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68 lines
2.4 KiB
ReStructuredText
68 lines
2.4 KiB
ReStructuredText
Motivation
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===========================
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.. highlight:: c
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This library provides a multi-dimensionnal array library
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for numerical computations with the following characteristics/goals :
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* **Simplicity of use**.
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Arrays must be as simple to use as in python (numpy) or fortran.
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This library is designed to be used by physicists, not only by professionnal programmers,
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We do *a lot* of array manipulations, and we want to maintain *readable* codes.
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Examples::
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using namespace triqs::arrays; // All classes of this library are here. We will omit in the following
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array<int,3> A(4,2,3); // creating an array
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A(0,1,2) // access an element
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A(range(1,2), range(), 4) // a partial_view (or slice).
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* Various interoperable forms of arrays :
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* array : the general cuboid n-dimensional array, with **custom memory ordering** at compile time.
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* matrix : a matrix class, with C or Fortran order at compile time.
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* vector : a vector class.
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* **Genericity, abstraction and performance** :
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We want to have simple, readeable code, with the same (or better) speed than manually written low level code.
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Most optimisations should be delegated to the library and the compiler.
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For example, we allow the use of **expression templates** for the algebra of arrays or matrices ::
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array<int,2> A(4,2),B(4,2),C;
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// fill A, B....
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C = 2* A + B/2
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Expressions templates allows the elimination of temporaries and hence compact and readable code
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with the speed of manually written codes. Thanks to boost::proto library, this can nowadays be achieved
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while maintaining a good compilation time, and with a short and readable code.
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* **Compilation time** is (at far as tested) kept under control.
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* **Complete interoperability with python numpy arrays**.
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This library is used a lot with mixed C++/python codes.
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It handles quick conversion between the C++ and python world, e.g. :
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* work on a view of a numpy,
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* create a array in C++, and return it as a numpy.
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* mix the various kind of arrays transparently in C++ expressions.
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* **HDF5** : simple interface to hdf5 library for an easy storing/retrieving into/from HDF5 files.
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* **STL compliance**.
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The arrays are compliant with STL (algorithms, std::vector<array<T,N> >, iterators, map, etc...).
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* **Simple interface to Blas/Lapack** for matrices, vectors.
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* **MPI** : compatibility with boost::mpi interface.
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