def plotMerged(self,
matrix,
expcol,
expdata=None,
title='',
showtable=True,
ax=None,
name=None,
stats=True):
"""Merge a set of exp vals with predictions and plot"""
if expdata == None:
expdata = self.parent.tablemodel.simpleCopy(include=['Mutations'])
merged = self.mergeMatrix(matrix, expdata)
x, y, names, muts = merged.getColumns(
['Total', expcol, 'name', 'Mutations'], allowempty=False)
from Correlation import CorrelationAnalyser
C = CorrelationAnalyser()
muts = ['mutation: ' + i for i in muts]
labels = zip(names, muts)
ax, frame, mh = C.plotCorrelation(x,
y,
labels,
title=title,
ylabel=expcol,
ax=ax,
plotname=name,
stats=stats,
err=4)
x = [round(float(i), 2) for i in x]
y = [round(float(i), 2) for i in y]
if showtable == True:
table = self.showTable(frame, merged)
mh.table = table
return ax, mh, x, y
def showAllResults(self):
"""Show results for single or multiple jobs together"""
names = self.jobstable.get_selectedRecordNames()
if len(names) == 1:
ax, mh, x, y = self.showResults()
else:
tx = []
ty = []
import pylab as plt
f = plt.figure(figsize=(8, 8))
ax = f.add_subplot(111)
for n in names:
a, mh, x, y = self.showResults(n,
showtable=False,
ax=ax,
stats=False)
tx.extend(x)
ty.extend(y)
ax.legend()
#add stats for summary
from Correlation import CorrelationAnalyser
C = CorrelationAnalyser()
C.addStats(ax, tx, ty)
f.show()
return
def plotMerged(self, matrix, expcol, expdata=None,
title='', showtable=True, ax=None, name=None,
stats=True):
"""Merge a set of exp vals with predictions and plot"""
if expdata==None:
expdata = self.parent.tablemodel.simpleCopy(include=['Mutations'])
merged = self.mergeMatrix(matrix, expdata)
x,y,names,muts = merged.getColumns(['Total',expcol,'name','Mutations'],allowempty=False)
from Correlation import CorrelationAnalyser
C = CorrelationAnalyser()
muts = ['mutation: '+i for i in muts]
labels = zip(names, muts)
ax,frame,mh = C.plotCorrelation(x,y,labels,title=title,ylabel=expcol,
ax=ax,plotname=name,stats=stats,err=4)
x=[round(float(i),2) for i in x]
y=[round(float(i),2) for i in y]
if showtable == True:
table = self.showTable(frame, merged)
mh.table = table
return ax,mh,x,y
def showAllResults(self):
"""Show results for single or multiple jobs together"""
names = self.jobstable.get_selectedRecordNames()
if len(names)==1:
ax,mh,x,y=self.showResults()
else:
tx=[]; ty=[]
import pylab as plt
f=plt.figure(figsize=(8,8))
ax=f.add_subplot(111)
for n in names:
a,mh,x,y = self.showResults(n,showtable=False, ax=ax,stats=False)
tx.extend(x)
ty.extend(y)
ax.legend()
#add stats for summary
from Correlation import CorrelationAnalyser
C = CorrelationAnalyser()
C.addStats(ax,tx,ty)
f.show()
return