def plotPRC(output, LTE, figure_fname = "", prc_label = 'PRC'):
"""Plots a precision recall curve into the supplied
figure_fname file"""
from matplotlib import use
use("Agg") # matplotlib save without display
from pylab import figure, plot, axis, xticks, yticks, ylabel, xlabel, legend, savefig
figure(2, dpi = 150, figsize = (4, 4))
pm = PerformanceMeasures(Labels(numpy.array(LTE)), Labels(numpy.array(output)))
points = pm.get_PRC()
points = numpy.array(points).T # for pylab.plot
plot(points[0], points[1], 'b-', label = prc_label)
axis([0, 1, 0, 1])
ticks = numpy.arange(0., 1., .1, dtype = numpy.float64)
xticks(ticks, size = 10)
yticks(ticks, size = 10)
xlabel('sensitivity (true positive rate)', size = 10)
ylabel('precision (1 - false discovery rate)', size = 10)
legend(loc = 'lower right')
if figure_fname != None:
warnings.filterwarnings('ignore', 'Could not match*')
tempfname = figure_fname + '.png'
savefig(tempfname)
shutil.move(tempfname, figure_fname)
auPRC = pm.get_auPRC()
return auPRC
def plotROC(output, LTE, draw_random = False, figure_fname = "", roc_label = 'ROC'):
"""Uses matplotlib to plot the area under
the ROC curve into a supplied figure_fname file"""
from matplotlib import use, font_manager
use("Agg") # matplotlib save without display
from pylab import figure, plot, xticks, yticks, xlabel, ylabel, legend, savefig, axis
figure(1, dpi = 150, figsize = (4, 4))
pm = PerformanceMeasures(Labels(numpy.array(LTE)), Labels(numpy.array(output)))
points = pm.get_ROC()
points = numpy.array(points).T # for pylab.plot
plot(points[0], points[1], 'b-', label = roc_label)
if draw_random:
plot([0, 1], [0, 1], 'r-', label = 'random guessing')
axis([0, 1, 0, 1])
ticks = numpy.arange(0., 1., .1, dtype = numpy.float64)
xticks(ticks, size = 10)
yticks(ticks, size = 10)
xlabel('1 - specificity (false positive rate)', size = 10)
ylabel('sensitivity (true positive rate)', size = 10)
legend(loc = 'lower right', prop = font_manager.FontProperties('tiny'))
if figure_fname != None:
warnings.filterwarnings('ignore', 'Could not match*')
tempfname = figure_fname + '.png'
savefig(tempfname)
shutil.move(tempfname, figure_fname)
auROC = pm.get_auROC()
return auROC
def calcPRC(output, LTE):
"""Uses shogun functions to calculate the precision recall curve"""
pm = PerformanceMeasures(Labels(numpy.array(LTE)), Labels(numpy.array(output)))
auPRC = pm.get_auPRC()
return auPRC
def calcROC(output, LTE):
"""Uses shogun functions to calculate the area under the ROC curve"""
pm = PerformanceMeasures(Labels(numpy.array(LTE)), Labels(numpy.array(output)))
auROC = pm.get_auROC()
return auROC
