{ "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": [ "$\\displaystyle u{\\left(t + dt,x,y \\right)} = dt \\left(- \\frac{\\partial}{\\partial x} u{\\left(t,x,y \\right)} - \\frac{\\partial}{\\partial y} u{\\left(t,x,y \\right)} + \\frac{u{\\left(t,x,y \\right)}}{dt}\\right)$" ], "text/plain": [ "Eq(u(t + dt, x, y), dt*(-Derivative(u(t, x, y), x) - Derivative(u(t, x, y), y) + 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` ran 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", "#define START_TIMER(S) struct timeval start_ ## S , end_ ## S ; gettimeofday(&start_ ## S , NULL);\n", "#define STOP_TIMER(S,T) gettimeofday(&end_ ## S, NULL); T->S += (double)(end_ ## S .tv_sec-start_ ## S.tv_sec)+(double)(end_ ## S .tv_usec-start_ ## S .tv_usec)/1000000;\n", "\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, const int x_M, const int x_m, const int y_M, const int y_m, const int nthreads, struct profiler * timers)\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", "\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", " /* Begin section0 */\n", " START_TIMER(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", " STOP_TIMER(section0,timers)\n", " /* End section0 */\n", " }\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": "3.8.8" }, "widgets": { "state": {}, "version": "1.1.2" } }, "nbformat": 4, "nbformat_minor": 4 }