From 61e5bcef2629e2d68b805a956a96fff264d4f74d Mon Sep 17 00:00:00 2001
From: untodesu <kirill@untode.su>
Date: Sat, 28 Jun 2025 01:59:49 +0500
Subject: Restructure dependencies and update to C++20 - Nuked static_assert
 from almost everywhere in the project - Nuked binary dependency support.
 Might add one later though - Separated dependency headers into a separate
 include subdirectory - Grafted a thirdpartylegalnotices.txt generator from
 RITEG - Pushed development snapshot version to 2126 (26th week of 2025)

---
 deps/include/glm/gtx/matrix_factorisation.inl | 84 ---------------------------
 1 file changed, 84 deletions(-)
 delete mode 100644 deps/include/glm/gtx/matrix_factorisation.inl

(limited to 'deps/include/glm/gtx/matrix_factorisation.inl')

diff --git a/deps/include/glm/gtx/matrix_factorisation.inl b/deps/include/glm/gtx/matrix_factorisation.inl
deleted file mode 100644
index 6f1683c..0000000
--- a/deps/include/glm/gtx/matrix_factorisation.inl
+++ /dev/null
@@ -1,84 +0,0 @@
-/// @ref gtx_matrix_factorisation
-
-namespace glm
-{
-	template <length_t C, length_t R, typename T, qualifier Q>
-	GLM_FUNC_QUALIFIER mat<C, R, T, Q> flipud(mat<C, R, T, Q> const& in)
-	{
-		mat<R, C, T, Q> tin = transpose(in);
-		tin = fliplr(tin);
-		mat<C, R, T, Q> out = transpose(tin);
-
-		return out;
-	}
-
-	template <length_t C, length_t R, typename T, qualifier Q>
-	GLM_FUNC_QUALIFIER mat<C, R, T, Q> fliplr(mat<C, R, T, Q> const& in)
-	{
-		mat<C, R, T, Q> out;
-		for (length_t i = 0; i < C; i++)
-		{
-			out[i] = in[(C - i) - 1];
-		}
-
-		return out;
-	}
-
-	template <length_t C, length_t R, typename T, qualifier Q>
-	GLM_FUNC_QUALIFIER void qr_decompose(mat<C, R, T, Q> const& in, mat<(C < R ? C : R), R, T, Q>& q, mat<C, (C < R ? C : R), T, Q>& r)
-	{
-		// Uses modified Gram-Schmidt method
-		// Source: https://en.wikipedia.org/wiki/Gram%E2%80%93Schmidt_process
-		// And https://en.wikipedia.org/wiki/QR_decomposition
-
-		//For all the linearly independs columns of the input...
-		// (there can be no more linearly independents columns than there are rows.)
-		for (length_t i = 0; i < (C < R ? C : R); i++)
-		{
-			//Copy in Q the input's i-th column.
-			q[i] = in[i];
-
-			//j = [0,i[
-			// Make that column orthogonal to all the previous ones by substracting to it the non-orthogonal projection of all the previous columns.
-			// Also: Fill the zero elements of R
-			for (length_t j = 0; j < i; j++)
-			{
-				q[i] -= dot(q[i], q[j])*q[j];
-				r[j][i] = 0;
-			}
-
-			//Now, Q i-th column is orthogonal to all the previous columns. Normalize it.
-			q[i] = normalize(q[i]);
-
-			//j = [i,C[
-			//Finally, compute the corresponding coefficients of R by computing the projection of the resulting column on the other columns of the input.
-			for (length_t j = i; j < C; j++)
-			{
-				r[j][i] = dot(in[j], q[i]);
-			}
-		}
-	}
-
-	template <length_t C, length_t R, typename T, qualifier Q>
-	GLM_FUNC_QUALIFIER void rq_decompose(mat<C, R, T, Q> const& in, mat<(C < R ? C : R), R, T, Q>& r, mat<C, (C < R ? C : R), T, Q>& q)
-	{
-		// From https://en.wikipedia.org/wiki/QR_decomposition:
-		// The RQ decomposition transforms a matrix A into the product of an upper triangular matrix R (also known as right-triangular) and an orthogonal matrix Q. The only difference from QR decomposition is the order of these matrices.
-		// QR decomposition is Gram-Schmidt orthogonalization of columns of A, started from the first column.
-		// RQ decomposition is Gram-Schmidt orthogonalization of rows of A, started from the last row.
-
-		mat<R, C, T, Q> tin = transpose(in);
-		tin = fliplr(tin);
-
-		mat<R, (C < R ? C : R), T, Q> tr;
-		mat<(C < R ? C : R), C, T, Q> tq;
-		qr_decompose(tin, tq, tr);
-
-		tr = fliplr(tr);
-		r = transpose(tr);
-		r = fliplr(r);
-
-		tq = fliplr(tq);
-		q = transpose(tq);
-	}
-} //namespace glm
-- 
cgit