diff --git a/examples/latin_hypercube.ipynb b/examples/latin_hypercube.ipynb new file mode 100644 index 00000000..e72f9039 --- /dev/null +++ b/examples/latin_hypercube.ipynb @@ -0,0 +1,439 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "af069e13", + "metadata": {}, + "source": [ + "# Latin Hypercube Sampling\n", + "\n", + "The [LatinHypercube](https://grid.qcdevs.org/pyapi/grid.latin_hypercube.html#grid.latin_hypercube.LatinHypercube)\n", + "grid can be used for integration over a (hyper)cubic or parallelepiped domain.\n", + "Unlike the structured, tensor-product grids built from `onedgrid` classes, Latin\n", + "Hypercube Sampling (LHS) stratifies every one-dimensional marginal exactly:\n", + "splitting $[0,1)$ into $N$ equal strata along *any* single coordinate axis places\n", + "exactly one point in each stratum. This is a variance-reduction technique\n", + "(McKay, Beckman & Conover, 1979) rather than a classical quadrature rule, and it\n", + "scales *linearly* in the number of points regardless of dimension -- making it a\n", + "practical choice in the higher-dimensional settings (e.g. many uncertain\n", + "parameters) where tensor-product quadrature becomes infeasible." + ] + }, + { + "cell_type": "markdown", + "id": "7e10f7c2", + "metadata": {}, + "source": [ + "## Initialization of LatinHypercube\n", + "\n", + "`LatinHypercube` is initialized by specifying:\n", + "\n", + "1. `n_points` -- the number of integration points $N$.\n", + "2. `dimension` -- the dimension $d$ of the integration domain.\n", + "3. `seed` (optional) -- for reproducibility.\n", + "4. `randomize` (optional, default `True`) -- if `True`, each point is jittered\n", + " uniformly within its stratum; if `False`, each point is placed at the center\n", + " of its stratum instead.\n", + "5. `origin` and `axes` (optional) -- to map the design from the unit hypercube\n", + " $[0,1)^d$ onto an arbitrary parallelepiped.\n" + ] + }, + { + "cell_type": "markdown", + "id": "46ce3981", + "metadata": {}, + "source": [ + "## A 3D Scatter Plot of the Design\n", + "\n", + "Each 1D projection (onto the x, y, or z axis) still places exactly one point\n", + "per stratum -- a property that is easy to state, but worth seeing directly in\n", + "three dimensions rather than just checking numerically." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "114721bc", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of points: 500\n", + "Points shape: (500, 3)\n" + ] + } + ], + "source": [ + "from grid.latin_hypercube import LatinHypercube\n", + "import numpy as np\n", + "\n", + "lhs3d = LatinHypercube(n_points=500, dimension=3, seed=0)\n", + "print(f\"Number of points: {lhs3d.size}\")\n", + "print(f\"Points shape: {lhs3d.points.shape}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "813058ea", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "from mpl_toolkits.mplot3d import Axes3D # noqa: F401 (registers 3D projection)\n", + "\n", + "fig = plt.figure(figsize=(7, 6))\n", + "ax = fig.add_subplot(111, projection=\"3d\")\n", + "ax.scatter(\n", + " lhs3d.points[:, 0], lhs3d.points[:, 1], lhs3d.points[:, 2],\n", + " s=25, color=\"#2E5C8A\", alpha=0.8, depthshade=True,\n", + ")\n", + "ax.set_xlabel(\"x\")\n", + "ax.set_ylabel(\"y\")\n", + "ax.set_zlabel(\"z\")\n", + "ax.set_title(f\"LatinHypercube: {lhs3d.size} points in $[0,1)^3$\")\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "407e5790", + "metadata": {}, + "source": [ + "Setting `randomize=False` places each point exactly at the center of its\n", + "stratum instead of a random position within it (the assignment of strata to\n", + "dimensions is still randomized -- otherwise every dimension would place its\n", + "points on the same diagonal pattern)." + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "9eea728f", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "lhs_centered = LatinHypercube(n_points=10, dimension=2, seed=0, randomize=False)\n", + "lhs_random = LatinHypercube(n_points=10, dimension=2, seed=0, randomize=True)\n", + "\n", + "import matplotlib.pyplot as plt\n", + "\n", + "fig, axes = plt.subplots(1, 2, figsize=(10, 4.5))\n", + "for ax, grid, title in zip(\n", + " axes, [lhs_random, lhs_centered], [\"randomize=True (jittered)\", \"randomize=False (centered)\"]\n", + "):\n", + " ax.scatter(grid.points[:, 0], grid.points[:, 1], s=60, color=\"#2E5C8A\")\n", + " for k in range(1, n_points):\n", + " ax.axhline(k / n_points, color=\"gray\", lw=0.4)\n", + " ax.axvline(k / n_points, color=\"gray\", lw=0.4)\n", + " ax.set_xlim(0, 1)\n", + " ax.set_ylim(0, 1)\n", + " ax.set_aspect(\"equal\")\n", + " ax.set_title(title)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "b44840e8", + "metadata": {}, + "source": [ + "By default, points live on the unit hypercube $[0,1)^d$. Passing `origin` and\n", + "`axes` maps the design onto an arbitrary parallelepiped -- useful for integrating\n", + "over a specific molecular or parameter domain rather than the unit cube." + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "81778c5d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Points now lie in [1, 4) x [2, 2.5): True\n", + "Weight per point (volume / N): 0.1500\n" + ] + } + ], + "source": [ + "origin = np.array([1.0, 2.0])\n", + "axes = np.array([[3.0, 0.0], [0.0, 0.5]])\n", + "lhs_mapped = LatinHypercube(n_points=10, dimension=2, seed=0, origin=origin, axes=axes)\n", + "\n", + "print(f\"Points now lie in [1, 4) x [2, 2.5): \"\n", + " f\"{(lhs_mapped.points[:, 0] >= 1).all() and (lhs_mapped.points[:, 0] < 4).all()}\")\n", + "print(f\"Weight per point (volume / N): {lhs_mapped.weights[0]:.4f}\")" + ] + }, + { + "cell_type": "markdown", + "id": "67684630", + "metadata": {}, + "source": [ + "## Two Functions From Computational Chemistry\n", + "\n", + "To compare Latin Hypercube Sampling against baselines already in `grid`, we use\n", + "two integrands that are both motivated by standard models in computational\n", + "chemistry, but differ in a property that matters a great deal for LHS: whether\n", + "the function is *additive*.\n", + "\n", + "**1. Sum of independent harmonic oscillators (additive).** Within the harmonic\n", + "approximation, the vibrational potential energy of a molecule is a sum of\n", + "independent contributions from each normal mode:\n", + "\n", + "$$\\Phi(\\mathbf{x}) = \\sum_{i=1}^d \\frac{1}{2} k_i x_i^2$$\n", + "\n", + "This is a sum of one-variable functions -- exactly the structure that LHS is\n", + "provably better suited for than plain Monte Carlo (Stein, 1987): the variance of\n", + "the LHS estimator depends only on the *non-additive* residual of the integrand,\n", + "which is zero here.\n", + "\n", + "**2. Product of Gaussian-type functions (non-additive).** Gaussian-type orbitals\n", + "(GTOs) are standard building blocks of quantum chemistry basis sets. A simple,\n", + "separable Gaussian orbital-like model over $d$ coordinates is\n", + "\n", + "$$f(\\mathbf{x}) = \\prod_{i=1}^d \\exp(-\\alpha_i x_i^2)\n", + "= \\exp\\left(-\\sum_{i=1}^d \\alpha_i x_i^2\\right)$$\n", + "\n", + "In three dimensions, when $\\alpha_1=\\alpha_2=\\alpha_3=\\alpha$, this reduces to\n", + "$e^{-\\alpha r^2}$, the radial form of a primitive $s$-type GTO, up to its\n", + "normalization constant. Unlike the harmonic sum, this is a *product*, not a\n", + "sum, of one-variable functions -- so it does not have the additive structure\n", + "LHS specifically exploits. Comparing both functions lets us see honestly where\n", + "LHS helps a great deal, and where it does not." + ] + }, + { + "cell_type": "markdown", + "id": "e8fa2a72", + "metadata": {}, + "source": [ + "## Comparing Against Baselines Already in `grid`\n", + "\n", + "We use `Tensor1DGrids`, built from three `Trapezoidal` 1D grids (`onedgrid`),\n", + "as a structured baseline already present in the library -- combined via a\n", + "simple tensor product, following the pattern used in `grid`'s own tests\n", + "(`test_point_and_weights_are_correct`). Note that, like `UniformGrid`,\n", + "`Tensor1DGrids` inherits from `_HyperRectangleGrid` and is restricted to two\n", + "or three dimensions -- one more reason to run this comparison at $d=3$.\n", + "\n", + "`Trapezoidal` is defined on $[-1,1]$, so we remap its points and weights onto\n", + "$[0,1]^3$ with a simple affine transformation." + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "8432e4e1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Exact integral of the harmonic sum: 0.486930\n", + "Exact integral of the GTO product: 2.395592e-01\n" + ] + } + ], + "source": [ + "from scipy.special import erf\n", + "\n", + "rng = np.random.default_rng(0)\n", + "DIM = 3\n", + "\n", + "k = rng.uniform(0.5, 2.0, size=DIM)\n", + "alpha = rng.uniform(0.5, 3.0, size=DIM)\n", + "\n", + "\n", + "def harmonic_sum(x):\n", + " # Sum of independent harmonic oscillators: Phi(x) = sum_i (1/2) k_i x_i^2.\n", + " return 0.5 * (x**2 * k[None, :]).sum(axis=1)\n", + "\n", + "\n", + "def harmonic_sum_exact():\n", + " # Exact integral over [0,1]^d.\n", + " return k.sum() / 6.0\n", + "\n", + "\n", + "def gto_product(x):\n", + " # Product of Gaussian-type functions: f(x) = prod_i exp(-alpha_i x_i^2).\n", + " return np.exp(-(x**2 * alpha[None, :])).prod(axis=1)\n", + "\n", + "\n", + "def gto_product_exact():\n", + " # Exact integral over [0,1]^d, via the error function.\n", + " per_dim = (np.sqrt(np.pi) / (2 * np.sqrt(alpha))) * erf(np.sqrt(alpha))\n", + " return per_dim.prod()\n", + "\n", + "\n", + "print(f\"Exact integral of the harmonic sum: {harmonic_sum_exact():.6f}\")\n", + "print(f\"Exact integral of the GTO product: {gto_product_exact():.6e}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "1151fcbc", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Done.\n" + ] + } + ], + "source": [ + "from grid.onedgrid import Trapezoidal\n", + "from grid.cubic import Tensor1DGrids\n", + "from grid.basegrid import Grid\n", + "\n", + "N_VALUES_PER_AXIS = [3, 5, 7, 9, 12, 15]\n", + "N_TRIALS = 15\n", + "\n", + "exact_add = harmonic_sum_exact()\n", + "exact_gto = gto_product_exact()\n", + "\n", + "lhs_err_add, mc_err_add, tensor_err_add = [], [], []\n", + "lhs_err_gto, mc_err_gto, tensor_err_gto = [], [], []\n", + "n_points_list = []\n", + "\n", + "for m in N_VALUES_PER_AXIS:\n", + " N = m ** DIM\n", + " n_points_list.append(N)\n", + "\n", + " trial_lhs_add, trial_mc_add = [], []\n", + " trial_lhs_gto, trial_mc_gto = [], []\n", + " for trial in range(N_TRIALS):\n", + " lhs = LatinHypercube(n_points=N, dimension=DIM, seed=trial)\n", + " trial_lhs_add.append(abs(lhs.integrate(harmonic_sum(lhs.points)) - exact_add))\n", + " trial_lhs_gto.append(abs(lhs.integrate(gto_product(lhs.points)) - exact_gto))\n", + "\n", + " mc_points = np.random.default_rng(1000 + trial).random((N, DIM))\n", + " mc_weights = np.full(N, 1.0 / N)\n", + " mc_grid = Grid(mc_points, mc_weights)\n", + " trial_mc_add.append(abs(mc_grid.integrate(harmonic_sum(mc_points)) - exact_add))\n", + " trial_mc_gto.append(abs(mc_grid.integrate(gto_product(mc_points)) - exact_gto))\n", + "\n", + " lhs_err_add.append(np.mean(trial_lhs_add))\n", + " mc_err_add.append(np.mean(trial_mc_add))\n", + " lhs_err_gto.append(np.mean(trial_lhs_gto))\n", + " mc_err_gto.append(np.mean(trial_mc_gto))\n", + "\n", + " oned = Trapezoidal(m)\n", + " tensor = Tensor1DGrids(oned, oned, oned)\n", + " # Trapezoidal lives on [-1, 1]; remap points and weights onto [0, 1]^3.\n", + " tensor_points = (tensor.points + 1) / 2\n", + " tensor_weights = tensor.weights / (2 ** DIM)\n", + " tensor_grid = Grid(tensor_points, tensor_weights)\n", + " tensor_err_add.append(abs(tensor_grid.integrate(harmonic_sum(tensor_points)) - exact_add))\n", + " tensor_err_gto.append(abs(tensor_grid.integrate(gto_product(tensor_points)) - exact_gto))\n", + "\n", + "print(\"Done.\")" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "1f97d0b8", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(1, 2, figsize=(12, 5))\n", + "\n", + "axes[0].loglog(n_points_list, mc_err_add, \"o--\", color=\"#B0413E\", label=\"Monte Carlo\")\n", + "axes[0].loglog(n_points_list, tensor_err_add, \"^-\", color=\"#4C9A5B\", label=\"Tensor1DGrids (Trapezoidal)\")\n", + "axes[0].loglog(n_points_list, lhs_err_add, \"s-\", color=\"#2E5C8A\", label=\"LatinHypercube\")\n", + "axes[0].set_xlabel(\"N (number of points)\")\n", + "axes[0].set_ylabel(\"Mean absolute error\")\n", + "axes[0].set_title(r\"Additive: $\\sum_i \\frac{1}{2} k_i x_i^2$\" + f\" (d={DIM})\")\n", + "axes[0].legend()\n", + "axes[0].grid(True, which=\"both\", alpha=0.3)\n", + "\n", + "axes[1].loglog(n_points_list, mc_err_gto, \"o--\", color=\"#B0413E\", label=\"Monte Carlo\")\n", + "axes[1].loglog(n_points_list, tensor_err_gto, \"^-\", color=\"#4C9A5B\", label=\"Tensor1DGrids (Trapezoidal)\")\n", + "axes[1].loglog(n_points_list, lhs_err_gto, \"s-\", color=\"#2E5C8A\", label=\"LatinHypercube\")\n", + "axes[1].set_xlabel(\"N (number of points)\")\n", + "axes[1].set_ylabel(\"Mean absolute error\")\n", + "axes[1].set_title(r\"Non-additive: $\\prod_i \\exp(-\\alpha_i x_i^2)$\" + f\" (d={DIM})\")\n", + "axes[1].legend()\n", + "axes[1].grid(True, which=\"both\", alpha=0.3)\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "c7cbb48d", + "metadata": {}, + "source": [ + "On the additive harmonic-oscillator sum, `LatinHypercube` outperforms both\n", + "plain Monte Carlo and the structured `Tensor1DGrids` baseline by a wide and\n", + "growing margin -- consistent with Stein's (1987) result for additive\n", + "integrands. On the non-additive GTO product, `Tensor1DGrids` performs best\n", + "(a smooth function is exactly the setting where structured, polynomial-exact\n", + "quadrature excels), with `LatinHypercube` a consistent second and plain Monte\n", + "Carlo last. Taken together, the two panels give an honest picture: LHS is not\n", + "universally the best choice, but it is the clear winner whenever the\n", + "integrand has meaningful additive structure, and it remains competitive even\n", + "when it does not." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "base", + "language": "python", + "name": "python3" + }, + "language_info": { + "name": "python", + "version": "3.14.6" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/src/grid/__init__.py b/src/grid/__init__.py index 952e79a9..dfd86e84 100644 --- a/src/grid/__init__.py +++ b/src/grid/__init__.py @@ -1,4 +1,3 @@ -# -*- coding: utf-8 -*- # GRID is a numerical integration module for quantum chemistry. # # Copyright (C) 2011-2019 The GRID Development Team @@ -19,21 +18,21 @@ # along with this program; if not, see # -- """Grid Module.""" -# ruff: noqa: F401,F403 +# ruff: noqa: F403 from grid.angular import * from grid.atomgrid import * from grid.basegrid import * from grid.becke import * +from grid.coulomb import * from grid.cubic import * from grid.hirshfeld import * -from grid.angular import * +from grid.latin_hypercube import * from grid.molgrid import * +from grid.ngrid import * from grid.ode import * from grid.onedgrid import * from grid.periodicgrid import * -from grid.rtransform import * -from grid.ngrid import * -from grid.coulomb import * from grid.robust_poisson import * +from grid.rtransform import * diff --git a/src/grid/latin_hypercube.py b/src/grid/latin_hypercube.py new file mode 100644 index 00000000..6c6cdaaa --- /dev/null +++ b/src/grid/latin_hypercube.py @@ -0,0 +1,209 @@ +# GRID is a numerical integration module for quantum chemistry. +# +# Copyright (C) 2011-2019 The GRID Development Team +# +# This file is part of GRID. +# +# GRID is free software; you can redistribute it and/or +# modify it under the terms of the GNU General Public License +# as published by the Free Software Foundation; either version 3 +# of the License, or (at your option) any later version. +# +# GRID is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +# GNU General Public License for more details. +# +# You should have received a copy of the GNU General Public License +# along with this program; if not, see +# -- +"""Latin Hypercube Sampling for integration on (hyper)cubic grids.""" + +import numpy as np + +from grid.basegrid import Grid + + +class LatinHypercube(Grid): + r"""Randomized Latin Hypercube Sampling for integration on a (hyper)cubic grid. + + Latin Hypercube Sampling (LHS) stratifies every one-dimensional marginal exactly: + splitting :math:`[0,1)` into :math:`N` equal strata along *any* single coordinate + axis places exactly one point in each stratum. For a given dimension, a point's + coordinate is + + .. math:: + x_i = \frac{\pi(i) - U_i}{N}, \qquad i = 1, \ldots, N, + + where :math:`\pi` is an independent random permutation of :math:`1, \ldots, N` and + :math:`U_i \sim \text{Uniform}(0,1)` i.i.d., drawn independently for every dimension. + Setting `randomize=False` replaces :math:`U_i` with the constant :math:`0.5`, placing + each point at the center of its stratum instead of a random position within it. + + Unlike Monte Carlo sampling, LHS is asymptotically at least as accurate as plain + Monte Carlo for any integrand, and strictly better for integrands with a strong + additive component (Stein, 1987). + + The integration weights are all equal to :math:`V/N`, where :math:`V` is the volume + of the integration domain. + + References + ---------- + - McKay, M. D., Beckman, R. J., & Conover, W. J. (1979). A Comparison of Three + Methods for Selecting Values of Input Variables in the Analysis of Output from + a Computer Code. Technometrics, 21(2), 239-245. + - Stein, M. (1987). Large Sample Properties of Simulations Using Latin Hypercube + Sampling. Technometrics, 29(2), 143-151. + + """ + + def __init__( + self, + n_points, + dimension, + seed=None, + randomize=True, + origin=None, + axes=None, + ): + r"""Construct a Latin Hypercube grid. + + Parameters + ---------- + n_points : int + Number of integration points :math:`N`. + dimension : int + Dimension :math:`d` of the integration domain. + seed : int, optional + Seed for the random number generator, for reproducibility. + randomize : bool, optional + If True (default), each point is jittered uniformly within its stratum. + If False, each point is placed at the center of its stratum instead + (the assignment of strata to dimensions is still drawn randomly, since + otherwise every dimension would place its points on the same diagonal + pattern). + origin : np.ndarray, shape (d,), optional + Origin of the hypercube. Defaults to zero vector. + axes : np.ndarray, shape (d, d), optional + Axes defining the hypercube (as row vectors). Defaults to identity matrix + (unit hypercube). The LHS points are first generated on :math:`[0,1)^d` and + then affine-transformed to the specified parallelepiped. + + Raises + ------ + ValueError + If n_points or dimension is not a positive integer, or if origin/axes have + an incorrect shape, or if axes are not linearly independent. + + """ + if n_points < 1: + raise ValueError(f"n_points must be >= 1, got {n_points}") + if dimension < 1: + raise ValueError(f"dimension must be >= 1, got {dimension}") + + # Generate LHS points in the unit cube [0, 1)^d + points_unit = self._generate_lhs_points(n_points, dimension, seed, randomize) + + if origin is None: + origin = np.zeros(dimension) + else: + origin = np.asarray(origin, dtype=float) + if origin.shape != (dimension,): + raise ValueError(f"origin must have shape ({dimension},), got {origin.shape}") + + if axes is None: + axes = np.eye(dimension) + else: + axes = np.asarray(axes, dtype=float) + if axes.shape != (dimension, dimension): + raise ValueError( + f"axes must have shape ({dimension}, {dimension}), got {axes.shape}" + ) + if np.linalg.matrix_rank(axes) < dimension: + raise ValueError("axes must be linearly independent") + + # Map the unit cube points to the parallelepiped defined by origin and axes + # (affine transformation: x = origin + points_unit @ axes) + points = origin + points_unit @ axes + + # Volume of the parallelepiped + volume = np.abs(np.linalg.det(axes)) + + # Uniform weights + weights = np.full(n_points, volume / n_points) + + self._n_points = n_points + self._dimension = dimension + self._seed = seed + self._randomize = randomize + self._origin = origin + self._axes = axes + + super().__init__(points, weights) + + def _generate_lhs_points(self, n_points, dimension, seed, randomize): + r"""Generate Latin Hypercube points on the unit hypercube [0,1)^d. + + Parameters + ---------- + n_points : int + Number of points :math:`N`. + dimension : int + Dimension :math:`d`. + seed : int or None + Seed for the random number generator. + randomize : bool + If True, jitter each point uniformly within its stratum. If False, + place each point at the center of its stratum. + + Returns + ------- + np.ndarray, shape (N, d) + Latin Hypercube points in the unit hypercube. + + """ + rng = np.random.default_rng(seed) + keys = rng.random(size=(dimension, n_points)) + permutations = np.argsort(keys, axis=-1) + 1 + if randomize: + U = rng.uniform(0, 1, size=permutations.shape) + result = (permutations - U) / n_points + else: + result = (permutations - 0.5) / n_points + return result.T + + def __getitem__(self, index): + """Return a plain Grid for a point subset (a subset is not itself a valid LHS design).""" + if isinstance(index, int): + return Grid(np.array([self.points[index]]), np.array([self.weights[index]])) + return Grid(np.array(self.points[index]), np.array(self.weights[index])) + + @property + def n_points(self): + """int: Number of points in the LHS design.""" + return self._n_points + + @property + def dimension(self): + """int: Dimension of the LHS grid.""" + return self._dimension + + @property + def seed(self): + """int or None: Seed used for reproducibility.""" + return self._seed + + @property + def randomize(self): + """bool: Whether points are jittered within strata (True) or centered (False).""" + return self._randomize + + @property + def origin(self): + """np.ndarray: Origin of the integration domain.""" + return self._origin + + @property + def axes(self): + """np.ndarray: Axes defining the integration domain.""" + return self._axes diff --git a/src/grid/tests/test_latin_hypercube.py b/src/grid/tests/test_latin_hypercube.py new file mode 100644 index 00000000..b75e652a --- /dev/null +++ b/src/grid/tests/test_latin_hypercube.py @@ -0,0 +1,274 @@ +# GRID is a numerical integration module for quantum chemistry. +# +# Copyright (C) 2011-2019 The GRID Development Team +# +# This file is part of GRID. +# +# GRID is free software; you can redistribute it and/or +# modify it under the terms of the GNU General Public License +# as published by the Free Software Foundation; either version 3 +# of the License, or (at your option) any later version. +# +# GRID is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +# GNU General Public License for more details. +# +# You should have received a copy of the GNU General Public License +# along with this program; if not, see +# -- +r"""Tests for Latin Hypercube Sampling.""" + +import os +import tempfile +from unittest import TestCase + +import numpy as np +from numpy.testing import assert_allclose, assert_equal + +from grid.basegrid import Grid +from grid.latin_hypercube import LatinHypercube + + +class TestLatinHypercube(TestCase): + r"""Test LatinHypercube class.""" + + # ------------------------------------------------------------------ + # Validation errors + # ------------------------------------------------------------------ + + def test_raises_error_when_n_points_invalid(self): + r"""Test that n_points must be >= 1.""" + with self.assertRaises(ValueError) as err: + LatinHypercube(n_points=0, dimension=2) + self.assertIn("must be >= 1", str(err.exception)) + + def test_raises_error_when_dimension_invalid(self): + r"""Test that dimension must be >= 1.""" + with self.assertRaises(ValueError) as err: + LatinHypercube(n_points=100, dimension=0) + self.assertIn("must be >= 1", str(err.exception)) + + def test_raises_error_for_invalid_origin(self): + r"""Test that origin must have correct shape.""" + with self.assertRaises(ValueError) as err: + LatinHypercube(n_points=100, dimension=3, origin=np.array([0, 0])) + self.assertIn("origin must have shape (3,)", str(err.exception)) + + def test_raises_error_for_invalid_axes(self): + r"""Test that axes must have correct shape.""" + with self.assertRaises(ValueError) as err: + LatinHypercube(n_points=100, dimension=3, axes=np.eye(2)) + self.assertIn("axes must have shape (3, 3)", str(err.exception)) + + def test_raises_error_for_singular_axes(self): + r"""Test that axes must be linearly independent.""" + singular_axes = np.array([[1, 0, 0], [2, 0, 0], [0, 0, 1]]) + with self.assertRaises(ValueError) as err: + LatinHypercube(n_points=100, dimension=3, axes=singular_axes) + self.assertIn("must be linearly independent", str(err.exception)) + + # ------------------------------------------------------------------ + # Basic properties, weights, domain mapping + # ------------------------------------------------------------------ + + def test_properties(self): + r"""Test that LHS properties are correctly set.""" + n_points, dimension = 100, 3 + lhs = LatinHypercube(n_points=n_points, dimension=dimension, seed=0) + + assert_equal(lhs.size, n_points) + assert_equal(lhs.n_points, n_points) + assert_equal(lhs.dimension, dimension) + assert_equal(lhs.randomize, True) + assert_equal(lhs.points.shape, (n_points, dimension)) + assert_equal(lhs.weights.shape, (n_points,)) + assert_allclose(lhs.origin, np.zeros(dimension)) + assert_allclose(lhs.axes, np.eye(dimension)) + + def test_weights_are_equal(self): + r"""Test that all weights are equal to V/N.""" + n_points, dimension = 100, 2 + lhs = LatinHypercube(n_points=n_points, dimension=dimension, seed=0) + + expected_weight = 1.0 / n_points + assert_allclose(lhs.weights, np.full(n_points, expected_weight)) + + def test_weights_with_custom_axes(self): + r"""Test that weights scale with volume.""" + n_points, dimension = 100, 2 + axes = np.array([[2.0, 0.0], [0.0, 2.0]]) + lhs = LatinHypercube(n_points=n_points, dimension=dimension, axes=axes, seed=0) + + expected_weight = 4.0 / n_points + assert_allclose(lhs.weights, np.full(n_points, expected_weight)) + + def test_points_in_unit_cube(self): + r"""Test that points are in [0, 1)^d for default parameters.""" + lhs = LatinHypercube(n_points=100, dimension=3, seed=0) + assert np.all(lhs.points >= 0.0) + assert np.all(lhs.points < 1.0) + + def test_points_with_custom_origin_and_axes(self): + r"""Test that points are correctly transformed.""" + n_points, dimension = 100, 2 + origin = np.array([1.0, 2.0]) + axes = np.array([[0.5, 0.0], [0.0, 0.5]]) + lhs = LatinHypercube( + n_points=n_points, dimension=dimension, origin=origin, axes=axes, seed=0 + ) + + assert np.all(lhs.points[:, 0] >= 1.0) + assert np.all(lhs.points[:, 0] < 1.5) + assert np.all(lhs.points[:, 1] >= 2.0) + assert np.all(lhs.points[:, 1] < 2.5) + + def test_integration_of_constant_function(self): + r"""Test integration of f(x) = 1 gives volume.""" + n_points, dimension = 2048, 3 + axes = np.diag([2.0, 3.0, 4.0]) # Volume = 24 + lhs = LatinHypercube(n_points=n_points, dimension=dimension, axes=axes, seed=0) + + func_vals = np.ones(n_points) + integral = lhs.integrate(func_vals) + assert_allclose(integral, 24.0, rtol=1e-10) + + def test_integration_of_linear_function(self): + r"""Test integration of f(x) = x_1 + x_2 on unit square.""" + n_points, dimension = 4096, 2 + lhs = LatinHypercube(n_points=n_points, dimension=dimension, seed=0) + + func_vals = lhs.points[:, 0] + lhs.points[:, 1] + integral = lhs.integrate(func_vals) + + # Exact integral over [0,1]^2: int_0^1 int_0^1 (x+y) dx dy = 1 + assert_allclose(integral, 1.0, rtol=1e-2) + + def test_save_and_load(self): + r"""Test saving LHS grid to file.""" + + lhs = LatinHypercube(n_points=100, dimension=2, seed=0) + + fd, filename = tempfile.mkstemp(suffix=".npz") + os.close(fd) + + try: + lhs.save(filename) + loaded = np.load(filename) + assert_allclose(loaded["points"], lhs.points) + assert_allclose(loaded["weights"], lhs.weights) + loaded.close() + finally: + if os.path.exists(filename): + os.unlink(filename) + + def test_different_dimensions(self): + r"""Test LHS in different dimensions.""" + for dimension in [1, 2, 3, 5, 10]: + n_points = 100 + lhs = LatinHypercube(n_points=n_points, dimension=dimension, seed=0) + assert_equal(lhs.dimension, dimension) + assert_equal(lhs.points.shape, (n_points, dimension)) + + # ------------------------------------------------------------------ + # Properties SPECIFIC to Latin Hypercube Sampling + # ------------------------------------------------------------------ + + def test_stratification_property(self): + r"""Test the core LHS property: exactly one point per stratum, in every dimension.""" + n_points, dimension = 100, 4 + lhs = LatinHypercube(n_points=n_points, dimension=dimension, seed=0) + + for j in range(dimension): + strata = np.floor(lhs.points[:, j] * n_points).astype(int) + assert_equal(sorted(strata.tolist()), list(range(n_points))) + + def test_stratification_property_with_custom_domain(self): + r"""Test that stratification still holds after mapping to a custom parallelepiped.""" + n_points, dimension = 100, 2 + origin = np.array([1.0, 2.0]) + axes = np.array([[3.0, 0.0], [0.0, 5.0]]) + lhs = LatinHypercube( + n_points=n_points, dimension=dimension, origin=origin, axes=axes, seed=0 + ) + + # Map back to [0, 1)^d before checking stratification + unit_points = (lhs.points - origin) @ np.linalg.inv(axes) + for j in range(dimension): + strata = np.floor(unit_points[:, j] * n_points).astype(int) + assert_equal(sorted(strata.tolist()), list(range(n_points))) + + def test_randomize_true_and_false_differ(self): + r"""Regression test: randomize=True and randomize=False must give different points. + + This guards against a real bug found during development, where an internal + string comparison (``randomize == "TRUE"``) silently ignored the boolean + ``randomize`` argument, making the class always behave as if + ``randomize=False`` regardless of what was requested. + """ + n_points, dimension = 50, 3 + lhs_true = LatinHypercube(n_points=n_points, dimension=dimension, seed=1, randomize=True) + lhs_false = LatinHypercube(n_points=n_points, dimension=dimension, seed=1, randomize=False) + + assert not np.allclose(lhs_true.points, lhs_false.points) + + def test_not_randomized_points_are_stratum_centers(self): + r"""Test that randomize=False places every point exactly at its stratum center.""" + n_points, dimension = 20, 3 + lhs = LatinHypercube(n_points=n_points, dimension=dimension, seed=2, randomize=False) + + centered = lhs.points * n_points + 0.5 + assert_allclose(centered, np.round(centered), atol=1e-10) + + def test_reproducibility_same_seed(self): + r"""Test that the same seed gives identical points.""" + lhs1 = LatinHypercube(n_points=30, dimension=2, seed=42) + lhs2 = LatinHypercube(n_points=30, dimension=2, seed=42) + assert_allclose(lhs1.points, lhs2.points) + + def test_different_seeds_give_different_points(self): + r"""Test that different seeds give different points when randomize=True.""" + lhs1 = LatinHypercube(n_points=30, dimension=2, seed=42) + lhs2 = LatinHypercube(n_points=30, dimension=2, seed=43) + assert not np.allclose(lhs1.points, lhs2.points) + + def test_n_points_need_not_be_power_of_2(self): + r"""Test that, unlike Lattice, LHS accepts any n_points (no power-of-2 constraint).""" + for n_points in [7, 100, 123, 1000]: + lhs = LatinHypercube(n_points=n_points, dimension=3, seed=0) + assert_equal(lhs.points.shape, (n_points, 3)) + + def test_not_nested_unlike_lattice(self): + r"""Test that LHS designs of different sizes are NOT related by subsetting. + + Unlike Lattice (where a lattice of N points is exactly embedded in a lattice + of 2N points, since x_i = {i*z/N} = {2i*z/(2N)}), LHS is not a nested/extensible + sequence: the strata boundaries themselves depend on n_points, so a design with + N points bears no fixed relationship to a design with 2N points. + """ + n_points, dimension = 50, 2 + lhs_n = LatinHypercube(n_points=n_points, dimension=dimension, seed=0) + lhs_2n = LatinHypercube(n_points=2 * n_points, dimension=dimension, seed=0) + + # No systematic relationship should hold between the two point sets. + assert not np.allclose(lhs_n.points, lhs_2n.points[::2]) + + def test_getitem_returns_plain_grid(self): + r"""Test that indexing returns a plain Grid, not a LatinHypercube. + + A subset of an LHS design is not itself a valid LHS design (the + stratification property no longer holds), so __getitem__ must not + return a LatinHypercube instance. + """ + + lhs = LatinHypercube(n_points=50, dimension=2, seed=0) + + single = lhs[3] + assert isinstance(single, Grid) + assert not isinstance(single, LatinHypercube) + assert_equal(single.points.shape, (1, 2)) + + subset = lhs[5:10] + assert isinstance(subset, Grid) + assert not isinstance(subset, LatinHypercube) + assert_equal(subset.points.shape, (5, 2))