{ "info": { "author": "Dan Maljovec", "author_email": "maljovec002@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Intended Audience :: Science/Research", "License :: OSI Approved :: BSD License", "Programming Language :: C++", "Programming Language :: Python :: 2", "Programming Language :: Python :: 3", "Topic :: Scientific/Engineering :: Mathematics" ], "description": "A Collection of Space-filling Sampling Designs for Arbitrary Dimensions.\nThe API is structured such that the top level packages represent the shape\nof the domain you are interested in:\n\n * ball - The n-dimensional solid unit ball\n * directional - The space of unit length directions in n-dimensional space.\n You can also consider this a sampling of the boundary of the n-dimensional\n unit ball.\n * hypercube - The n-dimensional solid unit hypercube :math:`x \\\\in [0,1]^n`.\n * subspace - Sampling a n-1-dimensional subspace orthogonal to a unit vector\n or sampling the Grassmanian Atlas of projections from a dimension n to a\n lower dimension m.\n * shape - a collection of (n-1)-manifold and non-manifold shapes embedded in\n an n dimensional space. For now these must all be sampled using a uniform\n distribution.\n\nWithin each module is a list of ways to fill the space of the samples.\nNote, that not all of the methods listed below are applicable to the modules\nlisted above. They include:\n\n * Uniform - a random, uniform distribution of points (available for ball,\n directional, hypercube, subspace, and shape)\n * Normal - a Gaussian distribution of points (available for hypercube)\n * Multimodal - a mixture of Gaussian distributions of points (available for hypercube)\n * CVT - an approximate centroidal Voronoi tessellation of the points\n constrained to the given space (available for hypercube and directional)\n * LHS - a Latin hypercube sampling design of points constrained to the space\n (available for hypercube)\n *\n\nThe python CVT code is adapted from a C++ implementation provided by\nCarlos Correa. 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