def analyse_sample_set(self, samples):
""" Analyses a set of sample of length sample_size """
result = self.template.copy()
result.update( { 'index' : self.index,
'mean' : get_average(samples)[0],
'median': get_median(samples),
} )
self.rev_results.append(result)
if len(set(samples)) == 1:
t_prob1 = -1
t_prob2 = -1
t_prob3 = -1
else:
(t_stat, t_prob1) = stats.ttest_1samp(samples, self.popmean)
(t_stat, t_prob2) = stats.ttest_1samp(samples, min(int(self.popmean * (1-self.threshold)), self.popmean - 1))
(t_stat, t_prob3) = stats.ttest_1samp(samples, max(int(self.popmean * (1+self.threshold)), self.popmean + 1))
result = self.template.copy()
result.update( { 'index' : self.index,
'same' : t_prob1 > 0.05,
'same_stat' : t_prob1,
'less' : t_prob2 < 0.05,
'less_stat' : t_prob2,
'more' : t_prob3 < 0.05,
'more_stat' : t_prob3,
} )
self.conf_results.append(result)
def test_ttest_1samp(self):
"Testing ttest_1samp"
data = [self.L, self.A]
results = (-1.1338934190276817, 0.27094394816451473)
i = 0
for d in data:
self.assertEqual(stats.ttest_1samp(d, 12)[i], results[i])
i += 1
def test_ttest_1samp(self):
"Testing ttest_1samp"
data = [ self.L, self.A ]
results = (-1.1338934190276817, 0.27094394816451473)
i = 0
for d in data:
self.assertEqual( stats.ttest_1samp( d, 12 )[i], results[i] )
i += 1
print('spearmanr:')
print(stats.spearmanr(l, m))
print(stats.spearmanr(a, b))
print('pointbiserialr:')
print(stats.pointbiserialr(pb, l))
print(stats.pointbiserialr(apb, a))
print('kendalltau:')
print(stats.kendalltau(l, m))
print(stats.kendalltau(a, b))
print('linregress:')
print(stats.linregress(l, m))
print(stats.linregress(a, b))
print('\nINFERENTIAL')
print('ttest_1samp:')
print(stats.ttest_1samp(l, 12))
print(stats.ttest_1samp(a, 12))
print('ttest_ind:')
print(stats.ttest_ind(l, m))
print(stats.ttest_ind(a, b))
print('ttest_rel:')
print(stats.ttest_rel(l, m))
print(stats.ttest_rel(a, b))
print('chisquare:')
print(stats.chisquare(l))
print(stats.chisquare(a))
print('ks_2samp:')
print(stats.ks_2samp(l, m))
print(stats.ks_2samp(a, b))
print('mannwhitneyu:')
print 'spearmanr:' print stats.spearmanr(l,m) print stats.spearmanr(a,b) print 'pointbiserialr:' print stats.pointbiserialr(pb,l) print stats.pointbiserialr(apb,a) print 'kendalltau:' print stats.kendalltau(l,m) print stats.kendalltau(a,b) print 'linregress:' print stats.linregress(l,m) print stats.linregress(a,b) print '\nINFERENTIAL' print 'ttest_1samp:' print stats.ttest_1samp(l,12) print stats.ttest_1samp(a,12) print 'ttest_ind:' print stats.ttest_ind(l,m) print stats.ttest_ind(a,b) print 'ttest_rel:' print stats.ttest_rel(l,m) print stats.ttest_rel(a,b) print 'chisquare:' print stats.chisquare(l) print stats.chisquare(a) print 'ks_2samp:' print stats.ks_2samp(l,m) print stats.ks_2samp(a,b) print 'mannwhitneyu:'
from statlib import stats, pstat reload(stats) from Numeric import * reload(pstat) import statshelp print '\n\nSingle Sample t-test' x = [50, 75, 65, 72, 68, 65, 73, 59, 64] print 'SHOULD BE ... t=-3.61, p<0.01 (df=8) ... Basic Stats 1st ed, p.307' stats.ttest_1samp(x, 75, 1) stats.attest_1samp(array(x), 75, 1) print '\n\nIndependent Samples t-test' a = [11, 16, 20, 17, 10, 12] b = [8, 11, 15, 11, 11, 12, 11, 7] print '\n\nSHOULD BE ??? <p< (df=) ... ' stats.ttest_ind(a, b, 1) stats.attest_ind(array(a), array(b), 0, 1) print '\n\nRelated Samples t-test' before = [11, 16, 20, 17, 10] after = [8, 11, 15, 11, 11] print '\n\nSHOULD BE t=+2.88, 0.01<p<0.05 (df=4) ... Basic Stats 1st ed, p.359' stats.ttest_rel(before, after, 1, 'Before', 'After') stats.attest_rel(array(before), array(after), 1, 'Before', 'After') print "\n\nPearson's r"
def evaluate(self, *args, **params):
return _stats.ttest_1samp(*args, **params)
parser = argparse.ArgumentParser(description="")
parser.add_argument('-l', '--length', help="Length of the structure")
parser.add_argument('-m', '--mfe', help="MFE of the structure")
args = parser.parse_args()
al = int(args.length)
am = int(args.mfe)
a = []
m = re.compile("(?P<l>\d+)\s(?P<m>\d+)")
L = sys.stdin.readlines()
for l in L:
s = m.match(l)
length = int(s.group("l"))
if (abs(length - al) < 5):
a.append(int(s.group("m")))
print a
print 't-statistic = %6.3f pvalue = %s' % stats.ttest_1samp(a,am)
# length -= length%10 +5
# a[length].append(int(s.group("m")))
# b = []
# for i in xrange(200,501):
# if (a[i] != []):
# print i, stats.mean(a[i]), stats.stdev(a[i])
# b.append(len(a[i]))
# print stats.mean(b), stats.stdev(b)
from statlib import stats, pstat reload(stats) from Numeric import * reload(pstat) import statshelp print '\n\nSingle Sample t-test' x = [50,75,65,72,68,65,73,59,64] print 'SHOULD BE ... t=-3.61, p<0.01 (df=8) ... Basic Stats 1st ed, p.307' stats.ttest_1samp(x,75,1) stats.attest_1samp(array(x),75,1) print '\n\nIndependent Samples t-test' a = [11,16,20,17,10,12] b = [8,11,15,11,11,12,11,7] print '\n\nSHOULD BE ??? <p< (df=) ... ' stats.ttest_ind(a,b,1) stats.attest_ind(array(a),array(b),0,1) print '\n\nRelated Samples t-test' before = [11,16,20,17,10] after = [8,11,15,11,11] print '\n\nSHOULD BE t=+2.88, 0.01<p<0.05 (df=4) ... Basic Stats 1st ed, p.359' stats.ttest_rel(before,after,1,'Before','After') stats.attest_rel(array(before),array(after),1,'Before','After')
print 'spearmanr:' print stats.spearmanr(l, m) print stats.spearmanr(a, b) print 'pointbiserialr:' print stats.pointbiserialr(pb, l) print stats.pointbiserialr(apb, a) print 'kendalltau:' print stats.kendalltau(l, m) print stats.kendalltau(a, b) print 'linregress:' print stats.linregress(l, m) print stats.linregress(a, b) print '\nINFERENTIAL' print 'ttest_1samp:' print stats.ttest_1samp(l, 12) print stats.ttest_1samp(a, 12) print 'ttest_ind:' print stats.ttest_ind(l, m) print stats.ttest_ind(a, b) print 'ttest_rel:' print stats.ttest_rel(l, m) print stats.ttest_rel(a, b) print 'chisquare:' print stats.chisquare(l) print stats.chisquare(a) print 'ks_2samp:' print stats.ks_2samp(l, m) print stats.ks_2samp(a, b) print 'mannwhitneyu:'
