91 lines
44 KiB
Plaintext
91 lines
44 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": 23,
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"import numpy as np\n",
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"\n",
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"fname_in=\"./test_cg_smooth_0_in\"\n",
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"fname_out=\"./test_cg_smooth_0_out\"\n",
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"\n",
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"nx=50\n",
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"ny=50\n",
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"nz=50\n",
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"\n",
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"# Read in the input file and convert to a 3D numpy array by genfromtxt\n",
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"data_in = np.genfromtxt(fname_in, delimiter=' ', dtype=None)\n",
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"data_in = data_in.reshape((nx,ny,nz))\n",
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"\n",
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"# Read in the output file and convert to a 3D numpy array by genfromtxt\n",
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"data_out = np.genfromtxt(fname_out, delimiter=' ', dtype=None)\n",
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"data_out = data_out.reshape((nx,ny,nz))"
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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": 24,
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"metadata": {},
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"outputs": [
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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 1000x1000 with 4 Axes>"
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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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"source": [
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"#plot\n",
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"import matplotlib.pyplot as plt\n",
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"\n",
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"plt.figure(figsize=(10,10))\n",
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"plt.subplot(1,2,1)\n",
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"plt.imshow(data_in[:,25,:], origin='lower', cmap='jet')\n",
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"plt.colorbar()\n",
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"plt.title('Input')\n",
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"plt.subplot(1,2,2)\n",
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"plt.imshow(data_out[:,25,:], origin='lower', cmap='jet')\n",
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"plt.colorbar()\n",
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"plt.title('Output')\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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"language": "python",
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"name": "python3"
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},
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"language_info": {
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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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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.8"
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},
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"orig_nbformat": 4
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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