def plotPrecisionRecall(precision, recall, outFileName, Fig=None, drawCol=1, textLabel = None, title = None, fontsize1 = 24, fontsize2 = 20, linewidth = 3):
'''
:param precision:
:param recall:
:param outFileName:
:param Fig:
:param drawCol:
:param textLabel:
:param fontsize1:
:param fontsize2:
:param linewidth:
'''
clearFig = False
if Fig == None:
Fig = pylab.figure()
clearFig = True
#tableString = 'Algo avgprec Fmax prec recall accuracy fpr Q(TonITS)\n'
linecol = ['g','m','b','c']
#if we are evaluating SP, then BL is available
#sectionName = 'Evaluation_'+tag+'PxProb'
#fullEvalFile = os.path.join(eval_dir,evalName)
#Precision,Recall,evalString = readEvaluation(fullEvalFile,sectionName,AlgoLabel)
pylab.plot(100*recall, 100*precision, linewidth=linewidth, color=linecol[drawCol], label=textLabel)
#writing out PrecRecall curves as graphic
setFigLinesBW(Fig)
if textLabel!= None:
pylab.legend(loc='lower left',prop={'size':fontsize2})
if title!= None:
pylab.title(title, fontsize=fontsize1)
#pylab.title(title,fontsize=24)
pylab.ylabel('PRECISION [%]',fontsize=fontsize1)
pylab.xlabel('RECALL [%]',fontsize=fontsize1)
pylab.xlim(0,100)
pylab.xticks( [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100],
('0','','20','','40','','60','','80','','100'), fontsize=fontsize2 )
pylab.ylim(0,100)
pylab.yticks( [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100],
('0','','20','','40','','60','','80','','100'), fontsize=fontsize2 )
pylab.grid(True)
#
if type(outFileName) != list:
pylab.savefig( outFileName )
else:
for outFn in outFileName:
pylab.savefig( outFn )
if clearFig:
pylab.close()
Fig.clear()
python类xticks()的实例源码
def plotPrecisionRecall(precision, recall, outFileName, Fig=None, drawCol=1, textLabel = None, title = None, fontsize1 = 24, fontsize2 = 20, linewidth = 3):
'''
:param precision:
:param recall:
:param outFileName:
:param Fig:
:param drawCol:
:param textLabel:
:param fontsize1:
:param fontsize2:
:param linewidth:
'''
clearFig = False
if Fig == None:
Fig = pylab.figure()
clearFig = True
#tableString = 'Algo avgprec Fmax prec recall accuracy fpr Q(TonITS)\n'
linecol = ['g','m','b','c']
#if we are evaluating SP, then BL is available
#sectionName = 'Evaluation_'+tag+'PxProb'
#fullEvalFile = os.path.join(eval_dir,evalName)
#Precision,Recall,evalString = readEvaluation(fullEvalFile,sectionName,AlgoLabel)
pylab.plot(100*recall, 100*precision, linewidth=linewidth, color=linecol[drawCol], label=textLabel)
#writing out PrecRecall curves as graphic
setFigLinesBW(Fig)
if textLabel!= None:
pylab.legend(loc='lower left',prop={'size':fontsize2})
if title!= None:
pylab.title(title, fontsize=fontsize1)
#pylab.title(title,fontsize=24)
pylab.ylabel('PRECISION [%]',fontsize=fontsize1)
pylab.xlabel('RECALL [%]',fontsize=fontsize1)
pylab.xlim(0,100)
pylab.xticks( [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100],
('0','','20','','40','','60','','80','','100'), fontsize=fontsize2 )
pylab.ylim(0,100)
pylab.yticks( [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100],
('0','','20','','40','','60','','80','','100'), fontsize=fontsize2 )
pylab.grid(True)
#
if type(outFileName) != list:
pylab.savefig( outFileName )
else:
for outFn in outFileName:
pylab.savefig( outFn )
if clearFig:
pylab.close()
Fig.clear()
def plotPrecisionRecall(precision, recall, outFileName, Fig=None, drawCol=1, textLabel = None, title = None, fontsize1 = 24, fontsize2 = 20, linewidth = 3):
'''
:param precision:
:param recall:
:param outFileName:
:param Fig:
:param drawCol:
:param textLabel:
:param fontsize1:
:param fontsize2:
:param linewidth:
'''
clearFig = False
if Fig == None:
Fig = pylab.figure()
clearFig = True
#tableString = 'Algo avgprec Fmax prec recall accuracy fpr Q(TonITS)\n'
linecol = ['g','m','b','c']
#if we are evaluating SP, then BL is available
#sectionName = 'Evaluation_'+tag+'PxProb'
#fullEvalFile = os.path.join(eval_dir,evalName)
#Precision,Recall,evalString = readEvaluation(fullEvalFile,sectionName,AlgoLabel)
pylab.plot(100*recall, 100*precision, linewidth=linewidth, color=linecol[drawCol], label=textLabel)
#writing out PrecRecall curves as graphic
setFigLinesBW(Fig)
if textLabel!= None:
pylab.legend(loc='lower left',prop={'size':fontsize2})
if title!= None:
pylab.title(title, fontsize=fontsize1)
#pylab.title(title,fontsize=24)
pylab.ylabel('PRECISION [%]',fontsize=fontsize1)
pylab.xlabel('RECALL [%]',fontsize=fontsize1)
pylab.xlim(0,100)
pylab.xticks( [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100],
('0','','20','','40','','60','','80','','100'), fontsize=fontsize2 )
pylab.ylim(0,100)
pylab.yticks( [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100],
('0','','20','','40','','60','','80','','100'), fontsize=fontsize2 )
pylab.grid(True)
#
if type(outFileName) != list:
pylab.savefig( outFileName )
else:
for outFn in outFileName:
pylab.savefig( outFn )
if clearFig:
pylab.close()
Fig.clear()
def drawMembersCMD(self,data):
ax = plt.gca()
if isinstance(data,basestring):
filename = data
data = pyfits.open(filename)[1].data
xmin, xmax = -0.25,0.25
ymin, ymax = -0.25,0.25
mmin, mmax = 16., 24.
cmin, cmax = -0.5, 1.0
mbins = np.linspace(mmin, mmax, 150)
cbins = np.linspace(cmin, cmax, 150)
mag_1 = data[self.config['catalog']['mag_1_field']]
mag_2 = data[self.config['catalog']['mag_2_field']]
x_prob, y_prob = sphere2image(self.ra, self.dec, data['RA'], data['DEC'])
sel = (x_prob > xmin)&(x_prob < xmax) & (y_prob > ymin)&(y_prob < ymax)
sel_prob = data['PROB'][sel] > 5.e-2
index_sort = numpy.argsort(data['PROB'][sel][sel_prob])
plt.scatter(data['COLOR'][sel][~sel_prob], mag_1[sel][~sel_prob],
marker='o',s=2,c='0.75',edgecolor='none')
sc = pylab.scatter(data['COLOR'][sel][sel_prob][index_sort], mag_1[sel][sel_prob][index_sort],
c=data['PROB'][sel][sel_prob][index_sort],
marker='o', s=10, edgecolor='none', cmap='jet', vmin=0., vmax=1)
pylab.xlim(cmin, cmax)
pylab.ylim(mmax, mmin)
pylab.xlabel(r'$g - r$')
pylab.ylabel(r'$g$')
#axes[1].yaxis.set_major_locator(MaxNLocator(prune='lower'))
pylab.xticks([-0.5, 0., 0.5, 1.])
pylab.yticks(numpy.arange(mmax - 1., mmin - 1., -1.))
ugali.utils.plotting.drawIsochrone(self.isochrone, c='k', zorder=10)
pylab.text(0.05, 0.95, r'$\Sigma p_{i} = %i$'%(data['PROB'].sum()),
fontsize=10, horizontalalignment='left', verticalalignment='top', color='k', transform=pylab.gca().transAxes,
bbox=dict(facecolor='white', alpha=1., edgecolor='none'))
divider = make_axes_locatable(pylab.gca())
ax_cb = divider.new_horizontal(size="7%", pad=0.1)
plt.gcf().add_axes(ax_cb)
pylab.colorbar(sc, cax=ax_cb, orientation='vertical', ticks=[0, 0.2, 0.4, 0.6, 0.8, 1.0], label='Membership Probability')
ax_cb.yaxis.tick_right()
