def addmodeldata(m):
value = []
value.append('')
for k in Observable:
#parameter.append(Observable[k])
if type(m.__dict__[k]) in (tuple, list):
val, err = m.__dict__[k]
if k == 'RAJ':
ra = RA(m.__dict__[k][0])
raerr = m.__dict__[k][1]
value.append('%s:%s:%s' % (ra.HH,ra.MM, parseerror(Decimal(ra.SS),Decimal(raerr))))
elif k == 'DECJ':
dec = Dec(m.__dict__[k][0])
decerr = m.__dict__[k][1]
value.append('%s:%s:%s' % (dec.dd,dec.mm, parseerror(Decimal(dec.ss),Decimal(decerr))))
else:
value.append(parseerror(*m.__dict__[k]))
else:
if k == 'DM':
value.append(parseerror(*aveDM(m)))
else:
value.append((m.__dict__[k]))
value.append('')
for k in Fixed:
#parameter.append(Fixed[k])
try:
value.append(parseerror(*m.__dict__[k]))
except:
if type(m.__dict__[k]) == type(''):
value.append(m.__dict__[k])
elif k == 'PEPOCH':
value.append(m.__dict__[k].quantize(50000))
elif k == 'OMDOT':
value.append(m.__dict__[k].quantize(Decimal(0.0001)))
else:
value.append(SF(globals()[k](m)))
#data = [parameter, value]
value.append('')
for k in Derived:
#parameter.append(Derived[k])
if k == 'PAASCNODE':
value.append(m.__dict__[k])
else:
try:
value.append(parseerror(*m.__dict__[k]))
except:
value.append(SF(globals()[k](m)))
return value
def addmodeldata(m):
value = []
value.append('')
for k in Observable:
if k == 'KIN':
try:
kin = float(m.__dict__[k][0])/180.*np.pi; kinerr = float(m.__dict__[k][1])/180.*np.pi
cosi = Decimal(str(np.cos(kin)))
dcosi = Decimal(str(np.sin(kin)*kinerr))
value.append(parseerror(*[cosi, dcosi]))
except:
k = 'SINI'
sini = float(m.__dict__[k][0]); dsini = float(m.__dict__[k][0])
cosi = np.sqrt(1 - sini**2)
dcosi = Decimal(str(np.abs(dsini*sini/cosi)))
cosi = Decimal(str(cosi))
value.append(parseerror(*[cosi, dcosi]))
#parameter.append(Observable[k])
elif type(m.__dict__[k]) in (tuple, list):
val, err = m.__dict__[k]
if k == 'RAJ':
ra = RA(m.__dict__[k][0])
raerr = m.__dict__[k][1]
value.append('%s:%s:%s' % (ra.HH,ra.MM, parseerror(Decimal(ra.SS),Decimal(raerr))))
elif k == 'DECJ':
dec = Dec(m.__dict__[k][0])
decerr = m.__dict__[k][1]
value.append('%s:%s:%s' % (dec.dd,dec.mm, parseerror(Decimal(dec.ss),Decimal(decerr))))
elif k == 'PBDOT':
if m.__dict__[k][0] < Decimal(1.e-10):
m.__dict__[k][0]/=Decimal(1.e-12)
m.__dict__[k][1]/=Decimal(1.e-12)
value.append(parseerror(*m.__dict__[k]))
else:
value.append(parseerror(*m.__dict__[k]))
else:
value.append(parseerror(*m.__dict__[k]))
else:
if k == 'DM':
value.append(parseerror(*aveDM(m)))
else:
value.append((m.__dict__[k]))
value.append('')
for k in Fixed:
#parameter.append(Fixed[k])
if k == 'OMDOT':
value.append(m.__dict__[k][0].quantize(Decimal(0.00001)))
elif not m.__dict__.has_key(k):
value.append('--')
else:
try:
value.append(parseerror(*m.__dict__[k]))
except:
if type(m.__dict__[k]) == type(''):
value.append(m.__dict__[k])
elif k == 'PEPOCH':
value.append(m.__dict__[k].quantize(50000))
elif k in ['RNAMP', 'RNIDX']:
value.append(m.__dict__[k].quantize(Decimal(0.001)))
else:
value.append(SF(globals()[k](m)))
#data = [parameter, value]
value.append('')
for k in Derived:
#parameter.append(Derived[k])
try:
value.append(parseerror(*m.__dict__[k]))
except:
if k == 'M1':
value.append(parseerror(*M1(m)))
else:
value.append(parseerror(*globals()[k](m)))
return value
value.append((m.__dict__[k]))
parameter.append(r'\textit{Fixed Parameters}')
value.append('')
for k in Fixed:
parameter.append(Fixed[k])
try:
value.append(parseerror(*m.__dict__[k]))
except:
if type(m.__dict__[k]) == type(''):
value.append(m.__dict__[k])
elif type(m.__dict__[k]) == type(m.__dict__['PEPOCH']):
value.append(m.__dict__[k].quantize(50000))
else:
value.append(SF(globals()[k](m)))
data = [parameter, value]
parameter.append(r'\textit{Derived Parameters}')
value.append('')
for k in Derived:
parameter.append(Derived[k])
try:
value.append(parseerror(*m.__dict__[k]))
except:
value.append(SF(globals()[k](m)))
data = [parameter, value]
table = deluxetable(Caption=Caption, colsetting='lc', colnames = colnames, data=data, label="tab:par", comments=['Numbers in parentheses indicate the uncertainties on the last digit(s). Uncertainties on parameters are estimated from a general least square fit using {\sc tempo}.', 'The averaged DM value; See Section 3.2 and Figure 2 for the more discussion.', 'See Figure 2 of \citealt{sns+05} for definition.'])
import numpy as np
from round import TexStyle as SF
#data = np.genfromtxt("g_rob.txt", dtypes=[('gx'), (), (), ()])
data = np.loadtxt("g_orb.txt", dtype='f')
print data.shape
g_x = data[:, 0]
g_y = data[:, 1]
print(g_x.mean(), np.std(g_x)), (g_y.mean(), np.std(g_y))
print SF([g_x.mean(), np.std(g_x)]), SF([g_y.mean(), np.std(g_y)])
def addmodeldata(m):
value = []
value.append('')
for k in Observable:
#parameter.append(Observable[k])
if type(m.__dict__[k]) in (tuple, list):
val, err = m.__dict__[k]
if k == 'RAJ':
ra = RA(m.__dict__[k][0])
raerr = m.__dict__[k][1]
value.append(
'%s:%s:%s' %
(ra.HH, ra.MM, parseerror(Decimal(ra.SS), Decimal(raerr))))
elif k == 'DECJ':
dec = Dec(m.__dict__[k][0])
decerr = m.__dict__[k][1]
value.append('%s:%s:%s' %
(dec.dd, dec.mm,
parseerror(Decimal(dec.ss), Decimal(decerr))))
elif k == 'PBDOT':
if m.__dict__[k][0] < Decimal(1.e-10):
m.__dict__[k][0] /= Decimal(1.e-12)
m.__dict__[k][1] /= Decimal(1.e-12)
value.append(parseerror(*m.__dict__[k]))
else:
value.append(parseerror(*m.__dict__[k]))
else:
value.append(parseerror(*m.__dict__[k]))
else:
if k == 'DM':
value.append(parseerror(*aveDM(m)))
else:
value.append((m.__dict__[k]))
value.append('')
for k in Fixed:
#parameter.append(Fixed[k])
if k == 'OMDOT':
value.append(m.__dict__[k][0].quantize(Decimal(0.00001)))
elif not m.__dict__.has_key(k):
value.append('--')
else:
try:
value.append(parseerror(*m.__dict__[k]))
except:
if type(m.__dict__[k]) == type(''):
value.append(m.__dict__[k])
elif k == 'PEPOCH':
value.append(m.__dict__[k].quantize(50000))
elif k in ['RNAMP', 'RNIDX', 'TNRedAmp', 'TNRedGam']:
value.append(m.__dict__[k].quantize(Decimal(0.001)))
else:
value.append(SF(globals()[k](m)))
#data = [parameter, value]
value.append('')
for k in Derived:
#parameter.append(Derived[k])
try:
value.append(parseerror(*m.__dict__[k]))
except:
if k == 'M1':
value.append(parseerror(*M1(m)))
else:
value.append(parseerror(*globals()[k](m)))
return value
#pf.PBDOT[0] *= Decimal('1.e-15')
#pf.PBDOT[1] *= Decimal('1.e-15')
Shl = Shlkovskii(pf)
Gal = Pbdot_Gal(pf)
GW = Pbdot_GW(pf)
Pbdot_exc_1713 = float(pf.PBDOT[0]) - Gal[0] - Shl[0] - GW[0]
Pbdot_Shl = Shl[0]
Pbdot_Shl_err = Shl[1]
Pbdot_Gal_val = Gal[0]
Pbdot_Gal_err = Gal[1]
Pbdot_exc_err = sqrt(float(pf.PBDOT[1])**2 + Gal[1]**2 + Shl[1]**2 + GW[1]**2)
print 'PSR ', pf.PSRJ
#print Pbdot_Shl_err, Pbdot_Gal_err, Pbdot_exc_err
#print M1(pf)
#print 'Pbdot_obs:', SF((float(pf.PBDOT[0])*1.e13, float(pf.PBDOT[1])*1.e13))
print 'Pbdot_obs:', SF((float(pf.PBDOT[0]), float(pf.PBDOT[1])))
print 'Pbdot_Shl:', SF((Pbdot_Shl, Pbdot_Shl_err))
print 'Pbdot_Gal:', SF((Pbdot_Gal_val, Pbdot_Gal_err))
#print 'Pbdot_exc:', SF((float(Pbdot_exc_1713)*1.e13, Pbdot_exc_err))
print 'Pbdot_exc:', SF((float(Pbdot_exc_1713), Pbdot_exc_err))
print 'Pbdot_GW:', SF(Pbdot_GW(pf))
#sys.exit(0)
PbdOPb1713 = float(Pbdot_exc_1713) / float(pf.PB[0]) / secperday
#PbdOPberr1713 = float(pf.PBDOT[1])/float(pf.PB[0])/secperday
PbdOPberr1713 = Pbdot_exc_err / float(pf.PB[0]) / secperday
print 'Pbdot/Pb [%s]:' % (pf.PSRJ), SF((PbdOPb1713, PbdOPberr1713))
#sys.exit(0)
PbdOPb1012 = -0.4e-14 / 0.60467271355 / secperday
def testSF(self):
self.assertEqual(SF(self.string),self.stringres)
self.assertEqual(SF(self.float),self.floatres)
self.assertEqual(SF(self.float1),self.float1res)
self.assertEqual(SF(self.float2),self.float2res)
self.assertEqual(SF(self.float3),self.float3res)
self.assertEqual(SF(self.tuple2),self.tuple2res)
self.assertEqual(SF(self.tuple2s),self.tuple2sres)
self.assertEqual(SF(self.tuple2a),self.tuple2ares)
self.assertEqual(SF(self.tuple2b),self.tuple2bres)
self.assertEqual(SF(self.tuple2c),self.tuple2cres)
self.assertEqual(SF(self.tuple2d),self.tuple2dres)
self.assertEqual(SF(self.tuple2e),self.tuple2eres)
self.assertEqual(SF(self.tuple2f),self.tuple2fres)
self.assertEqual(SF(self.tuple3),self.tuple3res)
self.assertEqual(SF(self.tuple3s),self.tuple3sres)
self.assertEqual(SF(self.tuple3a),self.tuple3ares)
self.assertEqual(SF(self.tuple3b),self.tuple3bres)
self.assertEqual(SF(self.tuple3c),self.tuple3cres)
self.assertEqual(SF(self.tuple3d),self.tuple3dres)
self.assertEqual(SF(self.tuple3e),self.tuple3eres)
self.assertEqual(SF(self.tuple3f),self.tuple3fres)
#self.assertEqual(SF(self.tuplewithstring),self.tuplewithstringres)
self.assertEqual(SF(self.tuple3jinwei),self.tuple3jinweires)
#self.assertEqual(SF(self.lists1),self.lists1res)
#self.assertEqual(SF(self.lists2),self.lists2res)
self.assertEqual(SF(self.tentotheone),self.tentotheoneres)
self.assertEqual(SF(self.verysmallerr),self.verysmallerrres)
self.assertEqual(SF(self.numsigdigittest, NumSigDigit=1),self.numsigdigittestres)
self.assertEqual(SF(self.numsigdigittest1, NumSigDigit=1),self.numsigdigittestres1)
self.assertEqual(SF(self.numsigdigittest2, NumSigDigit=1),self.numsigdigittestres2)
self.show(self.string,self.stringres)
self.show(self.float,self.floatres)
self.show(self.float1,self.float1res)
self.show(self.float2,self.float2res)
self.show(self.float3,self.float3res)
self.show(self.tuple2,self.tuple2res)
self.show(self.tuple2s,self.tuple2sres)
self.show(self.tuple2a,self.tuple2ares)
self.show(self.tuple2b,self.tuple2bres)
self.show(self.tuple2c,self.tuple2cres)
self.show(self.tuple2d,self.tuple2dres)
self.show(self.tuple2e,self.tuple2eres)
self.show(self.tuple2f,self.tuple2fres)
self.show(self.tuple3,self.tuple3res)
self.show(self.tuple3s,self.tuple3sres)
self.show(self.tuple3a,self.tuple3ares)
self.show(self.tuple3b,self.tuple3bres)
self.show(self.tuple3c,self.tuple3cres)
self.show(self.tuple3d,self.tuple3dres)
self.show(self.tuple3e,self.tuple3eres)
self.show(self.tuple3f,self.tuple3fres)
#self.show(self.tuplewithstring,self.tuplewithstringres)
self.show(self.tuple3jinwei,self.tuple3jinweires)
#self.show(self.lists1,self.lists1res)
#self.show(self.lists2,self.lists2res)
self.show(SF(self.tentotheone),self.tentotheoneres)
self.show(SF(self.verysmallerr),self.verysmallerrres)
self.show(SF(self.numsigdigittest, NumSigDigit=1),self.numsigdigittestres)
self.show(SF(self.numsigdigittest1, NumSigDigit=1),self.numsigdigittestres1)
self.show(SF(self.numsigdigittest2, NumSigDigit=1),self.numsigdigittestres2)
#pf = PARfile('./mcmcresult.par')
#pf = PARfile('./1713.Apr.par')
pf = PARfile('./Oct.T2.par')
if pf.PBDOT[0] > Decimal('1.e-10'):#tempo 1 units
pf.PBDOT[0] *= Decimal('1.e-12')
pf.PBDOT[1] *= Decimal('1.e-12')
from round import shortform as SF
Shl = Shlkovskii(pf)
Gal = Pbdot_Gal(pf)
GW = Pbdot_GW(pf)
if pf.__dict__.has_key('PSR'):
print pf.PSR
else:
print pf.PSRJ
print 'PBdot(shlkovskii):', SF(Shl)
print 'PBdot(Galaxtic):' , SF(Gal)
print 'PBdot(GW):', SF(GW)
pb_exc = (float(pf.PBDOT[0]) - Gal[0] - Shl[0] - GW[0]), sqrt(float(pf.PBDOT[1])**2 + Gal[1]**2 + Shl[1]**2 + GW[1]**2)
print "PBdot - PBdot(Galaxtic) - PBdot(shlkovskii) - PBdot(GW), PBdot_exc_err:",
print SF(pb_exc)
print float(pf.PBDOT[0]) - Gal[0] - Shl[0] - GW[0], sqrt(float(pf.PBDOT[1])**2 + Gal[1]**2 + Shl[1]**2 + GW[1]**2)
print "PBdot , PBdot(Galaxtic) + PBdot(shlkovskii) + PBdot(GW):",
print pf.PBDOT[0] , Shl[0]+Gal[0]+GW[0]
print "-PBdot_excess/PB/2 --> Gdot/G (95%):",
print SF((-1*pb_exc[0]/float(pf.PB[0])/secperday/2*secperyear, pb_exc[1]/float(pf.PB[0])/secperday*secperyear))
print ((pb_exc[0]/float(pf.PB[0])/secperday*secperyear, pb_exc[1]/float(pf.PB[0])/secperday*secperyear*2))
#print SF(( float((pf.PBDOT[0] - Pbdot_Gal(pf) - Decimal(Shlkovskii(pf)) )/ pf.PB[0]/ secperday) , float( pf.PBDOT[1]*2 / pf.PB[0]/ secperday ) ))
#Pbdot_exc_1713 = (pf.PBDOT[0] - Pbdot_Gal(pf) - Decimal(Shlkovskii(pf)) )
ddmers = data[3, ...]
#A,B,r,p,s = linregress(np.log(delays), np.log(ddmsqs))
a = axes([.62, .6, .25, .3])
def func(x, b, c):
return c * (x)**(b - 2)
popt, pcov = curve_fit(func, delays, ddmsqs)
popt, pcov = curve_fit(func, delays, ddmsqs, sigma=ddmers, p0=popt)
B, C = popt
Berr = np.sqrt(pcov[0, 0])
Cerr = np.sqrt(pcov[1, 1])
from round import shortform as SF
print 'beta:', SF((B, Berr)), 'C:', SF((C, Cerr))
x = np.linspace(10, 1.e4, 30)
y = func(x, B, C)
a.plot(x, y, 'k-')
#def Kfunc(x, c):
#return c*(x)**(11./3-2)
#popt, pcov = curve_fit(Kfunc, delays, ddmsqs, sigma=ddmers)
#C = popt[0]
#y = Kfunc(x, C)#Kolmogorov
#y = func(x, 11./3, C)#Kolmogorov
#a.plot(x,y, 'k--')
a.errorbar(delays, ddmsqs, xerr=biners, yerr=ddmers, fmt='ok')
a.semilogx()
a.semilogy()
ylim = (int(ymax / ybinwidth) + 1) * ybinwidth
axScatter.set_xlim((-xlim, xlim))
axScatter.set_ylim((-ylim, ylim))
xbins = np.arange(-xlim, xlim + xbinwidth, xbinwidth)
ybins = np.arange(-ylim, ylim + ybinwidth, ybinwidth)
axHistx.hist(x, bins=xbins, normed=1)
axHisty.hist(y, bins=ybins, orientation='horizontal', normed=1)
axHistx.plot(xbins, xkde.evaluate(xbins), 'r-')
axHisty.plot(ykde.evaluate(ybins), ybins, 'r-')
axHistx.plot(xbins, xpdf.pdf(xbins), 'g-')
axHisty.plot(ypdf.pdf(ybins), ybins, 'g-')
axHistx.set_xlim(axScatter.get_xlim())
axHisty.set_ylim(axScatter.get_ylim())
for t1 in axHistx.get_xticklabels():
t1.set_visible(False)
axHistx.set_yticks([0])
for t1 in axHisty.get_yticklabels():
t1.set_visible(False)
axHisty.set_xticks([0])
plt.draw()
plt.show()
from round import shortform as SF
print SF((xm, xsigma)), SF((ym, ysigma))