Problem 55250. Find the minimum of the column-maximums of a matrix

Created by Matt Tearle

Solve Later

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Beneath that is the single minimum value of the row vector.\"/><w:attr w:name=\"relationshipId\" w:val=\"rId1\"/></w:customXmlPr></w:customXml></w:p><w:p><w:pPr><w:pStyle w:val=\"code\"/></w:pPr><w:r><w:t><![CDATA[A = [5 3 4 3;1 2 6 3;1 1 4 4];\nm = minimax(A)\nm =\n    3]]></w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/><w:jc w:val=\"left\"/></w:pPr><w:r><w:t>Note that your function should work for matrices with one row or column (ie vectors) and scalars (in which case m = A).</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/><w:jc w:val=\"left\"/></w:pPr><w:customXml w:element=\"image\"><w:customXmlPr><w:attr w:name=\"height\" w:val=\"279\"/><w:attr w:name=\"width\" w:val=\"583\"/><w:attr w:name=\"verticalAlign\" w:val=\"baseline\"/><w:attr w:name=\"altText\" w:val=\"On the left, a 3-by-1 column vector; underneath is the scalar maximum value; under that is the minimum, which is the same value. On the right, a 1-by-4 row vector; underneath that is the same vector (representing the column maximums); under that is the minimum value.\"/><w:attr w:name=\"relationshipId\" 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","relationship":null},{"partUri":"/media/image2.png","contentType":"image/png","content":"data:image/png;base64,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<div 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; "><div style="block-size: 751.733px; display: block; min-width: 0px; padding-block-start: 0px; padding-top: 0px; perspective-origin: 407px 375.867px; transform-origin: 407px 375.867px; vertical-align: baseline; "><div 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; "><span style="block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 383.5px 8px; transform-origin: 383.5px 8px; unicode-bidi: normal; "><span style="">Given a matrix A, find the maximum value of each column, then return the smallest of those maximum values (ie return the minimum of the column maximums).</span></span></div><div style="block-size: 284.5px; 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 142.25px; text-align: left; transform-origin: 384px 142.25px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; "><img class="imageNode" style="vertical-align: baseline;width: 337px;height: 279px" 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" alt="A 3-by-4 matrix. Beneath it is a 1-by-4 row vector with the maximum value of each column of the matrix independently. Beneath that is the single minimum value of the row vector." data-image-state="image-loaded" width="337" height="279"></div><div style="background-color: rgb(247, 247, 247); block-size: 81.7333px; border-bottom-left-radius: 4px; border-bottom-right-radius: 4px; border-end-end-radius: 4px; border-end-start-radius: 4px; border-start-end-radius: 4px; border-start-start-radius: 4px; border-top-left-radius: 4px; border-top-right-radius: 4px; margin-block-end: 10px; margin-block-start: 10px; margin-bottom: 10px; margin-inline-end: 3px; margin-inline-start: 3px; margin-left: 3px; margin-right: 3px; margin-top: 10px; perspective-origin: 404px 40.8667px; transform-origin: 404px 40.8667px; margin-left: 3px; margin-top: 10px; margin-bottom: 10px; margin-right: 3px; "><div 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; "><span 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: 120px 8.5px; tab-size: 4; transform-origin: 120px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; "><span style="margin-inline-end: 0px; margin-right: 0px; ">A = [5 3 4 3;1 2 6 3;1 1 4 4];</span></span></div><div 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; "><span style="block-size: auto; border-inline-end-color: rgb(0, 0, 0); border-inline-end-style: none; border-inline-end-width: 0px; border-inline-start-color: rgb(0, 0, 0); border-inline-start-style: none; border-inline-start-width: 0px; border-left-color: rgb(0, 0, 0); border-left-style: none; border-left-width: 0px; border-right-color: rgb(0, 0, 0); border-right-style: none; border-right-width: 0px; display: inline; margin-inline-end: 45px; margin-right: 45px; min-block-size: 0px; min-height: 0px; padding-inline-start: 0px; padding-left: 0px; perspective-origin: 56px 8.5px; tab-size: 4; transform-origin: 56px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; "><span style="margin-inline-end: 0px; margin-right: 0px; ">m = minimax(A)</span></span></div><div 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; "><span 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: 12px 8.5px; tab-size: 4; transform-origin: 12px 8.5px; unicode-bidi: normal; white-space: pre; margin-right: 45px; "><span style="margin-inline-end: 0px; margin-right: 0px; ">m =</span></span></div><div 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; "><span 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; "><span style="margin-inline-end: 0px; margin-right: 0px; ">    3</span></span></div></div><div style="block-size: 21px; font-family: Helvetica, Arial, sans-serif; line-height: 21px; margin-block-end: 9px; margin-block-start: 10px; margin-bottom: 9px; margin-inline-end: 10px; margin-inline-start: 4px; margin-left: 4px; margin-right: 10px; margin-top: 10px; perspective-origin: 384px 10.5px; text-align: left; transform-origin: 384px 10.5px; white-space: pre-wrap; margin-left: 4px; margin-top: 10px; margin-bottom: 9px; margin-right: 10px; "><span style="block-size: auto; display: inline; margin-block-end: 0px; margin-block-start: 0px; margin-bottom: 0px; margin-inline-end: 0px; margin-inline-start: 0px; margin-left: 0px; margin-right: 0px; margin-top: 0px; perspective-origin: 371px 8px; transform-origin: 371px 8px; unicode-bidi: normal; "><span style="">Note that your function should work for matrices with one row or column (ie vectors) and scalars (in which case m = A).</span></span></div><div style="block-size: 284.5px; 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 142.25px; text-align: left; transform-origin: 384px 142.25px; white-space: pre-wrap; margin-left: 4px; margin-top: 2px; margin-bottom: 9px; margin-right: 10px; "><img class="imageNode" style="vertical-align: baseline;width: 583px;height: 279px" 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" alt="On the left, a 3-by-1 column vector; underneath is the scalar maximum value; under that is the minimum, which is the same value. On the right, a 1-by-4 row vector; underneath that is the same vector (representing the column maximums); under that is the minimum value." data-image-state="image-loaded" width="583" height="279"></div></div></div>

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Last Solution submitted on Jan 30, 2023

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2 Comments

Neha Shaah on 22 Oct 2022

Test suite 9 fails - min logic used

Matt Tearle on 24 Oct 2022

@Neha Shaah: how so? If the input is a row vector, the column maximums will be the elements themselves. Hence the minimum will be the minimum of the input vector itself.

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Problem 55250. Find the minimum of the column-maximums of a matrix

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Problem 55250. Find the minimum of the column-maximums of a matrix

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