Effective Pandas by Tom Augspurger

Author:Tom Augspurger
Language: eng
Format: epub
Published: 2016-07-06T23:04:34+00:00

The second implementation uses NumPy. Aside from numpy having a builtin deg2rad convenience function (which is probably a bit slower than multiplying by a constant $rac{\pi}{180}$), basically all we’ve done is swap the math prefix for np. Thanks to NumPy’s broadcasting, we can write code that works on scalars or arrays of conformable shape.

def gcd_vec(lat1, lng1, lat2, lng2): ''' Calculate great circle distance. http://www.johndcook.com/blog/python_longitude_latitude/ Parameters ---------- lat1, lng1, lat2, lng2: float or array of float Returns ------- distance: distance from ``(lat1, lng1)`` to ``(lat2, lng2)`` in kilometers. ''' # python2 users will have to use ascii identifiers ϕ1 = np.deg2rad(90 - lat1) ϕ2 = np.deg2rad(90 - lat2) θ1 = np.deg2rad(lng1) θ2 = np.deg2rad(lng2) cos = (np.sin(ϕ1) * np.sin(ϕ2) * np.cos(θ1 - θ2) + np.cos(ϕ1) * np.cos(ϕ2)) arc = np.arccos(cos) return arc * 6373

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