def venn_runner(dataset,outputfilename='vennrunner.txt',vennengine='',outputdir=''):
outputdir = os.path.abspath(outputdir)
outputfilename=os.path.join(outputdir,outputfilename)
logger.info('#########\nvenn run started#########\n')
if isinstance(dataset,list):
datadic=dict(dataset)
uniqueinfo=[]
commoninfo=[]
for i in range(0,len(datadic)):
for v in itertools.combinations(datadic.keys(),i+1):
combo=[set(datadic[x]) for x in v ]
tmp=combo[0]
excl=combo[0]
for ele in combo[1:]:
tmp=tmp&ele
excl=excl-ele
commoninfo.append((v,tmp))
uniqueinfo.append((v,excl))
tabinfo=[]
for name,ele in commoninfo:
logger.info('total in {name}: {lenset}'.format(name=' & '.join(name),lenset=len(ele)))
tabinfo.append(['_&_'.join(name)]+list(ele))
for name,ele in uniqueinfo:
logger.info('total in {name}: {lenset}'.format(name=' not '.join(name),lenset=len(ele)))
tabinfo.append([' not '.join(name)]+list(ele))
tabinfotrsp=fhutils.transpose(tabinfo,'')
out=open(outputfilename,'w')
for ele in tabinfotrsp:
out.write('\t'.join([str(x) for x in ele])+'\n')
out.close()
if vennengine=='evenn':
logger.error('NOT WORKING EVENN')
pyevenn(dataset,figurename=fhutils.renamefilename(outputfilename,midtag='_'+vennengine,suffix='png'),outputdir =outputdir)
elif vennengine=='rvenn':
pyrvenn(dataset,figurename=fhutils.renamefilename(outputfilename,midtag='_'+vennengine,suffix='tiff'),outputdir = outputdir)
elif vennengine=='venneuler':
pyvenneuler(dataset,figurename=fhutils.renamefilename(outputfilename,midtag='_'+vennengine,suffix='pdf'),outputdir=outputdir)
elif vennengine=='rvennerable':
logger.error('NOT WORKING rvennerable')
pyrvennerable(dataset,figurename=fhutils.renamefilename(outputfilename,midtag='_'+vennengine,suffix='pdf'),outputdir=outputdir)
else:
print 'no venn pdf'
def pynormtest(valuelis, numericvars=list(), filename='normtest_data.txt', gformat='pdf'):
rconsole = rpystatinit()
rnormcheck = rconsole("rnormcheck")
dataframe = pyobj2dataframe(valuelis)
from rpy2.robjects.packages import importr
grdevices = importr('grDevices')
grdevices.pdf(file=fhutils.renamefilename(filename, suffix=gformat))
data = rnormcheck(data=dataframe, numericvars=robjects.vectors.StrVector(tuple(numericvars)))
grdevices.dev_off()
out = open(filename, 'w')
out.write('\n'.join(
['######## glvma fit results ########', str(data[0]), '######## LM-fit results ########', str(data[1])]))
out.close()
def pyanova(table, formula, term, filename='anovaimage', gformat='pdf'):
from rpy2.robjects.packages import importr
rconsole=rpystatinit()
ranova = rconsole("ranova")
grdevices = importr('grDevices')
grdevices.pdf(file=fhutils.renamefilename(filename, suffix=gformat))
dataframe = pyobj2dataframe(table)
results = ranova(data=dataframe, formulastring=formula, term=term)
aovw = dataframe2pyobj(results[0])
tukey = dataframe2pyobj(results[1])
grdevices.dev_off()
return aovw, tukey
def pynlsfit(valuelis, formulastr='', startvalues=list(), filename='nlsfit.txt', gformat='pdf'):
"""
nonlinear fit of function to data
"""
rconsole = rpystatinit()
rnonlinfit = rconsole("rnonlinfit")
dataframe = pyobj2dataframe(valuelis)
from rpy2.robjects.packages import importr
grdevices = importr('grDevices')
graphplotfile = fhutils.renamefilename(filename, suffix=gformat)
grdevices.pdf(file=graphplotfile)
nlfit = rnonlinfit(data=dataframe, formulastr=formulastr, startvalues=robjects.ListVector(dict(startvalues)))
grdevices.dev_off()
nlfit = rlisttodic(nlfit)
return nlfit
def simpleheatmap(tabdata, figname='defaultheatplot.pdf', main='title',
colormode='jet', gformat='pdf', scale='none', dendrogram='both'):
"""
scale: none, row, both, col
"""
rconsole = rpy2.robjects.r
rsimpleheatmap = rconsole("rsimpleheatmap")
dopdfgraph = rconsole("dopdfgraph")
rdataframe = pyobj2dataframe(tabdata, rownames=True, columnames=True)
from rpy2.robjects.packages import importr
grdevices = importr('grDevices')
grdevices.pdf(file=fhutils.renamefilename(figname, suffix=gformat))
roworder = {'both': True, 'row': True, 'column': False}[dendrogram]
colorder = {'both': True, 'row': False, 'column': True}[dendrogram]
rsimpleheatmap(tabdata=rdataframe, scale=scale, dendros=dendrogram, roworder=roworder, colorder=colorder)
grdevices.dev_off()
def statoverview(valuelis, group='NA', filename='overview_data.txt', gformat='pdf'):
"""
overview statistics
R psych::describe which shows:
item name ,item number, nvalid, mean, sd,
median, mad, min, max, skew, kurtosis, se
"""
rconsole = rpystatinit()
rgeneralstats = rconsole("rgeneralstats")
dataframe = pyobj2dataframe(valuelis)
from rpy2.robjects.packages import importr
grdevices = importr('grDevices')
grdevices.pdf(file=fhutils.renamefilename(filename, suffix=gformat))
gdic = {'NA': rinterface.NARealType()}
group = gdic.get(group, group)
data = rgeneralstats(data=dataframe, group=group)
grdevices.dev_off()
out = open(filename, 'w')
out.write(str(data))
out.close()
def venn_runner(dataset,
outputfilename='vennrunner.txt',
vennengine='',
outputdir=''):
outputdir = os.path.abspath(outputdir)
outputfilename = os.path.join(outputdir, outputfilename)
logger.info('#########\nvenn run started#########\n')
if isinstance(dataset, list):
datadic = dict(dataset)
uniqueinfo = []
commoninfo = []
for i in range(0, len(datadic)):
for v in itertools.combinations(datadic.keys(), i + 1):
combo = [set(datadic[x]) for x in v]
tmp = combo[0]
excl = combo[0]
for ele in combo[1:]:
tmp = tmp & ele
excl = excl - ele
commoninfo.append((v, tmp))
uniqueinfo.append((v, excl))
tabinfo = []
for name, ele in commoninfo:
logger.info('total in {name}: {lenset}'.format(name=' & '.join(name),
lenset=len(ele)))
tabinfo.append(['_&_'.join(name)] + list(ele))
for name, ele in uniqueinfo:
logger.info('total in {name}: {lenset}'.format(name=' not '.join(name),
lenset=len(ele)))
tabinfo.append([' not '.join(name)] + list(ele))
tabinfotrsp = fhutils.transpose(tabinfo, '')
out = open(outputfilename, 'w')
for ele in tabinfotrsp:
out.write('\t'.join([str(x) for x in ele]) + '\n')
out.close()
if vennengine == 'evenn':
logger.error('NOT WORKING EVENN')
pyevenn(dataset,
figurename=fhutils.renamefilename(outputfilename,
midtag='_' + vennengine,
suffix='png'),
outputdir=outputdir)
elif vennengine == 'rvenn':
pyrvenn(dataset,
figurename=fhutils.renamefilename(outputfilename,
midtag='_' + vennengine,
suffix='tiff'),
outputdir=outputdir)
elif vennengine == 'venneuler':
pyvenneuler(dataset,
figurename=fhutils.renamefilename(outputfilename,
midtag='_' + vennengine,
suffix='pdf'),
outputdir=outputdir)
elif vennengine == 'rvennerable':
logger.error('NOT WORKING rvennerable')
pyrvennerable(dataset,
figurename=fhutils.renamefilename(outputfilename,
midtag='_' +
vennengine,
suffix='pdf'),
outputdir=outputdir)
else:
print 'no venn pdf'
