Exp_B_2D.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ae424bc3",
   "metadata": {},
   "outputs": [],
   "source": [
    "import underworld.visualisation as vis\n",
    "\n",
    "from underworld import function as fn\n",
    "import underworld as uw\n",
    "\n",
    "import matplotlib.pyplot as pyplot\n",
    "import numpy as np\n",
    "from scipy.spatial import distance\n",
    "\n",
    "import math\n",
    "import os\n",
    "import sys\n",
    "\n",
    "import time\n",
    "\n",
    "from scipy.signal import savgol_filter\n",
    "\n",
    "# deform the mesh geometry towards the ice-rock interface?\n",
    "deform_mesh = False\n",
    "perfect_mesh = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ff80bfe6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "resX: 64 resY: 32\n"
     ]
    }
   ],
   "source": [
    "# details of the bottom curve\n",
    "# L = [160, 80, 40, 20, 10, 5]\n",
    "L = 10\n",
    "# make it command line compatible\n",
    "if len(sys.argv):\n",
    "    try:\n",
    "        km_index = int(sys.argv[1])\n",
    "    except:\n",
    "        km_index = 5\n",
    "\n",
    "maxX = L * 1000.\n",
    "min_bed_height = 500.           # we want a minimum of 500 m of rock beneath the ice\n",
    "omega = 2.0 * np.pi / maxX\n",
    "amplitude = 500.\n",
    "average_bedthickness = 1000.\n",
    "surface_height = average_bedthickness + amplitude + min_bed_height\n",
    "maxY = surface_height\n",
    "\n",
    "minY = minX = 0.\n",
    "\n",
    "g = 9.81\n",
    "ice_density = 910.\n",
    "\n",
    "A = 1e-16\n",
    "n = 3.\n",
    "\n",
    "\n",
    "resX = 64\n",
    "resY = 32\n",
    "\n",
    "\n",
    "print(\"resX: \" + str(resX) + \" resY: \" + str(resY))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c3f4913",
   "metadata": {},
   "source": [
    "## generate output path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c36625e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "outputPath = os.path.join(os.path.abspath(\".\"), \"output_\" + str(maxX) + \"_res_\" + str(resX) + \"_x_\" + str(resY) + \"/\")\n",
    "\n",
    "if not os.path.exists(outputPath):\n",
    "    os.makedirs(outputPath)\n",
    "\n",
    "os.chdir(outputPath)\n",
    "\n",
    "delta_timestep = 1.\t\t\t\t\t\t# in years, used in the main loop\n",
    "# after how many timesteps do we need new figures?\n",
    "update_figures_after_n_timesteps = 1\n",
    "number_of_deformation_lines = 11\n",
    "\n",
    "number_of_deformation_points = 50000\n",
    "distance_between_deformation_lines = maxY / (number_of_deformation_lines + 1)\n",
    "\n",
    "cell_height = maxY / resY\n",
    "cell_width = maxX / resX"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2e7b6a3",
   "metadata": {},
   "source": [
    "## Mesh and mesh variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9c9afc20",
   "metadata": {},
   "outputs": [],
   "source": [
    "elementType = \"Q1/dQ0\"\n",
    "#elementType = \"Q2/dQ1\"\n",
    "#elementType = \"Q1/dPc1\"\n",
    "#elementType = \"Q2/dPc1\"\n",
    "\n",
    "mesh = uw.mesh.FeMesh_Cartesian(elementType=(elementType),\n",
    "                                elementRes=(resX, resY),\n",
    "                                minCoord=(minX, minY),\n",
    "                                maxCoord=(maxX, maxY),\n",
    "                                periodic=[True, False])\n",
    "\n",
    "submesh = mesh.subMesh\n",
    "\n",
    "# save the mesh\n",
    "# mesh.save(outputPath + \"mesh.h5\")\n",
    "\n",
    "velocityField = uw.mesh.MeshVariable(mesh=mesh, nodeDofCount=mesh.dim)\n",
    "#pressureField = uw.mesh.MeshVariable(mesh=mesh.subMesh, nodeDofCount=1)\n",
    "pressureField = uw.mesh.MeshVariable(mesh=mesh, nodeDofCount=1)\n",
    "\n",
    "viscosityField = uw.mesh.MeshVariable(mesh=mesh, nodeDofCount=1)\n",
    "\n",
    "strainRateField = mesh.add_variable(nodeDofCount=1)\n",
    "\n",
    "#pressureField.data[:] = 0.\n",
    "velocityField.data[:] = [0., 0.]\n",
    "\n",
    "# Initialise the 'materialVariable' data to represent different materials.\n",
    "materialA = 0  \t# accommodation layer, a.k.a. Sticky Air\n",
    "materialV = 1  \t# ice, isotropic\n",
    "materialR = 2   # rock\n",
    "materialT = 5   # test material in order to test eg interface detection\n",
    "\n",
    "coord = fn.input()\n",
    "\n",
    "z_bed_function = surface_height - average_bedthickness + amplitude * fn.math.sin(omega * coord[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "25dddca0",
   "metadata": {},
   "outputs": [
    {
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# # Define the ice-rock / ice-air interface \n",
    "\n",
    "botSet = mesh.specialSets['Bottom_VertexSet']\n",
    "topSet = mesh.specialSets['Top_VertexSet']\n",
    "\n",
    "dx = (maxX - minX) / resX\n",
    "iceRockInterface = []\n",
    "iceAirInterface = []\n",
    "\n",
    "dx = (maxX - minX) / resX\n",
    "\n",
    "for index in range(resX+1):\n",
    "    \n",
    "    start_x = dx * index\n",
    "\n",
    "    interface_y =  surface_height - average_bedthickness + amplitude * np.sin(start_x * (np.pi * 2.) / (maxX-minX) )\n",
    "                \n",
    "    #ind = np.where(abs(mesh.data[:,0] - start_x) < 0.01*dx)\n",
    "    iceRockInterface.append([start_x, interface_y])\n",
    "    iceAirInterface.append([start_x, maxY])\n",
    "\n",
    "\n",
    "# # Deform mesh to be almost structurally conforming\n",
    "\n",
    "# In[15]:\n",
    "\n",
    "\n",
    "def mesh_deform(section,fixPoint,mi):\n",
    "    \n",
    "    # fixPoint: the position to be refined\n",
    "    # mi: representing the gradient of mesh resolution; the larger mi, the larger gradient\n",
    "    # generally, mi ranges from 0.1 to 3, dependnig on the resolution \n",
    " \n",
    "    # note from Till: \n",
    "    # I normalize it, because then it becomes more clear to me.\n",
    "    # normalization is not strictly necessary\n",
    "    normalize = maxY - minY\n",
    "\n",
    "    section /= normalize\n",
    "    fixPoint /= normalize\n",
    "\n",
    "    for index in range(len(section)):\n",
    "        \n",
    "        maxCoord = np.max(section)\n",
    "        minCoord = np.min(section)\n",
    "        \n",
    "        if  section[index] < fixPoint:\n",
    "            zz_sqrt = (fixPoint - section[index])**mi\n",
    "            zz_sqrt_max = (fixPoint - minCoord)**mi\n",
    "            section[index] = fixPoint - (fixPoint - section[index]) * zz_sqrt / zz_sqrt_max\n",
    "\n",
    "        if  section[index] > fixPoint:\n",
    "            zz_sqrt = (section[index] - fixPoint)**mi\n",
    "            zz_sqrt_max = (maxCoord - fixPoint)**mi\n",
    "            section[index] = fixPoint + (section[index] - fixPoint) * zz_sqrt/zz_sqrt_max        \n",
    "    \n",
    "    return (section * normalize)\n",
    "\n",
    "dx = (maxX - minX) / resX\n",
    "\n",
    "\n",
    "if deform_mesh:\n",
    "    \n",
    "    with mesh.deform_mesh():\n",
    "\n",
    "        for index in range(resX+1):  \n",
    "\n",
    "            start_x = dx * index\n",
    "\n",
    "            interface_y =  surface_height - average_bedthickness + amplitude * np.sin(start_x * (np.pi * 2.) / (maxX-minX) )\n",
    "\n",
    "            #print (start_x,interface_y)\n",
    "            #lx.append(start_x)\n",
    "            #ly.append(interface_y)\n",
    "\n",
    "            #ind = np.where(abs(mesh.data[:,0] - start_x) < 0.01*dx)\n",
    "            ind = np.where(abs(mesh.data[:,0] - start_x) < 0.01*dx)\n",
    "\n",
    "            mesh.data[ind[0],1] = mesh_deform(mesh.data[ind[0],1], interface_y, 0.25)\n",
    "\n",
    "# visualise the result\n",
    "figMesh = vis.Figure(figsize=(1200,600))\n",
    "figMesh.append( vis.objects.Mesh(mesh) )\n",
    "figMesh.save_image(\"mesh_postdeform.png\")\n",
    "figMesh.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a5181b7",
   "metadata": {},
   "source": [
    "## Deform mesh to a perfect body fit mesh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d6f0a873",
   "metadata": {},
   "outputs": [
    {
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'>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualise the result\n",
    "def mesh_deform_Ind(section,fixPoint_index,fixPoint,mi):\n",
    "    \n",
    "    section[int(fixPoint_index)] = fixPoint\n",
    "    seqN = len(section)\n",
    "    \n",
    "    # fixPoint_index (int): specify the index of the section to be at the place need to be refined\n",
    "    # fixPoint: the position to be refined\n",
    "    # mi: representing the gradient of mesh resolution; the larger mi, the larger gradient\n",
    "    for index in range(len(section)):\n",
    "        \n",
    "        maxCoord = np.max(section)\n",
    "        minCoord = np.min(section)\n",
    "        \n",
    "        if  index < fixPoint_index:\n",
    "            section[index] = minCoord + index*(fixPoint-minCoord)/fixPoint_index            \n",
    "            zz_sqrt = (fixPoint-section[index])**mi\n",
    "            zz_sqrt_max = (fixPoint-minCoord)**mi\n",
    "            section[index] = fixPoint-(fixPoint-section[index])*zz_sqrt/zz_sqrt_max\n",
    "\n",
    "        if  index > fixPoint_index:\n",
    "            section[index] = fixPoint + (index-fixPoint_index)*(maxCoord-fixPoint)/(seqN-fixPoint_index-1)\n",
    "            zz_sqrt = (section[index]-fixPoint)**mi\n",
    "            zz_sqrt_max = (maxCoord-fixPoint)**mi\n",
    "            section[index] =fixPoint+(section[index]-fixPoint)*zz_sqrt/zz_sqrt_max    \n",
    "            \n",
    "    return (section)\n",
    "\n",
    "if (perfect_mesh):\n",
    "    \n",
    "    with mesh.deform_mesh():\n",
    "        \n",
    "        for index in range(resX+1):  \n",
    "            start_x = dx * index\n",
    "            \n",
    "            interface_y =  surface_height - average_bedthickness + amplitude * np.sin(start_x * (np.pi * 2.) / (maxX-minX) )\n",
    "            \n",
    "            ind = np.where(abs(mesh.data[:,0]-start_x)<0.01*dx)\n",
    "            \n",
    "            mesh.data[ind[0],1] = mesh_deform_Ind(mesh.data[ind[0],1],resY/2,interface_y,0.2)\n",
    "    # make the swarm belong the element that is the same as the in the regular mesh\n",
    "    \n",
    "    # visualise the result\n",
    "    figMesh = vis.Figure(figsize=(1200,600))\n",
    "    figMesh.append( vis.objects.Mesh(mesh) )\n",
    "    figMesh.save_image(\"mesh_deform_default_swarm.png\")\n",
    "    figMesh.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "80646580",
   "metadata": {},
   "outputs": [],
   "source": [
    "part_per_cell = 30\n",
    "swarm = uw.swarm.Swarm(mesh=mesh, particleEscape=True)\n",
    "\n",
    "#swarmLayout = uw.swarm.layouts.PerCellSpaceFillerLayout(swarm=swarm, particlesPerCell=part_per_cell)\n",
    "swarmLayout = uw.swarm.layouts.PerCellGaussLayout( swarm=swarm, gaussPointCount=5 )\n",
    "\n",
    "swarm.populate_using_layout(layout=swarmLayout)\n",
    "\n",
    "measurementSwarm = uw.swarm.Swarm(mesh=mesh, particleEscape=True)\n",
    "\n",
    "# create pop control object\n",
    "pop_control1 = uw.swarm.PopulationControl(swarm, aggressive=True, particlesPerCell=part_per_cell)\n",
    "pop_control2 = uw.swarm.PopulationControl(measurementSwarm)\n",
    "\n",
    "# ### Create a particle advection system\n",
    "#\n",
    "# Note that we need to set up one advector systems for each particle swarm (our global swarm and a separate one if we add passive tracers).\n",
    "advector1 = uw.systems.SwarmAdvector(swarm=swarm,velocityField=velocityField, order=2)\n",
    "advector2 = uw.systems.SwarmAdvector(swarm=measurementSwarm,     velocityField=velocityField, order=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "497bd34a",
   "metadata": {},
   "outputs": [
    {
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'>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Tracking different materials\n",
    "\n",
    "materialVariable = swarm.add_variable(dataType=\"int\", count=1)\n",
    "\n",
    "numbMeasurementPoints = resX + 1\n",
    "xloc = np.linspace(0, maxX, numbMeasurementPoints).reshape(-1,1)\n",
    "yloc = (surface_height - average_bedthickness + amplitude * np.sin(omega * xloc)).reshape(-1,1)\n",
    "xycoor = np.concatenate((xloc,yloc),axis = 1)\n",
    "\n",
    "measurementSwarm.add_particles_with_coordinates(xycoor)\n",
    "\n",
    "particleDensity = swarm.add_variable(dataType=\"double\", count=1)\n",
    "particleDensity.data[:] = 0.0\n",
    "\n",
    "coord = fn.input()\n",
    "\n",
    "conditions = [(coord[1] > surface_height, materialA),\n",
    "              (coord[1] < z_bed_function, materialR),\n",
    "              (True, materialV)]\n",
    "\n",
    "materialVariable.data[:] = fn.branching.conditional(conditions).evaluate(swarm)\n",
    "\n",
    "#pyplot.plot(measurementSwarm.data[:,0], measurementSwarm.data[:,1], color='black')\n",
    "\n",
    "figMesh = vis.Figure(figsize=(1200,600))\n",
    "figMesh.append( vis.objects.Mesh(mesh) )\n",
    "figMesh.append( vis.objects.Points( swarm, materialVariable, pointSize=10.0 ) )\n",
    "figMesh.save_image(\"mesh_deform.png\")\n",
    "figMesh.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a4b03d9",
   "metadata": {},
   "source": [
    "## Model viscosity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f407ff7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "strainRateTensor = fn.tensor.symmetric(velocityField.fn_gradient)\n",
    "strainRate_2ndInvariantFn = fn.tensor.second_invariant(strainRateTensor)\n",
    "\n",
    "minViscosityIceFn = fn.misc.constant(1e+10 / 3.1536e7)\n",
    "maxViscosityIceFn = fn.misc.constant(1e+15 / 3.1536e7)\n",
    "\n",
    "viscosityFnAir = fn.misc.constant(1e6 / 3.1536e7)\n",
    "viscosityFnRock = fn.misc.constant(1e22 / 3.1536e7)\n",
    "\n",
    "viscosityFnIceBase = 0.5 * A ** (-1./n) * (strainRate_2ndInvariantFn**((1.-n) / float(n)))\n",
    "viscosityFnIce = fn.misc.max(fn.misc.min(viscosityFnIceBase, maxViscosityIceFn), minViscosityIceFn)\n",
    "\n",
    "viscosityMap = {\n",
    "                materialV: viscosityFnIce,\n",
    "                materialA: viscosityFnAir,\n",
    "                materialR: viscosityFnRock,\n",
    "               }\n",
    "\n",
    "viscosityFn = fn.branching.map( fn_key=materialVariable, mapping=viscosityMap )\n",
    "\n",
    "logViscosityFn = fn.math.log10( fn.misc.max( fn.misc.min( viscosityFnIceBase, viscosityFnRock ), viscosityFnAir ) )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3817a13",
   "metadata": {},
   "source": [
    "## Bouyance force "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "27946c8d",
   "metadata": {},
   "outputs": [],
   "source": [
    "devStressFn = 2.0 * viscosityFn * strainRateTensor\n",
    "shearStressFn = strainRate_2ndInvariantFn * viscosityFn * 2.0\n",
    "\n",
    "densityFnAir = fn.misc.constant( 0. )\n",
    "densityFnIce = fn.misc.constant( ice_density )\n",
    "densityFnRock = fn.misc.constant( 2700. )\n",
    "\n",
    "densityMap = {\n",
    "                materialA: densityFnAir,\n",
    "                materialV: densityFnIce,\n",
    "                materialR: densityFnRock\n",
    "             }\n",
    "\n",
    "densityFn = fn.branching.map(fn_key=materialVariable, mapping=densityMap)\n",
    "\n",
    "particleDensity.data[:] = densityFn.evaluate(swarm)\n",
    "\n",
    "surf_inclination = 0.5 * np.pi / 180. # 0.1 = Experiment D, 0.5 = Experiment B\n",
    "#surf_inclination = 0.\n",
    "z_hat = (math.sin(surf_inclination), - math.cos(surf_inclination))\n",
    "#z_hat = (0.00872653549, -0.99996192306417128874)\n",
    "\n",
    "buoyancyFn = densityFn * z_hat * 9.81"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c1f06d4",
   "metadata": {},
   "source": [
    "## Solver and boundary conditions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "de8090e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "iWalls = mesh.specialSets[\"MinI_VertexSet\"] + mesh.specialSets[\"MaxI_VertexSet\"]\n",
    "jWalls = mesh.specialSets[\"MinJ_VertexSet\"] + mesh.specialSets[\"MaxJ_VertexSet\"]\n",
    "base = mesh.specialSets[\"MinJ_VertexSet\"]\n",
    "top = mesh.specialSets[\"MaxJ_VertexSet\"]\n",
    "\n",
    "velocityField.data[:] = [0., 0.]\n",
    "\n",
    "leftSet = mesh.specialSets['Left_VertexSet']\n",
    "rightSet = mesh.specialSets['Right_VertexSet']\n",
    "\n",
    "### Dirichlet\n",
    "condition1 = uw.conditions.DirichletCondition(variable=velocityField,indexSetsPerDof=(botSet, botSet))\n",
    "\n",
    "velocityField.data[:] = [0., 0.]\n",
    "\n",
    "stokes = uw.systems.Stokes(\n",
    "    velocityField=velocityField,\n",
    "    pressureField=pressureField,\n",
    "    voronoi_swarm=swarm,\n",
    "    conditions=[\n",
    "            condition1,\n",
    "            ],\n",
    "    fn_viscosity=viscosityFn,\n",
    "    fn_bodyforce=buoyancyFn,\n",
    ")\n",
    "\n",
    "solver = uw.systems.Solver(stokes)\n",
    "\n",
    "#solver.set_inner_method(\"lu\")\n",
    "#solver.set_inner_method(\"superlu\")\n",
    "solver.set_inner_method(\"mumps\")\n",
    "# solver.set_inner_method(\"superludist\")\n",
    "# solver.set_inner_method(\"mg\")\n",
    "#solver.set_inner_method(\"nomg\")\n",
    "\n",
    "# solver.set_penalty(1.0e10)  # higher penalty = larger stability\n",
    "# solver.options.scr.ksp_rtol = 1.0e-3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b671d44a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# nl_tol = 2.e1\n",
    "nl_tol = 5.e-3\n",
    "\n",
    "surfaceArea = uw.utils.Integral( fn=1.0, mesh=mesh, integrationType='surface', surfaceIndexSet=top)\n",
    "surfacePressureIntegral = uw.utils.Integral( fn=pressureField, mesh=mesh, integrationType='surface', surfaceIndexSet=top)\n",
    "\n",
    "def calibrate_pressure():\n",
    "\n",
    "    global pressureField\n",
    "    global surfaceArea\n",
    "    global surfacePressureIntegral\n",
    "\n",
    "    (area,) = surfaceArea.evaluate()\n",
    "    (p0,) = surfacePressureIntegral.evaluate() \n",
    "    pressureField.data[:] -= p0 / area\n",
    "\n",
    "    print (f'Calibration pressure {p0 / area}')\n",
    "\n",
    "# test it out\n",
    "try:\n",
    "    exec_time = time.time()\n",
    "    # solver.solve(nonLinearIterate=True, nonLinearTolerance=nl_tol, callback_post_solve=calibrate_pressure)\n",
    "    solver.solve(nonLinearIterate=True, callback_post_solve=calibrate_pressure)\n",
    "    # solver.solve(nonLinearIterate=True)\n",
    "    exec_time = time.time() - exec_time\n",
    "\n",
    "    # print time to a file\n",
    "    with open('../time.txt', 'a') as f:\n",
    "        f.write('length,' + str(maxX) + ',x_res:,' + str(resX) + ',y_res:,' + str(resY) + ',time in secs:,' + str(exec_time) + '\\n')\n",
    "        \n",
    "    # print full stats to a file\n",
    "    original_stdout = sys.stdout # Save a reference to the original standard output\n",
    "    \n",
    "    with open('../stats_' + \"output_\" + str(maxX) + \"_res_\" + str(resX) + '_x_' + str(resY) + '.txt', 'w') as f:\n",
    "        sys.stdout = f # Change the standard output to the file we created.\n",
    "        solver.print_stats()\n",
    "        sys.stdout = original_stdout # Reset the standard output to its original value\n",
    "        \n",
    "    solver.print_stats()\n",
    "except:\n",
    "    print(\"Solver died early..\")\n",
    "    exit(0)\n",
    "\n",
    "\n",
    "# # Output\n",
    "\n",
    "# In[48]:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1cd2dac8",
   "metadata": {},
   "outputs": [],
   "source": [
    "meshStressTensor = uw.mesh.MeshVariable(mesh, 3 )\n",
    "projectorStress = uw.utils.MeshVariable_Projection( meshStressTensor, devStressFn, type=0 )\n",
    "projectorStress.solve()\n",
    "\n",
    "## correct the pressure\n",
    "meshCorrectedPressure = uw.mesh.MeshVariable(mesh, 1 )\n",
    "meshSecondCorrectedPressure = mesh.add_variable( 1 )\n",
    "\n",
    "## a) from the pressureField\n",
    "meshCorrectedPress = uw.utils.MeshVariable_Projection( meshCorrectedPressure, pressureField, type=0 )\n",
    "meshCorrectedPress.solve()\n",
    "\n",
    "## b) from the stranirate tensor\n",
    "pressureFn = (strainRateTensor[0] + strainRateTensor[1]) * viscosityFn\n",
    "meshSecondCorrectedPress = uw.utils.MeshVariable_Projection( meshSecondCorrectedPressure, pressureFn, type=1 )\n",
    "meshSecondCorrectedPress.solve()\n",
    "\n",
    "## shear stress as saved to disk\n",
    "shearStressFn = 2.0 * viscosityFn * strainRateTensor[2]\n",
    "meshShearStress = mesh.add_variable( 1 )\n",
    "\n",
    "projectorStress = uw.utils.MeshVariable_Projection( meshShearStress, shearStressFn, type=0 )\n",
    "projectorStress.solve()\n",
    "\n",
    "## second invariant of stress as saved to disk\n",
    "secInvStressFn = 2.0 * viscosityFn * strainRate_2ndInvariantFn\n",
    "secInvStress = mesh.add_variable( 1 )\n",
    "\n",
    "projectorStress = uw.utils.MeshVariable_Projection( secInvStress, secInvStressFn, type=0 )\n",
    "projectorStress.solve()\n",
    "\n",
    "# save to disc\n",
    "outputFile = os.path.join(os.path.abspath(\".\"), outputPath + \"output_\" + str(maxX) + \".csv\")\n",
    "\n",
    "####\n",
    "\n",
    "x = np.linspace(0, maxX, resX+1)\n",
    "interfacex = [item[0] for item in iceRockInterface]\n",
    "interfacey = [item[1] for item in iceRockInterface]\n",
    "\n",
    "airinterfacey = [maxY for item in range(resX + 1)]\n",
    "\n",
    "iceRockInterface = np.array(iceRockInterface)\n",
    "iceAirInterface = np.array(iceAirInterface)\n",
    "\n",
    "add = 1. * cell_height\n",
    "sub = - 1. * cell_height\n",
    "\n",
    "#add = 5.\n",
    "#sub = - 5.\n",
    "\n",
    "###\n",
    "\n",
    "shearstress_xy_above = []\n",
    "corr_shearstress_xy_above = []\n",
    "shearstress_xy_below = []\n",
    "corr_shearstress_xy_below = []\n",
    "\n",
    "for i,j in zip(interfacex,interfacey):\n",
    "    \n",
    "    shearstress_xy_above.append(shearStressFn.evaluate((i,j + add))[0][0])\n",
    "    corr_shearstress_xy_above.append(meshStressTensor.evaluate((i,j + add))[0][2])\n",
    "    \n",
    "    shearstress_xy_below.append(shearStressFn.evaluate((i,j + sub))[0][0])\n",
    "    corr_shearstress_xy_below.append(meshStressTensor.evaluate((i,j + sub))[0][2])\n",
    "    \n",
    "secinvstress_above = []\n",
    "corr_secinvstress_above = []\n",
    "secinvstress_below = []\n",
    "corr_secinvstress_below = []\n",
    "\n",
    "for i,j in zip(interfacex,interfacey):\n",
    "    \n",
    "    secinvstress_above.append(secInvStressFn.evaluate((i,j + add))[0][0])\n",
    "    corr_secinvstress_above.append(secInvStress.evaluate((i,j + add))[0][0])\n",
    "    \n",
    "    secinvstress_below.append(secInvStressFn.evaluate((i,j + sub))[0][0])\n",
    "    corr_secinvstress_below.append(secInvStress.evaluate((i,j + sub))[0][0])\n",
    "    \n",
    "####\n",
    "\n",
    "pressure = []\n",
    "corr_pressure = []\n",
    "for i,j in zip(interfacex,interfacey):\n",
    "    pressure.append(pressureField.evaluate((i, j + add))[0][0])\n",
    "    corr_pressure.append(meshCorrectedPressure.evaluate((i, j + add))[0][0])\n",
    "    \n",
    "with open(outputFile, \"w\") as text_file:\n",
    "\n",
    "    text_file.write(\"X,\" + \"Y,\" + \"surf vx,\" + \"surf vy,\" +                     \"tauxy integr. above,\" + \"tauxy dir. above,\" +                     \"secinvare integr. above,\" + \"secinvar dir. above,\" +                     \"tauxy integr. below,\" + \"tauxy dir. below,\" +                     \"secinvare integr. below,\" + \"secinvar dir. below,\" +                     \"P integr.,\" + \"P dir.,\" + \"\\n\")\n",
    "    \n",
    "    for i in range(0,len(interfacex)):\n",
    "\n",
    "        textline =         str(interfacex[i]) + \",\"         + str(interfacey[i]) + \",\"                 + str(velocityField.evaluate((interfacex[i], airinterfacey[i]))[0][0]) + \",\"         + str(velocityField.evaluate((interfacex[i], airinterfacey[i]))[0][1]) + \",\"                 + str(corr_shearstress_xy_above[i]) + \",\"         + str(shearstress_xy_above[i]) + \",\"         + str(corr_secinvstress_above[i]) + \",\"         + str(secinvstress_above[i]) + \",\"                 + str(corr_shearstress_xy_below[i]) + \",\"         + str(shearstress_xy_below[i]) + \",\"         + str(corr_secinvstress_below[i]) + \",\"         + str(secinvstress_below[i]) + \",\"                 + str(corr_pressure[i]) + \",\"         + str(pressure[i]) +         \"\\n\"\n",
    "        \n",
    "        text_file.write(textline)\n",
    "\n",
    "# In[116]:\n",
    "\n",
    "# plot saved files\n",
    "\n",
    "outputFile = outputPath + \"output_\" + str(maxX) + \".csv\"\n",
    "a = np.loadtxt(open(outputFile, \"rb\"), delimiter=\",\", skiprows=1)\n",
    "a = a.T\n",
    "\n",
    "print (\"topo\")\n",
    "pyplot.scatter (a[0], a[1])\n",
    "yhat = savgol_filter(a[1], 13, 7)\n",
    "pyplot.plot(a[0], yhat, color='red')\n",
    "pyplot.show()\n",
    "pyplot.savefig(\"topo.png\")\n",
    "\n",
    "print (\"top x vel\")\n",
    "pyplot.scatter (a[0], a[2])\n",
    "yhat = savgol_filter(a[2], 13, 7)\n",
    "pyplot.plot(a[0], yhat, color='red')\n",
    "pyplot.show()\n",
    "pyplot.savefig(\"top x vel.png\")\n",
    "\n",
    "print (\"top y vel\")\n",
    "pyplot.scatter (a[0], a[3])\n",
    "yhat = savgol_filter(a[3], 13, 9)\n",
    "pyplot.plot(a[0], yhat, color='red')\n",
    "pyplot.show()\n",
    "pyplot.savefig(\"top y vel.png\")\n",
    "\n",
    "print (\"top total vel\")\n",
    "pyplot.scatter (a[0], np.sqrt(a[3]**2 + a[2]**2))\n",
    "yhat = savgol_filter(np.sqrt(a[3]**2 + a[2]**2), 13, 5)\n",
    "pyplot.plot(a[0], yhat, color='red')\n",
    "pyplot.show()\n",
    "pyplot.savefig(\"top total vel.png\")\n",
    "\n",
    "print (\"tau integr. above\")\n",
    "pyplot.scatter (a[0], a[4])\n",
    "yhat = savgol_filter(a[4], 13, 4)\n",
    "pyplot.plot(a[0], yhat, color='red')\n",
    "pyplot.show()\n",
    "pyplot.savefig(\"tau integr. above.png\")\n",
    "\n",
    "print (\"tau integr. below\")\n",
    "pyplot.scatter (a[0], a[8])\n",
    "yhat = savgol_filter(a[8], 13, 4)\n",
    "pyplot.plot(a[0], yhat, color='red')\n",
    "pyplot.show()\n",
    "pyplot.savefig(\"tau integr. below.png\")\n",
    "\n",
    "print (\"tau dir. above\")\n",
    "pyplot.scatter (a[0], a[5])\n",
    "yhat = savgol_filter(a[5], 13, 5)\n",
    "pyplot.plot(a[0], yhat, color='red')\n",
    "pyplot.show()\n",
    "pyplot.savefig(\"tau dir. above.png\")\n",
    "\n",
    "print (\"tau dir. below\")\n",
    "pyplot.scatter (a[0], a[9])\n",
    "yhat = savgol_filter(a[9], 13, 5)\n",
    "pyplot.plot(a[0], yhat, color='red')\n",
    "pyplot.show()\n",
    "pyplot.savefig(\"tau dir. below.png\")\n",
    "\n",
    "print (\"sec inv integr. above\")\n",
    "pyplot.scatter (a[0], a[6])\n",
    "yhat = savgol_filter(a[6], 13, 5)\n",
    "pyplot.plot(a[0], yhat, color='red')\n",
    "pyplot.show()\n",
    "pyplot.savefig(\"sec inv integr. above.png\")\n",
    "\n",
    "print (\"sec inv integr. below\")\n",
    "pyplot.scatter (a[0], a[10])\n",
    "yhat = savgol_filter(a[10], 13, 5)\n",
    "pyplot.plot(a[0], yhat, color='red')\n",
    "pyplot.show()\n",
    "pyplot.savefig(\"sec inv integr. below.png\")\n",
    "\n",
    "print (\"sec inv dir. above\")\n",
    "pyplot.scatter (a[0], a[7])\n",
    "yhat = savgol_filter(a[7], 13, 5)\n",
    "pyplot.plot(a[0], yhat, color='red')\n",
    "pyplot.show()\n",
    "pyplot.savefig(\"sec inv dir. above.png\")\n",
    "\n",
    "print (\"sec inv dir. below\")\n",
    "pyplot.scatter (a[0], a[11])\n",
    "yhat = savgol_filter(a[11], 13, 5)\n",
    "pyplot.plot(a[0], yhat, color='red')\n",
    "pyplot.show()\n",
    "pyplot.savefig(\"sec inv dir. below.png\")\n",
    "\n",
    "print (\"basal pressure integr.\")\n",
    "pyplot.scatter (a[0], a[12])\n",
    "yhat = savgol_filter(a[12], 13, 5)\n",
    "pyplot.plot(a[0], yhat, color='red')\n",
    "pyplot.show()\n",
    "pyplot.savefig(\"basal pressure integr.png\")\n",
    "\n",
    "print (\"basal pressure dir.\")\n",
    "pyplot.scatter (a[0], a[13])\n",
    "yhat = savgol_filter(a[13], 13, 5)\n",
    "pyplot.plot(a[0], yhat, color='red')\n",
    "pyplot.show()\n",
    "pyplot.savefig(\"basal pressure dir.png\")\n",
    "\n",
    "\n",
    "# In[ ]:\n",
    "\n",
    "\n",
    "# plot figures\n",
    "\n",
    "figinflow = vis.Figure(figsize=(1800,500), title=\"free slip with in/out flow\")\n",
    "figinflow.append(vis.objects.VectorArrows(mesh, velocityField))\n",
    "figinflow.append(vis.objects.Surface(mesh, uw.function.math.dot(velocityField,velocityField), colours=\"gebco\"))\n",
    "figinflow.save_image(outputPath + \"velocity_\" + str(maxX) + \".png\")\n",
    "figinflow.show()\n",
    "\n",
    "figMaterial = vis.Figure(figsize=(1800, 500), title=\"Material\")\n",
    "figMaterial.append(vis.objects.Points( swarm, materialVariable, pointSize=1.0))\n",
    "figMaterial.append( vis.objects.Mesh(mesh) )\n",
    "figMaterial.save_image(outputPath + \"material_\" + str(maxX) + \".png\")\n",
    "figMaterial.show()\n",
    "\n",
    "figDensity = vis.Figure(figsize=(1800, 500), title=\"Density\")\n",
    "figDensity.append(vis.objects.Points( swarm, particleDensity, pointSize=1.0))\n",
    "figDensity.save_image(outputPath + \"density_\" + str(maxX) + \".png\")\n",
    "figDensity.show()\n",
    "\n",
    "figViscosity = vis.Figure(figsize=(1800, 500), title=\"viscosity\")\n",
    "figViscosity.append(vis.objects.Surface(mesh, logViscosityFn))\n",
    "figViscosity.save_image(outputPath + \"logviscosity_\" + str(maxX) + \".png\")\n",
    "figViscosity.show()\n",
    "\n",
    "figPressure = vis.Figure(figsize=(1800, 500), title=\"pressure\")\n",
    "figPressure.append(vis.objects.Surface(mesh, pressureField))\n",
    "figPressure.save_image(outputPath + \"pressure_\" + str(maxX) + \".png\")\n",
    "figPressure.show()\n",
    "\n",
    "figShearStress = vis.Figure(figsize=(1800, 500), title=\"corr_shearstress_xy\")\n",
    "figShearStress.append(vis.objects.Surface(mesh, meshShearStress))\n",
    "figShearStress.save_image(outputPath + \"corr_shearstress_xy\" + str(maxX) + \".png\")\n",
    "figShearStress.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cde0535d",
   "metadata": {},
   "source": [
    "\n",
    "## finally save meshvars, swarmvars, xdmf vars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fda42da2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# In[ ]:\n",
    "\n",
    "\n",
    "xdmf_info_mesh    = mesh.save('mesh.h5')\n",
    "xdmf_info_meshVelocityField = velocityField.save('meshVelocityField.h5')\n",
    "xdmf_info_meshShearStress = meshShearStress.save('meshShearStress.h5')\n",
    "xdmf_info_meshCorrectedPressure = meshCorrectedPressure.save('meshCorrectedPressure.h5')\n",
    "\n",
    "# swarm\n",
    "xdmf_info_swarm    = swarm.save('swarm.h5')\n",
    "xdmf_info_swarmMaterialVariable = materialVariable.save('swarmMaterialVariable.h5')\n",
    "\n",
    "# xdmf mesh\n",
    "velocityField.xdmf('meshVelocityField.xdmf', xdmf_info_meshVelocityField, \"velocityField\", xdmf_info_mesh, \"TheMesh\", modeltime=0.0)\n",
    "meshShearStress.xdmf('meshShearStress.xdmf', xdmf_info_meshShearStress, \"meshShearStress\", xdmf_info_mesh, \"TheMesh\", modeltime=0.0)\n",
    "meshCorrectedPressure.xdmf('meshCorrectedPressure.xdmf', xdmf_info_meshCorrectedPressure, \"correctedPressureField\", xdmf_info_mesh, \"TheMesh\", modeltime=0.0)\n",
    "\n",
    "# xdmf swarm\n",
    "materialVariable.xdmf('swarmMaterialVariable.xdmf', xdmf_info_swarmMaterialVariable, \"material\", xdmf_info_swarm, \"TheSwarm\", modeltime=0.0)\n",
    "\n",
    "\n",
    "# In[ ]:"
   ]
  }
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