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c0742fe83d
If a polygon is smaller than the largest polygon in our dataset of simplified polygons then we’re only throwing away useful detail by simplifying it. We should still simplify larger polygons as a fallback, to avoid sending anything to the CBC that we’re not sure it will like. The thresholds here are low: we can raise them as we test and experiment more. Here’s some data about the Flood Warning Service polygons Percentile | 80% | 90% | 95% | 98% | 99% | 99.9% -----------|-----|-------|--------|---------|---------|--------- Point count| 226 | 401.9 | 640.45 | 1015.38 | 1389.07 | 3008.609 Percentile | 80% | 90% | 95% | 98% | 99% | 99.9% --------------|-----|-------|--------|---------|---------|--------- Polygon count |2----|3------|5-------|8--------|10-------|40.469
34 lines
1004 B
Python
34 lines
1004 B
Python
from bs4 import BeautifulSoup
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def cap_xml_to_dict(cap_xml):
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# This function assumes that it’s being passed valid CAP XML
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cap = BeautifulSoup(cap_xml, "xml")
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return {
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"msgType": cap.alert.msgType.text,
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"reference": cap.alert.identifier.text,
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"cap_event": cap.alert.info.event.text,
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"category": cap.alert.info.category.text,
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"expires": cap.alert.info.expires.text,
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"content": cap.alert.info.description.text,
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"areas": [
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{
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"name": area.areaDesc.text,
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"polygons": [
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cap_xml_polygon_to_list(polygon.text)
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for polygon in area.find_all('polygon')
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]
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}
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for area in cap.alert.info.find_all('area')
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]
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}
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def cap_xml_polygon_to_list(polygon_string):
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return [
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[
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float(coordinate) for coordinate in pair.split(',')
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]
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for pair in polygon_string.strip().split(' ')
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]
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