{"group":{"id":1,"name":"Community","lockable":false,"created_at":"2012-01-18T18:02:15.000Z","updated_at":"2026-04-06T14:01:22.000Z","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":"2026-04-06T00:00:00.000Z","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":47583,"title":"Approximation of an integral - Riemann sum","description":"Riemann sum is a certain kind of approximation of an integral by a finite sum.\r\nIn this problem, I want you to use Midpoint Riemann sum to integrate a function. \r\nAs a test case, we should know that the integral of cos(x) over the interval [0,pi/2] is 1. Code numerical code, has only known spacing of the interval:\r\ndx = pi/10;\r\nx=0:dx:pi/2;\r\nfx = cos(x([1:end-1])+dx/2)\r\nriemannInt(fx,deltax)\r\nans =\r\n          1.004124203953987\r\nRound the answer according to the test suite","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: 266.1px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 133.05px; transform-origin: 407px 133.05px; 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\u003ca target='_blank' href = \"https://en.wikipedia.org/wiki/Riemann_sum\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eRiemann sum\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 198.5px 8px; transform-origin: 198.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is a certain kind of approximation of an integral by a finite sum.\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: 251.5px 8px; transform-origin: 251.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIn this problem, I want you to use Midpoint Riemann sum to integrate a function. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 371.5px 8px; transform-origin: 371.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAs a test case, we should know that the integral of cos(x) over the interval [0,pi/2] is 1. Code numerical code, has only known spacing of the interval:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 122.6px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 61.3px; transform-origin: 404px 61.3px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 44px 8.5px; tab-size: 4; transform-origin: 44px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003edx = pi/10;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003ex=0:dx:pi/2;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 108px 8.5px; tab-size: 4; transform-origin: 108px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003efx = cos(x([1:end-1])+dx/2)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 84px 8.5px; tab-size: 4; transform-origin: 84px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eriemannInt(fx,deltax)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 20px 8.5px; tab-size: 4; transform-origin: 20px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eans =\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: 108px 8.5px; tab-size: 4; transform-origin: 108px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e          1.004124203953987\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.5px; 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 10.75px; text-align: left; transform-origin: 384px 10.75px; 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: 176px 8px; transform-origin: 176px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 176px 8.5px; transform-origin: 176px 8.5px; \"\u003eRound the answer according to the test suite\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = riemannInt(fx,deltax)\r\n  y = x;\r\nend","test_suite":"%%\r\ndx = pi/10;\r\nx = 0:dx:pi/2;\r\nfx = cos(x([1:end-1])+dx/2);\r\ny_correct1 = 1.004;\r\n\r\nassert(isequal(riemannInt(fx,dx),y_correct1))\r\n\r\n%%\r\ndx = 0.1;\r\nx = 0:dx:10;\r\nfx = 3*sin(x([1:end-1])+dx/2);\r\ny_correct2 = 5.52;\r\n\r\nassert(isequal(riemannInt(fx,dx),y_correct2))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":219618,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":20,"test_suite_updated_at":"2020-11-26T10:25:20.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-11-21T19:49:59.000Z","updated_at":"2026-03-02T14:02:18.000Z","published_at":"2020-11-21T19:49:59.000Z","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:hyperlink w:docLocation=\\\"https://en.wikipedia.org/wiki/Riemann_sum\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eRiemann sum\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e is a certain kind of approximation of an integral by a finite sum.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn this problem, I want you to use Midpoint Riemann sum to integrate a function. \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\u003eAs a test case, we should know that the integral of cos(x) over the interval [0,pi/2] is 1. Code numerical code, has only known spacing of the interval:\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[dx = pi/10;\\nx=0:dx:pi/2;\\nfx = cos(x([1:end-1])+dx/2)\\nriemannInt(fx,deltax)\\nans =\\n          1.004124203953987]]\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:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eRound the answer according to the test suite\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":43007,"title":"Euclidean inter-point distance matrix","description":"The Euclidean distance between two points in a p-dimensional space is a really common thing to compute in the field of computational geometry. In fact, it is pretty easy to do. norm(u-v) would seem to do the trick, for vectors u and v.\r\n\r\nBut what if you have a large number of points between which you want to compute ALL of those distances between every pair of points? In this problem, given an n by p array A, where each row of the matrix will be viewed as containing the coordinates of one p-dimensional point, you need to compute the n by n inter-point distance matrix.\r\n\r\nThus, D(i,J) will be the Euclidean distance between the i'th and j'th rows of A. Of course, D will be a symmetric matrix, with zeros on the diagonal.\r\n\r\nSo you can test your code, here is an example:\r\n\r\n  A = [1 1\r\n       5 2\r\n       2 2\r\n       4 5]\r\n\r\n  format short g\r\n  D = interDist(A)\r\n  D =\r\n         0       4.1231       1.4142            5\r\n    4.1231            0            3       3.1623\r\n    1.4142            3            0       3.6056\r\n         5       3.1623       3.6056            0\r\n\r\nThus, thinking of the points [1 1] and [5 2] as the coordinates of two points in the (x,y) plane, the Euclidean distance between them in that plane is 4.1231...\r\n\r\nAs you can see, the matrix is symmetric, with zeros on the main diagonal. That must always happen, since the distance between any point and itself must be zero.","description_html":"\u003cp\u003eThe Euclidean distance between two points in a p-dimensional space is a really common thing to compute in the field of computational geometry. In fact, it is pretty easy to do. norm(u-v) would seem to do the trick, for vectors u and v.\u003c/p\u003e\u003cp\u003eBut what if you have a large number of points between which you want to compute ALL of those distances between every pair of points? In this problem, given an n by p array A, where each row of the matrix will be viewed as containing the coordinates of one p-dimensional point, you need to compute the n by n inter-point distance matrix.\u003c/p\u003e\u003cp\u003eThus, D(i,J) will be the Euclidean distance between the i'th and j'th rows of A. Of course, D will be a symmetric matrix, with zeros on the diagonal.\u003c/p\u003e\u003cp\u003eSo you can test your code, here is an example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eA = [1 1\r\n     5 2\r\n     2 2\r\n     4 5]\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003eformat short g\r\nD = interDist(A)\r\nD =\r\n       0       4.1231       1.4142            5\r\n  4.1231            0            3       3.1623\r\n  1.4142            3            0       3.6056\r\n       5       3.1623       3.6056            0\r\n\u003c/pre\u003e\u003cp\u003eThus, thinking of the points [1 1] and [5 2] as the coordinates of two points in the (x,y) plane, the Euclidean distance between them in that plane is 4.1231...\u003c/p\u003e\u003cp\u003eAs you can see, the matrix is symmetric, with zeros on the main diagonal. That must always happen, since the distance between any point and itself must be zero.\u003c/p\u003e","function_template":"function D = interDist(A)\r\n  % compute the interpoint distance matrix between rows of A\r\n  D = A;\r\nend\r\n\r\n","test_suite":"%%\r\nA = eye(3);\r\ny_correct = (1-A)*sqrt(2);\r\ntol = 10*eps;\r\nassert(norm(interDist(A)-y_correct) \u003c tol)\r\n\r\n%%\r\nA = (1:4)';\r\ny_correct = [     0     1     2     3;...\r\n     1     0     1     2;...\r\n     2     1     0     1;...\r\n     3     2     1     0];\r\ntol = 10*eps;\r\nassert(norm(interDist(A)-y_correct) \u003c tol)\r\n\r\n\r\n\r\n\r\n%%\r\nA = magic(3);\r\ny_correct = [0       6.48074069840786 9.79795897113271; ...\r\n  6.48074069840786                0 6.48074069840786; ...\r\n  9.79795897113271 6.48074069840786                0];\r\ntol = 1000*eps;\r\nassert(norm(interDist(A)-y_correct) \u003c tol)\r\n\r\n%%\r\nA = reshape((1:20).^2,4,5);\r\ntol = 1e-12;\r\ny_correct = [0 49.4469412603045 102.761860629321 160.015624237135; ...\r\n   49.4469412603045 0 53.3385414123783 110.634533487515; ...\r\n   102.761860629321 53.3385414123783 0 57.3149195236284; ...\r\n   160.015624237135 110.634533487515 57.3149195236284 0];\r\nassert(norm(interDist(A)-y_correct) \u003c tol)\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":544,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":28,"test_suite_updated_at":"2016-10-02T16:43:44.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-02T13:56:26.000Z","updated_at":"2026-04-02T13:14:06.000Z","published_at":"2016-10-02T16:43:44.000Z","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\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Euclidean distance between two points in a p-dimensional space is a really common thing to compute in the field of computational geometry. In fact, it is pretty easy to do. norm(u-v) would seem to do the trick, for vectors u and v.\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\u003eBut what if you have a large number of points between which you want to compute ALL of those distances between every pair of points? In this problem, given an n by p array A, where each row of the matrix will be viewed as containing the coordinates of one p-dimensional point, you need to compute the n by n inter-point distance matrix.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThus, D(i,J) will be the Euclidean distance between the i'th and j'th rows of A. Of course, D will be a symmetric matrix, with zeros on the diagonal.\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 you can test your code, here is an 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[A = [1 1\\n     5 2\\n     2 2\\n     4 5]\\n\\nformat short g\\nD = interDist(A)\\nD =\\n       0       4.1231       1.4142            5\\n  4.1231            0            3       3.1623\\n  1.4142            3            0       3.6056\\n       5       3.1623       3.6056            0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThus, thinking of the points [1 1] and [5 2] as the coordinates of two points in the (x,y) plane, the Euclidean distance between them in that plane is 4.1231...\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\u003eAs you can see, the matrix is symmetric, with zeros on the main diagonal. That must always happen, since the distance between any point and itself must be zero.\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":58817,"title":"Find the phi variation as a function of distance after solving through finite volume method. Return dphi/dx at all faces in form of array.","description":"\r\nThe question is a NPTEL online course assignment question. I have put it here becuase I wanted to create a problem set for numerical methods and computational engineering so that mechanical engineers can try it out. Interested ones can contact me so that we can create a problem group for CFD and FEM. 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data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63.0199px; 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: 384.502px 31.5044px; text-align: left; transform-origin: 384.502px 31.51px; 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=\"\"\u003eThe question is a NPTEL online course assignment question. I have put it here becuase I wanted to create a problem set for numerical methods and computational engineering so that mechanical engineers can try it out. Interested ones can contact me so that we can create a problem group for CFD and FEM. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = oneD(n) %n is the number of grid points\r\n  \r\nend","test_suite":"%%\r\nn = 5;\r\ny_correct =  [0,47.5,38.5,23.5,2.5,0];\r\nassert(isequal(oneD(n),y_correct))\r\n%% \r\nfiletext = fileread('oneD.m');\r\nillegal = contains(filetext,'47.5'); \r\nassert(~illegal)","published":true,"deleted":false,"likes_count":0,"comments_count":1,"created_by":1809490,"edited_by":1809490,"edited_at":"2023-08-13T05:44:21.000Z","deleted_by":null,"deleted_at":null,"solvers_count":4,"test_suite_updated_at":"2023-08-13T05:44:21.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2023-08-07T17:01:20.000Z","updated_at":"2024-11-02T15:52:16.000Z","published_at":"2023-08-07T17:29:20.000Z","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:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"523\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"1200\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe question is a NPTEL online course assignment question. I have put it here becuase I wanted to create a problem set for numerical methods and computational engineering so that mechanical engineers can try it out. Interested ones can contact me so that we can create a problem group for CFD and FEM. 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rule (but not Homer Simpson)","description":"I wonder what Homer Simpson would have thought of Simpson's rule? Somehow I doubt his thoughts would have included the phrase Newton-Cotes, or even numerical integration.\r\n\r\nIn this problem, I want you to use \u003chttps://en.wikipedia.org/wiki/Simpson%27s_rule Simpson's rule\u003e to integrate a function, provided as a list of points in a vector. The points must be equally spaced in x, so all that need be provided is the spacing between points in x. As well, I'll be nice and always give you an odd number of points, since that is important for Simpson's rule to work smoothly.\r\n\r\nAs a test case, we should know that the integral of cos(x) over the interval [0,pi/2] is 1, at least analytically that is true. Your Simpson's rule code, for only 7 points spanning that interval will do pretty well:\r\n\r\n  deltax = pi/12;\r\n  Fx = cos(linspace(0,pi/2,7));\r\n  simpsInt(Fx,deltax)\r\n  ans =\r\n            1.00002631217059\r\n\r\nThus, Fx is a vector of supplied function values, and deltax is the step size taken on the x-axis.\r\n\r\nHomer would be proud.","description_html":"\u003cp\u003eI wonder what Homer Simpson would have thought of Simpson's rule? Somehow I doubt his thoughts would have included the phrase Newton-Cotes, or even numerical integration.\u003c/p\u003e\u003cp\u003eIn this problem, I want you to use \u003ca href = \"https://en.wikipedia.org/wiki/Simpson%27s_rule\"\u003eSimpson's rule\u003c/a\u003e to integrate a function, provided as a list of points in a vector. The points must be equally spaced in x, so all that need be provided is the spacing between points in x. As well, I'll be nice and always give you an odd number of points, since that is important for Simpson's rule to work smoothly.\u003c/p\u003e\u003cp\u003eAs a test case, we should know that the integral of cos(x) over the interval [0,pi/2] is 1, at least analytically that is true. Your Simpson's rule code, for only 7 points spanning that interval will do pretty well:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003edeltax = pi/12;\r\nFx = cos(linspace(0,pi/2,7));\r\nsimpsInt(Fx,deltax)\r\nans =\r\n          1.00002631217059\r\n\u003c/pre\u003e\u003cp\u003eThus, Fx is a vector of supplied function values, and deltax is the step size taken on the x-axis.\u003c/p\u003e\u003cp\u003eHomer would be proud.\u003c/p\u003e","function_template":"function y = simpsInt(Fx,deltax)\r\n  % simple Simpson's rule integration.\r\n  y = Fx;\r\nend\r\n","test_suite":"%%\r\ndeltax = pi/12;\r\nFx = cos(linspace(0,pi/2,7));\r\ny_correct = 1.00002631217059;\r\ntol = 1e-14;\r\nassert(abs(simpsInt(Fx,deltax) - y_correct) \u003c tol)\r\n\r\n%%\r\ndeltax = 0.125;\r\nFx = exp((0:8)/8);\r\ny_correct = 1.7182841546999;\r\ntol = 1e-14;\r\nassert(abs(simpsInt(Fx,deltax) - y_correct) \u003c tol)\r\n\r\n%%\r\ndeltax = 1;\r\nFx = (0:10).^2;\r\ny_correct = 1000/3;\r\ntol = 1e-11;\r\nassert(abs(simpsInt(Fx,deltax) - y_correct) \u003c tol)\r\n\r\n%%\r\ndeltax = 1;\r\nFx = (0:10).^4;\r\ny_correct = 20001.3333333333333;\r\ntol = 1e-9;\r\nassert(abs(simpsInt(Fx,deltax) - y_correct) \u003c tol)\r\n\r\n%%\r\ndeltax = 1;\r\nFx = sin(-5:5);\r\ny_correct = 0;\r\ntol = 1e-15;\r\nassert(abs(simpsInt(Fx,deltax) - y_correct) \u003c tol)\r\n\r\n%%\r\ndeltax = 0.25;\r\nFx = sin(0:.25:100);\r\ny_correct = 0.13768413796203;\r\ntol = 1e-15;\r\nassert(abs(simpsInt(Fx,deltax) - y_correct) \u003c tol)\r\n\r\n%%\r\ndeltax = 1;\r\nFx = double((0:10) \u003e= 5);\r\ny_correct = 5.66666666666667;\r\ntol = 1e-14;\r\nabs(simpsInt(Fx,deltax) - y_correct) \u003c tol\r\n\r\n","published":true,"deleted":false,"likes_count":4,"comments_count":9,"created_by":544,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":49,"test_suite_updated_at":"2016-10-02T01:31:18.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-01T23:16:52.000Z","updated_at":"2026-04-04T10:41:35.000Z","published_at":"2016-10-01T23:16:52.000Z","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\",\"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\u003eI wonder what Homer Simpson would have thought of Simpson's rule? Somehow I doubt his thoughts would have included the phrase Newton-Cotes, or even numerical integration.\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 this problem, I want you to use\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://en.wikipedia.org/wiki/Simpson%27s_rule\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eSimpson's rule\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e to integrate a function, provided as a list of points in a vector. The points must be equally spaced in x, so all that need be provided is the spacing between points in x. As well, I'll be nice and always give you an odd number of points, since that is important for Simpson's rule to work smoothly.\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\u003eAs a test case, we should know that the integral of cos(x) over the interval [0,pi/2] is 1, at least analytically that is true. Your Simpson's rule code, for only 7 points spanning that interval will do pretty well:\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[deltax = pi/12;\\nFx = cos(linspace(0,pi/2,7));\\nsimpsInt(Fx,deltax)\\nans =\\n          1.00002631217059]]\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\u003eThus, Fx is a vector of supplied function values, and deltax is the step size taken on the x-axis.\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\u003eHomer would be proud.\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":46918,"title":"Numerical differentiation with high precision","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: 447.9px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 223.95px; transform-origin: 407px 223.95px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 98.2px; 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 49.1px; text-align: left; transform-origin: 384px 49.1px; 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: 264.658px 8px; transform-origin: 264.658px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA basic approach for numerical differentiation is by calculating the difference quotient \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-15px\"\u003e\u003cimg src=\"data:image/png;base64,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\" alt=\"f'(x) = (f(x+h) - f(x-h)) / (2h)\" style=\"width: 178px; height: 35px;\" width=\"178\" height=\"35\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 27.2167px 8px; transform-origin: 27.2167px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, see for example \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://www.mathworks.com/matlabcentral/cody/problems/2892\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eProblem 2892\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 233.242px 8px; transform-origin: 233.242px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. Unfortunately, this approach leads to the problem that for small step sizes \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: 3.89167px 8px; transform-origin: 3.89167px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003eh\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: 43.5583px 8px; transform-origin: 43.5583px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e a subtractive cancellation error occurs, while for large step sizes the truncation error of the numerical scheme dominates. The same problem occurs also for similar numerical schemes of higher order.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 238.7px; 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 119.35px; text-align: left; transform-origin: 384px 119.35px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline;width: 273px;height: 233px\" 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\" data-image-state=\"image-loaded\" width=\"273\" height=\"233\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 17.7667px 8px; transform-origin: 17.7667px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eTask:\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: 355.55px 8px; transform-origin: 355.55px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e Can you find a numerical approach that eliminates the subtractive cancellation error and enables accuracies up to machine accuracy for small step sizes? Inputs to your function are a function handle \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: 11.55px 8px; transform-origin: 11.55px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003efun\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: 108.9px 8px; transform-origin: 108.9px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e to a scalar function, as well as the point \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: 7.7px 8px; transform-origin: 7.7px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex0\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: 173.108px 8px; transform-origin: 173.108px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, at which the numerical derivative should be calculated.\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: 15.9417px 8px; transform-origin: 15.9417px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eHint:\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: 121.733px 8px; transform-origin: 121.733px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e If you do not have any idea, check out \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://blogs.mathworks.com/cleve/\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eCleve's Corner\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 178.15px 8px; transform-origin: 178.15px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. Back in the year 2013, you will find an interesting article.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function Df = numerical_diff(fun,x0)\r\n  % this basic approach will not be good enough.. :-(\r\n  % h  = 1e-5;\r\n  % Df = (fun(x0+h) - fun(x0-h)) / (2*h);\r\nend","test_suite":"%%\r\nfun = @sin;\r\nfor k = 1:5\r\n  x = randn;\r\n  assert(abs(numerical_diff(fun,x) - cos(x)) \u003c 1e-12)\r\nend\r\n%%\r\nfun = @(x)x^(9/2);\r\nfor k = 1:5\r\n  x = abs(randn);\r\n  assert(abs(numerical_diff(fun,x) - (9/2)*x^(7/2)) \u003c 1e-12);\r\nend\r\n%%\r\nfun = @(x)exp(x)/(cos(x)^3+sin(x)^3);\r\nx  = [ 0 pi/4 pi/2 pi ];\r\nDf = [ 1 exp(pi/4)*sqrt(2) exp(pi/2) -exp(pi)];\r\nfor k = 1:4\r\n  assert(abs(numerical_diff(fun,x(k)) - Df(k)) \u003c 1e-12);\r\nend\r\n%%\r\nfun = @(x)exp(x)/sqrt(cos(x)^3+sin(x)^3);\r\nx  = [ -pi/8 0 pi/8 pi/4 pi/2 ];\r\nDf = [ 0.042678767134941 1 2.15903261751524 exp(pi/4)*2^(1/4) exp(pi/2) -exp(pi)];\r\nfor k = 1:5\r\n  assert(abs(numerical_diff(fun,x(k)) - Df(k)) \u003c 1e-12)\r\nend\r\n%%\r\nstr = fileread('numerical_diff.m'); % sorry, no regexp hacks :-)\r\nassert(isempty(regexp(str,'regexp')));","published":true,"deleted":false,"likes_count":2,"comments_count":2,"created_by":11486,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":10,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-10-18T17:51:29.000Z","updated_at":"2020-10-18T17:56:54.000Z","published_at":"2020-10-18T17:56:16.000Z","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\u003eA basic approach for numerical differentiation is by calculating the difference quotient \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"f'(x) = (f(x+h) - f(x-h)) / (2h)\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ef^\\\\prime(x) \\\\approx \\\\frac{f(x+h) - f(x-h)}{2h}\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e, see for example \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.mathworks.com/matlabcentral/cody/problems/2892\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eProblem 2892\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. Unfortunately, this approach leads to the problem that for small step sizes \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eh\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e a subtractive cancellation error occurs, while for large step sizes the truncation error of the numerical scheme dominates. The same problem occurs also for similar numerical schemes of higher order.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"233\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"273\\\"/\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:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eTask:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Can you find a numerical approach that eliminates the subtractive cancellation error and enables accuracies up to machine accuracy for small step sizes? Inputs to your function are a function handle \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\u003efun\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e to a scalar function, as well as the point \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\u003ex0\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, at which the numerical derivative should be calculated.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eHint:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e If you do not have any idea, check out \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://blogs.mathworks.com/cleve/\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eCleve's Corner\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. Back in the year 2013, you will find an interesting 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\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":46053,"title":"Construct finite difference approximations of derivatives","description":"In solving a differential equation with a finite-difference method, one computes derivatives with various combinations of the function's values at chosen grid points. For example, the forward difference formula for the first derivative is\r\n\r\n f' = (f_{j+1} - f_j)/h\r\n\r\nwhere j is the grid index and h is the spacing between points. The systematic approach for deriving such formulas is to \u003chttp://www2.math.umd.edu/~dlevy/classes/amsc466/lecture-notes/differentiation-chap.pdf use Taylor series\u003e. In the example above, one can write\r\n\r\n f_{j+1} = f_j + h f' + h^2 f''/2 + h^3 f'''/6 + ...\r\n\r\nThen solving for f' and neglecting terms of order h^2 and higher gives\r\n\r\n f' = (f_{j+1} - f_j)/h - h f''/2\r\n\r\nBecause the exponent on h in the last term is 1, the method is called a first order method.\r\n\r\nWrite a function that takes the order |n| of the derivative and a vector |terms| indicating the terms to use (based on the number of grid cells away from the point in question) and produces a vector of coefficients, the order of the error term, and the numerical coefficient of the error term. In the above example, |n = 1| and |terms = [1 0]|, and \r\n\r\n coeffs   = [1 -1]\r\n errOrder = 1\r\n errCoeff = -0.5; \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: 435.55px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 217.775px; transform-origin: 407px 217.775px; 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: 380.183px 7.91667px; transform-origin: 380.183px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIn solving a differential equation with a finite-difference method, one computes derivatives with various combinations of the function's values at chosen grid points. For example, the forward difference formula for the first derivative is\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 37.5833px; 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 18.7917px; text-align: left; transform-origin: 384px 18.7917px; 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: 13.5917px 7.91667px; transform-origin: 13.5917px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e       \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-15px\"\u003e\u003cimg src=\"data:image/png;base64,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\" alt=\"f' = (f_{j+1} - f_j})/h\" style=\"width: 84.5px; height: 37.5px;\" width=\"84.5\" height=\"37.5\"\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 365.642px 7.91667px; transform-origin: 365.642px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ewhere j is the grid index and h is the spacing between points. The systematic approach for deriving such formulas is to\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: 1.94167px 7.91667px; transform-origin: 1.94167px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://www2.math.umd.edu/~dlevy/classes/amsc466/lecture-notes/differentiation-chap.pdf\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003euse Taylor series\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 116.3px 7.91667px; transform-origin: 116.3px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. In the example above, one can write\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 36.0833px; 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 18.0417px; text-align: left; transform-origin: 384px 18.0417px; 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: 13.5917px 7.91667px; transform-origin: 13.5917px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e       \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-15px\"\u003e\u003cimg src=\"data:image/png;base64,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\" alt=\"f_{j+1} = f_j + hf' + h^2 f''/2 + h^3 f'''/6 + ...\" style=\"width: 226.5px; height: 36px;\" width=\"226.5\" height=\"36\"\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: 51.7333px 7.91667px; transform-origin: 51.7333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThen solving for \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACMAAAAkCAYAAAAD3IPhAAABNklEQVRYhe2XXbGEMAxGj4c6wAAGVsEqwEEdrINrAQ1IwAMWqgEL3IcmU3Zm2W2ZBnjgPPET2kyS5gtwc3MDQAM8Mu0aKydaIAAj0AMz4L/YLsBk4chDFh/k3sv9DLgP9n/yvq/tiJNNZ1LYn7LZuPFNkPdtbWdevEflF5qiXPsiZlm8y7TXFFaPSicLL+SfjAmjqAziSMi0d2L/qah34Yl18iKlKKye+S+bdcSTVA3dtCelaFg9/1U7Jo1OT9FCXsc1Retlq7EditbLVmM7jIaUoqoFuQdt94tcn4oKXdWesZcRwxGgFI1K9RGgFFXdEnE0Q1W3RBzNUBnIFUdTJi7SX3QEMBmOStFh6vAj7Yj1sf7dUHE8XKXXI4IjHelTektLVOZATE84yxGlIabJc4GecnMp/gGjCl04ApTc8QAAAABJRU5ErkJggg==\" alt=\"f'\" style=\"width: 17.5px; height: 18px;\" width=\"17.5\" height=\"18\"\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: 94.9083px 7.91667px; transform-origin: 94.9083px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and neglecting terms of order \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,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\" alt=\"h^2\" style=\"width: 15.5px; height: 19.5px;\" width=\"15.5\" height=\"19.5\"\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: 53.3px 7.91667px; transform-origin: 53.3px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and higher gives\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 38.5833px; 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 19.2917px; text-align: left; transform-origin: 384px 19.2917px; 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: 13.5917px 7.91667px; transform-origin: 13.5917px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e       \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-15px\"\u003e\u003cimg src=\"data:image/png;base64,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\" alt=\"f' = (f_{j+1} - f_j)/h - hf''/2\" style=\"width: 130px; height: 38.5px;\" width=\"130\" height=\"38.5\"\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: 81.3px 7.91667px; transform-origin: 81.3px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eBecause the exponent on \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: \u0026quot;STIXGeneral\u0026quot;, \u0026quot;STIXGeneral-webfont\u0026quot;, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003eh\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: 191.35px 7.91667px; transform-origin: 191.35px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e in the last term is 1, the method is called a first order method.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 110.717px 7.91667px; transform-origin: 110.717px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function that takes the order\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: 1.94167px 7.91667px; transform-origin: 1.94167px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: \u0026quot;STIXGeneral\u0026quot;, \u0026quot;STIXGeneral-webfont\u0026quot;, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003en\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: 91.7917px 7.91667px; transform-origin: 91.7917px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e of the derivative and 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: 1.94167px 7.91667px; transform-origin: 1.94167px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eterms\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: 130.3px 7.91667px; transform-origin: 130.3px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e indicating the terms to use (based on the number of grid cells away from the point in question) and produces a vector of coefficients, the order of the error term, and the numerical coefficient of the error term. In the above example,\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: 1.94167px 7.91667px; transform-origin: 1.94167px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003en = 1\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: 13.6167px 7.91667px; transform-origin: 13.6167px 7.91667px; 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: 1.94167px 7.91667px; transform-origin: 1.94167px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 50.05px 7.91667px; transform-origin: 50.05px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eterms = [1 0]\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: 15.5583px 7.91667px; transform-origin: 15.5583px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, and\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: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; 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: 69.3px 7.91667px; transform-origin: 69.3px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e coeffs   = [1 -1]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; 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: 50.05px 7.91667px; transform-origin: 50.05px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e errOrder = 1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; 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: 65.45px 7.91667px; transform-origin: 65.45px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e errCoeff = -0.5;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [coeff,errOrder,errCoeff] = FDderiv(n,terms)\r\n%  n        = order of the derivative sought\r\n%  terms    = grid indices of terms to include\r\n%  coeff    = coefficients of the terms in the formula \r\n%  errOrder = exponent of h in the first non-zero higher-order term\r\n%  errCoeff = coefficient of the first non-zero higher-order term\r\n\r\n  coeff    = ...\r\n  errOrder = ...\r\n  errCoeff = ...\r\nend","test_suite":"%%\r\n%  First-order forward difference for the first derivative\r\nn = 1;\r\nterms = [1 0];\r\ncoeff_correct = [1 -1];\r\nerrOrder_correct = 1;\r\nerrCoeff_correct = -1/2;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  First-order backward difference for the first derivative\r\nn = 1;\r\nterms = [0 -1];\r\ncoeff_correct = [1 -1];\r\nerrOrder_correct = 1;\r\nerrCoeff_correct = 1/2;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  Second-order centered difference for the first derivative\r\nn = 1;\r\nterms = [1 -1];\r\ncoeff_correct = [1/2 -1/2];\r\nerrOrder_correct = 2;\r\nerrCoeff_correct = -1/6;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  Second-order forward difference for the first derivative\r\nn = 1;\r\nterms = [2 1 0];\r\ncoeff_correct = [-1/2 2 -3/2];\r\nerrOrder_correct = 2;\r\nerrCoeff_correct = 1/3;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  Second-order backward difference for the first derivative\r\nn = 1;\r\nterms = [0 -1 -2];\r\ncoeff_correct = [3/2 -2 1/2];\r\nerrOrder_correct = 2;\r\nerrCoeff_correct = 1/3;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  Fourth-order centered difference for the first derivative\r\nn = 1;\r\nterms = [2 1 0 -1 -2];\r\ncoeff_correct = [-1 8 0 -8 1]/12\r\nerrOrder_correct = 4;\r\nerrCoeff_correct = 1/30;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  Second-order centered difference for the second derivative\r\nn = 2;\r\nterms = [1 0 -1];\r\ncoeff_correct = [1 -2 1];\r\nerrOrder_correct = 2;\r\nerrCoeff_correct = -1/12;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  Fourth-order centered difference for the second derivative\r\nn = 2;\r\nterms = [2 1 0 -1 -2];\r\ncoeff_correct = [-1 16 -30 16 -1]/12;\r\nerrOrder_correct = 4;\r\nerrCoeff_correct = 1/90;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  Second-order centered difference for the third derivative\r\nn = 3;\r\nterms = [2 1 0 -1 -2];\r\ncoeff_correct = [1/2 -1 0 1 -1/2];\r\nerrOrder_correct = 2;\r\nerrCoeff_correct = -1/4;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  Second-order centered difference for the fourth derivative\r\nn = 4;\r\nterms = [2 1 0 -1 -2];\r\ncoeff_correct = [1 -4 6 -4 1];\r\nerrOrder_correct = 2;\r\nerrCoeff_correct = -1/6;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":46909,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-07-22T03:37:57.000Z","updated_at":"2020-11-15T13:41:30.000Z","published_at":"2020-07-22T05:20:57.000Z","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\u003eIn solving a differential equation with a finite-difference method, one computes derivatives with various combinations of the function's values at chosen grid points. For example, the forward difference formula for the first derivative is\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:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"f' = (f_{j+1} - f_j})/h\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ef\\\\prime=\\\\frac{f_{j+1}-f_j}{h}\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ewhere j is the grid index and h is the spacing between points. The systematic approach for deriving such formulas is to\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www2.math.umd.edu/~dlevy/classes/amsc466/lecture-notes/differentiation-chap.pdf\\\"\u003e\u003cw:r\u003e\u003cw:t\u003euse Taylor series\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. In the example above, one can write\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:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"f_{j+1} = f_j + hf' + h^2 f''/2 + h^3 f'''/6 + ...\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e f_{j+1} = f_j + h f\\\\prime +  \\\\frac{h^2}{2}f\\\\prime\\\\prime +  \\\\frac{h^3}{6}f\\\\prime\\\\prime\\\\prime + \\\\ldots\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThen solving for \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"f'\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e$f\\\\prime$\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e and neglecting terms of order \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"h^2\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e$h^2$\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e and higher gives\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:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"f' = (f_{j+1} - f_j)/h - hf''/2\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ef\\\\prime = \\\\frac{f_{j+1} - f_j}{h} - \\\\frac{h}{2}f\\\\prime\\\\prime\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eBecause the exponent on \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"h\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eh\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e in the last term is 1, the method is called a first order method.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function that takes the order\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"n\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e of the derivative and a vector\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\u003eterms\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e indicating the terms to use (based on the number of grid cells away from the point in question) and produces a vector of coefficients, the order of the error term, and the numerical coefficient of the error term. In the above example,\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\u003en = 1\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eterms = [1 0]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, and\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[ coeffs   = [1 -1]\\n errOrder = 1\\n errCoeff = -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\"}]}"}],"problem_search":{"errors":[],"problems":[{"id":47583,"title":"Approximation of an integral - Riemann sum","description":"Riemann sum is a certain kind of approximation of an integral by a finite sum.\r\nIn this problem, I want you to use Midpoint Riemann sum to integrate a function. \r\nAs a test case, we should know that the integral of cos(x) over the interval [0,pi/2] is 1. Code numerical code, has only known spacing of the interval:\r\ndx = pi/10;\r\nx=0:dx:pi/2;\r\nfx = cos(x([1:end-1])+dx/2)\r\nriemannInt(fx,deltax)\r\nans =\r\n          1.004124203953987\r\nRound the answer according to the test suite","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: 266.1px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 133.05px; transform-origin: 407px 133.05px; 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\u003ca target='_blank' href = \"https://en.wikipedia.org/wiki/Riemann_sum\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eRiemann sum\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 198.5px 8px; transform-origin: 198.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e is a certain kind of approximation of an integral by a finite sum.\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: 251.5px 8px; transform-origin: 251.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIn this problem, I want you to use Midpoint Riemann sum to integrate a function. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 371.5px 8px; transform-origin: 371.5px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eAs a test case, we should know that the integral of cos(x) over the interval [0,pi/2] is 1. Code numerical code, has only known spacing of the interval:\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgb(247, 247, 247); block-size: 122.6px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 61.3px; transform-origin: 404px 61.3px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; \"\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 44px 8.5px; tab-size: 4; transform-origin: 44px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003edx = pi/10;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 48px 8.5px; tab-size: 4; transform-origin: 48px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003ex=0:dx:pi/2;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 108px 8.5px; tab-size: 4; transform-origin: 108px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003efx = cos(x([1:end-1])+dx/2)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 84px 8.5px; tab-size: 4; transform-origin: 84px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eriemannInt(fx,deltax)\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 1px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 1px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 1px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 1px; border-start-end-radius: 0px; border-start-start-radius: 0px; border-top-left-radius: 0px; border-top-right-radius: 0px; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; min-block-size: 18px; min-height: 18px; padding-inline-start: 4px; padding-left: 4px; perspective-origin: 404px 10.2167px; transform-origin: 404px 10.2167px; white-space: nowrap; \"\u003e\u003cspan style=\"block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 20px 8.5px; tab-size: 4; transform-origin: 20px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003eans =\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; 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\"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e          1.004124203953987\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 21.5px; 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 10.75px; text-align: left; transform-origin: 384px 10.75px; 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: 176px 8px; transform-origin: 176px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; perspective-origin: 176px 8.5px; transform-origin: 176px 8.5px; \"\u003eRound the answer according to the test suite\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = riemannInt(fx,deltax)\r\n  y = x;\r\nend","test_suite":"%%\r\ndx = pi/10;\r\nx = 0:dx:pi/2;\r\nfx = cos(x([1:end-1])+dx/2);\r\ny_correct1 = 1.004;\r\n\r\nassert(isequal(riemannInt(fx,dx),y_correct1))\r\n\r\n%%\r\ndx = 0.1;\r\nx = 0:dx:10;\r\nfx = 3*sin(x([1:end-1])+dx/2);\r\ny_correct2 = 5.52;\r\n\r\nassert(isequal(riemannInt(fx,dx),y_correct2))\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":219618,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":20,"test_suite_updated_at":"2020-11-26T10:25:20.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2020-11-21T19:49:59.000Z","updated_at":"2026-03-02T14:02:18.000Z","published_at":"2020-11-21T19:49:59.000Z","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:hyperlink w:docLocation=\\\"https://en.wikipedia.org/wiki/Riemann_sum\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eRiemann sum\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e is a certain kind of approximation of an integral by a finite sum.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eIn this problem, I want you to use Midpoint Riemann sum to integrate a function. \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\u003eAs a test case, we should know that the integral of cos(x) over the interval [0,pi/2] is 1. Code numerical code, has only known spacing of the interval:\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[dx = pi/10;\\nx=0:dx:pi/2;\\nfx = cos(x([1:end-1])+dx/2)\\nriemannInt(fx,deltax)\\nans =\\n          1.004124203953987]]\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:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eRound the answer according to the test suite\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":43007,"title":"Euclidean inter-point distance matrix","description":"The Euclidean distance between two points in a p-dimensional space is a really common thing to compute in the field of computational geometry. In fact, it is pretty easy to do. norm(u-v) would seem to do the trick, for vectors u and v.\r\n\r\nBut what if you have a large number of points between which you want to compute ALL of those distances between every pair of points? In this problem, given an n by p array A, where each row of the matrix will be viewed as containing the coordinates of one p-dimensional point, you need to compute the n by n inter-point distance matrix.\r\n\r\nThus, D(i,J) will be the Euclidean distance between the i'th and j'th rows of A. Of course, D will be a symmetric matrix, with zeros on the diagonal.\r\n\r\nSo you can test your code, here is an example:\r\n\r\n  A = [1 1\r\n       5 2\r\n       2 2\r\n       4 5]\r\n\r\n  format short g\r\n  D = interDist(A)\r\n  D =\r\n         0       4.1231       1.4142            5\r\n    4.1231            0            3       3.1623\r\n    1.4142            3            0       3.6056\r\n         5       3.1623       3.6056            0\r\n\r\nThus, thinking of the points [1 1] and [5 2] as the coordinates of two points in the (x,y) plane, the Euclidean distance between them in that plane is 4.1231...\r\n\r\nAs you can see, the matrix is symmetric, with zeros on the main diagonal. That must always happen, since the distance between any point and itself must be zero.","description_html":"\u003cp\u003eThe Euclidean distance between two points in a p-dimensional space is a really common thing to compute in the field of computational geometry. In fact, it is pretty easy to do. norm(u-v) would seem to do the trick, for vectors u and v.\u003c/p\u003e\u003cp\u003eBut what if you have a large number of points between which you want to compute ALL of those distances between every pair of points? In this problem, given an n by p array A, where each row of the matrix will be viewed as containing the coordinates of one p-dimensional point, you need to compute the n by n inter-point distance matrix.\u003c/p\u003e\u003cp\u003eThus, D(i,J) will be the Euclidean distance between the i'th and j'th rows of A. Of course, D will be a symmetric matrix, with zeros on the diagonal.\u003c/p\u003e\u003cp\u003eSo you can test your code, here is an example:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003eA = [1 1\r\n     5 2\r\n     2 2\r\n     4 5]\r\n\u003c/pre\u003e\u003cpre class=\"language-matlab\"\u003eformat short g\r\nD = interDist(A)\r\nD =\r\n       0       4.1231       1.4142            5\r\n  4.1231            0            3       3.1623\r\n  1.4142            3            0       3.6056\r\n       5       3.1623       3.6056            0\r\n\u003c/pre\u003e\u003cp\u003eThus, thinking of the points [1 1] and [5 2] as the coordinates of two points in the (x,y) plane, the Euclidean distance between them in that plane is 4.1231...\u003c/p\u003e\u003cp\u003eAs you can see, the matrix is symmetric, with zeros on the main diagonal. That must always happen, since the distance between any point and itself must be zero.\u003c/p\u003e","function_template":"function D = interDist(A)\r\n  % compute the interpoint distance matrix between rows of A\r\n  D = A;\r\nend\r\n\r\n","test_suite":"%%\r\nA = eye(3);\r\ny_correct = (1-A)*sqrt(2);\r\ntol = 10*eps;\r\nassert(norm(interDist(A)-y_correct) \u003c tol)\r\n\r\n%%\r\nA = (1:4)';\r\ny_correct = [     0     1     2     3;...\r\n     1     0     1     2;...\r\n     2     1     0     1;...\r\n     3     2     1     0];\r\ntol = 10*eps;\r\nassert(norm(interDist(A)-y_correct) \u003c tol)\r\n\r\n\r\n\r\n\r\n%%\r\nA = magic(3);\r\ny_correct = [0       6.48074069840786 9.79795897113271; ...\r\n  6.48074069840786                0 6.48074069840786; ...\r\n  9.79795897113271 6.48074069840786                0];\r\ntol = 1000*eps;\r\nassert(norm(interDist(A)-y_correct) \u003c tol)\r\n\r\n%%\r\nA = reshape((1:20).^2,4,5);\r\ntol = 1e-12;\r\ny_correct = [0 49.4469412603045 102.761860629321 160.015624237135; ...\r\n   49.4469412603045 0 53.3385414123783 110.634533487515; ...\r\n   102.761860629321 53.3385414123783 0 57.3149195236284; ...\r\n   160.015624237135 110.634533487515 57.3149195236284 0];\r\nassert(norm(interDist(A)-y_correct) \u003c tol)\r\n\r\n","published":true,"deleted":false,"likes_count":1,"comments_count":0,"created_by":544,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":28,"test_suite_updated_at":"2016-10-02T16:43:44.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-02T13:56:26.000Z","updated_at":"2026-04-02T13:14:06.000Z","published_at":"2016-10-02T16:43:44.000Z","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\",\"targetMode\":\"\",\"relationshipId\":\"rId1\",\"target\":\"/matlab/document.xml\"},{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/output\",\"targetMode\":\"\",\"relationshipId\":\"rId2\",\"target\":\"/matlab/output.xml\"}],\"parts\":[{\"partUri\":\"/matlab/document.xml\",\"relationship\":[],\"contentType\":\"application/vnd.mathworks.matlab.code.document+xml\",\"content\":\"\u003c?xml version=\\\"1.0\\\" encoding=\\\"UTF-8\\\"?\u003e\\n\u003cw:document xmlns:w=\\\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\\\"\u003e\u003cw:body\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe Euclidean distance between two points in a p-dimensional space is a really common thing to compute in the field of computational geometry. In fact, it is pretty easy to do. norm(u-v) would seem to do the trick, for vectors u and v.\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\u003eBut what if you have a large number of points between which you want to compute ALL of those distances between every pair of points? In this problem, given an n by p array A, where each row of the matrix will be viewed as containing the coordinates of one p-dimensional point, you need to compute the n by n inter-point distance matrix.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThus, D(i,J) will be the Euclidean distance between the i'th and j'th rows of A. Of course, D will be a symmetric matrix, with zeros on the diagonal.\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 you can test your code, here is an 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[A = [1 1\\n     5 2\\n     2 2\\n     4 5]\\n\\nformat short g\\nD = interDist(A)\\nD =\\n       0       4.1231       1.4142            5\\n  4.1231            0            3       3.1623\\n  1.4142            3            0       3.6056\\n       5       3.1623       3.6056            0]]\u003e\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThus, thinking of the points [1 1] and [5 2] as the coordinates of two points in the (x,y) plane, the Euclidean distance between them in that plane is 4.1231...\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\u003eAs you can see, the matrix is symmetric, with zeros on the main diagonal. That must always happen, since the distance between any point and itself must be zero.\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":58817,"title":"Find the phi variation as a function of distance after solving through finite volume method. Return dphi/dx at all faces in form of array.","description":"\r\nThe question is a NPTEL online course assignment question. I have put it here becuase I wanted to create a problem set for numerical methods and computational engineering so that mechanical engineers can try it out. Interested ones can contact me so that we can create a problem group for CFD and FEM. 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data-image-state=\"image-loaded\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63.0199px; 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: 384.502px 31.5044px; text-align: left; transform-origin: 384.502px 31.51px; 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=\"\"\u003eThe question is a NPTEL online course assignment question. I have put it here becuase I wanted to create a problem set for numerical methods and computational engineering so that mechanical engineers can try it out. Interested ones can contact me so that we can create a problem group for CFD and FEM. \u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function y = oneD(n) %n is the number of grid points\r\n  \r\nend","test_suite":"%%\r\nn = 5;\r\ny_correct =  [0,47.5,38.5,23.5,2.5,0];\r\nassert(isequal(oneD(n),y_correct))\r\n%% \r\nfiletext = fileread('oneD.m');\r\nillegal = contains(filetext,'47.5'); \r\nassert(~illegal)","published":true,"deleted":false,"likes_count":0,"comments_count":1,"created_by":1809490,"edited_by":1809490,"edited_at":"2023-08-13T05:44:21.000Z","deleted_by":null,"deleted_at":null,"solvers_count":4,"test_suite_updated_at":"2023-08-13T05:44:21.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2023-08-07T17:01:20.000Z","updated_at":"2024-11-02T15:52:16.000Z","published_at":"2023-08-07T17:29:20.000Z","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:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"523\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"1200\\\"/\u003e\u003cw:attr w:name=\\\"verticalAlign\\\" w:val=\\\"baseline\\\"/\u003e\u003cw:attr w:name=\\\"altText\\\" w:val=\\\"\\\"/\u003e\u003cw:attr w:name=\\\"relationshipId\\\" w:val=\\\"rId1\\\"/\u003e\u003c/w:customXmlPr\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThe question is a NPTEL online course assignment question. I have put it here becuase I wanted to create a problem set for numerical methods and computational engineering so that mechanical engineers can try it out. Interested ones can contact me so that we can create a problem group for CFD and FEM. 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rule (but not Homer Simpson)","description":"I wonder what Homer Simpson would have thought of Simpson's rule? Somehow I doubt his thoughts would have included the phrase Newton-Cotes, or even numerical integration.\r\n\r\nIn this problem, I want you to use \u003chttps://en.wikipedia.org/wiki/Simpson%27s_rule Simpson's rule\u003e to integrate a function, provided as a list of points in a vector. The points must be equally spaced in x, so all that need be provided is the spacing between points in x. As well, I'll be nice and always give you an odd number of points, since that is important for Simpson's rule to work smoothly.\r\n\r\nAs a test case, we should know that the integral of cos(x) over the interval [0,pi/2] is 1, at least analytically that is true. Your Simpson's rule code, for only 7 points spanning that interval will do pretty well:\r\n\r\n  deltax = pi/12;\r\n  Fx = cos(linspace(0,pi/2,7));\r\n  simpsInt(Fx,deltax)\r\n  ans =\r\n            1.00002631217059\r\n\r\nThus, Fx is a vector of supplied function values, and deltax is the step size taken on the x-axis.\r\n\r\nHomer would be proud.","description_html":"\u003cp\u003eI wonder what Homer Simpson would have thought of Simpson's rule? Somehow I doubt his thoughts would have included the phrase Newton-Cotes, or even numerical integration.\u003c/p\u003e\u003cp\u003eIn this problem, I want you to use \u003ca href = \"https://en.wikipedia.org/wiki/Simpson%27s_rule\"\u003eSimpson's rule\u003c/a\u003e to integrate a function, provided as a list of points in a vector. The points must be equally spaced in x, so all that need be provided is the spacing between points in x. As well, I'll be nice and always give you an odd number of points, since that is important for Simpson's rule to work smoothly.\u003c/p\u003e\u003cp\u003eAs a test case, we should know that the integral of cos(x) over the interval [0,pi/2] is 1, at least analytically that is true. Your Simpson's rule code, for only 7 points spanning that interval will do pretty well:\u003c/p\u003e\u003cpre class=\"language-matlab\"\u003edeltax = pi/12;\r\nFx = cos(linspace(0,pi/2,7));\r\nsimpsInt(Fx,deltax)\r\nans =\r\n          1.00002631217059\r\n\u003c/pre\u003e\u003cp\u003eThus, Fx is a vector of supplied function values, and deltax is the step size taken on the x-axis.\u003c/p\u003e\u003cp\u003eHomer would be proud.\u003c/p\u003e","function_template":"function y = simpsInt(Fx,deltax)\r\n  % simple Simpson's rule integration.\r\n  y = Fx;\r\nend\r\n","test_suite":"%%\r\ndeltax = pi/12;\r\nFx = cos(linspace(0,pi/2,7));\r\ny_correct = 1.00002631217059;\r\ntol = 1e-14;\r\nassert(abs(simpsInt(Fx,deltax) - y_correct) \u003c tol)\r\n\r\n%%\r\ndeltax = 0.125;\r\nFx = exp((0:8)/8);\r\ny_correct = 1.7182841546999;\r\ntol = 1e-14;\r\nassert(abs(simpsInt(Fx,deltax) - y_correct) \u003c tol)\r\n\r\n%%\r\ndeltax = 1;\r\nFx = (0:10).^2;\r\ny_correct = 1000/3;\r\ntol = 1e-11;\r\nassert(abs(simpsInt(Fx,deltax) - y_correct) \u003c tol)\r\n\r\n%%\r\ndeltax = 1;\r\nFx = (0:10).^4;\r\ny_correct = 20001.3333333333333;\r\ntol = 1e-9;\r\nassert(abs(simpsInt(Fx,deltax) - y_correct) \u003c tol)\r\n\r\n%%\r\ndeltax = 1;\r\nFx = sin(-5:5);\r\ny_correct = 0;\r\ntol = 1e-15;\r\nassert(abs(simpsInt(Fx,deltax) - y_correct) \u003c tol)\r\n\r\n%%\r\ndeltax = 0.25;\r\nFx = sin(0:.25:100);\r\ny_correct = 0.13768413796203;\r\ntol = 1e-15;\r\nassert(abs(simpsInt(Fx,deltax) - y_correct) \u003c tol)\r\n\r\n%%\r\ndeltax = 1;\r\nFx = double((0:10) \u003e= 5);\r\ny_correct = 5.66666666666667;\r\ntol = 1e-14;\r\nabs(simpsInt(Fx,deltax) - y_correct) \u003c tol\r\n\r\n","published":true,"deleted":false,"likes_count":4,"comments_count":9,"created_by":544,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":49,"test_suite_updated_at":"2016-10-02T01:31:18.000Z","rescore_all_solutions":false,"group_id":1,"created_at":"2016-10-01T23:16:52.000Z","updated_at":"2026-04-04T10:41:35.000Z","published_at":"2016-10-01T23:16:52.000Z","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\",\"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\u003eI wonder what Homer Simpson would have thought of Simpson's rule? Somehow I doubt his thoughts would have included the phrase Newton-Cotes, or even numerical integration.\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 this problem, I want you to use\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://en.wikipedia.org/wiki/Simpson%27s_rule\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eSimpson's rule\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e to integrate a function, provided as a list of points in a vector. The points must be equally spaced in x, so all that need be provided is the spacing between points in x. As well, I'll be nice and always give you an odd number of points, since that is important for Simpson's rule to work smoothly.\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\u003eAs a test case, we should know that the integral of cos(x) over the interval [0,pi/2] is 1, at least analytically that is true. Your Simpson's rule code, for only 7 points spanning that interval will do pretty well:\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[deltax = pi/12;\\nFx = cos(linspace(0,pi/2,7));\\nsimpsInt(Fx,deltax)\\nans =\\n          1.00002631217059]]\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\u003eThus, Fx is a vector of supplied function values, and deltax is the step size taken on the x-axis.\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\u003eHomer would be proud.\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":46918,"title":"Numerical differentiation with high precision","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: 447.9px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 223.95px; transform-origin: 407px 223.95px; vertical-align: baseline; \"\u003e\u003cdiv style=\"block-size: 98.2px; 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 49.1px; text-align: left; transform-origin: 384px 49.1px; 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: 264.658px 8px; transform-origin: 264.658px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eA basic approach for numerical differentiation is by calculating the difference quotient \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-15px\"\u003e\u003cimg src=\"data:image/png;base64,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\" alt=\"f'(x) = (f(x+h) - f(x-h)) / (2h)\" style=\"width: 178px; height: 35px;\" width=\"178\" height=\"35\"\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 27.2167px 8px; transform-origin: 27.2167px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, see for example \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://www.mathworks.com/matlabcentral/cody/problems/2892\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eProblem 2892\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 233.242px 8px; transform-origin: 233.242px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. Unfortunately, this approach leads to the problem that for small step sizes \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: 3.89167px 8px; transform-origin: 3.89167px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-style: italic; \"\u003eh\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: 43.5583px 8px; transform-origin: 43.5583px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e a subtractive cancellation error occurs, while for large step sizes the truncation error of the numerical scheme dominates. The same problem occurs also for similar numerical schemes of higher order.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 238.7px; 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 119.35px; text-align: left; transform-origin: 384px 119.35px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cimg class=\"imageNode\" style=\"vertical-align: baseline;width: 273px;height: 233px\" 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\" data-image-state=\"image-loaded\" width=\"273\" height=\"233\"\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 17.7667px 8px; transform-origin: 17.7667px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eTask:\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: 355.55px 8px; transform-origin: 355.55px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e Can you find a numerical approach that eliminates the subtractive cancellation error and enables accuracies up to machine accuracy for small step sizes? Inputs to your function are a function handle \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: 11.55px 8px; transform-origin: 11.55px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003efun\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: 108.9px 8px; transform-origin: 108.9px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e to a scalar function, as well as the point \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: 7.7px 8px; transform-origin: 7.7px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003ex0\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: 173.108px 8px; transform-origin: 173.108px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, at which the numerical derivative should be calculated.\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: 15.9417px 8px; transform-origin: 15.9417px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-weight: 700; \"\u003eHint:\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: 121.733px 8px; transform-origin: 121.733px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e If you do not have any idea, check out \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"https://blogs.mathworks.com/cleve/\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003eCleve's Corner\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 178.15px 8px; transform-origin: 178.15px 8px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. Back in the year 2013, you will find an interesting article.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function Df = numerical_diff(fun,x0)\r\n  % this basic approach will not be good enough.. :-(\r\n  % h  = 1e-5;\r\n  % Df = (fun(x0+h) - fun(x0-h)) / (2*h);\r\nend","test_suite":"%%\r\nfun = @sin;\r\nfor k = 1:5\r\n  x = randn;\r\n  assert(abs(numerical_diff(fun,x) - cos(x)) \u003c 1e-12)\r\nend\r\n%%\r\nfun = @(x)x^(9/2);\r\nfor k = 1:5\r\n  x = abs(randn);\r\n  assert(abs(numerical_diff(fun,x) - (9/2)*x^(7/2)) \u003c 1e-12);\r\nend\r\n%%\r\nfun = @(x)exp(x)/(cos(x)^3+sin(x)^3);\r\nx  = [ 0 pi/4 pi/2 pi ];\r\nDf = [ 1 exp(pi/4)*sqrt(2) exp(pi/2) -exp(pi)];\r\nfor k = 1:4\r\n  assert(abs(numerical_diff(fun,x(k)) - Df(k)) \u003c 1e-12);\r\nend\r\n%%\r\nfun = @(x)exp(x)/sqrt(cos(x)^3+sin(x)^3);\r\nx  = [ -pi/8 0 pi/8 pi/4 pi/2 ];\r\nDf = [ 0.042678767134941 1 2.15903261751524 exp(pi/4)*2^(1/4) exp(pi/2) -exp(pi)];\r\nfor k = 1:5\r\n  assert(abs(numerical_diff(fun,x(k)) - Df(k)) \u003c 1e-12)\r\nend\r\n%%\r\nstr = fileread('numerical_diff.m'); % sorry, no regexp hacks :-)\r\nassert(isempty(regexp(str,'regexp')));","published":true,"deleted":false,"likes_count":2,"comments_count":2,"created_by":11486,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":10,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-10-18T17:51:29.000Z","updated_at":"2020-10-18T17:56:54.000Z","published_at":"2020-10-18T17:56:16.000Z","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\u003eA basic approach for numerical differentiation is by calculating the difference quotient \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"f'(x) = (f(x+h) - f(x-h)) / (2h)\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ef^\\\\prime(x) \\\\approx \\\\frac{f(x+h) - f(x-h)}{2h}\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e, see for example \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://www.mathworks.com/matlabcentral/cody/problems/2892\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eProblem 2892\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. Unfortunately, this approach leads to the problem that for small step sizes \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:i/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eh\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e a subtractive cancellation error occurs, while for large step sizes the truncation error of the numerical scheme dominates. The same problem occurs also for similar numerical schemes of higher order.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:customXml w:element=\\\"image\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"height\\\" w:val=\\\"233\\\"/\u003e\u003cw:attr w:name=\\\"width\\\" w:val=\\\"273\\\"/\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:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eTask:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e Can you find a numerical approach that eliminates the subtractive cancellation error and enables accuracies up to machine accuracy for small step sizes? Inputs to your function are a function handle \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\u003efun\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e to a scalar function, as well as the point \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\u003ex0\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, at which the numerical derivative should be calculated.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:b/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eHint:\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e If you do not have any idea, check out \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"https://blogs.mathworks.com/cleve/\\\"\u003e\u003cw:r\u003e\u003cw:t\u003eCleve's Corner\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. Back in the year 2013, you will find an interesting 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IimcNDXphbgulDYN+KKnMSdvqrirFrlWtALDxg580SCb/3iEcEfLgm52iZwILxgVokP9ekbcS8h8JNZTfjvJMdVDv3Z357qaLdjh4eHs2rWLrVu3VsgYGFla0n/ZMhrOn8+FMWM48NVXZKWlyZtTIpHks6R1scxI5E5qYc5mXZr2dOJrU4FnYBzxj35jSt9+dWgeEcKma5lY2+iTnlHQxFZgaKSLTj6xXn3roXehk7k+lqYGmi3YO3fuBGD16tUV5hbRMTCg+zff0H77dsIWLWLflCnSry2RSPKpnDFN7ZPYczWl0MgPhVEtJgyvidnV67kLkHlWdhN+aqdgwZ/HeP+cHj3tdJ76rXaN2rxZW/lIrDuZ6wPwZttaL+ZUynNj6/O5Jfbu3VuhY9Ji6FB6enmReOkSu4YOJfziRXmjSiQSQI8WrSw4fjiYW+rCZdDSuRmLHNUs2HGTaxm5sq4wpvOYPoTM6MJvY5rgoPd0BZF0w2r8s8eH1bdU/Na7EacSHrpDWjew1mzBvnjxIufPn3/0b3d39wofFvuOHRnk7o5+zZrsb91aWtoSieShtezYgCncZaXfg8LjqxVm9BnakDeig5h/QsXjgD4l1axNsNB9Wqzzu0G8PnLF40ok7Ux0AWhSz0qzBdvLy4vly5c/+ndERAThlSCY5rVrM/Sff+h88CDmtWvLe1UieWUQpMfe55DnTfZeiCIyI580K6sx5A0rvLb4F5lSrlPLgZk9jdiz9yLu94tPO795N+6RWAPsikymoaUBg2yNX4j/GsqpWl9aWhpTpkxh2bJlGBoaPjyZmzc5dOgQkyZNkveRRCJ5waiJ9DvPqLVhHM9VNGOT6iwd48LoJsYPK+uJBxz78zjDY+viObkFzQyftppFShgL5p3lQPvOnBhkTXHVr1VJaViaGjB43v5Hor28ZwMmDWmjuYKtUqkwMDDAwMAAheLhRRBCEB4eTm1p5UokkhdMVuhlRvx8G7VTLQbU1OLerQj+fSeDZIUR8yd04+tmhigAkRrF2pU+/EQDdkxohtNToi1Ijoon3tSCOgYlq3qtSkpj3LLjvOVaj7fdr+L1kSsdW9TRXMF+YoP5BPv533CSUZ07zb0EM2xfc8bKXKfMm0oID2fX0KF0WrIE+44d5R0ukbw0pHPmb092NnqNea+Z5dapziTs0lW+XXeb9VizfbobQ2s8/EQdG8zcpRf4x6IhG8c2o61F+VS2TsvI4ubdOOxszF6YS0RzU9OFitBf3mV7+z749G2Pe9u3OXYsnOwybk7H0BCzli1lko1E8tKQQ3xAMGcTk7gWYsbg1mb5mgroUqdla/4zsSEDM6OZuSfsUZEnpZU933/diVk6ofT+1Zv/3Xictv4sMf7g30fwvhxW5HcM9HRo5WDzwsRaswU79jQX55zDcNFpRj0Ip+98ByKHf8ixo2UTbZlkI5G8bDzg+KFIEnKyUKlSiU15OrHFuFFzfn3DgqiLQRyOeqwcCsMa/Gtidw531mbzqkMM/uMSx0LTChXugkkxlYmGF39KJxslOsa1sBv5Dd1/NCVk0iqCVGWzs2WSjUTyMnlCErmYbEx9YwWIZG5EFVZdT4cGXZrwuX4Sx4NSn/xIaUybXh3ZNrMjU2oms+4PD9rPPcZ3u66y/eRN9t14wIMCoXsvyjdddQVbrSYHwMoZhw8cSZ8zBy+fWMAY23en4/LDSOpaaIOII2z/GRLVpfeVyyQbieQlIDmVuwZ6mOiY0txBzd+X4sgo7Hv61gxw1eNI2INCLGgF+lY16N2/I+vmvsGRj1oytLEl9WqYUt1Ii8+eIdbuJ2+gSqrYt3TNEuzky5z7aA7Xo9WgqInjrJ9p6HKZ2+OWEqjKBuPWtBrRDD1FOqodczncfzSH/7lVJhdJwSQbWfFPIqmCxKcRn2NAEwcTlEqtIhrj6lC/nhmZUSmPa4UUihJz62q0dKxJ0/pW/LHdp0ix9r4cxrAtl7keEgvAeo8rL6ykquYKdlY8iVf+4dJ6v4eVtSxccf32X2jd2MOt87G5X8om3XclHmPWwHvf0WlEo2JjJSGTtNgkCnq48pJsrMePJzkqSt78EklVIymJsGQt6ri2Y1vPouKmHxZpMjPQQa8Em0wrgRtk0e4rDLI1fvTZmD3XCbwX/4oJtkVH2i8eh5gzkQO/+5CYnkFGwgPAEF1DHUCQHXGAo/+aRYrLdNx+HE4N/bxYyQySI1WFWNuCrMCteHR6h2Oe959KS9UxMGDwH3/QYuhQefNLJFUJU2MctFV4XE8BQ1PqmT1bziwt9TEqwWa/W+/zTLH2vhzGrshkvhzYHIDA0DjgxdUP0VzBRolJ588ZsHMoqV90YLOBEVuGrUVr7FRat7eA5Av4TJzMvajBNFs2GQdbvXyivI3D3Yewf/vtJ0U73ptTE74mhqbYNrRAIW9zieTlQNcSVycFq4ss6sSjt/KIe2m41jMtwds4TBnU6pkLjAWt66t3HrZGeFH1QzRYsAH0MOvxDW8GXqDzlk208/Bk2H9HYKW8T+D8L7i2ux52//xIu2Zmj23omJOcnPA1MdmtqetS+/GgZN3C//Mp3D7fnqabvsGppl6JjyIhPFz6tSUSjcaAtu2sqR15i9kHoymyHa5axZGzCtzs9Uu01drWpkWKdUHrGuBMYPQLrR+i4YL98LB0bFvjOGIkrfq0xkxfi5zruzj70yX05/9I1951nhDli9M/I/h8Cxqu+5YWdrmDIlSELv0S37Va2KxbiGtL81Idgc+yZTLJRiLRaBSYOjVhvqM2mw+c5euj0SQ/9Z10Ag5dYXODhnS3eH65K2hdAyy6eJ+eTjUqyAdRVYZG3whdY0u061RDJ8+vIWK5s2gavmuh+qYldHG1ejRIqh0/cOTLCxgt2krvIfVL9CqUn55z5nDK3JwLY8YQc/UqPefMQcfAQM4RiUSTUFow8O0WzF56gR/cPfG+ZMf07nY0t9VDHRvHmdOB/HjDhP98a4NhIT/PSydv5WBT7K7yrOu86nxQsf5r0PRaIk+QQeKxpXhM2IPuBx/j5GZL2vE/8Jt5Cr3v1jPwu66YKACyybi0ip1un5CYDNAIw9Fv4/DB+7TuaPdY7EvIZXd3zgwbhvX48XT97jtZslUi0UDUsXf4+Td/ZhYsi6pXjTWTOjLWXv+p9av80SBxC94o1qWRV5Fv57f9Hv3N/eQNhm25XKLfv2KCDZBDVuRFAg8cI8R9Jff2RaF8byX9f3snN1pEkB2xD48eb3PPZAod/55MXfMUYnb8xPEJflhs2szAkY1KbW0He3tzato0AHr8/ju1W7WSM0Qi0TBERhIXzgaxOyCOkBQtbO1r83Y3e1oWUtwprQwZjO4nb2Bva/6ENf7VH54ERiU/IeJSsJ8iicg/P+XA3/a4bfjycbRI8iV8xo/gyr5WNPX6Hbc8v7W4g/+oXpy/NoG+Zz/HTq/0sSIJ4eEcnDSJxF276HzwII69e8sZIpFUiPmcwNmbWrRxMi0XH25aOaabr9jhR01LI4Z2cZSC/ezHaTJJUWBqY5w7qGHc+HY0ngszqLVnE30H2OWzpFUEzR7A0RUd6Hx7IY6WeZ+oyUoHHf2S3QZZaWnsmzKF6NWreTMsTLpHJJIXThZBB0/gsleb1bO7MLS69nNtLU3DaoOUFq0qO44K48diLRKJXD+X0wtPwMipdOhv96TbIzWI8CM3wKUpluaC5JBwMkQ2GVf/YpfLFPyDU0u0y7wkm37+/lKsJZIXTbaa9KxETvok4ujmSN9XXKyhCkWJPFu89TFs6ITFwK4kqhJIVwserS6KBMLXLCLQxx7bPb2onnCSg69/SfKotzA6toJ4p9nYWOuVanfShy2RvGBEMp5/n2Ke2ph68Uo6NTQvNMrjVRLrqm1hP4EeZp2nMmTH7zQzWsGxWf8QFBBI1KUT+H//PgennMFw9gI6962NwrIrXde+Reqs6YSd70CzWW9ha6z93EeQolLJSSaRlKMR1qiZOWr/SP5Qq7kZm87zOFnTMtRcup9carH+4N9HKqSo0ysm2Hln05CWC2dicuwLjjZrzK5W3Tj/wzWM562kz5fdMVMqQH2PoM07STfugGmnAK5OXkxAcNJzi/W2vn1lko1EUo4v/7ZtXNgwtg7dFDkcPRfC5dSyS7alqQEn5/QvlVh7Xw5j9S0VRvo6hVrseTHYUrDL/lhGx2EkAw6dorfHTtrvOUbf4NOMmNkPK2Pth77uNTM5/W+o9c8/jHDfQ6dOvpxdfJLE53h86xoYUGfwYNnJRiJ5QaLtEnWbESuvEvAcom2gV7qesIVlNeZx4EwQjRcerfB62FU3SqTUZJB4cB47+65DZ9FWhn7+Gg9Dt1NJS1JiYJpM2LbTKF9/vcwuEplkI5GUHZGRxAW/u3gFqgjBiOYOtXi9jQ22etlE+p1n1Nowwu2bFNHtvHzxvhyG2yqfIl0oFR1//ZJa2EXeCmQFbuPY5P+QPeHf9P20HY+qsioMMTDLQbXjBw6/OZsz+4LL3OhXdrKRSMo4Q1OjWPufo7TdGMTh2AxiQ8OZuuEUDvPOcDSWR5Z27eDrDCnG0s5rmLve40qZj+dZ1jVUbP2QV0+wc25zafq3xGh/gtv8QVgq8z+ds8m49CeHxyxFbVEd4bWMwz/+zhW/e2SV4SWhYCebG4cOydkokTyTdC7sOc/UeBuOfD+AvV/05n+z+xM40YHhKWEMXnoBnyStXNGui1s1Iyx1FUWKdV40SIOa5mU6msIq8uWnouuHvHqCnRxG7NkQcKiPuanWE5Z3dsQBjrw1ncTkRhi92Q5LO3MyjyzG5+1lBMWqy7S7/J1sPPv0kYuREsmzyFJx3DedHm6N6W6VF2msg22zFvw6pg5NVGEsP5+IQIltm9f4c4w9tspni/XzhO4VZ11XZP3rgihfiRvCtCOufy8k8cMv2NP7DHWnfUHXNxxQJl/m3GefcS/7LZqfn0e7tjUeJtxM+5yEGCXmFonE3srEpL4NesrS+czykmy8W7bEskEDOSklkvzkTzdPSyM8XQsbE50CBZq0sGjeiAnV7/FFoIr4HhZYPsMNUh5iXVhFvoJUZP3rV9PCRg+z7l8w9NQR2r/bHtvGNVGqw7gx71Ou7GuI/eq5tM8TawClOea2SlS757LboSbrO3yCz6nQMrlIOk6ahH3HjnKCSiSPTWqCjp7n9ZW+7I7JBmMTHE2z2XLmHhEF55iWEqNidLE8k2KKs66h8vzXr5BgPzxVHVtnnMaNw6lRdm4qeyLVl/5Ep042hbQO08O83xxGBPvTaSwE9hvKgR13yrwgKZFIKDzdXMuCXp3NIeg6M/dHEp9vkqnvR+IRrsXgplZYvGCxBvhzSjd+Hv1akZ9Xpv/61XGJFEShj2HD5tj8+CYdRzen8OJ9CrT0zTCp3wrHiYux1BvPzpnrCek5iwamz/ecC794kfuXL9N29Gg5gSWvDkWmm+vQoEdbVgeeZNh+bwKu1+Kj1hYYp8ez/9Q9fOo7sre9aaH9WJds8yvXdHNLU4Nnujoq03/96go2eph1nky/zgX+rL5H0G9LuOwbj65DFxqNGEBDB0u00EXP3AzFjUhSUnLgOQX7/uXLspON5JU0lBo1M0e9Now/hBaDYtMRGD4UYqUFQyf2wOfQReYdDmP8nTBQ6PFep5bsfaMhDkWURB7dqyldmteqsNogQ7s4Ete6bqX4r+GVSpwpjkxUmyey/a3rWP38LjUenOXWknPof7aArh/V5NbEkVwL/pDeZ2dQrxyC9mWSjeSV4tEioyExuUkw52s0xOvz1rQsOJ+yM4mNz0RpaoS5rkJeu3xoyUuQRzLxAdcR9QbQespEOvywlneurcIu6hd213qNa7ttqbVgFHXKKcNKJtlIXh3yLzIqik8319bFysq4wsS6otPLpWCXCyZYtWuPMmQb/hv8SVUr0KnjjH1HJ7Spg/GiJfTob4c2gpyEQII2r+Lk4sWcXLaOgEvRZVqMlEk2kpeeQmtaK0uVuZhHWkbWC6mcN27ZcX7ccEYKdtVCB7P+3zPQ4x2yf+rJP70/xGPKKPaO3gCP0tmzyQhYz652bTj61hxCTlwgesd8vFv1Zfefl8kogxeoYJKN94oVsniU5OVAJOP592EGrr/OmadqWitLnW4+5beT9FnnS3h0UrkdYl7cdZfmtaRgVzkUplj1+YLhl6/S610dIpbvJqfbbLr9OAhLJWQHb2P/kEnE1p7Ca1ev8K+9GxlxzJehewaSOnUch/aFFajZqyYrvfhsybwkG6flywmYPJn4sDA5FpKXYD4VV9NaWep0c6+PXKltbVpuh1iSuOs82s3YifflSp6bopwBxAvYbMWTdkdc/3G+8A9Kyf1DrLg9y02sshgrzt9OKfDlByLit5Hi9w7LRHhGpnhwJ0yk56hF+pU/xNZmE8WFoJQS7zY5Lk5IJC8PWSLC97To9slmYfyDn7iYklOqX6emZ4rxSw4LPt4svC6FluuReV0KLfF2b96NfSHHUFqU0gwoAv16OH79TT5fXDiRey+i9cEcmjUo2KzIGJtBH9OmsT02yZ4cLrYFWTY5ai20Ckl3N7K0lNdeUoV91hmEhcYTnaGNtV016hjmWtHAqLW3GbFSp8TlUV90W6/SWNeVHX/9+J1EUsJXETXZSckoqpuhW9jbn21nnG0BbOm69i22uE5HZTyS5mcKtiBT88BzEft/1ab1b1NxsC2+n2R0YCDWDg5yDCSaPUVSo/h7zVk+vpFOMoCuMdMHODO9q00+0b7OkJUUK9ovWqxLUjMkP5VZP0T6sMuCtg1WvZqR43WJmGcVFSmuBZlIINbLmyTPK8TFpRe724TwcHY2biw72Ug0nGSObzzDx9FWbPyiP2m/9idgsAnH3L355EgcWaVYZKyIhrmlsa6hcuuHSMEuC4qaOH75LVbX5nL4yzUEBqrIecrEKEELMoUV9b/eyNCzv9CumVmxuzWvXZv227cTtmgR+6ZMISE8XI6FRPNIieXgFTXDezoxoL4RetnJnPFTYdyuNb/0qIZO7gt9yRYZy9Ywt7TWdVH1rgtS2fVDntQYuehYCtQiPWCLONDfUazCWKzuNlfcjM7K/SxdJHh8K/6ijtiw6IxIy1tbyUkRqQkZQuTEitB9PiIhK6dMew7y8hJ/ubiIv1xcRJi/v1zLkmgWqkDx0SfuYuqZByIn5b5Y88tO0e2vIBGROz3UwdfEXI974tF0qUS2n7guBs3dV6rv8/FmEZeYWunHLlPTy4I6nthLF4lKrYdDp/roIMgK3MjeAZOJ77GawcuHFOhqk47KfQY7hx3Fao8HAweULeYzITycg5MmkbhrF50PHsSxd29p2Uk0g5xY/vzhBN9a1ObL7Cj2VGvOhlF5jQayCT16HKdj1Tg7tzVNq9h7fWX1b5QukfJCaYFVm244dar/8FWvmBZk6b4r8RizBibMwa1vTUBNckh4qRNtZJKNRGPRsuD13tUxDgxldmp9Vo563BVGHRvCfw8n0qNDbRpVQcXRFP/1Q6eS5PnJa0HmUngLsqP/mkWK61z6LMwV85zbBHw0mrCRqxk4rkWhUSdFkb+TTcDkySSFhvL6zz/LMZBUMtrYurZh9a2T9D8XyEe/ZTCuhQmG6YnsPR6Gt7Uje3ta5fqy8/urHy4wtqxrwaQhbTTyzA6OaUs9GzONOBbpEikXMkg8thSPD38i2W54vhZkfniNGs6166/j4rGY1vYP47dF4J/80/hHdDcdZtjI+pS1xE2wtze6RkbUbtVK6oVEQ0gn8PQVlhwIZaUqG3QNmdC+MdPeaIhDgTC+iogGedmQgl1u5JAVeZHAAxfB7U2c7OO58e1oPP9jRMNDf9Hd1erRDR3952h2TjXBJeA3WtvpyrtQ8lKiTstEbaCLfiGfVbRYB4bGEZOQWuUfCtIlUm7ktSBzfhje9/s3nFqYSPX1/6GTa77sqJwQ7mz2QjFiBfZ1dJ9wn+SkZ4K+nlxYkLwUKA10CxWYyrCsv1p/FqDKC7bUhhfy3qKPYZN21FrwKz3fbfqE307cPk3QoWrUGPoaZnlviOn3CN0yh60terP3f2Wr+pffTSKTbCTlayon4bn9CO0mbaPtwjPsDC1YxKnkVIZYlzbuWgr2K0duC7IZXTF5wm2XToyXB8kWPWjQrgaIVBLPbsBjeE88Rm5GDBmLk1tddJ6jbntmSopMspGUI2n4bvei//FkrOsaQFgoQ/7tzdrg0ot2ZfmsS5vVmN+NUunV+aRgVyJ57pCR3bBNP8PZaYPZ0n4CEcajae97hGE/vUeD+mbPNSiOvXvLTjaS8iFbTXp8BH+fVrL4s77s+bIfJ75uzSyjeN5fUXrRXrP/coWL9fNY16sPBrBo9xWNGhLpw65ARPglwk6no2uynv1O7qQ1GY/jgWW07dkYA6UgK9KPK7v2Eno2hOwaztQfMRRH51qltrjtO3bE0t2dg5Mmsb91a5lkIymTG+ToBm8WxmiRYWHDx/X0UQDGtRoxe6o2iqUXeH+FN0zqyFh7/RJFOr3frwVuTrVo5WBTYadRVusaHsZfL+/ZQFrYr6hck4MJJi7GZBx8gMW/jzPk2Eo69XXEQJlJoucydnXpis/ik2RY18UgYS/n2r7B3i23ytR+TCbZSJ7PlNPFprouIXcS8YyN5mzk40YcSit7Zk11ZnYpLW0DPZ0KFevnsa41qn5IPmRYX0WLdvwdolNqYFPb6NHfsoM2ssPlXVTxXbHzWE+vPnXQJh3V5k/ZPs2SLjfm4WBa9mer94oVBEyejPX48fRftgwdAwM5FJISkE7Afm+G7Isj1q4xnpNb0CxfLLU6Npi5Sy9yyrEt20fZYaFhRz943n6AMqWUu5+8wbAtl4lb8Eall1SVFnblPR/RsrDPJ9YAKkLWrUTl+DXOG1yJe/t9PDZfJUPoY9m5N9UirxEXnv5ce+04adIjv3ZKXJwcBkkJ0cepX0d29K+GVehNhhYoiaq0smfWF73ZOvJpsU7LyML95I1KO/LnjQzRlPrXT734yJuykskOJ3JvEAYf/obzO41o7LCeI++8zc6gRXR57RqJtk1pVlv/uXdj37EjNTw8ZEcbSeHvfhlJXPC7i1egihCMaO5Qi9fb2GCrlyvaeDNk39PNB5RmxlQrRKzzokFu1q+Og121Cj+fujZmLO/ZoMyLm5rov5YWtkbMFDXZSXoYWBijhR4mbccz8OS/qX52Grt7/or2Z0OoZ1o+wyTFWlLoLZgaxdr/HKXtxiAOx2YQGxrO1A2ncJh3hqOx6icsbYJK13ygMsQaoLa1aZlrk2iq/1pa2JqAtg1WvYwJ9DiHalhdLJUKtG170H3DDqqvOovJOGdeZPJ6sLc3dZydpV/7ZUedRmSKDrZmBad8Ohf2nGdqvA1Hvnehh5USyCLyagDf/BnI4KXaHPqyLa6meZb2aWbGFN584GWpDaIp/Rulha2J5HWy8Z7L4blbCQ1NetjJxtiR5p+PoZ6F9gvbdYpKxRE3N5lk89KLdRJHNxzDafH5XIs5H1kqjvum08OtMd2t8sRcB9tmLfh1TB2aqMJYfj4xNwpEH6d+Xdn27uPSqS+bWAMkp2VppP9aCrZmKDba9sPpt3M2Zn7f4VHXjDXdF3EnPvuF79nI0lIm2bxC1LAwxsawgAGQlkZ4uhY2JjoFYqm1sGjeiAnVBR6BKuLz/V2p/fKKNcDovs01olmBdIlorl8EvaYj6LuzD/GBN1Bl1cGuWMtakJNwizsHjxMe9gB0q2PV5XUcW1pTGptcJtm8AihN6TGqJz5ZupgbKIAc1Nm5wmtsgqNpNt+cucdsV0dq5ldtLSVGxRiZmiTW3pfD2HX2DjNGumikdSwt7JdwYlk0bUeDlrbFiG42GQHr2dWuDUffmkPIiQtE75iPd6u+7P7zsuxkIynk3tLLFet0AvafYPjfwUSqAS0LenU2h6DrzNwfSf4XO/X9SDzCtRjc1KrYGGtNsKwX7b5CYFTySyvW0sJlVk0lAAAgAElEQVSukgiyg7exf8gkYmtP4bUdn9HcqRpaIonYfb9y8O1xHLLewYABdUrVGKFgJ5uYS5dkks1LfA9dO3eBUcCGUfY06NGW1YEnGbbfm4DrtfiotQXG6fHsP3UPn/qO7G1vWuS9ZKCnwx+f9qz0M8qLu/b6yPWlHjmZ6VjliCNo9mCOrmiE8/kVtG1gmO+zZCJXjmfv/zrS7/gkaumWrexfsLc3R9zcMBs0iJE7d8pLXlVlOTuHHG2t3Le1LBKStTA31uZxBmM8tds5P2yWywPOHLrIvMOR7MsEFHq816kpXxfSKUYTeZ6sxoIuHgM9HSnYknIi+xJeLm7c6LWLdxd2f6qbh4j0xP+GPS07GRB/JxOT+jboKUs/4aIDA9E1NMS8dm15zauiWKdGsXblJe52ac+sNrrc3O/N8LPmbPramZb6isJFWwlkZxIbn4nS1AjzIkL38ixrTcH7chhuq3ye2y0TGBpH44VH8Z/auUJrnpQG6cOucjNRTXZSMorqZoXGZytsO+PczYrE3XPZ7VCT9R0+wedUKFmlfH5aOzhIsa7ypPDDWk8+++MkQ/an8+bARjjp54lwXjKMBeHnLjBqQ65PW1sXKyvjIsV6ym8nmfLbSY06y+epyJefvPhrOw1puCsF+2VA2warXs3I8bpETJEqrId5vzmMCPan01gI7DeUAzvuUB6BgnIxsmqgMKzB2I/aMt8kjeUXk7Dq1JrpbUwLLFoVIdpFuAryokHe695Yo6zr8uomo6n1Q6RgV+mZmJtoc20uh79cQ2Cg6mGizZNfQkvfDJP6rXCcuJjXlzpwf+Z6QpJynmvXl93dZZJNlSGLO2du8dcDXfpba+Nzyp+Ffkk8rcd5om2JKcWLtabFWZeXdQ0P64f0dKqh0aMqBbvqKXZuos3PWN3+hRON67K2+zwCI0IIWv4FO8a8z7756/MJuS565mYobkSSkvJ8gm1co4ZMsqky6GDXzJ7vx3Vjx5cdWWOfyQ9rTzE3v2hnJHLpTirqKprBWJ7WtSbXD5GCXfX9IrmJNqcZ6rub9nOGY3ZqLsemnIZmbbDIOIpPm45s/W4nUREXuLLOA9GsLqZmz5fmbt+xI4Pc3dGvWZP9rVtz49AhORQaZlVH3rmP3y0VsZkCZY16vONsio5hDcZO6FBAtAWpdwKZ+O8LeKYIqmIGY8cWdcrtuDS5fsgT5pqMEnkZUBE0ewBH/zeA3je+pp6eICvMC9/5M7m6yguBK7X2bKLvALuHIV4ilpB/TqM3sD+2xqUX8ay0NPZNmUL06tU4LV9Ou/ffl/HalYxIjeLvNWf5+EY6yYCxSXX++6Er7+Zr3/UwcuQ07wcr+ai9JdyMIriVKzuH2WJYhdwgL4Kv/vAkMCpZY1PSpYX9UmGCVbv2KEO24b/Bn1S1Ap06zth3dEKbOhgvWkKP/rliTTqqHfM4Nup7zuwLLtNCZF6SjdPy5QRMnsy+KVPkYmRloo5nxxof5mbUZOtEN3xGO/C+ThyjC7TvUuRa2usbCzb43OOYRSOWvG7zlFhD5TTMrUyqgv9aWtgvlYmVROyh3zkx+UcSaw+jVrNo7i0/hmLCOgYvH4KlUgFkk+67HPdu00hOBrBFb8RoHMaPx7lXQ/TKkB+Rl2Sj5+LCIHd3GQpY8QNP0iUfXludxvczuzDSRvn4b7+Hc0OvGmueapSrJjYyBaqZYlVEclVaRhY378ZpbDxyeZIXf10VHk7Swn5ZUJhi1ecLhl++Sq93dYhYvpucbrPp9uOgXLEWZEcc4Oi/ZpFsO5amHv4MvedJ5x5xXO/zFgfLGPZn37Ejg2/eRL9mTXQMDeU4VDjZJCRkoNeiAa/bPFwxFPF3+XVbDO27NeTbQhvlKrGyNStSrKHiG+aWBlVS+b7N1alhiv/Uzhrvv5YW9stKegg3lmwkfeSntLLPFdFkP7xGDefaKTeae67AtVluckDODc6+3p1LqbN548QEbLXl5asynpC0TNQGuuiTRVyiwNJMF4V4wMFVx5ml05x94+pjHuJP/8W3OKxnxabPOzGylk6VPue8rMaw7/pS29r0lRtzaWG/jOjXw/Hrbx6LtTqMG/O+4Nruetj98yPtmj3O5BKxt4m+EomijgV68m6oGk6Q1Fj2bj5Chy8P8PXpRNToUM1MFwWQeTuQHwKMmTHQjuoKQVZKBpHGpnzqZk/nGjpFuj9W7PB7lHauyeTFXb+KYi0F+5WY3YlErvmGUwtDMFu2mG696zwu3Zp1i4szZhP5YBAOn/XCspxr/Fx2d5dJNuUu1lGsXXmKt/3hzRHOTGxqlK8Ubw5xEQmc1jakppkW6VHBLNwcSfPuLvw8tN5TMdZ5Yj3lt5NMPhLEzbtxGm9dl1fcdVVFlld92VHoY9ikLdVnvEW3ic6PFxZFLHcWTcN3LVTftAi3tpaUV1MEgITwcPx/+gl/oMfvv1O7VSs5Fs/Nw/6L79+rxp4ZHRhQveD0VWBibUo39R1cp4UC0KhBMzx6VEOHosU6LxpE0xcYyzOrscpOZ+nDfjUnvsp9BjuHuaP33XoGftcVE0U2GQF/s3/IJGJumaDXvyuGKb7EnzCm+pq/6De2RamjSBLCwzk4aRKJu3bJTjblQfZ9ln3txebX3Dg+zKaI5sxqIq/e5M9T94m1tGNiEeVRq1qcdXlV5CvIeo8rNKhpXmUeAtIl8urNetJ9V+IxZg28t4CeM7pgoijQFOHqFf61dyMjjvkydM9AUqeO49C+MEr7CJadbMqbHDKzwFhfWeirsYgKZIF7BDg6MXNiD5aMbPRSiPWLtK7H7LmOf1B0lbkDpGC/aogEon38SHeZjtuPw6mhrwBUhPy1gpjYEbT+YyYtnao9vDEUplgN+ILuixpyf8FOIjJL/9Ykk2zKc7YaUMdGwaEzd7nyVB+4bMKuhvKjz30injFMVVGsX5TvuqrUD5GC/SqjqIbdpN8YvvFTHGz1cud6OJF7L6L1wbs0a1AwltoYm0Ef02beEGx0y74q2XHSJHp6eRG9ejUbu3SRi5FlGjszevW0wVF1h2mbggnNJ9rqmGCW7E+kR9f6tNB5ecT6RVrXVaV+SH7kouMrOfGNMc2/vlSSpgi2z7/bvCSbA+++y4k5cxj8xx9yLIpCnYTnrnN8cTyBnDq1+fbtVgyy08eyTWv+vJFA79N+dL8dwtj2NtipEzjiE4lPrcbs6GZFcZHWVUms85JkXkRkSFWof/3UXJSLjhLEPQI+7svpyGkM3DqWGjoFLekcsiL9ubFrL6FnQ8iu4Uz9EUNxdK6FTqFGdyZpsenoWZkW+gqXolKRlZoq09iLdlzgu/k43U5l0qWuDvfvpuCnmz/FPIPgs1dZtDeElaps0DVkQvvGTKsi/Rc1Rvw+2cLyng2YNKSNFGwp2FVKsckO3sLuvjNI6TeTdh8PpaGDZa7YZpDo+RuHx89CleOC1bDOmCT6ELoqBstNmxk4slGBkD9BVuBG9g7agtmfa+juaiUvb2nIVpOedJcZ3wfRZGpnPrTXI+XebX5eeYm5KRZP1QV5nO0oKQ1VqX5IfqQPW0KRTRFi1GQHbePw4GmobrXF7j/rGLTwe3qt3MWQTe2InbaWoAJdbETMSU5O+JoYkxbUrGdSqqNIUaleeTfI0b8PM3DNbfwtatCtnj4KFBjXasTsqc7MLqQuiPIZYp2WkVUlshcrg6rov5aCLclHwaYIo6hfPZGQdStROX6N8wZX4t5+H4/NV8kQ+lh27k21yGvEhac/3kTWLS5O/4zgi11o/ucXONrq5bpHkiiu143v+vVs69v31e5ko9TFprouIXcS8YyN5my+BotKK3tmFSHaRYm1JjbM1RSqov9aCrakENGwwKpNN5w61UcnO5zIvUEYjH4H53e+Y+ChEWTOepudCzy4f+0aibZNqVY71757lDmpT63183PrlQiyArfi0elfnPCJfeZuG3bvLjvZPOqvWI1GIp6pfwdwNVUUItqJ/O0TTUIxYq1pDXNLg/vJG+VelS8/dlZGjO5kX/UujChnAPECNiupDLJ8xYkG9cTWTXdy/5Aj1BFHxNGBjmIVFmLdonMiQwghRJqI2z5VrKGe2LTMV6Tn5H47+rg43K2OWOXyrbgekV7s7jJTU8WO8ePFKhBey5eLzNTUV+RCp4mrh/zEhqA0kZP3731HRKOPN4tGv1wWV1NynhyWhAciNqvwLaWmZ4rxSw4LPt4svC6FVsmr4XUptEof/4tEWtiSZ3hJbLDqZUy8xzlUavHQ123bg+4bduC6eAmd33dGN3/m5IRf6JVXr6RQ98izeVWTbERSNLs8gxn1yNXx2NIm6DpDVl4lIL+lbWZMNeWzLeuq3ClG1gyRFrakTOQIddAm4d6omdg0e7O4ezdRZBf8/N4esdfRWPzea4m4m6jO/XOMCJ7fX/yOq9i7565Ql2HPQV5eYhWIv1xcRHxY2Mv/MhMTJGZ/u1Uw7YhYU0JL+2WzrKV1LS1syXORFz0yGzO/7/Coa8aa7ou4E5/bmyb5Aj4TJ3Mv+1+0Xfkhdqba5PWMPD4zANNly+n5qJdk6chLsgHYUqfOS7gYmU16pihmUTHP0raiaTUjLJ/RzutlaZgrrWtpYUvKxQRMFKqAs+L2xYiHFnNWqLg+vatYZdxfHD0dk/sltUg7v0RsMDYWayZsF3FZOc+92+S4uJfQn/3QcnYtzD9dqKWdLbKe8Zqy/cT1l8IqrQjrOjU9U9y8G1tlr5FMnJGU4SmfSOTvk9g7IQCr9X8z4F9N0UGQHbEPjx5vE1FnLn22Tc61uAF1HLF3MjGpb4Oe8hXOxFMncPamFm2cdLm535sh++KgQRN2TGiGU74Mxax7Vxnz0zX+0SmsgW7hBIbG4WBXrUpfnsHz9gOw89t+LzT6ZNiWy8QteKPKhfSBDOuTlOmprI9hk3bUWvArPd9t+rB2RaHuER66SHbPZbdDTdZ3+ASfU6FkvZLP8iyCjp7n9ZW+7I7Reeaiok6tOgyvqw0Z8c8M38tPVRfriuomU1Xjr6VgS54DPcw6T6bfjK6YKHjcM/KYEw3X/UBre8Mnvmvebw4jgv3pNBYC+w3lQBk7tD8xwVesqDp+7Ww16VmJnPRJxNHNkb7VteEZkSAiScW5KCt2T+/D1pF2WLwCd1RF+a4XXbxPT6caVfY6ScGWPL97ZM03nFqYSPX//kynp2qHKNDSN8OkfiscJy7m9aUO3J+5npCkgrmParLS1SXaZYpKRfiRI1UjyUYk4/n3YQauv86ZeCWdGprz+HFWULT9OXo9mFWrL3OhvQM97EyeCt+rSg1zS8PoTvZ8/6bzC91HVax/LQVb8uLdI+p7BC3/gh1j3mff/PUEBqpyU9N10TM3Q3EjkpSUHEBNckg4GSKbjKt/sctlCv7BqcXu0sjSsup0slHo06iZOWr/SP5Qq7kZWzCl/KFo7xxqQ63g2/Rc4cuv2LPkdRsKViavSg1zS8vQLo4vvKdkVa0fkh9ZD1tSPu6Rznn/zkS1fTbHplzH6ud3sXhwFJ82C/D/bAFdP6rJrXUeiGYfYmqmDapjeL3+Jcmj3sLo2ArinWZjY61Xor3mJdl4t2xJwOTJxFy6RP9ly9AxqDzfpMjOIUdbKzeMMYuEZC3MjZXYtnFhAzBqbRhHz4VwuZMFLZ8og6pP0x4d2GIXhneMkpata1PfQFGoWFeVhrmaSFX3X4Msryopd1QEzR7A0f8NoPeNr6mnJ8gK88J3/kyurvJC4EqtPZvoO8AObbJJP/MLW1ynk248kuZnVuPqZFxge9nkqLXQekZ0SbC3N0fc3NBzcWGQu3ul1NkWqVGsXXmJu13aM6vNwyiQ4WfN2fS1My31FYCaSL/zjFobRrj905Ehz0Ij4qyzMwi7G821sETu3E8lGdA1NsbexhyHulbYW+lqvPVXFetfS5eI5AVjglW79ihDtuG/wZ9UtQKdOs7Yd3RCmzoYL1pCj7xkGvU9gjbvJN24A6adArg6eTEBwUn5tqXmgefPbB2+iMDIjCL3WDDJJtjbu5LOPYUf1nry2R8nGbI/nTcHNsJJX/HoZda2jQsbxtahdvDTkSGaLNYiKZxVa33ZfP0BKSixtjHF3sYQ3YRYtu70ofF3u2m/wJPlnhFEZmimofYy+K/zLGGZOCMp54z2RBHjsUhsbWQhVncbLw5MHihWUyCZJidBRKx893H6etodcX12f7Fm4m6RkJdLkpfibvGuOH0loURJNjvGjxc7xo+vnNNODhXzZ2wRfLxFuG66J1IKz0ASEb6nRbdPXpZ0c7WIDw8Te3adFP0/3SyMpx8V//WNEw9K8MvxSw6Lg2eDKuQo85KL4hKrdgKWdIlIXhzpEYRunMeR938ju9vP9Nz+GfUttIEMEg/OY2ffdegs2srQz19DXwGIVNKSlBiY6eY374i7nY55I+sSpbjnLT5WvC87i+Cjp+i74wEO1bPZF6PH7LGdmNXGtBBXgZpIPz9mXq3O/FH22BbhS/jg30eqVLq5+kEcnp7X+PVIFKlOzVj5TuMiW5Z5Xw7DbZVPhZ5beHQSta1Nq/SUkoItecGiHcKNJRtJH/kprewNedRCbMBk4nusZvDyIVgW9E+LOMIO3MK092uYVaHMSHVUCFvuWTLCMY3/rTzN+8G6T4p2RiKXInRwqm9YIn/vih1+tG5gXXlinZ1JbEIOxtX0S9GCTJAeFcof//NnuVaDIn31FZHV+FIiXSKSCiU7UJwfXE+scvxW3IxTF1pn42Ft7WZi157wctllZmqqCPP3r1j3SMp9seYXd8Ene8Vs30SRJXJEyvVzwnXKKXE0OUfDBylHPAi6IiZM3yr4eKtwWXpRnI/PLnXtmSN/7RWOvwSIoCxZkU9W65NUTZLDiD0bAg71MTctePvlr609B7e+Nctll5e2bq3wJBuFYQ3GTujAGvtMflh7kkl/n+azDWEYd25AeyPNfmtQRwUye18a/d52xWd0QzrE3OJf2+6iAsjOoUTpTUpTeozqxIpqd/lsXxT5GsnJinzPgRRsScVi2hHXvxdiFvAFe3p/xJE9gbkCIMiOOMDRf80ixXUuPRcOetpVUkZajhhRKUk2eaK9vrFgg889jlk0KjQhBh5Gg7zIllil8cUHnlXx2pvOvNGyFu1fa8XiT5xofyWU80k5pN69zuyNgQSWIMIFpSk93nKm79Xr7I/JfuS7roiaIS8r0octqQRyyIq8SOCBi+D2Jk4OxpDsh9eo4Vy7/jouHotz65Hkfe8YYefvoe3YippdX8expXWZamx7r1hBwOTJWI8fX8FJNmpiI1OgmilWhdS0zgvdu3Q/mXM/Da7kscnEb9sVUl9vhauRdq6vPR2/zZ7scuzEDy3h1F+HGPSgKTcmN6L4IDlB6g0/Pgqqx7r+VgytBN91uxk7WfJOm6csevUDFb5XwvEKiObE7QT2JeeWS1Do0r+eOc71qtGukQ1tHK2w1dOMt6ISCLZAnZKK2tAI/RIcsxRsSen1LIwb347G8z9GNDz0F91drYAMEo8uYu/gWaTU6IbVMFcM7hwmfKsaqzV/0W9sC8oyhzQhyaYwsdacaJAcVH5neWtLBCENnTn7QX0sgMxbF/gg0I4/28XywQ83sX6vBwvaGFOiIciJ43+rItDpYM7bv1dsZEhgaByNFx59cp/qZPyOX2ThmUxaOtvStrYpVno6mBgKHqRmk5WSwt37iQQE3WfjzVSCdI35qltjxnStR1NT7codnmKXHyJ2i4mN6oleS/2KiCuVi46S51nfyovHbi3c1weIzIKNEN77XdyNTs8LdBZxe78Rfxm/I87cTCnzLqNu3hR/ubiIVSCCvLwq7dQ1N846XQSdvSLWXkwUj9YLMyPFspUXxbZ/9gjjuZfEzazSLWImJ6WLgXP3iUFz91XomTwdf50tVNdvii1XE0VaSdZOUxLERd+r4udfdgrjaQfFojMlizF/UVBcUHycx2wxaPQ0sdgzUuQUMrAxgUEiJl9nESnYktKKQ8LJZWLfguMi6VHCTLC48HYDscpxurgeVUAZcm6J84MaiPW/XRHZz7HXvCSbVVDhESRVJykmPxni4ra9go93ium+D0RZ4lziElMrvNvLl7+fLKeHRKaIuH5NzP5htxi9PUzEVFKgTzGLjtpYtGhP+w5vMc61RiGvP9F4zluGZ0y2fK2XlJECtbUB4gOJ8IhC9/3hNLQuGLGsRFs/m8zkjOfaq5GlJf2XLcN53TpqNG78irtBSoIuTVrY4GZbn3EtS+gKKYClqUGFN1oov/rXOtg6NuH7rzrxzoNrfHUgiuRKGAVlcf7rbJ36tFP+l2HDNtJvUHvszfNnod3H83omnaXqSMr1rtRBW98CgxrmBRYXBdlh5wg5lIFBb6OHoiFiCfnnNHoD+2NrXDr/oo6BAW1Hj5ZiXVLJru/IH2MUNKoiNT5fRP0QhZ45fUa1R7nBj+VXTZjRzJCKXI5UFrcAEX/mvwwav5xk4PjupYV85yMp2JLyxaQhNfsaEXbsAvFvN3gc3pd8Bb/vfiKGwbTv2wBFbof2Y6M8sdjUhIEjG6Gt4ad26lJY1e1urjTCsQod8pP1rwXJt4PYHatHy7pWNLA1eJy9qX7AhduC5o6mD+u5F3sdTOnxVlNu/xXCnaZNsa/A4GhlsS4RWzsafLWHnZ+24elKxREcmLpOCoykfFHUocmMbwka8AV7PgjG6c3WGD0I4u765YTuM6D6pmk41dQi3fc/eIxZihqIeasLf28fjcP48Tj3akhZo7Cy0tLYN2UKjiNG4Ni7d7mfWu929oTVs6pSNS1EZjpRD8C8VCnqD1ElpVVa/emC9a/1zQTnf/NhVDoYG5swtmkNXmtcnZY60ayNrc+yeuH8tEXNx6PrUezo6NXg/bHVKjyTpdjdaVm3YUqfFtjZ2mJrWx0THQUKAwtsbG2xtW1Am+E9aGAi828k5arY6Di8Rb+9y6mT5o5/v76cGjmde6k9aOqxhX5vNoTcJJtk27E09fBn6D1POveI43qftzhYDj0jX2SSjWaKtZrQ0xfZGPxkRxwRH8KcuXuxnb2Xzssu4hObm+aUFI3XnYLdc55m3LLj/LjhTKWcUUH/tbJ6Q+Z+4sg056bsfLM+rfSTObTvHM3/DOKvY2f4cMVVQutaYFJSa1dXWfE1wEsaenVzz69iQrdGuVEgtsLlvUVi99VYkSXD+iQvlCyRHhMpEiLjRWbeyvwDX3FqYD2xqmDZ1ezr4kxvW7HK7TcRoX6+vXotXy5WgdgxfrzITE19+S9zZqRY+vUWwaf7xXzfvHC+FOG54azYE54ogq4FiOnfbhXG354WR2KyHtYK2XBa/H03o+hrWMk1Qw6eDSokKiVLRJz1E4sfneMD4bHyhFh67IL4as5BseZulkYPU/GmsUgkYO2XDPreEx23cSxatIhFiz6mW85+prV/n3/7qpApMpIX6bXTs7LBzMYcnfwd2nfXw+6fH2nXzOzxrRp7m+grkSjqWKD3nC99HSdNoqeXF9GrV7OxSxcSwsNLvY20jCx+3HCG8OgkTXd6kHrzLh4OTdjZXpu/1p5g8sEokrOT8I83o00tU+ybNGXelx1ZanGfwUvPczTBkB7D6qM6HEJEEQJQ2TVDerezLyQqRYltu6b0Vd1mS3A6IiuJqzp1eLdbI7rbWtLURsNXVItT9OygjWLSdwfE3bTsp2K0H1z9S4wdukpczZBx2JKKTLKpJzYt8xXp+WNhMwPFhbGtxSrjQeLE+bhy22VZk2yqWpx1TmqyiEzNEUKkiYAjJ0XXT7aKbmt9xc+rA0RwvuucV4XQ+FtvsftunDj6P3/hq9Y867r4F7dEcXT7RXHI109M9ogTObnJPVkaPk5axfm1oi4n0e2jntjpaz21IGnsNJwvegVx6naaNAQlFeDa1sewSVuqz1hB34nOjxcWRSx3Fk3Ddy1UX70It7aW5bZLawcHhnt4YD1+PEfc3PBdv75ElnVVC91TGBhhY6AgryHwxvH1sL4cxFcXgtl+83GtvbyCVkstohi48CT/q14LJ23Ns66Lf3EzpVtfG8JOxtHUwQQFCoxM9DS+L6WyOMF+kKRH9SLz5/WwsNYjOS1HiomkAtDDrPNUBj8RR/owtO/4zMsYfreenm+Wf2hfXpLNqfr1SSrGNVKlxDrlLkuO6/PJgBroFnQbtGrDalN9LH6/wZwN/rSe6kIPK+Uj0R732RsMSwZTY+VTcch5Ffm8PnLV7IeUYQ3GTe2BWrvqBE0Uc6S62NROwudKfOF+ahGF3/FsHOvoSy2RVAL56me/t4CeM7o8zpYsZ3QMDOj+zTd0/+abl8eyNjSl5u1gvJIKM7gUGNs3Y/kXbfhaN5LBi0/xvyciSJSYFSLWmmBdB4bG4X05rGRf1tZCWYXueK3iPjZt74b+ws9ZsP0UAXfuERkZSWRkKIF+h1k/4xOWNxpGd2ul1A5JxSMSiPbxI91lOm4/DqeGfuWVwKySGYwKM3p1gjXHY55oMPCErW1Vn68/78h/az3g4+XHWeCX9MwGBppQ73r1wQAW7b5S0puI9NhY/G7c51psVu4DSZAUcJXlZ1WVkn7+7MMtQaWtrIhDYna3Oo8WFB/+V0d0m75d3HyglmF9kkpcLXsgEiMrr35aZmqqCPLyqmKFnPIvvkWLNfMOiEXXUp9d0CkrURz9e79o8LG7eG/f/SIr1m0/cb3CK/IVhI83i+XuviUbv/AAMXbaZsHHmwWf7BTvbbopriaqhRDpIsj7rJhxKLpEVf0qihI3MBDpkVzx8cH3SjAq3Zo0d+lCF+daT9XIlvWwJa8SeU0RQmf9Ra+BbnRp26DKnUPWvWt8tCISt3GujG70rAbB6QQc9GHsYT1+meNKJw1sdVZo/etcqzk57D6BBla0ttLJdeVkcW2PH1dc2jBIPwl/v5v8tDecY3pWLHq7De+1NCB49wWuvE7U4iMAACAASURBVObCyBqaUfSgBL6MvAYGtrToNpQW3eQklUjy6Dhp0sP/mfwe8ZHjyXKqyE425eSfr+XIwpFJjFx2jMDh7ZjuZo1Fofqkj1OfLhzvnIOhgWb2pXyyfsiTDxv/o+fo7AvvdXLk094NaGkhSMvQo66lDvq61XDt0YHtzvdx3+3PN78fZW+rugxQZGGk1hzjs9jlURG5lymtmzFw+QVS5fyUSAoV7edNsqlsGajeyoXtU+yI2uVJn/9c4GhoWhG+ai2MDJRoahvhgvVDHgtZGiERBszta03a2Uu0+uEQ0/eFkWyQhnfwYw++0sKGN8f04PiHjXBOTya5aROG1NKcNbpiXCLZqA7+wLiND+g0/is+62RTYKAyiL11D+rXxyq3opp0iUhedtIyskjLUD8lCtGBgRx4910yzp+np5cX9h07VrlzU8dHsHn7Rb7zT8exVQOmdLOnc0MTqkocmOKTLSzv2YBJQ9oUEOxkznonYd+xJhbJcXh6XuPXI5HsywRjm4Z4fd6aloYKzT+/4nzYIvIAC3dX46P3XbB4qot1GO5jfoGfFjPUVikFW/JKiHVew9yTc/pjoPdkQc4UlYrD06cTvXo1zuvWVXi97eIV+QE++/35yTuaYxgxtnltBnduSGc7g3z+0SwibwSx4fBtVt5IBctqjGprg2s9C2wtjLA2VJD+IIUoVSLXInSp18yM2tpUeHOCghTtvy5U2UiPjWT/0Wv8dErFdWNL5g1uxRgXK8w1uEZvMYItUMfexHPXf5m3W6vwBgYLr9J51zIp2JJXRqyLC93LSkvj1JIl3J45U8Ms7VR8Nhyn9+mUAuFqSga6tmDJsAbYP+GbziE5KpaLd2K4cjOGczGZ5OS6RSyszGnhYEPX5rZ8tvQgULGd0AvD/eQNhm25TNyCN0pR0lWQHhXGxt1X+fFiMtSw5Zv+TRnaqppGCnexLpGYvdOwf2P5M+IRP2J7xAop2BIp1gUI9vbWKLeIiLrGqLk30enWnM9crbHWziIi/D7HTt7mh6AMbBs0YceEZjiVwjXgfTkMt1U+GhF7vt7jCu6+YU88OLIiI7igY81rVsX5obNJCA1h3barfBuURZMGdswe3oL+dvoa5a8v1iWi9ltM2y2Oz2xgYL70VynYEinWGo0gyc+brv61ODK+Pk9WW8kg+LQf4zfeI7l1W/aNq0/1EqrU4Hn7NcK6LvKsk0KY808G495vjF2J1g4fuoPW7rrOP7VcOPtubQw16HyKPQUta2cmuNpgbWPL0w9eA9oM7wGygYFEinWJSFGpMLK0rJRzUauhVSNLnt67HvYdXNltc5XJK67wy4XqLGhTfKPdqlAzRGFamw+bn+GTDTr8d5Q9tsUqng62jo584+jAV9mal7ZerNIqlClc/qo/gwsN6zOn5ZuDaGksBVsixbpY2y0tjb3jxr2wTjbPOBP8ToWRWt2IO5ejiS58pmNs34T5w83ZdyCYW+rit6rxFflybdKaHdoyr3oIE/+6QUBSSXsRaaHUQB+2VnF+nfjLvkS4DqFP65o87cbPIPZWMLFq6f6QvHzcvBtXrm4QHQMDavfsScDkyeybMqUCRTuTu34R3LG0pn/kbdZfTyui6YiSmu2aMI0IjoVllci6rsyaISVHH6d+HZhfJ5IPFhxn8ckIQlNLV2FUZKrJ0HzB1saiRXvad3iLca41CnlFisZz3jI8Y7Ll7Ja8dLRysCFuwRvlakFWTpKNNkZ6qYSkVmNIFyW/brzCmaQiBEtZjQHdDTgc+OCZnaQ0zbpOy8gqXrT7dGLXGFtiT56h7sz9TPj7EnuvxhL+QF3kuapTE7l07hLfr7/+//bOPC6qev3j75EdEQERBAEFVFBccF8g9yXLkvDaHlqZ3q6KeiurW13rpv4sK3O5F8s2zUwtSdMyUTMUFDcEBBVUSEFQRJBNRJb5/QFjZqwywJmZ5/2PL4eZOd/v93zPZ57znGfhzI3mN0xrcdGoKTNxZ4Dx/5g0aUPVYX2nbzFUrm1BT2mMjt8efn4EJCay8+mn2ezq2gShf+a4u5Wz9fdbPD28Fwtjoth0+gaDB1pVacO17dgGswM3KatGIJTmu9bEX5+YMxTfLu1qlLu23j4secOD506m8OOBZOaGJHKeFvR1tKafUys6aWr/q0tIu3CNn3MsmT6+G39/xgkns+aPF6lFsMvJifofE6dVhPXt+3F5Fe+ZIYItCPVE08lm96uvssffv5GTbIzp2MWW+NCLpAzwIej5ISQZVx/7oDI1xiQ1j6s441TF3zu0a83K0Z6Ksa419UPc2rWu4w2HBV18u/Gybzfm3sgjKSWb5KwC0i7fqAxfNsHRqQ2DBvRgYQdrrBTkyzau1SXi5Ibn/O01hvUJgq5TVFzCgnWHCJ7oi4uDdZMc885ONtFTpnA1Pp7x77/fKMcydXfj2ZIoVh5xZekQe7rV8N6y/CIy7NtQ3Sq4OFj/NfW7Gam2fkhZEUkxyew8eZWYvBZ07tCGPp5ODOpqdzspxtjSmm4+1jWuh5KoQ1hfX4LHeeLm5FSFw1vC+gT9EGtNNMjEgblNJtjwRycbe29v8tPTG/FKb0PAeDuWfnOMHu38eNajuoSQm8QcyUDV1hVdqTm4NOYyK0ffXda2iGPf72PE/oI/kv4SLwMJeDo68a9AX4K6t0LXWq/UuR42qCktyCartCWONuZQfJNbpuaYST1sQU/EWneTYuqIOp9fv9jHqBMteHVyVWVU1RQkxzFtWRpDgscQ3NlU8VOqrn5IRVZnPEcc2vHK6A70tTOB4hsk/n6FsEMZrMs3YuqDQ1j5gCNW+iXYakozolj38Xssfn8b54O2kL52IubHvuLd71U8+XIQ/e5I+xTBFkSsFazZN67w5eqDPH++BE87e/7u78ZAN0ssy25y7szvrP4ti1iPnsTP88ZZ+cXrqqkfUpHV6f2dEZv+NZD7rP/sAVAX5xEdGc9/tmdiN2awTol27fWw847w8ZSZrM/15aV1IcxvZwQYYdvvOd5/qSNhH+0iQ7RZELHWOtfT0ji2bp1W47VVlo48O3MEe0faYZeTxSs/RjN0VQT9Qo7x+L4sjtm68l1Qp7+IdWRcKvPX7Cc7r0hRa1Sd/9rIuAVtursywPqvEqcys6bvyMF8M88bx8MnWF1tXLrOCXYZOYfCyX5pG2Gr3+bFZx5kYFvNPZQK47Z+PNE1mp1nb4oCCCLWWubikSNET5mi9SQblZkNIyeN5Ne3/NnxYEfme9kS5OXE0ocHcHz+AEZVUShp6Y8nSbpS0Chhjg1hacxlRvs43j1DLN3aMiyrgGvVKrEKKzcv3nzagYjQs3XK7FQCtfjci7mc5sjDT7tU88YWGJveIDu/VFRA0Bl0xQ3SMzAQq4gI9vj7syE2lomhodi4uGjNVrNydObBB5x5sJZ3KrVmSNLFawD09nT4s1cg5zKR+W0ItDrMu/sdWTnMthr9UmHVuRtvdTrA+oQb/KeXpeL3bi0WthntXK7y24mcqm8ZSi9yMAy8Xc1FBQSdYepIL53xWWuSbAA2u7qSHBnZ9FasQmuGuDpac2LO0L/2b7yVzepdufR6yB1+PMib4Vk1lIc2p/dgB6KPZJKn+y4RI2wH9Kfo33NYvHEPx5MucT0vm8yMFE4d3snnL8/hi64BDG1rLCog6Ax+PV116gGjJsnGYdo09vj7c2zduiY7tpJrhliYmeDbpd1f3DSqto6My7rEMYtOLH62LUe+O8jy+Ordti3at2X4pRzSypW/F2pVWpWtP698fJm3Zj5Hv99SK158F8CVEa9+zOq/98NaJSIgCI1JVUk2o995p9E7tOtGRb67FdiGUUNKeGx7Bj891Zctc5L44UYt9Y4KCrlcpKZbS2WLWZ3jsNU3LxEdHs7Rk+kUWDnTo/8whvVpj7nEYQsKpqi4hMQL12qpMaFbxIWGEjVpUqPXIFFSN5l6U3yF1UujyRjvx1t9rWu0TNXp8Tzy3nWCF/sxUl8Eu85fKIItKEisNQ8Y69fnT/lcT0vT4gPIqlF6N5laTExuJsfy2LJL9HpiEPOHtKkm1rqIqG/2MvhUexLe7U03hSdtS065oPdiHTFjsF6JNdDoYq30etfrfjlJZFxqTaYj5h7dWT3VjogN+xj50RG2xF8j65b6D0G/fpW9WyIIOljEkD5OdNIBNRQLW9B7sTaEDEaoaD9mamGhNb92ZFyqYtdONXMzK0d71qEIVSkZ8fG8s/4cn+SXAy3o69gKj5ICvsuu8Gtb2XUk7JV+DLZWvmKLhS2IWOuJWH9///1aTbJR6tpVF39dNcY4dfdl1Rsj2PuwGzPsVBy/klsp1sY86NuV3XP66IRYi4UtiFjrEcmRkezx98esf38tJ9koi6rrh9SVcgqu3yC/VI3KzALHVsboUpCbWNiCiLWeoIQkm6ag2vrXdZQ8KxsrnOxb0U7HxFoEW9AbtN0wV1dpaJKN0oo7VUXV9UMMAxFsQS9ojIa5uoomyabTokVET5nCzvnz6+TXjoxLpc3r20nLVG6Sdv381/qH5JQLeoO+he41hDs72URNmsRPOTkErFlTs+VamdXYlB136oumf+Nf6oeIYAuCoOtoKv7dKiys1bpWYkW+u2mY/1oEWxCaHM0DxqkjvcQFUgfqkr6uKzVD3OxbMqiLg8GeSxFsQSfF+rOz2UwdKeuhDXTFugYU1a29OZCHjoJOirWhR4M0lOtpaWx94QVKiop0syKfWNiCIGJtKGRfuEDmZ5/xzmULtrn564R1LYiFLYhYGySaJJudTn3oVVyAU/5FWRQRbEEQsVbs7XU7V5zbt+Fxo7Qm72RzL/tAyfHhTXbOZNsKSmbBukMi1o2EnbUF2xc8REnRaA50MG7STjb1ZWfU+QbUDxHBFoQmIXiiLxMH5opYNyJVJdkMX7BAUcWjDD3+WoO4RARF4+JgLWLdRPQMDGR0RAS5sbEUZGUpamyGXD9ELGxBEKrEw88P1/BwRblEDL1+iFjYgiIpKi4hJumyLEQjE3YkmaLikmr/rjT/taHXDxHBFhQp1sEh4fRevl8nSnzqKpFxqYxbe4zoxPr9MKbFxGitk019Ef+1CLagQLHW14a5SuJeshpLiorYO306G4YN43paWtOPWfzXItiCMsVaHjA2rnV9L53QTSwsGL9+PdD0nWzEfy2CLYhYi3VdTxrayeZeEf/1n5EoEUHE2oCs64bUDNF0sjng7t5kSTaBw7xJ7eosbrJKpGu6IGJtAAQs/BmArW8+oJXviwsNJWrSJBymTVNcko0+Iy4Rocm5lltE7OUCEesmtq7r67uuiTuTbLYFBsoii4Ut6LuVbWFmIguhg9b1nVxPS6MgKwsXX19ZaBFsQRAaSmj4GTycbPDt0k4WQwRbBFsQBO0z4LWtLHuyr7jN7kB82EKjUlRcwgsf7yEyLlUWw0BIi4lh7YABDUqySbp4jaP5t2QxRbCFphRrTTSIYDhY2VfETDckyUbir0WwhWYSa4kGMSxsXFwanGQj9UNEsAURa4PhhY/3EHYkudmOr0my6bRoEdFTprBz/vx6FY+S+iEi2IKItUEQGZfKZ2ezaWnevGGTmk42g7ZsIXXpUn4KDq6TX1vqh4hgCyLWBkNDaoY0Bncn2WQmJdX4fvFfi2ALTcCy74+LWCvAutZ2VqM28PDzY2JoKObOzrW+V/zX1SNx2ILWSMvM48JlaZjbnDRmVmOTidLMzawc7cmsR/rKCb0LqdYnaA0XB2tcHKxlIZrZum5IRT4lsOXRnnR3bysnVCxsQRDrWmkkR0Zi16GDVPyrA+LDFu6JouKSZg0bE6q2rpXmu64LB+bNa/JONiLYgkGJdXBIOOPWHiMtM08WRAEoLTKkPjRHJxtdRVwiwj2JtUSDKIvsvCKyrt+gi1sbnRx/SVERB5Yt49wbb+D6yiuN3slGBFsEW8RaEBpA0sVrRP38Gzdf/Jt0sqkGcYkIItaCIvhsVwKhWRZ/SrJJi4mRhRHBFkSsBaWhqR9yZ5LN3unT61WDRN+ROGxBxFpHyc4r0ptswLvrh9i4uBD47bfkpKaKL1ssbKHugl0qDXMVynMr9rH4myi9mEtV9UNMLCxw6NJFTrQItlBX7KwtOLIkQMRaYWjirof1aK8X86lP/ZDCbMNtiCGCLQg6iC7HXVc5nzrWv06LieGbNm0MNslGBFsQdNS61sWsxqqoT/1rWzc3g06yEcEWbqNpmLvqh+OyGGJdNxn1qX/d0E42ItiC3oi1JhpEOn2Idd2UFBSV1Kv+9b12stEHJNNRkNA9HUIf6l1rk+TISA7MmwfAqE8/xcXXVyxsQcRaEOtaidyZZPNz7956/zBSBFvEWsRaR7iSU6hXvmttoUmy6bRoEXYdOuj1XMUlImItYi0IYmELSubzn+NErAVFGA6CWNhCHS6UxAvX8O3SThZDaBaSLl7D6729nJgztNH2YVxoKFaOFQWlxMIWdBYLMxMRa6FZ0cRfu7Vr3WjHSN65U6+SbKRanyAo3AoFdLaTTE3Up37IvfLgihUccHcnesoUrsbH63wnG7GwDYCi4hJCw8/IQugg89cdZv66w3o5t7rWD2kI+pZkI4JtAGIdHBLOpM1xt601QTfQ57jr+tQP0QY9AwP1opONCLYBiLUmGkQfb6v1GX2rGXIn9akfoi3uTrI5ExYmgi0oU6wldE+sayXRFP7rqtAk2ThMm8bhN9/Uudra8tBRxFoQ67rp5xdzmZWjPZvl2CYWFgSsWUNhdjYt7ezEwhYMS6zLkpcxbYkv7x5NlRMg1nWtNLX/ujp0TaxFsEWsm5Ay8s6sZNHa6XwQlUS5nC6Dta5dHa05MWdok/qv60pmUpIIttC0KNMNoqY4P4kzGb9wJqcAyYM1TOsa/kjaUlrH9zNhYWz18lJ0ko34sPXsQlgzd7Rit1rb/iv5uv9KOVE10NbGkpWjPeW5QzPged99pFd2slFqko0ItiAoiC5ubST8spnQJNnYe3sTNWkSP+XkMHzBAmxcXESwhYZTVFyChdktEnc/ycKEIbxwvz2Hdn1AfFEhGPszYvwSJtnGsGnHfziQnQkqL3r4f8Qsvx5YAlDGjbSf2Lh3Bb9lJKEGVK2e5qmJrzLO5c76DsVcPfsN68NWEZ2fBRhh1uphhvkH82gvz8pNVMatnINs27SB7SknKMYBl+5L+ef44bQ1qigIVpa8jBmb19Jh1Hbe6u8K5XF8uyKQA17LmGa2hy+O/kCu2ggzu1lMnzyLAbZmfwyhLJ3Y8PdYU9N7/kJd56emNOcQW8Pe45eUExQDGPvSo/tMnhw5FhdTVeXxl7E2+nuulpYB9rR1e5ZJo57Dz1FNws6/sSS2M1NnLGOUrTFQytWj8/jn3rOMffR7nvGw+mO+Pht4xzOZzbs/ICr/KV6bF4x7RkPG+RhdCr5iS3J/XvzHuwyxMrr9/qKzS5m3ZTe9AzYyw1t+COpCz8BArCIiODBvHtsCAxXVyUYEW4fFOjgknF4dzBlhXgw3/8tne6fy5Li1jC9NZH/4EvbteJCD5n6MGr6K18wyiT78HmERH7Ov0/940NEMKCLl5LektH6SKf260c40h7iDC1m/qRSL5xYx1NYEKCX7zMf837bvMPN6iVk+3lhxnbSU7ew+k8zDvTyxAiCX36O/wO6+15nXp5SU2JVsjl9MaKee1QuFupTS0lvkx77G+s5v8ezkJyhN38GmyFV8Fj4QnwB/WgKQRezOWXyYaM3wkesZaFNI3MGFrPrWgjeefxEvM1V1q1SH+YE6bz9fbJjFEZPJPDLhdTpaQkHmEcKjI7joPxoXkyyO75jJ8rPm+A1ew1QnW7iRTELcDxy58ih+ji3rdtIq51uY+G8WRaeicn2BxweMxLlFQ8d5mtZDJ2B37kvC4l9g8CB3KlYkm9MJuyk0G8Ngd2VERKz75SSezjaKd/l4+PlhFxrKrlmz+Ll3b4bu2oX32LEi2MK9i/VnZ7OJGNkLLgG40vu+mdzv7Qj0wi73Vw4fiMKmx2wm9/LBGDUexLFv61bi06/xoKMzYIXP+G95947v7mp1hei177E97nn8h3nRovgYW3eu5prTMpZODMChUht9Oo9i3G07toIWbnOY4jccO6Bb6yscPPcmsamXKPNug1FNE2oxkb+Nm0xfKyNwb0vW6R/Y+HssaeX+eLVQU3JhE1/EX8Rr+GaC+ntgDPg4mZP96TKOXHoGL49W1XxxHebHdU7u/z8OFIxk6guvM8rOpPKKHcTAQRordS1rTqfiPSqU6f3dKsWwLz27T6781oJ6nb/ygkxaD/iWV0f2rLzTAduGjrP8HDcOfcbG6D0k95+Gp5EKCqIJT0rBrvc4ulb7o9a0TNl+Wmd89Jokm5+Cg9k/bhy3tmyhZ2Bgs45JokR0WaxnDMavZ/vKv3Snm7PGijLCzNQKcKGbq2vlr7IKU9OWtKCUW6Vl1W8IcxusKSTnRiFq1BSl7CGiuB2+voNvi3XVtMShvSc2lf9TmbTEgjJulZbWPin73nhobuNVppibmkDpLUrVADe5eD6cbNVoRnTv8IeFYdWD/m5FnM7IrFfEyZ/nBxTHc+j0KVp0nEA/jQj+ieucTviFQtVohndtj1ZkzyiQibfdUhWRIfPX7Cc7r+jex9miA/19R9IibwcHL+RX3Bmd3UVM+UBGdPfCRAF7Vynx1/X1awesWUOftWvxHD5cLGyhIWLteod1Z4qx0d1yYoSJUS2/yWWZJJ74nj0JOziREV/hFwXMKm3ngvwrlNAae6vabvvNsLa0vDcLwMikBgs8i99Tk0AdRciqDYTcfdSWuZRD9Z+vcX7AjSwyy8DEuk2la+duCsjJzQYjR1pbGGnnRDp0x/UOi3fpjyeBXK4mxfPtPY/TBIfukxlyYCqRp07xNw834k9HoHZ4iYHtzBWxf5ujfoi26BcUpIhxiGDrtFg3kLJz7PpmCt/k9GD0gJcIHt6FTtbH+fCTYC5UCr5VK0dMiCG36CZUIxWNiwWtWrYC8xd4M3gmXi20OT/A0h4HI0guzKOoyhlaYdvaDq7kUFhcDpbavSmNjEtl2+VzrPJZz6LIPg0YJ2DRE/+uPkSc2U9SZjeiUkvxHjmQdsrwhjRb/RB9QlwihirWQFnaLralWzL8gfcJGjyKnh1csSwr4Q8nhgqLDsMZaJrG8dgjXPuT76GMosJ8Sht99jZ06jIU85u7iDx/d6GeG+TfuNWA+QFmXenf2YvS5J+Izr1rNjdzyS+zxst7FBbluwlPzLjL/VLT8YvJy8+qdXYVWY2JJOS2buA41UArvHpMwLF4N7v3fUeCaqz23DhaoCnqXzclkatWNXmSjVjYOkBjNcw1snGnoyqF40c24k1fWpdlcDp2HSmA6W2rrT+PjHiC47v+zQfbcgjw8caq7Cq/p2xlZ1IPZs+eSadG3qJ2PtN4PD6Ir378Jwx5hn6ONhVRGglbSe6wiDcGdbz3+WFHz6Hz6JMczLpNrcgfMpaOlqVczzjEb8eO4BHwFU90foan3feyZu/LfHrjeQY7taY0P4n42K847PQhK8Z0wcqyDfA759MzGWZtwoWEzWw4EQV41WxdZxQQ8cxAIsN3NXycHVpi3H4c450/4auUc1h4f00vKyNF7GFd9F/XRnFeHgmzZzdpko0Itg7w/AM98fdpr/0ejK2H8ujQAD7Yv5CQVFBZDGeAR2ecVPHkG2u2hhkOvRewyKIDX+79kFVnsoCWWLd9nDGjx+PaFPdoRu6MemwT9uHLWBs5jX2lZaByp6PXP3i8m1MD56fC2G48s5/9gu93fsAPOz6jGFBZjGCI7yzuczQHIzeG/u1rWv66lG8OvUDE7eM/x5Re7hhhjlvvGYxM/Ce/bh/EgR3udPR8goHdhnI29noVzxbutK6t8Bv0AO3VcQ0fJ4CqPf18x7I+PZpBPt1pqZA9rMv+6+pojiQb6ZouCM1xOx2Xiv8nhxqh7ksZuXFvMTe8Pa+9+A+8jJXhEJm/Zj9JVwrY+uYDencukyMjOTBvHkCjJ9mID1sQmoHGq8h3hdj4A9j3HE1nY5Vi5utm35Kg+zz08lw2ZScbEWyFUVRcwqofjlNUXCKLocfWtXYr8qkpzjzBifQr5F7Yzs60Ptzfw0NRF/esR/oSOMxbb8/pnZ1s9o8bR+SqVZQUFWn9OFp3iTyzxK3O7/36tYv39Nm7Pyef1f4a6+JnDffcqrmV/DFzNi+rc86l7IvG/+wXcxK1/iBSLGxB0HlUmHrMI6QKcRGaj8aIGpGHjgpxg0gPRkEQxMIWsRaEZt3faZl5shAi2CLWgm5xZ3EnQ2Fn1Hlc3/nFIOcugi1iLegokXGptHl9u8FZm1I/RARbrxCxNgw0cdcuDtaGNW89qx/S3EhqejOh7Ia5grat620ZBUTMGGxQ89bH+iFiYQuCgVjXhnYnpY/1Q8TCNhA0mYsWZiayGGJdGwTivxYLW2fFOjgknOCQcFkMsa4NZ+7ivxYLW1fFWhMNIoh1bQiI/1osbJ0Xa4kGEevaUBD/tVjYItaCzqBJFNFeRT7dInCYN6ldncV/rWWkloiItSAIOoK4RESsBUEQwTZMdkadF7EWBKFREJdII5B08Rpd3NrI7hIEQSxspSNibbiEHUk2+PZuAQt/JjIuVTaDCLYgKJfIuFTGrT1GdOJlg7673JZRIJtBBFt5SMNc4U4MOe5ag8Rfi2ArVqyDQ8KZvec8iReuyYKIda3lTui6idQPEcFWrFhrokF8u7STRRHr2uCta5D6IY2NZDo2UKwldE8w5JohdyL1Q8TCFrEWxLrWEQzJfx0TE0NkZCRFRU3bq1IEW8Ra0IJ1bei+azAs/7Wvry8nTpzA0tKSVatWERMT0yTHbbTEGb3CsRPc/xK0tIP4XbD/C1EqoYLnP6/49/PnZS3+sQkuJ0Lovw1y+v379ycoKIiAgABcXFzEwm42rpyDF4kyzwAAB7tJREFU/Ksi1sJff8gvnYKEPbIWAMlHIP20wU7/6NGjzJ49m8DAQMLCwnTDwhYEQTAEioqKWLBgAUuXLgVg5cqV+Pv74+vr22jHlCgRQRCEexDr4OBg3N3diYiIoE+fPlhYNL7vXixsQRCEepKUlIS9vT12dnZNelwRbEEQBB1BHjoKgiCIYAtCc6PmRuxKxrZyY+yKaG402WEvsePFHqhUKlSqR/ki6aacCkEEW1AKpWTFnSDlpnjXAFC1Z0LIYRJCJoL/SAZ5msuaCCLYglIM2StEhaznRE6Z0pQTy16zCcu/SFhwHyybdE3SOf5LLL0m9sPTSLaIIIItKEKs80j+aQ0frS+UtbiTnPMc39+GcX06YiarIWgJicMWahHkXE59v4aNv9vg42lDcWoCCTFHyXwohC9HX2LF3P8SkXKYfQWgnvMs2yxa0KLHND56+T5sUVN69TibVn3LyTa98DU9T3iKG0Fzn2awkxllp1Yz3OdFIgAmLWbtsFxOXLXBWZ3IzjhHnn49mKBBzjVv0prGN/wUczvdz/IcIGgL6WsDcaKUjNBZOM/PYG7wJPxdrFCpszj834W8nzGFvZFvM9LOCEqvcHzTGr4+2Yq+vqacDU+lfdAsnh/sXIeLRk1hwiFCSzyYnrSBxdGmuLTN4OetrZj56VzuayuXnXCv16MgVEu5ujhmhXrEW/vVBbdfK1AnhDylDtpysfL/Jer0LTPUMEO9Jb3kz5/OjVIvHdNXPXXjOXXFX4rUFzbOUDuNWaGOKSyvfFOKeuNjHdXYPq1effK6uuLVUnX2/nfV/a0mqpcevVb52j2OT/P9QVvU6bfH+4p67i8Zt4+Ve3SZeoxVX/XftyRXjLP8mvro0olqp6mb1BdKytVqdbm65MIm9VSnAPXymNw6rFuhOiFkohqr8ep/70mtnPtF9Zag7uqxn59Wl8nGEu4RcYkINVDGtfMJxFxIIa1A459uidfgoTia1uaYLSZl2yreOTOB5yZ4VFql5rgOHcu4Q2vZEFXZpUdlhImZETz0CA93b01F6TAjbP2f4qWH4nln0U+klDdgfJrvv2NcmWlG9OliW3GsmwlseHcVvz/9L15/uCPGQHnKTyx6J5Npz43GzVgFqDB2HcRD4xJYsuEYeXXyX8fT/5+vMnekS8Xc1cUU5hZwtaAYeTQriA9baBSPmWO/MTxyaCbeTgOZGLyA5V/8TLzzFN6f4FyLaKUSuSWcgiFd6Wj5RwVHVdsO+Dgmsjv+EjU+olQ50Xt0Hwq27iLyQrEWx2dG++GP4u9kChSQ8NViXjkwlLdevr9SnIu5ELmLrQXe+HRsdcd47Ojg056M3fGk1PJsVX05jl/3OnD/6B7Yaqaef5H4I60Z6tUOeQYpiA9baJxfdLcJLPnua7quDmH1yv/wI4DnE6zYtIpZfe2otphuWS5X4lPBNZrdP5hgc8efPN7/moWezrVYC8a0srEDErmSXQLuZloanzH2PXtjj5qSpM288Uo0D/1vB497amJISsi+cgkwJXr3Nkxs7hilx2y2LPSkfY0DLyf/9DF2mQzhS5/Wt33axWej2ZXfl9e72sqmEkSwhcagnILYcOLtxvNySAAvhxSTdWofG977F//6cDcTv3kMt78oYilZcSfJ72SNY3dXMO/DmEcCca13mfRS8q9nA+1xtDPR4vg0unyWjW8vYe/Il4ma3BkTyri6YykbXaczwbE9YEqfMRMJdDWp57gLOBt9jIyhz9DFVmNLF3Im8jdihwTS28WIgsuZ4OiAlUp2mCAuEUGLgp1/fjvLf0ut9LuaYd/tfma/PY9RR1K5WqVr4CYXwn7gRK4zfpOGYbU/lrP5f3ZCqzN2s3zrecpr9CtkEh9xEquAcfh1MNPi+ABucH7jEuZs78PSxU/iY64CbpKeXEJ7B2s6+I0jwCqO6LO5d40pjV3Lt9fgUwfK04ndfYZe/l1x1gjyrXOEb0pg7GND6MRZNr+9k3RxZAsi2IL2KWHblzuIvv1QT01J3nVuPTmAzsYARrR27kB3srmeXwrqArJy2uLc2hL3R+ayuH8Yn357kgKNQJWmEvZJJO16Ov158x3az6GLmhTuMnIi1rEk4j6WL3wY9xYNGd9ffgkovfgLH7y7j36L5hPkY1Xxal4cP23MqLgo3B/i7cUefP3pVuJvf28xGWEbCGvnjUsN41FfOcWBgw5/jr/OTeNUnAtDu7Xj5on9nJ8wks5y5Qn3gFTrE2qgjKs73mB6THtGl+RS3skLh1sXSMh05/HZAXSzMtKoFIc+epk5+2x5uE9rLIbPYE5ldIS64Azblr/Hl+ec8PexJCtNRd/ps5jcTRMRkkrolBFMKnyOz8eYkm/ijF1+NL8mtmfS3Od4sEvr6v3ktYzPK/175i76jvjIXfxGPybfN5HZHz1GyZJJjHr/BpPnP8aAtiagzuXczk18cnE6x868TF9jQJ1L0rb/8vaX5/H098Y86zK3+j7LK5O71+jKKItdQf/Jv/Of8PeY4FTpTlFnEfXhq3xV7Esn+x489fwwnIzFHyKIYAs6R6Vg835lYosgCOISEQRBEMEWBEEQRLAFvaYsaROzn3mRxaHnIXQxLzzzGpukdrQgVIv4sAVBEMTCFgRBEESwBUEQDJD/B3n7+r390XbCAAAAAElFTkSuQmCC\",\"relationship\":null}],\"relationships\":[{\"relationshipType\":\"http://schemas.mathworks.com/matlab/code/2013/relationships/document\",\"target\":\"/matlab/document.xml\",\"relationshipId\":\"rId1\"}]}"},{"id":46053,"title":"Construct finite difference approximations of derivatives","description":"In solving a differential equation with a finite-difference method, one computes derivatives with various combinations of the function's values at chosen grid points. For example, the forward difference formula for the first derivative is\r\n\r\n f' = (f_{j+1} - f_j)/h\r\n\r\nwhere j is the grid index and h is the spacing between points. The systematic approach for deriving such formulas is to \u003chttp://www2.math.umd.edu/~dlevy/classes/amsc466/lecture-notes/differentiation-chap.pdf use Taylor series\u003e. In the example above, one can write\r\n\r\n f_{j+1} = f_j + h f' + h^2 f''/2 + h^3 f'''/6 + ...\r\n\r\nThen solving for f' and neglecting terms of order h^2 and higher gives\r\n\r\n f' = (f_{j+1} - f_j)/h - h f''/2\r\n\r\nBecause the exponent on h in the last term is 1, the method is called a first order method.\r\n\r\nWrite a function that takes the order |n| of the derivative and a vector |terms| indicating the terms to use (based on the number of grid cells away from the point in question) and produces a vector of coefficients, the order of the error term, and the numerical coefficient of the error term. In the above example, |n = 1| and |terms = [1 0]|, and \r\n\r\n coeffs   = [1 -1]\r\n errOrder = 1\r\n errCoeff = -0.5; \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: 435.55px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 217.775px; transform-origin: 407px 217.775px; 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: 380.183px 7.91667px; transform-origin: 380.183px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eIn solving a differential equation with a finite-difference method, one computes derivatives with various combinations of the function's values at chosen grid points. For example, the forward difference formula for the first derivative is\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 37.5833px; 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 18.7917px; text-align: left; transform-origin: 384px 18.7917px; 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: 13.5917px 7.91667px; transform-origin: 13.5917px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e       \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-15px\"\u003e\u003cimg src=\"data:image/png;base64,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\" alt=\"f' = (f_{j+1} - f_j})/h\" style=\"width: 84.5px; height: 37.5px;\" width=\"84.5\" height=\"37.5\"\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 42px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 21px; text-align: left; transform-origin: 384px 21px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 365.642px 7.91667px; transform-origin: 365.642px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003ewhere j is the grid index and h is the spacing between points. The systematic approach for deriving such formulas is to\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: 1.94167px 7.91667px; transform-origin: 1.94167px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003ca target='_blank' href = \"http://www2.math.umd.edu/~dlevy/classes/amsc466/lecture-notes/differentiation-chap.pdf\"\u003e\u003cspan style=\"\"\u003e\u003cspan style=\"\"\u003euse Taylor series\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 116.3px 7.91667px; transform-origin: 116.3px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e. In the example above, one can write\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 36.0833px; 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 18.0417px; text-align: left; transform-origin: 384px 18.0417px; 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: 13.5917px 7.91667px; transform-origin: 13.5917px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e       \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-15px\"\u003e\u003cimg src=\"data:image/png;base64,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\" alt=\"f_{j+1} = f_j + hf' + h^2 f''/2 + h^3 f'''/6 + ...\" style=\"width: 226.5px; height: 36px;\" width=\"226.5\" height=\"36\"\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: 51.7333px 7.91667px; transform-origin: 51.7333px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eThen solving for \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACMAAAAkCAYAAAAD3IPhAAABNklEQVRYhe2XXbGEMAxGj4c6wAAGVsEqwEEdrINrAQ1IwAMWqgEL3IcmU3Zm2W2ZBnjgPPET2kyS5gtwc3MDQAM8Mu0aKydaIAAj0AMz4L/YLsBk4chDFh/k3sv9DLgP9n/yvq/tiJNNZ1LYn7LZuPFNkPdtbWdevEflF5qiXPsiZlm8y7TXFFaPSicLL+SfjAmjqAziSMi0d2L/qah34Yl18iKlKKye+S+bdcSTVA3dtCelaFg9/1U7Jo1OT9FCXsc1Retlq7EditbLVmM7jIaUoqoFuQdt94tcn4oKXdWesZcRwxGgFI1K9RGgFFXdEnE0Q1W3RBzNUBnIFUdTJi7SX3QEMBmOStFh6vAj7Yj1sf7dUHE8XKXXI4IjHelTektLVOZATE84yxGlIabJc4GecnMp/gGjCl04ApTc8QAAAABJRU5ErkJggg==\" alt=\"f'\" style=\"width: 17.5px; height: 18px;\" width=\"17.5\" height=\"18\"\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: 94.9083px 7.91667px; transform-origin: 94.9083px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and neglecting terms of order \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-5px\"\u003e\u003cimg src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAB8AAAAnCAYAAAD3h5P5AAABYklEQVRYhe2WYc2DMBCGHw84wAAGUICCOagDHGABDZ8EPMzCNGCB/ehdOFgZa8uWfEmfpFlGcz16974tUChcQwv0MtpfJa2AO/CQ30XGn8x9lQlw5n8DzPIC/TcT1/jd7nGSPDQXtXh9Mt8EnrcpyVU0E3ml0+RDbGCFF4sKJ0W5vcSGqnLKKMEP0hT7IGHXNljtEouT+CQa1pLfEmLvZPhbbbLwXul79LDJOt1UbDE7qPAOCSWOqp5azAqmZT06Z7Yq1h3bU05xRFhV/bkAnTwb8ALqzYtNJsbaMjQ+bp36c8bvaJShC6gLNHnDepOFRlTJJ7O4Y3szWRcke/iIyiw+4ndpS2Zd0L1EZ9Kx7dVeudpbbcmlDLwva0hsl6FimnlVqO13yFJZ1Gz7vSf11PuIG8e9hrXf1mKXVeDsCtV+O5nfOyELXTx0hdp+Txyf4UmcXaE125PtZ9/khUKh8L94Ap3giAaNUZJzAAAAAElFTkSuQmCC\" alt=\"h^2\" style=\"width: 15.5px; height: 19.5px;\" width=\"15.5\" height=\"19.5\"\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: 53.3px 7.91667px; transform-origin: 53.3px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e and higher gives\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 38.5833px; 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 19.2917px; text-align: left; transform-origin: 384px 19.2917px; 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: 13.5917px 7.91667px; transform-origin: 13.5917px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e       \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"vertical-align:-15px\"\u003e\u003cimg src=\"data:image/png;base64,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\" alt=\"f' = (f_{j+1} - f_j)/h - hf''/2\" style=\"width: 130px; height: 38.5px;\" width=\"130\" height=\"38.5\"\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: 81.3px 7.91667px; transform-origin: 81.3px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eBecause the exponent on \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: \u0026quot;STIXGeneral\u0026quot;, \u0026quot;STIXGeneral-webfont\u0026quot;, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003eh\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: 191.35px 7.91667px; transform-origin: 191.35px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e in the last term is 1, the method is called a first order method.\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"block-size: 63px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 2px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 2px; perspective-origin: 384px 31.5px; text-align: left; transform-origin: 384px 31.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; \"\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 110.717px 7.91667px; transform-origin: 110.717px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003eWrite a function that takes the order\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: 1.94167px 7.91667px; transform-origin: 1.94167px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"font-family: \u0026quot;STIXGeneral\u0026quot;, \u0026quot;STIXGeneral-webfont\u0026quot;, serif; font-style: italic; font-weight: 400; color: rgb(0, 0, 0);\"\u003en\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: 91.7917px 7.91667px; transform-origin: 91.7917px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e of the derivative and 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: 1.94167px 7.91667px; transform-origin: 1.94167px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eterms\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: 130.3px 7.91667px; transform-origin: 130.3px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e indicating the terms to use (based on the number of grid cells away from the point in question) and produces a vector of coefficients, the order of the error term, and the numerical coefficient of the error term. In the above example,\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: 1.94167px 7.91667px; transform-origin: 1.94167px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 19.25px 7.91667px; transform-origin: 19.25px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003en = 1\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: 13.6167px 7.91667px; transform-origin: 13.6167px 7.91667px; 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: 1.94167px 7.91667px; transform-origin: 1.94167px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e \u003c/span\u003e\u003c/span\u003e\u003cspan style=\"block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 50.05px 7.91667px; transform-origin: 50.05px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"font-family: Menlo, Monaco, Consolas, \u0026quot;Courier New\u0026quot;, monospace; \"\u003eterms = [1 0]\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: 15.5583px 7.91667px; transform-origin: 15.5583px 7.91667px; unicode-bidi: normal; \"\u003e\u003cspan style=\"\"\u003e, and\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: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; 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: 69.3px 7.91667px; transform-origin: 69.3px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e coeffs   = [1 -1]\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; 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: 50.05px 7.91667px; transform-origin: 50.05px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e errOrder = 1\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003cdiv style=\"background-color: rgba(0, 0, 0, 0); block-size: 20.4333px; border-bottom-left-radius: 0px; border-bottom-right-radius: 0px; border-end-end-radius: 0px; border-end-start-radius: 0px; border-inline-end-color: rgb(233, 233, 233); border-inline-end-style: solid; border-inline-end-width: 0.833333px; border-inline-start-color: rgb(233, 233, 233); border-inline-start-style: solid; border-inline-start-width: 0.833333px; border-left-color: rgb(233, 233, 233); border-left-style: solid; border-left-width: 0.833333px; border-right-color: rgb(233, 233, 233); border-right-style: solid; border-right-width: 0.833333px; 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: 65.45px 7.91667px; transform-origin: 65.45px 7.91667px; unicode-bidi: normal; white-space: pre; margin-right: 45px; \"\u003e\u003cspan style=\"margin-inline-end: 0px; margin-right: 0px; \"\u003e errCoeff = -0.5;\u003c/span\u003e\u003c/span\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e","function_template":"function [coeff,errOrder,errCoeff] = FDderiv(n,terms)\r\n%  n        = order of the derivative sought\r\n%  terms    = grid indices of terms to include\r\n%  coeff    = coefficients of the terms in the formula \r\n%  errOrder = exponent of h in the first non-zero higher-order term\r\n%  errCoeff = coefficient of the first non-zero higher-order term\r\n\r\n  coeff    = ...\r\n  errOrder = ...\r\n  errCoeff = ...\r\nend","test_suite":"%%\r\n%  First-order forward difference for the first derivative\r\nn = 1;\r\nterms = [1 0];\r\ncoeff_correct = [1 -1];\r\nerrOrder_correct = 1;\r\nerrCoeff_correct = -1/2;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  First-order backward difference for the first derivative\r\nn = 1;\r\nterms = [0 -1];\r\ncoeff_correct = [1 -1];\r\nerrOrder_correct = 1;\r\nerrCoeff_correct = 1/2;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  Second-order centered difference for the first derivative\r\nn = 1;\r\nterms = [1 -1];\r\ncoeff_correct = [1/2 -1/2];\r\nerrOrder_correct = 2;\r\nerrCoeff_correct = -1/6;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  Second-order forward difference for the first derivative\r\nn = 1;\r\nterms = [2 1 0];\r\ncoeff_correct = [-1/2 2 -3/2];\r\nerrOrder_correct = 2;\r\nerrCoeff_correct = 1/3;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  Second-order backward difference for the first derivative\r\nn = 1;\r\nterms = [0 -1 -2];\r\ncoeff_correct = [3/2 -2 1/2];\r\nerrOrder_correct = 2;\r\nerrCoeff_correct = 1/3;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  Fourth-order centered difference for the first derivative\r\nn = 1;\r\nterms = [2 1 0 -1 -2];\r\ncoeff_correct = [-1 8 0 -8 1]/12\r\nerrOrder_correct = 4;\r\nerrCoeff_correct = 1/30;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  Second-order centered difference for the second derivative\r\nn = 2;\r\nterms = [1 0 -1];\r\ncoeff_correct = [1 -2 1];\r\nerrOrder_correct = 2;\r\nerrCoeff_correct = -1/12;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  Fourth-order centered difference for the second derivative\r\nn = 2;\r\nterms = [2 1 0 -1 -2];\r\ncoeff_correct = [-1 16 -30 16 -1]/12;\r\nerrOrder_correct = 4;\r\nerrCoeff_correct = 1/90;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  Second-order centered difference for the third derivative\r\nn = 3;\r\nterms = [2 1 0 -1 -2];\r\ncoeff_correct = [1/2 -1 0 1 -1/2];\r\nerrOrder_correct = 2;\r\nerrCoeff_correct = -1/4;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)\r\n\r\n%%\r\n%  Second-order centered difference for the fourth derivative\r\nn = 4;\r\nterms = [2 1 0 -1 -2];\r\ncoeff_correct = [1 -4 6 -4 1];\r\nerrOrder_correct = 2;\r\nerrCoeff_correct = -1/6;\r\n[coeff,errOrder,errCoeff] = FDderiv(n,terms);\r\nassert(all(abs(coeff-coeff_correct) \u003c 1e-6))\r\nassert(isequal(errOrder,errOrder_correct))\r\nassert(abs((errCoeff-errCoeff_correct)/errCoeff_correct) \u003c 1e-4)","published":true,"deleted":false,"likes_count":0,"comments_count":0,"created_by":46909,"edited_by":null,"edited_at":null,"deleted_by":null,"deleted_at":null,"solvers_count":2,"test_suite_updated_at":null,"rescore_all_solutions":false,"group_id":1,"created_at":"2020-07-22T03:37:57.000Z","updated_at":"2020-11-15T13:41:30.000Z","published_at":"2020-07-22T05:20:57.000Z","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\u003eIn solving a differential equation with a finite-difference method, one computes derivatives with various combinations of the function's values at chosen grid points. For example, the forward difference formula for the first derivative is\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:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"f' = (f_{j+1} - f_j})/h\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ef\\\\prime=\\\\frac{f_{j+1}-f_j}{h}\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003ewhere j is the grid index and h is the spacing between points. The systematic approach for deriving such formulas is to\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:hyperlink w:docLocation=\\\"http://www2.math.umd.edu/~dlevy/classes/amsc466/lecture-notes/differentiation-chap.pdf\\\"\u003e\u003cw:r\u003e\u003cw:t\u003euse Taylor series\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:hyperlink\u003e\u003cw:r\u003e\u003cw:t\u003e. In the example above, one can write\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:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"f_{j+1} = f_j + hf' + h^2 f''/2 + h^3 f'''/6 + ...\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e f_{j+1} = f_j + h f\\\\prime +  \\\\frac{h^2}{2}f\\\\prime\\\\prime +  \\\\frac{h^3}{6}f\\\\prime\\\\prime\\\\prime + \\\\ldots\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eThen solving for \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"f'\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e$f\\\\prime$\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e and neglecting terms of order \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"h^2\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003e$h^2$\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e and higher gives\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:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"true\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"f' = (f_{j+1} - f_j)/h - hf''/2\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003ef\\\\prime = \\\\frac{f_{j+1} - f_j}{h} - \\\\frac{h}{2}f\\\\prime\\\\prime\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eBecause the exponent on \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"h\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003eh\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e in the last term is 1, the method is called a first order method.\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:p\u003e\u003cw:p\u003e\u003cw:pPr\u003e\u003cw:pStyle w:val=\\\"text\\\"/\u003e\u003cw:jc w:val=\\\"left\\\"/\u003e\u003c/w:pPr\u003e\u003cw:r\u003e\u003cw:t\u003eWrite a function that takes the order\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:customXml w:element=\\\"equation\\\"\u003e\u003cw:customXmlPr\u003e\u003cw:attr w:name=\\\"displayStyle\\\" w:val=\\\"false\\\"/\u003e\u003cw:attr w:name=\\\"altTextString\\\" w:val=\\\"n\\\"/\u003e\u003c/w:customXmlPr\u003e\u003cw:r\u003e\u003cw:t\u003en\u003c/w:t\u003e\u003c/w:r\u003e\u003c/w:customXml\u003e\u003cw:r\u003e\u003cw:t\u003e of the derivative and a vector\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\u003eterms\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e indicating the terms to use (based on the number of grid cells away from the point in question) and produces a vector of coefficients, the order of the error term, and the numerical coefficient of the error term. In the above example,\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\u003en = 1\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e and\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e \u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:rPr\u003e\u003cw:rFonts w:cs=\\\"monospace\\\"/\u003e\u003c/w:rPr\u003e\u003cw:t\u003eterms = [1 0]\u003c/w:t\u003e\u003c/w:r\u003e\u003cw:r\u003e\u003cw:t\u003e, and\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[ coeffs   = [1 -1]\\n errOrder = 1\\n errCoeff = 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