blob: 15c6e1070e0c6b6fd070aa7d1d1aa07e66e52161 (
plain) (
tree)
|
|
#!/usr/bin/env python
import os
import sys
import math
import numpy
import data
# Haversine distance calculation
# --------- -------- -----------
rearth = 6371.
deg2rad = 3.141592653589793 / 180.
def hdist(a, b):
lat1 = a[:, 0] * deg2rad
lon1 = a[:, 1] * deg2rad
lat2 = b[:, 0] * deg2rad
lon2 = b[:, 1] * deg2rad
dlat = abs(lat1-lat2)
dlon = abs(lon1-lon2)
al = numpy.sin(dlat/2)**2 + numpy.cos(lat1) * numpy.cos(lat2) * (numpy.sin(dlon/2)**2)
d = numpy.arctan2(numpy.sqrt(al), numpy.sqrt(1.-al))
hd = 2. * rearth * d
return hd
# Read the inputs
# ---- --- ------
def readcsv(f):
return numpy.genfromtxt(f, delimiter=',', skip_header=1)[:, 1:3]
answer = readcsv(os.path.join(data.path, 'test_answer.csv'))
tables = [readcsv(f) for f in sys.argv if '.csv' in f]
etables = [hdist(t, answer) for t in tables]
# Calculate p-values
# --------- --------
pvalue = numpy.zeros((len(tables), len(tables)))
for i, a in enumerate(etables):
for j, b in enumerate(etables):
if i == j:
continue
d = b - a
var = (numpy.mean((a - numpy.mean(a))**2)
+ numpy.mean((b - numpy.mean(b))**2)) / 2.
pv = 1 - .5 * (1 + math.erf(numpy.mean(d) / numpy.sqrt(2 * var)))
pvalue[i, j] = pv
print pvalue
|