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<a href="#func-members">Functions</a> </div>
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<div class="title">GLM_GTX_matrix_factorisation<div class="ingroups"><a class="el" href="a00157.html">GTX Extensions (Experimental)</a></div></div> </div>
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</div><!--header-->
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<div class="contents">
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<p>Functions to factor matrices in various forms.
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<a href="#details">More...</a></p>
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<table class="memberdecls">
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a>
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Functions</h2></td></tr>
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<tr class="memitem:ga834fe9f3b29ac4f6636e102dcf6c45be"><td class="memTemplParams" colspan="2">template<length_t C, length_t R, typename T , qualifier P, template< length_t, length_t, typename, qualifier > class matType> </td></tr>
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<tr class="memitem:ga834fe9f3b29ac4f6636e102dcf6c45be"><td class="memTemplItemLeft" align="right" valign="top">GLM_FUNC_DECL matType< C, R, T, P > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="a00209.html#ga834fe9f3b29ac4f6636e102dcf6c45be">fliplr</a> (matType< C, R, T, P > const &in)</td></tr>
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<tr class="memdesc:ga834fe9f3b29ac4f6636e102dcf6c45be"><td class="mdescLeft"> </td><td class="mdescRight">Flips the matrix columns right and left. <a href="a00209.html#ga834fe9f3b29ac4f6636e102dcf6c45be">More...</a><br /></td></tr>
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<tr class="separator:ga834fe9f3b29ac4f6636e102dcf6c45be"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:ga5c0b0b7dde6aef33a8c73376fe00ddc6"><td class="memTemplParams" colspan="2">template<length_t C, length_t R, typename T , qualifier P, template< length_t, length_t, typename, qualifier > class matType> </td></tr>
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<tr class="memitem:ga5c0b0b7dde6aef33a8c73376fe00ddc6"><td class="memTemplItemLeft" align="right" valign="top">GLM_FUNC_DECL matType< C, R, T, P > </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="a00209.html#ga5c0b0b7dde6aef33a8c73376fe00ddc6">flipud</a> (matType< C, R, T, P > const &in)</td></tr>
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<tr class="memdesc:ga5c0b0b7dde6aef33a8c73376fe00ddc6"><td class="mdescLeft"> </td><td class="mdescRight">Flips the matrix rows up and down. <a href="a00209.html#ga5c0b0b7dde6aef33a8c73376fe00ddc6">More...</a><br /></td></tr>
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<tr class="separator:ga5c0b0b7dde6aef33a8c73376fe00ddc6"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:ga3f35a503ef41c16f83cf6cd8a191aca6"><td class="memTemplParams" colspan="2">template<length_t C, length_t R, typename T , qualifier P, template< length_t, length_t, typename, qualifier > class matType> </td></tr>
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<tr class="memitem:ga3f35a503ef41c16f83cf6cd8a191aca6"><td class="memTemplItemLeft" align="right" valign="top">GLM_FUNC_DECL void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="a00209.html#ga3f35a503ef41c16f83cf6cd8a191aca6">qr_decompose</a> (matType< C, R, T, P > const &in, matType<(C< R?C:R), R, T, P > &q, matType< C,(C< R?C:R), T, P > &r)</td></tr>
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<tr class="memdesc:ga3f35a503ef41c16f83cf6cd8a191aca6"><td class="mdescLeft"> </td><td class="mdescRight">Performs QR factorisation of a matrix. <a href="a00209.html#ga3f35a503ef41c16f83cf6cd8a191aca6">More...</a><br /></td></tr>
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<tr class="separator:ga3f35a503ef41c16f83cf6cd8a191aca6"><td class="memSeparator" colspan="2"> </td></tr>
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<tr class="memitem:gac81cf0350006c3f004887fa4fb57880e"><td class="memTemplParams" colspan="2">template<length_t C, length_t R, typename T , qualifier P, template< length_t, length_t, typename, qualifier > class matType> </td></tr>
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<tr class="memitem:gac81cf0350006c3f004887fa4fb57880e"><td class="memTemplItemLeft" align="right" valign="top">GLM_FUNC_DECL void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="a00209.html#gac81cf0350006c3f004887fa4fb57880e">rq_decompose</a> (matType< C, R, T, P > const &in, matType<(C< R?C:R), R, T, P > &r, matType< C,(C< R?C:R), T, P > &q)</td></tr>
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<tr class="memdesc:gac81cf0350006c3f004887fa4fb57880e"><td class="mdescLeft"> </td><td class="mdescRight">Performs RQ factorisation of a matrix. <a href="a00209.html#gac81cf0350006c3f004887fa4fb57880e">More...</a><br /></td></tr>
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<tr class="separator:gac81cf0350006c3f004887fa4fb57880e"><td class="memSeparator" colspan="2"> </td></tr>
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</table>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
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<p>Functions to factor matrices in various forms. </p>
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<p><<a class="el" href="a00067.html" title="GLM_GTX_matrix_factorisation ">glm/gtx/matrix_factorisation.hpp</a>> need to be included to use these functionalities. </p>
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<h2 class="groupheader">Function Documentation</h2>
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<a class="anchor" id="ga834fe9f3b29ac4f6636e102dcf6c45be"></a>
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<td class="memname">GLM_FUNC_DECL matType<C, R, T, P> glm::fliplr </td>
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<td>(</td>
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<td class="paramtype">matType< C, R, T, P > const & </td>
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<td class="paramname"><em>in</em></td><td>)</td>
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<p>Flips the matrix columns right and left. </p>
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<p>From GLM_GTX_matrix_factorisation extension. </p>
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<td class="memname">GLM_FUNC_DECL matType<C, R, T, P> glm::flipud </td>
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<td>(</td>
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<td class="paramtype">matType< C, R, T, P > const & </td>
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<td class="paramname"><em>in</em></td><td>)</td>
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<p>Flips the matrix rows up and down. </p>
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<p>From GLM_GTX_matrix_factorisation extension. </p>
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</div>
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</div>
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<td class="memname">GLM_FUNC_DECL void glm::qr_decompose </td>
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<td>(</td>
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<td class="paramtype">matType< C, R, T, P > const & </td>
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<td class="paramname"><em>in</em></td><td>)</td>
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</div><div class="memdoc">
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<p>Performs QR factorisation of a matrix. </p>
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<p>Returns 2 matrices, q and r, such that the columns of q are orthonormal and span the same subspace than those of the input matrix, r is an upper triangular matrix, and q*r=in. Given an n-by-m input matrix, q has dimensions min(n,m)-by-m, and r has dimensions n-by-min(n,m). From GLM_GTX_matrix_factorisation extension. </p>
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<a class="anchor" id="gac81cf0350006c3f004887fa4fb57880e"></a>
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<td class="memname">GLM_FUNC_DECL void glm::rq_decompose </td>
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<td>(</td>
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<td class="paramtype">matType< C, R, T, P > const & </td>
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<td class="paramname"><em>in</em></td><td>)</td>
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<td></td>
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</table>
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</div><div class="memdoc">
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<p>Performs RQ factorisation of a matrix. </p>
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<p>Returns 2 matrices, r and q, such that r is an upper triangular matrix, the rows of q are orthonormal and span the same subspace than those of the input matrix, and r*q=in. Note that in the context of RQ factorisation, the diagonal is seen as starting in the lower-right corner of the matrix, instead of the usual upper-left. Given an n-by-m input matrix, r has dimensions min(n,m)-by-m, and q has dimensions n-by-min(n,m). From GLM_GTX_matrix_factorisation extension. </p>
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