{ "cells": [ { "cell_type": "markdown", "source": [ "# Create inscribed circles\n", "\n", "This notebook creates a center and a radius of a maximum inscribed circle of each enclosed tessellation cell. We will need it to generate distance-based weights used to measure contextual characters.\n", "\n", "It requires custom piece of code within pygeos. Therefore, we use a custom docker container based on `docker/Dockerfile`." ], "metadata": {} }, { "cell_type": "code", "execution_count": 9, "source": [ "from dask.distributed import Client, LocalCluster, as_completed\n", "from tqdm.notebook import tqdm\n", "from time import time" ], "outputs": [], "metadata": {} }, { "cell_type": "code", "execution_count": 6, "source": [ "client = Client(LocalCluster())\n", "client" ], "outputs": [ { "output_type": "execute_result", "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "
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" ], "text/plain": [ "" ] }, "metadata": {}, "execution_count": 6 } ], "metadata": {} }, { "cell_type": "markdown", "source": [ "`pygeos.constructive.maximum_inscribed_circle` is custom function implemented in https://github.com/martinfleis/pygeos/tree/circle branch. It is likely that it will, in some form, be part of the future release of pygeos." ], "metadata": {} }, { "cell_type": "code", "execution_count": 10, "source": [ "def _circle(chunk):\n", " import geopandas as gpd\n", " import pygeos\n", " gpd._compat.USE_PYGEOS = True\n", " \n", " s = time()\n", " df = gpd.read_parquet(f'../../urbangrammar_samba/spatial_signatures/tessellation/tess_{chunk}.pq', columns=['hindex', 'tessellation'])\n", " geoms = df.tessellation.values.data\n", " insc = pygeos.constructive.maximum_inscribed_circle(geoms, 0.1)\n", " lenghts = pygeos.length(insc)\n", " points = pygeos.points(pygeos.get_coordinates(insc)[::2])\n", " res = gpd.GeoDataFrame({'hindex': df.hindex, 'radius': lenghts}, geometry=points, crs=27700, index=df.index)\n", " res.to_parquet(f'../../urbangrammar_samba/spatial_signatures/inscribed_circle/circle_{chunk}.pq')\n", " return f\"Chunk {chunk} processed sucessfully in {time() - s} seconds.\"" ], "outputs": [], "metadata": {} }, { "cell_type": "code", "execution_count": 11, "source": [ "%%time\n", "workers=16\n", "inputs = iter(range(103))\n", "futures = [client.submit(_circle, next(inputs)) for i in range(workers)]\n", "ac = as_completed(futures)\n", "for finished_future in ac:\n", " # submit new future \n", " try:\n", " new_future = client.submit(_circle, next(inputs))\n", " ac.add(new_future)\n", " except StopIteration:\n", " pass\n", " print(finished_future.result())" ], "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Chunk 11 processed sucessfully in 75.18252611160278 seconds.\n", "Chunk 3 processed sucessfully in 79.87826347351074 seconds.\n", "Chunk 0 processed sucessfully in 86.3075304031372 seconds.\n", "Chunk 2 processed sucessfully in 89.55268573760986 seconds.\n", "Chunk 10 processed sucessfully in 90.74024438858032 seconds.\n", "Chunk 1 processed sucessfully in 97.34478044509888 seconds.\n", "Chunk 9 processed sucessfully in 100.90103268623352 seconds.\n", "Chunk 15 processed sucessfully in 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