Lines Matching refs:inlist
272 def lgeometricmean(inlist):
277 Usage: lgeometricmean(inlist)
280 one_over_n = 1.0 / len(inlist)
281 for item in inlist:
286 def lharmonicmean(inlist):
291 Usage: lharmonicmean(inlist)
294 for item in inlist:
296 return len(inlist) / sum
299 def lmean(inlist):
304 Usage: lmean(inlist)
307 for item in inlist:
309 return sum / float(len(inlist))
312 def lmedian(inlist, numbins=1000):
319 Usage: lmedian (inlist, numbins=1000)
322 inlist, numbins, [min(inlist), max(inlist)]) # make histog
325 if cumhist[i] >= len(inlist) / 2.0:
332 (len(inlist) / 2.0 - cfbelow) / float(freq)) * binsize # median formula
336 def lmedianscore(inlist):
341 Usage: lmedianscore(inlist)
344 newlist = copy.deepcopy(inlist)
355 def lmode(inlist):
361 Usage: lmode(inlist)
365 scores = pstat.unique(inlist)
369 freq.append(inlist.count(item))
388 def lmoment(inlist, moment=1):
393 Usage: lmoment(inlist,moment=1)
394 Returns: appropriate moment (r) from ... 1/n * SUM((inlist(i)-mean)**r)
399 mn = mean(inlist)
400 n = len(inlist)
402 for x in inlist:
407 def lvariation(inlist):
412 Usage: lvariation(inlist)
414 return 100.0 * samplestdev(inlist) / float(mean(inlist))
417 def lskew(inlist):
422 Usage: lskew(inlist)
424 return moment(inlist, 3) / pow(moment(inlist, 2), 1.5)
427 def lkurtosis(inlist):
432 Usage: lkurtosis(inlist)
434 return moment(inlist, 4) / pow(moment(inlist, 2), 2.0)
437 inlist):
441 Usage: ldescribe(inlist)
444 n = len(inlist)
445 mm = (min(inlist), max(inlist))
446 m = mean(inlist)
447 sd = stdev(inlist)
448 sk = skew(inlist)
449 kurt = kurtosis(inlist)
457 def litemfreq(inlist):
459 Returns a list of pairs. Each pair consists of one of the scores in inlist
462 Usage: litemfreq(inlist)
465 scores = pstat.unique(inlist)
469 freq.append(inlist.count(item))
473 def lscoreatpercentile(inlist, percent):
476 given by inlist.
478 Usage: lscoreatpercentile(inlist,percent)
483 targetcf = percent * len(inlist)
484 h, lrl, binsize, extras = histogram(inlist)
494 def lpercentileofscore(inlist, score, histbins=10, defaultlimits=None):
497 given by inlist. Formula depends on the values used to histogram the data(!).
499 Usage: lpercentileofscore(inlist,score,histbins=10,defaultlimits=None)
502 h, lrl, binsize, extras = histogram(inlist, histbins, defaultlimits)
507 (lrl + binsize * i)) / float(binsize)) * h[i]) / float(len(inlist)) * 100
511 def lhistogram(inlist, numbins=10, defaultreallimits=None, printextras=0):
517 spanning all the numbers in the inlist.
519 Usage: lhistogram (inlist, numbins=10,
527 upperreallimit = 1.000001 * max(inlist)
533 estbinwidth = (max(inlist) -
534 min(inlist)) / float(numbins) + 1e-6 #1=>cover all
535 binsize = ((max(inlist) - min(inlist) + estbinwidth)) / float(numbins)
536 lowerreallimit = min(inlist) - binsize / 2 #lower real limit,1st bin
539 for num in inlist:
553 def lcumfreq(inlist, numbins=10, defaultreallimits=None):
557 Usage: lcumfreq(inlist,numbins=10,defaultreallimits=None)
560 h, l, b, e = histogram(inlist, numbins, defaultreallimits)
565 def lrelfreq(inlist, numbins=10, defaultreallimits=None):
569 Usage: lrelfreq(inlist,numbins=10,defaultreallimits=None)
572 h, l, b, e = histogram(inlist, numbins, defaultreallimits)
574 h[i] = h[i] / float(len(inlist))
618 def lsamplevar(inlist):
623 Usage: lsamplevar(inlist)
625 n = len(inlist)
626 mn = mean(inlist)
628 for item in inlist:
633 def lsamplestdev(inlist):
638 Usage: lsamplestdev(inlist)
640 return math.sqrt(samplevar(inlist))
668 def lvar(inlist):
673 Usage: lvar(inlist)
675 n = len(inlist)
676 mn = mean(inlist)
677 deviations = [0] * len(inlist)
678 for i in range(len(inlist)):
679 deviations[i] = inlist[i] - mn
683 def lstdev(inlist):
688 Usage: lstdev(inlist)
690 return math.sqrt(var(inlist))
693 def lsterr(inlist):
698 Usage: lsterr(inlist)
700 return stdev(inlist) / float(math.sqrt(len(inlist)))
703 def lsem(inlist):
708 Usage: lsem(inlist)
710 sd = stdev(inlist)
711 n = len(inlist)
715 def lz(inlist, score):
720 Usage: lz(inlist, score)
722 z = (score - mean(inlist)) / samplestdev(inlist)
726 def lzs(inlist):
730 Usage: lzs(inlist)
733 for item in inlist:
734 zscores.append(z(inlist, item))
1691 def lsum(inlist):
1695 Usage: lsum(inlist)
1698 for item in inlist:
1703 def lcumsum(inlist):
1708 Usage: lcumsum(inlist)
1710 newlist = copy.deepcopy(inlist)
1716 def lss(inlist):
1721 Usage: lss(inlist)
1724 for item in inlist:
1759 def lsquare_of_sums(inlist):
1764 Usage: lsquare_of_sums(inlist)
1765 Returns: sum(inlist[i])**2
1767 s = sum(inlist)
1771 def lshellsort(inlist):
1775 Usage: lshellsort(inlist)
1776 Returns: sorted-inlist, sorting-index-vector (for original list)
1778 n = len(inlist)
1779 svec = copy.deepcopy(inlist)
1793 # svec is now sorted inlist, and ivec has the order svec[i] = vec[ivec[i]]
1797 def lrankdata(inlist):
1799 Ranks the data in inlist, dealing with ties appropritely. Assumes
1800 a 1D inlist. Adapted from Gary Perlman's |Stat ranksort.
1802 Usage: lrankdata(inlist)
1803 Returns: a list of length equal to inlist, containing rank scores
1805 n = len(inlist)
1806 svec, ivec = shellsort(inlist)
