workflow_multiscale_linear_elasticity_gui.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d7fbc132-99f7-4250-8692-4e9313b2fc42",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyiron_workflow import Workflow\n",
    "from typing import Optional"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e7259d8a-3dfd-4202-b31f-2ab3ffddd2a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "bbe12797f3c34ee8a7d281e99ea6c726",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from python.pyironflow import PyironFlow\n",
    "import pyiron_nodes.continuum_fem.geometries as pnf_geom\n",
    "import pyiron_nodes.continuum_fem.function_spaces as pnf_func\n",
    "import pyiron_nodes.continuum_fem.mesh_visualization as pnf_viz\n",
    "import pyiron_nodes.continuum_fem.boundary_conditions as pnf_bc\n",
    "import pyiron_nodes.continuum_fem.load_definitions as pnf_load\n",
    "import pyiron_nodes.continuum_fem.solvers as pnf_solve\n",
    "import pyiron_nodes.continuum_fem.custom_nodes as pnf_custom\n",
    "import pyiron_nodes.atomistic.engine as pna_eng\n",
    "import pyiron_nodes.atomistic.structure as pna_struct\n",
    "import pyiron_nodes.atomistic.property as pna_prop\n",
    "import pyiron_nodes.large_scale_atomistic.structure as pnl_struct"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "662239a9-8d40-4f51-a747-280d965f62b8",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Info    : Clearing all models and views...\n",
      "Info    : Done clearing all models and views\n",
      "Info    : Meshing 1D...\n",
      "Info    : [  0%] Meshing curve 1 (Line)\n",
      "Info    : [ 10%] Meshing curve 2 (Line)\n",
      "Info    : [ 20%] Meshing curve 3 (Line)\n",
      "Info    : [ 30%] Meshing curve 4 (Line)\n",
      "Info    : [ 40%] Meshing curve 5 (Line)\n",
      "Info    : [ 50%] Meshing curve 6 (Line)\n",
      "Info    : [ 50%] Meshing curve 7 (Line)\n",
      "Info    : [ 60%] Meshing curve 8 (Line)\n",
      "Info    : [ 70%] Meshing curve 9 (Line)\n",
      "Info    : [ 80%] Meshing curve 10 (Line)\n",
      "Info    : [ 90%] Meshing curve 11 (Line)\n",
      "Info    : [100%] Meshing curve 12 (Line)\n",
      "Info    : Done meshing 1D (Wall 0.000683181s, CPU 0.000799s)\n",
      "Info    : Meshing 2D...\n",
      "Info    : [  0%] Meshing surface 1 (Plane, Frontal-Delaunay)\n",
      "Info    : [ 20%] Meshing surface 2 (Plane, Frontal-Delaunay)\n",
      "Info    : [ 40%] Meshing surface 3 (Plane, Frontal-Delaunay)\n",
      "Info    : [ 50%] Meshing surface 4 (Plane, Frontal-Delaunay)\n",
      "Info    : [ 70%] Meshing surface 5 (Plane, Frontal-Delaunay)\n",
      "Info    : [ 90%] Meshing surface 6 (Plane, Frontal-Delaunay)\n",
      "Info    : Done meshing 2D (Wall 0.0255503s, CPU 0.025479s)\n",
      "Info    : Meshing 3D...\n",
      "Info    : 3D Meshing 1 volume with 1 connected component\n",
      "Info    : Tetrahedrizing 1297 nodes...\n",
      "Info    : Done tetrahedrizing 1305 nodes (Wall 0.0120343s, CPU 0.008109s)\n",
      "Info    : Reconstructing mesh...\n",
      "Info    :  - Creating surface mesh\n",
      "Info    :  - Identifying boundary edges\n",
      "Info    :  - Recovering boundary\n",
      "Info    : Done reconstructing mesh (Wall 0.0249791s, CPU 0.021143s)\n",
      "Info    : Found volume 1\n",
      "Info    : It. 0 - 0 nodes created - worst tet radius 2.33374 (nodes removed 0 0)\n",
      "Info    : 3D refinement terminated (1603 nodes total):\n",
      "Info    :  - 0 Delaunay cavities modified for star shapeness\n",
      "Info    :  - 0 nodes could not be inserted\n",
      "Info    :  - 5571 tetrahedra created in 0.0120002 sec. (464243 tets/s)\n",
      "Info    : 0 node relocations\n",
      "Info    : Done meshing 3D (Wall 0.0597228s, CPU 0.056068s)\n",
      "Info    : Optimizing mesh...\n",
      "Info    : Optimizing volume 1\n",
      "Info    : Optimization starts (volume = 0.00096) with worst = 0.0156139 / average = 0.747111:\n",
      "Info    : 0.00 < quality < 0.10 :        24 elements\n",
      "Info    : 0.10 < quality < 0.20 :        62 elements\n",
      "Info    : 0.20 < quality < 0.30 :        76 elements\n",
      "Info    : 0.30 < quality < 0.40 :       101 elements\n",
      "Info    : 0.40 < quality < 0.50 :       111 elements\n",
      "Info    : 0.50 < quality < 0.60 :       287 elements\n",
      "Info    : 0.60 < quality < 0.70 :       995 elements\n",
      "Info    : 0.70 < quality < 0.80 :      1611 elements\n",
      "Info    : 0.80 < quality < 0.90 :      1585 elements\n",
      "Info    : 0.90 < quality < 1.00 :       717 elements\n",
      "Info    : 161 edge swaps, 4 node relocations (volume = 0.00096): worst = 0.300125 / average = 0.765773 (Wall 0.00160378s, CPU 0.001538s)\n",
      "Info    : No ill-shaped tets in the mesh :-)\n",
      "Info    : 0.00 < quality < 0.10 :         0 elements\n",
      "Info    : 0.10 < quality < 0.20 :         0 elements\n",
      "Info    : 0.20 < quality < 0.30 :         0 elements\n",
      "Info    : 0.30 < quality < 0.40 :       101 elements\n",
      "Info    : 0.40 < quality < 0.50 :       105 elements\n",
      "Info    : 0.50 < quality < 0.60 :       283 elements\n",
      "Info    : 0.60 < quality < 0.70 :       964 elements\n",
      "Info    : 0.70 < quality < 0.80 :      1649 elements\n",
      "Info    : 0.80 < quality < 0.90 :      1594 elements\n",
      "Info    : 0.90 < quality < 1.00 :       724 elements\n",
      "Info    : Done optimizing mesh (Wall 0.00510042s, CPU 0.005255s)\n",
      "Info    : 1603 nodes 8292 elements\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "width": 300
      }
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[ 2.00224187e+02  1.50926574e+02  1.25868031e+02  0.00000000e+00\n",
      "  -3.89089971e-15  0.00000000e+00]\n",
      " [ 1.50926574e+02  1.75165644e+02  1.50926574e+02  0.00000000e+00\n",
      "  -2.54536099e-15  0.00000000e+00]\n",
      " [ 1.25868031e+02  1.50926574e+02  2.00224187e+02  0.00000000e+00\n",
      "  -3.89089971e-15  0.00000000e+00]\n",
      " [ 0.00000000e+00  0.00000000e+00  0.00000000e+00  3.71780777e+01\n",
      "   0.00000000e+00 -1.11376737e-15]\n",
      " [-3.12189556e-15 -2.54536099e-15 -3.12189556e-15  0.00000000e+00\n",
      "   1.21195353e+01  0.00000000e+00]\n",
      " [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 -1.11376737e-15\n",
      "   0.00000000e+00  3.71780777e+01]]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'visualize_atoms__image': None,\n",
       " 'init_mesh_plotter_obj__plotter': <pyvista.plotting.plotter.Plotter at 0x777304de0e90>,\n",
       " 'vonMises_plotter_obj__plotter': <pyvista.plotting.plotter.Plotter at 0x7772def33490>}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wf = Workflow(\"multiscale_linear_elasticity\")\n",
    "\n",
    "#----------------------------------------------------------------------------------------------------------------------------------------\n",
    "# atomistic part\n",
    "wf.ase_emt_engine = pna_eng.ase.EMT()\n",
    "\n",
    "wf.structure = pna_struct.build.CubicBulkCell(element=\"Au\", cell_size = 2)\n",
    "\n",
    "wf.elastic_calc_params = pna_prop.elastic.InputElasticTensor(num_of_point=7, eps_range=0.005, sqrt_eta=True, fit_order=3)\n",
    "\n",
    "wf.elastic_constants = pna_prop.elastic.ElasticConstants(wf.structure, wf.ase_emt_engine, wf.elastic_calc_params)\n",
    "\n",
    "wf.rotated_elastic_tensor = pna_prop.elastic.RotateElasticityTensor(wf.elastic_constants, crystal=\"fcc\", \n",
    "                                                                      x_indices=\"0 -1 1\", y_indices=\"1 0 0\", z_indices=\"0 1 1\")\n",
    "\n",
    "wf.visualize_atoms = pnl_struct.visualize_structures.Ase2OvitoTachyonRenderPersp(structure=wf.structure)\n",
    "\n",
    "#----------------------------------------------------------------------------------------------------------------------------------------\n",
    "# FEM part\n",
    "wf.bar_geom_params = pnf_geom.three_d_geometries.BarParameters(length=0.6, width=0.04, depth=0.04, density=1.0)\n",
    "\n",
    "wf.bar_domain = pnf_geom.three_d_geometries.Bar(x0=0, y0=0, z0=0, min_mesh=0.01, max_mesh=0.01, parameters=wf.bar_geom_params)\n",
    "\n",
    "wf.vector_function_space = pnf_func.general_function_spaces.VectorFunctionSpace(wf.bar_domain, \"Lagrange\", 2)\n",
    "\n",
    "wf.init_mesh_plotter_obj= pnf_viz.pyvista_viz.PlotInitMeshObject(wf.vector_function_space)\n",
    "\n",
    "wf.bc_left = pnf_bc.scalar_geometric.ScalarDirichlet3D(function_space=wf.vector_function_space, bc_function=\"np.isclose(x[0], 0)\",\n",
    "                                                       value_x=0, value_y=0, value_z=0\n",
    "                                                      )\n",
    "\n",
    "wf.bc_right = pnf_bc.scalar_geometric.ScalarDirichlet3D(function_space=wf.vector_function_space, bc_function=\"np.isclose(x[0], 0.6)\",\n",
    "                                                        value_x=0, value_y=0, value_z=0\n",
    "                                                       )\n",
    "wf.bc_array = pnf_bc.scalar_geometric.CollectBcs(bc1=wf.bc_left, bc2=wf.bc_right)\n",
    "\n",
    "wf.solution_vector = pnf_solve.linear_elasticity.LinearElasticity3D(domain=wf.bar_domain, function_space=wf.vector_function_space,\n",
    "                                                                    bcs_array=wf.bc_array, traction_x=0, traction_y=0.0006, \n",
    "                                                                    traction_z=-0, body_force_x=0, body_force_y=0, body_force_z=0, \n",
    "                                                                    gravity_factor=10, elasticity_tensor=wf.rotated_elastic_tensor,\n",
    "                                                                    parameters=wf.bar_geom_params\n",
    "                                                                   )\n",
    "\n",
    "wf.vonMises_plotter_obj = pnf_viz.pyvista_viz.PlotVonMises3DObject(domain=wf.bar_domain,\n",
    "                                                                   function_space=wf.vector_function_space,\n",
    "                                                                   solution_vector=wf.solution_vector,\n",
    "                                                                   elasticity_tensor=wf.rotated_elastic_tensor, \n",
    "                                                                   warp_factor=20.0                                                                                         \n",
    "                                                                  )\n",
    "\n",
    "#----------------------------------------------------------------------------------------------------------------------------------------\n",
    "\n",
    "wf()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3c55717b-75c7-454f-b778-b7bb282f16ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<title>clustermultiscale_linear_elasticity</title>\n",
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       "<title>clustermultiscale_linear_elasticityInputsrotated_elastic_tensor__y_indices</title>\n",
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       "<text text-anchor=\"middle\" x=\"248.72\" y=\"-951.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">rotated_elastic_tensor__y_indices: Union</text>\n",
       "</g>\n",
       "<!-- clustermultiscale_linear_elasticityrotated_elastic_tensorInputsy_indices -->\n",
       "<g id=\"node85\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityrotated_elastic_tensorInputsy_indices</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"1860.02\" cy=\"-1019.48\" rx=\"90.67\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"1860.02\" y=\"-1014.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">y_indices: Union</text>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsrotated_elastic_tensor__y_indices&#45;&gt;clustermultiscale_linear_elasticityrotated_elastic_tensorInputsy_indices -->\n",
       "<g id=\"edge68\" class=\"edge\">\n",
       "<title>clustermultiscale_linear_elasticityInputsrotated_elastic_tensor__y_indices&#45;&gt;clustermultiscale_linear_elasticityrotated_elastic_tensorInputsy_indices</title>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsrotated_elastic_tensor__z_indices -->\n",
       "<g id=\"node13\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityInputsrotated_elastic_tensor__z_indices</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"248.72\" cy=\"-902.48\" rx=\"205.88\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"248.72\" y=\"-897.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">rotated_elastic_tensor__z_indices: Union</text>\n",
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       "<!-- clustermultiscale_linear_elasticityrotated_elastic_tensorInputsz_indices -->\n",
       "<g id=\"node86\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityrotated_elastic_tensorInputsz_indices</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"1860.02\" cy=\"-965.48\" rx=\"90.14\" ry=\"18\"/>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsrotated_elastic_tensor__z_indices&#45;&gt;clustermultiscale_linear_elasticityrotated_elastic_tensorInputsz_indices -->\n",
       "<g id=\"edge69\" class=\"edge\">\n",
       "<title>clustermultiscale_linear_elasticityInputsrotated_elastic_tensor__z_indices&#45;&gt;clustermultiscale_linear_elasticityrotated_elastic_tensorInputsz_indices</title>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsrotated_elastic_tensor__print_tensor -->\n",
       "<g id=\"node14\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityInputsrotated_elastic_tensor__print_tensor</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"248.72\" cy=\"-686.48\" rx=\"232.72\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"248.72\" y=\"-681.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">rotated_elastic_tensor__print_tensor: Optional</text>\n",
       "</g>\n",
       "<!-- clustermultiscale_linear_elasticityrotated_elastic_tensorInputsprint_tensor -->\n",
       "<g id=\"node87\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityrotated_elastic_tensorInputsprint_tensor</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"1860.02\" cy=\"-911.48\" rx=\"116.97\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"1860.02\" y=\"-906.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">print_tensor: Optional</text>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsrotated_elastic_tensor__print_tensor&#45;&gt;clustermultiscale_linear_elasticityrotated_elastic_tensorInputsprint_tensor -->\n",
       "<g id=\"edge70\" class=\"edge\">\n",
       "<title>clustermultiscale_linear_elasticityInputsrotated_elastic_tensor__print_tensor&#45;&gt;clustermultiscale_linear_elasticityrotated_elastic_tensorInputsprint_tensor</title>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsvisualize_atoms__particle_size -->\n",
       "<g id=\"node15\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityInputsvisualize_atoms__particle_size</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"248.72\" cy=\"-470.48\" rx=\"192.21\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"248.72\" y=\"-465.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">visualize_atoms__particle_size: Union</text>\n",
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       "<!-- clustermultiscale_linear_elasticityvisualize_atomsInputsparticle_size -->\n",
       "<g id=\"node93\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityvisualize_atomsInputsparticle_size</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"1242.48\" cy=\"-121.48\" rx=\"105.92\" ry=\"18\"/>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsvisualize_atoms__particle_size&#45;&gt;clustermultiscale_linear_elasticityvisualize_atomsInputsparticle_size -->\n",
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       "<title>clustermultiscale_linear_elasticityInputsvisualize_atoms__particle_size&#45;&gt;clustermultiscale_linear_elasticityvisualize_atomsInputsparticle_size</title>\n",
       "<path fill=\"none\" stroke=\"#edb22c\" d=\"M344.81,-486.51C395.01,-489.15 453.48,-481.96 489.43,-443.48 510.08,-421.37 480.29,-193.12 501.43,-171.48 515.42,-157.16 536.92,-145.58 563.91,-136.29\"/>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsvisualize_atoms__camera_dir_x -->\n",
       "<g id=\"node16\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityInputsvisualize_atoms__camera_dir_x</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"248.72\" cy=\"-416.48\" rx=\"196.94\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"248.72\" y=\"-411.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">visualize_atoms__camera_dir_x: Union</text>\n",
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       "<!-- clustermultiscale_linear_elasticityvisualize_atomsInputscamera_dir_x -->\n",
       "<g id=\"node94\" class=\"node\">\n",
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       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"1242.48\" cy=\"-67.48\" rx=\"110.66\" ry=\"18\"/>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsvisualize_atoms__camera_dir_x&#45;&gt;clustermultiscale_linear_elasticityvisualize_atomsInputscamera_dir_x -->\n",
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       "<title>clustermultiscale_linear_elasticityInputsvisualize_atoms__camera_dir_x&#45;&gt;clustermultiscale_linear_elasticityvisualize_atomsInputscamera_dir_x</title>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsvisualize_atoms__camera_dir_y -->\n",
       "<g id=\"node17\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityInputsvisualize_atoms__camera_dir_y</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"248.72\" cy=\"-578.48\" rx=\"196.41\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"248.72\" y=\"-573.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">visualize_atoms__camera_dir_y: Union</text>\n",
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       "<!-- clustermultiscale_linear_elasticityvisualize_atomsInputscamera_dir_y -->\n",
       "<g id=\"node95\" class=\"node\">\n",
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       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"1242.48\" cy=\"-229.48\" rx=\"110.13\" ry=\"18\"/>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsvisualize_atoms__camera_dir_y&#45;&gt;clustermultiscale_linear_elasticityvisualize_atomsInputscamera_dir_y -->\n",
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       "<title>clustermultiscale_linear_elasticityInputsvisualize_atoms__camera_dir_y&#45;&gt;clustermultiscale_linear_elasticityvisualize_atomsInputscamera_dir_y</title>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsvisualize_atoms__camera_dir_z -->\n",
       "<g id=\"node18\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityInputsvisualize_atoms__camera_dir_z</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"248.72\" cy=\"-524.48\" rx=\"196.41\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"248.72\" y=\"-519.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">visualize_atoms__camera_dir_z: Union</text>\n",
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       "<!-- clustermultiscale_linear_elasticityvisualize_atomsInputscamera_dir_z -->\n",
       "<g id=\"node96\" class=\"node\">\n",
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       "<title>clustermultiscale_linear_elasticityInputsvisualize_atoms__camera_dir_z&#45;&gt;clustermultiscale_linear_elasticityvisualize_atomsInputscamera_dir_z</title>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsbar_geom_params__length -->\n",
       "<g id=\"node19\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityInputsbar_geom_params__length</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"248.72\" cy=\"-1712.48\" rx=\"176.42\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"248.72\" y=\"-1707.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">bar_geom_params__length: Union</text>\n",
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       "<!-- clustermultiscale_linear_elasticitybar_geom_paramsInputslength -->\n",
       "<g id=\"node101\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticitybar_geom_paramsInputslength</title>\n",
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       "<g id=\"edge75\" class=\"edge\">\n",
       "<title>clustermultiscale_linear_elasticityInputsbar_geom_params__length&#45;&gt;clustermultiscale_linear_elasticitybar_geom_paramsInputslength</title>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsbar_geom_params__width -->\n",
       "<g id=\"node20\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityInputsbar_geom_params__width</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"248.72\" cy=\"-1658.48\" rx=\"172.21\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"248.72\" y=\"-1653.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">bar_geom_params__width: Union</text>\n",
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       "<!-- clustermultiscale_linear_elasticitybar_geom_paramsInputswidth -->\n",
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       "<title>clustermultiscale_linear_elasticitybar_geom_paramsInputswidth</title>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsbar_geom_params__width&#45;&gt;clustermultiscale_linear_elasticitybar_geom_paramsInputswidth -->\n",
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       "<title>clustermultiscale_linear_elasticityInputsbar_geom_params__width&#45;&gt;clustermultiscale_linear_elasticitybar_geom_paramsInputswidth</title>\n",
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       "<title>clustermultiscale_linear_elasticityInputsbar_geom_params__depth</title>\n",
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       "<g id=\"node103\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticitybar_geom_paramsInputsdepth</title>\n",
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       "<title>clustermultiscale_linear_elasticityInputsbar_geom_params__density</title>\n",
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       "<title>clustermultiscale_linear_elasticitybar_geom_paramsInputsdensity</title>\n",
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       "<text text-anchor=\"middle\" x=\"632.3\" y=\"-1738.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">density: Union</text>\n",
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       "<g id=\"edge78\" class=\"edge\">\n",
       "<title>clustermultiscale_linear_elasticityInputsbar_geom_params__density&#45;&gt;clustermultiscale_linear_elasticitybar_geom_paramsInputsdensity</title>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsbar_domain__x0 -->\n",
       "<g id=\"node23\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityInputsbar_domain__x0</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"248.72\" cy=\"-2576.48\" rx=\"124.86\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"248.72\" y=\"-2571.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">bar_domain__x0: Union</text>\n",
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       "<title>clustermultiscale_linear_elasticityInputsbar_domain__x0&#45;&gt;clustermultiscale_linear_elasticitybar_domainInputsx0</title>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsbar_domain__y0 -->\n",
       "<g id=\"node24\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityInputsbar_domain__y0</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"248.72\" cy=\"-2522.48\" rx=\"124.86\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"248.72\" y=\"-2517.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">bar_domain__y0: Union</text>\n",
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       "<!-- clustermultiscale_linear_elasticitybar_domainInputsy0 -->\n",
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       "<title>clustermultiscale_linear_elasticitybar_domainInputsy0</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"632.3\" cy=\"-2531.48\" rx=\"58.05\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"632.3\" y=\"-2526.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">y0: Union</text>\n",
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       "<g id=\"edge80\" class=\"edge\">\n",
       "<title>clustermultiscale_linear_elasticityInputsbar_domain__y0&#45;&gt;clustermultiscale_linear_elasticitybar_domainInputsy0</title>\n",
       "<path fill=\"none\" stroke=\"#edb22c\" d=\"M372.29,-2525.37C403.81,-2526.11 438.19,-2526.92 471.3,-2527.7\"/>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsbar_domain__z0 -->\n",
       "<g id=\"node25\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityInputsbar_domain__z0</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"248.72\" cy=\"-2738.48\" rx=\"124.34\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"248.72\" y=\"-2733.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">bar_domain__z0: Union</text>\n",
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       "<!-- clustermultiscale_linear_elasticitybar_domainInputsz0 -->\n",
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       "<title>clustermultiscale_linear_elasticitybar_domainInputsz0</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"632.3\" cy=\"-2747.48\" rx=\"57.52\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"632.3\" y=\"-2742.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">z0: Union</text>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsbar_domain__z0&#45;&gt;clustermultiscale_linear_elasticitybar_domainInputsz0 -->\n",
       "<g id=\"edge81\" class=\"edge\">\n",
       "<title>clustermultiscale_linear_elasticityInputsbar_domain__z0&#45;&gt;clustermultiscale_linear_elasticitybar_domainInputsz0</title>\n",
       "<path fill=\"none\" stroke=\"#edb22c\" d=\"M372.03,-2741.36C403.71,-2742.11 438.29,-2742.92 471.58,-2743.71\"/>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsbar_domain__min_mesh -->\n",
       "<g id=\"node26\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityInputsbar_domain__min_mesh</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"248.72\" cy=\"-2684.48\" rx=\"162.74\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"248.72\" y=\"-2679.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">bar_domain__min_mesh: Union</text>\n",
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       "<!-- clustermultiscale_linear_elasticitybar_domainInputsmin_mesh -->\n",
       "<g id=\"node112\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticitybar_domainInputsmin_mesh</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"632.3\" cy=\"-2693.48\" rx=\"95.93\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"632.3\" y=\"-2688.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">min_mesh: Union</text>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsbar_domain__min_mesh&#45;&gt;clustermultiscale_linear_elasticitybar_domainInputsmin_mesh -->\n",
       "<g id=\"edge82\" class=\"edge\">\n",
       "<title>clustermultiscale_linear_elasticityInputsbar_domain__min_mesh&#45;&gt;clustermultiscale_linear_elasticitybar_domainInputsmin_mesh</title>\n",
       "<path fill=\"none\" stroke=\"#edb22c\" d=\"M408.5,-2688.22C428.25,-2688.69 448.47,-2689.16 468.29,-2689.63\"/>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsbar_domain__max_mesh -->\n",
       "<g id=\"node27\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityInputsbar_domain__max_mesh</title>\n",
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       "<text text-anchor=\"middle\" x=\"248.72\" y=\"-2625.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">bar_domain__max_mesh: Union</text>\n",
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       "<!-- clustermultiscale_linear_elasticitybar_domainInputsmax_mesh -->\n",
       "<g id=\"node113\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticitybar_domainInputsmax_mesh</title>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsbar_domain__max_mesh&#45;&gt;clustermultiscale_linear_elasticitybar_domainInputsmax_mesh -->\n",
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       "<title>clustermultiscale_linear_elasticityInputsbar_domain__max_mesh&#45;&gt;clustermultiscale_linear_elasticitybar_domainInputsmax_mesh</title>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsvector_function_space__el_type -->\n",
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       "<title>clustermultiscale_linear_elasticityInputsvector_function_space__el_type</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"248.72\" cy=\"-2792.48\" rx=\"211.15\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"248.72\" y=\"-2787.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">vector_function_space__el_type: Optional</text>\n",
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       "<!-- clustermultiscale_linear_elasticityvector_function_spaceInputsel_type -->\n",
       "<g id=\"node120\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityvector_function_spaceInputsel_type</title>\n",
       "<ellipse fill=\"#edb22c\" stroke=\"#edb22c\" cx=\"632.3\" cy=\"-2981.48\" rx=\"93.3\" ry=\"18\"/>\n",
       "<text text-anchor=\"middle\" x=\"632.3\" y=\"-2976.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">el_type: Optional</text>\n",
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       "<title>clustermultiscale_linear_elasticityInputsvector_function_space__el_type&#45;&gt;clustermultiscale_linear_elasticityvector_function_spaceInputsel_type</title>\n",
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       "<!-- clustermultiscale_linear_elasticityInputsvector_function_space__el_order -->\n",
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       "<!-- clustermultiscale_linear_elasticityvector_function_spaceInputsel_order -->\n",
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       "<!-- clustermultiscale_linear_elasticityInputsbc_left__bc_function -->\n",
       "<g id=\"node30\" class=\"node\">\n",
       "<title>clustermultiscale_linear_elasticityInputsbc_left__bc_function</title>\n",
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       "<!-- clustermultiscale_linear_elasticityvonMises_plotter_objInputsrun&#45;&gt;clustermultiscale_linear_elasticityvonMises_plotter_objOutputsWithInjectionran -->\n",
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       "<!-- clustermultiscale_linear_elasticityvonMises_plotter_objOutputsWithInjectionplotter&#45;&gt;clustermultiscale_linear_elasticityOutputsvonMises_plotter_obj__plotter -->\n",
       "<g id=\"edge108\" class=\"edge\">\n",
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       "</g>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "<graphviz.graphs.Digraph at 0x7772df091750>"
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     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wf.draw(size=(17,17))\n",
    "#pic = wf.draw(size=(15,15))\n",
    "#pic.render(outfile='workflow.svg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f3b724c0-7ace-4975-8294-22ef18f83fa9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3847bf24c1c54f52b16a0fad987dbf0b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(Accordion(children=(Tree(nodes=(Node(icon_style='warning', name='atomistic'), Node(icon_style='…"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pf = PyironFlow([wf])\n",
    "#pf = PyironFlow()\n",
    "pf.gui"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3dc7963a-8259-4647-82bd-51120f6e3940",
   "metadata": {},
   "outputs": [],
   "source": [
    "#pf.display_workflow(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0ce66048-52a4-4dd2-97fe-64e86f6499a8",
   "metadata": {},
   "outputs": [],
   "source": [
    "wf_from_gui = pf.get_workflow()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f09736b6-2cb5-47b6-8423-6937939ac2e7",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning : Gmsh has aleady been initialized\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Info    : Clearing all models and views...\n",
      "Info    : Done clearing all models and views\n",
      "Info    : Meshing 1D...\n",
      "Info    : [  0%] Meshing curve 1 (Line)\n",
      "Info    : [ 10%] Meshing curve 2 (Line)\n",
      "Info    : [ 20%] Meshing curve 3 (Line)\n",
      "Info    : [ 30%] Meshing curve 4 (Line)\n",
      "Info    : [ 40%] Meshing curve 5 (Line)\n",
      "Info    : [ 50%] Meshing curve 6 (Line)\n",
      "Info    : [ 50%] Meshing curve 7 (Line)\n",
      "Info    : [ 60%] Meshing curve 8 (Line)\n",
      "Info    : [ 70%] Meshing curve 9 (Line)\n",
      "Info    : [ 80%] Meshing curve 10 (Line)\n",
      "Info    : [ 90%] Meshing curve 11 (Line)\n",
      "Info    : [100%] Meshing curve 12 (Line)\n",
      "Info    : Done meshing 1D (Wall 0,000723116s, CPU 0,001043s)\n",
      "Info    : Meshing 2D...\n",
      "Info    : [  0%] Meshing surface 1 (Plane, Frontal-Delaunay)\n",
      "Info    : [ 20%] Meshing surface 2 (Plane, Frontal-Delaunay)\n",
      "Info    : [ 40%] Meshing surface 3 (Plane, Frontal-Delaunay)\n",
      "Info    : [ 50%] Meshing surface 4 (Plane, Frontal-Delaunay)\n",
      "Info    : [ 70%] Meshing surface 5 (Plane, Frontal-Delaunay)\n",
      "Info    : [ 90%] Meshing surface 6 (Plane, Frontal-Delaunay)\n",
      "Info    : Done meshing 2D (Wall 0,02944s, CPU 0,026985s)\n",
      "Info    : Meshing 3D...\n",
      "Info    : 3D Meshing 1 volume with 1 connected component\n",
      "Info    : Tetrahedrizing 1297 nodes...\n",
      "Info    : Done tetrahedrizing 1305 nodes (Wall 0,0114789s, CPU 0,007595s)\n",
      "Info    : Reconstructing mesh...\n",
      "Info    :  - Creating surface mesh\n",
      "Info    :  - Identifying boundary edges\n",
      "Info    :  - Recovering boundary\n",
      "Info    : Done reconstructing mesh (Wall 0,0227506s, CPU 0,019058s)\n",
      "Info    : Found volume 1\n",
      "Info    : It. 0 - 0 nodes created - worst tet radius 2,33374 (nodes removed 0 0)\n",
      "Info    : 3D refinement terminated (1603 nodes total):\n",
      "Info    :  - 0 Delaunay cavities modified for star shapeness\n",
      "Info    :  - 0 nodes could not be inserted\n",
      "Info    :  - 5571 tetrahedra created in 0,0121592 sec. (458171 tets/s)\n",
      "Info    : 0 node relocations\n",
      "Info    : Done meshing 3D (Wall 0,0576845s, CPU 0,053925s)\n",
      "Info    : Optimizing mesh...\n",
      "Info    : Optimizing volume 1\n",
      "Info    : Optimization starts (volume = 0,00096) with worst = 0,0156139 / average = 0,747111:\n",
      "Info    : 0,00 < quality < 0,10 :        24 elements\n",
      "Info    : 0,10 < quality < 0,20 :        62 elements\n",
      "Info    : 0,20 < quality < 0,30 :        76 elements\n",
      "Info    : 0,30 < quality < 0,40 :       101 elements\n",
      "Info    : 0,40 < quality < 0,50 :       111 elements\n",
      "Info    : 0,50 < quality < 0,60 :       287 elements\n",
      "Info    : 0,60 < quality < 0,70 :       995 elements\n",
      "Info    : 0,70 < quality < 0,80 :      1611 elements\n",
      "Info    : 0,80 < quality < 0,90 :      1585 elements\n",
      "Info    : 0,90 < quality < 1,00 :       717 elements\n",
      "Info    : 161 edge swaps, 4 node relocations (volume = 0,00096): worst = 0,300125 / average = 0,765773 (Wall 0,00158079s, CPU 0,001627s)\n",
      "Info    : No ill-shaped tets in the mesh :-)\n",
      "Info    : 0,00 < quality < 0,10 :         0 elements\n",
      "Info    : 0,10 < quality < 0,20 :         0 elements\n",
      "Info    : 0,20 < quality < 0,30 :         0 elements\n",
      "Info    : 0,30 < quality < 0,40 :       101 elements\n",
      "Info    : 0,40 < quality < 0,50 :       105 elements\n",
      "Info    : 0,50 < quality < 0,60 :       283 elements\n",
      "Info    : 0,60 < quality < 0,70 :       964 elements\n",
      "Info    : 0,70 < quality < 0,80 :      1649 elements\n",
      "Info    : 0,80 < quality < 0,90 :      1594 elements\n",
      "Info    : 0,90 < quality < 1,00 :       724 elements\n",
      "Info    : Done optimizing mesh (Wall 0,00498405s, CPU 0,005219s)\n",
      "Info    : 1603 nodes 8292 elements\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "Widget(value='<iframe src=\"http://localhost:46123/index.html?ui=P_0x7772defa9150_3&reconnect=auto\" class=\"pyvi…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wf_from_gui.init_mesh_plotter_obj.pull().show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "dd553e25-ad78-48da-b9ef-ce6676af7f66",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A view with name (P_0x7772dc724c90_5) is already registered\n",
      " => returning previous one\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "40206182392440d4850a4fc353397e5e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Widget(value='<iframe src=\"http://localhost:46123/index.html?ui=P_0x7772dc724c90_5&reconnect=auto\" class=\"pyvi…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wf_from_gui.vonMises_plotter_obj.pull().show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c4318bfd-b04a-462b-82b6-9e6406f06ad8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "FunctionSpace(Mesh(blocked element (Basix element (P, tetrahedron, 1, equispaced, unset, False, float64, []), (3,)), 1), blocked element (Basix element (P, tetrahedron, 2, gll_warped, unset, False, float64, []), (3,)))"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tmp = wf_from_gui.vector_function_space.pull()\n",
    "tmp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "90b9ebec-3ca6-4858-b1f1-b6d2017db013",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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