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tatami bindings for k-means

Unit tests Documentation Codecov

Overview

This library implements a wrapper class to use tatami::Matrix instances in the kmeans library. The goal is to support k-means clustering from alternative matrix representations (e.g., sparse, file-backed) without requiring realization into a kmeans::SimpleMatrix.

Quick start

Not much to say, really. Just replace the usual kmeans::SimpleMatrix with an instance of a kmeans_tatami::Matrix.

#include "kmeans_tatami/kmeans_tatami.hpp"

// Initialize this with an instance of a concrete tatami subclass.
std::shared_ptr<tatami::Matrix<double, int> > tmat;

kmeans_tatami::Matrix<int, double, double, int> wrapper(std::move(tmat));
auto res = kmeans::compute(
    wrapper,
    kmeans::InitializeKmeanspp<int, double, int, double>(),
    kmeans::RefineHartiganWong<int, double, int, double>(),
    /* k = */ 10
);

See the reference documentation for more details.

Building projects

CMake with FetchContent

If you're using CMake, you just need to add something like this to your CMakeLists.txt:

include(FetchContent)

FetchContent_Declare(
  kmeans_tatami
  GIT_REPOSITORY https://github.com/libscran/kmeans_tatami
  GIT_TAG master # or any version of interest
)

FetchContent_MakeAvailable(kmeans_tatami)

Then you can link to kmeans_tatami to make the headers available during compilation:

# For executables:
target_link_libraries(myexe libscran::kmeans_tatami)

# For libaries
target_link_libraries(mylib INTERFACE libscran::kmeans_tatami)

By default, this will use FetchContent to fetch all external dependencies. Applications are advised to pin the versions of each dependency for stability - see extern/CMakeLists.txt for suggested versions. If you want to install them manually, use -DKMEANS_TATAMI_FETCH_EXTERN=OFF.

CMake with find_package()

To install the library, clone an appropriate version of this repository and run:

mkdir build && cd build
cmake .. -DKMEANS_TATAMI_TESTS=OFF
cmake --build . --target install

Then we can use find_package() as usual:

find_package(libscran_kmeans_tatami CONFIG REQUIRED)
target_link_libraries(mylib INTERFACE libscran::kmeans_tatami)

Again, this will automatically acquire all its dependencies, see recommendations above.

Manual

If you're not using CMake, the simple approach is to just copy the files in include/ - either directly or with Git submodules - and include their path during compilation with, e.g., GCC's -I. This requires the external dependencies listed in extern/CMakeLists.txt.

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Wrapping tatami for k-means clustering

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