Ruby: Calculating the orthodromic distance using the Haversine formula
As part of the UI I’m building around my football stadiums data set I wanted to calculate the distance from a football stadium to a point on the map in Ruby since cypher doesn’t currently return this value.
I had the following cypher query to return the football stadiums near Westminster along with their lat/long values:
lat, long, distance = ["51.55786291569685", "0.144195556640625", 10]
query = " START node = node:geom('withinDistance:[#{lat}, #{long}, #{distance}]')"
query << " RETURN node.name, node.team, node.lat, node.lon"
rows = result["data"].map do |row|
{ :team => row[1],
:stadium => row[0],
:lat => row[2],
:lon => row[3]
}
p rows
which returns the following:
[{:team=>"Millwall", :stadium=>"The Den", :lat=>51.4859, :lon=>-0.050743},
{:team=>"Arsenal", :stadium=>"Emirates Stadium", :lat=>51.5549, :lon=>-0.108436},
{:team=>"Chelsea", :stadium=>"Stamford Bridge", :lat=>51.4816, :lon=>-0.191034},
{:team=>"Fulham", :stadium=>"Craven Cottage", :lat=>51.4749, :lon=>-0.221619},
{:team=>"Queens Park Rangers", :stadium=>"Loftus Road", :lat=>51.5093, :lon=>-0.232204},
{:team=>"Leyton Orient", :stadium=>"Brisbane Road", :lat=>51.5601, :lon=>-0.012551}]
In the neo4j spatial code the distance between two points is referred to as the 'orthodromic distance' but searching for that didn’t come up with anything. However, I did eventually come across the following post which referred to the Haversine formula which is exactly what we want.
There is a good explanation of the formula on the Ask Dr Math forum which defines the formula like so:
dlon = lon2 - lon1
dlat = lat2 - lat1
a = (sin(dlat/2))^2 + cos(lat1) * cos(lat2) * (sin(dlon/2))^2
c = 2 * atan2(sqrt(a), sqrt(1-a))
d = R * c
where:
-
R - the radius of the Earth
-
c - the great circle distance in radians
-
c - the great circle distance in the same units as R
-
lat1, lat2, lon1, lon2 - latitude and longitudes in radians
To convert decimal degrees to radians we need to multiply the number of degrees by pi/180 radians/degree.
The Ruby translation of that formula looks like this:
def haversine(lat1, long1, lat2, long2)
radius_of_earth = 6378.14
rlat1, rlong1, rlat2, rlong2 = [lat1, long1, lat2, long2].map { |d| as_radians(d)}
dlon = rlong1 - rlong2
dlat = rlat1 - rlat2
a = power(Math::sin(dlat/2), 2) + Math::cos(rlat1) * Math::cos(rlat2) * power(Math::sin(dlon/2), 2)
great_circle_distance = 2 * Math::atan2(Math::sqrt(a), Math::sqrt(1-a))
radius_of_earth * great_circle_distance
end
def as_radians(degrees)
degrees * Math::PI/180
end
def power(num, pow)
num ** pow
end
And if we change our initial code to use it:
lat, long, distance = ["51.55786291569685", "0.144195556640625", 10]
query = " START node = node:geom('withinDistance:[#{lat}, #{long}, #{distance}]')"
query << " RETURN node.name, node.team, node.lat, node.lon"
rows = result["data"].map do |row|
{ :team => row[1],
:stadium => row[0],
:distance => haversine(lat, long, row[2], row[3]).round(2),
:lat => row[2],
:lon => row[3]
}
p rows
which gives us the output we want:
~ruby
~
About the author
I'm currently working on short form content at ClickHouse. I publish short 5 minute videos showing how to solve data problems on YouTube @LearnDataWithMark. I previously worked on graph analytics at Neo4j, where I also co-authored the O'Reilly Graph Algorithms Book with Amy Hodler.