def plotCorrelation(self,
x,
y,
labels=None,
key='Mutations',
title='',
xlabel='Predicted',
ylabel='Experimental',
ms=5,
err=None,
axeslabels=True,
plotname=None,
stats=True,
side=LEFT,
ax=None):
"""Show exp vs pred. for a set of x-y values """
#check if x and y are number cols and round
x = [round(float(i), 2) for i in x]
y = [round(float(i), 2) for i in y]
if min(x) < min(y): a = min(x) - 2
else: a = min(y) - 4
if max(x) > max(y): b = max(x) + 2
else: b = max(y) + 4
colors = ['b', 'g', 'r', 'y', 'm', 'c']
if ax == None:
fig = plt.figure(figsize=(6, 6))
ax = fig.add_subplot(111)
else:
#fig = ax.get_figure()
fig = None
if axeslabels == True:
ax.set_xlabel(xlabel)
ax.set_ylabel(ylabel)
legs = []
legnames = []
bad = []
good = []
if len(x) == 0:
return
errs = [i - j for i, j in zip(x, y)]
line = ax.plot(x,
y,
'o',
mew=0,
ms=ms,
alpha=0.6,
label=plotname,
picker=3)
#draw expected correlation line with slope x
slope = 1
#set range of axes
ax.plot((a, b), (a, b), 'g')
ax.axhline(y=0, color='grey')
ax.axvline(x=0, color='grey')
ax.set_xlim(a, b)
ax.set_ylim(a, b)
ax.set_title(title)
if err != None:
ax.plot((a, b), (a + err, b + err), '--', color='g')
ax.plot((a, b), (a - err, b - err), '--', color='g')
if stats == True:
self.addStats(ax, x, y)
if fig != None:
fig.suptitle('Predicted vs Experimental')
from PEATDB.Actions import DBActions
frame = DBActions.showTkFigure(fig, side=side)
#mh = MouseHandler(ax, self, labels, key)
#mh.connect()
mh = self.addMouseHandler(ax, labels, key)
else:
mh = frame = None
return ax, frame, mh
def plotCorrelation(self, x, y, labels=None,
key='Mutations',
title='',
xlabel='Predicted',
ylabel='Experimental', ms=5,
err=None, axeslabels=True,
plotname=None, stats=True,
side=LEFT, ax=None):
"""Show exp vs pred. for a set of x-y values """
#check if x and y are number cols and round
x=[round(float(i),2) for i in x]
y=[round(float(i),2) for i in y]
if min(x)<min(y): a=min(x)-2
else: a=min(y)-4
if max(x)>max(y): b=max(x)+2
else: b=max(y)+4
colors = ['b','g','r','y','m','c']
if ax==None:
fig = plt.figure(figsize=(6,6))
ax = fig.add_subplot(111)
else:
#fig = ax.get_figure()
fig = None
if axeslabels==True:
ax.set_xlabel(xlabel)
ax.set_ylabel(ylabel)
legs=[]; legnames=[]
bad=[]; good=[]
if len(x) ==0:
return
errs = [i - j for i, j in zip(x, y)]
line = ax.plot(x, y, 'o', mew=0, ms=ms,
alpha=0.6, label=plotname,
picker=3)
#draw expected correlation line with slope x
slope=1
#set range of axes
ax.plot((a,b),(a,b),'g')
ax.axhline(y=0, color='grey'); ax.axvline(x=0,color='grey')
ax.set_xlim(a,b); ax.set_ylim(a,b)
ax.set_title(title)
if err!=None:
ax.plot((a,b),(a+err,b+err),'--',color='g')
ax.plot((a,b),(a-err,b-err),'--',color='g')
if stats==True:
self.addStats(ax,x,y)
if fig!=None:
fig.suptitle('Predicted vs Experimental')
from PEATDB.Actions import DBActions
frame = DBActions.showTkFigure(fig, side=side)
#mh = MouseHandler(ax, self, labels, key)
#mh.connect()
mh = self.addMouseHandler(ax, labels, key)
else:
mh = frame = None
return ax, frame, mh
