diff options
| -rw-r--r-- | src/ipa/raspberrypi/controller/rpi/alsc.cpp | 24 | ||||
| -rw-r--r-- | src/ipa/raspberrypi/controller/rpi/alsc.h | 10 |
2 files changed, 21 insertions, 13 deletions
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<double> &C, double sigma, - std::vector<std::array<double, 4>> &W) + SparseArray<double> &W) { size_t XY = C.size(); size_t X = C.dimensions().width; @@ -623,8 +623,8 @@ static void computeW(const Array2D<double> &C, double sigma, /* Compute M, the large but sparse matrix such that M * lambdas = 0. */ static void constructM(const Array2D<double> &C, - const std::vector<std::array<double, 4>> &W, - std::vector<std::array<double, 4>> &M) + const SparseArray<double> &W, + SparseArray<double> &M) { size_t XY = C.size(); size_t X = C.dimensions().width; @@ -651,37 +651,37 @@ static void constructM(const Array2D<double> &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<std::array<double, 4>> &M, +static double computeLambdaBottom(int i, const SparseArray<double> &M, Array2D<double> &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<std::array<double, 4>> &M, +static double computeLambdaBottomStart(int i, const SparseArray<double> &M, Array2D<double> &lambda) { return M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + lambda.dimensions().width]; } -static double computeLambdaInterior(int i, const std::vector<std::array<double, 4>> &M, +static double computeLambdaInterior(int i, const SparseArray<double> &M, Array2D<double> &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<std::array<double, 4>> &M, +static double computeLambdaTop(int i, const SparseArray<double> &M, Array2D<double> &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<std::array<double, 4>> &M, +static double computeLambdaTopEnd(int i, const SparseArray<double> &M, Array2D<double> &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<std::array<double, 4>> &M, double omega, +static double gaussSeidel2Sor(const SparseArray<double> &M, double omega, Array2D<double> &lambda, double lambdaBound) { int XY = lambda.size(); @@ -753,8 +753,8 @@ static void reaverage(Array2D<double> &data) static void runMatrixIterations(const Array2D<double> &C, Array2D<double> &lambda, - const std::vector<std::array<double, 4>> &W, - std::vector<std::array<double, 4>> &M, double omega, + const SparseArray<double> &W, + SparseArray<double> &M, double omega, unsigned int nIter, double threshold, double lambdaBound) { constructM(C, W, M); @@ -813,7 +813,7 @@ void Alsc::doAlsc() { Array2D<double> &cr = tmpC_[0], &cb = tmpC_[1], &calTableR = tmpC_[2], &calTableB = tmpC_[3], &calTableTmp = tmpC_[4]; - std::vector<std::array<double, 4>> &wr = tmpM_[0], &wb = tmpM_[1], &M = tmpM_[2]; + SparseArray<double> &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<T> 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<typename T> +using SparseArray = std::vector<std::array<T, 4>>; + struct AlscCalibration { double ct; Array2D<double> table; @@ -160,7 +168,7 @@ private: /* Temporaries for the computations */ std::array<Array2D<double>, 5> tmpC_; - std::array<std::vector<std::array<double, 4>>, 3> tmpM_; + std::array<SparseArray<double>, 3> tmpM_; }; } /* namespace RPiController */ |