1edab6123Sjeremylt{ 2edab6123Sjeremylt "cells": [ 3edab6123Sjeremylt { 4edab6123Sjeremylt "cell_type": "markdown", 5edab6123Sjeremylt "metadata": {}, 6edab6123Sjeremylt "source": [ 7edab6123Sjeremylt "# libCEED for Python examples\n", 8edab6123Sjeremylt "\n", 9edab6123Sjeremylt "This is a tutorial to illustrate the main feautures of the Python interface for [libCEED](https://github.com/CEED/libCEED/), the low-level API library for efficient high-order discretization methods developed by the co-design [Center for Efficient Exascale Discretizations](https://ceed.exascaleproject.org/) (CEED) of the [Exascale Computing Project](https://www.exascaleproject.org/) (ECP).\n", 10edab6123Sjeremylt "\n", 1113964f07SJed Brown "While libCEED's focus is on high-order finite/spectral element method implementations, the approach is mostly algebraic and thus applicable to other discretizations in factored form, as explained in the [user manual](https://libceed.org/)." 12edab6123Sjeremylt ] 13edab6123Sjeremylt }, 14edab6123Sjeremylt { 15edab6123Sjeremylt "cell_type": "markdown", 16edab6123Sjeremylt "metadata": {}, 17edab6123Sjeremylt "source": [ 18edab6123Sjeremylt "## Setting up libCEED for Python\n", 19edab6123Sjeremylt "\n", 20edab6123Sjeremylt "Install libCEED for Python by running" 21edab6123Sjeremylt ] 22edab6123Sjeremylt }, 23edab6123Sjeremylt { 24edab6123Sjeremylt "cell_type": "code", 25edab6123Sjeremylt "execution_count": null, 26edab6123Sjeremylt "metadata": {}, 27edab6123Sjeremylt "outputs": [], 28edab6123Sjeremylt "source": [ 29edab6123Sjeremylt "! python -m pip install libceed" 30edab6123Sjeremylt ] 31edab6123Sjeremylt }, 32edab6123Sjeremylt { 33edab6123Sjeremylt "cell_type": "markdown", 34edab6123Sjeremylt "metadata": {}, 35edab6123Sjeremylt "source": [ 36edab6123Sjeremylt "## CeedOperator\n", 37edab6123Sjeremylt "\n", 3813964f07SJed Brown "Here we show some basic examples to illustrate the `libceed.Operator` class. In libCEED, a `libceed.Operator` defines the finite/spectral element operator associated to a `libceed.QFunction` (see [the API documentation](https://libceed.org/en/latest/libCEEDapi.html#finite-element-operator-decomposition))." 39edab6123Sjeremylt ] 40edab6123Sjeremylt }, 41edab6123Sjeremylt { 42edab6123Sjeremylt "cell_type": "markdown", 43edab6123Sjeremylt "metadata": {}, 44edab6123Sjeremylt "source": [ 45edab6123Sjeremylt "* In the following example, we create and apply a CeedOperator for the mass matrix in 1D. By applying this operator to a vector of 1's, we compute the length of this 1D domain, similar to Ex1-Volume in the [tutorial-6-shell tutorial](./tutorial-6-shell.ipynb)" 46edab6123Sjeremylt ] 47edab6123Sjeremylt }, 48edab6123Sjeremylt { 49edab6123Sjeremylt "cell_type": "code", 50edab6123Sjeremylt "execution_count": null, 51edab6123Sjeremylt "metadata": {}, 52edab6123Sjeremylt "outputs": [], 53edab6123Sjeremylt "source": [ 54edab6123Sjeremylt "import libceed\n", 55edab6123Sjeremylt "import numpy as np\n", 56edab6123Sjeremylt "\n", 57edab6123Sjeremylt "ceed = libceed.Ceed()\n", 58edab6123Sjeremylt "\n", 59edab6123Sjeremylt "nelem = 15\n", 60edab6123Sjeremylt "p = 5\n", 61edab6123Sjeremylt "q = 8\n", 62edab6123Sjeremylt "nx = nelem + 1\n", 63edab6123Sjeremylt "nu = nelem*(p-1) + 1\n", 64edab6123Sjeremylt "\n", 65edab6123Sjeremylt "# Vectors\n", 66edab6123Sjeremylt "x = ceed.Vector(nx)\n", 67edab6123Sjeremylt "x_array = np.zeros(nx)\n", 68edab6123Sjeremylt "for i in range(nx):\n", 69edab6123Sjeremylt " x_array[i] = i / (nx - 1.0)\n", 70edab6123Sjeremylt "x.set_array(x_array, cmode=libceed.USE_POINTER)\n", 71edab6123Sjeremylt "\n", 72edab6123Sjeremylt "qdata = ceed.Vector(nelem*q)\n", 73edab6123Sjeremylt "u = ceed.Vector(nu)\n", 74edab6123Sjeremylt "v = ceed.Vector(nu)\n", 75edab6123Sjeremylt "\n", 76edab6123Sjeremylt "# Restrictions\n", 77edab6123Sjeremylt "indx = np.zeros(nx*2, dtype=\"int32\")\n", 78edab6123Sjeremylt "for i in range(nx):\n", 79edab6123Sjeremylt " indx[2*i+0] = i\n", 80edab6123Sjeremylt " indx[2*i+1] = i+1\n", 81edab6123Sjeremylt "rx = ceed.ElemRestriction(nelem, 2, 1, 1, nx, indx, cmode=libceed.USE_POINTER)\n", 82edab6123Sjeremylt "\n", 83edab6123Sjeremylt "indu = np.zeros(nelem*p, dtype=\"int32\")\n", 84edab6123Sjeremylt "for i in range(nelem):\n", 85edab6123Sjeremylt " for j in range(p):\n", 86edab6123Sjeremylt " indu[p*i+j] = i*(p-1) + j\n", 87edab6123Sjeremylt "ru = ceed.ElemRestriction(nelem, p, 1, 1, nu, indu, cmode=libceed.USE_POINTER)\n", 88edab6123Sjeremylt "strides = np.array([1, q, q], dtype=\"int32\")\n", 89edab6123Sjeremylt "rui = ceed.StridedElemRestriction(nelem, q, 1, q*nelem, strides)\n", 90edab6123Sjeremylt "\n", 91edab6123Sjeremylt "# Bases\n", 92edab6123Sjeremylt "bx = ceed.BasisTensorH1Lagrange(1, 1, 2, q, libceed.GAUSS)\n", 93edab6123Sjeremylt "bu = ceed.BasisTensorH1Lagrange(1, 1, p, q, libceed.GAUSS)\n", 94edab6123Sjeremylt "\n", 95edab6123Sjeremylt "# QFunctions\n", 96edab6123Sjeremylt "qf_setup = ceed.QFunctionByName(\"Mass1DBuild\")\n", 97edab6123Sjeremylt "qf_mass = ceed.QFunctionByName(\"MassApply\")\n", 98edab6123Sjeremylt "\n", 99edab6123Sjeremylt "# Setup operator\n", 100edab6123Sjeremylt "op_setup = ceed.Operator(qf_setup)\n", 101edab6123Sjeremylt "op_setup.set_field(\"dx\", rx, bx, libceed.VECTOR_ACTIVE)\n", 102edab6123Sjeremylt "op_setup.set_field(\"weights\", libceed.ELEMRESTRICTION_NONE, bx,\n", 103edab6123Sjeremylt " libceed.VECTOR_NONE)\n", 104*a36217cbSJeremy L Thompson "op_setup.set_field(\"qdata\", rui, libceed.BASIS_NONE,\n", 105edab6123Sjeremylt " libceed.VECTOR_ACTIVE)\n", 10628d09c20SJeremy L Thompson "op_setup.check()\n", 107edab6123Sjeremylt "print('Setup operator: ', op_setup)\n", 108edab6123Sjeremylt "\n", 109edab6123Sjeremylt "# Mass operator\n", 110edab6123Sjeremylt "op_mass = ceed.Operator(qf_mass)\n", 111edab6123Sjeremylt "op_mass.set_field(\"u\", ru, bu, libceed.VECTOR_ACTIVE)\n", 112*a36217cbSJeremy L Thompson "op_mass.set_field(\"qdata\", rui, libceed.BASIS_NONE, qdata)\n", 113edab6123Sjeremylt "op_mass.set_field(\"v\", ru, bu, libceed.VECTOR_ACTIVE)\n", 11428d09c20SJeremy L Thompson "op_mass.check()\n", 115edab6123Sjeremylt "print('Mass operator: ', op_mass)\n", 116edab6123Sjeremylt "\n", 117edab6123Sjeremylt "# Setup\n", 118edab6123Sjeremylt "op_setup.apply(x, qdata)\n", 119edab6123Sjeremylt "\n", 120edab6123Sjeremylt "# Apply mass matrix\n", 121edab6123Sjeremylt "u.set_value(1)\n", 122edab6123Sjeremylt "op_mass.apply(u, v)\n", 123edab6123Sjeremylt "\n", 124edab6123Sjeremylt "# Check\n", 125edab6123Sjeremylt "with v.array_read() as v_array:\n", 126edab6123Sjeremylt " print('The length of the domain is l = %4.2f'%np.sum(v_array))" 127edab6123Sjeremylt ] 128edab6123Sjeremylt } 129edab6123Sjeremylt ], 130edab6123Sjeremylt "metadata": { 131edab6123Sjeremylt "kernelspec": { 132edab6123Sjeremylt "display_name": "Python 3", 133edab6123Sjeremylt "language": "python", 134edab6123Sjeremylt "name": "python3" 135edab6123Sjeremylt }, 136edab6123Sjeremylt "language_info": { 137edab6123Sjeremylt "codemirror_mode": { 138edab6123Sjeremylt "name": "ipython", 139edab6123Sjeremylt "version": 3 140edab6123Sjeremylt }, 141edab6123Sjeremylt "file_extension": ".py", 142edab6123Sjeremylt "mimetype": "text/x-python", 143edab6123Sjeremylt "name": "python", 144edab6123Sjeremylt "nbconvert_exporter": "python", 145edab6123Sjeremylt "pygments_lexer": "ipython3", 146edab6123Sjeremylt "version": "3.8.5" 147edab6123Sjeremylt } 148edab6123Sjeremylt }, 149edab6123Sjeremylt "nbformat": 4, 150edab6123Sjeremylt "nbformat_minor": 4 151edab6123Sjeremylt} 152