104 lines
24 KiB
Plaintext
104 lines
24 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n",
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"# 3D plotting\n",
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"\n",
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"Demo 3D plotting with matplotlib and style the figure.\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": 1,
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"metadata": {
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"collapsed": false,
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"jupyter": {
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"outputs_hidden": false
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}
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},
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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 640x480 with 1 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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"import matplotlib.pyplot as plt\n",
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"from mpl_toolkits.mplot3d.axes3d import Axes3D, get_test_data\n",
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"\n",
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"ax: Axes3D = plt.figure().add_subplot(projection=\"3d\")\n",
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"X, Y, Z = get_test_data(0.05)\n",
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"cset = ax.contourf(X, Y, Z)\n",
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"ax.clabel(cset, fontsize=9, inline=1)\n",
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"\n",
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"plt.xticks([])\n",
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"plt.yticks([])\n",
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"ax.set_zticks([])\n",
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"\n",
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"\n",
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"ax.text2D(\n",
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" -0.05,\n",
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" 1.05,\n",
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" \" 3D plots \\n\",\n",
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" horizontalalignment=\"left\",\n",
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" verticalalignment=\"top\",\n",
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" bbox={\"facecolor\": \"white\", \"alpha\": 1.0},\n",
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" family=\"DejaVu Sans\",\n",
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" size=\"x-large\",\n",
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" transform=plt.gca().transAxes,\n",
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")\n",
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"\n",
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"ax.text2D(\n",
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" -0.05,\n",
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" 0.975,\n",
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" \" Plot 2D or 3D data\",\n",
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" horizontalalignment=\"left\",\n",
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" verticalalignment=\"top\",\n",
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" family=\"DejaVu Sans\",\n",
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" size=\"medium\",\n",
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" transform=plt.gca().transAxes,\n",
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")\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 (ipykernel)",
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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": "3.12.11"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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