[SciPy-User] fisherexact.py returns None

Pete Shepard peter.shepard@gmail....
Sun Dec 20 19:07:28 CST 2009


Your corrected version seems to work. Strangely though when I uncomment line
99 it fails?

98    res = fisherExact([[100, 2], [1000, 5]])
99    assert(approxEqual(res[1],  0.1973244))

On Sun, Dec 20, 2009 at 2:04 PM, <josef.pktd@gmail.com> wrote:

> On Sun, Dec 20, 2009 at 4:44 PM, Pete Shepard <peter.shepard@gmail.com>
> wrote:
> > I think the indent issue was due to copying and pasting also, attached is
> > the code.
>
> your attached file has inconsistent indentation all over the place
> (according to IDLE, which refuses to run the file, or maybe there are
> additional tabs instead of white space)
> your return statement is indented relative to the if , as mentioned in
> my previous message. If you unindent then the None disappears.
>
> I attach my indent corrected version.
>
> What editor are you using? It is possible that you are seeing
> different formatting than I do on Windows.
>
> Josef
>
> >
> > On Sun, Dec 20, 2009 at 1:05 PM, <josef.pktd@gmail.com> wrote:
> >>
> >> On Sun, Dec 20, 2009 at 3:50 PM, Pete Shepard <peter.shepard@gmail.com>
> >> wrote:
> >> > Thanks for the reply Josef,
> >> >
> >> > Numpy version =1:1.3.0-3
> >> > SciPy version=0.7.0-2
> >> >
> >> >
> >> > Here is the code I am using, interstingly line 99 chokes in the
> >> > testFisherExact() : example, don't know if these problems are related
> >> >
> >> >
> >> > # -*- coding: utf-8 -*-
> >> >
> >> > #!/usr/bin/python
> >> >
> >> >
> >> > import re
> >> > import sys, os
> >> > from scipy.stats import *
> >> > #from scipy import array,searchsorted, histogram
> >> > import re
> >> > import operator
> >> > import matplotlib
> >> > matplotlib.use('PDF')
> >> > import pylab
> >> > "
> >> >
> >> > def fisherExact(c) :
> >> >             """Performs a Fisher exact test on a 2x2 contingency table
> >> > in
> >> > list of lists
> >> >                format.  Returns a tuple of (odds ratio, two-tailed
> >> > P-value).
> >> >
> >> >                Examples:
> >> >                >>> fisherExact([[100, 2], [1000, 5]])
> >> >                (0.25, 0.13007593634330314)
> >> >                """
> >> >             oddsRatio = c[0][0] * c[1][1] / float(c[1][0] * c[0][1])
> >> >             n1 = c[0][0] + c[0][1]
> >> >             n2 = c[1][0] + c[1][1]
> >> >             n  = c[0][0] + c[1][0]
> >> >
> >> >             mode = int(float((n + 1) * (n1 + 1)) / (n1 + n2 + 2))
> >> >             pExact = hypergeom.pmf(c[0][0], n1 + n2, n1, n)
> >> >             pMode = hypergeom.pmf(c[0][0], n1 + n2, n1, n)
> >> >
> >> >             if c[0][0] == mode :
> >> >                     return oddsRatio, 1.0
> >> >             elif c[0][0] < mode :
> >> >                     pLower = hypergeom.cdf(c[0][0], n1 + n2, n1, n)
> >> >
> >> >                     # Binary search for where to begin upper half.
> >> >                     min = mode
> >> >                     max = n
> >> >                     guess = -1
> >> >                     while min != max :
> >> >                             guess = max if (max == min + 1 and guess
> ==
> >> > min)
> >> > else \
> >> >                                             (max + min) / 2
> >> >
> >> >                             pGuess = hypergeom.pmf(guess, n1 + n2, n1,
> >> > n)
> >> >                             if pGuess <= pExact and
> hypergeom.pmf(guess
> >> > - 1,
> >> > n1 + n2, n1, n) > pExact :
> >> >                                     break
> >> >                             elif pGuess < pExact :
> >> >                                     max = guess
> >> >                             else :
> >> >                                     min = guess
> >> >
> >> >                     if guess == -1 and min == max :
> >> >                             guess = min
> >> >
> >> >                     return oddsRatio, pLower + hypergeom.sf(guess - 1,
> >> > n1 +
> >> > n2, n1, n)
> >> >             else :
> >> >                     pUpper = hypergeom.sf(c[0][0] - 1, n1 + n2, n1,
> n);
> >> >
> >> >                     # Special case to prevent binary search from
> getting
> >> > stuck.
> >> >                     if hypergeom.pmf(0, n1 + n2, n1, n) > pExact :
> >> >                             return oddsRatio, pUpper
> >> >
> >> >                     # Binary search for where to begin lower half.
> >> >                     min = 0
> >> >                     max = mode
> >> >                     guess = -1
> >> >                     while min != max :
> >> >                             guess = max if (max == min + 1 and guess
> ==
> >> > min)
> >> > else \
> >> >                                             (max + min) / 2
> >> >                             pGuess = hypergeom.pmf(guess, n1 + n2, n1,
> >> > n);
> >> >
> >> >                             if pGuess <= pExact and
> hypergeom.pmf(guess
> >> > + 1,
> >> > n1 + n2, n1, n) > pExact :
> >> >                                     break;
> >> >                             elif pGuess <= pExact  :
> >> >                                     min = guess
> >> >                             else :
> >> >                                     max = guess
> >> >
> >> >                     if guess == -1 and min == max :
> >> >                             guess = min
> >> >                         return oddsRatio, pUpper +
> hypergeom.cdf(guess,
> >> > n1 +
> >> > n2, n1, n)
> >>
> >> this return line has the wrong indent, it should be at the same column
> >> as the   if guess == -1 and min == max :
> >>
> >> Note: I had to reformat the indent to 4 spaces because IDLE
> >> complained. In these cases, it would be better to also attach the
> >> file, then I would be sure I have the same file than with copy and
> >> paste from the mail reader.
> >>
> >> Tell me if that solves the problem, I would think it's unlikely that
> >> your versions of scipy is to old for this.
> >>
> >> Josef
> >>
> >> >
> >> > def testFisherExact() :
> >> >     """Just some tests to show that fisherExact() works correctly."""
> >> >     def approxEqual(n1, n2) :
> >> >         return abs(n1 - n2) < 0.01
> >> >
> >> >     res = fisherExact([[100, 2], [1000, 5]])
> >> >     assert(approxEqual(res[1], 0.1301))
> >> >     assert(approxEqual(res[0], 0.25))
> >> >     res = fisherExact([[2, 7], [8, 2]])
> >> >     assert(approxEqual(res[1], 0.0230141))
> >> >     assert(approxEqual(res[0], 4.0 / 56))
> >> >     res = fisherExact([[100, 2], [1000, 5]])
> >> >     #assert(approxEqual(res[1],  0.1973244))
> >> >         res = fisherExact([[5, 15], [20, 20]])
> >> >     assert(approxEqual(res[1], 0.0958044))
> >> >     res = fisherExact([[5, 16], [20, 25]])
> >> >     assert(approxEqual(res[1], 0.1725862))
> >> >     res = fisherExact([[10, 5], [10, 1]])
> >> >     assert(approxEqual(res[1], 0.1973244))
> >> >
> >> > D=[[6, 1], [1, 6]]
> >> > testFisherExact()
> >> > p=fisherExact(D)
> >> > print p
> >> > On Sun, Dec 20, 2009 at 10:37 AM, <josef.pktd@gmail.com> wrote:
> >> >>
> >> >> On Sun, Dec 20, 2009 at 12:26 PM, Pete Shepard
> >> >> <peter.shepard@gmail.com>
> >> >> wrote:
> >> >> > Hello,
> >> >> >
> >> >> > I am using a fisher exact test I got from
> >> >> > http://projects.scipy.org/scipy/attachment/ticket/956/fisher.py.
> This
> >> >> > program takes in two tuples and returns an odds ratio and a
> p-value.
> >> >> > Most
> >> >> > tuples are handled nicely by the script but certain tuples eg "[[6,
> >> >> > 1],
> >> >> > [1,
> >> >> > 6]]" return "None". I am wondering if anyone knows why this is
> true?
> >> >>
> >> >> I get this, with and without the patch of thomas in the comments
> >> >>
> >> >> >>> fisherExact([[6, 1], [1, 6]])
> >> >> (36.0, 0.029137529137528768)
> >> >>
> >> >> Do you have an exact example? Which version of numpy and scipy?
> >> >> Looking at the code, I don't see any reason why it should return
> None.
> >> >>
> >> >> Josef
> >> >> >
> >> >> > TIA
> >> >> >
> >> >> > _______________________________________________
> >> >> > SciPy-User mailing list
> >> >> > SciPy-User@scipy.org
> >> >> > http://mail.scipy.org/mailman/listinfo/scipy-user
> >> >> >
> >> >> >
> >> >> _______________________________________________
> >> >> SciPy-User mailing list
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> >> >> http://mail.scipy.org/mailman/listinfo/scipy-user
> >> >
> >> >
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> >> > SciPy-User mailing list
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> >> > http://mail.scipy.org/mailman/listinfo/scipy-user
> >> >
> >> >
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