Created
November 2, 2020 13:19
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| { | |
| "cells": [ | |
| { | |
| "cell_type": "code", | |
| "execution_count": 1, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "import matplotlib.pyplot as plt\n", | |
| "import matplotlib\n", | |
| "import numpy as np" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 2, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "3.2.2 module://ipykernel.pylab.backend_inline\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "print(matplotlib.__version__, matplotlib.get_backend())" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 3, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "data": { | |
| "image/png": 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\n", | |
| "text/plain": [ | |
| "<Figure size 864x216 with 11 Axes>" | |
| ] | |
| }, | |
| "metadata": { | |
| "needs_background": "light" | |
| }, | |
| "output_type": "display_data" | |
| } | |
| ], | |
| "source": [ | |
| "fig,ax = plt.subplots(ncols=11, figsize=[12,3])\n", | |
| "for i in range(11):\n", | |
| " ax[i].imshow(np.full((100,100), 0.1), cmap='gray', vmin=0, vmax=1)\n", | |
| " ax[i].imshow(np.full((100,100), 0.9), cmap='inferno', vmin=0, vmax=1, alpha=0.1*i)\n", | |
| " ax[i].set_title(f\"$\\\\alpha=${0.1*i:.1f}\")\n", | |
| "plt.tight_layout()\n", | |
| "plt.savefig('test.png')\n", | |
| "plt.savefig('test.pdf')" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| } | |
| ], | |
| "metadata": { | |
| "kernelspec": { | |
| "display_name": "Python 3", | |
| "language": "python", | |
| "name": "python3" | |
| }, | |
| "language_info": { | |
| "codemirror_mode": { | |
| "name": "ipython", | |
| "version": 3 | |
| }, | |
| "file_extension": ".py", | |
| "mimetype": "text/x-python", | |
| "name": "python", | |
| "nbconvert_exporter": "python", | |
| "pygments_lexer": "ipython3", | |
| "version": "3.7.3" | |
| } | |
| }, | |
| "nbformat": 4, | |
| "nbformat_minor": 4 | |
| } |
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| numpy | |
| matplotlib |
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