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    A simple and surprisingly easy to use partial-differential equation solver of the heat/diffusion equation and wave equation. The goal of this project was for driving visualizations not for performing exacting scientific analysis. The forward Euler step is employed for simplicity and speed, as well as further simplifying the discrete equations with the convolution operator.

    It solves the pde on an mxn grid with m and n being set by the setResolution method. Each call to update increases the solution by a time step given by dt. Depending on what the spatial step dx is set at is how fast the solution will converge - remember v = x/t from highschool. update outputs a single column vector that must be indexed by f[i*n + j] where 0 < i < m and 0 < j < n. The reason pde-engine outputs a 2D array strung out as a 1D vector is for computational speed.

    Version 0.2.0 uses Typed Arrays for computational efficiency / speed.

    I am using this thing without problems on my website by matching the output of each update step from the solver with a range of color values from colormap.

    How to use

    var engine = require('pde-engine')
      , aprint = require('printarray')
      , field = engine( {
        dt: 0.1
      , gamma: 0.02
      , eqn: "wave"        // put "diffusion" here to solve the heat eqn.
    var dims = {
      x: 12
    , y: 12
     * This sets up the dimensions of the field.
     * Everytime setResolution is called the field
     * arrays are reset (new Typed Arrays of given size
     * are created.)
    field.setResolution(dims.x, dims.y)
    var src = {
      x: 3
    , y: 5
    , mag: 1
     * You can add sources before you begin the timesteps (updates)
     * or during. Note if you begin updating field (progressing in time)
     * before adding a source the field will have no energy and will not
     * evolve (the 2D diffusion of zero is zero).
    field.addSource(src.x, src.y, src.mag)
     * Run the wave eqn solver.
     * Do something cool with the
     * coefficients: plot with html5 canvas
     * or gnuplot or whatever, or turn it into
     * animations within a website or video game.
    var steps = 5
    var tic = setInterval( function () {
      var coeffs = field.update()
      // Render coeffs
      aprint(coeffs, 5, [dims.x, dims.y])
      if (steps === 0)
    } , 1000 )

    The addSource method specifies the location of the source at that particular timestep with magnitude mag. Right now it emplaces a hard-coded Gaussian source centred at (row, col), with boundary cases already implemented. Every time field.update


    The following are possible configuration options. If configs are omitted defaults will be used. The defaults are given after the ||:

          dt = spec.dt || 0.1          // time step
        , dx = spec.dx || 1            // spatial step
        , gamma = spec.gamma || 0.02   // wave or diffusion paramater (controls decay)
        , vel = spec.vel || 2          // wave velocity
        , eqn = spec.eqn || 'wave'     // or "diffusion"

    Note that the forward Euler approach suffers from poor stability. It is a good idea to keep dt < dx , probably by a factor of 0.5. If your solutions are not converging (things go crazy) try modifying these variables.


    npm install pde-engine

    then write some code with engine = require('pde-engine') in it. If you want it in the browser do a

    browserify mycode.js -o bundle.js

    to include it. See benpostlethwaite.ca for a working example.

    Versioning and updates

    This is an early but fully working physics engine. Future releases may optimize algorithms or add new methods/configs, but this basic API should remain stable.

    Tests will be coming soon. For now this is primarily a tool for graphics.




    npm i pde-engine

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