gTestResults = []
gTestYatesResults = []
permutationResults = []
diffBetweenPropResults = []
bootstrapResults = []
for a in xrange(0, maxPositiveSeqs+1):
for b in xrange(a, maxPositiveSeqs+1):
# calculate p-values
barnardOneSided, barnardTwoSided = barnard.hypothesisTest(a, b, totalSamples1, totalSamples2)
if (barnardTwoSided < 0.01 or barnardTwoSided > 0.1):
continue
fishersOneSided, fishersTwoSided = fishers.hypothesisTest(a, b, totalSamples1, totalSamples2)
chiSquareOneSided, chiSquareTwoSided = chiSquare.hypothesisTest(a, b, totalSamples1, totalSamples2)
chiSquareYatesOneSided, chiSquareYatesTwoSided = chiSquareYates.hypothesisTest(a, b, totalSamples1, totalSamples2)
gTestOneSided, gTestTwoSided = gTest.hypothesisTest(a, b, totalSamples1, totalSamples2)
gTestYatesOneSided, gTestYatesTwoSided = gTestYates.hypothesisTest(a, b, totalSamples1, totalSamples2)
diffBetweenPropOneSided, diffBetweenPropTwoSided = diffBetweenProp.hypothesisTest(a, b, totalSamples1, totalSamples2)
permutationOneSided, permutationTwoSided = permutation.hypothesisTest(a, b, totalSamples1, totalSamples2)
bootstrapOneSided, bootstrapTwoSided = bootstrap.hypothesisTest(a, b, totalSamples1, totalSamples2)
# calculate p-values relative to Barnard's
fishersResults.append(100 * (fishersTwoSided - barnardTwoSided) / barnardTwoSided)
chiSquareResults.append(100 * (chiSquareTwoSided - barnardTwoSided) / barnardTwoSided)
chiSquareYatesResults.append(100 * (chiSquareYatesTwoSided - barnardTwoSided) / barnardTwoSided)
gTestResults.append(100 * (gTestTwoSided - barnardTwoSided) / barnardTwoSided)
gTestYatesResults.append(100 * (gTestYatesTwoSided - barnardTwoSided) / barnardTwoSided)
permutationResults.append(100 * (permutationTwoSided - barnardTwoSided) / barnardTwoSided)
diffBetweenPropResults.append(100 * (diffBetweenPropTwoSided - barnardTwoSided) / barnardTwoSided)
bootstrapResults.append(100 * (bootstrapTwoSided - barnardTwoSided) / barnardTwoSided)
# draw samples w/o replacement for community 2
samplesInSS = popSize*prop
samplesNotInSS = popSize - samplesInSS
inSS2 = 0
for s in xrange(0, sampleSize2[sampleSizeIndex]):
rnd = random.random()
if rnd <= float(samplesInSS) / popSize:
samplesInSS -= 1
inSS2 += 1
else:
samplesNotInSS -= 1
fishersOneSided, fishersTwoSided = fishers.hypothesisTest(inSS1, inSS2, totalSamples1, totalSamples2)
gTestOneSided, gTestTwoSided = gTest.hypothesisTest(inSS1, inSS2, totalSamples1, totalSamples2)
gTestYatesOneSided, gTestYatesTwoSided = gTestYates.hypothesisTest(inSS1, inSS2, totalSamples1, totalSamples2)
diffBetweenPropOneSided, diffBetweenPropTwoSided = diffBetweenProp.hypothesisTest(inSS1, inSS2, totalSamples1, totalSamples2)
fishersResults.append(fishersTwoSided)
gTestResults.append(gTestTwoSided)
gTestYatesResults.append(gTestYatesTwoSided)
diffBetweenPropResults.append(diffBetweenPropTwoSided)
pValues = [fishersResults,gTestResults,gTestYatesResults,diffBetweenPropResults]
bins = {}
numBins = 20
binSize = 1.0 / numBins
for i in xrange(0,numBins):
bins[i] = []
