def testFiltre(): alist = [] for i in range(20): r = random.randint(0,100) alist.append(r) print 'alist', alist score = stats.scoreatpercentile(alist, 0.1) print 'score', score
print('tmean:', stats.tmean(a, (5, 17)), stats.tmean(af, (5, 17))) print('tvar:', stats.tvar(a, (5, 17)), stats.tvar(af, (5, 17))) print('tstdev:', stats.tstdev(a, (5, 17)), stats.tstdev(af, (5, 17))) print('tsem:', stats.tsem(a, (5, 17)), stats.tsem(af, (5, 17))) print('describe:') print(stats.describe(l)) print(stats.describe(lf)) print(stats.describe(a)) print(stats.describe(af)) print('\nFREQUENCY') print('freqtable:') print('itemfreq:') print(stats.itemfreq(l)) print(stats.itemfreq(a)) print('scoreatpercentile:', stats.scoreatpercentile(l, 40), stats.scoreatpercentile(lf, 40), stats.scoreatpercentile(a, 40), stats.scoreatpercentile(af, 40)) print('percentileofscore:', stats.percentileofscore(l, 12), stats.percentileofscore(lf, 12), stats.percentileofscore(a, 12), stats.percentileofscore(af, 12)) print('histogram:', stats.histogram(l), stats.histogram(a)) print('cumfreq:') print(stats.cumfreq(l)) print(stats.cumfreq(lf)) print(stats.cumfreq(a)) print(stats.cumfreq(af)) print('relfreq:') print(stats.relfreq(l)) print(stats.relfreq(lf)) print(stats.relfreq(a))
print 'tmean:',stats.tmean(a,(5,17)),stats.tmean(af,(5,17)) print 'tvar:',stats.tvar(a,(5,17)),stats.tvar(af,(5,17)) print 'tstdev:',stats.tstdev(a,(5,17)),stats.tstdev(af,(5,17)) print 'tsem:',stats.tsem(a,(5,17)),stats.tsem(af,(5,17)) print 'describe:' print stats.describe(l) print stats.describe(lf) print stats.describe(a) print stats.describe(af) print '\nFREQUENCY' print 'freqtable:' print 'itemfreq:' print stats.itemfreq(l) print stats.itemfreq(a) print 'scoreatpercentile:',stats.scoreatpercentile(l,40),stats.scoreatpercentile(lf,40),stats.scoreatpercentile(a,40),stats.scoreatpercentile(af,40) print 'percentileofscore:',stats.percentileofscore(l,12),stats.percentileofscore(lf,12),stats.percentileofscore(a,12),stats.percentileofscore(af,12) print 'histogram:',stats.histogram(l),stats.histogram(a) print 'cumfreq:' print stats.cumfreq(l) print stats.cumfreq(lf) print stats.cumfreq(a) print stats.cumfreq(af) print 'relfreq:' print stats.relfreq(l) print stats.relfreq(lf) print stats.relfreq(a) print stats.relfreq(af) print '\nVARIATION' print 'obrientransform:'
def test_scoreatpercentile(self): "Testing scoreatpercentile" data = [self.L, self.LF, self.A, self.AF] for d in data: self.EQ(stats.scoreatpercentile(d, 40), 8.31500035)
def evaluate(self, *args, **params): return _stats.scoreatpercentile(*args, **params)
def test_scoreatpercentile(self): "Testing scoreatpercentile" data = [ self.L, self.LF, self.A, self.AF ] for d in data: self.EQ( stats.scoreatpercentile( d, 40 ), 8.31500035 )
# run in wt/visual-cluster from statlib import stats OFILE = open("stats.txt",'w') for i in range(1,8): BEs = [] IFILE = open("visual_cluster-%s.pdb" % i, 'r') for l in IFILE: values = l.split() BEs.append(float(values[9]) / 0.7) # if given BEs are weighted OFILE.write("visual_cluster-%s: %s, stddev %s, lower %s, upper %s, min %s, max %s, median %s \n" % (i,stats.mean(BEs), stats.stdev(BEs), stats.scoreatpercentile(BEs,25), stats.scoreatpercentile(BEs,75), min(BEs), max(BEs), stats.median(BEs) )) OFILE.close()