本文整理汇总了Python中pylab.figtext函数的典型用法代码示例。如果您正苦于以下问题：Python figtext函数的具体用法？Python figtext怎么用？Python figtext使用的例子？那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了figtext函数的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: regressionANN
def regressionANN(mypathforResults,predicted,observed,regress,variable_to_fill, Site_ID,units,list_out,index_str):
for index, item in enumerate(list_out):
fig=pl.figure(4, figsize=(16, 12), dpi=80, facecolor='w', edgecolor='k')
ANN_label=str(item+"_NN")
graphtext1=str('slope ' + str("{0:.2f}".format(regress[index][0])) +'\n' +
'intercept ' + str("{0:.2f}".format(regress[index][1])) +'\n' +
'r-value ' + str("{0:.2f}".format(regress[index][2])) +'\n' +
'p-value ' + str("{0:.2f}".format(regress[index][3])) +'\n' +
'slope SE ' + str("{0:.2f}".format(regress[index][4])) +'\n' +
'estim. SE ' + str("{0:.2f}".format(regress[index][5])) )
pl.figtext(0.7,0.6,graphtext1, bbox=dict())
pl.plot(observed[:,index], predicted[:,index], 'o', label='targets vs. outputs')
slope = regress[index][0]; intercept = regress[index][1]
x = np.linspace(min(observed[:,index]),max(observed[:,index]))
y = slope * x + intercept
pl.plot(x, y, linewidth = 2, label = 'regression line')
pl.legend()
pl.title('Tower vs ANN for '+item+' at ' +Site_ID+ ' index '+index_str)
pl.xlabel('Tower ' + '('+units+')')
pl.ylabel('ANN ' + '('+units+')')
pl.legend(shadow=True, fancybox=True,loc='best')
pl.savefig(mypathforResults+'/'+'Tower vs ANN for '+item+' at ' +Site_ID+ ' index '+index_str)
#pl.show()
pl.close(4)
time.sleep(2)示例2: OnCalcShift
def OnCalcShift(self, event):
if (len(self.PSFLocs) > 0):
import pylab
x,y,z = self.PSFLocs[0]
z_ = numpy.arange(self.image.data.shape[2])*self.image.mdh['voxelsize.z']*1.e3
z_ -= z_.mean()
pylab.figure()
p_0 = 1.0*self.image.data[x,y,:,0].squeeze()
p_0 -= p_0.min()
p_0 /= p_0.max()
#print (p_0*z_).sum()/p_0.sum()
p0b = numpy.maximum(p_0 - 0.5, 0)
z0 = (p0b*z_).sum()/p0b.sum()
p_1 = 1.0*self.image.data[x,y,:,1].squeeze()
p_1 -= p_1.min()
p_1 /= p_1.max()
p1b = numpy.maximum(p_1 - 0.5, 0)
z1 = (p1b*z_).sum()/p1b.sum()
dz = z1 - z0
print(('z0: %f, z1: %f, dz: %f' % (z0,z1,dz)))
pylab.plot(z_, p_0)
pylab.plot(z_, p_1)
pylab.vlines(z0, 0, 1)
pylab.vlines(z1, 0, 1)
pylab.figtext(.7,.7, 'dz = %3.2f' % dz)示例3: myplot_setlabel
def myplot_setlabel(xlabel=None,ylabel=None,title=None, label=None, xy=(0,0), ax=None, labsize=15,rightticks=False):
import matplotlib as mpl
mpl.rcParams['font.size'] = labsize+0.
# mpl.rcParams['font.family'] = 'serif'# New Roman'
mpl.rcParams['font.serif'] = 'Bitstream Vera Serif'
mpl.rcParams['axes.labelsize'] = labsize+1.
print labsize+1
mpl.rcParams['xtick.labelsize'] = labsize+0.
mpl.rcParams['ytick.labelsize'] = labsize+0.
if label:
print "######################## LABELS HERE##########################"
if xy==(0,0):
xy=(0.3,0.90)
if not ax:
print "WARNING: no axix, cannot place label"
pl.figtext(xy[0],xy[1],label, fontsize=labsize)
else:
pl.text(xy[0],xy[1],label, transform=ax.transAxes, fontsize=labsize)
if rightticks:
ax.yaxis.tick_right()
pl.xlabel(xlabel, fontsize=labsize+1)
pl.ylabel(ylabel, fontsize=labsize+1)
if title:
pl.title(title)示例4: dovis
def dovis(self):
"""
Do runtime visualization.
"""
pylab.clf()
phi = self.cc_data.get_var("phi")
myg = self.cc_data.grid
pylab.imshow(numpy.transpose(phi[myg.ilo:myg.ihi+1,
myg.jlo:myg.jhi+1]),
interpolation="nearest", origin="lower",
extent=[myg.xmin, myg.xmax, myg.ymin, myg.ymax])
pylab.xlabel("x")
pylab.ylabel("y")
pylab.title("phi")
pylab.colorbar()
pylab.figtext(0.05,0.0125, "t = %10.5f" % self.cc_data.t)
pylab.draw()示例5: buildAtmos
def buildAtmos(self, secz, xlim=[300, 1100], doPlot=False):
"""Generate the total atmospheric transmission profile at this airmass, using the coefficients C."""
# Burke paper says atmosphere put together as
# Trans_total (alt/az/time) = Tgray * (e^-Z*tau_aerosol(alt/az/t)) *
# * (1 - C_mol * BP(t)/BPo * A_mol(Z)) -- line 2
# * (1 - sqrt(C_mol * BP(t)/BPo) * A_mol(Z)) -- 3
# * (1 - C_O3 * A_O3(A) )
# * (1 - C_H2O(alt/az/time) * A_H2O(Z))
# Tau_aerosol = trans['aerosol'] ... but replace with power law (because here all 1's)
# typical power law index is about tau ~ lambda^-1
# A_mol = trans['O2']
# secz = secz of this observation
# wavelen / atmo_templates == building blocks of atmosphere, with seczlist / atmo_ind keys
# C = coeffsdictionary = to, t1, t2, alpha0 (for aerosol), C_mol, BP, C_O3, C_H2O values
if (abs(secz - self.secz) > interplimit):
print "Generating interpolated atmospheric absorption profiles for this airmass %f" %(secz)
self.interpolateSecz(secz)
BP0 = 782 # mb
# set aerosol appropriately with these coefficients
self.atmo_abs['aerosol'] = 1.0 - numpy.exp(-secz * (self.C['t0'] + self.C['t1']*0.0 + self.C['t2']*0.0)
* (self.wavelen/675.0)**self.C['alpha'])
# set total transmission, with appropriate coefficients
self.trans_total = numpy.ones(len(self.wavelen), dtype='float')
self.trans_total = self.trans_total * (1.0 - self.C['mol'] * self.C['BP']/BP0 * self.atmo_abs['rayleigh']) \
* ( 1 - numpy.sqrt(self.C['mol'] * self.C['BP']/BP0) * self.atmo_abs['O2']) \
* ( 1 - self.C['O3'] * self.atmo_abs['O3']) \
* ( 1 - self.C['H2O'] * self.atmo_abs['H2O']) \
* ( 1 - self.atmo_abs['aerosol'])
# now we can plot the atmosphere
if doPlot:
pylab.figure()
pylab.subplot(212)
colorindex = 0
for comp in self.atmo_ind:
pylab.plot(self.wavelen, self.atmo_abs[comp], colors[colorindex], label='%s' %(comp))
colorindex = self._next_color(colorindex)
leg =pylab.legend(loc=(0.88, 0.3), fancybox=True, numpoints=1, shadow=True)
ltext = leg.get_texts()
pylab.setp(ltext, fontsize='small')
coefflabel = ""
for comp in ('mol', 't0', 'alpha', 'O3', 'H2O'):
coefflabel = coefflabel + "C[%s]:%.2f " %(comp, self.C[comp])
if (comp=='alpha') | (comp=='mol'):
coefflabel = coefflabel + "\n"
pylab.figtext(0.2, 0.35, coefflabel, fontsize='small')
pylab.xlim(xlim[0], xlim[1])
pylab.ylim(0, 1.0)
pylab.xlabel("Wavelength (nm)")
pylab.subplot(211)
pylab.plot(self.wavelen, self.atmo_trans[self.seczToString(1.2)]['comb'], 'r-', label='Standard X=1.2 (no aerosols)')
pylab.plot(self.wavelen, self.trans_total, 'k-', label='Observed')
leg = pylab.legend(loc=(0.12, 0.05), fancybox=True, numpoints=1, shadow=True)
ltext = leg.get_texts()
pylab.setp(ltext, fontsize='small')
pylab.xlim(xlim[0], xlim[1])
pylab.ylim(0, 1.0)
pylab.title("Example Atmosphere at X=%.2f" %(secz))
return示例6: plotData
def plotData():
marr = fetchData()
textsize = 18
yticks([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], xt, size=textsize)
ylabel("Periode [s]", size=textsize)
xticks([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], yt, size=textsize)
xlabel("Ausstattung [%]", size=textsize)
title(
"Abweichung der Geschwindigkeit zwischen FCD und des simulierten Verkehrs", size=textsize)
# title("Relative Anzahl erfasster Kanten", size=textsize)
figtext(0.7865, 0.92, '[%]', size=textsize)
# levels=arange(mmin-mmin*.1, mmax+mmax*.1, (mmax-mmin)/10.))
contourf(marr, 50)
# set fontsize and ticks for the colorbar:
if showVal == EDGENO:
cb = colorbar(ticks=[0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100])
else:
# cb = colorbar(ticks=range(17))
cb = colorbar()
for t in cb.ax.get_yticklabels(): # set colorbar fontsize of each tick
t.set_fontsize(textsize)
show()示例7: feature_label
def feature_label(self, data):
f = data[0]
s = data[1]
base_x = 0.88
base_y = 0.74
for i in range(0, len(data[0])):
pl.figtext(base_y, base_x-0.05*i, '{} -> {}'.format(f[i], s[i]))示例8: gen_hrf
def gen_hrf(self):
m_A, q_Z, mu_k, m_H, sigma_k, width, height, hrf0 = self.analy.Vbjde()
fgs = self.ConditionalNRLHist(m_A, q_Z)
MMin = -1.0 # Y.min()
MMax = 1.0 # Y.max()
pas = (MMax - MMin) / 100
xx = arange(MMin, MMax, pas)
nf = 1
g0 = self.gaussian(xx, mu_k[0][0], sigma_k[0][0])
g1 = self.gaussian(xx, mu_k[0][1], sigma_k[0][1])
print (g0, g1)
fgs.insert(0, figure((self.nf + 1) * 123))
title("Fonction de reponse", fontsize='xx-large')
figtext(0.2, 0.04,
'bande = ' + str(self.bande)+
' beta =' + str(self.beta) +
' sigma = ' + str(self.sigmaH) +
' pl = ' + str(self.pl) +
' dt = ' + str(self.dt) +
' thrf = ' + str(self.Thrf),
#'mu_k = '+ str(self.mu_k) +
#'sigma_k = '+ str(self.sigma_k),
fontsize='x-large')
plot(m_H)
if self.shower == 1:
show()
return fgs示例9: main
def main(args):
if len(args) != 3:
print "Usage: python plots.py <results file> <start time> <end time>"
sys.exit()
fh = open(args[0], "r")
l = fh.readline().split()
N = int(l[0])
T = int(l[1])
step = int(l[2])
mean_c = float(l[3])
ts = int(args[1]) / step
td = int(args[2]) / step + step
x = range(0, T + step, step)
cl = []
for line in fh.readlines():
c = float(line)
cl.append(c)
fh.close()
# Time evolution of the fraction of cooperators.
pylab.figure(1, figsize = (7, 4.5), dpi = 500)
pylab.xlabel(r"$t$")
pylab.ylabel(r"$x$")
pylab.plot(x[ts:td], cl[ts:td], "#000000", alpha = 0.6, linewidth = 2.0)
pylab.figtext(0.82, 0.85, r"$x_\infty = %4.3f$" %(mean_c),
ha = 'center', va = 'center',
bbox = dict(facecolor = 'white', edgecolor = 'black'))
pylab.xlim(int(args[1]), int(args[2]))
pylab.ylim(0, 1)
ax = pylab.gca()
ax.xaxis.major.formatter.set_powerlimits((0,0))
pylab.savefig("plot.pdf", format = "pdf")
pylab.close(1)示例10: add_label
def add_label(self, feature_result, min_feature_label):
base_x = 0.88
base_y = 0.74
for i in range(0, len(feature_result)):
x1 = feature_result[i]
x2 = min_feature_label[i]
pl.figtext(base_y, base_x-0.05*i, '{} -> [{}]'.format(x1, x2))示例11: showImage
def showImage(self, xlim=None, ylim=None, clims=None, cmap=None, copy=False, stats=True):
if copy:
# useful if you're going to apply a hanning filter or something later, but
# want to keep an imge of the original
image = numpy.copy(self.image)
else:
image = self.image
pylab.figure()
pylab.title('Image')
if xlim == None:
x0 = 0
x1 = self.nx
else:
x0 = xlim[0]
x1 = xlim[1]
if ylim == None:
y0 = 0
y1 = self.ny
else:
y0 = ylim[0]
y1 = ylim[1]
if clims == None:
pylab.imshow(image, origin='lower', cmap=cmap)
else:
pylab.imshow(image, origin='lower', vmin=clims[0], vmax=clims[1], cmap=cmap)
pylab.xlabel('X')
pylab.ylabel('Y')
cb = pylab.colorbar()
clims = cb.get_clim()
pylab.xlim(x0, x1)
pylab.ylim(y0, y1)
if stats:
statstxt = 'Mean/Stdev/Min/Max:\n %.2f/%.2f/%.2f/%.2f' %(numpy.mean(image), numpy.std(image), image.min(), image.max())
pylab.figtext(0.75, 0.03, statstxt)
return clims示例12: display_settings
def display_settings(self):
from pylab import figtext
assert self.search
search = self.search
figtext(.01,.99,search.str_graph_fixed(), va='top',fontsize='medium')
figtext(.35, .99, search.str_graph_used(), va='top',fontsize='medium')示例13: test_varying_inclination
def test_varying_inclination(self):
#""" Test that the waveform is consistent for changes in inclination
#"""
sigmas = []
incs = numpy.arange(0, 21, 1.0) * lal.PI / 10.0
for inc in incs:
# WARNING: This does not properly handle the case of SpinTaylor*
# where the spin orientation is not relative to the inclination
hp, hc = get_waveform(self.p, inclination=inc)
s = sigma(hp, low_frequency_cutoff=self.p.f_lower)
sigmas.append(s)
f = pylab.figure()
pylab.axes([.1, .2, 0.8, 0.70])
pylab.plot(incs, sigmas)
pylab.title("Vary %s inclination, $\\tilde{h}$+" % self.p.approximant)
pylab.xlabel("Inclination (radians)")
pylab.ylabel("sigma (flat PSD)")
info = self.version_txt
pylab.figtext(0.05, 0.05, info)
if self.save_plots:
pname = self.plot_dir + "/%s-vary-inclination.png" % self.p.approximant
pylab.savefig(pname)
if self.show_plots:
pylab.show()
else:
pylab.close(f)
self.assertAlmostEqual(sigmas[-1], sigmas[0], places=7)
self.assertAlmostEqual(max(sigmas), sigmas[0], places=7)
self.assertTrue(sigmas[0] > sigmas[5])示例14: do_panel
def do_panel(condition, refcondition, figtitle, cursor, band='r'):
cmd = "select a.BT, f.flag, a.r_bulge, a.n_bulge, a.ba_bulge, a.ba_disk, c.z from CAST as c, Flags_catalog as f, {band}_band_serexp as a, gz2_flags as z where a.galcount = c.galcount and a.galcount = f.galcount and a.galcount = z.galcount and f.band='{band}' and f.model='serexp' and f.ftype ='u' and {condition};"
#a.r_bulge,
BT, flags, r_bulge, n_bulge,ba_bulge,ba_disk, zspec =cursor.get_data(cmd.format(condition=condition, band=band))
ref_BT,ref_flag, ref_rb, ref_nb, ref_ba,ref_badisk, ref_zspec = cursor.get_data(cmd.format(condition=refcondition, band=band))
BT = np.array(BT)
flags = np.array(flags, dtype=int)
r_bulge = np.array(r_bulge)
n_bulge= np.array(n_bulge)
ba_bulge= np.array(ba_bulge)
ba_disk= np.array(ba_disk)
zspec = np.array(zspec)
ref_BT = np.array(ref_BT)
ref_flag = np.array(ref_flag, dtype=int)
ref_rb = np.array(ref_rb)
ref_nb= np.array(ref_nb)
ref_ba= np.array(ref_ba)
ref_badisk= np.array(ref_badisk)
ref_zspec = np.array(ref_zspec)
panel_plot(BT, flags, r_bulge, n_bulge,ba_bulge,ba_disk,
ref_BT,ref_flag, ref_rb, ref_nb, ref_ba,ref_badisk,
zspec, ref_zspec)
pl.figtext(0.5, 0.95, figtitle)
print figtitle+' ',BT.size, ' objects'
pl.savefig('bar_params_serexp_%s.eps' %band)
#pl.savefig('bar_z_serexp.eps')
return示例15: plot_Rnl
def plot_Rnl(self,filename=None):
""" Plot radial wave functions with matplotlib.
filename: output file name + extension (extension used in matplotlib)
"""
if pl==None:
raise AssertionError('pylab could not be imported')
rmax = data[self.symbol]['R_cov']/0.529177*3
ri = np.where( self.rgrid<rmax )[0][-1]
states=len(self.list_states())
p = np.ceil(np.sqrt(states)) #p**2>=states subplots
fig=pl.figure()
i=1
# as a function of grid points
for n,l,nl in self.list_states():
ax=pl.subplot(2*p,p,i)
pl.plot(self.Rnlg[nl])
pl.yticks([],[])
pl.xticks(size=5)
# annotate
c = 'k'
if nl in self.valence:
c='r'
pl.text(0.5,0.4,r'$R_{%s}(r)$' %nl,transform=ax.transAxes,size=15,color=c)
if ax.is_first_col():
pl.ylabel(r'$R_{nl}(r)$',size=8)
i+=1
# as a function of radius
i = p**2+1
for n,l,nl in self.list_states():
ax=pl.subplot(2*p,p,i)
pl.plot(self.rgrid[:ri],self.Rnlg[nl][:ri])
pl.yticks([],[])
pl.xticks(size=5)
if ax.is_last_row():
pl.xlabel('r (Bohr)',size=8)
c = 'k'
if nl in self.valence:
c='r'
pl.text(0.5,0.4,r'$R_{%s}(r)$' %nl,transform=ax.transAxes,size=15,color=c)
if ax.is_first_col():
pl.ylabel(r'$R_{nl}(r)$',size=8)
i+=1
file = '%s_KSAllElectron.pdf' %self.symbol
#pl.rc('figure.subplot',wspace=0.0,hspace=0.0)
fig.subplots_adjust(hspace=0.2,wspace=0.1)
s=''
if self.confinement!=None:
s='(confined)'
pl.figtext(0.4,0.95,r'$R_{nl}(r)$ for %s-%s %s' %(self.symbol,self.symbol,s))
if filename is not None:
file = filename
pl.savefig(file)