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Some formatting fixes.
1 parent 443362c commit 1282e94

10 files changed

+54
-242
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‎.flake8

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[flake8]
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max-line-length = 88
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extend-ignore = E203, E741
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extend-ignore = E203, E741

‎examples/closures/plot_closure_comparison.ipynb

+10-65
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‎examples/closures/plot_extrema.ipynb

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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
@@ -18,176 +18,99 @@
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"import numpy as np\n",
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"from mpl_toolkits.mplot3d import Axes3D\n",
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"\n",
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"from fiberoripy.closures import (\n",
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" IBOF_closure,\n",
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" compute_closure,\n",
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" hybrid_closure,\n",
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" linear_closure,\n",
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" quadratic_closure,\n",
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")\n",
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"from fiberoripy.tensorplot import (\n",
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" plot_orbit2,\n",
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" plot_orbit4,\n",
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" plot_projection2,\n",
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" plot_projection4,\n",
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")"
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"from fiberoripy.closures import get_random_tensor_pair\n",
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"\n",
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"from fiberoripy.tensorplot import plot_orbit2, plot_orbit4\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# define second order fiber orientation tensor\n",
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"a_iso = 1.0 / 3.0 * np.eye(3)\n",
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"a_uni = np.array([[0.9,0,0],[0,0.05, 0],[0,0,0.05]])\n",
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"a_pln = np.array([[0.4,0,0],[0,0.4, 0],[0,0,0.1]])\n",
34+
"a_uni = np.array([[0.9, 0, 0], [0, 0.05, 0], [0, 0, 0.05]])\n",
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"a_pln = np.array([[0.4, 0, 0], [0, 0.4, 0], [0, 0, 0.1]])\n",
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"\n",
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"# create a fourth order fiber orientation tensor\n",
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"A_iso = compute_closure(a_iso, \"RANDOM\", N=1000)\n",
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"A_uni = compute_closure(a_uni, \"RANDOM\", N=1000)\n",
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"A_pln = compute_closure(a_pln, \"RANDOM\", N=1000)"
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"_, A_iso = get_random_tensor_pair(seed=a_iso, N=5000)\n",
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"_, A_uni = get_random_tensor_pair(seed=a_uni, N=5000)\n",
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"_, A_pln = get_random_tensor_pair(seed=a_pln, N=5000)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "e710d3dd22534b28937261bf1db80c28",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"outputs": [],
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"source": [
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"# Second order tensor plot (isotropic)\n",
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"fig = plt.figure(figsize=(12, 8))\n",
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"\n",
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"ax = fig.add_subplot(111, projection=Axes3D.name)\n",
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"ax._axis3don = False\n",
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"plotargs = {\"color\":[0,0.588,0.510], \"rstride\":1, \"cstride\":1}\n",
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"plotargs = {\"color\": [0, 0.588, 0.510], \"rstride\": 1, \"cstride\": 1}\n",
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"plot_orbit2(ax, plotargs, a_iso)\n",
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"\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "c259da2fd6e64d34b59acf3d98a17feb",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"outputs": [],
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"source": [
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"# Second order tensor plot (unidirectional)\n",
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"fig = plt.figure(figsize=(12, 8))\n",
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"\n",
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"ax = fig.add_subplot(111, projection=Axes3D.name)\n",
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"ax._axis3don = False\n",
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"plotargs = {\"color\":[0,0.588,0.510], \"rstride\":1, \"cstride\":1}\n",
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"plotargs = {\"color\": [0, 0.588, 0.510], \"rstride\": 1, \"cstride\": 1}\n",
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"plot_orbit2(ax, plotargs, a_uni)\n",
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"\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "63d737f971c54dfc9f5d77ccd1cca695",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"outputs": [],
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"source": [
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"# Second order tensor plot (planar)\n",
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"fig = plt.figure(figsize=(12, 8))\n",
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"\n",
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"ax = fig.add_subplot(111, projection=Axes3D.name)\n",
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"ax._axis3don = False\n",
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"plotargs = {\"color\":[0,0.588,0.510], \"rstride\":4, \"cstride\":4}\n",
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"plotargs = {\"color\": [0, 0.588, 0.510], \"rstride\": 4, \"cstride\": 4}\n",
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"plot_orbit2(ax, plotargs, a_pln)\n",
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"\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "9fca6f4e29b545feaab4909884f70fae",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"outputs": [],
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"source": [
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"# Fourth order tensor plot\n",
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"fig = plt.figure(figsize=(12, 8))\n",
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"\n",
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"ax = fig.add_subplot(111, projection=Axes3D.name)\n",
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"plotargs = {\"color\":[0,0.588,0.510], \"rstride\":1, \"cstride\":1}\n",
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"plotargs = {\"color\": [0, 0.588, 0.510], \"rstride\": 1, \"cstride\": 1}\n",
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"plot_orbit4(ax, plotargs, A_iso)\n",
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"\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"display_name": "base",
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"language": "python",
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"name": "python3"
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.0"
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"version": "3.10.6"
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}
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},
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"nbformat": 4,

‎examples/orientation/ardrsc_perfectrotation.ipynb

+2-9
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"plt.tight_layout()\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": ".venv313",
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"display_name": "base",
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"language": "python",
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"name": "python3"
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.13.0"
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"version": "3.10.6"
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}
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},
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"nbformat": 4,

‎examples/orientation/ardrsc_perfectshear.ipynb

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"plt.tight_layout()\n",
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"plt.show()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": ".venv313",
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"display_name": "base",
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"language": "python",
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"name": "python3"
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.13.0"
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"version": "3.10.6"
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}
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},
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"nbformat": 4,

‎examples/orientation/comparison_perfectshear.ipynb

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"\n",
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"# time steps\n",
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"t0, tf = 0, 80\n",
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"t = np.linspace(t0, tf, 100)\n",
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"t = np.linspace(t0, tf, 500)\n",
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"\n",
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"# initial fiber orientation state\n",
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"A0 = 1.0 / 3.0 * np.eye(3)"
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" return np.array([[0.0, 0.0, 1.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0]])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# compute solutions by integrating the ODEs\n",
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"A_ft = odeint(folgar_tucker_ode, A0.ravel(), t, args=(xi, L, 0.0311),)\n",
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"A_iard = odeint(iard_ode, A0.ravel(), t, args=(xi, L, 0.0562, 0.9977),)\n",
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"A_pard = odeint(pard_ode, A0.ravel(), t, args=(xi, L, 0.0169, 0.9868),)\n",
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"A_mrd = odeint(mrd_ode, A0.ravel(), t, args=(xi, L, 0.0198, 1.0, 0.4796, 0.0120),)\n",
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"A_wpt = odeint(ard_rsc_ode, A0.ravel(), t, args=(xi, L, 0.0504 * (1.0 - 0.995), 1.0, 0.0, 0.0504 * 0.995, 0.0, 0.0),)\n",
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"A_pt = odeint(ard_rsc_ode, A0.ravel(), t, args=(xi, L, 1.924e-4, 1.0, 5.839e-3, 0.04, 1.168e-5, 0.0),)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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],
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"metadata": {
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"kernelspec": {
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"display_name": ".venv313",
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"display_name": "base",
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"language": "python",
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"name": "python3"
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.13.0"
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"version": "3.10.6"
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}
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},
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"nbformat": 4,

‎examples/orientation/iard_perfectshear.ipynb

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"plt.tight_layout()\n",
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"plt.show()"
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]
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{
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"cell_type": "code",
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"execution_count": null,
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "base",
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"language": "python",
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"name": "python3"
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.13.0"
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"version": "3.10.6"
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}
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},
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"nbformat": 4,

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