def testFishers(self):
"""Verify computation of Fisher's exact test (minimum-likelihood approach)"""
from plugins.statisticalTests.Fishers import Fishers
fishers = Fishers(preferences)
# Ground truth obtained from R version 2.10
oneSided, twoSided = fishers.hypothesisTest(table1[0], table1[1],
table1[2], table1[3])
self.assertAlmostEqual(oneSided, 0.16187126209690825)
self.assertAlmostEqual(twoSided, 0.2715543327789185)
oneSided, twoSided = fishers.hypothesisTest(table2[0], table2[1],
table2[2], table2[3])
self.assertAlmostEqual(oneSided, 2.220446049e-16)
self.assertAlmostEqual(twoSided, 2.220446049e-16)
from plugins.statisticalTests.Fishers import Fishers
preferences = {}
fishers = Fishers(preferences)
sampleSizes = [
20, 50, 100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000
]
fout = open('effectSizeTest.txt', 'w')
for sampleSize in sampleSizes:
print sampleSize
a = sampleSize / 2
b = sampleSize / 2
pValueTwoSided = 1.0
while pValueTwoSided > 0.05:
pValueOneSided, pValueTwoSided = fishers.hypothesisTest(
a, b, sampleSize, sampleSize)
a += 1
p1 = float(a) / sampleSize
p2 = float(b) / sampleSize
fout.write(
str(sampleSize) + ',' + str(p1 - p2) + ',' + str(p1 / p2) + ',' +
str(pValueTwoSided) + ',' + str(a) + '\n')
fout = open('FishersTest.txt','w')
random.seed()
for C1 in C1s:
print C1
totalSamples1 = C1
totalSamples2 = C1*2
relativelErrors = {}
for a in xrange(0, maxX1):
print a
for b in xrange(a, maxX1):
# calculate p-values
fishersOneSided, fishersTwoSided = fishers.hypothesisTest(a, b, totalSamples1, totalSamples2)
hypergeometricOneSided, hypergeometricTwoSided = hypergeometric.hypothesisTest(a, b, totalSamples1, totalSamples2)
relativeError = 100 * (hypergeometricTwoSided - fishersTwoSided) / fishersTwoSided
if fishersTwoSided < 1e-6:
l = relativelErrors.get(1e-6, [])
l.append(relativeError)
relativelErrors[1e-6] = l
elif fishersTwoSided < 1e-5:
l = relativelErrors.get(1e-5, [])
l.append(relativeError)
relativelErrors[1e-5] = l
elif fishersTwoSided < 1e-4:
l = relativelErrors.get(1e-4, [])
l.append(relativeError)
relativelErrors[1e-4] = l
elif fishersTwoSided < 1e-3:
fout = open('FishersTest.txt', 'w')
random.seed()
for C1 in C1s:
print C1
totalSamples1 = C1
totalSamples2 = C1 * 2
relativelErrors = {}
for a in xrange(0, maxX1):
print a
for b in xrange(a, maxX1):
# calculate p-values
fishersOneSided, fishersTwoSided = fishers.hypothesisTest(
a, b, totalSamples1, totalSamples2)
hypergeometricOneSided, hypergeometricTwoSided = hypergeometric.hypothesisTest(
a, b, totalSamples1, totalSamples2)
relativeError = 100 * (hypergeometricTwoSided -
fishersTwoSided) / fishersTwoSided
if fishersTwoSided < 1e-6:
l = relativelErrors.get(1e-6, [])
l.append(relativeError)
relativelErrors[1e-6] = l
elif fishersTwoSided < 1e-5:
l = relativelErrors.get(1e-5, [])
l.append(relativeError)
relativelErrors[1e-5] = l
elif fishersTwoSided < 1e-4:
l = relativelErrors.get(1e-4, [])
l.append(relativeError)
from plugins.statisticalTests.Fishers import Fishers
preferences = {}
fishers = Fishers(preferences)
sampleSizes = [20, 50, 100, 200, 500, 1000, 2000, 5000, 10000, 20000, 50000, 100000]
fout = open('effectSizeTest.txt' ,'w')
for sampleSize in sampleSizes:
print sampleSize
a = sampleSize / 2
b = sampleSize / 2
pValueTwoSided = 1.0
while pValueTwoSided > 0.05:
pValueOneSided, pValueTwoSided = fishers.hypothesisTest(a, b, sampleSize, sampleSize)
a += 1
p1 = float(a) / sampleSize
p2 = float(b) / sampleSize
fout.write(str(sampleSize) + ',' + str(p1-p2) + ',' + str(p1/p2) + ',' + str(pValueTwoSided) + ',' + str(a) + '\n')
