{"id":18474,"url":"https://patchwork.libcamera.org/api/patches/18474/?format=json","web_url":"https://patchwork.libcamera.org/patch/18474/","project":{"id":1,"url":"https://patchwork.libcamera.org/api/projects/1/?format=json","name":"libcamera","link_name":"libcamera","list_id":"libcamera_core","list_email":"libcamera-devel@lists.libcamera.org","web_url":"","scm_url":"","webscm_url":""},"msgid":"<20230327122030.11756-6-naush@raspberrypi.com>","date":"2023-03-27T12:20:25","name":"[libcamera-devel,v2,05/10] ipa: raspberrypi: alsc: Use a better type name for sparse arrays","commit_ref":null,"pull_url":null,"state":"superseded","archived":false,"hash":"c0eddf9838a1b38bca38c4fdf6282a7f8f921581","submitter":{"id":34,"url":"https://patchwork.libcamera.org/api/people/34/?format=json","name":"Naushir Patuck","email":"naush@raspberrypi.com"},"delegate":null,"mbox":"https://patchwork.libcamera.org/patch/18474/mbox/","series":[{"id":3819,"url":"https://patchwork.libcamera.org/api/series/3819/?format=json","web_url":"https://patchwork.libcamera.org/project/libcamera/list/?series=3819","date":"2023-03-27T12:20:20","name":"Raspberry Pi: Generalised algorithms","version":2,"mbox":"https://patchwork.libcamera.org/series/3819/mbox/"}],"comments":"https://patchwork.libcamera.org/api/patches/18474/comments/","check":"pending","checks":"https://patchwork.libcamera.org/api/patches/18474/checks/","tags":{},"headers":{"Return-Path":"","X-Original-To":"parsemail@patchwork.libcamera.org","Delivered-To":"parsemail@patchwork.libcamera.org","Received":["from lancelot.ideasonboard.com (lancelot.ideasonboard.com\n\t[92.243.16.209])\n\tby patchwork.libcamera.org (Postfix) with ESMTPS id EE1FDC326C\n\tfor ;\n\tMon, 27 Mar 2023 12:20:51 +0000 (UTC)","from lancelot.ideasonboard.com (localhost 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05:20:45 -0700 (PDT)","To":"libcamera-devel@lists.libcamera.org","Date":"Mon, 27 Mar 2023 13:20:25 +0100","Message-Id":"<20230327122030.11756-6-naush@raspberrypi.com>","X-Mailer":"git-send-email 2.34.1","In-Reply-To":"<20230327122030.11756-1-naush@raspberrypi.com>","References":"<20230327122030.11756-1-naush@raspberrypi.com>","MIME-Version":"1.0","Content-Transfer-Encoding":"8bit","Subject":"[libcamera-devel] [PATCH v2 05/10] ipa: raspberrypi: alsc: Use a\n\tbetter type name for sparse arrays","X-BeenThere":"libcamera-devel@lists.libcamera.org","X-Mailman-Version":"2.1.29","Precedence":"list","List-Id":"","List-Unsubscribe":",\n\t","List-Archive":"","List-Post":"","List-Help":"","List-Subscribe":",\n\t","From":"Naushir Patuck via libcamera-devel\n\t","Reply-To":"Naushir Patuck ","Cc":"Jacopo Mondi ","Errors-To":"libcamera-devel-bounces@lists.libcamera.org","Sender":"\"libcamera-devel\" "},"content":"From: David Plowman \n\nThe algorithm uses the data type std::vector> to\nrepresent the large sparse matrices that are XY (X, Y being the ALSC\ngrid size) high but with only 4 non-zero elements on each row.\n\nReplace this slightly long type name by SparseArray.\n\nNo functional changes.\n\nSigned-off-by: David Plowman \nReviewed-by: Naushir Patuck \nReviewed-by: Jacopo Mondi \n---\n src/ipa/raspberrypi/controller/rpi/alsc.cpp | 24 ++++++++++-----------\n src/ipa/raspberrypi/controller/rpi/alsc.h | 10 ++++++++-\n 2 files changed, 21 insertions(+), 13 deletions(-)","diff":"diff --git a/src/ipa/raspberrypi/controller/rpi/alsc.cpp b/src/ipa/raspberrypi/controller/rpi/alsc.cpp\nindex 524c48093590..3a2e8fe00ca6 100644\n--- a/src/ipa/raspberrypi/controller/rpi/alsc.cpp\n+++ b/src/ipa/raspberrypi/controller/rpi/alsc.cpp\n@@ -607,7 +607,7 @@ static double computeWeight(double Ci, double Cj, double sigma)\n \n /* Compute all weights. */\n static void computeW(const Array2D &C, double sigma,\n-\t\t std::vector> &W)\n+\t\t SparseArray &W)\n {\n \tsize_t XY = C.size();\n \tsize_t X = C.dimensions().width;\n@@ -623,8 +623,8 @@ static void computeW(const Array2D &C, double sigma,\n \n /* Compute M, the large but sparse matrix such that M * lambdas = 0. */\n static void constructM(const Array2D &C,\n-\t\t const std::vector> &W,\n-\t\t std::vector> &M)\n+\t\t const SparseArray &W,\n+\t\t SparseArray &M)\n {\n \tsize_t XY = C.size();\n \tsize_t X = C.dimensions().width;\n@@ -651,37 +651,37 @@ static void constructM(const Array2D &C,\n * left/right neighbours are zero down the left/right edges, so we don't need\n * need to test the i value to exclude them.\n */\n-static double computeLambdaBottom(int i, const std::vector> &M,\n+static double computeLambdaBottom(int i, const SparseArray &M,\n \t\t\t\t Array2D &lambda)\n {\n \treturn M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + lambda.dimensions().width] +\n \t M[i][3] * lambda[i - 1];\n }\n-static double computeLambdaBottomStart(int i, const std::vector> &M,\n+static double computeLambdaBottomStart(int i, const SparseArray &M,\n \t\t\t\t Array2D &lambda)\n {\n \treturn M[i][1] * lambda[i + 1] + M[i][2] * lambda[i + lambda.dimensions().width];\n }\n-static double computeLambdaInterior(int i, const std::vector> &M,\n+static double computeLambdaInterior(int i, const SparseArray &M,\n \t\t\t\t Array2D &lambda)\n {\n \treturn M[i][0] * lambda[i - lambda.dimensions().width] + M[i][1] * lambda[i + 1] +\n \t M[i][2] * lambda[i + lambda.dimensions().width] + M[i][3] * lambda[i - 1];\n }\n-static double computeLambdaTop(int i, const std::vector> &M,\n+static double computeLambdaTop(int i, const SparseArray &M,\n \t\t\t Array2D &lambda)\n {\n \treturn M[i][0] * lambda[i - lambda.dimensions().width] + M[i][1] * lambda[i + 1] +\n \t M[i][3] * lambda[i - 1];\n }\n-static double computeLambdaTopEnd(int i, const std::vector> &M,\n+static double computeLambdaTopEnd(int i, const SparseArray &M,\n \t\t\t\t Array2D &lambda)\n {\n \treturn M[i][0] * lambda[i - lambda.dimensions().width] + M[i][3] * lambda[i - 1];\n }\n \n /* Gauss-Seidel iteration with over-relaxation. */\n-static double gaussSeidel2Sor(const std::vector> &M, double omega,\n+static double gaussSeidel2Sor(const SparseArray &M, double omega,\n \t\t\t Array2D &lambda, double lambdaBound)\n {\n \tint XY = lambda.size();\n@@ -753,8 +753,8 @@ static void reaverage(Array2D &data)\n \n static void runMatrixIterations(const Array2D &C,\n \t\t\t\tArray2D &lambda,\n-\t\t\t\tconst std::vector> &W,\n-\t\t\t\tstd::vector> &M, double omega,\n+\t\t\t\tconst SparseArray &W,\n+\t\t\t\tSparseArray &M, double omega,\n \t\t\t\tunsigned int nIter, double threshold, double lambdaBound)\n {\n \tconstructM(C, W, M);\n@@ -813,7 +813,7 @@ void Alsc::doAlsc()\n {\n \tArray2D &cr = tmpC_[0], &cb = tmpC_[1], &calTableR = tmpC_[2],\n \t\t\t&calTableB = tmpC_[3], &calTableTmp = tmpC_[4];\n-\tstd::vector> &wr = tmpM_[0], &wb = tmpM_[1], &M = tmpM_[2];\n+\tSparseArray &wr = tmpM_[0], &wb = tmpM_[1], &M = tmpM_[2];\n \n \t/*\n \t * Calculate our R/B (\"Cr\"/\"Cb\") colour statistics, and assess which are\ndiff --git a/src/ipa/raspberrypi/controller/rpi/alsc.h b/src/ipa/raspberrypi/controller/rpi/alsc.h\nindex 1ab61299c4cd..0b6d9478073c 100644\n--- a/src/ipa/raspberrypi/controller/rpi/alsc.h\n+++ b/src/ipa/raspberrypi/controller/rpi/alsc.h\n@@ -68,6 +68,14 @@ private:\n \tstd::vector data_;\n };\n \n+/*\n+ * We'll use the term SparseArray for the large sparse matrices that are\n+ * XY tall but have only 4 non-zero elements on each row.\n+ */\n+\n+template\n+using SparseArray = std::vector>;\n+\n struct AlscCalibration {\n \tdouble ct;\n \tArray2D table;\n@@ -160,7 +168,7 @@ private:\n \n \t/* Temporaries for the computations */\n \tstd::array, 5> tmpC_;\n-\tstd::array>, 3> tmpM_;\n+\tstd::array, 3> tmpM_;\n };\n \n } /* namespace RPiController */\n","prefixes":["libcamera-devel","v2","05/10"]}