127 lines
20 KiB
Plaintext
127 lines
20 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"Text(0.5, 1.0, 'vel_init')"
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]
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},
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"execution_count": 1,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 432x288 with 2 Axes>"
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]
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},
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"metadata": {
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"needs_background": "light"
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},
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"output_type": "display_data"
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},
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 432x288 with 2 Axes>"
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]
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},
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"metadata": {
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"needs_background": "light"
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},
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"output_type": "display_data"
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}
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],
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"source": [
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"# final model\n",
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"fpath_final_model = './OUTPUT_FILES/final_model.h5'\n",
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"fpath_true_model = \"./test_model_init_100-100-100.h5\"\n",
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"\n",
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"import h5py\n",
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"\n",
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"# read vel, xi, eta dataset \n",
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"with h5py.File(fpath_final_model, 'r') as f:\n",
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" vel = f['vel'][:]\n",
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" xi = f['xi'][:]\n",
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" eta = f['eta'][:]\n",
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" #zeta = f['zeta'][:]\n",
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"\n",
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"# read true model\n",
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"with h5py.File(fpath_true_model, 'r') as f:\n",
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" vel_true = f['vel'][:]\n",
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" xi_true = f['xi'][:]\n",
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" eta_true = f['eta'][:]\n",
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" #zeta_true = f['zeta'][:]\n",
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"# plot\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"\n",
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"# plot vel\n",
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"plt.figure()\n",
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"plt.imshow(vel[:,:,5], origin='lower', aspect='auto')\n",
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"plt.colorbar()\n",
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"plt.title('vel')\n",
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"\n",
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"# plot xi\n",
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"#plt.figure()\n",
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"#plt.imshow(xi[:,:,10], origin='lower', aspect='auto')\n",
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"#plt.colorbar()\n",
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"#plt.title('xi')\n",
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"#\n",
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"## plot eta\n",
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"#plt.figure()\n",
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"#plt.imshow(eta[:,:,10], origin='lower', aspect='auto')\n",
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"#plt.colorbar()\n",
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"#plt.title('eta')\n",
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"\n",
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"# plot vel_true\n",
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"plt.figure()\n",
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"plt.imshow(vel_true[:,:,5], origin='lower', aspect='auto')\n",
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"plt.colorbar()\n",
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"plt.title('vel_init')\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": null,
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"metadata": {},
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"outputs": [],
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||
|
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"source": []
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}
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|
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],
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|
"metadata": {
|
||
|
|
"kernelspec": {
|
||
|
|
"display_name": "Python 3.9.1 64-bit ('3.9.1')",
|
||
|
|
"language": "python",
|
||
|
|
"name": "python3"
|
||
|
|
},
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||
|
|
"language_info": {
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||
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|
"codemirror_mode": {
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||
|
|
"name": "ipython",
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"version": 3
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||
|
|
},
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|
|
"file_extension": ".py",
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|
"mimetype": "text/x-python",
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"name": "python",
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||
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"nbconvert_exporter": "python",
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||
|
|
"pygments_lexer": "ipython3",
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|
"version": "3.9.1"
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|
},
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"vscode": {
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"interpreter": {
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|
"hash": "02f83e1f4cd9619657a6845405e2dd67c4de23753ba48bca5dce2ebf57b3813a"
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}
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|
}
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|
|
},
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||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 2
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||
|
|
}
|