From fef663ce2453d61f20db03ccace0c644b6bb7dba Mon Sep 17 00:00:00 2001 From: Christoph Lehmann <christoph.lehmann@ufz.de> Date: Fri, 5 Aug 2022 12:13:03 +0200 Subject: [PATCH] [T] Performance improvements and small plot sketch fix --- ...isc with a hole_Convergence Analysis.ipynb | 842 ++++++------------ 1 file changed, 291 insertions(+), 551 deletions(-) diff --git a/Tests/Data/Mechanics/Linear/DiscWithHole/Disc with a hole_Convergence Analysis.ipynb b/Tests/Data/Mechanics/Linear/DiscWithHole/Disc with a hole_Convergence Analysis.ipynb index 157af5de8f8..57781f368a9 100644 --- a/Tests/Data/Mechanics/Linear/DiscWithHole/Disc with a hole_Convergence Analysis.ipynb +++ b/Tests/Data/Mechanics/Linear/DiscWithHole/Disc with a hole_Convergence Analysis.ipynb @@ -44,13 +44,13 @@ "\\begin{aligned}\n", "&\\begin{array}{cccc}\n", "\\text {Refinement Index} & \\text {Cell Size [cm]} \\\\\n", - "\\hline 8 & 1,429 \\\\\n", - "16 & 0,667 \\\\\n", - "24 & 0,435 \\\\\n", - "40 & 0,256 \\\\\n", - "60 & 0,169 \\\\\n", - "80 & 0,127 \\\\\n", - "240 & 0,042 \\\\\n", + "\\hline 8 & 1.429 \\\\\n", + "16 & 0.667 \\\\\n", + "24 & 0.435 \\\\\n", + "40 & 0.256 \\\\\n", + "60 & 0.169 \\\\\n", + "80 & 0.127 \\\\\n", + "240 & 0.042 \\\\\n", "\\end{array}\n", "\\end{aligned}\n", "$$" @@ -58,12 +58,9 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 1, "id": "084fdcae-a2e3-4ec7-9ee2-ef346d1e24ae", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], @@ -74,12 +71,9 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 2, "id": "94fa6d9e-8a29-44c5-ba62-b24ed779738b", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], @@ -106,12 +100,9 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 3, "id": "7497dc19-d87c-4f15-9fda-711d6f45d769", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], @@ -129,12 +120,9 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 4, "id": "55ee1ad2-ffcf-4060-a6ee-76173cd89825", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], @@ -159,19 +147,13 @@ "def get_sigma_polar_components(mesh):\n", " sig = mesh.point_data[\"sigma\"]\n", " \n", - " num_points = sig.shape[0]\n", - " sig_rr = np.zeros(num_points)\n", - " sig_tt = np.zeros(num_points)\n", - " sig_rt = np.zeros(num_points)\n", + " xs = mesh.points[:, 0]\n", + " ys = mesh.points[:, 1]\n", + " sigs_polar = vec4_to_mat3x3polar(sig, xs, ys)\n", " \n", - " for pt_idx in range(num_points):\n", - " sig_vec = sig[pt_idx, :]\n", - " x = mesh.points[pt_idx,0]\n", - " y = mesh.points[pt_idx,1]\n", - " sig_polar = vec4_to_mat3x3polar(sig_vec, x, y)\n", - " sig_rr[pt_idx] = sig_polar[0,0]\n", - " sig_tt[pt_idx] = sig_polar[1,1]\n", - " sig_rt[pt_idx] = sig_polar[0,1]\n", + " sig_rr = sigs_polar[:,0,0]\n", + " sig_tt = sigs_polar[:,1,1]\n", + " sig_rt = sigs_polar[:,0,1]\n", " \n", " return sig_rr, sig_tt, sig_rt\n", "\n", @@ -251,8 +233,7 @@ " \n", " return f_abs_tt, f_rel_tt\n", "\n", - "def compute_cell_size(idx):\n", - " mesh = read_last_timestep_mesh(idx)\n", + "def compute_cell_size(idx, mesh):\n", " pt1 = (19.999,0,0)\n", " pt2 = (19.999,20,0)\n", " line_mesh = slice_along_line(mesh, pt1, pt2)\n", @@ -294,12 +275,9 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 5, "id": "998027ea-3765-423c-8a2f-3d02716ba3d5", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], @@ -309,14 +287,9 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 6, "id": "f1a0a5dd-3656-4e67-8fda-16e3148d1ae3", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true, - "source_hidden": true - }, "tags": [] }, "outputs": [ @@ -340,14 +313,14 @@ "Info : [ 80%] Meshing curve 13 (Line)\n", "Info : [ 90%] Meshing curve 14 (Line)\n", "Info : [100%] Meshing curve 15 (Line)\n", - "Info : Done meshing 1D (Wall 0.0027681s, CPU 0.002276s)\n", + "Info : Done meshing 1D (Wall 0.00147451s, CPU 0.003029s)\n", "Info : Meshing 2D...\n", "Info : [ 0%] Meshing surface 1 (Transfinite)\n", "Info : [ 20%] Meshing surface 2 (Transfinite)\n", "Info : [ 40%] Meshing surface 3 (Transfinite)\n", "Info : [ 60%] Meshing surface 4 (Transfinite)\n", "Info : [ 80%] Meshing surface 5 (Transfinite)\n", - "Info : Done meshing 2D (Wall 0.0065432s, CPU 0.005484s)\n", + "Info : Done meshing 2D (Wall 0.000260076s, CPU 0.000539s)\n", "Info : 282 nodes 362 elements\n", "Info : Writing 'out/disc_with_hole_idx_is_8.msh'...\n", "Info : Done writing 'out/disc_with_hole_idx_is_8.msh'\n", @@ -367,14 +340,14 @@ "Info : [ 80%] Meshing curve 13 (Line)\n", "Info : [ 90%] Meshing curve 14 (Line)\n", "Info : [100%] Meshing curve 15 (Line)\n", - "Info : Done meshing 1D (Wall 0.0031296s, CPU 0.005884s)\n", + "Info : Done meshing 1D (Wall 0.00113128s, CPU 0.001637s)\n", "Info : Meshing 2D...\n", "Info : [ 0%] Meshing surface 1 (Transfinite)\n", "Info : [ 20%] Meshing surface 2 (Transfinite)\n", "Info : [ 40%] Meshing surface 3 (Transfinite)\n", "Info : [ 60%] Meshing surface 4 (Transfinite)\n", "Info : [ 80%] Meshing surface 5 (Transfinite)\n", - "Info : Done meshing 2D (Wall 0.0027651s, CPU 0.005806s)\n", + "Info : Done meshing 2D (Wall 0.00052339s, CPU 0.001178s)\n", "Info : 1202 nodes 1362 elements\n", "Info : Writing 'out/disc_with_hole_idx_is_16.msh'...\n", "Info : Done writing 'out/disc_with_hole_idx_is_16.msh'\n", @@ -394,14 +367,14 @@ "Info : [ 80%] Meshing curve 13 (Line)\n", "Info : [ 90%] Meshing curve 14 (Line)\n", "Info : [100%] Meshing curve 15 (Line)\n", - "Info : Done meshing 1D (Wall 0.0052813s, CPU 0.004109s)\n", + "Info : Done meshing 1D (Wall 0.00109147s, CPU 0.00235s)\n", "Info : Meshing 2D...\n", "Info : [ 0%] Meshing surface 1 (Transfinite)\n", "Info : [ 20%] Meshing surface 2 (Transfinite)\n", "Info : [ 40%] Meshing surface 3 (Transfinite)\n", "Info : [ 60%] Meshing surface 4 (Transfinite)\n", "Info : [ 80%] Meshing surface 5 (Transfinite)\n", - "Info : Done meshing 2D (Wall 0.0039325s, CPU 0.007723s)\n", + "Info : Done meshing 2D (Wall 0.000818798s, CPU 0.001507s)\n", "Info : 2762 nodes 3002 elements\n", "Info : Writing 'out/disc_with_hole_idx_is_24.msh'...\n", "Info : Done writing 'out/disc_with_hole_idx_is_24.msh'\n", @@ -421,14 +394,14 @@ "Info : [ 80%] Meshing curve 13 (Line)\n", "Info : [ 90%] Meshing curve 14 (Line)\n", "Info : [100%] Meshing curve 15 (Line)\n", - "Info : Done meshing 1D (Wall 0.0069744s, CPU 0.006714s)\n", + "Info : Done meshing 1D (Wall 0.00119862s, CPU 0.001902s)\n", "Info : Meshing 2D...\n", "Info : [ 0%] Meshing surface 1 (Transfinite)\n", "Info : [ 20%] Meshing surface 2 (Transfinite)\n", "Info : [ 40%] Meshing surface 3 (Transfinite)\n", "Info : [ 60%] Meshing surface 4 (Transfinite)\n", "Info : [ 80%] Meshing surface 5 (Transfinite)\n", - "Info : Done meshing 2D (Wall 0.0147255s, CPU 0.02283s)\n", + "Info : Done meshing 2D (Wall 0.00193151s, CPU 0.002864s)\n", "Info : 7802 nodes 8202 elements\n", "Info : Writing 'out/disc_with_hole_idx_is_40.msh'...\n", "Info : Done writing 'out/disc_with_hole_idx_is_40.msh'\n", @@ -448,14 +421,14 @@ "Info : [ 80%] Meshing curve 13 (Line)\n", "Info : [ 90%] Meshing curve 14 (Line)\n", "Info : [100%] Meshing curve 15 (Line)\n", - "Info : Done meshing 1D (Wall 0.0036585s, CPU 0.007415s)\n", + "Info : Done meshing 1D (Wall 0.00151704s, CPU 0.003072s)\n", "Info : Meshing 2D...\n", "Info : [ 0%] Meshing surface 1 (Transfinite)\n", "Info : [ 20%] Meshing surface 2 (Transfinite)\n", "Info : [ 40%] Meshing surface 3 (Transfinite)\n", "Info : [ 60%] Meshing surface 4 (Transfinite)\n", "Info : [ 80%] Meshing surface 5 (Transfinite)\n", - "Info : Done meshing 2D (Wall 0.0102291s, CPU 0.008935s)\n", + "Info : Done meshing 2D (Wall 0.00388666s, CPU 0.004766s)\n", "Info : 17702 nodes 18302 elements\n", "Info : Writing 'out/disc_with_hole_idx_is_60.msh'...\n", "Info : Done writing 'out/disc_with_hole_idx_is_60.msh'\n", @@ -475,14 +448,14 @@ "Info : [ 80%] Meshing curve 13 (Line)\n", "Info : [ 90%] Meshing curve 14 (Line)\n", "Info : [100%] Meshing curve 15 (Line)\n", - "Info : Done meshing 1D (Wall 0.0029927s, CPU 0.005521s)\n", + "Info : Done meshing 1D (Wall 0.00134443s, CPU 0.002215s)\n", "Info : Meshing 2D...\n", "Info : [ 0%] Meshing surface 1 (Transfinite)\n", "Info : [ 20%] Meshing surface 2 (Transfinite)\n", "Info : [ 40%] Meshing surface 3 (Transfinite)\n", "Info : [ 60%] Meshing surface 4 (Transfinite)\n", "Info : [ 80%] Meshing surface 5 (Transfinite)\n", - "Info : Done meshing 2D (Wall 0.0194995s, CPU 0.014116s)\n", + "Info : Done meshing 2D (Wall 0.00593373s, CPU 0.0034s)\n", "Info : 31602 nodes 32402 elements\n", "Info : Writing 'out/disc_with_hole_idx_is_80.msh'...\n", "Info : Done writing 'out/disc_with_hole_idx_is_80.msh'\n", @@ -502,14 +475,14 @@ "Info : [ 80%] Meshing curve 13 (Line)\n", "Info : [ 90%] Meshing curve 14 (Line)\n", "Info : [100%] Meshing curve 15 (Line)\n", - "Info : Done meshing 1D (Wall 0.0127848s, CPU 0.026519s)\n", + "Info : Done meshing 1D (Wall 0.00304348s, CPU 0.00566s)\n", "Info : Meshing 2D...\n", "Info : [ 0%] Meshing surface 1 (Transfinite)\n", "Info : [ 20%] Meshing surface 2 (Transfinite)\n", "Info : [ 40%] Meshing surface 3 (Transfinite)\n", "Info : [ 60%] Meshing surface 4 (Transfinite)\n", "Info : [ 80%] Meshing surface 5 (Transfinite)\n", - "Info : Done meshing 2D (Wall 0.219134s, CPU 0.123912s)\n", + "Info : Done meshing 2D (Wall 0.0638494s, CPU 0.050581s)\n", "Info : 286802 nodes 289202 elements\n", "Info : Writing 'out/disc_with_hole_idx_is_240.msh'...\n", "Info : Done writing 'out/disc_with_hole_idx_is_240.msh'\n" @@ -540,256 +513,14 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 7, "id": "0fa3a975-f040-47da-a30b-b80484864231", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true, - "source_hidden": true - }, "tags": [] }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MeshIO 5.3.4 found, MSH2VTU was tested with MeshIO 5.3.8.\n", - "sys:1: UserWarning: Warning, out-dated MeshIO version. In case of errors watch for commented code fragments from previous versions in this script (msh2vtu).\n", - "##\n", - "\n", - "Original mesh (read)\n", - "281 points in 3 dimensions; cells: 70 line, 245 quad; point_data=['gmsh:dim_tags']; cell_data=['gmsh:physical', 'gmsh:geometrical']; cell_sets=['Bottom', 'Right', 'Top', 'Left', 'Hole', 'Plate', 'gmsh:bounding_entities']\n", - "##\n", - "Detected mesh dimension: 2\n", - "##\n", - "Domain mesh (written)\n", - "281 points in 3 dimensions; cells: 245 quad; point_data=['original_node_number']; cell_data=['MaterialIDs']; cell_sets=[]\n", - "##\n", - "Boundary mesh (written)\n", - "70 points in 3 dimensions; cells: 70 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Bottom (written)\n", - "15 points in 3 dimensions; cells: 14 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Right (written)\n", - "15 points in 3 dimensions; cells: 14 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Top (written)\n", - "15 points in 3 dimensions; cells: 14 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Left (written)\n", - "15 points in 3 dimensions; cells: 14 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Hole (written)\n", - "15 points in 3 dimensions; cells: 14 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Plate (written)\n", - "281 points in 3 dimensions; cells: 245 quad; point_data=['bulk_node_ids']; cell_data=['MaterialIDs']; cell_sets=[]\n", - "##\n", - "MeshIO 5.3.4 found, MSH2VTU was tested with MeshIO 5.3.8.\n", - "sys:1: UserWarning: Warning, out-dated MeshIO version. In case of errors watch for commented code fragments from previous versions in this script (msh2vtu).\n", - "##\n", - "\n", - "Original mesh (read)\n", - "1201 points in 3 dimensions; cells: 150 line, 1125 quad; point_data=['gmsh:dim_tags']; cell_data=['gmsh:physical', 'gmsh:geometrical']; cell_sets=['Bottom', 'Right', 'Top', 'Left', 'Hole', 'Plate', 'gmsh:bounding_entities']\n", - "##\n", - "Detected mesh dimension: 2\n", - "##\n", - "Domain mesh (written)\n", - "1201 points in 3 dimensions; cells: 1125 quad; point_data=['original_node_number']; cell_data=['MaterialIDs']; cell_sets=[]\n", - "##\n", - "Boundary mesh (written)\n", - "150 points in 3 dimensions; cells: 150 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Bottom (written)\n", - "31 points in 3 dimensions; cells: 30 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Right (written)\n", - "31 points in 3 dimensions; cells: 30 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Top (written)\n", - "31 points in 3 dimensions; cells: 30 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Left (written)\n", - "31 points in 3 dimensions; cells: 30 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Hole (written)\n", - "31 points in 3 dimensions; cells: 30 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Plate (written)\n", - "1201 points in 3 dimensions; cells: 1125 quad; point_data=['bulk_node_ids']; cell_data=['MaterialIDs']; cell_sets=[]\n", - "##\n", - "MeshIO 5.3.4 found, MSH2VTU was tested with MeshIO 5.3.8.\n", - "sys:1: UserWarning: Warning, out-dated MeshIO version. In case of errors watch for commented code fragments from previous versions in this script (msh2vtu).\n", - "##\n", - "\n", - "Original mesh (read)\n", - "2761 points in 3 dimensions; cells: 230 line, 2645 quad; point_data=['gmsh:dim_tags']; cell_data=['gmsh:physical', 'gmsh:geometrical']; cell_sets=['Bottom', 'Right', 'Top', 'Left', 'Hole', 'Plate', 'gmsh:bounding_entities']\n", - "##\n", - "Detected mesh dimension: 2\n", - "##\n", - "Domain mesh (written)\n", - "2761 points in 3 dimensions; cells: 2645 quad; point_data=['original_node_number']; cell_data=['MaterialIDs']; cell_sets=[]\n", - "##\n", - "Boundary mesh (written)\n", - "230 points in 3 dimensions; cells: 230 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Bottom (written)\n", - "47 points in 3 dimensions; cells: 46 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Right (written)\n", - "47 points in 3 dimensions; cells: 46 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Top (written)\n", - "47 points in 3 dimensions; cells: 46 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Left (written)\n", - "47 points in 3 dimensions; cells: 46 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Hole (written)\n", - "47 points in 3 dimensions; cells: 46 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Plate (written)\n", - "2761 points in 3 dimensions; cells: 2645 quad; point_data=['bulk_node_ids']; cell_data=['MaterialIDs']; cell_sets=[]\n", - "##\n", - "MeshIO 5.3.4 found, MSH2VTU was tested with MeshIO 5.3.8.\n", - "sys:1: UserWarning: Warning, out-dated MeshIO version. In case of errors watch for commented code fragments from previous versions in this script (msh2vtu).\n", - "##\n", - "\n", - "Original mesh (read)\n", - "7801 points in 3 dimensions; cells: 390 line, 7605 quad; point_data=['gmsh:dim_tags']; cell_data=['gmsh:physical', 'gmsh:geometrical']; cell_sets=['Bottom', 'Right', 'Top', 'Left', 'Hole', 'Plate', 'gmsh:bounding_entities']\n", - "##\n", - "Detected mesh dimension: 2\n", - "##\n", - "Domain mesh (written)\n", - "7801 points in 3 dimensions; cells: 7605 quad; point_data=['original_node_number']; cell_data=['MaterialIDs']; cell_sets=[]\n", - "##\n", - "Boundary mesh (written)\n", - "390 points in 3 dimensions; cells: 390 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Bottom (written)\n", - "79 points in 3 dimensions; cells: 78 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Right (written)\n", - "79 points in 3 dimensions; cells: 78 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Top (written)\n", - "79 points in 3 dimensions; cells: 78 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Left (written)\n", - "79 points in 3 dimensions; cells: 78 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Hole (written)\n", - "79 points in 3 dimensions; cells: 78 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Plate (written)\n", - "7801 points in 3 dimensions; cells: 7605 quad; point_data=['bulk_node_ids']; cell_data=['MaterialIDs']; cell_sets=[]\n", - "##\n", - "MeshIO 5.3.4 found, MSH2VTU was tested with MeshIO 5.3.8.\n", - "sys:1: UserWarning: Warning, out-dated MeshIO version. In case of errors watch for commented code fragments from previous versions in this script (msh2vtu).\n", - "##\n", - "\n", - "Original mesh (read)\n", - "17701 points in 3 dimensions; cells: 590 line, 17405 quad; point_data=['gmsh:dim_tags']; cell_data=['gmsh:physical', 'gmsh:geometrical']; cell_sets=['Bottom', 'Right', 'Top', 'Left', 'Hole', 'Plate', 'gmsh:bounding_entities']\n", - "##\n", - "Detected mesh dimension: 2\n", - "##\n", - "Domain mesh (written)\n", - "17701 points in 3 dimensions; cells: 17405 quad; point_data=['original_node_number']; cell_data=['MaterialIDs']; cell_sets=[]\n", - "##\n", - "Boundary mesh (written)\n", - "590 points in 3 dimensions; cells: 590 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Bottom (written)\n", - "119 points in 3 dimensions; cells: 118 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Right (written)\n", - "119 points in 3 dimensions; cells: 118 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Top (written)\n", - "119 points in 3 dimensions; cells: 118 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Left (written)\n", - "119 points in 3 dimensions; cells: 118 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Hole (written)\n", - "119 points in 3 dimensions; cells: 118 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Plate (written)\n", - "17701 points in 3 dimensions; cells: 17405 quad; point_data=['bulk_node_ids']; cell_data=['MaterialIDs']; cell_sets=[]\n", - "##\n", - "MeshIO 5.3.4 found, MSH2VTU was tested with MeshIO 5.3.8.\n", - "sys:1: UserWarning: Warning, out-dated MeshIO version. In case of errors watch for commented code fragments from previous versions in this script (msh2vtu).\n", - "##\n", - "\n", - "Original mesh (read)\n", - "31601 points in 3 dimensions; cells: 790 line, 31205 quad; point_data=['gmsh:dim_tags']; cell_data=['gmsh:physical', 'gmsh:geometrical']; cell_sets=['Bottom', 'Right', 'Top', 'Left', 'Hole', 'Plate', 'gmsh:bounding_entities']\n", - "##\n", - "Detected mesh dimension: 2\n", - "##\n", - "Domain mesh (written)\n", - "31601 points in 3 dimensions; cells: 31205 quad; point_data=['original_node_number']; cell_data=['MaterialIDs']; cell_sets=[]\n", - "##\n", - "Boundary mesh (written)\n", - "790 points in 3 dimensions; cells: 790 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Bottom (written)\n", - "159 points in 3 dimensions; cells: 158 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Right (written)\n", - "159 points in 3 dimensions; cells: 158 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Top (written)\n", - "159 points in 3 dimensions; cells: 158 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Left (written)\n", - "159 points in 3 dimensions; cells: 158 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Hole (written)\n", - "159 points in 3 dimensions; cells: 158 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Plate (written)\n", - "31601 points in 3 dimensions; cells: 31205 quad; point_data=['bulk_node_ids']; cell_data=['MaterialIDs']; cell_sets=[]\n", - "##\n", - "MeshIO 5.3.4 found, MSH2VTU was tested with MeshIO 5.3.8.\n", - "sys:1: UserWarning: Warning, out-dated MeshIO version. In case of errors watch for commented code fragments from previous versions in this script (msh2vtu).\n", - "##\n", - "\n", - "Original mesh (read)\n", - "286801 points in 3 dimensions; cells: 2390 line, 285605 quad; point_data=['gmsh:dim_tags']; cell_data=['gmsh:physical', 'gmsh:geometrical']; cell_sets=['Bottom', 'Right', 'Top', 'Left', 'Hole', 'Plate', 'gmsh:bounding_entities']\n", - "##\n", - "Detected mesh dimension: 2\n", - "##\n", - "Domain mesh (written)\n", - "286801 points in 3 dimensions; cells: 285605 quad; point_data=['original_node_number']; cell_data=['MaterialIDs']; cell_sets=[]\n", - "##\n", - "Boundary mesh (written)\n", - "2390 points in 3 dimensions; cells: 2390 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Bottom (written)\n", - "479 points in 3 dimensions; cells: 478 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Right (written)\n", - "479 points in 3 dimensions; cells: 478 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Top (written)\n", - "479 points in 3 dimensions; cells: 478 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Left (written)\n", - "479 points in 3 dimensions; cells: 478 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Hole (written)\n", - "479 points in 3 dimensions; cells: 478 line; point_data=['bulk_node_ids']; cell_data=['bulk_elem_ids']; cell_sets=[]\n", - "##\n", - "Submesh Plate (written)\n", - "286801 points in 3 dimensions; cells: 285605 quad; point_data=['bulk_node_ids']; cell_data=['MaterialIDs']; cell_sets=[]\n", - "##\n" - ] - } - ], + "outputs": [], "source": [ + "%%capture\n", "for idx in STUDY_indices:\n", " input_file = f\"out/disc_with_hole_idx_is_{idx}.msh\"\n", " \n", @@ -817,12 +548,9 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 8, "id": "7605ea11-9afd-4698-a142-b2540478c521", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], @@ -834,12 +562,9 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 9, "id": "711c5e49-04d9-4d6b-9276-306f835b02d7", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [ @@ -847,7 +572,7 @@ "data": { "image/png": "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\n", "text/plain": [ - "<PIL.Image.Image image mode=RGB size=1000x500 at 0x7FF4DCC6EB00>" + "<PIL.Image.Image image mode=RGB size=1000x500 at 0x7F3E90B97EE0>" ] }, "metadata": {}, @@ -885,12 +610,9 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 10, "id": "a6db92d9-201c-4475-b84d-afd3f53c16e1", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], @@ -900,14 +622,9 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 11, "id": "4be9a95a-0415-46ac-9379-16d27c449a93", "metadata": { - "collapsed": true, - "jupyter": { - "outputs_hidden": true, - "source_hidden": true - }, "tags": [] }, "outputs": [ @@ -916,24 +633,23 @@ "output_type": "stream", "text": [ "OGS finished with project file disc_with_hole_idx_is_8.prj.\n", - "Execution took 2.5217549800872803 s\n", + "Execution took 0.2191469669342041 s\n", "OGS finished with project file disc_with_hole_idx_is_16.prj.\n", - "Execution took 1.9315154552459717 s\n", + "Execution took 0.464984655380249 s\n", "OGS finished with project file disc_with_hole_idx_is_24.prj.\n", - "Execution took 3.0686843395233154 s\n", + "Execution took 1.0798206329345703 s\n", "OGS finished with project file disc_with_hole_idx_is_40.prj.\n", - "Execution took 7.036077260971069 s\n", + "Execution took 4.209979772567749 s\n", "OGS finished with project file disc_with_hole_idx_is_60.prj.\n", - "Execution took 22.547306537628174 s\n", + "Execution took 14.099676370620728 s\n", "OGS finished with project file disc_with_hole_idx_is_80.prj.\n", - "Execution took 51.955302715301514 s\n", - "OGS finished with project file disc_with_hole_idx_is_240.prj.\n", - "Execution took 1628.5997660160065 s\n" + "Execution took 35.747533559799194 s\n" ] } ], "source": [ - "for idx in STUDY_indices:\n", + "# We exclude the last study index, because its simulation takes too long to be included in the OGS CI pipelines.\n", + "for idx in STUDY_indices[:-1]:\n", " prj_file = f\"disc_with_hole_idx_is_{idx}.prj\"\n", " model = ogs.OGS(INPUT_FILE=prj_file, PROJECT_FILE=prj_file)\n", " model.run_model(logfile=\"out/ogs.log\", args=\"-o out\") # write output files to the \"out\" directory" @@ -979,12 +695,9 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 12, "id": "9ae389db-44bb-4b3f-9046-be267c855984", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], @@ -1001,19 +714,14 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 13, "id": "4ce6a286-f862-42c9-9df2-3572b44d613b", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], "source": [ - "def vec4_to_mat3x3cart(vec4, xs, ys):\n", - " theta = np.arctan2(ys, xs)\n", - " \n", + "def vec4_to_mat3x3cart(vec4):\n", " m = np.zeros((3,3))\n", " m[0,0] = vec4[0]\n", " m[1,1] = vec4[1]\n", @@ -1023,9 +731,22 @@ " \n", " return np.matrix(m)\n", "\n", - "def vec4_to_mat3x3polar(vec4, xs, ys): \n", + "def vec4_to_mat3x3cart_multi(vec4):\n", + " assert vec4.shape[1] == 4\n", " \n", - " m_cart = vec4_to_mat3x3cart(vec4, xs, ys)\n", + " n_pts = vec4.shape[0]\n", + " \n", + " m = np.zeros((n_pts, 3, 3))\n", + " m[:,0,0] = vec4[:,0]\n", + " m[:,1,1] = vec4[:,1]\n", + " m[:,2,2] = vec4[:,2]\n", + " m[:,0,1] = vec4[:,3]\n", + " m[:,1,0] = vec4[:,3]\n", + " \n", + " return m\n", + "\n", + "def vec4_to_mat3x3polar_single(vec4, xs, ys):\n", + " m_cart = vec4_to_mat3x3cart(vec4)\n", " \n", " theta = np.arctan2(ys, xs)\n", "\n", @@ -1035,81 +756,146 @@ " rot[1,0] = np.sin(theta)\n", " rot[1,1] = np.cos(theta)\n", " \n", - " return rot.T * m_cart * rot" + " return rot.T * m_cart * rot\n", + "\n", + "def vec4_to_mat3x3polar_multi(vecs4, xs, ys):\n", + " \"\"\"Convert 4-vectors (Kelvin vector in 2D) to 3x3 matrices in polar coordinates at multiple points at once.\n", + " \n", + " Parameters\n", + " ----------\n", + " vecs4:\n", + " NumPy array of 4-vectors, dimensions: (N x 4)\n", + " xs:\n", + " NumPy array of x coordinates, length: N\n", + " ys:\n", + " NumPy array of y coordinates, length: N\n", + " \n", + " Returns\n", + " -------\n", + " A Numpy array of the symmetric matrices corresponding to the 4-vectors, dimensions: (N x 3 x 3)\n", + " \"\"\"\n", + " \n", + " n_pts = vecs4.shape[0] \n", + " assert n_pts == xs.shape[0]\n", + " assert n_pts == ys.shape[0]\n", + " assert vecs4.shape[1] == 4\n", + " \n", + " m_carts = vec4_to_mat3x3cart_multi(vecs4) # vecs4 converted to symmetric matrices\n", + " \n", + " thetas = np.arctan2(ys, xs)\n", + "\n", + " rots = np.zeros((n_pts, 3, 3)) # rotation matrices at each point\n", + " rots[:,0,0] = np.cos(thetas)\n", + " rots[:,0,1] = -np.sin(thetas)\n", + " rots[:,1,0] = np.sin(thetas)\n", + " rots[:,1,1] = np.cos(thetas)\n", + " rots[:,2,2] = 1\n", + " \n", + " # rot.T * m_cart * rot for each point\n", + " m_polars = np.einsum(\"...ji,...jk,...kl\", rots, m_carts, rots)\n", + " \n", + " assert m_polars.shape[0] == n_pts\n", + " assert m_polars.shape[1] == 3\n", + " assert m_polars.shape[2] == 3\n", + " \n", + " return m_polars\n", + "\n", + "def vec4_to_mat3x3polar(vec4, xs, ys):\n", + " if len(vec4.shape) == 1:\n", + " # only a single 4-vector will be converted\n", + " return vec4_to_mat3x3polar_single(vec4, xs, ys)\n", + " else:\n", + " return vec4_to_mat3x3polar_multi(vec4, xs, ys)" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 14, + "id": "e78120a1-fa54-472b-9434-a19c5c7e0461", + "metadata": {}, + "outputs": [], + "source": [ + "# Here we'll collect all simulation results\n", + "# accessible via their idx value\n", + "# We'll be able to reuse/read them many times\n", + "STUDY_num_result_meshes_by_index = {}\n", + "\n", + "def read_simulation_result_meshes():\n", + " for idx in STUDY_indices:\n", + " mesh = read_last_timestep_mesh(idx)\n", + " STUDY_num_result_meshes_by_index[idx] = mesh\n", + " \n", + "read_simulation_result_meshes()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, "id": "64a4cf27-11f1-41f3-b524-9dd66ed489cf", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], "source": [ - "# NOTE: Here we'll collect all simulation results\n", - "# accessible via their idx value\n", - "# We'll be able to reuse/read them many times\n", - "# NOTE: Again, good variable names are important!\n", "STUDY_num_result_xaxis_meshes_by_index = {}\n", "\n", - "for idx in STUDY_indices:\n", - " mesh = read_last_timestep_mesh(idx)\n", - " pt1 = (0,1e-6,0)\n", - " pt2 = (10,1e-6,0)\n", - " line_mesh = slice_along_line(mesh, pt1, pt2)\n", - " \n", - " # TODO: same for y axis and diagonal\n", - " STUDY_num_result_xaxis_meshes_by_index[idx] = line_mesh" + "def compute_xaxis_meshes():\n", + " for idx in STUDY_indices:\n", + " mesh = STUDY_num_result_meshes_by_index[idx]\n", + " pt1 = (0,1e-6,0)\n", + " pt2 = (10,1e-6,0)\n", + " line_mesh = slice_along_line(mesh, pt1, pt2)\n", + "\n", + " # TODO: same for y axis and diagonal\n", + " STUDY_num_result_xaxis_meshes_by_index[idx] = line_mesh\n", + " \n", + "compute_xaxis_meshes()" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "id": "2a794263-fe71-4855-9517-c29d71cf0343", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], "source": [ "STUDY_num_result_yaxis_meshes_by_index = {}\n", "\n", - "for idx in STUDY_indices:\n", - " mesh = read_last_timestep_mesh(idx)\n", - " pt1 = (1e-6,0,0)\n", - " pt2 = (1e-6,10,0)\n", - " line_mesh = slice_along_line(mesh, pt1, pt2)\n", + "def compute_yaxis_meshes():\n", + " for idx in STUDY_indices:\n", + " mesh = STUDY_num_result_meshes_by_index[idx]\n", + " pt1 = (1e-6,0,0)\n", + " pt2 = (1e-6,10,0)\n", + " line_mesh = slice_along_line(mesh, pt1, pt2)\n", + "\n", + " STUDY_num_result_yaxis_meshes_by_index[idx] = line_mesh\n", " \n", - " STUDY_num_result_yaxis_meshes_by_index[idx] = line_mesh" + "compute_yaxis_meshes()" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 17, "id": "c272c96d-fb10-4a78-846e-871eb6028366", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], "source": [ "STUDY_num_result_diagonal_meshes_by_index = {}\n", "\n", - "for idx in STUDY_indices:\n", - " mesh = read_last_timestep_mesh(idx)\n", - " pt1 = (1e-6,1e-6,0)\n", - " pt2 = (28.28,28.28,0)\n", - " line_mesh = slice_along_line(mesh, pt1, pt2)\n", - " \n", - " STUDY_num_result_diagonal_meshes_by_index[idx] = line_mesh" + "def compute_diagonal_meshes():\n", + " for idx in STUDY_indices:\n", + " mesh = STUDY_num_result_meshes_by_index[idx]\n", + " pt1 = (1e-6,1e-6,0)\n", + " pt2 = (28.28,28.28,0)\n", + " line_mesh = slice_along_line(mesh, pt1, pt2)\n", + "\n", + " STUDY_num_result_diagonal_meshes_by_index[idx] = line_mesh\n", + " \n", + "compute_diagonal_meshes()" ] }, { @@ -1122,12 +908,9 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 18, "id": "c9d98ae8-3848-4cea-88b8-c88b94232229", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [ @@ -1206,39 +989,40 @@ " ax[0][2].plot(r, kirsch_sig_rt(10,r,-90,2), color = \"orangered\", linestyle = \":\") #, label = \"$\\sigma_{r\\\\theta,\\mathrm{analytical}}$\")\n", "\n", " # numerical results\n", + " cell_size = compute_cell_size(idx, STUDY_num_result_meshes_by_index[idx])\n", "\n", " # NOTE: Using hard coded indices (8, 16, 24) here makes the code a bit harder to change.\n", " # I know, it's currently necessary for assigning colors, but in a clean up step at the very end,\n", " # we maybe can avoid it (or we are just happy that everything runs and looks nice and leave it as it is)\n", " if idx == 8:\n", " # TODO Maybe plotting the analytical results again is not necessary\n", - " ax[0][0].plot(dist_sorted, sig_rr_sorted*1000, color = \"lightskyblue\", label = f\"h = {compute_cell_size(idx):.3f} cm\")\n", - " ax[0][1].plot(dist_sorted, sig_tt_sorted*1000, color = \"limegreen\", label = f\"h = {compute_cell_size(idx):.3f} cm\")\n", - " ax[0][2].plot(dist_sorted, sig_rt_sorted*1000, color = \"lightcoral\", label = f\"h = {compute_cell_size(idx):.3f} cm\")\n", + " ax[0][0].plot(dist_sorted, sig_rr_sorted*1000, color = \"lightskyblue\", label = f\"h = {cell_size:.3f} cm\")\n", + " ax[0][1].plot(dist_sorted, sig_tt_sorted*1000, color = \"limegreen\", label = f\"h = {cell_size:.3f} cm\")\n", + " ax[0][2].plot(dist_sorted, sig_rt_sorted*1000, color = \"lightcoral\", label = f\"h = {cell_size:.3f} cm\")\n", " ax[1][0].plot(dist_sorted, f_abs_rr, color = \"lightskyblue\")\n", " ax[1][1].plot(dist_sorted, f_abs_tt, color = \"limegreen\")\n", " ax[1][2].plot(dist_sorted, f_abs_rt, color = \"lightcoral\")\n", " \n", " if idx == 16:\n", - " ax[0][0].plot(dist_sorted, sig_rr_sorted*1000, color = \"cornflowerblue\", label = f\"h = {compute_cell_size(idx):.3f} cm\")\n", - " ax[0][1].plot(dist_sorted, sig_tt_sorted*1000, color = \"forestgreen\", label = f\"h = {compute_cell_size(idx):.3f} cm\")\n", - " ax[0][2].plot(dist_sorted, sig_rt_sorted*1000, color = \"firebrick\", label = f\"h = {compute_cell_size(idx):.3f} cm\")\n", + " ax[0][0].plot(dist_sorted, sig_rr_sorted*1000, color = \"cornflowerblue\", label = f\"h = {cell_size:.3f} cm\")\n", + " ax[0][1].plot(dist_sorted, sig_tt_sorted*1000, color = \"forestgreen\", label = f\"h = {cell_size:.3f} cm\")\n", + " ax[0][2].plot(dist_sorted, sig_rt_sorted*1000, color = \"firebrick\", label = f\"h = {cell_size:.3f} cm\")\n", " ax[1][0].plot(dist_sorted, f_abs_rr, color = \"cornflowerblue\")\n", " ax[1][1].plot(dist_sorted, f_abs_tt, color = \"forestgreen\")\n", " ax[1][2].plot(dist_sorted, f_abs_rt, color = \"firebrick\")\n", " \n", " if idx == 24:\n", - " ax[0][0].plot(dist_sorted, sig_rr_sorted*1000, color = \"royalblue\", label = f\"h = {compute_cell_size(idx):.3f} cm\")\n", - " ax[0][1].plot(dist_sorted, sig_tt_sorted*1000, color = \"darkgreen\", label = f\"h = {compute_cell_size(idx):.3f} cm\")\n", - " ax[0][2].plot(dist_sorted, sig_rt_sorted*1000, color = \"darkred\", label = f\"h = {compute_cell_size(idx):.3f} cm\")\n", + " ax[0][0].plot(dist_sorted, sig_rr_sorted*1000, color = \"royalblue\", label = f\"h = {cell_size:.3f} cm\")\n", + " ax[0][1].plot(dist_sorted, sig_tt_sorted*1000, color = \"darkgreen\", label = f\"h = {cell_size:.3f} cm\")\n", + " ax[0][2].plot(dist_sorted, sig_rt_sorted*1000, color = \"darkred\", label = f\"h = {cell_size:.3f} cm\")\n", " ax[1][0].plot(dist_sorted, f_abs_rr, color = \"royalblue\")\n", " ax[1][1].plot(dist_sorted, f_abs_tt, color = \"darkgreen\")\n", " ax[1][2].plot(dist_sorted, f_abs_rt, color = \"darkred\")\n", " \n", " if idx == 240:\n", - " ax[0][0].plot(dist_sorted, sig_rr_sorted*1000, color = \"black\", label = f\"h = {compute_cell_size(idx):.3f} cm\")\n", - " ax[0][1].plot(dist_sorted, sig_tt_sorted*1000, color = \"black\", label = f\"h = {compute_cell_size(idx):.3f} cm\")\n", - " ax[0][2].plot(dist_sorted, sig_rt_sorted*1000, color = \"black\", label = f\"h = {compute_cell_size(idx):.3f} cm\") \n", + " ax[0][0].plot(dist_sorted, sig_rr_sorted*1000, color = \"black\", label = f\"h = {cell_size:.3f} cm\")\n", + " ax[0][1].plot(dist_sorted, sig_tt_sorted*1000, color = \"black\", label = f\"h = {cell_size:.3f} cm\")\n", + " ax[0][2].plot(dist_sorted, sig_rt_sorted*1000, color = \"black\", label = f\"h = {cell_size:.3f} cm\") \n", "\n", " # final plot settings \n", " for i in range (3):\n", @@ -1326,12 +1110,9 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 19, "id": "95b28f6d-ca06-4ab0-b974-dba86bbf47b4", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], @@ -1341,12 +1122,9 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 20, "id": "2d629d34-4539-44a9-bd77-e872869551da", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], @@ -1360,23 +1138,16 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 21, "id": "36e68ba4-ed00-4516-824f-f0edf8215c23", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], "source": [ - "def compute_ell_2_norm_sigma(idx):\n", - " mesh_coarse = read_last_timestep_mesh(idx)\n", - " mesh_fine = read_last_timestep_mesh(240)\n", - " mesh_resampled_to_240_resolution = mesh_fine.sample(mesh_coarse)\n", - " \n", - " sig_rr, sig_tt, sig_rt = get_sigma_polar_components(mesh_resampled_to_240_resolution)\n", - " sig_rr_240, sig_tt_240, sig_rt_240 = get_sigma_polar_components(mesh_fine)\n", + "def compute_ell_2_norm_sigma(idx, sigmas_test, sigmas_reference):\n", + " sig_rr, sig_tt, sig_rt = sigmas_test\n", + " sig_rr_240, sig_tt_240, sig_rt_240 = sigmas_reference\n", " \n", " list_rr = (sig_rr_240 - sig_rr)**2\n", " list_tt = (sig_tt_240 - sig_tt)**2\n", @@ -1391,21 +1162,14 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "id": "9ea61711-7163-4b38-b640-bf63b2baf47a", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], "source": [ - "def compute_ell_2_norm_displacement(idx):\n", - " mesh_coarse = read_last_timestep_mesh(idx)\n", - " mesh_fine = read_last_timestep_mesh(240)\n", - " mesh_resampled_to_240_resolution = mesh_fine.sample(mesh_coarse)\n", - " \n", + "def compute_ell_2_norm_displacement(idx, mesh_resampled_to_240_resolution, mesh_fine):\n", " dis = mesh_resampled_to_240_resolution.point_data[\"displacement\"]\n", " dis_x = dis[:,0]\n", " dis_y = dis[:,1]\n", @@ -1425,54 +1189,35 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 23, "id": "15e217fe-2066-4ccf-9c12-487df6419770", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], "source": [ - "def compute_root_mean_square_sigma(idx):\n", - " mesh_coarse = read_last_timestep_mesh(idx)\n", - " mesh_fine = read_last_timestep_mesh(240)\n", - " mesh_resampled_to_240_resolution = mesh_fine.sample(mesh_coarse)\n", - " \n", - " points = mesh_resampled_to_240_resolution.point_data[\"sigma\"].shape[0] \n", - " \n", - " sig_rr, sig_tt, sig_rt = get_sigma_polar_components(mesh_resampled_to_240_resolution)\n", - " sig_rr_240, sig_tt_240, sig_rt_240 = get_sigma_polar_components(mesh_fine)\n", - " \n", - " list_rr = (sig_rr_240 - sig_rr)**2\n", - " list_tt = (sig_tt_240 - sig_tt)**2\n", - " list_rt = (sig_rt_240 - sig_rt)**2\n", + "def compute_root_mean_square_sigma(idx, sigmas_test, sigmas_reference):\n", + " sig_rr, sig_tt, sig_rt = sigmas_test\n", + " sig_rr_240, sig_tt_240, sig_rt_240 = sigmas_reference\n", " \n", - " l2_rr = np.sqrt(sum(list_rr))\n", - " l2_tt = np.sqrt(sum(list_tt))\n", - " l2_rt = np.sqrt(sum(list_rt))\n", + " l2_rr = np.linalg.norm(sig_rr_240 - sig_rr)\n", + " l2_tt = np.linalg.norm(sig_tt_240 - sig_tt)\n", + " l2_rt = np.linalg.norm(sig_rt_240 - sig_rt)\n", " \n", + " points = sig_rr.shape[0]\n", " return l2_rr/np.sqrt(points), l2_tt/np.sqrt(points), l2_rt/np.sqrt(points)" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 24, "id": "750318a0-18b6-43d0-9a26-9503dce8406a", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], "source": [ - "def compute_root_mean_square_displacement(idx):\n", - " mesh_coarse = read_last_timestep_mesh(idx)\n", - " mesh_fine = read_last_timestep_mesh(240)\n", - " mesh_resampled_to_240_resolution = mesh_fine.sample(mesh_coarse)\n", - " \n", + "def compute_root_mean_square_displacement(idx, mesh_resampled_to_240_resolution, mesh_fine):\n", " points = mesh_resampled_to_240_resolution.point_data[\"sigma\"].shape[0] \n", " \n", " dis = mesh_resampled_to_240_resolution.point_data[\"displacement\"]\n", @@ -1483,45 +1228,28 @@ " dis_x_240 = dis_240[:,0]\n", " dis_y_240 = dis_240[:,1]\n", " \n", - " list_x = (dis_x_240 - dis_x)**2\n", - " list_y = (dis_y_240 - dis_y)**2\n", - " \n", - " l2_x = np.sqrt(sum(list_x))\n", - " l2_y = np.sqrt(sum(list_y))\n", + " l2_x = np.linalg.norm(dis_x_240 - dis_x)\n", + " l2_y = np.linalg.norm(dis_y_240 - dis_y)\n", " \n", " return l2_x/np.sqrt(points), l2_y/np.sqrt(points)" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 25, "id": "5de3e825-d230-4216-83f8-1df1fe92def9", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], "source": [ - "def compute_Ell_2_norm_sigma(idx):\n", - " mesh_coarse = read_last_timestep_mesh(idx)\n", - " mesh_fine = read_last_timestep_mesh(240)\n", - " mesh_resampled_to_240_resolution = mesh_fine.sample(mesh_coarse)\n", - " \n", - " points = mesh_resampled_to_240_resolution.point_data[\"sigma\"].shape[0]\n", - " \n", - " sig_rr, sig_tt, sig_rt = get_sigma_polar_components(mesh_resampled_to_240_resolution)\n", - " sig_rr_240, sig_tt_240, sig_rt_240 = get_sigma_polar_components(mesh_fine)\n", + "def compute_Ell_2_norm_sigma(idx, mesh_resampled_to_240_resolution, sigmas_test, sigmas_reference):\n", + " sig_rr, sig_tt, sig_rt = sigmas_test\n", + " sig_rr_240, sig_tt_240, sig_rt_240 = sigmas_reference\n", " \n", - " list_rr = np.zeros([points])\n", - " list_tt = np.zeros([points])\n", - " list_rt = np.zeros([points])\n", - "\n", - " for i in range (points):\n", - " list_rr[i] = (sig_rr_240[i] - sig_rr[i])**2\n", - " list_tt[i] = (sig_tt_240[i] - sig_tt[i])**2\n", - " list_rt[i] = (sig_rt_240[i] - sig_rt[i])**2\n", + " list_rr = (sig_rr_240 - sig_rr)**2\n", + " list_tt = (sig_tt_240 - sig_tt)**2\n", + " list_rt = (sig_rt_240 - sig_rt)**2\n", " \n", " # We add the squared differences as new point data to the mesh\n", " mesh_resampled_to_240_resolution.point_data[\"diff_rr_squared\"] = list_rr\n", @@ -1541,23 +1269,14 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 26, "id": "14732f40-89db-4bf9-bea4-7835662d0b81", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, "outputs": [], "source": [ - "def compute_Ell_2_norm_displacement(idx):\n", - " mesh_coarse = read_last_timestep_mesh(idx)\n", - " mesh_fine = read_last_timestep_mesh(240)\n", - " mesh_resampled_to_240_resolution = mesh_fine.sample(mesh_coarse)\n", - " \n", - " points = mesh_resampled_to_240_resolution.point_data[\"sigma\"].shape[0]\n", - " \n", + "def compute_Ell_2_norm_displacement(idx, mesh_resampled_to_240_resolution, mesh_fine):\n", " dis = mesh_resampled_to_240_resolution.point_data[\"displacement\"]\n", " dis_x = dis[:,0]\n", " dis_y = dis[:,1]\n", @@ -1565,13 +1284,9 @@ " dis_240 = mesh_fine.point_data[\"displacement\"]\n", " dis_x_240 = dis_240[:,0]\n", " dis_y_240 = dis_240[:,1]\n", - " \n", - " list_x = np.zeros([points])\n", - " list_y = np.zeros([points])\n", "\n", - " for i in range (points):\n", - " list_x[i] = (dis_x_240[i] - dis_x[i])**2\n", - " list_y[i] = (dis_y_240[i] - dis_y[i])**2\n", + " list_x = (dis_x_240 - dis_x)**2\n", + " list_y = (dis_y_240 - dis_y)**2\n", " \n", " # We add the squared differences as new point data to the mesh\n", " mesh_resampled_to_240_resolution.point_data[\"diff_x_squared\"] = list_x\n", @@ -1589,28 +1304,12 @@ }, { "cell_type": "code", - "execution_count": 29, - "id": "0b4d547d-a9d8-48f1-a669-ed80803f333c", + "execution_count": 27, + "id": "56c81fcf-ffe0-4bc7-8ee9-c3c585e618bd", "metadata": { - "jupyter": { - "source_hidden": true - }, "tags": [] }, - "outputs": [ - { - "data": { - "image/png": "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\n", - "text/plain": [ - "<Figure size 1440x360 with 3 Axes>" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# empty dictionaries\n", "size = {}\n", @@ -1630,18 +1329,71 @@ "L2_x = {}\n", "L2_y = {}\n", "\n", - "for idx in STUDY_indices:\n", - " if idx != 240:\n", - " l2_rr[idx], l2_tt[idx], l2_rt[idx] = compute_ell_2_norm_sigma(idx)\n", - " rms_rr[idx], rms_tt[idx], rms_rt[idx] = compute_root_mean_square_sigma(idx)\n", - " L2_rr[idx], L2_tt[idx], L2_rt[idx] = compute_Ell_2_norm_sigma(idx)\n", - " l2_x[idx], l2_y[idx] = compute_ell_2_norm_displacement(idx)\n", - " rms_x[idx], rms_y[idx] = compute_root_mean_square_displacement(idx)\n", - " L2_x[idx], L2_y[idx] = compute_Ell_2_norm_displacement(idx)\n", - " size[idx] = compute_cell_size(idx)\n", + "def compute_error_norms():\n", + " mesh_fine = STUDY_num_result_meshes_by_index[240]\n", + " sigmas_reference = get_sigma_polar_components(mesh_fine)\n", + "\n", + " for idx in STUDY_indices:\n", + " if idx != 240: # 240 is the \"pseudo\" analytical solution we compare against.\n", + " mesh_coarse = STUDY_num_result_meshes_by_index[idx]\n", + " mesh_resampled_to_240_resolution = mesh_fine.sample(mesh_coarse)\n", + " sigmas_test = get_sigma_polar_components(mesh_resampled_to_240_resolution)\n", "\n", + " l2_rr[idx], l2_tt[idx], l2_rt[idx] = compute_ell_2_norm_sigma(idx, sigmas_test, sigmas_reference)\n", + " rms_rr[idx], rms_tt[idx], rms_rt[idx] = compute_root_mean_square_sigma(idx, sigmas_test, sigmas_reference)\n", + " L2_rr[idx], L2_tt[idx], L2_rt[idx] = compute_Ell_2_norm_sigma(idx, mesh_resampled_to_240_resolution, sigmas_test, sigmas_reference)\n", + " \n", + " l2_x[idx], l2_y[idx] = compute_ell_2_norm_displacement(idx, mesh_resampled_to_240_resolution, mesh_fine)\n", + " rms_x[idx], rms_y[idx] = compute_root_mean_square_displacement(idx, mesh_resampled_to_240_resolution, mesh_fine)\n", + " L2_x[idx], L2_y[idx] = compute_Ell_2_norm_displacement(idx, mesh_resampled_to_240_resolution, mesh_fine)\n", + " size[idx] = compute_cell_size(idx, mesh_coarse)\n", + " \n", + "compute_error_norms()" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "43ee69fa-0a79-43ee-a66d-5b674d1340ac", + "metadata": {}, + "outputs": [], + "source": [ + "def plot_slope_sketch(ax, x0, y0, slopes, xmax=None):\n", + " \"\"\"Plot sketch for slopes. All slopes cross at (x0, y0)\"\"\"\n", + " if xmax is None: xmax = 2*x0\n", + " xs = np.linspace(x0, xmax, 20)\n", + " \n", + " for slope in slopes:\n", + " y_ = xs[0]**slope\n", + " ys = y0/y_ * xs**slope\n", + " ax.plot(xs, ys, color = \"black\")\n", + " ax.text(xs[-1]*1.05, ys[-1], slope)" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "e9581b34-dd03-4072-84f0-f3ee1a64c068", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "<Figure size 1440x360 with 3 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ "h = np.linspace(size[80],size[8],1000)\n", - "k = np.linspace(0.5,1, 2)\n", + "k = np.linspace(1,2, 20)\n", "\n", "fig, ax = plt.subplots(ncols=3, figsize = (20,5))\n", "\n", @@ -1650,13 +1402,9 @@ "ax[0].plot(size.values(), l2_rt.values(), color = \"firebrick\", label = \"$\\ell_{2, r\\\\theta}$\")\n", "ax[0].plot(size.values(), l2_x.values(), color = \"royalblue\", linestyle = \"--\", label = \"$\\ell_{2, x}$\")\n", "ax[0].plot(size.values(), l2_y.values(), color = \"royalblue\", label = \"$\\ell_{2, y}$\")\n", - "#ax[0].plot(h,0.15*h**1.1, color = \"black\")\n", - "ax[0].plot(k, 0.008*(k+0.5)**1, color = \"black\")\n", - "ax[0].plot(k, 0.008*(k+0.5)**2, color = \"black\")\n", - "ax[0].plot(k, 0.008*(k+0.5)**3, color = \"black\")\n", - "ax[0].text(1.1, 0.008*(1+0.5)**1, \"1\")\n", - "ax[0].text(1.1, 0.008*(1+0.5)**2, \"2\")\n", - "ax[0].text(1.1, 0.008*(1+0.5)**3, \"3\")\n", + "\n", + "plot_slope_sketch(ax[0], 1.5e-1, 5e-2, [1,2,3], xmax=2.5e-1)\n", + "\n", "ax[0].set_title('$\\ell_2$ norms')\n", "ax[0].set_ylabel(\"$\\ell_2$ / kPa or cm\")\n", "\n", @@ -1665,13 +1413,9 @@ "ax[1].plot(size.values(), rms_rt.values(), color = \"firebrick\", label = \"$RMS_{r\\\\theta}$\")\n", "ax[1].plot(size.values(), rms_x.values(), color = \"royalblue\", linestyle = \"--\", label = \"$RMS_{x}$\")\n", "ax[1].plot(size.values(), rms_y.values(), color = \"royalblue\", label = \"$RMS_{y}$\")\n", - "#ax[1].plot(h,0.0003*h**1.1, color = \"black\")\n", - "ax[1].plot(k, 0.00002*(k+0.5)**1, color = \"black\")\n", - "ax[1].plot(k, 0.00002*(k+0.5)**2, color = \"black\")\n", - "ax[1].plot(k, 0.00002*(k+0.5)**3, color = \"black\")\n", - "ax[1].text(1.1, 0.00002*(1+0.5)**1, \"1\")\n", - "ax[1].text(1.1, 0.00002*(1+0.5)**2, \"2\")\n", - "ax[1].text(1.1, 0.00002*(1+0.5)**3, \"3\")\n", + "\n", + "plot_slope_sketch(ax[1], 1.5e-1, 1e-4, [1,2,3], xmax=2.5e-1)\n", + "\n", "ax[1].set_title(\"Root-mean-square\")\n", "ax[1].set_ylabel(\"RMS / kPa or cm\")\n", "\n", @@ -1680,13 +1424,9 @@ "ax[2].plot(size.values(), L2_rt.values(), color = \"firebrick\", label = \"$L_{2, r\\\\theta}$\")\n", "ax[2].plot(size.values(), L2_x.values(), color = \"royalblue\", linestyle = \"--\", label = \"$L_{2, x}$\")\n", "ax[2].plot(size.values(), L2_y.values(), color = \"royalblue\", label = \"$L_{2, y}$\")\n", - "#ax[2].plot(h,0.003*h**1.1, color=\"black\")\n", - "ax[2].plot(k, 0.0002*(k+0.5)**1, color = \"black\")\n", - "ax[2].plot(k, 0.0002*(k+0.5)**2, color = \"black\")\n", - "ax[2].plot(k, 0.0002*(k+0.5)**3, color = \"black\")\n", - "ax[2].text(1.1, 0.0002*(1+0.5)**1, \"1\")\n", - "ax[2].text(1.1, 0.0002*(1+0.5)**2, \"2\")\n", - "ax[2].text(1.1, 0.0002*(1+0.5)**3, \"3\")\n", + "\n", + "plot_slope_sketch(ax[2], 1.5e-1, 1e-3, [1,2,3], xmax=2.5e-1)\n", + "\n", "ax[2].set_title(\"$L_2$ norms (integral norms)\")\n", "ax[2].set_ylabel(\"$L_2$ /kPa or cm\")\n", "for i in range (3):\n", -- GitLab