sum_location_geometries_acres.ipynb

{
  "metadata": {
    "kernelspec": {
      "name": "python",
      "display_name": "Python (Pyodide)",
      "language": "python"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "python",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.8"
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  "nbformat_minor": 5,
  "nbformat": 4,
  "cells": [
    {
      "id": "e9079dc9-2acf-446d-a9d0-3ba82c1571aa",
      "cell_type": "code",
      "source": "from pyodide.http import pyfetch\nfrom js import location\n\nasync def get_all_entities(base_url):\n    next_page = base_url\n    while next_page is not None:\n        resp = await pyfetch(next_page, method='GET')\n\n        data = await resp.json()\n\n        for entity in data.get('data', []):\n            yield entity\n\n        next_page = data.get('links', {}).get('next', {}).get('href', None)\n\nall_asset_types = [q['attributes']['drupal_internal__id'] async for q in get_all_entities(location.origin + '/api/asset_type/asset_type')]\n\nprint(all_asset_types)\n\nasync def query_all_locations():\n    for asset_type in all_asset_types:\n        async for q in get_all_entities(location.origin + f'/api/asset/{asset_type}?filter[is_location]=1&filter[status]=active'):\n            yield q\n\nall_locations = [q async for q in query_all_locations()]\n\nprint(len(all_locations))",
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": "['animal', 'equipment', 'group', 'land', 'material', 'money', 'plant', 'seed', 'structure', 'water']\n432\n"
        }
      ],
      "execution_count": 70
    },
    {
      "id": "fcebf342-0dd8-47a8-9a58-60458145d8bf",
      "cell_type": "code",
      "source": "import piplite\nawait piplite.install(\"shapely\")",
      "metadata": {
        "trusted": true
      },
      "outputs": [],
      "execution_count": 67
    },
    {
      "id": "159e2035-7199-486c-bd13-a1dced3cb4a4",
      "cell_type": "code",
      "source": "from shapely.wkt import loads as loads_wkt\nfrom functools import partial\nfrom pyproj import Proj, Transformer\nfrom shapely.geometry import Point\nfrom shapely.ops import transform\n\n# Copied from https://racum.blog/articles/projection-shapely/\ndef get_projections(anchor_point=None):\n    if not anchor_point:  # If no anchor, set 0/0 (normal Mercator).\n        anchor_point = Point(0, 0)\n    crs = {\n        'proj': 'omerc',\n        'lat_0': anchor_point.y,\n        'lonc': anchor_point.x,\n        'alpha': 1e-6,\n        'k': 1,\n        'gamma': 0.0,\n        'units': 'm',\n        'ellps': 'WGS84',\n        'no_defs': True,\n    }\n    proj = Proj(crs, preserve_units=True)\n    proj_inverse = Transformer.from_proj(proj, 'EPSG:4326', always_xy=True).transform\n    return partial(transform, proj), partial(transform, proj_inverse)\n\ntotal_area_meters = 0\n\nfor idx, location in enumerate(all_locations):\n    if location.get('attributes')['geometry']:\n        geom = loads_wkt(location.get('attributes')['geometry']['value'])\n        geodesic_to_cartesian, _ = get_projections(geom.centroid)\n        geom_projected = geodesic_to_cartesian(geom)\n        total_area_meters += geom_projected.area\n\nprint(total_area_meters)",
      "metadata": {
        "trusted": true
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": "10843.147495371248\n"
        }
      ],
      "execution_count": 69
    }
  ]
}