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author | Sam Ockman | 2012-06-09 06:23:48 -0400 |
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committer | Sam Ockman | 2012-06-09 06:23:48 -0400 |
commit | 7085c3644adc569e7ce297b60f8666e5830339ea (patch) | |
tree | 9532cf895628e3ead9f15cc534395a23d56d8743 /wqflask/basicStatistics | |
parent | f3733aa972a3b1ab2eb1ab9d02d859eb75cebbb9 (diff) | |
download | genenetwork2-7085c3644adc569e7ce297b60f8666e5830339ea.tar.gz |
Trying to get the stats to work
Diffstat (limited to 'wqflask/basicStatistics')
-rwxr-xr-x | wqflask/basicStatistics/BasicStatisticsFunctions.py | 109 |
1 files changed, 69 insertions, 40 deletions
diff --git a/wqflask/basicStatistics/BasicStatisticsFunctions.py b/wqflask/basicStatistics/BasicStatisticsFunctions.py index 285addae..d2584bdd 100755 --- a/wqflask/basicStatistics/BasicStatisticsFunctions.py +++ b/wqflask/basicStatistics/BasicStatisticsFunctions.py @@ -1,9 +1,15 @@ +from __future__ import print_function + #import string from math import * #import piddle as pid #import os -#import reaper +from pprint import pformat as pf + +from corestats import Stats + +import reaper from htmlgen import HTMLgen2 as HT #from utility import Plot @@ -12,58 +18,81 @@ from base import webqtlConfig from dbFunction import webqtlDatabaseFunction def basicStatsTable(vals, trait_type=None, cellid=None, heritability=None): - + st = {} # This is the dictionary where we'll put everything for the template valsOnly = [] dataXZ = vals[:] for i in range(len(dataXZ)): valsOnly.append(dataXZ[i][1]) - traitmean, traitmedian, traitvar, traitstdev, traitsem, N = reaper.anova(valsOnly) #ZS: Should convert this from reaper to R in the future + (st['traitmean'], + st['traitmedian'], + st['traitvar'], + st['traitstdev'], + st['traitsem'], + st['N']) = reaper.anova(valsOnly) #ZS: Should convert this from reaper to R in the future + + #tbl = HT.TableLite(cellpadding=20, cellspacing=0) + #dataXZ = vals[:] + dataXZ = sorted(vals, webqtlUtil.cmpOrder) + + print("data for stats is:", pf(dataXZ)) + for num, item in enumerate(dataXZ): + print(" %i - %s" % (num, item)) + print(" length:", len(dataXZ)) + + st['min'] = dataXZ[0][1] + st['max'] = dataXZ[-1][1] + + numbers = [x[1] for x in dataXZ] + stats = Stats(numbers) + + at75 = stats.percentile(75) + at25 = stats.percentile(25) + print("Interquartile:", at75 - at25) + + #tbl.append(HT.TR(HT.TD("Statistic",align="left", Class="fs14 fwb ffl b1 cw cbrb", width = 180), + # HT.TD("Value", align="right", Class="fs14 fwb ffl b1 cw cbrb", width = 60))) + #tbl.append(HT.TR(HT.TD("N of Samples",align="left", Class="fs13 b1 cbw c222"), + # HT.TD(N,nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) + #tbl.append(HT.TR(HT.TD("Mean",align="left", Class="fs13 b1 cbw c222",nowrap="yes"), + # HT.TD("%2.3f" % traitmean,nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) + #tbl.append(HT.TR(HT.TD("Median",align="left", Class="fs13 b1 cbw c222",nowrap="yes"), + # HT.TD("%2.3f" % traitmedian,nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) + ##tbl.append(HT.TR(HT.TD("Variance",align="left", Class="fs13 b1 cbw c222",nowrap="yes"), + ## HT.TD("%2.3f" % traitvar,nowrap="yes",align="left", Class="fs13 b1 cbw c222"))) + #tbl.append(HT.TR(HT.TD("Standard Error (SE)",align="left", Class="fs13 b1 cbw c222",nowrap="yes"), + # HT.TD("%2.3f" % traitsem,nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) + #tbl.append(HT.TR(HT.TD("Standard Deviation (SD)", align="left", Class="fs13 b1 cbw c222",nowrap="yes"), + # HT.TD("%2.3f" % traitstdev,nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) + #tbl.append(HT.TR(HT.TD("Minimum", align="left", Class="fs13 b1 cbw c222",nowrap="yes"), + # HT.TD("%s" % dataXZ[0][1],nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) + #tbl.append(HT.TR(HT.TD("Maximum", align="left", Class="fs13 b1 cbw c222",nowrap="yes"), + # HT.TD("%s" % dataXZ[-1][1],nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) + + - tbl = HT.TableLite(cellpadding=20, cellspacing=0) - dataXZ = vals[:] - dataXZ.sort(webqtlUtil.cmpOrder) - tbl.append(HT.TR(HT.TD("Statistic",align="left", Class="fs14 fwb ffl b1 cw cbrb", width = 180), - HT.TD("Value", align="right", Class="fs14 fwb ffl b1 cw cbrb", width = 60))) - tbl.append(HT.TR(HT.TD("N of Samples",align="left", Class="fs13 b1 cbw c222"), - HT.TD(N,nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - tbl.append(HT.TR(HT.TD("Mean",align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%2.3f" % traitmean,nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - tbl.append(HT.TR(HT.TD("Median",align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%2.3f" % traitmedian,nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - #tbl.append(HT.TR(HT.TD("Variance",align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - # HT.TD("%2.3f" % traitvar,nowrap="yes",align="left", Class="fs13 b1 cbw c222"))) - tbl.append(HT.TR(HT.TD("Standard Error (SE)",align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%2.3f" % traitsem,nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - tbl.append(HT.TR(HT.TD("Standard Deviation (SD)", align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%2.3f" % traitstdev,nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - tbl.append(HT.TR(HT.TD("Minimum", align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%s" % dataXZ[0][1],nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - tbl.append(HT.TR(HT.TD("Maximum", align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%s" % dataXZ[-1][1],nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) if (trait_type != None and trait_type == 'ProbeSet'): - #IRQuest = HT.Href(text="Interquartile Range", url=webqtlConfig.glossaryfile +"#Interquartile",target="_blank", Class="fs14") - #IRQuest.append(HT.BR()) - #IRQuest.append(" (fold difference)") - tbl.append(HT.TR(HT.TD("Range (log2)",align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%2.3f" % (dataXZ[-1][1]-dataXZ[0][1]),nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - tbl.append(HT.TR(HT.TD(HT.Span("Range (fold)"),align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%2.2f" % pow(2.0,(dataXZ[-1][1]-dataXZ[0][1])), nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) - tbl.append(HT.TR(HT.TD(HT.Span(HT.Href(url="/glossary.html#Interquartile", target="_blank", text="Interquartile Range", Class="non_bold")), align="left", Class="fs13 b1 cbw c222",nowrap="yes"), - HT.TD("%2.2f" % pow(2.0,(dataXZ[int((N-1)*3.0/4.0)][1]-dataXZ[int((N-1)/4.0)][1])), nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) + #tbl.append(HT.TR(HT.TD("Range (log2)",align="left", Class="fs13 b1 cbw c222",nowrap="yes"), + # HT.TD("%2.3f" % (dataXZ[-1][1]-dataXZ[0][1]),nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) + #tbl.append(HT.TR(HT.TD(HT.Span("Range (fold)"),align="left", Class="fs13 b1 cbw c222",nowrap="yes"), + # HT.TD("%2.2f" % pow(2.0,(dataXZ[-1][1]-dataXZ[0][1])), nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) + #tbl.append(HT.TR(HT.TD(HT.Span(HT.Href(url="/glossary.html#Interquartile", target="_blank", text="Interquartile Range", Class="non_bold")), align="left", Class="fs13 b1 cbw c222",nowrap="yes"), + # HT.TD("%2.2f" % pow(2.0,(dataXZ[int((N-1)*3.0/4.0)][1]-dataXZ[int((N-1)/4.0)][1])), nowrap="yes", Class="fs13 b1 cbw c222"), align="right")) + st['range_log2'] = dataXZ[-1][1]-dataXZ[0][1] + st['range_fold'] = pow(2.0, (dataXZ[-1][1]-dataXZ[0][1])) + st['interquartile'] = pow(2.0, (dataXZ[int((st['N']-1)*3.0/4.0)][1]-dataXZ[int((st['N']-1)/4.0)][1])) #XZ, 04/01/2009: don't try to get H2 value for probe. - if cellid: - pass - else: + if not cellid: if heritability: - tbl.append(HT.TR(HT.TD(HT.Span("Heritability"),align="center", Class="fs13 b1 cbw c222",nowrap="yes"),HT.TD("%s" % heritability, nowrap="yes",align="center", Class="fs13 b1 cbw c222"))) - else: - pass + # This field needs to still be put into the Jinja2 template + st['heritability'] = heritability + #tbl.append(HT.TR(HT.TD(HT.Span("Heritability"),align="center", Class="fs13 b1 cbw c222",nowrap="yes"),HT.TD("%s" % heritability, nowrap="yes",align="center", Class="fs13 b1 cbw c222"))) + # Lei Yan # 2008/12/19 - return tbl + return st def plotNormalProbability(vals=None, RISet='', title=None, showstrains=0, specialStrains=[None], size=(750,500)): |