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src/c/o/cogent-1.5.3/cogent/maths/stats/test.py   cogent(Download)
from __future__ import division
import warnings
from cogent.maths.stats.distribution import chi_high, z_low, z_high, zprob, \
    t_high, t_low, tprob, f_high, f_low, fprob, binomial_high, binomial_low, \
    ndtri
        return t_low(t, df)
    else:
        return tprob(t,df)
 
def reverse_tails(tails):

src/p/y/pycogent-HEAD/cogent/maths/stats/test.py   pycogent(Download)
from __future__ import division
import warnings
from cogent.maths.stats.distribution import chi_high, z_low, z_high, zprob, \
    t_high, t_low, tprob, f_high, f_low, fprob, binomial_high, binomial_low, \
    ndtri
        return t_low(t, df)
    else:
        return tprob(t,df)
 
def reverse_tails(tails):

src/q/i/qiime-1.8.0/qiime/pycogent_backports/test.py   qiime(Download)
from __future__ import division
import warnings
from cogent.maths.stats.distribution import (chi_high, z_low, z_high, zprob,
    t_high, t_low, tprob, f_high, f_low, fprob, binomial_high, binomial_low,
    ndtri)
        return t_low(t, df)
    else:
        return tprob(t,df)
 
def reverse_tails(tails):
        try:
            ts = corr*((df/(1.-corr**2))**.5)
            return tprob(ts, df) #two tailed test because H0 is corr=0
        except (ValueError, FloatingPointError, ZeroDivisionError):
            # something unpleasant happened, most likely r or rho where +- 1 

src/q/i/qiime-HEAD/qiime/pycogent_backports/test.py   qiime(Download)
from __future__ import division
import warnings
from cogent.maths.stats.distribution import (chi_high, z_low, z_high, zprob,
                                             t_high, t_low, tprob, f_high, f_low, fprob, binomial_high, binomial_low,
                                             ndtri)
        return t_low(t, df)
    else:
        return tprob(t, df)
 
 
        try:
            ts = corr * ((df / (1. - corr ** 2)) ** .5)
            return tprob(ts, df)  # two tailed test because H0 is corr=0
        except (ValueError, FloatingPointError, ZeroDivisionError):
            # something unpleasant happened, most likely r or rho where +- 1

src/c/o/cogent-1.5.3/tests/test_maths/test_stats/test_distribution.py   cogent(Download)
 
from cogent.util.unit_test import TestCase, main
from cogent.maths.stats.distribution import z_low, z_high, zprob, chi_low, \
    chi_high, t_low, t_high, tprob, poisson_high, poisson_low, poisson_exact, \
    binomial_high, binomial_low, binomial_exact, f_low, f_high, fprob, \

src/p/y/pycogent-HEAD/tests/test_maths/test_stats/test_distribution.py   pycogent(Download)
 
from cogent.util.unit_test import TestCase, main
from cogent.maths.stats.distribution import z_low, z_high, zprob, chi_low, \
    chi_high, t_low, t_high, tprob, poisson_high, poisson_low, poisson_exact, \
    binomial_high, binomial_low, binomial_exact, f_low, f_high, fprob, \

src/q/i/qiime-1.8.0/tests/test_pycogent_backports/test_test.py   qiime(Download)
# cogent imports
from cogent.maths.stats import chisqprob
from cogent.maths.stats.distribution import zprob, tprob
 
__author__ = "Rob Knight"
        n = 12
        ts = 5.45618 # only 5 sig figs in sokal and rohlf
        exp = tprob(ts, n-2)
        obs = assign_correlation_pval(r, n, 'parametric_t_distribution')
        self.assertFloatEqual(exp, obs, eps=10**-5)

src/q/i/qiime-HEAD/tests/test_pycogent_backports/test_test.py   qiime(Download)
# cogent imports
from cogent.maths.stats import chisqprob
from cogent.maths.stats.distribution import zprob, tprob
 
__author__ = "Rob Knight"
        n = 12
        ts = 5.45618  # only 5 sig figs in sokal and rohlf
        exp = tprob(ts, n - 2)
        obs = assign_correlation_pval(r, n, 'parametric_t_distribution')
        self.assertFloatEqual(exp, obs, eps=10 ** -5)

src/p/i/picrust-HEAD/picrust/evaluate_test_datasets.py   picrust(Download)
from copy import copy
from cogent.maths.stats.test import correlation,spearman,correlation_test 
from cogent.maths.stats.distribution import tprob,t_high
from biom.table import table_factory,DenseOTUTable
 
 
    if tails == 'two-tailed':
        prob = tprob(t,n-2)
    elif tails == 'high':
        prob = t_high(t,n-2)