82 lines
3.4 KiB
Python
82 lines
3.4 KiB
Python
"""The steps a country's geo import may share with another's."""
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import argparse
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import collections
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import math
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import sys
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from pathlib import Path
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DATA = Path(__file__).resolve().parent.parent / "data" / "geo"
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CACHE = Path(__file__).resolve().parent / "cache"
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def parser(doc, country, **own):
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"""A parser for the options every country's import takes, plus the script's own: each keyword names one option, with
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"_" standing for "-"."""
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options = {"cache": {"default": str(CACHE)}, "out": {"default": str(DATA / country)}, "streets_per_locality": {"type": int, "default": 10}, **own}
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p = argparse.ArgumentParser(description=doc.splitlines()[0])
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for name in sorted(options):
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p.add_argument("--" + name.replace("_", "-"), **options[name])
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return p
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def directories(args):
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"""The cache and out directories of the parsed options, both created."""
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cache, out = Path(args.cache), Path(args.out)
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cache.mkdir(parents=True, exist_ok=True)
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out.mkdir(parents=True, exist_ok=True)
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return cache, out
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def centroid(rows):
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"""The mean lat and lon of the rows with a point, or None where no row has one."""
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points = [r for r in rows if r["lat"] is not None]
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if not points:
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return None
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return sum(r["lat"] for r in points) / len(points), sum(r["lon"] for r in points) / len(points)
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class Nearest:
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"""Nearest point by an equirectangular distance, over a degree grid."""
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def __init__(self, points, cell=0.05):
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self.cell = cell
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self.grid = collections.defaultdict(list)
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for lat, lon, value in points:
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self.grid[(int(lat // cell), int(lon // cell))].append((lat, lon, value))
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def find(self, lat, lon):
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ci, cj = int(lat // self.cell), int(lon // self.cell)
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best, best_d = None, math.inf
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ring = 0
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while ring < 400:
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for i in range(ci - ring, ci + ring + 1):
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for j in range(cj - ring, cj + ring + 1):
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if max(abs(i - ci), abs(j - cj)) != ring:
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continue
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for plat, plon, value in self.grid.get((i, j), ()):
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d = (plat - lat) ** 2 + ((plon - lon) * math.cos(math.radians(lat))) ** 2
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if d < best_d:
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best, best_d = value, d
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if best is not None and math.sqrt(best_d) < ring * self.cell * math.cos(math.radians(lat)):
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return best
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ring += 1
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return best
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def top_streets(count, per_locality, column):
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"""count maps (locality, street name) to a count. Returns, per locality, rows for the per_locality names counted
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most, ties broken by name; each row holds its count under column."""
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of = collections.defaultdict(list)
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for (locality, name), n in count.items():
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of[locality].append((n, name))
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return {locality: [{"name": name, "locality": locality, column: n} for n, name in sorted(named, key=lambda s: (-s[0], s[1]))[:per_locality]] for locality, named in of.items()}
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def with_streets(places, named):
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"""The places that named holds streets for; logs each other place as dropped."""
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for key, place in places.items():
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if key not in named:
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label = key if key == place["name"] else f"{key} {place['name']}"
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print(f"{label}: no streets, dropped", file=sys.stderr)
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return {key: place for key, place in places.items() if key in named}
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