09_tutorial_lees-edwards.ipynb 258 KB
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{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
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    "# Lees Edwards boundary conditions with lbmpy\n",
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    "\n",
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    "This example shows how to implement Lees Edwards boundary conditions following the principles discussed in Wagner, A.J., Pagonabarraga, I. Lees–Edwards Boundary Conditions for Lattice Boltzmann. Journal of Statistical Physics 107, 521–537 (2002). https://doi.org/10.1023/A:1014595628808"
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from lbmpy.session import *\n",
    "from lbmpy.updatekernels import create_stream_pull_with_output_kernel\n",
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    "from lbmpy.macroscopic_value_kernels import macroscopic_values_setter\n",
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    "from lbmpy.maxwellian_equilibrium import get_weights\n",
    "from lbmpy.relaxationrates import lattice_viscosity_from_relaxation_rate\n",
    "from pystencils.astnodes import LoopOverCoordinate\n",
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    "from pystencils.slicing import get_periodic_boundary_functor\n",
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    "from functools import partial"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "N = 64                   # domain size\n",
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    "omega = 1.0             # relaxation rate of first component\n",
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    "U_x = 0.1                # shear velocity\n",
    "shear_dir = 0            # direction of shear flow\n",
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    "shear_dir_normal = 1     # direction normal to shear plane, for interpolation\n",
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    "\n",
    "stencil = get_stencil(\"D2Q9\")\n",
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    "weights = get_weights(stencil, c_s_sq=sp.Rational(1, 3))"
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   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data structures\n",
    "\n",
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    "We allocate a set of PDFs `src` and `dst`, the density field `rho` and the velocity field `u`.\n",
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    "For later testing, we also need a force field `F`. This will be allocated as well. \n",
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    "\n",
    "To run the simulation on GPU, change the `default_target` to gpu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "dim = len(stencil[0])\n",
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    "dh = ps.create_data_handling((N, ) * dim,\n",
    "                             periodicity=True,\n",
    "                             default_target='cpu')\n",
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    "\n",
    "src = dh.add_array('src', values_per_cell=len(stencil))\n",
    "dst = dh.add_array_like('dst', 'src')\n",
    "F = dh.add_array('F', values_per_cell=dh.dim)\n",
    "\n",
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    "rho = dh.add_array('rho', values_per_cell=1)\n",
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    "u = dh.add_array('u', values_per_cell=dh.dim)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Kernels\n",
    "\n",
    "Following Wagner et al., we need to find all the populations that will cross the boundary in the direction normal to the shearing direction and alter their equilibrium distribution.\n",
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    "Hence, we construct a piecewise function that fulfils this."
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
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    "counters = [LoopOverCoordinate.get_loop_counter_symbol(i) for i in range(dim)]\n",
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    "points_up = sp.Symbol('points_up')\n",
    "points_down = sp.Symbol('points_down')\n",
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    "\n",
    "U_p = sp.Piecewise((1,  sp.And(ps.data_types.type_all_numbers(counters[1] <= 1, 'int'), points_down)),\n",
    "                   (-1, sp.And(ps.data_types.type_all_numbers(counters[1] >= src.shape[1] - 2, 'int'),\n",
    "                               points_up)), (0, True)) * U_x"
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   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
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    "For the LB update, we will use a velocity input in the shearing direction with the magnitude `U_x` that is defined further up."
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
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   "outputs": [],
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   "source": [
    "collision = create_lb_update_rule(stencil=stencil,\n",
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    "                                  relaxation_rate=omega,\n",
    "                                  compressible=True,\n",
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    "                                  velocity_input=u.center_vector+sp.Matrix([U_p, 0]),\n",
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    "                                  density_input=rho,\n",
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    "                                  force_model='luo',\n",
    "                                  force=F.center_vector,\n",
    "                                  kernel_type='collide_only',\n",
    "                                  optimization={'symbolic_field': src})"
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   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
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    "We need to get the populations that cross the upper and lower boundary, respectively."
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
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   "outputs": [],
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   "source": [
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    "to_insert = [s.lhs for s in collision.subexpressions\n",
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    "             if collision.method.first_order_equilibrium_moment_symbols[shear_dir]\n",
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    "             in s.free_symbols]\n",
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    "for s in to_insert:\n",
    "    collision = collision.new_with_inserted_subexpression(s)\n",
    "ma = []\n",
    "for a, c in zip(collision.main_assignments, collision.method.stencil):\n",
    "    if c[shear_dir_normal] == -1:\n",
    "        b = (True, False)\n",
    "    elif c[shear_dir_normal] == 1:\n",
    "        b = (False, True)\n",
    "    else:\n",
    "        b = (False, False)\n",
    "    a = ps.Assignment(a.lhs, a.rhs.replace(points_down, b[0]))\n",
    "    a = ps.Assignment(a.lhs, a.rhs.replace(points_up, b[1]))\n",
    "    ma.append(a)\n",
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    "collision.main_assignments = ma"
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
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   "outputs": [],
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   "source": [
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    "stream = create_stream_pull_with_output_kernel(collision.method, src, dst,\n",
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    "                                               {'density': rho, 'velocity': u})\n",
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    "\n",
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    "stream_kernel = ps.create_kernel(stream, target=dh.default_target).compile()\n",
    "collision_kernel = ps.create_kernel(collision, target=dh.default_target).compile()"
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   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initialization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
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   "outputs": [],
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   "source": [
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    "init = macroscopic_values_setter(collision.method, velocity=(0, 0),\n",
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    "                                 pdfs=src.center_vector, density=rho.center)\n",
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    "init_kernel = ps.create_kernel(init, ghost_layers=0).compile()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def init():\n",
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    "    dh.fill(rho.name, 1.0, ghost_layers=True)\n",
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    "    dh.fill(src.name, 0.0, ghost_layers=True)\n",
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    "    dh.fill(u.name, 0.0, ghost_layers=True)\n",
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    "    dh.fill(F.name, 0.0, ghost_layers=True)\n",
    "    dh.run_kernel(init_kernel)"
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   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Interpolation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
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    "After applying the normal periodic boundary conditions, we interpolate back in the original cells by using a linear interpolation scheme. In this step, the corners are not special anymore so that we can use the entire upper and lower slab."
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
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    "def get_le_boundary_functor(neighbor_stencil, shear_offset, ghost_layers=1, thickness=None):\n",
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    "\n",
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    "    functor_2 = get_periodic_boundary_functor(neighbor_stencil, ghost_layers, thickness)\n",
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    "\n",
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    "    def functor(pdfs, **_):\n",
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    "\n",
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    "        functor_2(pdfs)\n",
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    "        weight = np.fmod(shear_offset[0] + N, 1.)\n",
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    "\n",
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    "        # First, we interpolate the upper pdfs\n",
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    "#        for i in range(len(pdfs[:, ghost_layers, :])):\n",
    "#\n",
    "#            ind1 = int(np.floor(i - shear_offset[0]) % N)\n",
    "#            ind2 = int(np.ceil(i - shear_offset[0]) % N)\n",
    "#\n",
    "#            res = (1-weight) * pdfs[ind1, ghost_layers, :] + \\\n",
    "#                     weight * pdfs[ind2, ghost_layers, :]\n",
    "#            pdfs[i, -ghost_layers, :] = res\n",
    "#\n",
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    "        # Second, we interpolate the lower pdfs\n",
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    "#        for i in range(len(pdfs[:, -ghost_layers, :])):\n",
    "#\n",
    "#            ind1 = int(np.floor(i + shear_offset[0]) % N)\n",
    "#            ind2 = int(np.ceil(i + shear_offset[0]) % N)\n",
    "#\n",
    "#            res = (1-weight) * pdfs[ind1, -ghost_layers-1, :] + \\\n",
    "#                     weight * pdfs[ind2, -ghost_layers-1, :]\n",
    "#            pdfs[i, ghost_layers-1, :] = res\n",
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    "\n",
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    "    return functor"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Timeloop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "offset = [0.0]\n",
    "\n",
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    "sync_pdfs = dh.synchronization_function([src.name],\n",
    "                                        functor=partial(get_le_boundary_functor, shear_offset=offset))\n",
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    "\n",
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    "\n",
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    "def time_loop(steps, shift):\n",
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    "    dh.all_to_gpu()\n",
    "    for i in range(steps):\n",
    "        dh.run_kernel(collision_kernel)\n",
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    "\n",
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    "        sync_pdfs()\n",
    "        dh.run_kernel(stream_kernel)\n",
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    "\n",
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    "        dh.swap(src.name, dst.name)\n",
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    "        shift[0] += U_x\n",
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    "    dh.all_to_cpu()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_v():\n",
    "    plt.subplot(121)\n",
    "    plt.title(\"$v_A$\")\n",
    "    plt.vector_field(dh.gather_array(u.name), step=2)\n",
    "    plt.subplot(122)\n",
    "    plt.vector_field_magnitude(dh.gather_array(u.name))\n",
    "    plt.colorbar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run the simulation\n",
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    "### Initialize all velocities with zero"
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
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   "outputs": [],
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   "source": [
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    "init()"
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  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
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    "### Run the simulation to show the flow profile"
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  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "image/png": 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\n",
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      "text/plain": [
       "<Figure size 1152x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "time = 500\n",
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    "time_loop(time, offset)\n",
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    "\n",
    "plot_v()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Checking the results\n",
    "\n",
    "This transient shear flow (planar Couette flow) can be modeled with the Navier Stokes equation. We use this as a testcase here.\n",
    "\n",
    "The solution of the Navier Stokes equation in this particular case yields:\n",
    "\n",
    "$ w(x,t) = v \\left[ \\frac{x}{h} - \\frac{1}{2} + \\sum_{k=1} ^\\infty \\frac{1}{\\pi k} e^{-\\frac{4 \\pi^2 \\nu k^2}{h^2} t} \\sin \\left( \\frac{2 \\pi}{h} kx \\right) \\right] $\n",
    "\n",
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    "with $w$ as the resulting velocity, $v$ as shear velocity, $h$ as the height, $\\nu$ as kinematic viscosity and $t$ as time."
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
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    "def get_solution_navier_stokes(x, t, viskosity, velocity=1.0, height=1.0, max_iterations=10):\n",
    "    w = x / height - 0.5\n",
    "    for k in np.arange(1, max_iterations + 1):\n",
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    "        w += 1.0 / (np.pi * k) * \\\n",
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    "            np.exp(-4 * np.pi**2 * viskosity * k**2 / height**2 * t) * \\\n",
    "            np.sin(2 * np.pi / height * k * x)\n",
    "    return velocity * w"
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "image/png": 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\n",
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      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "nu = lattice_viscosity_from_relaxation_rate(omega)\n",
    "h = N\n",
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    "k_max = 100\n",
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    "\n",
    "X = np.linspace(0.5, h-0.5, h)\n",
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    "U = get_solution_navier_stokes(X, time, nu, U_x, h, k_max)\n",
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    "plt.plot(U, X, label='analytical')\n",
    "\n",
    "X_lb = np.linspace(0.5, h-0.5, h)\n",
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    "U_lb = dh.gather_array(u.name)[0, :, 0]\n",
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    "\n",
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    "plt.plot(U_lb, X_lb, 'o-', label='lbmpy')\n",
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    "plt.legend()\n",
    "\n",
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    "np.testing.assert_array_almost_equal(U,\n",
    "                                     U_lb,\n",
    "                                     decimal=5)"
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   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing of the interpolation scheme\n",
    "\n",
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    "We redefine our init function here. In order to test the interpolation scheme, we send an impulse across the boundary in the shear gradient direction. If interpolated correctly, it should appear shifted to the right by the preselected offset. Therefore we also need to fix the offset and redefine the time loop."
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def time_loop_2(steps):\n",
    "    dh.all_to_gpu()\n",
    "    for i in range(steps):\n",
    "        dh.run_kernel(collision_kernel)\n",
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    "\n",
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    "        sync_pdfs()\n",
    "        dh.run_kernel(stream_kernel)\n",
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    "\n",
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    "        dh.swap(src.name, dst.name)\n",
    "    dh.all_to_cpu()\n",
    "\n",
    "\n",
    "def init_2():\n",
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    "    dh.fill(rho.name, 1.0, ghost_layers=True)\n",
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    "    dh.fill(src.name, 0.0, ghost_layers=True)\n",
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    "    dh.fill(u.name, 0.0, ghost_layers=True)\n",
    "    dh.fill(F.name, 0.0, ghost_layers=True)\n",
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    "    dh.cpu_arrays[F.name][N//3, 1, :] = [1e-2, -1e-1]\n",
    "    dh.run_kernel(init_kernel)"
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   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run the simulation without any offset and a constant offset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "image/png": 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\n",
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      "text/plain": [
       "<Figure size 1152x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "offset[0] = 0\n",
    "\n",
    "init_2()\n",
    "time = 20\n",
    "time_loop_2(time)\n",
    "plot_v()\n",
    "\n",
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    "vel_unshifted = np.array(dh.gather_array(u.name)[:, -3:-1, :])"
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   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "image/png": 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\n",
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      "text/plain": [
       "<Figure size 1152x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "offset[0] = 10\n",
    "\n",
    "init_2()\n",
    "time = 20\n",
    "time_loop_2(time)\n",
    "plot_v()\n",
    "\n",
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    "vel_shifted = np.array(dh.gather_array(u.name)[:, -3:-1, :])"
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   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### We role the array back by the offset and compare it to the results of the unshifted measurement"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
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   "outputs": [
    {
     "ename": "AssertionError",
     "evalue": "\nArrays are not almost equal to 6 decimals\n\nMismatched elements: 187 / 256 (73%)\nMax absolute difference: 0.07692255\nMax relative difference: 1.73693318e+13\n x: array([[[ 1.649015e-02,  2.973693e-08],\n        [ 2.793467e-02,  4.658195e-08]],\n...\n y: array([[[ 1.507849e-02,  1.511962e-03],\n        [ 2.727587e-02,  1.979193e-03]],\n...",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-20-ce36d3f4fc61>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mvel_rolled\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mroll\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvel_shifted\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0moffset\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtesting\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0massert_array_almost_equal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvel_unshifted\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvel_rolled\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "    \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n",
      "\u001b[0;32m~/Library/Python/3.7/lib/python/site-packages/numpy/testing/_private/utils.py\u001b[0m in \u001b[0;36massert_array_compare\u001b[0;34m(comparison, x, y, err_msg, verbose, header, precision, equal_nan, equal_inf)\u001b[0m\n\u001b[1;32m    844\u001b[0m                                 \u001b[0mverbose\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mverbose\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheader\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheader\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    845\u001b[0m                                 names=('x', 'y'), precision=precision)\n\u001b[0;32m--> 846\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mAssertionError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    847\u001b[0m     \u001b[0;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    848\u001b[0m         \u001b[0;32mimport\u001b[0m \u001b[0mtraceback\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mAssertionError\u001b[0m: \nArrays are not almost equal to 6 decimals\n\nMismatched elements: 187 / 256 (73%)\nMax absolute difference: 0.07692255\nMax relative difference: 1.73693318e+13\n x: array([[[ 1.649015e-02,  2.973693e-08],\n        [ 2.793467e-02,  4.658195e-08]],\n...\n y: array([[[ 1.507849e-02,  1.511962e-03],\n        [ 2.727587e-02,  1.979193e-03]],\n..."
     ]
    }
   ],
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   "source": [
    "vel_rolled = np.roll(vel_shifted, -offset[0], axis=0)\n",
    "\n",
Markus Holzer's avatar
Markus Holzer committed
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    "np.testing.assert_array_almost_equal(vel_unshifted, vel_rolled)"
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   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Finally let's run the simualtion with fixed offset a while longer"
   ]
  },
  {
   "cell_type": "code",
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   "execution_count": null,
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   "metadata": {},
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   "outputs": [],
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   "source": [
    "init_2()\n",
    "time = 500\n",
    "time_loop_2(time)\n",
    "plot_v()"
   ]
  }
 ],
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    "name": "ipython",
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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   "version": "3.7.9"
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