100 lines
22 KiB
Plaintext
100 lines
22 KiB
Plaintext
|
{
|
||
|
|
"cells": [
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"\n",
|
||
|
|
"# GridSpec\n",
|
||
|
|
"\n",
|
||
|
|
"An example demoing gridspec\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 1,
|
||
|
|
"metadata": {
|
||
|
|
"collapsed": false,
|
||
|
|
"jupyter": {
|
||
|
|
"outputs_hidden": false
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAk4AAAGGCAYAAACNCg6xAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjYsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvq6yFwwAAAAlwSFlzAAAPYQAAD2EBqD+naQAAOpZJREFUeJzt3flvlNdi//HPeN8dHEPA9hhiY2NsYwIkBMgCqUwCCSIEEpE06W1FJVCbqrpVlV8q9U+oEik/5KYliUq+t1UWTAJOAoE0QLjWDTLGjsGYsHm84n0ZL+NlZr4/jObRGG/H4CWe+35JSPPMnOd5zlg8M5855zzn2Lxer1cAAACYUsh8VwAAAGChIDgBAAAYIjgBAAAYIjgBAAAYIjgBAAAYIjgBAAAYIjgBAAAYIjgBAAAYCjMp5PF41NjYqPj4eNlsttmuEwAAwJzxer1yOp1KSUlRSMjkbUpGwamxsVF2u31GKgcAAPBbVFdXp7S0tEnLGAWn+Ph464AJCQkPXjMAAIDfiJ6eHtntdivvTMYoOPm75xISEghOAAAgKJkMR2JwOAAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgCGCEwAAgKGw+a4AgNnz5Zdf6sqVK9b2Cy+8oM2bN89jjRY+j8ej1tZWNTQ0qLGxUY2NjWpubpbb7ZYkrVixQn/3d383v5UEMGsITkCQcrlcqq6uHvVceXk5wekBVFdX6+jRoxoeHp7vqgCYJ3TVAUHq6tWrGhkZGfVcc3Oz7t69O081WvhcLhehCfgLR4sTEKQqKiqsx2FhYVaIKi8v144dO+arWkEhLi5OKSkpSk1NVUpKim7duqU///nP810tAHOA4AQEoY6ODtXW1kqSbDabtm/fru+++06SVFlZqeeff14hITQ4T9fKlSv1L//yL0pMTBz1fENDwzzVCMBc45MTCEKBrU0rVqzQ448/rujoaElSX1+fbty4MV9VW9Di4uLGhCYAf1locQKCjNfrHRWc1q5dq9DQUOXl5am0tFSSL1itWrVq0uNcvXpVX3zxhSQpJCREBw4cUFpa2oTlR0ZGdPjwYWsMVU5Ojl5//fUJy9++fVtVVVVyOBzq7e3V0NCQYmJitGTJEq1atUrr1q1TeHj4lO+3u7tbly9f1p07d9TW1iaXy6XQ0FDFxMQoNjZWixcvVmZmpjIzMxUTEzPl8QBgMgQnIMg4HA51dXVJksLDw7V69WpJvgDlD07Xr1/XwMCA1Qo1nry8PN28eVOXL1+Wx+NRUVGRDh06pMjIyHHLnzlzxgpN8fHx2r1797jluru7dezYMdXU1Ix5zel0yul06tatW/rpp5/06quvavny5RPWsbS0VKdOnRozYNvtdmtoaEhdXV1qaGhQeXm50tPTdeDAgQmPBQAm6KoDgkx5ebn1OCcnxwo6drtdSUlJknzBInB+p4ns3LlTDz/8sCTfuCn/OKl73bx5Uz///LMk35iqPXv2jNu609raqsOHD1uhyWazadmyZSooKNCGDRuUnZ1t1dfpdOrTTz/VnTt3xj1ndXW1iouLrdAUGRmplStXav369Xr88ceVn5+vZcuWKTQ0dMr3CQCmaHECgsjw8LCuXbtmbRcUFIx6vaCgQGfPnpXk66574oknJj1eRESE9u3bp48++khut1vl5eXKyspSXl6eVaavr09fffWVvF6vJGnTpk3KzMwct26ff/65nE6nJCkjI0MvvfSSFcz8BgcHdfr0aZWWlmpkZERFRUV6++23FRUVNaqc/31I0saNG7V9+/Zxu/aGhoZ048YNNTU1TfpeAcAELU5AELl27ZoGBwclSbGxsWMCzNq1a63H9fX1amtrm/KYKSkpeu6556ztEydOqLu729r++uuv1dvbK0launSpCgsLxz1OSUmJWltbJfnuTnvrrbfGhCbJ13K0a9cuq65Op9PqYvQbGhqyugUTExO1c+fOCcdDRUREKC8vb8J6AcB0EJyAIBLYTbdmzZoxUw4sWrRI6enp1nbgIPLJPPXUU3r00Ucl+SaBLCoqktfr1cWLF/Xrr79K8o2n2rdv37hdY263WxcvXpTk657btWvXlNMhFBYWymazSfJNoRDIHw4lKTo62ioHALON4AQEiZ6enlHjge7tphvv+YqKCquLbTI2m02vvPKKNZjc4XDo+PHj+v77760yzz//vBYvXjzu/o2Njerr65PkG2v10EMPTXnO+Ph4JScnS5JaWlrkcrms12JiYqwWppaWFjkcjimPBwAzgTFOQJAIDEHJyclKSUkZt1xeXp5OnjypkZERK2xlZGRMefyEhATt3r1bn332mSTp8uXL1murVq2adLxUfX299bi/v1/ffvut0XvyhyWv16uenh5rnFNoaKhycnJUWVkpj8ejI0eOKDc3V7m5uVq+fDnTDgCYNQQnIEjcO3fTRKKjo5Wdna2qqipJvu49k+AkSatXr9b69etVVlZmPRcXFzfh1AN+/gHhktTW1mY0tupegS1OkrRjxw41NTWpra1NbrdblZWVqqyslM1mU3JystLT05WZmans7GyFhfFRB2Bm8GkCBIHAgd42m01r1qyZtHxBQYEVnPwDyiean+lecXFxo7bT09MVGxs76T73hp774fF4Rm3Hxsbq4MGDKikp0aVLl6xw5vV61draqtbWVl26dEnR0dF66qmntGXLFpaZAfDACE5AEAhsbfJ6vXrvvfeM9x0eHlZVVZXWrVs3ZVmHw6ELFy6Meq6qqkpXrlxRfn7+hPtFRERYjzdt2jRjiwxHRERo27Zt2rp1q5qamuRwOORwOFRbW6v+/n5J0sDAgM6cOaP6+nrt37+fgeQAHgjBCVjgTCeznExFRcWUwcnlcunYsWNWy09ycrLVylVcXCy73T7hOm6BLVIdHR0PVNfx2Gw2paSkKCUlRZs3b5bX61VdXZ1KSkpUXV0tyTdh5rVr15Sbmzvj5wfwl4N2a2CB8y+fIvkGTaelpRn9Cxw8HrhMy0S++eYbq8ySJUt06NAhazkUf6ia6A69wDXuampqNDIy8gDveGo2m03p6enav3+/Vq5caT1//fr1WT0vgOBHixOwwAV202VnZ2v//v3G+77//vtqb2+3FgbeunXrhOfwz6UUFhamffv2KTw8XHv37tUHH3wgl8ulmpoaXbhwQc8888yY/e12u6KiouRyuTQ0NKSysjJt3Lhxmu90+mw2m7KysnTz5k1JsibqBID7RYsTsID19fXpxo0b1vZUg8LvFVh+oskwOzs7R00fUFhYqEceeUSSb9buXbt2Wa+dPXtWjY2NY44RFhamTZs2Wds//PCDmpubjet5b+AZHByU2+022jdwlvOpBrEDwFQITsAC5p/HSPItVZKdnT2t/QMnw+zo6FBtbe2o1z0ej4qKiqyZujMzM/Xkk0+OKpOfn29Nf+B2u3X06FENDQ2NOdeWLVu0ZMkSSb7g8/HHH+vSpUsTBqD+/n6VlZXpww8/VElJyajXmpqa9O677+rHH39US0vLuPt7PB798ssv1ozlkpSVlTVuWQAwRVcdsIAFLrGSm5s77fmKkpKSlJqaqoaGBkm+VqfAJVnOnz+vuro6Sb7Zuvfs2TPuXWkvvviiamtr1dnZqfb2dp08eXLM3E4RERF64403dOTIEXV2dmpwcFAnTpzQ6dOnlZaWpoSEBEm+u+D8cz35x0z5l3sJ1Nvbq3PnzuncuXOKi4vT0qVLFRcXp5CQEPX29qqpqWnU/FHLly+f9M4/U3/84x9HHddfF7/Gxkb94Q9/GLPfm2++qfj4+Ac+P4D5RXACFqjm5mZroVtp+t10fgU
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 600x400 with 5 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"import matplotlib.pyplot as plt\n",
|
||
|
|
"from matplotlib import gridspec\n",
|
||
|
|
"\n",
|
||
|
|
"plt.figure(figsize=(6, 4))\n",
|
||
|
|
"G = gridspec.GridSpec(3, 3)\n",
|
||
|
|
"\n",
|
||
|
|
"axes_1 = plt.subplot(G[0, :])\n",
|
||
|
|
"plt.xticks([])\n",
|
||
|
|
"plt.yticks([])\n",
|
||
|
|
"plt.text(0.5, 0.5, \"Axes 1\", ha=\"center\", va=\"center\", size=24, alpha=0.5)\n",
|
||
|
|
"\n",
|
||
|
|
"axes_2 = plt.subplot(G[1, :-1])\n",
|
||
|
|
"plt.xticks([])\n",
|
||
|
|
"plt.yticks([])\n",
|
||
|
|
"plt.text(0.5, 0.5, \"Axes 2\", ha=\"center\", va=\"center\", size=24, alpha=0.5)\n",
|
||
|
|
"\n",
|
||
|
|
"axes_3 = plt.subplot(G[1:, -1])\n",
|
||
|
|
"plt.xticks([])\n",
|
||
|
|
"plt.yticks([])\n",
|
||
|
|
"plt.text(0.5, 0.5, \"Axes 3\", ha=\"center\", va=\"center\", size=24, alpha=0.5)\n",
|
||
|
|
"\n",
|
||
|
|
"axes_4 = plt.subplot(G[-1, 0])\n",
|
||
|
|
"plt.xticks([])\n",
|
||
|
|
"plt.yticks([])\n",
|
||
|
|
"plt.text(0.5, 0.5, \"Axes 4\", ha=\"center\", va=\"center\", size=24, alpha=0.5)\n",
|
||
|
|
"\n",
|
||
|
|
"axes_5 = plt.subplot(G[-1, -2])\n",
|
||
|
|
"plt.xticks([])\n",
|
||
|
|
"plt.yticks([])\n",
|
||
|
|
"plt.text(0.5, 0.5, \"Axes 5\", ha=\"center\", va=\"center\", size=24, alpha=0.5)\n",
|
||
|
|
"\n",
|
||
|
|
"plt.tight_layout()\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"kernelspec": {
|
||
|
|
"display_name": "Python 3 (ipykernel)",
|
||
|
|
"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": "3.12.11"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 4
|
||
|
|
}
|