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Created January 7, 2011 19:07
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Some geo functions for Ruby (haversine) and a mixin for spherical search in Mongo (tested with mongoid)
# geo.rb
# Formulas from
#
# haversine formula to compute the great circle distance between two points given their latitude and longitudes
#
# Copyright (C) 2008, 360VL, Inc
# Copyright (C) 2008, Landon Cox
#
# http://www.esawdust.com (Landon Cox)
# contact:
# http://www.esawdust.com/blog/businesscard/businesscard.html
#
# LICENSE: GNU Affero GPL v3
# The ruby implementation of the Haversine formula is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License version 3 as published by the Free Software Foundation.
#
# This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the
# implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public
# License version 3 for more details. http://www.gnu.org/licenses/
#
# Landon Cox - 9/25/08
#
# Notes:
#
# translated into Ruby based on information contained in:
# http://mathforum.org/library/drmath/view/51879.html Doctors Rick and Peterson - 4/20/99
# http://www.movable-type.co.uk/scripts/latlong.html
# http://en.wikipedia.org/wiki/Haversine_formula
#
# This formula can compute accurate distances between two points given latitude and longitude, even for
# short distances.
#
# The rest shamelessly inspired by my friend tbhar https://gist.github.com/559482
#
# PI = 3.1415926535
RAD_PER_DEG = 0.017453293 # PI/180
KMS_PER_MILE = 1.609
NMS_PER_MILE = 0.868976242
EARTH_RADIUS_IN_MILES = 3963.19
EARTH_RADIUS_IN_KMS = EARTH_RADIUS_IN_MILES * KMS_PER_MILE
EARTH_RADIUS_IN_NMS = EARTH_RADIUS_IN_MILES * NMS_PER_MILE
MILES_PER_LATITUDE_DEGREE = 69.1
KMS_PER_LATITUDE_DEGREE = MILES_PER_LATITUDE_DEGREE * KMS_PER_MILE
NMS_PER_LATITUDE_DEGREE = MILES_PER_LATITUDE_DEGREE * NMS_PER_MILE
LATITUDE_DEGREES = EARTH_RADIUS_IN_MILES / MILES_PER_LATITUDE_DEGREE
@distances = Hash.new # this is global because if computing lots of track point distances, it didn't make
# sense to new a Hash each time over potentially 100's of thousands of points
=begin rdoc
given two lat/lon points, compute the distance between the two points using the haversine formula
the result will be a Hash of distances which are key'd by 'mi','km','ft', and 'm'
=end
def haversine_distance(lat1, lon1, lat2, lon2, unit=:mi)
dlon = lon2 - lon1
dlat = lat2 - lat1
dlon_rad = dlon * RAD_PER_DEG
dlat_rad = dlat * RAD_PER_DEG
lat1_rad = lat1 * RAD_PER_DEG
lat2_rad = lat2 * RAD_PER_DEG
a = (Math.sin(dlat_rad/2))**2 + Math.cos(lat1_rad) * Math.cos(lat2_rad) * (Math.sin(dlon_rad/2))**2
c = 2 * Math.atan2(Math.sqrt(a), Math.sqrt(1-a))
if unit == :km
EARTH_RADIUS_IN_KMS * c # delta in kilometers
else
EARTH_RADIUS_IN_MILES * c # delta between the two points in miles
end
end
def units_per_longitude_degree(lat, units=:mi)
miles_per_longitude_degree = (LATITUDE_DEGREES * Math.cos(lat * RAD_PER_DEG)).abs
case units
when :km;
miles_per_longitude_degree * KMS_PER_MILE
else
miles_per_longitude_degree
end
end
module Geo
# Mixin for a better nearby search on mongo < 1.8 (can't handle spherical search, do it here)
# Tested with mongoid && allow_dynamic_fields=true
module NearbyFinder
#In a mongo based model:
# class MongoModel
# extend ::Geo::NearbyFinder
# @location_field = 'coords'
#
# def self.collection
# #must be there (but defined by mongoid if you are using it)
# end
# end
#
# res = MongoModel.find_near([lon, lat], radius...)
# res.first.['distance']
#
# coord field is an array representing [X, Y] -> [lon, lat]
#
# Given a class, try to extrapolate an appropriate location field based on a
# class instance variable or `location_field` method.
def location_field_from_klass(klass)
klass.instance_variable_get(:@location_field) ||
(klass.respond_to?(:location_field) and klass.location_field)
end
def find_near(center, radius=75, unit=:mi, filter={})
radius = radius/units_per_longitude_degree(center[1], unit)
field = location_field_from_klass(self)
query = {field => {"$within" => {"$center" => [center, radius]}}}.merge(filter)
self.collection.find(query).sort_by do |r|
r['distance'] = haversine_distance(r[field][0], r[field][1], center[0], center[1])
end
end
end
end
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