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"body": "So that the users get the PC scores and the rotation matrix. We also compute\nthe variance explained by each PC, instead of just having the singular values.\n\nRefactored the internals of pca() to a single call to compute(). This involves\nsome fixes to CenteredMatrix and ScaledMatrix to work with smart pointers.",
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"body": "This mostly affects compute() and ParallelSparseMatrix, where some of the\narithmetic and implicit casts for allocations were a bit too relaxed. We add a\ndependency on the sanisizer library to ensure that these calculations are ok.\n\nWe improve the worksharing across threads in ParallelSparseMatrix, a\n[…]\narts/ends into a single vector to reduce memory usage.\nThis involves some renaming of the getters for the per-thread data structures.\n\nFinally, we slapped const on everything to indicate immutability.",
"is_bot": false,
"headline": "Choose better integer types and protect against integer overflow. (#20)",
"author_name": "Aaron Lun",
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"body": "We introduce Matrix and Workspace interfaces that can be inherited from. Each\nMatrix subclass produces instances of various Workspace subclasses, the latter\nof which handles the actual multiplication/realization with non-const\nintermediates. Eigen matrix instances are now wrapped in a SimpleMatrix t\n[…]\npute() functions now only accept a Matrix-compliant object. Eigen matrices\nneed to be supplied to compute_simple() instead. We also rename the PCA function\nto pca(), which also accepts Eigen matrices.",
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"headline": "Overhauled matrix interfaces to support run-time polymorphism. (#19)",
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"body": "- Fiddle with Cmake to get Eigen to build its own install files, otherwise the\n Cmake installation of irlba itself will fail.\n- Switch JacobiSVD options to compile-time parameters. Also use more specific\n SFINAE to detect if a matrix can be directly used in JacobiSVD::compute()\n- Minor testfix as setNbThreads throttles itself to OMP's max threads.",
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"headline": "Updates for compatibility with Eigen 5.0.0. (#18)",
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"headline": "Testfix to make sure that errors are actually thrown on invalid inputs.",
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"headline": "Use the JacobiSVD algorithm everywhere, for consistency.",
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"headline": "Commented on why we use classical Gram-Schmidt instead of the modifie…",
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"body": "The documentation talks about some cursory testing to justify the use of this\nclass, so I should probably keep the tests somewhere before they get lost.",
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"headline": "Added some performance testing for ParallelSparseMatrix. (#15)",
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"body": "Otherwise, the constructor will attempt to coerce its inputs to an ordinary\nEigen matrix. Hopefully this should be a compile-time error, but for sparse\nEigen matrices, this will cause Centered to hold a dangling reference when the\ntemporary Eigen::MatrixXd goes out of scope.",
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"headline": "Bugfix for template parameters passed to the Centered definition.",
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"headline": "Test that the workspaces and output vectors are correctly zeroed.",
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"body": "Done by writing the products into a thread-specific buffer in the Workspaces.",
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"headline": "Protect against false sharing during parallelized sparse multiplication.",
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"body": "This allows developers to use it in more places (e.g., for observation-level\nweighting in PCA) without having to define their own specialized wrappers.",
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"body": "This supports use of find_package in downstream projects to get the new\r\nltla::irlba target; it also enables use of find_package instead of\r\nFetchContent to get CppIrlba's various dependencies.",
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"headline": "Add CMake install targets. (#8)",
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"body": "These utilities can also be used in third-party code to make it easier\nto develop wrappers without manually checking whether the wrapped object\nis an Eigen matrix-like instance or an irlba wrapper class.",
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"body": "Specifically, these are intermediate objects that depend on the RHS in the\r\nwrapper class's multiply or adjoint_multiply methods. We don't want to have to\r\nre-allocate memory for these intermediates upon every call to multiply, so the\r\nidea is to allocate it once in the workspace at the start of the\n[…]\nedWorkspace\r\nclass. This allows wrappers to define their own workspace classes that\r\ncontain the workspace for the wrapped matrix, without needing to worry\r\nabout the exact type of the wrapped matrix.",
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"body": "The requirements inherited from libscran don't really apply here, as the\npartitioning of jobs into workers is already performed by the parallel\nmatrix class; the macro function only needs to launch the jobs.",
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"body": "This allows users to control the number of threads in a RAII-compatible\nmanner. Admittedly, it doesn't really belong here, but short of Eigen\nitself adding a thread-scoping mechanism, this is the best we can do.",
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"body": "This migrates the parallelized sparse matrix from libscran, with some\r\nmodifications for fully templated data representations. It supports\r\nparallelization of sparse multiplication in both orientations relevant to Irlba\r\n(i.e., multiply() and adjoint_multiply()). It also supports parallelization\r\nwith schemes other than OpenMP, for use in environments where OpenMP is not\r\navailable. Of course, OpenMP itself is still supported with explicit num_threads.",
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"headline": "Support custom parallelization for sparse matrix multiplication. (#6)",
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{
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{
"key": "branch_protection",
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{
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