Functions

test type	p-value	-log( p-value )	-log10( p-value )
left-tailed	test1l(a, b, c, d) or test2l(a, a+b, a+c, a+b+c+d)	mlnTest1l(a, b, c, d) or mlnTest2l(a, a+b, a+c, a+b+c+d)	mlog10Test1l(a, b, c, d) or mlog10Test2l(a, a+b, a+c, a+b+c+d)
right-tailed	test1r(a, b, c, d) or test2r(a, a+b, a+c, a+b+c+d)	mlnTest1r(a, b, c, d) or mlnTest2r(a, a+b, a+c, a+b+c+d)	mlog10Test1r(a, b, c, d) or mlog10Test2r(a, a+b, a+c, a+b+c+d)
two-tailed	test1t(a, b, c, d) or test2t(a, a+b, a+c, a+b+c+d)	mlnTest1t(a, b, c, d) or mlnTest2t(a, a+b, a+c, a+b+c+d)	mlog10Test1t(a, b, c, d) or mlog10Test2t(a, a+b, a+c, a+b+c+d)
all	test1(a, b, c, d) or test2(a, a+b, a+c, a+b+c+d)	mlnTest1(a, b, c, d) or mlnTest2(a, a+b, a+c, a+b+c+d)	mlog10Test1(a, b, c, d) or mlog10Test2(a, a+b, a+c, a+b+c+d)

Speed

Comparison of scipy.stats.fisher_exact([[a, b], [c, d]], *) and fisher.test1*(a, b, c, d). See benchmark.py.

a	b	c	d	test type	scipy	fisher
8	2	1	5	left-tailed	150 us	3 us
8	2	1	5	right-tailed	150 us	3 us
8	2	1	5	two-tailed	938 us	6 us
100	1000	10000	100000	left-tailed	155 us	55 us
100	1000	10000	100000	right-tailed	243 us	75 us
100	1000	10000	100000	two-tailed	187 us	128 us
10000	100	1000	100000	left-tailed	950 us	8 us
10000	100	1000	100000	right-tailed	159 us	6 us
10000	100	1000	100000	two-tailed	71292 us	680 us
10000	10000	10000	10000	left-tailed	950 us	369 us
10000	10000	10000	10000	right-tailed	955 us	376 us
10000	10000	10000	10000	two-tailed	193 us	732 us

Precision

>>> from scipy import stats
>>> -log10(stats.fisher_exact([[100, 1], [10, 1000]])[1])
128.93472935802367
>>> -log10(stats.fisher_exact([[100, 1], [10, 10000]])[1])
226.6210481678513
>>> -log10(stats.fisher_exact([[100, 1], [10, 100000]])[1])
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: math domain error

>>> import fisher
>>> fisher.mlog10Test1t(100, 1, 10, 1000)
128.93472935802276
>>> fisher.mlog10Test1t(100, 1, 10, 10000)
226.62104816784367
>>> fisher.mlog10Test1t(100, 1, 10, 100000)
326.3812661050023
>>> fisher.mlog10Test1t(100, 1, 10, 1000000)
426.3571991266363
>>> fisher.mlog10Test1t(100, 1, 10, 10000000)
526.3547915418933
>>> fisher.mlog10Test1t(100, 1, 10, 100000000)
626.354550887692
>>> fisher.mlog10Test1t(100, 1, 10, 1000000000)
726.3545256659792
>>> fisher.mlog10Test1t(100, 1, 10, 10000000000)
826.3545146294285
>>> fisher.mlog10Test1t(100, 1, 10, 100000000000)
926.354583114538
>>> fisher.mlog10Test1t(100, 1, 10, 1000000000000)
1026.3549166719595
>>> fisher.mlog10Test1t(100, 1, 10, 10000000000000)
1126.3970256263215
>>> fisher.mlog10Test1t(100, 1, 10, 100000000000000)
1226.447616894783
>>> fisher.mlog10Test1t(100, 1, 10, 1000000000000000)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
OverflowError: the grand total of contingency table is too large