.5px 10.8333px; text-align: left; transform-origin: 384.5px 10.8333px; 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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eGiven a vector \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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ev\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e of length \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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003en\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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e, write a MATLAB function to calculate the sum of the squares of its elements.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = [2, 3, 5];\r\ny_correct = 38;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3495653,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":45,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-07-18T14:38:04.000Z","updated_at":"2026-02-13T19:05:22.000Z","published_at":"2023-07-18T14:38:04.000Z","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\u003eGiven a vector \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\u003ev\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e of length \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\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, write a MATLAB function to calculate the sum of the squares of its 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\"}]}"},{"id":44299,"title":"Vector Element Multiplication","description":"Take two incoming vectors, and output the element wise multiplication of the vectors.","description_html":"\u003cp\u003eTake two incoming vectors, and output the element wise multiplication of the vectors.\u003c/p\u003e","function_template":"function ele_mult_vec = your_fcn_name(x,y)\r\n ele_mult_vec = ...;\r\nend","test_suite":"%%\r\nx = [1 2 3 4 5];\r\ny = [1 2 3 4 5];\r\nele_mult_vec = [1 4 9 16 25];\r\nassert(isequal(your_fcn_name(x,y),ele_mult_vec))\r\n\r\n%%\r\nx = ones(1,10);\r\ny = ones(1,10);\r\nele_mult_vec = ones(1,10);\r\nassert(isequal(your_fcn_name(x,y),ele_mult_vec))\r\n\r\n%%\r\nx = ones(1,10);\r\ny = 10:10:100;\r\nele_mult_vec = 10:10:100;\r\nassert(isequal(your_fcn_name(x,y),ele_mult_vec))\r\n\r\n%%\r\nx = 10:10:100;\r\ny = 0.1*ones(1,10);\r\nele_mult_vec = 1:10;\r\nassert(isequal(your_fcn_name(x,y),ele_mult_vec))\r\n\r\n%%\r\nx = 1:3;\r\ny = 4:6;\r\nele_mult_vec = [4 10 18];\r\nassert(isequal(your_fcn_name(x,y),ele_mult_vec))\r\n\r\n%%\r\nx = mod(1:100,2);\r\ny = mod([2:100,1],2);\r\nele_mult_vec = zeros(1,100);\r\nassert(isequal(your_fcn_name(x,y),ele_mult_vec))\r\n","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":12852,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":124,"test_suite_updated_at":"2017-09-08T19:34:56.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2017-09-06T01:08:51.000Z","updated_at":"2026-02-11T18:34:27.000Z","published_at":"2017-09-06T01:08:51.000Z","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\",\"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\u003eTake two incoming vectors, and output the element wise multiplication of the vectors.\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":47538,"title":"Summy's even sum","description":null,"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: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 21px; transform-origin: 407px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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=\"\"\u003eSummy wants to sum the elements of the vector x which are present at even indices. Can you help Summy by making a function which returns the required sum?\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(x)\r\n \r\nend","test_suite":"%%\r\nx = [1 2 3 4 5 6];\r\ny_correct = 12;\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n%%\r\nx = [1];\r\ny_correct = 0;\r\nassert(isequal(your_fcn_name(x),y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":731238,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":77,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-11-17T12:09:49.000Z","updated_at":"2026-02-09T14:04:03.000Z","published_at":"2020-11-17T12:10:41.000Z","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\u003eSummy wants to sum the elements of the vector x which are present at even indices. Can you help Summy by making a function which returns the required sum?\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":58593,"title":" findPositiveEvenNumbers ","description":"Write a MATLAB function findPositiveEvenNumbers that takes an array of integers as input and returns a new array containing only the positive even numbers from the input array. The output array should be sorted in ascending order.","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: 42px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407.5px 21px; transform-origin: 407.5px 21px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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: 384.5px 21px; text-align: left; transform-origin: 384.5px 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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eWrite a MATLAB function findPositiveEvenNumbers that takes an array of integers as input and returns a new array containing only the positive even numbers from the input array. The output array should be sorted in ascending order.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(inputArray)\r\n y = inputArray;\r\nend","test_suite":"%%\r\nx = [3, -2, 8, 0, -5, 12, -10, 7];\r\ny_correct = [8, 12];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":10,"comments_count":0,"created_by":3495653,"edited_by":3495653,"edited_at":"2023-07-18T13:35:17.000Z","deleted_by":null,"deleted_at":null,"solvers_count":58,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-07-17T23:19:52.000Z","updated_at":"2026-02-27T14:12:15.000Z","published_at":"2023-07-17T23:19:52.000Z","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\u003eWrite a MATLAB function findPositiveEvenNumbers that takes an array of integers as input and returns a new array containing only the positive even numbers from the input array. The output array should be sorted in ascending order.\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":43303,"title":"Pointwise multiplication of vectors.","description":"Pointwise multiplication of vectors x and y. \r\nExample x= [1 3 5 7 9 11 13 15 17 19]\r\ny=[ 1 4 7 10 13 16 19 22 25 28]\r\nresult= [ 1 12 35 70 117 176 247 330 425 532]","description_html":"\u003cp\u003ePointwise multiplication of vectors x and y. \r\nExample x= [1 3 5 7 9 11 13 15 17 19]\r\ny=[ 1 4 7 10 13 16 19 22 25 28]\r\nresult= [ 1 12 35 70 117 176 247 330 425 532]\u003c/p\u003e","function_template":"function z = your_fcn_name(x,y)\r\n z = x;\r\nend","test_suite":"%%\r\nx = [1 3 5 7 9 11 13 15 17 19];\r\ny=[ 1 4 7 10 13 16 19 22 25 28];\r\ny_correct = [ 1 12 35 70 117 176 247 330 425 532];\r\nassert(isequal(your_fcn_name(x,y),y_correct))\r\n%%\r\nx = [1 12 23 34 45 56 67 78 89 100];\r\ny=[ 1 -10 -21 -32 -43 -54 -65 -76 -87 -98];\r\ny_correct = [ 1 -120 -483 -1088 -1935 -3024 -4355 -5928 -7743 -9800];\r\nassert(isequal(your_fcn_name(x,y),y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":90467,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":112,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-10T09:58:16.000Z","updated_at":"2026-02-11T18:41:17.000Z","published_at":"2016-10-10T09:58:16.000Z","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\u003ePointwise multiplication of vectors x and y. Example x= [1 3 5 7 9 11 13 15 17 19] y=[ 1 4 7 10 13 16 19 22 25 28] result= [ 1 12 35 70 117 176 247 330 425 532]\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":44301,"title":"Find the mean of two vectors","description":"Take two vectors, and output the mean of them (bonus if you don't use the in-built mean function)","description_html":"\u003cp\u003eTake two vectors, and output the mean of them (bonus if you don't use the in-built mean function)\u003c/p\u003e","function_template":"function out_mean = your_fcn_name(x,y)\r\n out_mean = ...;\r\nend","test_suite":"%%\r\nx = [1 2 3 4 5];\r\ny = [6 7 8 9 10];\r\nout_mean = [3.5000 4.5000 5.5000 6.5000 7.5000];\r\nassert(isequal(your_fcn_name(x,y),out_mean))\r\n\r\n%%\r\nx = [1 1 2 3 5 8 13 21];\r\ny = ones(1,8);\r\nout_mean = [1 1 1.5 2 3 4.5 7 11];\r\nassert(isequal(your_fcn_name(x,y),out_mean))\r\n\r\n%%\r\nx = ones(1,100);\r\ny = 7*ones(1,100);\r\nout_mean = 4*ones(1,100);\r\nassert(isequal(your_fcn_name(x,y),out_mean))\r\n\r\n%%\r\nx = [5 3 8 1 6 7 9 4 2];\r\ny = [3 7 5 6 1 2 9 8 4];\r\nout_mean = [4 5 6.5 3.5 3.5 4.5 9 6 3];\r\nassert(isequal(your_fcn_name(x,y),out_mean))\r\n\r\n%%\r\nx = 5:-1:1;\r\ny = 1:5;\r\nout_mean = 3*ones(1,5);\r\nassert(isequal(your_fcn_name(x,y),out_mean))\r\n\r\n%%\r\nx = 42;\r\ny = -42;\r\nout_mean = 0;\r\nassert(isequal(your_fcn_name(x,y),out_mean))","published":true,"deleted":false,"likes_count":0,"comments_count":2,"created_by":12852,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":116,"test_suite_updated_at":"2017-09-08T19:42:49.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2017-09-06T01:16:44.000Z","updated_at":"2026-02-11T18:35:03.000Z","published_at":"2017-09-06T01:16:46.000Z","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\u003eTake two vectors, and output the mean of them (bonus if you don't use the in-built mean function)\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":61126,"title":"Sum of even numbers in a vector","description":"Write a function that takes a vector of numbers and returns the sum of all the even numbers in the vector.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 408.5px 10.5px; transform-origin: 408.5px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384.5px 10.5px; text-align: left; transform-origin: 384.5px 10.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function that takes a vector of numbers and returns the sum of all the even numbers in the vector.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = sumEven(x)\r\n y = x;\r\nend","test_suite":"%% Test 1: Single even number\r\nx = 2;\r\ny_correct = 2;\r\nassert(isequal(sumEven(x),y_correct))\r\n\r\n%% Test 2: Mix of even and odd\r\nx = [1 2 3 4 5 6];\r\ny_correct = 12; % 2+4+6\r\nassert(isequal(sumEven(x),y_correct))\r\n\r\n%% Test 3: All odd numbers\r\nx = [1 3 5 7];\r\ny_correct = 0;\r\nassert(isequal(sumEven(x),y_correct))\r\n\r\n%% Test 4: Empty vector\r\nx = [];\r\ny_correct = 0;\r\nassert(isequal(sumEven(x),y_correct))\r\n\r\n%% Test 5: Negative numbers included\r\nx = [-2 -3 -4 5];\r\ny_correct = -6; % -2 + -4\r\nassert(isequal(sumEven(x),y_correct))\r\n\r\n%% Test 6: Large vector\r\nx = 1:100;\r\ny_correct = sum(2:2:100); % sum of evens up to 100\r\nassert(isequal(sumEven(x),y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":5016520,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":16,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2025-12-14T03:56:27.000Z","updated_at":"2026-02-26T11:08:17.000Z","published_at":"2025-12-14T03:56:27.000Z","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\u003eWrite a function that takes a vector of numbers and returns the sum of all the even numbers in the vector.\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":2928,"title":"Find the product of a Vector","description":"How would you find the product of the vector [1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0] times 2?;\r\n\r\nx = [1 : 0.5 : 6];\r\n\r\ny = x;\r\n\r\n","description_html":"\u003cp\u003eHow would you find the product of the vector [1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0] times 2?;\u003c/p\u003e\u003cp\u003ex = [1 : 0.5 : 6];\u003c/p\u003e\u003cp\u003ey = x;\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = [1:0.5:6];\r\ny_correct = [2:12];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":34004,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":348,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2015-02-02T15:58:19.000Z","updated_at":"2026-02-10T21:50:52.000Z","published_at":"2015-02-02T15:58:19.000Z","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\u003eHow would you find the product of the vector [1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0] times 2?;\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\u003ex = [1 : 0.5 : 6];\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\u003ey = x;\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":45174,"title":"Given a vector x, return vector y with all negative elements from the vector x.","description":"Given a vector x, return vector y with all negative elements from the vector x if x has negative elements. Otherwise return 0.\r\nfor example: x=[1 2 3 4 -5 -2] y=[-5 -2]\r\n x=[1 2 3] y=0\r\n ","description_html":"\u003cp\u003eGiven a vector x, return vector y with all negative elements from the vector x if x has negative elements. Otherwise return 0.\r\nfor example: x=[1 2 3 4 -5 -2] y=[-5 -2]\r\n x=[1 2 3] y=0\u003c/p\u003e","function_template":"function y = vector(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = [1 2 2 -4 -5 -2];\r\ny_correct =[-4 -5 -2];\r\nassert(isequal(vector(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":346141,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":67,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2019-10-12T09:02:51.000Z","updated_at":"2026-03-14T13:28:45.000Z","published_at":"2019-10-12T09:07:50.000Z","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 vector x, return vector y with all negative elements from the vector x if x has negative elements. Otherwise return 0. for example: x=[1 2 3 4 -5 -2] y=[-5 -2] x=[1 2 3] y=0\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":44740,"title":"New Matrix with vector addition on diagonal","description":"consider 2 vectors \r\n\r\n x=[1 2 3]\r\n y=[4 5 6]\r\n\r\nthen generate a new Matrix, where Addition of x \u0026 y will be diagonal Elements of the new Matrix. i.e. new Matrix will have x+y=[5 7 9] as diagonal Elements\r\n\r\n Output =[5 6 7\r\n 6 7 8\r\n 7 8 9]","description_html":"\u003cp\u003econsider 2 vectors\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ex=[1 2 3]\r\ny=[4 5 6]\r\n\u003c/pre\u003e\u003cp\u003ethen generate a new Matrix, where Addition of x \u0026 y will be diagonal Elements of the new Matrix. i.e. new Matrix will have x+y=[5 7 9] as diagonal Elements\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eOutput =[5 6 7\r\n 6 7 8\r\n 7 8 9]\r\n\u003c/pre\u003e","function_template":"function z = addmat(x,y)\r\n z = x+y;\r\nend","test_suite":"%%\r\nx=[1 2 3];\r\ny=[4 5 6];\r\nz_correct = [5 6 7;6 7 8;7 8 9]\r\nassert(isequal(addmat(x,y),z_correct))\r\n\r\n%%\r\nx=[10 20 30 40];\r\ny=[-10 -20 -30 -40];\r\nz_correct = [0 10 20 30;-10 0 10 20;-20 -10 0 10;-30 -20 -10 0]\r\nassert(isequal(addmat(x,y),z_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":136465,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":47,"test_suite_updated_at":"2018-10-02T13:28:44.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2018-10-02T13:24:35.000Z","updated_at":"2026-02-27T14:16:57.000Z","published_at":"2018-10-02T13:24:35.000Z","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\u003econsider 2 vectors\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=[1 2 3]\\ny=[4 5 6]]]\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\u003ethen generate a new Matrix, where Addition of x \u0026amp; y will be diagonal Elements of the new Matrix. i.e. new Matrix will have x+y=[5 7 9] as diagonal Elements\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[Output =[5 6 7\\n 6 7 8\\n 7 8 9]]]\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":2311,"title":"Vector Magnitude Calculator","description":"'a' is a vector that starts at the origin and ends at (x, y). Find ||a||.\r\n\r\nHint: It is as simple as \"ABC\".","description_html":"\u003cp\u003e'a' is a vector that starts at the origin and ends at (x, y). Find \u003ctt\u003e|a|\u003c/tt\u003e.\u003c/p\u003e\u003cp\u003eHint: It is as simple as \"ABC\".\u003c/p\u003e","function_template":"function m = vector_magnitude(x, y)\r\n m = x;\r\nend","test_suite":"%%\r\nx = 5;\r\ny = 12;\r\nmm = 13;\r\nassert(isequal(vector_magnitude(x, y),mm))\r\n\r\n%%\r\nx = 3;\r\ny = 4;\r\nmm = 5;\r\nassert(isequal(vector_magnitude(x, y),mm))\r\n\r\n%%\r\nx = 12;\r\ny = 35;\r\nmm = 37;\r\nassert(isequal(vector_magnitude(x, y),mm))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":26349,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":167,"test_suite_updated_at":"2014-06-05T15:55:43.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2014-05-07T19:54:35.000Z","updated_at":"2026-02-18T09:28:19.000Z","published_at":"2014-05-07T19:54:35.000Z","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\u003e'a' is a vector that starts at the origin and ends at (x, y). Find\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\u003e|a\u003c/w:t\u003e\u003c/w:r\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\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eHint: It is as simple as \\\"ABC\\\".\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":46105,"title":"Find sum of numbers on the cornice of a matrix.","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=\"display: block; min-width: 0px; padding-top: 0px; vertical-align: baseline; perspective-origin: 407px 85.5px; transform-origin: 407px 85.5px; \"\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; white-space: pre-wrap; perspective-origin: 384px 10.5px; transform-origin: 384px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eGiven a matrix of random integers, calculate the sum of all the integers in the cornice of the matrix.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; white-space: pre-wrap; perspective-origin: 384px 10.5px; transform-origin: 384px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFor example if MTX = [ \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e1 3 5 6;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; white-space: pre-wrap; perspective-origin: 384px 10.5px; transform-origin: 384px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 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\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e4\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e 7 9 \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e2;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; white-space: pre-wrap; perspective-origin: 384px 10.5px; transform-origin: 384px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 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\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e5\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003e 6 1 \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e3;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; white-space: pre-wrap; perspective-origin: 384px 10.5px; transform-origin: 384px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 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\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003e 7 9 2 1\u003c/span\u003e\u003c/span\u003e\u003cspan style=\"display: inline; margin-bottom: 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=\"font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-bottom: 9px; margin-left: 4px; margin-right: 10px; margin-top: 2px; text-align: left; white-space: pre-wrap; perspective-origin: 384px 10.5px; transform-origin: 384px 10.5px; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"display: inline; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eoutput = 1 + 3 + 5 + 6 + 4 + 2 + 5 + 3 + 7 + 9 + 2 + 1 = 48\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = sumCornice(MTX)\r\n y = MTX;\r\nend","test_suite":"%% Test 1\r\nMTX = [ 1 3 5 6;\r\n 4 7 9 2;\r\n 5 6 1 3;\r\n 7 9 2 1];\r\ny_correct = 48;\r\nassert(isequal(sumCornice(MTX),y_correct))\r\n\r\n%% Test 2\r\nMTX = [ 7 1 7 4 5\r\n 4 3 3 7 6\r\n 6 1 9 8 7\r\n 2 1 1 2 7\r\n 7 8 4 5 3];\r\ny_correct = 83;\r\nassert(isequal(sumCornice(MTX),y_correct))\r\n\r\n%% Test 3\r\nMTX = [ 7 2\r\n 6 2];\r\ny_correct = 17;\r\nassert(isequal(sumCornice(MTX),y_correct))\r\n\r\n%% Test 4\r\nMTX = [ 5 7 3 5 7 2 5 1\r\n 9 9 8 4 4 6 2 3\r\n 4 9 3 8 6 5 6 9\r\n 6 5 9 6 1 1 3 2\r\n 3 2 4 5 1 4 6 8\r\n 7 2 2 9 5 2 7 5\r\n 3 3 3 3 8 8 7 9\r\n 5 8 6 7 9 3 5 1];\r\ny_correct = 147;\r\nassert(isequal(sumCornice(MTX),y_correct))\r\n\r\n%% Test 5\r\nMTX = [ 4 8 9 6 5 3\r\n 1 1 2 5 4 4\r\n 9 4 3 2 1 1\r\n 1 3 2 8 3 9\r\n 7 8 2 6 2 9\r\n 8 4 8 4 2 5];\r\ny_correct = 107;\r\nassert(isequal(sumCornice(MTX),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":522328,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":57,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-08-05T18:20:14.000Z","updated_at":"2026-02-18T21:40:33.000Z","published_at":"2020-08-05T18:20:14.000Z","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 a matrix of random integers, calculate the sum of all the integers in the cornice of the 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\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eFor example if MTX = [ \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e1 3 5 6;\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:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003e4\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e 7 9 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1\u003c/w:t\u003e\u003c/w:r\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\u003eoutput = 1 + 3 + 5 + 6 + 4 + 2 + 5 + 3 + 7 + 9 + 2 + 1 = 48\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":61087,"title":"How tall will my cactus be?","description":"\r\nMy Barbed Wire Cactus is a desert cactus that relies on just the right amount of rainfall to stay healthy. Given a 1×12 vector of monthly rainfall values (in mm), the cactus will die if any month has less than 10 mm of rain (too dry) or more than 150 mm (too wet). If it survives the year, the change in the average height of the cactus follows a realistic saturation model: \r\ng = Gmax * (1 - exp(-r ./ k))\r\nwhere Gmax⁡ = 5 cm is the maximum monthly growth and k = 40 mm controls how strongly rainfall influences growth. Find the final height if the initial height of my cactus is 140 mm. If my cactus dies, the height should be reported as 0.","description_html":"\u003cdiv style = \"text-align: start; line-height: 20.44px; min-height: 0px; white-space: normal; color: rgb(33, 33, 33); font-family: Menlo, Monaco, Consolas, monospace; font-style: normal; font-size: 14px; font-weight: 400; text-decoration: none; white-space: normal; \"\u003e\u003cdiv style=\"block-size: 863.667px; display: block; min-width: 0px; padding-block-start: 0px; padding-inline-start: 2px; padding-left: 2px; padding-top: 0px; perspective-origin: 408.5px 431.833px; transform-origin: 408.5px 431.833px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 711.667px; 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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384.5px 355.833px; 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\" data-image-state=\"image-loaded\"\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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384.5px 31.5px; text-align: left; transform-origin: 384.5px 31.5px; white-space-collapse: preserve; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eMy Barbed Wire Cactus\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: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\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: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eis a desert cactus that relies on just the right amount of rainfall to stay healthy. Given a 1×12 vector of monthly rainfall values (in mm), the cactus will die if any month has less than 10 mm of rain (too dry) or more than 150 mm (too wet). If it survives the year, the change in the average height of the cactus follows a realistic saturation model: \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 18px; 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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 404.5px 9px; transform-origin: 404.5px 9px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); 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: 0.666667px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.666667px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.666667px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.666667px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; line-height: 18.004px; 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; padding-inline-start: 4px; padding-left: 4px; text-wrap-mode: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(33, 33, 33); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(33, 33, 33); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(33, 33, 33); border-left-style: none; border-left-width: 0px; border-right-color: rgb(33, 33, 33); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 0px 0px; tab-size: 4; transform-origin: 0px 0px; unicode-bidi: normal; white-space-collapse: preserve; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eg = Gmax * (1 - exp(-r ./ k))\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; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 384.5px 21px; text-align: left; transform-origin: 384.5px 21px; white-space-collapse: preserve; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; \"\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; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ewhere Gmax⁡ = 5 cm is the maximum monthly growth and k = 40 mm controls how strongly rainfall influences growth. Find the final height if the initial height of my cactus is 140 mm. If my cactus dies, the height should be reported as 0.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function final_height = cactusGrowth(rain)\r\n \r\nend","test_suite":"%% Test 1: Healthy cactus with moderate rainfall\r\nrain = [20 30 40 50 60 70 80 90 60 40 30 20];\r\nassert(abs(cactusGrowth(rain) - 179.7959) \u003c 1e-4 )\r\n\r\n%% Test 2: Dies from drought\r\nrain = [12 20 30 40 50 60 70 80 90 100 70 5];\r\nassert(cactusGrowth(rain) == 0 )\r\n\r\n%% Test 3: Dies from overwatering\r\nrain = [20 30 40 50 60 70 80 90 100 110 120 200];\r\nassert(cactusGrowth(rain) == 0 )\r\n\r\n%% Test 4: Boundary case - exactly 10 mm (survives)\r\nrain = [10 15 20 25 30 35 40 45 50 55 60 65];\r\nassert(abs(cactusGrowth(rain) - 174.2549) \u003c 1e-4 )\r\n\r\n%% Test 5: Boundary case - exactly 150 mm (survives)\r\nrain = [150 100 80 60 40 20 20 40 60 80 100 150];\r\nassert(abs(cactusGrowth(rain) - 185.6152) \u003c 1e-4 )\r\n\r\n%% Test 6: Uniform rainfall\r\nrain = ones(1,12)*50;\r\nassert(abs(cactusGrowth(rain) - 182.8097) \u003c 1e-4 )\r\n\r\n%% Test 7: Random valid rainfall \r\nrain = [68 111 10 52 30 23 36 58 65 85 69 106];\r\nassert( abs(cactusGrowth(rain) - 182.3113) \u003c 1e-4 )\r\n\r\n%% Test 8: Random invalid rainfall\r\nrain = [15 20 30 40 50 60 70 80 90 100 70 9];\r\nassert(cactusGrowth(rain) == 0 )","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":5012276,"edited_by":5012276,"edited_at":"2025-11-29T12:13:14.000Z","deleted_by":null,"deleted_at":null,"solvers_count":13,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2025-11-29T11:59:27.000Z","updated_at":"2026-02-26T20:57:42.000Z","published_at":"2025-11-29T12:13:14.000Z","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:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"706\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"1024\\\"/\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:rPr/\u003e\u003cw:t\u003eMy Barbed Wire Cactus\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:t\u003eis a desert cactus that relies on just the right amount of rainfall to stay healthy. Given a 1×12 vector of monthly rainfall values (in mm), the cactus will die if any month has less than 10 mm of rain (too dry) or more than 150 mm (too wet). If it survives the year, the change in the average height of the cactus follows a realistic saturation model: \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[g = Gmax * (1 - exp(-r ./ k))]]\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\u003ewhere Gmax⁡ = 5 cm is the maximum monthly growth and k = 40 mm controls how strongly rainfall influences growth. Find the final height if the initial height of my cactus is 140 mm. If my cactus dies, the height should be reported as 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\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":45875,"title":"Replicate elements in vectors (★★★)","description":"(copy of Prob 867)\r\n\r\n\r\n\r\nReplicate each element of a row vector (with NaN) a constant number of times. Examples\r\n\r\n n=2, A=[1 2 3] -\u003e [1 1 2 2 3 3]\r\n\r\n n=0, A=[2 1] -\u003e []\r\n\r\n","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: 153.3px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 76.65px; transform-origin: 407px 76.65px; 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: 57.4583px 10.5px; transform-origin: 57.4583px 10.5px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e(copy of Prob 867)\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: 276.375px 10.5px; transform-origin: 276.375px 10.5px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eReplicate each element of a row vector (with NaN) a constant number of times. Examples\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: 134.933px 8.5px; transform-origin: 134.933px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e n=2, A=[1 2 3] -\u0026gt; [1 1 2 2 3 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: 0px 8.5px; 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: 88.55px 8.5px; transform-origin: 88.55px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e n=0, A=[2 1] -\u0026gt; []\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: 84.4167px 10.5px; transform-origin: 84.4167px 10.5px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAvoid using for/while loops.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = replicate_times(x,n)\r\n y = x*n;\r\nend","test_suite":"%%\r\nx = [1 2 3];\r\nn=1;\r\ny_correct = [1 2 3];\r\nassert(isequal(replicate_times(x,n),y_correct))\r\n%%\r\nx = [NaN 1 1];\r\nn=2;\r\ny_correct = [NaN NaN 1 1 1 1];\r\nassert(isequalwithequalnans(replicate_times(x,n),y_correct))\r\n%%\r\nx = [1 0 1 0];\r\nn=0;\r\nassert(isempty(replicate_times(x,n)))\r\n%%\r\nx = [-1 0 1 11];\r\nn=2;\r\ny_correct = [-1 -1 0 0 1 1 11 11];\r\nassert(isequal(replicate_times(x,n),y_correct))\r\n%%\r\nfiletext = fileread('replicate_times.m');\r\nassert(isempty(strfind(filetext, 'for')),'for forbidden')\r\nassert(isempty(strfind(filetext, 'while')),'while forbidden')\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":428668,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":62,"test_suite_updated_at":"2020-10-17T01:00:55.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-06-10T18:45:29.000Z","updated_at":"2026-03-31T14:54:59.000Z","published_at":"2020-06-10T18:45:29.000Z","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\u003e(copy of Prob 867)\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\u003eReplicate each element of a row vector (with NaN) a constant number of times. Examples\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=2, A=[1 2 3] -\u003e [1 1 2 2 3 3]\\n\\n n=0, A=[2 1] -\u003e []]]\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\u003eAvoid using for/while loops.\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":43688,"title":"Increment up an input vector","description":"Increment up an input vector by adding the indices to the vector values. For example, if an input vector is [3, 2, 6, 1, 6], the output vector is [3, 2, 6, 1, 6] + [1, 2, 3, 4, 5] = [4, 4, 9, 5, 11].","description_html":"\u003cp\u003eIncrement up an input vector by adding the indices to the vector values. For example, if an input vector is [3, 2, 6, 1, 6], the output vector is [3, 2, 6, 1, 6] + [1, 2, 3, 4, 5] = [4, 4, 9, 5, 11].\u003c/p\u003e","function_template":"function y = f(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = 1:10;\r\ny_correct = 2:2:20;\r\nassert(isequal(f(x),y_correct))\r\n%%\r\nx = [0.2400 0.4173 0.0497 0.9027 0.9448 0.4909 0.4893];\r\ny_correct = [1.2400 2.4173 3.0497 4.9027 5.9448 6.4909 7.4893];\r\nassert(isequal(f(x),y_correct))\r\n%%\r\nx = [4124 52351 pi i -242];\r\ny_correct = [4125 52353 pi+3 4+i -237];\r\nassert(isequal(f(x),y_correct))\r\n%%\r\nx = [7 4 1 5 8 6 9 2 3];\r\ny_correct = [8 6 4 9 13 12 16 10 12];\r\nassert(isequal(f(x),y_correct))\r\n%%\r\nx = -3:3;\r\ny_correct = -2:2:10;\r\nassert(isequal(f(x),y_correct))\r\n%%\r\nx = 10:-1:1;\r\ny_correct = 11*ones(1,10);\r\nassert(isequal(f(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":88423,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":84,"test_suite_updated_at":"2016-12-21T21:12:09.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-11-28T02:16:11.000Z","updated_at":"2026-02-17T14:46:42.000Z","published_at":"2016-11-28T02:16:11.000Z","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\u003eIncrement up an input vector by adding the indices to the vector values. For example, if an input vector is [3, 2, 6, 1, 6], the output vector is [3, 2, 6, 1, 6] + [1, 2, 3, 4, 5] = [4, 4, 9, 5, 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":46823,"title":"Create a vector of n alternating ones and minus ones (★★)","description":null,"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: 102px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 51px; transform-origin: 407px 51px; 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: 377.783px 10.5px; transform-origin: 377.783px 10.5px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven n, your output should be a vector y of numbers such that the first number is 1 and the numbers following it alternate between -1 and 1. Thus,\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: 128.075px 10.5px; transform-origin: 128.075px 10.5px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eif n = 10, then y = [1 -1 1 -1 1 -1 1 -1 1 -1]\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: 87.975px 10.5px; transform-origin: 87.975px 10.5px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eif n = 5, then y = [1 -1 1 -1 1]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = alternating1_1(n)\r\n y = n;\r\nend","test_suite":"%%\r\nn = 5;\r\ny_correct = [1 -1 1 -1 1];\r\nassert(isequal(alternating1_1(n),y_correct))\r\n%%\r\nn = 8;\r\ny_correct = [1 -1 1 -1 1 -1 1 -1];\r\nassert(isequal(alternating1_1(n),y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":428668,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":63,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-10-17T00:50:28.000Z","updated_at":"2026-03-31T15:10:26.000Z","published_at":"2020-10-17T00:50:28.000Z","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 n, your output should be a vector y of numbers such that the first number is 1 and the numbers following it alternate between -1 and 1. Thus,\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 n = 10, then y = [1 -1 1 -1 1 -1 1 -1 1 -1]\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 n = 5, then y = [1 -1 1 -1 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":58678,"title":"Find cross product of 2 vectors","description":"Find cross product of 2 vectors","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: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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-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: 0px 0px; transform-origin: 0px 0px; \"\u003e\u003cspan style=\"\"\u003eFind cross product of 2 vectors\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function ans = cross_prod(x,y)\r\n ans = x.*y;\r\nend","test_suite":"%%\r\nx = [1 2 3];\r\ny = [-1 2 3];\r\ny_correct = [0 -6 4];\r\nassert(isequal(cross_prod(x,y),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":3494818,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":38,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2023-07-18T15:36:20.000Z","updated_at":"2026-02-17T15:58:40.000Z","published_at":"2023-07-18T15:36:20.000Z","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 cross product of 2 vectors\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":2138,"title":"union without repitition","description":"Let \r\n\r\n a = [9 9 9 9 9 9 8 8 8 8 7 7 7 6 6 6 5 5 4 2 1]\r\n b = [1 1 1 3 3 3 3 3 4 4 4 4 4 10 10 10]\r\n\r\nOutput should be\r\n\r\n [9 8 7 6 5 4 2 1 3 10]\r\n\r\n","description_html":"\u003cp\u003eLet\u003c/p\u003e\u003cpre\u003e a = [9 9 9 9 9 9 8 8 8 8 7 7 7 6 6 6 5 5 4 2 1]\r\n b = [1 1 1 3 3 3 3 3 4 4 4 4 4 10 10 10]\u003c/pre\u003e\u003cp\u003eOutput should be\u003c/p\u003e\u003cpre\u003e [9 8 7 6 5 4 2 1 3 10]\u003c/pre\u003e","function_template":"function y = union_without_repitition(a,b)\r\n y = x;\r\nend","test_suite":"%%\r\na = [9 9 9 9 9 97 7 76 6 6 5 54 2 1];\r\n b = [1 1 13 3 3 44 4 10 110];\r\ny_correct = [9 97 7 76 6 5 54 2 1 13 3 44 4 10 110];\r\nassert(isequal(union_without_repitition(a,b),y_correct))\r\n\r\n%%\r\na = [96 6 65 54 2 1];\r\n b = [1 13 3 3 3 44 4 4 410 10 10];\r\n y_correct =[96 6 65 54 2 1 13 3 44 4 410 10];\r\nassert(isequal(union_without_repitition(a,b),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":1,"created_by":1690,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":110,"test_suite_updated_at":"2014-01-31T02:35:48.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2014-01-31T02:32:32.000Z","updated_at":"2026-02-18T11:01:35.000Z","published_at":"2014-01-31T02:32:32.000Z","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\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 = [9 9 9 9 9 9 8 8 8 8 7 7 7 6 6 6 5 5 4 2 1]\\n b = [1 1 1 3 3 3 3 3 4 4 4 4 4 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\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eOutput 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[ [9 8 7 6 5 4 2 1 3 10]]]\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":2689,"title":"vector to string","description":"Determine what the ASCII characters spell out. \r\n\r\nExample:\r\n\r\n input = [ 72 73 71 72] \r\n output = 'HIGH'","description_html":"\u003cp\u003eDetermine what the ASCII characters spell out.\u003c/p\u003e\u003cp\u003eExample:\u003c/p\u003e\u003cpre\u003e input = [ 72 73 71 72] \r\n output = 'HIGH'\u003c/pre\u003e","function_template":"function y = vector(x)\r\n y = x;\r\nend","test_suite":"%%\r\nvector = [70 73 86 69];\r\ny_correct = 'FIVE';\r\nassert(isequal(vector,y_correct))\r\n\r\n%%\r\nvector = [109 97 116 104 101 109 97 116 105 99 115];\r\ny_correct = 'mathematics';\r\nassert(isequal(vector,y_correct))","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":29473,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":138,"test_suite_updated_at":"2014-11-25T15:17:13.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2014-11-24T21:45:26.000Z","updated_at":"2026-02-18T11:13:43.000Z","published_at":"2014-11-24T21:52:18.000Z","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\u003eDetermine what the ASCII characters spell out.\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 = [ 72 73 71 72] \\n output = 'HIGH']]\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":44886,"title":"Given a Vector v1, create v2 which is the sum of each two adjacent elements in v1. {length(v2)=length(v1)-1}","description":"if v1 is [1 2 3 4 5 6 7 8] then v2 should be [3 5 7 9 11 13 15].\r\n\r\nif v1 is [1;\r\n 3;\r\n 5;\r\n 7] \r\nthen v2 should be [4;\r\n 8;\r\n 12].","description_html":"\u003cp\u003eif v1 is [1 2 3 4 5 6 7 8] then v2 should be [3 5 7 9 11 13 15].\u003c/p\u003e\u003cp\u003eif v1 is [1;\r\n 3;\r\n 5;\r\n 7] \r\nthen v2 should be [4;\r\n 8;\r\n 12].\u003c/p\u003e","function_template":"function v2 = sumEachPair(v1)\r\n v2 = v1;\r\nend","test_suite":"%%\r\nx = 1:10;\r\ny_correct = 3:2:19;\r\nassert(isequal(sumEachPair(x),y_correct))\r\n%%\r\nx = [1:100]';\r\ny_correct = [3:2:199]';\r\nassert(isequal(sumEachPair(x),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":278101,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":162,"test_suite_updated_at":"2019-04-21T12:59:23.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2019-04-21T12:50:42.000Z","updated_at":"2026-03-11T08:21:25.000Z","published_at":"2019-04-21T12:54:44.000Z","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\u003eif v1 is [1 2 3 4 5 6 7 8] then v2 should be [3 5 7 9 11 13 15].\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 v1 is [1; 3; 5; 7] then v2 should be [4; 8; 12].\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":45313,"title":"Find the shortest distance between a point and a straight line.","description":"Given the Cartesian coordinates of three points A, B and C (in a flat Euclidean space),\r\nfind the shortest distance between the straight line through A and B, and the point C.\r\n\r\nAssumption:\r\n\r\nA and B do not coincide.","description_html":"\u003cp\u003eGiven the Cartesian coordinates of three points A, B and C (in a flat Euclidean space),\r\nfind the shortest distance between the straight line through A and B, and the point C.\u003c/p\u003e\u003cp\u003eAssumption:\u003c/p\u003e\u003cp\u003eA and B do not coincide.\u003c/p\u003e","function_template":"function y = shortest_distance(x1,x2,x3)\r\n y = 0;\r\nend","test_suite":"%%\r\nx1 = [0 0 0];\r\nx2 = [1 1 1];\r\nx3 = [2 2 2];\r\n\r\ny_correct = 0; \r\neps = 4.999 * 10^(-7);\r\nassert(abs(shortest_distance(x1,x2,x3)-y_correct)\u003ceps)\r\n\r\n%%\r\nx1 = [0 0 0];\r\nx2 = [0 0 1];\r\nx3 = [1 0 0];\r\n\r\ny_correct = 1;\r\neps = 4.999 * 10^(-7);\r\nassert(abs(shortest_distance(x1,x2,x3)-y_correct)\u003ceps)\r\n\r\n%%\r\nx1 = [1 0 0];\r\nx2 = [0 1 0];\r\nx3 = [0 0 0];\r\n\r\ny_correct = sqrt(1/2);\r\neps = 4.999 * 10^(-7);\r\nassert(abs(shortest_distance(x1,x2,x3)-y_correct)\u003ceps)\r\n\r\n%%\r\ntheta = 0.5;\r\npsi = -0.2;\r\nphi = 1.1;\r\nR3=[cos(psi) sin(psi) 0.0; -sin(psi) cos(psi) 0.0; 0.0 0.0 1.0];\r\nR2=[cos(theta) 0.0 -sin(theta); 0.0 1.0 0.0; sin(theta) 0.0 cos(theta)];\r\nR1=[1.0 0.0 0.0; 0.0 cos(phi) sin(phi); 0.0 -sin(phi) cos(phi)];\r\n\r\nR = R3*R2*R1;\r\nx1 = [1 0 0]*R;\r\nx2 = [0 1 0]*R;\r\nx3 = [0 0 0]*R;\r\n\r\ny_correct = sqrt(1/2);\r\neps = 4.999 * 10^(-7);\r\nassert(abs(shortest_distance(x1,x2,x3)-y_correct)\u003ceps)\r\n\r\n%%\r\nx1 = [0 0 0];\r\nx2 = [0 0 1];\r\nx3 = x2;\r\n\r\ny_correct = 0;\r\neps = 4.999 * 10^(-7);\r\nassert(abs(shortest_distance(x1,x2,x3)-y_correct)\u003ceps)","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":393995,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":17,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-02-04T14:23:13.000Z","updated_at":"2026-03-19T07:20:29.000Z","published_at":"2020-02-18T12:21:57.000Z","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 the Cartesian coordinates of three points A, B and C (in a flat Euclidean space), find the shortest distance between the straight line through A and B, and the point C.\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\u003eAssumption:\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 and B do not coincide.\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":1988,"title":"Remove the middle element from a vector","description":"Remove the middle element of a vector?\r\n\r\n*Example:*\r\n\r\n[1,2,3] should return 2\r\n\r\n[1,2,3,4] should return 2\r\n\r\n[] should return empty vector","description_html":"\u003cp\u003eRemove the middle element of a vector?\u003c/p\u003e\u003cp\u003e\u003cb\u003eExample:\u003c/b\u003e\u003c/p\u003e\u003cp\u003e[1,2,3] should return 2\u003c/p\u003e\u003cp\u003e[1,2,3,4] should return 2\u003c/p\u003e\u003cp\u003e[] should return empty vector\u003c/p\u003e","function_template":"function y = remove_middle(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = [1,2,3];\r\ny_correct = 2;\r\nassert(isequal(remove_middle(x),y_correct))\r\n%%\r\nx = [1,2,3,4];\r\ny_correct = 2;\r\nassert(isequal(remove_middle(x),y_correct))\r\n%%\r\nx = [];\r\ny_correct = [];\r\nassert(isequal(remove_middle(x),y_correct))","published":true,"deleted":false,"likes_count":0,"comments_count":2,"created_by":19016,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":93,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2013-11-14T00:47:38.000Z","updated_at":"2026-02-18T14:46:19.000Z","published_at":"2013-11-14T00:47:38.000Z","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\u003eRemove the middle element of 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\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=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e[1,2,3] should return 2\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[1,2,3,4] should return 2\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[] should return empty vector\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":60704,"title":"Convert RGB to Grayscale","description":"Convert a 3 element RGB array to its correspoding grayscale pixel (a scalar)\r\n*Hint: a formula exists!","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: 51px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 25.5px; transform-origin: 407px 25.5px; 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-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: 236.5px 8px; transform-origin: 236.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eConvert a 3 element RGB array to its correspoding grayscale pixel (a scalar)\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-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: 70.0083px 8px; transform-origin: 70.0083px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e*Hint: a formula exists!\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function g = RGB_to_gray(x)\r\n g = 0;\r\nend","test_suite":"%%\r\nx = [0,0,0];\r\ng = 0;\r\nassert(abs(RGB_to_gray(x)-g) \u003c 1e-1)\r\n%assert(isequal(RGB_to_gray(x),g))\r\n%%\r\nx = [255,255,255];\r\ng = 255;\r\nassert(abs(RGB_to_gray(x)-g) \u003c 1e-1)\r\n%%\r\nx = [200,220,240];\r\ng = 216.3;\r\nassert(abs(RGB_to_gray(x)-g) \u003c 1e-1)\r\n%%\r\nx = [0,255,0];\r\ng = 149.7;\r\nassert(abs(RGB_to_gray(x)-g) \u003c 1e-1)\r\n%%\r\nx = [0,0,255];\r\ng = 29.1;\r\nassert(abs(RGB_to_gray(x)-g) \u003c 1e-1)\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":1,"created_by":4585291,"edited_by":4585291,"edited_at":"2024-08-07T19:08:12.000Z","deleted_by":null,"deleted_at":null,"solvers_count":26,"test_suite_updated_at":"2024-08-07T19:08:12.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2024-08-07T16:17:39.000Z","updated_at":"2026-02-18T14:54:19.000Z","published_at":"2024-08-07T16:17:39.000Z","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\u003eConvert a 3 element RGB array to its correspoding grayscale pixel (a scalar)\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*Hint: a formula exists!\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":44842,"title":"Double the next!","description":"Given two numbers, m and n, find a matrix [m,n] where each element value is twice the value of the previous element. Starting from the position (1,1) with value equal to 1, until the position (m,n), following the direction from left to right and from top to bottom.\r\nFor example, for m=2 and n=3, you should get:\r\ny = [1 2 4; 8 16 32].","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: 123.438px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 332px 61.7188px; transform-origin: 332px 61.7188px; 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: 309px 31.5px; text-align: left; transform-origin: 309px 31.5px; 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: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eGiven two numbers, m and n, find a matrix \u003c/span\u003e\u003cspan style=\"border-block-end-style: solid; border-block-end-width: 1px; border-bottom-style: solid; border-bottom-width: 1px; \"\u003e[\u003c/span\u003e\u003cspan style=\"\"\u003em,n\u003c/span\u003e\u003cspan style=\"border-block-end-style: solid; border-block-end-width: 1px; border-bottom-style: solid; border-bottom-width: 1px; \"\u003e]\u003c/span\u003e\u003cspan style=\"\"\u003e where each element value is twice the value of the previous element. Starting from the position (1,1) with value equal to 1, until the position (m,n), following the direction from left to right and from top to bottom.\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: 309px 10.5px; text-align: left; transform-origin: 309px 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: 0px 0px; transform-origin: 0px 0px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eFor example, for m=2 and n=3, you should get:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 20.4375px; 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: 329px 10.2188px; transform-origin: 329px 10.2188px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); 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; text-wrap: 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; unicode-bidi: normal; white-space-collapse: preserve; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003ey = [1 2 4; 8 16 32].\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(m,n)\r\n y = [];\r\nend","test_suite":"%%\r\nm = 3;\r\nn = 2; \r\ny_correct = [1 2; 4 8; 16 32];\r\nassert(isequal(your_fcn_name(m,n),y_correct))\r\n\r\n%%\r\nm = 1;\r\nn = 1; \r\ny_correct = [1];\r\nassert(isequal(your_fcn_name(m,n),y_correct))\r\n\r\n%%\r\nm = 1;\r\nn = 5; \r\ny_correct = [1 2 4 8 16];\r\nassert(isequal(your_fcn_name(m,n),y_correct))\r\n\r\n%%\r\nm = 3;\r\nn = 1; \r\ny_correct = [1; 2; 4];\r\nassert(isequal(your_fcn_name(m,n),y_correct))\r\n\r\n%%\r\nm = 4;\r\nn = 2; \r\ny_correct = [1 2; 4 8; 16 32; 64 128];\r\nassert(isequal(your_fcn_name(m,n),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":274816,"edited_by":274816,"edited_at":"2024-07-03T13:09:32.000Z","deleted_by":null,"deleted_at":null,"solvers_count":54,"test_suite_updated_at":"2019-03-23T22:36:07.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2019-01-29T11:50:39.000Z","updated_at":"2026-03-04T14:52:41.000Z","published_at":"2019-01-29T11:50:39.000Z","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\u003eGiven two numbers, m and n, find a matrix [m,n] where each element value is twice the value of the previous element. Starting from the position (1,1) with value equal to 1, until the position (m,n), following the direction from left to right and from top to bottom.\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, for m=2 and n=3, you should get:\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[y = [1 2 4; 8 16 32].]]\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":52005,"title":"Vector creation using colon operator","description":"Create a vector y containing n uniformly spaced values between a and b, with a \u003c b. Use the colon (:) operator.","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: 21px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 10.5px; transform-origin: 407px 10.5px; vertical-align: baseline; \"\u003e\u003cdiv style=\"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: 91px 8px; transform-origin: 91px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eCreate a vector y containing \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: 4.5px 8px; transform-origin: 4.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003en\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: 108.5px 8px; transform-origin: 108.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e uniformly spaced values between \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: 4px 8px; transform-origin: 4px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\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: 16px 8px; transform-origin: 16px 8px; 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: 4.5px 8px; transform-origin: 4.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eb\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: 120.5px 8px; transform-origin: 120.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, with a \u0026lt; b. Use the colon (:) operator.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = your_fcn_name(a,b,n) %% Do not change this line\r\n y = 1;\r\nend %% Do not change this line","test_suite":"%%\r\na = 2; b = 12; n = 6;\r\ny_correct = [2 4 6 8 10 12];\r\nassert(isequal(your_fcn_name(a,b,n),y_correct))\r\n%%\r\na = 10; b = 100; n = 11;\r\ny_correct = [ 10 19 28 37 46 55 64 73 82 91 100];\r\nassert(isequal(your_fcn_name(a,b,n),y_correct))\r\n%%\r\nfiletext = fileread('your_fcn_name.m');\r\nassert(isempty(strfind(filetext, 'linspace')),'linspace forbidden')\r\n%%\r\nfiletext = fileread('your_fcn_name.m');\r\nassert(isempty(strfind(filetext, ':'))==0,'use colon (:) operator')","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":428668,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":41,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2021-06-06T02:04:54.000Z","updated_at":"2026-03-05T16:12:30.000Z","published_at":"2021-06-06T02:04:54.000Z","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\u003eCreate a vector y containing \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e uniformly spaced values between \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003ea\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:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eb\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, with a \u0026lt; b. Use the colon (:) operator.\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":44156,"title":"Weighted average","description":"Compute the weighted average Y, of the vector A, given the weight vector W.\r\n\r\nThe weighted average is the sum of the dot product of A and W, normalized by the sum of W.\r\n\r\nExample 1:\r\n\r\n A = [10 15 20 10];\r\n W = [ 1 1 1 1];\r\n Y = 13.75\r\n\r\nExample 2:\r\n\r\n A = [ 10 15 20 10];\r\n W = [0.25 0.25 0.25 0.25];\r\n Y = 13.75\r\n\r\nExample 3:\r\n\r\n A = [10 15 20 10];\r\n W = [ 2 4 4 2];\r\n Y = 15","description_html":"\u003cp\u003eCompute the weighted average Y, of the vector A, given the weight vector W.\u003c/p\u003e\u003cp\u003eThe weighted average is the sum of the dot product of A and W, normalized by the sum of W.\u003c/p\u003e\u003cp\u003eExample 1:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eA = [10 15 20 10];\r\nW = [ 1 1 1 1];\r\nY = 13.75\r\n\u003c/pre\u003e\u003cp\u003eExample 2:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eA = [ 10 15 20 10];\r\nW = [0.25 0.25 0.25 0.25];\r\nY = 13.75\r\n\u003c/pre\u003e\u003cp\u003eExample 3:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eA = [10 15 20 10];\r\nW = [ 2 4 4 2];\r\nY = 15\r\n\u003c/pre\u003e","function_template":"function Y = weighted_average(A,W)\r\n Y = A;\r\nend","test_suite":"%%\r\nA = [10 15 20 10];\r\nW = [ 1 1 1 1];\r\nY = 13.75\r\nassert(isequal(weighted_average(A,W),Y))\r\n\r\n%%\r\nA = [ 10 15 20 10];\r\nW = [0.25 0.25 0.25 0.25];\r\nY = 13.75\r\nassert(isequal(weighted_average(A,W),Y))\r\n\r\n%%\r\nA = [10 15 20 10];\r\nW = [ 2 4 4 2];\r\nY = 15\r\nassert(isequal(weighted_average(A,W),Y))\r\n\r\n%%\r\nassert(~any(strfind(lower(fileread('weighted_average.m')),'regexp')))\r\n\r\n%%\r\nassert(~any(strfind(lower(fileread('weighted_average.m')),'feval')))\r\n\r\n%%\r\nassert(~any(strfind(lower(fileread('weighted_average.m')),'eval')))","published":true,"deleted":false,"likes_count":2,"comments_count":0,"created_by":130819,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":118,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-05-04T14:38:26.000Z","updated_at":"2026-04-03T03:15:25.000Z","published_at":"2017-05-04T14:38:26.000Z","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\u003eCompute the weighted average Y, of the vector A, given the weight vector W.\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 weighted average is the sum of the dot product of A and W, normalized by the sum of W.\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 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[A = [10 15 20 10];\\nW = [ 1 1 1 1];\\nY = 13.75]]\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\u003eExample 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[A = [ 10 15 20 10];\\nW = [0.25 0.25 0.25 0.25];\\nY = 13.75]]\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\u003eExample 3:\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 = [10 15 20 10];\\nW = [ 2 4 4 2];\\nY = 15]]\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":43047,"title":"Wrap-around effect","description":"In vector x of length n we define (n+1) position as going back to the first position (so called wrap-around effect). Can you return the value of x at a given position, taking into account the above rule?\r\n\r\nExample: x = [1 2 3] -\u003e x(1) yields 1, x(5) should yield 2; and so on.","description_html":"\u003cp\u003eIn vector x of length n we define (n+1) position as going back to the first position (so called wrap-around effect). Can you return the value of x at a given position, taking into account the above rule?\u003c/p\u003e\u003cp\u003eExample: x = [1 2 3] -\u0026gt; x(1) yields 1, x(5) should yield 2; and so on.\u003c/p\u003e","function_template":"function y = wrapAround(x,pos)\r\n y = x;\r\nend","test_suite":"%%\r\nx = 1;\r\npos = 1;\r\ny_correct = 1;\r\nassert(isequal(wrapAround(x,pos),y_correct))\r\n\r\n%%\r\nx = [1 2 3 4 5];\r\npos = 99;\r\ny_correct = 4;\r\nassert(isequal(wrapAround(x,pos),y_correct))\r\n\r\n%%\r\nx = 7:101;\r\npos = 909;\r\ny_correct = 60;\r\nassert(isequal(wrapAround(x,pos),y_correct))\r\n\r\n%%\r\nx = 5:5:100;\r\npos = 101;\r\ny_correct = 5;\r\nassert(isequal(wrapAround(x,pos),y_correct))\r\n\r\n%%\r\nx = -17:3:99;\r\npos = 1001;\r\ny_correct = 58;\r\nassert(isequal(wrapAround(x,pos),y_correct))\r\n\r\n%%\r\nx = 1:3:777;\r\npos = 789;\r\ny_correct = 34;\r\nassert(isequal(wrapAround(x,pos),y_correct))\r\n","published":true,"deleted":false,"likes_count":3,"comments_count":1,"created_by":29461,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":53,"test_suite_updated_at":"2016-10-17T18:00:48.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-05T11:23:52.000Z","updated_at":"2026-03-24T13:32:26.000Z","published_at":"2016-10-05T11:23:52.000Z","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\u003eIn vector x of length n we define (n+1) position as going back to the first position (so called wrap-around effect). Can you return the value of x at a given position, taking into account the above rule?\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: x = [1 2 3] -\u0026gt; x(1) yields 1, x(5) should yield 2; and so on.\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":760,"title":"Duplicate each element of a vector.","description":"for an n-dimensional vector x, the function should return another vector 2n-dimension which each element is repeated twice.\r\nExample :\r\nin-\u003e[2 3 NaN 5] and out-\u003e[2 2 3 3 NaN NaN 5 5]","description_html":"\u003cp\u003efor an n-dimensional vector x, the function should return another vector 2n-dimension which each element is repeated twice.\r\nExample :\r\nin-\u003e[2 3 NaN 5] and out-\u003e[2 2 3 3 NaN NaN 5 5]\u003c/p\u003e","function_template":"function y = duplicate(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = [2,3,5];\r\ny_correct = [2,2,3,3,5,5];\r\nassert(isequal(duplicate(x),y_correct))","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":1309,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":636,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-06-13T03:45:03.000Z","updated_at":"2026-03-11T12:03:40.000Z","published_at":"2012-06-13T03:58:24.000Z","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\u003efor an n-dimensional vector x, the function should return another vector 2n-dimension which each element is repeated twice. Example : in-\u003e[2 3 NaN 5] and out-\u003e[2 2 3 3 NaN NaN 5 5]\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":44737,"title":"Get the combinations","description":"Consider\r\np,q = 2 vectors of same or different length.\r\nGet a Output Array which has all the possible combinations of Elements of vectors p and q\r\nfor example: \r\n\r\n p = [1 2 3], q = [10 12]\r\nthen \r\n\r\n Output = [1 10;2 10;3 10;1 12;2 12;3 12]\r\n","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: 133.733px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 66.8667px; transform-origin: 407px 66.8667px; 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: 362px 8px; transform-origin: 362px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eConsider p,q = 2 vectors of same or different length. Get a Output Array which has all the possible combinations of Elements of vectors p and q for example:\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: 96px 8.5px; transform-origin: 96px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003ep = [1 2 3], q = [10 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: 20px 8.5px; transform-origin: 20px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003ethen \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; 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: 160px 8.5px; transform-origin: 160px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eOutput = [1 10;2 10;3 10;1 12;2 12;3 12]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = combineit(p,q)\r\n y = {p.*q};\r\nend","test_suite":"%%\r\np=[10:15]\r\nq=[2:5]\r\ny_correct = [10 2;\r\n 11 2;\r\n 12 2;\r\n 13 2;\r\n 14 2;\r\n 15 2;\r\n 10 3;\r\n 11 3;\r\n 12 3;\r\n 13 3;\r\n 14 3;\r\n 15 3;\r\n 10 4;\r\n 11 4;\r\n 12 4;\r\n 13 4;\r\n 14 4;\r\n 15 4;\r\n 10 5;\r\n 11 5;\r\n 12 5;\r\n 13 5;\r\n 14 5;\r\n 15 5]\r\nassert(isequal(combineit(p,q),y_correct))\r\n\r\n%%\r\np=[-2:2];\r\nq=[-1 0 1];\r\ny_correct = [-2 -1 0 1 2 -2 -1 0 1 2 -2 -1 0 1 2\r\n -1 -1 -1 -1 -1 0 0 0 0 0 1 1 1 1 1]'; \r\nassert(isequal(combineit(p,q),y_correct))\r\n\r\n%%\r\np=[1 1 2 3 5 8 13];\r\nq=[1.618];\r\ny_correct = [1 1.618; 1 1.618; 2 1.618; 3 1.618; 5 1.618; 8 1.618; 13 1.618]; \r\nassert(isequal(combineit(p,q),y_correct))\r\n\r\n%%\r\np=[0 0.5 1];\r\nq=[exp(1) pi];\r\ny_correct = [0 exp(1); 0.5 exp(1); 1 exp(1); 0 pi; 0.5 pi; 1 pi]\r\nassert(isequal(combineit(p,q),y_correct))\r\n\r\n%%\r\np=[];\r\nq=[];\r\nassert(isempty(combineit(p,q)))","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":136465,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":43,"test_suite_updated_at":"2021-05-09T10:37:16.000Z","rescore_all_solutions":true,"group_id":1,"created_at":"2018-09-11T12:58:36.000Z","updated_at":"2026-04-03T07:15:22.000Z","published_at":"2018-09-11T12:58:36.000Z","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\u003eConsider p,q = 2 vectors of same or different length. Get a Output Array which has all the possible combinations of Elements of vectors p and q for 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[p = [1 2 3], q = [10 12]\\nthen \\n\\nOutput = [1 10;2 10;3 10;1 12;2 12;3 12]]]\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":341,"title":"count to vector","description":"Return a matrix of numbers of dimension K by N, where K = prod(v), and N=length(v). The rows count from a vector of ones up to v, where the nth element of a row can take on the values 1:v(n).\r\n","description_html":"\u003cp\u003eReturn a matrix of numbers of dimension K by N, where K = prod(v), and N=length(v). The rows count from a vector of ones up to v, where the nth element of a row can take on the values 1:v(n).\u003c/p\u003e","function_template":"function y = count_to_v(v)\r\n y = x;\r\nend","test_suite":"%%\r\nv = [1 2];\r\ny_correct = [1 1; 1 2];\r\nassert(isequal(count_to_v(v),y_correct))\r\n%%\r\nv = [3 2];\r\ny_correct = [1 1; 1 2; 2 1; 2 2; 3 1; 3 2];\r\nassert(isequal(count_to_v(v),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":2,"created_by":153,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":92,"test_suite_updated_at":"2012-02-19T04:04:35.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2012-02-19T04:02:49.000Z","updated_at":"2026-03-11T12:09:55.000Z","published_at":"2012-02-19T04:10:20.000Z","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\u003eReturn a matrix of numbers of dimension K by N, where K = prod(v), and N=length(v). The rows count from a vector of ones up to v, where the nth element of a row can take on the values 1:v(n).\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":1737,"title":"The sum of individual numbers...","description":"Well this one is taking a number and then summing the individual parts till you reach a value of 1, 2, 3, 4, 5, 6, 7, 8, 9, or 0 (only if the original is 0 the answer will be 0). For example:\r\n \r\n x = [103]; So ---\u003e 1+0+3 = 4\r\n output = 4;\r\n\r\nanother example:\r\n\r\n x = [99]; So ---\u003e 9+9 = 18 ---\u003e 1+8 = 9\r\n output = 9;\r\n\r\nanother example:\r\n \r\n x = [1199]; So ---\u003e 1+1+9+9 = 20 ---\u003e 2+0 = 2\r\n output = 2;\r\n\r\n\r\nanother example:\r\n\r\n x = [11 3]; So ---\u003e 1+1 = 2 and 3 = 3\r\n output = [2 3];\r\n","description_html":"\u003cp\u003eWell this one is taking a number and then summing the individual parts till you reach a value of 1, 2, 3, 4, 5, 6, 7, 8, 9, or 0 (only if the original is 0 the answer will be 0). For example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ex = [103]; So ---\u003e 1+0+3 = 4\r\noutput = 4;\r\n\u003c/pre\u003e\u003cp\u003eanother example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ex = [99]; So ---\u003e 9+9 = 18 ---\u003e 1+8 = 9\r\noutput = 9;\r\n\u003c/pre\u003e\u003cp\u003eanother example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ex = [1199]; So ---\u003e 1+1+9+9 = 20 ---\u003e 2+0 = 2\r\noutput = 2;\r\n\u003c/pre\u003e\u003cp\u003eanother example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003ex = [11 3]; So ---\u003e 1+1 = 2 and 3 = 3\r\noutput = [2 3];\r\n\u003c/pre\u003e","function_template":"function y = individualNumSum(x)\r\ny = x;\r\nend","test_suite":"%%\r\nx = [1];\r\ny = [1];\r\nassert(isequal(individualNumSum(x),y))\r\n%%\r\nx = [103];\r\ny = [4];\r\nassert(isequal(individualNumSum(x),y))\r\n%%\r\nx=[189 22 39 88 55 485 769 215 3685 4589];\r\ny = [9 4 3 7 1 8 4 8 4 8];\r\nassert(isequal(individualNumSum(x),y))\r\n%%\r\nx=[1111 2222 3333 4444 5555 6666 7777 8888 9999 0];\r\ny = [4 8 3 7 2 6 1 5 9 0];\r\nassert(isequal(individualNumSum(x),y))\r\n%%\r\nx=[111 222 333 444 555 666 777 888 999 0];\r\ny = [3 6 9 3 6 9 3 6 9 0];\r\nassert(isequal(individualNumSum(x),y))\r\n%%\r\nx=[11 3];\r\ny = [2 3];\r\nassert(isequal(individualNumSum(x),y))","published":true,"deleted":false,"likes_count":3,"comments_count":0,"created_by":15013,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":85,"test_suite_updated_at":"2013-07-22T18:34:35.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2013-07-22T18:22:26.000Z","updated_at":"2026-04-02T15:51:44.000Z","published_at":"2013-07-22T18:34:35.000Z","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\u003eWell this one is taking a number and then summing the individual parts till you reach a value of 1, 2, 3, 4, 5, 6, 7, 8, 9, or 0 (only if the original is 0 the answer will be 0). For 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[x = [103]; So ---\u003e 1+0+3 = 4\\noutput = 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\u003eanother 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[x = [99]; So ---\u003e 9+9 = 18 ---\u003e 1+8 = 9\\noutput = 9;]]\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\u003eanother 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[x = [1199]; So ---\u003e 1+1+9+9 = 20 ---\u003e 2+0 = 2\\noutput = 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\u003eanother 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[x = [11 3]; So ---\u003e 1+1 = 2 and 3 = 3\\noutput = [2 3];]]\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":2530,"title":"Powers Of","description":"Fill the vector with powers of 2, so that vector(1) is 2^1, vector(2) is 2^2, etc. Stop with vector(10). Complete the function using a *for* loop.","description_html":"\u003cp\u003eFill the vector with powers of 2, so that vector(1) is 2^1, vector(2) is 2^2, etc. Stop with vector(10). Complete the function using a \u003cb\u003efor\u003c/b\u003e loop.\u003c/p\u003e","function_template":"function vector = PowersOf(vector)\r\n for ?\r\n ?\r\n end\r\nend","test_suite":"%%\r\nvector1 = [0 0 0 0 0 0 0 0 0 0];\r\nvector1_correct = [2 4 8 16 32 64 128 256 512 1024];\r\ncode = textread('PowersOf.m', '%s');\r\nassert(isequal(PowersOf(vector1), vector1_correct) \u0026\u0026 ...\r\n strcmp(code(5), 'for') \u0026\u0026 ...\r\n strcmp(code(end-7), 'end') \u0026\u0026 ...\r\n strcmp(code(end-6), 'end'));","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":24594,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":108,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2014-08-26T12:47:32.000Z","updated_at":"2026-03-22T17:55:53.000Z","published_at":"2014-08-26T13:56:12.000Z","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\u003eFill the vector with powers of 2, so that vector(1) is 2^1, vector(2) is 2^2, etc. Stop with vector(10). Complete the function using 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:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003efor\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e loop.\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":763,"title":"Find the elements of a matrix according to a defined property.","description":"From A = [5,2,3] and B = [1,2,3,4,5,6,7,8,9,10] produce a vector C where :\r\n\r\nC(1) is the sum of the first A(1) elements of B,\r\n\r\nC(2) is the sum of the next A(2) elements of B, etc.\r\n\r\nc(i) = 0 if A(i) = 0.\r\n\r\nout-\u003e [15 13 27];","description_html":"\u003cp\u003eFrom A = [5,2,3] and B = [1,2,3,4,5,6,7,8,9,10] produce a vector C where :\u003c/p\u003e\u003cp\u003eC(1) is the sum of the first A(1) elements of B,\u003c/p\u003e\u003cp\u003eC(2) is the sum of the next A(2) elements of B, etc.\u003c/p\u003e\u003cp\u003ec(i) = 0 if A(i) = 0.\u003c/p\u003e\u003cp\u003eout-\u003e [15 13 27];\u003c/p\u003e","function_template":"function C = your_fcn_name(A,B)\r\n C = A;\r\nend","test_suite":"%%\r\nA = [4,1,2,3];B = [1,2,3,4,5,6,7,8,9,10];\r\ny_correct = [10 5 13 27];\r\nassert(isequal(your_fcn_name(A,B),y_correct))\r\n\r\n%%\r\nA = [5,2,0,3];B = [1,2,3,4,5,6,7,8,9,10];\r\ny_correct = [15 13 0 27];\r\nassert(isequal(your_fcn_name(A,B),y_correct))","published":true,"deleted":false,"likes_count":3,"comments_count":0,"created_by":1309,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":91,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2012-06-13T05:06:25.000Z","updated_at":"2025-12-07T18:47:04.000Z","published_at":"2012-06-13T05:08:34.000Z","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\u003eFrom A = [5,2,3] and B = [1,2,3,4,5,6,7,8,9,10] produce a vector C where :\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\u003eC(1) is the sum of the first A(1) elements of 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\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eC(2) is the sum of the next A(2) elements of B, etc.\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\u003ec(i) = 0 if A(i) = 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\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eout-\u003e [15 13 27];\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":44439,"title":"Remove the air bubbles from a vector","description":"_*A reduced version of Problem 112*_\r\n\r\nGiven a column vector v, return a vector w in which all the zeros have \"bubbled\" to the top. The order of the remaining nonzero numbers in the vector should be preserved.\r\n\r\nExample:\r\n\r\n Input v = [1\r\n 3\r\n 0\r\n 5\r\n 0\r\n -1]\r\n\r\n Output w = [0\r\n 0\r\n 1\r\n 3\r\n 5\r\n -1]","description_html":"\u003cp\u003e\u003ci\u003e\u003cb\u003eA reduced version of Problem 112\u003c/b\u003e\u003c/i\u003e\u003c/p\u003e\u003cp\u003eGiven a column vector v, return a vector w in which all the zeros have \"bubbled\" to the top. The order of the remaining nonzero numbers in the vector should be preserved.\u003c/p\u003e\u003cp\u003eExample:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eInput v = [1\r\n 3\r\n 0\r\n 5\r\n 0\r\n -1]\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003eOutput w = [0\r\n 0\r\n 1\r\n 3\r\n 5\r\n -1]\r\n\u003c/pre\u003e","function_template":"function w = bubbles(v)\r\n w = v;\r\nend","test_suite":"%%\r\nfiletext = fileread('bubbles.m');\r\nassert(isempty(strfind(filetext, 'regexp')),'regexp hacks are forbidden')\r\n\r\n%%\r\nv = [1 3 0 5 0 -1]';\r\nw_correct = [0 0 1 3 5 -1]';\r\nassert(isequal(bubbles(v),w_correct))\r\n\r\n%%\r\nv = [0 0 9 2 6]';\r\nw_correct = v;\r\nassert(isequal(bubbles(v),w_correct))\r\n\r\n%%\r\nv = [1 3 5 -1]';\r\nw_correct = v;\r\nassert(isequal(bubbles(v),w_correct))\r\n\r\n%%\r\nv = [0 1 0 1 1 1 0]';\r\nw_correct = [0 0 0 1 1 1 1]';\r\nassert(isequal(bubbles(v),w_correct))\r\n","published":true,"deleted":false,"likes_count":4,"comments_count":1,"created_by":140356,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":193,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2017-12-03T21:41:30.000Z","updated_at":"2026-03-30T19:08:33.000Z","published_at":"2017-12-03T21:41:30.000Z","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: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:b/\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eA reduced version of Problem 112\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 column vector v, return a vector w in which all the zeros have \\\"bubbled\\\" to the top. The order of the remaining nonzero numbers in the vector should be preserved.\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 v = [1\\n 3\\n 0\\n 5\\n 0\\n -1]\\n\\nOutput w = [0\\n 0\\n 1\\n 3\\n 5\\n -1]]]\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":42581,"title":"Create sequnce 1 4 9 16 25.........","description":"Create sequnce 1 4 9 16 25......... upto entered input value using matlab scripting commands. Let y be output and x be input","description_html":"\u003cp\u003eCreate sequnce 1 4 9 16 25......... upto entered input value using matlab scripting commands. Let y be output and x be input\u003c/p\u003e","function_template":"function y = prntseq(x)\r\n% Enter code\r\nend","test_suite":"%%\r\nx = 25;\r\ny_correct = [1 4 9 16 25];\r\nassert(isequal(prntseq(x),y_correct))\r\n%%\r\nx = 100;\r\ny_correct = [1 4 9 16 25 36 49 64 81 100];\r\nassert(isequal(prntseq(x),y_correct))\r\n%%\r\nx = 9;\r\ny_correct = [1 4 9];\r\nassert(isequal(prntseq(x),y_correct))\r\n%%\r\nx = 36;\r\ny_correct = [1 4 9 16 25 36];\r\nassert(isequal(prntseq(x),y_correct))","published":true,"deleted":false,"likes_count":4,"comments_count":0,"created_by":46868,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":414,"test_suite_updated_at":"2015-08-28T11:26:07.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2015-08-28T11:17:32.000Z","updated_at":"2026-02-08T06:17:39.000Z","published_at":"2015-08-28T11:26:07.000Z","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\u003eCreate sequnce 1 4 9 16 25......... upto entered input value using matlab scripting commands. Let y be output and x be input\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":43109,"title":"How many complete pizzas (number 2)","description":"x is a vector with numbers of pizza slices. A corresponding vector n indicates in how many slices the pizza slices of x were cut and t is a vector indicating the type of pizza (e.g. 1 is a margarita, 2 is a peperoni, etc.). How many complete pizzas do we have, when we cannot join 2 different pizzas?\r\n\r\nExample:\r\n\r\n x = [1 3 12];\r\n n = [2 6 8];\r\n t = [1 2 1];\r\n\r\nin the first column we have on slice (x=1) from a pizza margarita (t=1) cut in half (n=2) -\u003e half a pizza margarita. in the second column we have 3 slices (x=3) from a peperoni pizza (t=2) cut in 6 slices (n=6) -\u003e so half a peperoni pizza. in the third column we have 12 slices of a margarita pizzas (t=1) cut in 8 slices -\u003e1.5 slices margarita pizza.\r\n\r\nso we can combine this to 2 pizza margaritas and 0.5 peperoni pizza. So in total we can combine 2 pizzas.","description_html":"\u003cp\u003ex is a vector with numbers of pizza slices. A corresponding vector n indicates in how many slices the pizza slices of x were cut and t is a vector indicating the type of pizza (e.g. 1 is a margarita, 2 is a peperoni, etc.). How many complete pizzas do we have, when we cannot join 2 different pizzas?\u003c/p\u003e\u003cp\u003eExample:\u003c/p\u003e\u003cpre\u003e x = [1 3 12];\r\n n = [2 6 8];\r\n t = [1 2 1];\u003c/pre\u003e\u003cp\u003ein the first column we have on slice (x=1) from a pizza margarita (t=1) cut in half (n=2) -\u0026gt; half a pizza margarita. in the second column we have 3 slices (x=3) from a peperoni pizza (t=2) cut in 6 slices (n=6) -\u0026gt; so half a peperoni pizza. in the third column we have 12 slices of a margarita pizzas (t=1) cut in 8 slices -\u0026gt;1.5 slices margarita pizza.\u003c/p\u003e\u003cp\u003eso we can combine this to 2 pizza margaritas and 0.5 peperoni pizza. So in total we can combine 2 pizzas.\u003c/p\u003e","function_template":"function y = completePizzas(x,n,t)\r\n y = x;\r\nend","test_suite":"%%%%\r\n x = [1 3 12];\r\n n = [2 6 8];\r\n t = [1 2 1];\r\ny_correct = 2;\r\nassert(isequal(completePizzas(x,n,t),y_correct))\r\n%%\r\n x = [1 3 12];\r\n n = [2 6 8];\r\n t = [1 1 1];\r\ny_correct = 2;\r\nassert(isequal(completePizzas(x,n,t),y_correct))\r\n%%\r\n x = [1 3 12];\r\n n = [2 6 8];\r\n t = [1 1 2];\r\ny_correct = 2;\r\nassert(isequal(completePizzas(x,n,t),y_correct))\r\n%%\r\n x = [1 3 12];\r\n n = [2 6 8];\r\n t = [1 2 3];\r\ny_correct = 1;\r\nassert(isequal(completePizzas(x,n,t),y_correct))\r\n%%\r\n x = [1 3 58 41 24 7 5];\r\n n = [2 6 8 50 5 4 3];\r\n t = [1 2 3 1 4 2 3];\r\ny_correct = 15;\r\nassert(isequal(completePizzas(x,n,t),y_correct))\r\n","published":true,"deleted":false,"likes_count":0,"comments_count":1,"created_by":94929,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":22,"test_suite_updated_at":"2016-10-21T17:41:02.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-06T08:13:26.000Z","updated_at":"2026-01-20T12:37:21.000Z","published_at":"2016-10-06T08:13:26.000Z","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\u003ex is a vector with numbers of pizza slices. A corresponding vector n indicates in how many slices the pizza slices of x were cut and t is a vector indicating the type of pizza (e.g. 1 is a margarita, 2 is a peperoni, etc.). How many complete pizzas do we have, when we cannot join 2 different pizzas?\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[ x = [1 3 12];\\n n = [2 6 8];\\n t = [1 2 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\u003ein the first column we have on slice (x=1) from a pizza margarita (t=1) cut in half (n=2) -\u0026gt; half a pizza margarita. in the second column we have 3 slices (x=3) from a peperoni pizza (t=2) cut in 6 slices (n=6) -\u0026gt; so half a peperoni pizza. in the third column we have 12 slices of a margarita pizzas (t=1) cut in 8 slices -\u0026gt;1.5 slices margarita pizza.\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 we can combine this to 2 pizza margaritas and 0.5 peperoni pizza. So in total we can combine 2 pizzas.\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":44398,"title":"ベクトルの値が増加しているかを調べよう","description":"ベクトルの値が増加している場合 (ベクトルの各要素が前の要素よりも大きい場合) には true を、そうでない場合には false を返すようなコードを書いてみましょう。\r\n\r\n例:\r\n\r\n 入力が x = [-3 0 7] のとき、\r\n 関数の出力 tf は true を返します。\r\n\r\n 入力が x = [2 2] のとき、\r\n 関数の出力 tf は false を返します。\r\n\r\n* (英語版) Problem 10. Determine whether a vector is monotonically increasing\r\n\u003chttps://www.mathworks.com/matlabcentral/cody/problems/10-determine-whether-a-vector-is-monotonically-increasing\u003e","description_html":"\u003cp\u003eベクトルの値が増加している場合 (ベクトルの各要素が前の要素よりも大きい場合) には true を、そうでない場合には false を返すようなコードを書いてみましょう。\u003c/p\u003e\u003cp\u003e例:\u003c/p\u003e\u003cpre\u003e 入力が x = [-3 0 7] のとき、\r\n 関数の出力 tf は true を返します。\u003c/pre\u003e\u003cpre\u003e 入力が x = [2 2] のとき、\r\n 関数の出力 tf は false を返します。\u003c/pre\u003e\u003cul\u003e\u003cli\u003e(英語版) Problem 10. Determine whether a vector is monotonically increasing \u003ca href = \"https://www.mathworks.com/matlabcentral/cody/problems/10-determine-whether-a-vector-is-monotonically-increasing\"\u003ehttps://www.mathworks.com/matlabcentral/cody/problems/10-determine-whether-a-vector-is-monotonically-increasing\u003c/a\u003e\u003c/li\u003e\u003c/ul\u003e","function_template":"function tf = mono_increase(x)\r\n tf = false;\r\nend","test_suite":"%%\r\nx = [0 1 2 3 4];\r\nassert(isequal(mono_increase(x),true));\r\n%%\r\nx = [0];\r\nassert(isequal(mono_increase(x),true));\r\n%%\t\r\nx = [0 0 0 0 0];\r\nassert(isequal(mono_increase(x),false));\r\n%%\t\r\nx = [0 1 2 3 -4];\r\nassert(isequal(mono_increase(x),false));\r\n%%\t\r\nx = [-3 -4 2 3 4];\r\nassert(isequal(mono_increase(x),false));\r\n%%\r\nx = 1:.1:10;\r\nassert(isequal(mono_increase(x),true));\r\n%%\t\r\nx = cumsum(rand(1,100));\r\nx(5) = -1;\r\nassert(isequal(mono_increase(x),false));\r\n%%\t\r\nx = cumsum(rand(1,50));\r\nassert(isequal(mono_increase(x),true));","published":true,"deleted":false,"likes_count":2,"comments_count":1,"created_by":11824,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":367,"test_suite_updated_at":"2017-11-05T23:19:13.000Z","rescore_all_solutions":false,"group_id":36,"created_at":"2017-11-05T23:15:41.000Z","updated_at":"2026-03-17T03:46:51.000Z","published_at":"2017-11-05T23:19:13.000Z","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\",\"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\u003eベクトルの値が増加している場合 (ベクトルの各要素が前の要素よりも大きい場合) には true を、そうでない場合には false を返すようなコードを書いてみましょう。\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例:\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[ 入力が x = [-3 0 7] のとき、\\n 関数の出力 tf は true を返します。\\n\\n 入力が x = [2 2] のとき、\\n 関数の出力 tf は false を返します。]]\u003e\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=\\\"1\\\"/\u003e\u003c/w:numPr\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003e(英語版) Problem 10. Determine whether a vector is monotonically increasing\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/10-determine-whether-a-vector-is-monotonically-increasing\\\"\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026lt;https://www.mathworks.com/matlabcentral/cody/problems/10-determine-whether-a-vector-is-monotonically-increasing\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e\u0026gt;\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":1038,"title":"Change the sign of even index entries of the reversed vector","description":"change the signs of the even index entries of the reversed vector\r\n\r\nexample 1\r\nvec = [4 -1 -2 9]\r\nans = [9 2 -1 -4]\r\n\r\nexample2\r\nvec = [-4 -1 -2 -9]\r\nans = [-9 2 -1 4]","description_html":"\u003cp\u003echange the signs of the even index entries of the reversed vector\u003c/p\u003e\u003cp\u003eexample 1\r\nvec = [4 -1 -2 9]\r\nans = [9 2 -1 -4]\u003c/p\u003e\u003cp\u003eexample2\r\nvec = [-4 -1 -2 -9]\r\nans = [-9 2 -1 4]\u003c/p\u003e","function_template":"function y = your_fcn_name(x)\r\n y = x;\r\nend","test_suite":"%%\r\nx = [4 -5 -2 9];\r\ny_correct = [9 2 -5 -4];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = ones(1,4);\r\ny_correct = [1 -1 1 -1];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = 1:10;\r\ny_correct = [10 -9 8 -7 6 -5 4 -3 2 -1];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = 2:2:12;\r\ny_correct = [12 -10 8 -6 4 -2];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = -3:3;\r\ny_correct = [3 -2 1 0 -1 2 -3];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = [1 1 2 3 5 8 13 21 34 55 89 144];\r\ny_correct = [144 -89 55 -34 21 -13 8 -5 3 -2 1 -1];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = [1 0 1 0 1 0 1 0 1 0 1 0];\r\ny_correct = [0 -1 0 -1 0 -1 0 -1 0 -1 0 -1];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = [0 1 0 2 0 3 0 4 0 5 0 6];\r\ny_correct = [6 0 5 0 4 0 3 0 2 0 1 0];\r\nassert(isequal(your_fcn_name(x),y_correct))\r\n\r\n%%\r\nx = [0 1 0 1 0 1 0 1 0 1 0 1];\r\ny_correct = [x(2:end) x(1)];\r\nassert(isequal(your_fcn_name(x),y_correct))","published":true,"deleted":false,"likes_count":5,"comments_count":1,"created_by":1023,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":646,"test_suite_updated_at":"2016-11-18T03:05:04.000Z","rescore_all_solutions":false,"group_id":13,"created_at":"2012-11-19T03:18:07.000Z","updated_at":"2026-04-02T19:22:10.000Z","published_at":"2012-11-19T03:18:34.000Z","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\u003echange the signs of the even index entries of the reversed 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 1 vec = [4 -1 -2 9] ans = [9 2 -1 -4]\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\u003eexample2 vec = [-4 -1 -2 -9] ans = [-9 2 -1 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