def _plot(self, x_list, y_list, x_range, y_range): self.no_of_curves += 1 if self.no_of_curves==1: r.plot(x_list, y_list, type='o',pch='*',xlab='dataset no.',xlim=x_range,ylim=y_range, \ ylab='expression value', col=self.no_of_curves) else: r.lines(x_list, y_list, type='o',pch='*',col=self.no_of_curves)
def rplot(data, par={}, title={}, xlab="", ylab=""):
r.plot_new()
xmax = -1e6
xmin = 1e6
ymax = -1e6
ymin = 1e6
for x in data:
#print x[0]
#print x[1]
xmax = max(xmax, max(x[0]))
xmin = min(xmin, min(x[0]))
ymax = max(ymax, max(x[1]))
ymin = min(ymin, min(x[1]))
#print xmin, xmax, ymin, ymax
r.plot_window(xlim=(xmin, xmax), ylim=(ymin, ymax))
r.title(
main=title.get("main", ""),
xlab=title.get("xlab", ""),
ylab=title.get("ylab", ""))
r.box(col="black") ; r.axis(1) ; r.axis(2)
for i, x in enumerate(data):
r.lines(x[0], x[1], col=i+1, **par)
def _plot(self, row):
self.no_of_curves += 1
#position 3 in row is the varying value
self.varying_list.append(row[3])
x_list = []
y_list = []
self.curs.execute("select tp, tp_m, tp1, tp1_m, tn, fp, fp_m, fn from stat_plot_data where\
%s=%s and %s=%s and %s=%s and %s=%s and tag='%s' order by p_value_cut_off"%\
(self.option_num_dict[0].label, row[0], self.option_num_dict[1].label, row[1], self.option_num_dict[2].label,\
row[2], self.option_num_dict[3].label, row[3], row[4]))
plot_data = self.curs.fetchall()
for entry in plot_data:
tn = entry[4]
fn = entry[7]
if self.based_on_clusters:
#using the tp_m, tp1_m and fp_m
tp = entry[1]
tp1 = entry[3]
fp = entry[6]
else:
#using the tp, tp1, fp
tp = entry[0]
tp1 = entry[2]
fp = entry[5]
if self.l1:
#tp1 is counted as true positive
tp += tp1
else:
#tp1 is counted as false positive
fp += tp1
x_list.append(tp)
y_list.append(float(tp)/(tp+fp))
if self.no_of_curves==1:
r.plot(x_list, y_list, type='o',pch='*',xlab='consistent predictions',xlim=self.x_range,ylim=self.y_range, \
ylab='percentage', main='%s'%(self.option_num_dict[3].label), col=self.no_of_curves)
else:
r.lines(x_list, y_list, type='o',pch='*',col=self.no_of_curves)
def plotBundle(self, bundleD, full_filename, colorsD=None, bundlePointsD=None, legendL=None, title=None, y_max=None):
if y_max is None:
y_max = 0.4
if legendL is None:
legendL = bundleD.keys()
legendL.sort()
if title is None:
title = 'data'
bundleIdL = bundleD.keys()
bundleIdL.sort()
if colorsD is None:
colorsL = r.rainbow(len(bundleIdL))
colorsD = dict(zip(bundleIdL, colorsL))
colorsL = [colorsD[x] for x in bundleIdL]
time_min = min([len(bundleD[x]) for x in bundleD.keys()])
timeVec = [0.5 * x for x in range(time_min)]
try:
r.png(full_filename, width=800, height=600)
oldPar = r.par(xpd = True, mar = [x + y for (x,y) in zip(r.par()['mar'], [0,0,0,6])])
print 'plot %s' % full_filename
r.plot(timeVec, timeVec,
type='n',
main=title, ylim=(0, y_max),
xlab="time in hours after transfection", ylab="Relative Cell Counts",
pch=20, lwd=1, lty = 1,
cex=1.0, cex_lab=1.2, cex_main=1.5)
for bundleId in bundleIdL:
if not bundlePointsD is None:
r.points(timeVec, bundlePointsD[bundleId],
col=colorsD[bundleId], pch=20,
lwd=1)
r.lines(timeVec, bundlePointsD[bundleId],
col=colorsD[bundleId],
lwd=1, lty = 1)
r.lines(timeVec, bundleD[bundleId],
col=colorsD[bundleId],
lwd=3, lty = 1)
r.legend(max(timeVec) * 1.1, y_max, legend=legendL, fill=colorsL, cex=1.0, bg= 'whitesmoke')
r.par(oldPar)
r.grid(col="darkgrey")
r.dev_off()
except:
r.dev_off()
print full_filename + ' has not been printed.'
return
from rpy import r
# first plot
x = range(1,11)
y = [i**2 for i in x]
r.plot(x, y, xlab='x', ylab='y', main='My first plot',
pch=21, col='blue', bg='lightblue', type='o')
# second plot
x = range(1,11)
y = [i**2 for i in x]
z = [i**3 for i in x]
r.plot(x, y, main='My second plot', xlab='x', ylab='y', type='l', col='blue')
r.lines(x, z, col='red')
# cosine function, save to file
import math
r.png('cosine.png')
x = r.seq(0,50, by=0.1)
y = [math.cos(i) for i in x]
r.plot(x, y, main='COS(X)', xlab='x', ylab='cos(x)', type='l', col='blue')
r.dev_off()
# histogram
x = range(10) + range(3,6) + range(5,10)
r.hist(x, main='A histogram', xlab='x', col='lightblue')
# adust plotting area
from rpy import r
def myhist(lnw, color="black", makenewplot=True, main=None, bins=None, support=None, xlab=None, ylab="", sub=None, xmin=None, xmax=None, bin_numbers=True):
nbins = len(lnw)
if bins!=None:
assert(nbins==len(bins)-1)
xss = [[]]
yss = [[]]
xlim = None
connect_to_prev = False
if bins==None:
for bin in range(nbins):
if (lnw[bin] > -inf or lnw[bin] < inf) and (support==None or support[bin]) and (xmin==None or xmin<=bin) and (xmax==None or (bin+1)<=xmax):
xss[-1] += [bin, bin+1]
yss[-1] += [lnw[bin], lnw[bin]]
elif xss[-1]!=[]:
xss.append([])
yss.append([])
if xmin==None and xmax==None:
xlim = (0, nbins+1)
else:
xs = reduce(operator.add, xss, [])
xlim = (min(xs), max(xs))
else:
for bin in range(nbins):
if (lnw[bin] > -inf or lnw[bin] < inf) and (support==None or support[bin]) and (xmin==None or xmin<=bins[bin]) and (xmax==None or bins[bin+1]<=xmax):
xss[-1] += [bins[bin], bins[bin+1]]
yss[-1] += [lnw[bin], lnw[bin]]
elif xss[-1]!=[]:
xss.append([])
yss.append([])
if xmin==None and xmax==None:
xlim = (bins[0], bins[-1])
else:
xs = reduce(operator.add, xss, [])
xlim = (min(xs), max(xs))
# Do the plotting
if makenewplot:
r.plot_new()
ys = reduce(operator.add, yss, [])
ymin = min(ys)
ymax = max(ys)
r.plot_window(xlim=xlim, ylim=(ymin, ymax))
if bins!=None and bin_numbers:
labels = array(r.pretty(range(nbins), 8), dtype=int)
labels = labels[(0<=labels) & (labels<nbins)]
ats = bins[labels]
r.axis(1)
r.axis(1, tick=False, labels=labels, at=ats, mgp=(3,2,0))
r.axis(2)
this_xlab = "E, bin"
else:
r.axis(1)
r.axis(2)
this_xlab = "E"
r.axis(1)
r.axis(2)
r.box()
r.title(ylab=ylab)
if xlab==None:
r.title(xlab=this_xlab)
else:
r.title(xlab=xlab)
if main!=None:
r.title(main=main)
if sub!=None:
r.title(sub=sub)
for (xs, ys) in zip(xss, yss):
r.lines(xs, ys, col=color, lwd=0.5)
return (xss, yss)
def plot(outfile, data, out_format='png'):
w = int(round(len(data)/4.0))
if out_format == 'png':
r.png(outfile, width=w*100, height=1000, res=72)
elif out_format == 'pdf':
r.pdf(outfile, width=w, height=10)
else:
raise Exception('Unrecognised format: ' + str(out_format))
print("total: " + str(len(data)))
series = []
points = {'translate': [], 'preprocessing': []}
for dat in data:
points['translate'].append(float(dat['translate']))
points['preprocessing'].append(float(dat['preprocessing']))
xlabels = []
for k, v in data[0].iteritems():
if k not in ["problem", 'translate', 'preprocessing']:
series.append(k)
points[k] = []
index = 0
for dat in data:
for k in series:
if dat[k] != 'no-plan':
points[k].append(float(dat[k]) + \
points['translate'][index] + \
points['preprocessing'][index])
else:
points[k].append(-1000)
xlabels.append(dat['problem'])
index += 1
max_value = max(iter([max(iter(points[k])) for k in series]))
yrange = (0, max_value)
legend_labels = []
x = [i for i in range(1,len(points['translate'])+1)]
y = [-1000 for i in x]
r.par(mar=(7,5,4,2))
r.plot(x, y, main='', xlab="", ylab='',
xaxt='n', yaxt='n', pch=0, ylim=yrange,
mgp=(5,1,0))
r.mtext("Problem", side=1, line=5)
r.mtext("CPU Time (s)", side=2, line=3)
pch_start = 1
pch_index = pch_start
# plotting "translate"
#r.plot(x, points['translate'], main='',
# xlab='', ylab='Time (s)',
# xaxt='n', yaxt='n',
# pch=0, ylim=yrange)
#legend_labels.append('translate')
r.lines(x, points['translate'], lty=1)
# preprocessing -- Removed since it's insignificant
#r.points(x, points['preprocessing'], pch=pch_index)
#pch_index =+ 1
# planner output
for k in series:
if k != 'translate' and k != 'preporcessing':
r.points(x, points[k], pch=pch_index)
pch_index += 1
legend_labels.append("FD+" + k.upper())
# put x-axis labels
for i in range(0, len(xlabels)):
r.axis(side=1, at=i+1, labels=xlabels[i], las=2)
# put y-axis labels
base, step = get_y_step(max_value)
print("base: " + str(base) + " -- step: " + str(step))
y = base
for i in range(0, step):
r.axis(side=2, at=y, labels=str(y), las=2)
y += base
# legend
r.legend(1, max_value, legend_labels, pch=[i for i in range(pch_start, pch_index)])
r.dev_off()
def plot(outfile, data, out_format='png'):
w = int(round(len(data) / 4.0))
if out_format == 'png':
r.png(outfile, width=w * 100, height=1000, res=72)
elif out_format == 'pdf':
r.pdf(outfile, width=w, height=10)
else:
raise Exception('Unrecognised format: ' + str(out_format))
print("total: " + str(len(data)))
series = []
points = {'translate': [], 'preprocessing': []}
for dat in data:
points['translate'].append(float(dat['translate']))
points['preprocessing'].append(float(dat['preprocessing']))
xlabels = []
for k, v in data[0].iteritems():
if k not in ["problem", 'translate', 'preprocessing']:
series.append(k)
points[k] = []
index = 0
for dat in data:
for k in series:
if dat[k] != 'no-plan':
points[k].append(float(dat[k]) + \
points['translate'][index] + \
points['preprocessing'][index])
else:
points[k].append(-1000)
xlabels.append(dat['problem'])
index += 1
max_value = max(iter([max(iter(points[k])) for k in series]))
yrange = (0, max_value)
legend_labels = []
x = [i for i in range(1, len(points['translate']) + 1)]
y = [-1000 for i in x]
r.par(mar=(7, 5, 4, 2))
r.plot(x,
y,
main='',
xlab="",
ylab='',
xaxt='n',
yaxt='n',
pch=0,
ylim=yrange,
mgp=(5, 1, 0))
r.mtext("Problem", side=1, line=5)
r.mtext("CPU Time (s)", side=2, line=3)
pch_start = 1
pch_index = pch_start
# plotting "translate"
#r.plot(x, points['translate'], main='',
# xlab='', ylab='Time (s)',
# xaxt='n', yaxt='n',
# pch=0, ylim=yrange)
#legend_labels.append('translate')
r.lines(x, points['translate'], lty=1)
# preprocessing -- Removed since it's insignificant
#r.points(x, points['preprocessing'], pch=pch_index)
#pch_index =+ 1
# planner output
for k in series:
if k != 'translate' and k != 'preporcessing':
r.points(x, points[k], pch=pch_index)
pch_index += 1
legend_labels.append("FD+" + k.upper())
# put x-axis labels
for i in range(0, len(xlabels)):
r.axis(side=1, at=i + 1, labels=xlabels[i], las=2)
# put y-axis labels
base, step = get_y_step(max_value)
print("base: " + str(base) + " -- step: " + str(step))
y = base
for i in range(0, step):
r.axis(side=2, at=y, labels=str(y), las=2)
y += base
# legend
r.legend(1,
max_value,
legend_labels,
pch=[i for i in range(pch_start, pch_index)])
r.dev_off()
