tutorials/shpToBitmap.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "68201c99-b741-4581-a479-aaba302f934a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas as gpd\n",
    "from shapely.geometry import mapping\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "46a34bc6-9bd9-41ea-928d-35c4dfc54616",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "module_path = os.path.abspath(os.path.join('../'))\n",
    "if module_path not in sys.path:\n",
    "    sys.path.append(module_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c90e46b1-4563-4167-afe3-d6c13af9afdb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: >"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "shp_data = gpd.read_file(r\"shpToBitmapDemo.geojson\")\n",
    "shp_data.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6f99ee09-15cf-4d68-b6f3-19f20817e8cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_geometry = list()\n",
    "\n",
    "for geometry in list(mapping(shp_data[\"geometry\"])[\"features\"]):\n",
    "    feature_geometry.append(geometry[\"geometry\"])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "328918c6-116e-4d8c-94e0-fda364a97f4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAaEAAAGgCAYAAAAD9NhnAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjYuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/P9b71AAAACXBIWXMAAA9hAAAPYQGoP6dpAAAYOElEQVR4nO3df2zV1f3H8delFy4tu72bEO7ljgKXpN+gVANrkaw0tolSM8miXxKn/BCM/8AKyrWJQIebjIx7gWWEKAMHWQgL6yDLWGSLi+380Ui6ja6uysoCW+ygEW86N9JbB2uFnu8fjM/XaxG50Prupc9H8km4n3vuvadHwtNz74eLzznnBACAgVHWEwAAjFxECABghggBAMwQIQCAGSIEADBDhAAAZogQAMAMEQIAmCFCAAAzRAgAYGbIIrRr1y7FYjGNHTtWpaWlevPNN4fqpQAAOco/FE966NAhxeNx7dq1S/PmzdOPfvQjfe1rX9OJEyc0ZcqUaz62v79fZ8+eVTAYlM/nG4rpAQCGkHNOPT09ikajGjXqM/Y6bgjcfffdbuXKlRnnZsyY4davX/+Zj+3s7HSSODg4ODhy/Ojs7PzMP/MHfSfU19en1tZWrV+/PuN8dXW1mpubB4zv7e1Vb2+vd9v990u9K/SA/Bo92NMDkMN+eeq49RRuyv/+z53WU/hcXNRHOqqXFQwGP3PsoEfogw8+0KVLlxQOhzPOh8NhpVKpAeOTyaS++93vXmVio+X3ESEA/68wmNvXUo2YP9Mu7yWu6yOVIflM6Gov7py76oTq6upUW1vr3U6n0yoqKhqqaQEYAq+cbbOeAnLUoEdowoQJysvLG7Dr6erqGrA7kqRAIKBAIDDY0wAA5IBB39uOGTNGpaWlamxszDjf2Nio8vLywX45AEAOG5K342pra/XYY4+prKxMX/3qV7Vnzx6dOXNGK1euHIqXAwDkqCGJ0COPPKJ//vOf2rRpk95//32VlJTo5Zdf1tSpU4fi5QAAOWrILkyoqalRTU3NUD09AOAWkNvXOwIAchoRAgCYIUIAADNECABghggBAMwQIQCAGSIEADBDhAAAZogQAMAMEQIAmCFCAAAzRAgAYIYIAQDMECEAgBkiBAAwQ4QAAGaG7B+1AwBkeuVsm/fr+6OzzOYxnLATAgCYIUIAADNECABghggBAMwQIQCAGSIEADBDhAAAZogQAMAMEQIAmCFCAAAzfG0PgJv28a+g+fhX0wCfhZ0QAMAMEQIAmCFCAAAzRAgAYIYIAQDMECEAgBkiBAAwQ4QAAGaIEADADBECAJghQgAAM0QIAGCGCAEAzBAhAIAZIgQAMEOEAABmiBAAwAwRAgCYIUIAADNECABghggBAMz4rScAALns/ugs6ynkNHZCAAAzRAgAYIYIAQDM8JkQgJzEZzG3BnZCAAAzRAgAYIYIAQDM8JkQgEHFZzXIBjshAIAZIgQAMEOEAABmiBAAwAwRAgCYySpCyWRSc+bMUTAY1MSJE/XQQw/p5MmTGWOcc9q4caOi0ajy8/NVVVWl9vb2QZ00AODWkFWEmpqatGrVKv3+979XY2OjLl68qOrqav373//2xmzbtk3bt2/Xzp071dLSokgkovnz56unp2fQJw8AyG0+55y70Qf/4x//0MSJE9XU1KR77rlHzjlFo1HF43GtW7dOktTb26twOKytW7dqxYoVA56jt7dXvb293u10Oq2ioiJV6UH5faNvdGoAACMX3Ud6Qy+pu7tbhYWF1xx7U58JdXd3S5Juu+02SVJHR4dSqZSqq6u9MYFAQJWVlWpubr7qcySTSYVCIe8oKiq6mSkBAHLIDUfIOafa2lpVVFSopKREkpRKpSRJ4XA4Y2w4HPbu+6S6ujp1d3d7R2dn541OCQCQY274a3tWr16td955R0ePHh1wn8/ny7jtnBtw7opAIKBAIHCj0wAA5LAb2gk9+eSTOnLkiF5//XVNnjzZOx+JRCRpwK6nq6trwO4IAICsIuSc0+rVq3X48GG99tprisViGffHYjFFIhE1NjZ65/r6+tTU1KTy8vLBmTEA4JaR1dtxq1atUn19vV566SUFg0FvxxMKhZSfny+fz6d4PK5EIqHi4mIVFxcrkUiooKBAixcvHpIfAACQu7KK0O7duyVJVVVVGef37dunxx9/XJK0du1aXbhwQTU1NTp37pzmzp2rhoYGBYPBQZkwAODWcVN/T2gopNNphUIh/p4QAOSoz+3vCQEAcDOIEADADBECAJghQgAAM0QIAGCGCAEAzBAhAIAZIgQAMEOEAABmiBAAwAwRAgCYIUIAADNECABghggBAMwQIQCAGSIEADBDhAAAZogQAMAMEQIAmCFCAAAzRAgAYIYIAQDMECEAgBkiBAAwQ4QAAGaIEADADBECAJghQgAAM0QIAGCGCAEAzBAhAIAZIgQAMEOEAABmiBAAwAwRAgCYIUIAADNECABghggBAMwQIQCAGSIEADBDhAAAZogQAMAMEQIAmCFCAAAzRAgAYIYIAQDMECEAgBkiBAAwQ4QAAGaIEADADBECAJghQgAAM0QIAGCGCAEAzBAhAIAZIgQAMEOEAABmiBAAwAwRAgCYIUIAADNECABghggBAMwQIQCAmZuKUDKZlM/nUzwe984557Rx40ZFo1Hl5+erqqpK7e3tNztPAMAt6IYj1NLSoj179uiuu+7KOL9t2zZt375dO3fuVEtLiyKRiObPn6+enp6bniwA4NZyQxH68MMPtWTJEu3du1df+tKXvPPOOe3YsUMbNmzQwoULVVJSov379+v8+fOqr6+/6nP19vYqnU5nHACAkeGGIrRq1SotWLBA9913X8b5jo4OpVIpVVdXe+cCgYAqKyvV3Nx81edKJpMKhULeUVRUdCNTAgDkoKwjdPDgQb311ltKJpMD7kulUpKkcDiccT4cDnv3fVJdXZ26u7u9o7OzM9spAQBylD+bwZ2dnVqzZo0aGho0duzYTx3n8/kybjvnBpy7IhAIKBAIZDMNAMAtIqudUGtrq7q6ulRaWiq/3y+/36+mpiY9//zz8vv93g7ok7uerq6uAbsjAACyitC9996r48ePq62tzTvKysq0ZMkStbW1afr06YpEImpsbPQe09fXp6amJpWXlw/65AEAuS2rt+OCwaBKSkoyzo0bN07jx4/3zsfjcSUSCRUXF6u4uFiJREIFBQVavHjx4M0aAHBLyCpC12Pt2rW6cOGCampqdO7cOc2dO1cNDQ0KBoOD/VIAgBznc84560l8XDqdVigUUpUelN832no6AIAsXXQf6Q29pO7ubhUWFl5zLN8dBwAwQ4QAAGaIEADADBECAJghQgAAM0QIAGCGCAEAzBAhAIAZIgQAMEOEAABmiBAAwAwRAgCYIUIAADNECABghggBAMwQIQCAGSIEADBDhAAAZogQAMAMEQIAmCFCAAAzRAgAYIYIAQDMECEAgBkiBAAwQ4QAAGaIEADADBECAJghQgAAM0QIAGCGCAEAzBAhAIAZIgQAMEOEAABmiBAAwAwRAgCYIUIAADNECABghggBAMwQIQCAGSIEADBDhAAAZogQAMAMEQIAmCFCAAAzRAgAYIYIAQDMECEAgBkiBAAwQ4QAAGaIEADADBECAJghQgAAM0QIAGCGCAEAzBAhAIAZIgQAMEOEAABmiBAAwAwRAgCYIUIAADNECABghggBAMxkHaH33ntPS5cu1fjx41VQUKBZs2aptbXVu985p40bNyoajSo/P19VVVVqb28f1EkDAG4NWUXo3LlzmjdvnkaPHq3f/OY3OnHihH7wgx/oi1/8ojdm27Zt2r59u3bu3KmWlhZFIhHNnz9fPT09gz13AECO82czeOvWrSoqKtK+ffu8c9OmTfN+7ZzTjh07tGHDBi1cuFCStH//foXDYdXX12vFihUDnrO3t1e9vb3e7XQ6ne3PAADIUVnthI4cOaKysjI9/PDDmjhxombPnq29e/d693d0dCiVSqm6uto7FwgEVFlZqebm5qs+ZzKZVCgU8o6ioqIb/FEAALkmqwi9++672r17t4qLi/XKK69o5cqVeuqpp/STn/xEkpRKpSRJ4XA443HhcNi775Pq6urU3d3tHZ2dnTfycwAAclBWb8f19/errKxMiURCkjR79my1t7dr9+7dWrZsmTfO5/NlPM45N+DcFYFAQIFAINt5AwBuAVnthCZNmqQ77rgj49ztt9+uM2fOSJIikYgkDdj1dHV1DdgdAQCQVYTmzZunkydPZpw7deqUpk6dKkmKxWKKRCJqbGz07u/r61NTU5PKy8sHYboAgFtJVm/HPf300yovL1cikdA3vvENHTt2THv27NGePXskXX4bLh6PK5FIqLi4WMXFxUokEiooKNDixYuH5AcAAOSurCI0Z84c/fKXv1RdXZ02bdqkWCymHTt2aMmSJd6YtWvX6sKFC6qpqdG5c+c0d+5cNTQ0KBgMDvrkAQC5zeecc9aT+Lh0Oq1QKKQqPSi/b7T1dAAAWbroPtIbeknd3d0qLCy85li+Ow4AYIYIAQDMECEAgBkiBAAwQ4QAAGayukQbwMjxytm2z/0174/O+txfE7bYCQEAzBAhAIAZ3o4DhhmLt8EAK+yEAABmiBAAwAwRAgCY4TMhAMPGJz8P45LtWx87IQCAGSIEADBDhAAAZogQAMAMEQIAmCFCAAAzRAgAYIYIAQDMECEAgBkiBAAwQ4QAAGaIEADADBECAJghQgAAM0QIAGCGCAEAzBAhAIAZIgQAMEOEAABmiBAAwAwRAgCYIUIAADNECABghggBAMwQIQCAGSIEADBDhAAAZogQAMAMEQIAmCFCAAAzRAgAYIYIAQDM+K0nAODWdn90lvUUMIyxEwIAmCFCAAAzRAgAYIbPhIARhM9nMNywEwIAmCFCAAAzRAgAYIbPhIBhhs9tMJKwEwIAmCFCAAAzRAgAYIYIAQDMECEAgBkiBAAwQ4QAAGaIEADADBECAJjJKkIXL17Us88+q1gspvz8fE2fPl2bNm1Sf3+/N8Y5p40bNyoajSo/P19VVVVqb28f9IkDAHJfVhHaunWrXnzxRe3cuVN/+ctftG3bNn3/+9/XCy+84I3Ztm2btm/frp07d6qlpUWRSETz589XT0/PoE8eAJDbsvruuN/97nd68MEHtWDBAknStGnT9LOf/Ux//OMfJV3eBe3YsUMbNmzQwoULJUn79+9XOBxWfX29VqxYMeA5e3t71dvb691Op9M3/MMAAHJLVjuhiooKvfrqqzp16pQk6e2339bRo0f1wAMPSJI6OjqUSqVUXV3tPSYQCKiyslLNzc1Xfc5kMqlQKOQdRUVFN/qzAAByTFY7oXXr1qm7u1szZsxQXl6eLl26pM2bN2vRokWSpFQqJUkKh8MZjwuHwzp9+vRVn7Ourk61tbXe7XQ6TYgAYITIKkKHDh3SgQMHVF9fr5kzZ6qtrU3xeFzRaFTLly/3xvl8vozHOecGnLsiEAgoEAjcwNQBALkuqwg988wzWr9+vR599FFJ0p133qnTp08rmUxq+fLlikQiki7viCZNmuQ9rqura8DuCACArD4TOn/+vEaNynxIXl6ed4l2LBZTJBJRY2Ojd39fX5+amppUXl4+CNMFANxKstoJff3rX9fmzZs1ZcoUzZw5U3/605+0fft2PfHEE5Iuvw0Xj8eVSCRUXFys4uJiJRIJFRQUaPHixUPyAwAAcldWEXrhhRf07W9/WzU1Nerq6lI0GtWKFSv0ne98xxuzdu1aXbhwQTU1NTp37pzmzp2rhoYGBYPBQZ88ACC3+ZxzznoSH5dOpxUKhVSlB+X3jbaeDgAgSxfdR3pDL6m7u1uFhYXXHMt3xwEAzBAhAIAZIgQAMEOEAABmiBAAwAwRAgCYIUIAADNECABghggBAMwQIQCAGSIEADBDhAAAZogQAMAMEQIAmCFCAAAzRAgAYIYIAQDMECEAgBkiBAAwQ4QAAGaIEADADBECAJghQgAAM0QIAGCGCAEAzBAhAIAZIgQAMEOEAABmiBAAwAwRAgCYIUIAADNECABghggBAMwQIQCAGSIEADBDhAAAZogQAMAMEQIAmCFCAAAzRAgAYIYIAQDMECEAgBkiBAAwQ4QAAGaIEADADBECAJghQgAAM0QIAGCGCAEAzBAhAIAZIgQAMEOEAABmiBAAwAwRAgCYIUIAADNECABghggBAMwQIQCAGSIEADBDhAAAZogQAMAMEQIAmCFCAAAzfusJfJJzTpJ0UR9JzngyAICsXdRHkv7/z/NrGXYR6unpkSQd1cvGMwEA3Iyenh6FQqFrjvG560nV56i/v19nz56Vc05TpkxRZ2enCgsLrac1bKXTaRUVFbFOn4F1uj6s0/Vhna7NOaeenh5Fo1GNGnXtT32G3U5o1KhRmjx5stLptCSpsLCQ/8jXgXW6PqzT9WGdrg/r9Ok+awd0BRcmAADMECEAgJlhG6FAIKDnnntOgUDAeirDGut0fVin68M6XR/WafAMuwsTAAAjx7DdCQEAbn1ECABghggBAMwQIQCAGSIEADAzbCO0a9cuxWIxjR07VqWlpXrzzTetp2QmmUxqzpw5CgaDmjhxoh566CGdPHkyY4xzThs3blQ0GlV+fr6qqqrU3t5uNOPhIZlMyufzKR6Pe+dYp8vee+89LV26VOPHj1dBQYFmzZql1tZW737WSbp48aKeffZZxWIx5efna/r06dq0aZP6+/u9MazTIHDD0MGDB93o0aPd3r173YkTJ9yaNWvcuHHj3OnTp62nZuL+++93+/btc3/+859dW1ubW7BggZsyZYr78MMPvTFbtmxxwWDQ/eIXv3DHjx93jzzyiJs0aZJLp9OGM7dz7NgxN23aNHfXXXe5NWvWeOdZJ+f+9a9/ualTp7rHH3/c/eEPf3AdHR3ut7/9rfvb3/7mjWGdnPve977nxo8f737961+7jo4O9/Of/9x94QtfcDt27PDGsE43b1hG6O6773YrV67MODdjxgy3fv16oxkNL11dXU6Sa2pqcs4519/f7yKRiNuyZYs35j//+Y8LhULuxRdftJqmmZ6eHldcXOwaGxtdZWWlFyHW6bJ169a5ioqKT72fdbpswYIF7oknnsg4t3DhQrd06VLnHOs0WIbd23F9fX1qbW1VdXV1xvnq6mo1NzcbzWp46e7uliTddtttkqSOjg6lUqmMNQsEAqqsrByRa7Zq1SotWLBA9913X8Z51umyI0eOqKysTA8//LAmTpyo2bNna+/evd79rNNlFRUVevXVV3Xq1ClJ0ttvv62jR4/qgQcekMQ6DZZh9y3aH3zwgS5duqRwOJxxPhwOK5VKGc1q+HDOqba2VhUVFSopKZEkb12utmanT5/+3Odo6eDBg3rrrbfU0tIy4D7W6bJ3331Xu3fvVm1trb71rW/p2LFjeuqppxQIBLRs2TLW6b/WrVun7u5uzZgxQ3l5ebp06ZI2b96sRYsWSeL302AZdhG6wufzZdx2zg04NxKtXr1a77zzjo4ePTrgvpG+Zp2dnVqzZo0aGho0duzYTx030tepv79fZWVlSiQSkqTZs2ervb1du3fv1rJly7xxI32dDh06pAMHDqi+vl4zZ85UW1ub4vG4otGoli9f7o0b6et0s4bd23ETJkxQXl7egF1PV1fXgP/jGGmefPJJHTlyRK+//romT57snY9EIpI04testbVVXV1dKi0tld/vl9/vV1NTk55//nn5/X5vLUb6Ok2aNEl33HFHxrnbb79dZ86ckcTvpyueeeYZrV+/Xo8++qjuvPNOPfbYY3r66aeVTCYlsU6DZdhFaMyYMSotLVVjY2PG+cbGRpWXlxvNypZzTqtXr9bhw4f12muvKRaLZdwfi8UUiUQy1qyvr09NTU0jas3uvfdeHT9+XG1tbd5RVlamJUuWqK2tTdOnT2edJM2bN2/AJf6nTp3S1KlTJfH76Yrz588P+FdB8/LyvEu0WadBYnhRxKe6con2j3/8Y3fixAkXj8fduHHj3N///nfrqZn45je/6UKhkHvjjTfc+++/7x3nz5/3xmzZssWFQiF3+PBhd/z4cbdo0SIuFXUu4+o451gn5y5fvu73+93mzZvdX//6V/fTn/7UFRQUuAMHDnhjWCfnli9f7r785S97l2gfPnzYTZgwwa1du9YbwzrdvGEZIeec++EPf+imTp3qxowZ477yla94lyOPRJKueuzbt88b09/f75577jkXiURcIBBw99xzjzt+/LjdpIeJT0aIdbrsV7/6lSspKXGBQMDNmDHD7dmzJ+N+1sm5dDrt1qxZ46ZMmeLGjh3rpk+f7jZs2OB6e3u9MazTzePfEwIAmBl2nwkBAEYOIgQAMEOEAABmiBAAwAwRAgCYIUIAADNECABghggBAMwQIQCAGSIEADBDhAAAZv4Pa7BSC52MQD8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from gtkit.imgops import bitmap_gen, geowrite\n",
    "for i, bmap in enumerate(bitmap_gen(shp_data.total_bounds, output_image_size=(100, 100), pixel_resolution=(1, 1), geometry_collection=feature_geometry)):\n",
    "    # geowrite(rf\"{i}.tiff\", bmap.array, bmap.transform)\n",
    "    plt.figure()\n",
    "    plt.imshow(bmap.array)\n",
    "    plt.show()\n"
   ]
  }
 ],
 "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": "3.8.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}