{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# The Devito domain specific language: an overview\n", "\n", "This notebook presents an overview of the Devito symbolic language, used to express and discretise operators, in particular partial differential equations (PDEs).\n", "\n", "For convenience, we import all Devito modules:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from devito import *" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## From equations to code in a few lines of Python\n", "\n", "The main objective of this tutorial is to demonstrate how Devito and its [SymPy](http://www.sympy.org/en/index.html)-powered symbolic API can be used to solve partial differential equations using the finite difference method with highly optimized stencils in a few lines of Python. We demonstrate how computational stencils can be derived directly from the equation in an automated fashion and how Devito can be used to generate and execute, at runtime, the desired numerical scheme in the form of optimized C code.\n", "\n", "\n", "## Defining the physical domain\n", "\n", "Before we can begin creating finite-difference (FD) stencils we will need to give Devito a few details regarding the computational domain within which we wish to solve our problem. For this purpose we create a `Grid` object that stores the physical `extent` (the size) of our domain and knows how many points we want to use in each dimension to discretise our data.\n", "\n", "" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Grid[extent=(1.0, 1.0), shape=(5, 6), dimensions=(x, y)]" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grid = Grid(shape=(5, 6), extent=(1., 1.))\n", "grid" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Functions and data\n", "\n", "To express our equation in symbolic form and discretise it using finite differences, Devito provides a set of `Function` types. A `Function` object:\n", "\n", "1. Behaves like a `sympy.Function` symbol\n", "2. Manages data associated with the symbol\n", "\n", "To get more information on how to create and use a `Function` object, or any type provided by Devito, we can take a look at the documentation." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", " Tensor symbol representing a discrete function in symbolic equations.\n", "\n", " A Function carries multi-dimensional data and provides operations to create\n", " finite-differences approximations.\n", "\n", " A Function encapsulates space-varying data; for data that also varies in time,\n", " use TimeFunction instead.\n", "\n", " Parameters\n", " ----------\n", " name : str\n", " Name of the symbol.\n", " grid : Grid, optional\n", " Carries shape, dimensions, and dtype of the Function. When grid is not\n", " provided, shape and dimensions must be given. For MPI execution, a\n", " Grid is compulsory.\n", " space_order : int or 3-tuple of ints, optional\n", " Discretisation order for space derivatives. Defaults to 1. ``space_order`` also\n", " impacts the number of points available around a generic point of interest. By\n", " default, ``space_order`` points are available on both sides of a generic point of\n", " interest, including those nearby the grid boundary. Sometimes, fewer points\n", " suffice; in other scenarios, more points are necessary. In such cases, instead of\n", " an integer, one can pass a 3-tuple ``(o, lp, rp)`` indicating the discretization\n", " order (``o``) as well as the number of points on the left (``lp``) and right\n", " (``rp``) sides of a generic point of interest.\n", " shape : tuple of ints, optional\n", " Shape of the domain region in grid points. Only necessary if ``grid`` isn't given.\n", " dimensions : tuple of Dimension, optional\n", " Dimensions associated with the object. Only necessary if ``grid`` isn't given.\n", " dtype : data-type, optional\n", " Any object that can be interpreted as a numpy data type. Defaults\n", " to ``np.float32``.\n", " staggered : Dimension or tuple of Dimension or Stagger, optional\n", " Define how the Function is staggered.\n", " initializer : callable or any object exposing the buffer interface, optional\n", " Data initializer. If a callable is provided, data is allocated lazily.\n", " allocator : MemoryAllocator, optional\n", " Controller for memory allocation. To be used, for example, when one wants\n", " to take advantage of the memory hierarchy in a NUMA architecture. Refer to\n", " `default_allocator.__doc__` for more information.\n", " padding : int or tuple of ints, optional\n", " .. deprecated:: shouldn't be used; padding is now automatically inserted.\n", "\n", " Allocate extra grid points to maximize data access alignment. When a tuple\n", " of ints, one int per Dimension should be provided.\n", "\n", " Examples\n", " --------\n", " Creation\n", "\n", " >>> from devito import Grid, Function\n", " >>> grid = Grid(shape=(4, 4))\n", " >>> f = Function(name='f', grid=grid)\n", " >>> f\n", " f(x, y)\n", " >>> g = Function(name='g', grid=grid, space_order=2)\n", " >>> g\n", " g(x, y)\n", "\n", " First-order derivatives through centered finite-difference approximations\n", "\n", " >>> f.dx\n", " Derivative(f(x, y), x)\n", " >>> f.dy\n", " Derivative(f(x, y), y)\n", " >>> g.dx\n", " Derivative(g(x, y), x)\n", " >>> (f + g).dx\n", " Derivative(f(x, y) + g(x, y), x)\n", "\n", " First-order derivatives through left/right finite-difference approximations\n", "\n", " >>> f.dxl\n", " Derivative(f(x, y), x)\n", "\n", " Note that the fact that it's a left-derivative isn't captured in the representation.\n", " However, upon derivative expansion, this becomes clear\n", "\n", " >>> f.dxl.evaluate\n", " f(x, y)/h_x - f(x - h_x, y)/h_x\n", " >>> f.dxr\n", " Derivative(f(x, y), x)\n", "\n", " Second-order derivative through centered finite-difference approximation\n", "\n", " >>> g.dx2\n", " Derivative(g(x, y), (x, 2))\n", "\n", " Notes\n", " -----\n", " The parameters must always be given as keyword arguments, since SymPy\n", " uses ``*args`` to (re-)create the dimension arguments of the symbolic object.\n", " \n" ] } ], "source": [ "print(Function.__doc__)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Ok, let's create a function $f(x, y)$ and look at the data Devito has associated with it. Please note that it is important to use explicit keywords, such as `name` or `grid` when creating `Function` objects." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle f{\\left(x,y \\right)}$" ], "text/plain": [ "f(x, y)" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "f = Function(name='f', grid=grid)\n", "f" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Data([[0., 0., 0., 0., 0., 0.],\n", " [0., 0., 0., 0., 0., 0.],\n", " [0., 0., 0., 0., 0., 0.],\n", " [0., 0., 0., 0., 0., 0.],\n", " [0., 0., 0., 0., 0., 0.]], dtype=float32)" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "f.data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "By default, Devito `Function` objects use the spatial dimensions `(x, y)` for 2D grids and `(x, y, z)` for 3D grids. To solve a PDE over several timesteps a time dimension is also required by our symbolic function. For this Devito provides an additional function type, the `TimeFunction`, which incorporates the correct dimension along with some other intricacies needed to create a time stepping scheme." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle g{\\left(t,x,y \\right)}$" ], "text/plain": [ "g(t, x, y)" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "g = TimeFunction(name='g', grid=grid)\n", "g" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Since the default time order of a `TimeFunction` is `1`, the shape of `f` is `(2, 5, 6)`, i.e. Devito has allocated two buffers to represent `g(t, x, y)` and `g(t + dt, x, y)`:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(2, 5, 6)" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "g.shape" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Derivatives of symbolic functions\n", "\n", "The functions we have created so far all act as `sympy.Function` objects, which means that we can form symbolic derivative expressions from them. Devito provides a set of shorthand expressions (implemented as Python properties) that allow us to generate finite differences in symbolic form. For example, the property `f.dx` denotes $\\frac{\\partial}{\\partial x} f(x, y)$ - only that Devito has already discretised it with a finite difference expression. There are also a set of shorthand expressions for left (backward) and right (forward) derivatives:\n", "\n", "| Derivative | Shorthand | Discretised | Stencil |\n", "| ---------- |:---------:|:-----------:|:-------:|\n", "| $\\frac{\\partial}{\\partial x}f(x, y)$ (right) | `f.dxr` | $\\frac{f(x+h_x,y)}{h_x} - \\frac{f(x,y)}{h_x}$ | |\n", "| $\\frac{\\partial}{\\partial x}f(x, y)$ (left) | `f.dxl` | $\\frac{f(x,y)}{h_x} - \\frac{f(x-h_x,y)}{h_x}$ | |\n", "\n", "A similar set of expressions exist for each spatial dimension defined on our grid, for example `f.dy` and `f.dyl`. Obviously, one can also take derivatives in time of `TimeFunction` objects. For example, to take the first derivative in time of `g` you can simply write:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle \\frac{\\partial}{\\partial t} g{\\left(t,x,y \\right)}$" ], "text/plain": [ "Derivative(g(t, x, y), t)" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "g.dt" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We may also want to take a look at the stencil Devito will generate based on the chosen discretisation:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle - \\frac{g{\\left(t,x,y \\right)}}{dt} + \\frac{g{\\left(t + dt,x,y \\right)}}{dt}$" ], "text/plain": [ "-g(t, x, y)/dt + g(t + dt, x, y)/dt" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "g.dt.evaluate" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There also exist convenient shortcuts to express the forward and backward stencil points, `g(t+dt, x, y)` and `g(t-dt, x, y)`." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle g{\\left(t + dt,x,y \\right)}$" ], "text/plain": [ "g(t + dt, x, y)" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "g.forward" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle g{\\left(t - dt,x,y \\right)}$" ], "text/plain": [ "g(t - dt, x, y)" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "g.backward" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And of course, there's nothing to stop us taking derivatives on these objects:" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle \\frac{\\partial}{\\partial t} g{\\left(t + dt,x,y \\right)}$" ], "text/plain": [ "Derivative(g(t + dt, x, y), t)" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "g.forward.dt" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle \\frac{\\partial}{\\partial y} g{\\left(t + dt,x,y \\right)}$" ], "text/plain": [ "Derivative(g(t + dt, x, y), y)" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "g.forward.dy" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## A linear convection operator\n", "\n", "**Note:** The following example is derived from [step 5](http://nbviewer.ipython.org/github/barbagroup/CFDPython/blob/master/lessons/07_Step_5.ipynb) in the excellent tutorial series [CFD Python: 12 steps to Navier-Stokes](http://lorenabarba.com/blog/cfd-python-12-steps-to-navier-stokes/).\n", "\n", "In this simple example we will show how to derive a very simple convection operator from a high-level description of the governing equation. We will go through the process of deriving a discretised finite difference formulation of the state update for the field variable $u$, before creating a callable `Operator` object. Luckily, the automation provided by SymPy makes the derivation very nice and easy.\n", "\n", "The governing equation we want to implement is the linear convection equation:\n", "$$\\frac{\\partial u}{\\partial t}+c\\frac{\\partial u}{\\partial x} + c\\frac{\\partial u}{\\partial y} = 0.$$\n", "\n", "Before we begin, we must define some parameters including the grid, the number of timesteps and the timestep size. We will also initialize our velocity `u` with a smooth field:" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "tags": [ "nbval-ignore-output" ] }, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from examples.cfd import init_smooth, plot_field\n", "\n", "nt = 100 # Number of timesteps\n", "dt = 0.2 * 2. / 80 # Timestep size (sigma=0.2)\n", "c = 1 # Value for c\n", "\n", "# Then we create a grid and our function\n", "grid = Grid(shape=(81, 81), extent=(2., 2.))\n", "u = TimeFunction(name='u', grid=grid)\n", "\n", "# We can now set the initial condition and plot it\n", "init_smooth(field=u.data[0], dx=grid.spacing[0], dy=grid.spacing[1])\n", "init_smooth(field=u.data[1], dx=grid.spacing[0], dy=grid.spacing[1])\n", "\n", "plot_field(u.data[0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next, we wish to discretise our governing equation so that a functional `Operator` can be created from it. We begin by simply writing out the equation as a symbolic expression, while using shorthand expressions for the derivatives provided by the `Function` object. This will create a symbolic object of the dicretised equation.\n", "\n", "Using the Devito shorthand notation, we can express the governing equations as:" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle \\frac{\\partial}{\\partial x} u{\\left(t,x,y \\right)} + \\frac{\\partial}{\\partial y} u{\\left(t,x,y \\right)} + \\frac{\\partial}{\\partial t} u{\\left(t,x,y \\right)} = 0$" ], "text/plain": [ "Eq(Derivative(u(t, x, y), x) + Derivative(u(t, x, y), y) + Derivative(u(t, x, y), t), 0)" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "eq = Eq(u.dt + c * u.dxl + c * u.dyl)\n", "eq" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We now need to rearrange our equation so that the term $u(t+dt, x, y)$ is on the left-hand side, since it represents the next point in time for our state variable $u$. Devito provides a utility called `solve`, built on top of SymPy's `solve`, to rearrange our equation so that it represents a valid state update for $u$. Here, we use `solve` to create a valid stencil for our update to `u(t+dt, x, y)`:" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle u{\\left(t + dt,x,y \\right)} = dt \\left(- \\frac{u{\\left(t,x,y \\right)}}{h_{y}} + \\frac{u{\\left(t,x,y - h_{y} \\right)}}{h_{y}} - \\frac{u{\\left(t,x,y \\right)}}{h_{x}} + \\frac{u{\\left(t,x - h_{x},y \\right)}}{h_{x}} + \\frac{u{\\left(t,x,y \\right)}}{dt}\\right)$" ], "text/plain": [ "Eq(u(t + dt, x, y), dt*(-u(t, x, y)/h_y + u(t, x, y - h_y)/h_y - u(t, x, y)/h_x + u(t, x - h_x, y)/h_x + u(t, x, y)/dt))" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "stencil = solve(eq, u.forward)\n", "update = Eq(u.forward, stencil)\n", "update" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The right-hand side of the 'update' equation should be a stencil of the shape\n", "\n", "\n", "Once we have created this 'update' expression, we can create a Devito `Operator`. This `Operator` will basically behave like a Python function that we can call to apply the created stencil over our associated data, as long as we provide all necessary unknowns. In this case we need to provide the number of timesteps to compute via the keyword `time` and the timestep size via `dt` (both have been defined above):" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "tags": [ "nbval-ignore-output" ] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Operator `Kernel` run in 0.01 s\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "op = Operator(update, opt='noop')\n", "op(time=nt+1, dt=dt)\n", "\n", "plot_field(u.data[0])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Note that the real power of Devito is hidden within `Operator`, it will automatically generate and compile the optimized C code. We can look at this code (noting that this is not a requirement of executing it) via:" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "tags": [ "nbval-ignore-output" ] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "#define _POSIX_C_SOURCE 200809L\n", "#include \"stdlib.h\"\n", "#include \"math.h\"\n", "#include \"sys/time.h\"\n", "#include \"omp.h\"\n", "\n", "struct dataobj\n", "{\n", " void *restrict data;\n", " int * size;\n", " int * npsize;\n", " int * dsize;\n", " int * hsize;\n", " int * hofs;\n", " int * oofs;\n", "} ;\n", "\n", "struct profiler\n", "{\n", " double section0;\n", "} ;\n", "\n", "\n", "int Kernel(const float dt, const float h_x, const float h_y, struct dataobj *restrict u_vec, const int time_M, const int time_m, struct profiler * timers, const int x_M, const int x_m, const int y_M, const int y_m, const int nthreads)\n", "{\n", " float (*restrict u)[u_vec->size[1]][u_vec->size[2]] __attribute__ ((aligned (64))) = (float (*)[u_vec->size[1]][u_vec->size[2]]) u_vec->data;\n", " for (int time = time_m, t0 = (time)%(2), t1 = (time + 1)%(2); time <= time_M; time += 1, t0 = (time)%(2), t1 = (time + 1)%(2))\n", " {\n", " struct timeval start_section0, end_section0;\n", " gettimeofday(&start_section0, NULL);\n", " /* Begin section0 */\n", " #pragma omp parallel num_threads(nthreads)\n", " {\n", " #pragma omp for collapse(1) schedule(dynamic,1)\n", " for (int x = x_m; x <= x_M; x += 1)\n", " {\n", " for (int y = y_m; y <= y_M; y += 1)\n", " {\n", " u[t1][x + 1][y + 1] = dt*(u[t0][x + 1][y]/h_y - u[t0][x + 1][y + 1]/h_y + u[t0][x][y + 1]/h_x - u[t0][x + 1][y + 1]/h_x + u[t0][x + 1][y + 1]/dt);\n", " }\n", " }\n", " }\n", " /* End section0 */\n", " gettimeofday(&end_section0, NULL);\n", " timers->section0 += (double)(end_section0.tv_sec-start_section0.tv_sec)+(double)(end_section0.tv_usec-start_section0.tv_usec)/1000000;\n", " }\n", " return 0;\n", "}\n", "\n" ] } ], "source": [ "print(op.ccode)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Second derivatives and high-order stencils\n", "\n", "In the above example only a combination of first derivatives was present in the governing equation. However, second (or higher) order derivatives are often present in scientific problems of interest, notably any PDE modeling diffusion. To generate second order derivatives we must give the `devito.Function` object another piece of information: the desired discretisation of the stencil(s).\n", "\n", "First, lets define a simple second derivative in `x`, for which we need to give $u$ a `space_order` of (at least) `2`. The shorthand for this second derivative is `u.dx2`. " ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle \\frac{\\partial^{2}}{\\partial x^{2}} u{\\left(t,x,y \\right)}$" ], "text/plain": [ "Derivative(u(t, x, y), (x, 2))" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "u = TimeFunction(name='u', grid=grid, space_order=2)\n", "u.dx2" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle - \\frac{2.0 u{\\left(t,x,y \\right)}}{h_{x}^{2}} + \\frac{u{\\left(t,x - h_{x},y \\right)}}{h_{x}^{2}} + \\frac{u{\\left(t,x + h_{x},y \\right)}}{h_{x}^{2}}$" ], "text/plain": [ "-2.0*u(t, x, y)/h_x**2 + u(t, x - h_x, y)/h_x**2 + u(t, x + h_x, y)/h_x**2" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "u.dx2.evaluate" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can increase the discretisation arbitrarily if we wish to specify higher order FD stencils:" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle \\frac{\\partial^{2}}{\\partial x^{2}} u{\\left(t,x,y \\right)}$" ], "text/plain": [ "Derivative(u(t, x, y), (x, 2))" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "u = TimeFunction(name='u', grid=grid, space_order=4)\n", "u.dx2" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle - \\frac{2.5 u{\\left(t,x,y \\right)}}{h_{x}^{2}} - \\frac{0.0833333333 u{\\left(t,x - 2 h_{x},y \\right)}}{h_{x}^{2}} + \\frac{1.33333333 u{\\left(t,x - h_{x},y \\right)}}{h_{x}^{2}} + \\frac{1.33333333 u{\\left(t,x + h_{x},y \\right)}}{h_{x}^{2}} - \\frac{0.0833333333 u{\\left(t,x + 2 h_{x},y \\right)}}{h_{x}^{2}}$" ], "text/plain": [ "-2.5*u(t, x, y)/h_x**2 - 0.0833333333*u(t, x - 2*h_x, y)/h_x**2 + 1.33333333*u(t, x - h_x, y)/h_x**2 + 1.33333333*u(t, x + h_x, y)/h_x**2 - 0.0833333333*u(t, x + 2*h_x, y)/h_x**2" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "u.dx2.evaluate" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To implement the diffusion or wave equations, we must take the Laplacian $\\nabla^2 u$, which is the sum of the second derivatives in all spatial dimensions. For this, Devito also provides a shorthand expression, which means we do not have to hard-code the problem dimension (2D or 3D) in the code. To change the problem dimension we can create another `Grid` object and use this to re-define our `Function`'s:" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle u{\\left(t,x,y,z \\right)}$" ], "text/plain": [ "u(t, x, y, z)" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "grid_3d = Grid(shape=(5, 6, 7), extent=(1., 1., 1.))\n", "\n", "u = TimeFunction(name='u', grid=grid_3d, space_order=2)\n", "u" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can re-define our function `u` with a different `space_order` argument to change the discretisation order of the stencil expression created. For example, we can derive an expression of the 12th-order Laplacian $\\nabla^2 u$:" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle \\frac{\\partial^{2}}{\\partial x^{2}} u{\\left(t,x,y,z \\right)} + \\frac{\\partial^{2}}{\\partial y^{2}} u{\\left(t,x,y,z \\right)} + \\frac{\\partial^{2}}{\\partial z^{2}} u{\\left(t,x,y,z \\right)}$" ], "text/plain": [ "Derivative(u(t, x, y, z), (x, 2)) + Derivative(u(t, x, y, z), (y, 2)) + Derivative(u(t, x, y, z), (z, 2))" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "u = TimeFunction(name='u', grid=grid_3d, space_order=12)\n", "u.laplace" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The same expression could also have been generated explicitly via:" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle \\frac{\\partial^{2}}{\\partial x^{2}} u{\\left(t,x,y,z \\right)} + \\frac{\\partial^{2}}{\\partial y^{2}} u{\\left(t,x,y,z \\right)} + \\frac{\\partial^{2}}{\\partial z^{2}} u{\\left(t,x,y,z \\right)}$" ], "text/plain": [ "Derivative(u(t, x, y, z), (x, 2)) + Derivative(u(t, x, y, z), (y, 2)) + Derivative(u(t, x, y, z), (z, 2))" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "u.dx2 + u.dy2 + u.dz2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Derivatives of composite expressions\n", "\n", "Derivatives of any arbitrary expression can easily be generated:" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": [ "u = TimeFunction(name='u', grid=grid, space_order=2)\n", "v = TimeFunction(name='v', grid=grid, space_order=2, time_order=2)" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle \\frac{\\partial^{2}}{\\partial x^{2}} u{\\left(t,x,y \\right)} + \\frac{\\partial^{2}}{\\partial y^{2}} u{\\left(t,x,y \\right)} + \\frac{\\partial^{2}}{\\partial t^{2}} v{\\left(t,x,y \\right)}$" ], "text/plain": [ "Derivative(u(t, x, y), (x, 2)) + Derivative(u(t, x, y), (y, 2)) + Derivative(v(t, x, y), (t, 2))" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "v.dt2 + u.laplace" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle \\frac{\\partial^{2}}{\\partial x^{2}} \\left(\\frac{\\partial^{2}}{\\partial x^{2}} u{\\left(t,x,y \\right)} + \\frac{\\partial^{2}}{\\partial y^{2}} u{\\left(t,x,y \\right)} + \\frac{\\partial^{2}}{\\partial t^{2}} v{\\left(t,x,y \\right)}\\right)$" ], "text/plain": [ "Derivative(Derivative(u(t, x, y), (x, 2)) + Derivative(u(t, x, y), (y, 2)) + Derivative(v(t, x, y), (t, 2)), (x, 2))" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "(v.dt2 + u.laplace).dx2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Which can, depending on the chosen discretisation, lead to fairly complex stencils: " ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "text/latex": [ "$\\displaystyle - \\frac{2.0 \\left(- \\frac{2.0 u{\\left(t,x,y \\right)}}{h_{y}^{2}} + \\frac{u{\\left(t,x,y - h_{y} \\right)}}{h_{y}^{2}} + \\frac{u{\\left(t,x,y + h_{y} \\right)}}{h_{y}^{2}} - \\frac{2.0 u{\\left(t,x,y \\right)}}{h_{x}^{2}} + \\frac{u{\\left(t,x - h_{x},y \\right)}}{h_{x}^{2}} + \\frac{u{\\left(t,x + h_{x},y \\right)}}{h_{x}^{2}} - \\frac{2.0 v{\\left(t,x,y \\right)}}{dt^{2}} + \\frac{v{\\left(t - dt,x,y \\right)}}{dt^{2}} + \\frac{v{\\left(t + dt,x,y \\right)}}{dt^{2}}\\right)}{h_{x}^{2}} + \\frac{- \\frac{2.0 u{\\left(t,x - h_{x},y \\right)}}{h_{y}^{2}} + \\frac{u{\\left(t,x - h_{x},y - h_{y} \\right)}}{h_{y}^{2}} + \\frac{u{\\left(t,x - h_{x},y + h_{y} \\right)}}{h_{y}^{2}} + \\frac{u{\\left(t,x,y \\right)}}{h_{x}^{2}} + \\frac{u{\\left(t,x - 2 h_{x},y \\right)}}{h_{x}^{2}} - \\frac{2.0 u{\\left(t,x - h_{x},y \\right)}}{h_{x}^{2}} - \\frac{2.0 v{\\left(t,x - h_{x},y \\right)}}{dt^{2}} + \\frac{v{\\left(t - dt,x - h_{x},y \\right)}}{dt^{2}} + \\frac{v{\\left(t + dt,x - h_{x},y \\right)}}{dt^{2}}}{h_{x}^{2}} + \\frac{- \\frac{2.0 u{\\left(t,x + h_{x},y \\right)}}{h_{y}^{2}} + \\frac{u{\\left(t,x + h_{x},y - h_{y} \\right)}}{h_{y}^{2}} + \\frac{u{\\left(t,x + h_{x},y + h_{y} \\right)}}{h_{y}^{2}} + \\frac{u{\\left(t,x,y \\right)}}{h_{x}^{2}} - \\frac{2.0 u{\\left(t,x + h_{x},y \\right)}}{h_{x}^{2}} + \\frac{u{\\left(t,x + 2 h_{x},y \\right)}}{h_{x}^{2}} - \\frac{2.0 v{\\left(t,x + h_{x},y \\right)}}{dt^{2}} + \\frac{v{\\left(t - dt,x + h_{x},y \\right)}}{dt^{2}} + \\frac{v{\\left(t + dt,x + h_{x},y \\right)}}{dt^{2}}}{h_{x}^{2}}$" ], "text/plain": [ "-2.0*(-2.0*u(t, x, y)/h_y**2 + u(t, x, y - h_y)/h_y**2 + u(t, x, y + h_y)/h_y**2 - 2.0*u(t, x, y)/h_x**2 + u(t, x - h_x, y)/h_x**2 + u(t, x + h_x, y)/h_x**2 - 2.0*v(t, x, y)/dt**2 + v(t - dt, x, y)/dt**2 + v(t + dt, x, y)/dt**2)/h_x**2 + (-2.0*u(t, x - h_x, y)/h_y**2 + u(t, x - h_x, y - h_y)/h_y**2 + u(t, x - h_x, y + h_y)/h_y**2 + u(t, x, y)/h_x**2 + u(t, x - 2*h_x, y)/h_x**2 - 2.0*u(t, x - h_x, y)/h_x**2 - 2.0*v(t, x - h_x, y)/dt**2 + v(t - dt, x - h_x, y)/dt**2 + v(t + dt, x - h_x, y)/dt**2)/h_x**2 + (-2.0*u(t, x + h_x, y)/h_y**2 + u(t, x + h_x, y - h_y)/h_y**2 + u(t, x + h_x, y + h_y)/h_y**2 + u(t, x, y)/h_x**2 - 2.0*u(t, x + h_x, y)/h_x**2 + u(t, x + 2*h_x, y)/h_x**2 - 2.0*v(t, x + h_x, y)/dt**2 + v(t - dt, x + h_x, y)/dt**2 + v(t + dt, x + h_x, y)/dt**2)/h_x**2" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "(v.dt2 + u.laplace).dx2.evaluate" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.7" }, "widgets": { "state": {}, "version": "1.1.2" } }, "nbformat": 4, "nbformat_minor": 4 }