74 lines
1.8 KiB
Python
74 lines
1.8 KiB
Python
import math
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import numpy as np
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lbstoN = 4.44822
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def uniqify(seq, idfun=None):
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# order preserving
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if idfun is None:
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def idfun(x): return x
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seen = {}
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result = []
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for item in seq:
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marker = idfun(item)
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# in old Python versions:
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# if seen.has_key(marker)
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# but in new ones:
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if marker in seen: continue
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seen[marker] = 1
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result.append(item)
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return result
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def serialize_list(value,token=','):
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assert(isinstance(value, list) or isinstance(value, tuple) or isinstance(value,np.ndarray))
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return token.join([unicode(s) for s in value])
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def deserialize_list(value,token=','):
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if isinstance(value, list):
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return value
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elif isinstance(value, np.ndarray):
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return value
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return value.split(token)
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def geo_distance(lat1,lon1,lat2,lon2):
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""" Approximate distance and bearing between two points
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defined by lat1,lon1 and lat2,lon2
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This is a slight underestimate but is close enough for our purposes,
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We're never moving more than 10 meters between trackpoints
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Bearing calculation fails if one of the points is a pole.
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(Hey, from the North pole you can walk South, East, North and end up
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on the same spot!)
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"""
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# radius of our earth in km --> should be moved to settings if
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# rowing takes off on other planets
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R = 6373.0
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# pi
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pi = math.pi
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lat1 = math.radians(lat1)
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lat2 = math.radians(lat2)
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lon1 = math.radians(lon1)
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lon2 = math.radians(lon2)
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dlon = lon2 - lon1
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dlat = lat2 - lat1
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a = sin(dlat / 2)**2 + cos(lat1) * cos(lat2) * sin(dlon / 2)**2
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c = 2 * atan2(sqrt(a), sqrt(1 - a))
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distance = R * c
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tc1 = atan2(sin(lon2-lon1)*cos(lat2),
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cos(lat1)*sin(lat2)-sin(lat1)*cos(lat2)*cos(lon2-lon1))
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tc1 = tc1 % (2*pi)
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bearing = math.degrees(tc1)
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return [distance,bearing]
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