From a82d08973f09f951e1de016ed8c1137663e7a58c Mon Sep 17 00:00:00 2001 From: David Plowman Date: Mon, 27 Mar 2023 13:20:25 +0100 Subject: ipa: raspberrypi: alsc: Use a better type name for sparse arrays The algorithm uses the data type std::vector> to represent the large sparse matrices that are XY (X, Y being the ALSC grid size) high but with only 4 non-zero elements on each row. Replace this slightly long type name by SparseArray. No functional changes. Signed-off-by: David Plowman Reviewed-by: Naushir Patuck Reviewed-by: Jacopo Mondi Signed-off-by: Kieran Bingham --- src/ipa/raspberrypi/controller/rpi/alsc.cpp | 24 ++++++++++++------------ src/ipa/raspberrypi/controller/rpi/alsc.h | 10 +++++++++- 2 files changed, 21 insertions(+), 13 deletions(-) (limited to 'src/ipa') diff --git a/src/ipa/raspberrypi/controller/rpi/alsc.cpp b/src/ipa/raspberrypi/controller/rpi/alsc.cpp index 524c4809..3a2e8fe0 100644 --- a/src/ipa/raspberrypi/controller/rpi/alsc.cpp +++ b/src/ipa/raspberrypi/controller/rpi/alsc.cpp @@ -607,7 +607,7 @@ static double computeWeight(double Ci, double Cj, double sigma) /* Compute all weights. */ static void computeW(const Array2D &C, double sigma, - std::vector> &W) + SparseArray &W) { size_t XY = C.size(); size_t X = C.dimensions().width; @@ -623,8 +623,8 @@ static void computeW(const Array2D &C, double sigma, /* Compute M, the large but sparse matrix such that M * lambdas = 0. */ static void constructM(const Array2D &C, - const std::vector> &W, - std::vector> &M) + const SparseArray &W, + SparseArray &M) { size_t XY = C.size(); size_t X = C.dimensions().width; @@ -651,37 +651,37 @@ static void constructM(const Array2D &C, * left/right neighbours are zero down the left/right edges, so we don't need * need to test the i value to exclude them. */ -static double computeLambdaBottom(int i, const std::vector> &M, +static double computeLambdaBottom(int i, const SparseArray &M, Array2D &lambda) { return M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + lambda.dimensions().width] + M[i][3] * lambda[i - 1]; } -static double computeLambdaBottomStart(int i, const std::vector> &M, +static double computeLambdaBottomStart(int i, const SparseArray &M, Array2D &lambda) { return M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + lambda.dimensions().width]; } -static double computeLambdaInterior(int i, const std::vector> &M, +static double computeLambdaInterior(int i, const SparseArray &M, Array2D &lambda) { return M[i][0] * lambda[i - lambda.dimensions().width] + M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + lambda.dimensions().width] + M[i][3] * lambda[i - 1]; } -static double computeLambdaTop(int i, const std::vector> &M, +static double computeLambdaTop(int i, const SparseArray &M, Array2D &lambda) { return M[i][0] * lambda[i - lambda.dimensions().width] + M[i][1] * lambda[i + 1] + M[i][3] * lambda[i - 1]; } -static double computeLambdaTopEnd(int i, const std::vector> &M, +static double computeLambdaTopEnd(int i, const SparseArray &M, Array2D &lambda) { return M[i][0] * lambda[i - lambda.dimensions().width] + M[i][3] * lambda[i - 1]; } /* Gauss-Seidel iteration with over-relaxation. */ -static double gaussSeidel2Sor(const std::vector> &M, double omega, +static double gaussSeidel2Sor(const SparseArray &M, double omega, Array2D &lambda, double lambdaBound) { int XY = lambda.size(); @@ -753,8 +753,8 @@ static void reaverage(Array2D &data) static void runMatrixIterations(const Array2D &C, Array2D &lambda, - const std::vector> &W, - std::vector> &M, double omega, + const SparseArray &W, + SparseArray &M, double omega, unsigned int nIter, double threshold, double lambdaBound) { constructM(C, W, M); @@ -813,7 +813,7 @@ void Alsc::doAlsc() { Array2D &cr = tmpC_[0], &cb = tmpC_[1], &calTableR = tmpC_[2], &calTableB = tmpC_[3], &calTableTmp = tmpC_[4]; - std::vector> &wr = tmpM_[0], &wb = tmpM_[1], &M = tmpM_[2]; + SparseArray &wr = tmpM_[0], &wb = tmpM_[1], &M = tmpM_[2]; /* * Calculate our R/B ("Cr"/"Cb") colour statistics, and assess which are diff --git a/src/ipa/raspberrypi/controller/rpi/alsc.h b/src/ipa/raspberrypi/controller/rpi/alsc.h index 1ab61299..0b6d9478 100644 --- a/src/ipa/raspberrypi/controller/rpi/alsc.h +++ b/src/ipa/raspberrypi/controller/rpi/alsc.h @@ -68,6 +68,14 @@ private: std::vector data_; }; +/* + * We'll use the term SparseArray for the large sparse matrices that are + * XY tall but have only 4 non-zero elements on each row. + */ + +template +using SparseArray = std::vector>; + struct AlscCalibration { double ct; Array2D table; @@ -160,7 +168,7 @@ private: /* Temporaries for the computations */ std::array, 5> tmpC_; - std::array>, 3> tmpM_; + std::array, 3> tmpM_; }; } /* namespace RPiController */ -- cgit v1.2.1