In [ ]:
# Avaliation of the parameters
In [2]:
%matplotlib inline
import numpy as np
import corner
import itertools
import matplotlib.pyplot as plt
from func import *
from scipy import optimize as op
In [3]:
#First data
#data = astro.io.ascii.read('Inputs/data/rvs_0001.txt', names=['time','vel','err'])
data = np.loadtxt('Inputs/data/rvs_0001.txt')
obser = [data[:,0],data[:,1],data[:,2]]
In [140]:
n_mixture = 2
samples = np.genfromtxt('chains/0pd0001a_equal_weights.txt')
z=!sed -n '38p' chains/0pd0001a.resume
z=np.float(z[0])
mus0p001 = np.mean(samples[:, 2:], axis=0)
sigs = np.std(samples[:, 2:], axis=0)
fig = corner.corner(samples[:, 2:], ranges=[[0, 1]*(3*n_mixture-1)],labels=['C','J'],truths=mus0p001)
print('The values of C and J, and evidence', mus0p001,z)
WARNING:root:Too few points to create valid contours
The values of C and J, and evidence [-0.77305997 2.08848499] -487.09969
In [34]:
samples_runtime = np.genfromtxt('chains/0pd0001a_phys_live.txt')
samples_dead = np.genfromtxt('chains/0pd0001a_dead.txt')
plt.figure(1,figsize=(15,8))
plt.subplot(121)
plt.tick_params(labelsize=20)
plt.plot(samples_dead[:,1],samples_dead[:,2], 'bo')
plt.plot(samples_runtime[:,0],samples_runtime[:,1], 'ro')
plt.subplot(122)
plt.tick_params(labelsize=20)
plt.plot(samples_runtime[:,0],samples_runtime[:,1], 'ro');
In [35]:
x = data[:,0]
xm = np.arange(0,data[-1,0],data[-1,0]/1000)
y = data[:,1]
y0 = model(mus0p001,xm,0)
yerr = data[:,2]
# First illustrate basic pyplot interface, using defaults where possible.
plt.figure(figsize=(15,8))
#plt.xlabel('teste')
plt.xlabel('Time (s)', fontsize=20)
plt.ylabel('Star Radial velocity (m/s)', fontsize=20)
plt.errorbar(x, y, yerr=yerr,fmt='o')
plt.plot(xm,y0)
plt.tick_params(labelsize=20)
plt.title("Data0001",fontsize=30)
#plt.plot(x,y,'o')
plt.show()
In [7]:
z=!sed -n '38p' chains/0pd0001a.resume
z0pd0001a=np.float(z[0])*np.log10(np.e)
print('Nominal value:',z0pd0001a)
print('Relative value:', 1)
Nominal value: -211.544707504
Relative value: 1
In [53]:
n_plan = 1
samples_runtime = np.genfromtxt('chains/1pd0001a_phys_live.txt')
samples_dead = np.genfromtxt('chains/1pd0001a_dead.txt')
plt.figure(1,figsize=(15,8))
plt.subplot(121)
plt.tick_params(labelsize=20)
plt.plot(samples_dead[:,5*n_plan+1],samples_dead[:,5*n_plan+2], 'bo')
plt.plot(samples_runtime[:,5*n_plan],samples_runtime[:,5*n_plan+1], 'ro')
plt.subplot(122)
plt.tick_params(labelsize=20)
plt.plot(samples_runtime[:,5*n_plan],samples_runtime[:,5*n_plan+1], 'ro');
In [22]:
teste = (np.mean(np.sin(samples[:, 5:7]), axis=0),np.mean(np.cos(samples[:, 5:7]), axis=0))
print(teste)
(array([ 0.18316025, -0.27334614]), array([ 0.2488231 , -0.16404937]))
In [163]:
print(np.arctan2(0.18316025,0.2488231)%(2*np.pi))
print(np.arctan2(-0.27334614,-0.16404937)%(2*np.pi))
0.634549677541
4.17185735339
In [30]:
!cat chains/1pd0001a_equal_weights.txt
0.10000000E+001 0.86254546E+003 0.41741497E+002 0.25401989E+001 0.42859626E+000 0.32343009E+001 0.11521488E+001 -0.71134910E+000 0.13756458E+001
0.10000000E+001 0.85095202E+003 0.42301605E+002 0.23186119E+001 0.45000545E-001 0.61968809E+001 0.49582808E+001 0.72480328E+000 0.12815465E+001
0.10000000E+001 0.84777407E+003 0.42274637E+002 0.21043992E+001 0.12859082E+000 0.57933762E+001 0.53564510E+001 -0.21985815E+000 0.13107406E+001
0.10000000E+001 0.85108655E+003 0.42202990E+002 0.22899272E+001 0.15201351E+000 0.52667995E+001 0.59688541E+001 -0.18680357E+001 0.13716648E+001
0.10000000E+001 0.85613001E+003 0.41990685E+002 0.24363150E+001 0.12549555E+000 0.59422065E+001 0.47252054E+001 -0.11023206E+001 0.12877369E+001
0.10000000E+001 0.85158798E+003 0.42098730E+002 0.25095084E+001 0.30801145E+000 0.50887829E+001 0.58654310E+001 -0.14687669E+000 0.14475608E+001
0.10000000E+001 0.85761226E+003 0.41730419E+002 0.22773368E+001 0.16229781E+000 0.45068163E+001 0.61784581E+001 -0.22970615E+001 0.14228953E+001
0.10000000E+001 0.85890062E+003 0.42300529E+002 0.17614972E+001 0.25181929E+000 0.12647418E+001 0.39070024E+001 -0.95978111E+000 0.14744481E+001
0.10000000E+001 0.84782335E+003 0.42224599E+002 0.21049963E+001 0.14116410E+000 0.57670357E+001 0.53870030E+001 -0.39998404E+000 0.12440920E+001
0.10000000E+001 0.85307924E+003 0.42173456E+002 0.20984129E+001 0.18357787E+000 0.53995496E+001 0.58799911E+001 -0.29452427E+000 0.12359123E+001
0.10000000E+001 0.84794647E+003 0.42218182E+002 0.26779453E+001 0.77121328E-001 0.56292996E+001 0.54686837E+001 0.13616802E+000 0.14157836E+001
0.10000000E+001 0.84807313E+003 0.42252439E+002 0.26841476E+001 0.15374901E+000 0.62076088E+001 0.50063743E+001 -0.12911541E-001 0.14555141E+001
0.10000000E+001 0.85519281E+003 0.42097547E+002 0.27450266E+001 0.28730030E+000 0.40707029E+001 0.40897952E+000 0.45705358E+000 0.14945545E+001
0.10000000E+001 0.84822531E+003 0.42192280E+002 0.23142916E+001 0.14460814E+000 0.52028859E+001 0.57569287E+001 -0.78044279E+000 0.14380959E+001
0.10000000E+001 0.85473269E+003 0.41928872E+002 0.27016517E+001 0.21365497E+000 0.53450773E+001 0.54778900E+001 -0.14672318E+001 0.12496178E+001
0.10000000E+001 0.85524962E+003 0.42128029E+002 0.17012776E+001 0.78789479E-001 0.35113282E+001 0.12430038E+001 -0.10985661E+001 0.15775335E+001
0.10000000E+001 0.84857488E+003 0.42196810E+002 0.26554365E+001 0.68119754E-001 0.55039877E+001 0.56284531E+001 -0.12186495E+001 0.12803033E+001
0.10000000E+001 0.85064658E+003 0.42199459E+002 0.24552942E+001 0.16592251E+000 0.41252282E+001 0.56194356E+000 -0.13213045E+001 0.12337258E+001
0.10000000E+001 0.85786627E+003 0.41984817E+002 0.29024429E+001 0.36890410E+000 0.32508286E+001 0.13385850E+001 -0.14692686E+001 0.12327891E+001
0.10000000E+001 0.84874796E+003 0.41844761E+002 0.25444362E+001 0.53074425E-001 0.46160782E+001 0.61519787E+001 -0.13861574E+001 0.14728354E+001
0.10000000E+001 0.84907928E+003 0.42076292E+002 0.20368658E+001 0.21110073E+000 0.62564011E+001 0.46301748E+001 -0.84156148E+000 0.15633343E+001
0.10000000E+001 0.85550887E+003 0.41652587E+002 0.21844426E+001 0.24363383E+000 0.40700315E+001 0.37401852E+000 -0.73527933E+000 0.13503335E+001
0.10000000E+001 0.84938190E+003 0.42272046E+002 0.22725060E+001 0.31443234E-001 0.51711593E+001 0.59082920E+001 -0.11117679E+001 0.15866568E+001
0.10000000E+001 0.85069500E+003 0.42139488E+002 0.19710595E+001 0.20489671E+000 0.13598374E+001 0.32591573E+001 -0.53819817E+000 0.13838491E+001
0.10000000E+001 0.85074530E+003 0.42240171E+002 0.23886420E+001 0.24610507E+000 0.31453289E+001 0.18059782E+001 -0.27850924E-001 0.14163347E+001
0.10000000E+001 0.85086506E+003 0.41932619E+002 0.26346240E+001 0.28848157E+000 0.12635360E+001 0.33650020E+001 0.35942441E+000 0.11494389E+001
0.10000000E+001 0.85737860E+003 0.41778947E+002 0.31391254E+001 0.41507858E+000 0.57733677E-001 0.43936300E+001 0.82606651E+000 0.15063135E+001
0.10000000E+001 0.85086837E+003 0.42316733E+002 0.29915288E+001 0.23834287E+000 0.98306478E+000 0.39414136E+001 0.45472981E+000 0.13755488E+001
0.10000000E+001 0.85723246E+003 0.41754493E+002 0.22094559E+001 0.15781256E+000 0.33634664E+001 0.11440196E+001 0.47176724E+000 0.15812527E+001
0.10000000E+001 0.85723137E+003 0.42251243E+002 0.25837114E+001 0.38374632E+000 0.35375895E+001 0.11913445E+001 -0.18667730E+001 0.14741518E+001
0.10000000E+001 0.85095532E+003 0.42101353E+002 0.28622201E+001 0.32437775E+000 0.10763293E-002 0.46699622E+001 -0.14530769E+001 0.11891747E+001
0.10000000E+001 0.85097058E+003 0.42409633E+002 0.22664805E+001 0.21692723E+000 0.45859409E+001 0.41132521E+000 -0.64586185E+000 0.13698208E+001
0.10000000E+001 0.85106750E+003 0.42022627E+002 0.25406629E+001 0.10995442E+000 0.25373416E+001 0.22819592E+001 -0.16159742E+001 0.13669351E+001
0.10000000E+001 0.84951298E+003 0.42064894E+002 0.21862353E+001 0.10185771E+000 0.52268745E+001 0.59500172E+001 -0.43987840E+000 0.12286068E+001
0.10000000E+001 0.85602930E+003 0.41804735E+002 0.21508980E+001 0.18034030E+000 0.30863338E+001 0.12401178E+001 -0.17346461E+001 0.14116968E+001
0.10000000E+001 0.85612980E+003 0.42201708E+002 0.26376168E+001 0.29184275E+000 0.25825869E+001 0.23257451E+001 -0.59143661E+000 0.16570735E+001
0.10000000E+001 0.85116044E+003 0.42126353E+002 0.20350323E+001 0.21223104E-001 0.39720929E+001 0.71503888E+000 -0.10514577E+001 0.11550331E+001
0.10000000E+001 0.85615064E+003 0.42307884E+002 0.24402069E+001 0.26661098E+000 0.33932031E+001 0.13261107E+001 -0.95965405E-001 0.13535104E+001
0.10000000E+001 0.85633937E+003 0.42111172E+002 0.31819982E+001 0.35320116E+000 0.98536844E+000 0.39068601E+001 -0.28220514E+000 0.17696272E+001
0.10000000E+001 0.85484095E+003 0.41697633E+002 0.28772186E+001 0.35153598E+000 0.34617565E+001 0.78416779E+000 -0.58995405E+000 0.13969190E+001
0.10000000E+001 0.85467409E+003 0.41815675E+002 0.18108529E+001 0.85460325E-001 0.41425952E+001 0.31736952E+000 -0.75799192E+000 0.12894199E+001
0.10000000E+001 0.85463443E+003 0.41984898E+002 0.24326555E+001 0.30842693E+000 0.15610482E+001 0.31538996E+001 -0.61893777E+000 0.17774370E+001
0.10000000E+001 0.85453955E+003 0.42335726E+002 0.18610578E+001 0.19962360E+000 0.11977724E+001 0.39089330E+001 -0.13449264E+001 0.13536744E+001
0.10000000E+001 0.85122051E+003 0.41866123E+002 0.26483938E+001 0.23384857E+000 0.16236389E+000 0.45343892E+001 -0.41557706E+000 0.15314785E+001
0.10000000E+001 0.85445576E+003 0.42191059E+002 0.22217345E+001 0.29934719E+000 0.42754531E+001 0.37405782E+000 0.49408495E+000 0.12294420E+001
0.10000000E+001 0.85432317E+003 0.42492666E+002 0.22706668E+001 0.26523526E+000 0.99744282E+000 0.40130965E+001 -0.10295261E+001 0.16451113E+001
0.10000000E+001 0.85123180E+003 0.41959589E+002 0.24041830E+001 0.10232420E+000 0.39652060E+001 0.66468307E+000 -0.59455858E+000 0.17536466E+001
0.10000000E+001 0.85136929E+003 0.41682088E+002 0.26206898E+001 0.36981043E+000 0.40417683E+000 0.38722815E+001 -0.73299771E+000 0.13536658E+001
0.10000000E+001 0.85407682E+003 0.42093318E+002 0.21611394E+001 0.12546133E+000 0.10530335E+001 0.36969534E+001 0.11140570E+001 0.11551066E+001
0.10000000E+001 0.85401101E+003 0.42238589E+002 0.18508549E+001 0.18034524E+000 0.30989360E+001 0.18360932E+001 -0.23322457E+000 0.13731280E+001
0.10000000E+001 0.85154885E+003 0.42269659E+002 0.21661984E+001 0.15894551E+000 0.12367648E+001 0.38529456E+001 -0.13108428E+001 0.16045618E+001
0.10000000E+001 0.85003325E+003 0.42196434E+002 0.18646623E+001 0.83426333E-001 0.48578872E+001 0.62542864E+001 0.10383386E+000 0.13921332E+001
0.10000000E+001 0.85373924E+003 0.42318169E+002 0.19649418E+001 0.24240019E+000 0.48544247E+000 0.44825746E+001 -0.39564228E+000 0.11807771E+001
0.10000000E+001 0.85367888E+003 0.41881833E+002 0.23841011E+001 0.18351456E+000 0.42737150E+001 0.71564949E-001 0.51044602E+000 0.15431226E+001
0.10000000E+001 0.85041682E+003 0.41880426E+002 0.24640591E+001 0.28595046E+000 0.57719476E+001 0.50094968E+001 -0.90871768E+000 0.13867994E+001
0.10000000E+001 0.84761624E+003 0.42201535E+002 0.24194888E+001 0.25626508E+000 0.44647350E+000 0.45883789E+001 -0.32987319E+000 0.14229640E+001
0.10000000E+001 0.84761841E+003 0.42307979E+002 0.23534289E+001 0.11311696E+000 0.95789070E+000 0.38514880E+001 -0.20913094E+000 0.12851503E+001
0.10000000E+001 0.84762502E+003 0.41798475E+002 0.22237578E+001 0.51792501E-001 0.42497544E+001 0.17960049E+000 -0.45525940E+000 0.13417341E+001
0.10000000E+001 0.85343804E+003 0.42076059E+002 0.23091511E+001 0.25367953E+000 0.38430935E+001 0.94515695E+000 -0.24985377E+001 0.13624481E+001
0.10000000E+001 0.85340476E+003 0.42431435E+002 0.25030637E+001 0.13218909E+000 0.10759671E+001 0.39597878E+001 -0.72727957E+000 0.11980228E+001
0.10000000E+001 0.85332672E+003 0.41888205E+002 0.25485164E+001 0.32000319E+000 0.38668575E+001 0.68558325E+000 -0.34531277E+000 0.10016244E+001
0.10000000E+001 0.85327952E+003 0.42221498E+002 0.27195173E+001 0.33489516E+000 0.54851588E+000 0.43083421E+001 -0.26615902E+001 0.13093504E+001
0.10000000E+001 0.85324836E+003 0.42042806E+002 0.23485036E+001 0.22436126E+000 0.63524669E+000 0.42857256E+001 -0.37470801E+000 0.16930792E+001
0.10000000E+001 0.85317990E+003 0.42018664E+002 0.24567732E+001 0.24374770E+000 0.36968414E+001 0.10955863E+001 0.86279245E+000 0.14805348E+001
0.10000000E+001 0.85192125E+003 0.42191830E+002 0.23853830E+001 0.39518242E+000 0.42306092E+000 0.44330692E+001 -0.16945209E+001 0.16744249E+001
0.10000000E+001 0.85301612E+003 0.41818603E+002 0.18783644E+001 0.23027960E+000 0.28428318E+000 0.41739093E+001 -0.59340769E+000 0.13642409E+001
0.10000000E+001 0.84766891E+003 0.42185351E+002 0.33012429E+001 0.43108990E+000 0.55186284E+000 0.42538195E+001 -0.13038898E+001 0.16085242E+001
0.10000000E+001 0.85196792E+003 0.41898752E+002 0.25071877E+001 0.94827528E-001 0.23459279E+001 0.21565554E+001 -0.19102194E+001 0.13569272E+001
0.10000000E+001 0.85296562E+003 0.42283762E+002 0.21024377E+001 0.14101713E+000 0.44184608E+001 0.34928891E+000 -0.12784229E+001 0.12993884E+001
0.10000000E+001 0.85198000E+003 0.41997135E+002 0.28402466E+001 0.27314232E+000 0.11097048E+001 0.36775676E+001 -0.58559412E+000 0.17141650E+001
0.10000000E+001 0.85203417E+003 0.41917089E+002 0.25341100E+001 0.11233203E+000 0.15115022E+001 0.30437499E+001 0.43655077E+000 0.11749820E+001
0.10000000E+001 0.85207532E+003 0.42109033E+002 0.24023866E+001 0.18993688E+000 0.23917329E+000 0.46931538E+001 -0.96037062E+000 0.16927570E+001
0.10000000E+001 0.85209373E+003 0.42235141E+002 0.23803863E+001 0.59035985E-001 0.45837229E+001 0.13853491E+000 0.33297304E+000 0.16177423E+001
0.10000000E+001 0.85288011E+003 0.42212433E+002 0.24589588E+001 0.12440262E+000 0.38740770E+001 0.94647573E+000 -0.16227144E+001 0.11355878E+001
0.10000000E+001 0.85213075E+003 0.41661642E+002 0.23936599E+001 0.35424512E+000 0.53631232E+000 0.38278749E+001 -0.57898163E+000 0.14524095E+001
0.10000000E+001 0.84766967E+003 0.41891337E+002 0.22410059E+001 0.87608058E-001 0.11091503E+001 0.34224169E+001 -0.42655893E+000 0.16186520E+001
0.10000000E+001 0.85219433E+003 0.42225578E+002 0.22307026E+001 0.32986229E+000 0.98201445E+000 0.41106254E+001 -0.15709637E+001 0.14214571E+001
0.10000000E+001 0.84767202E+003 0.41940552E+002 0.20550628E+001 0.26043139E+000 0.14192794E+001 0.32258317E+001 -0.79832721E+000 0.13532476E+001
0.10000000E+001 0.84768861E+003 0.41983821E+002 0.28050878E+001 0.42944114E+000 0.42043535E+001 0.57416966E+000 -0.17580804E+001 0.12532452E+001
0.10000000E+001 0.85226468E+003 0.41758940E+002 0.25972524E+001 0.29668247E+000 0.73522252E+000 0.35526661E+001 -0.41971497E+000 0.15758073E+001
0.10000000E+001 0.85233987E+003 0.42262651E+002 0.23643254E+001 0.32210933E-001 0.13736008E+001 0.35696359E+001 -0.21846054E+001 0.14625823E+001
0.10000000E+001 0.84769808E+003 0.42331127E+002 0.22349834E+001 0.10992179E+000 0.32744505E+001 0.16814424E+001 -0.61930546E+000 0.14559695E+001
0.10000000E+001 0.85054141E+003 0.42161871E+002 0.35174515E+001 0.38464879E+000 0.63187289E+000 0.41779705E+001 -0.78276545E+000 0.15525051E+001
0.10000000E+001 0.84771358E+003 0.42116747E+002 0.24692150E+001 0.42358421E+000 0.58514781E+000 0.43074297E+001 0.62325254E-001 0.15493535E+001
0.10000000E+001 0.85049846E+003 0.41793789E+002 0.24683505E+001 0.24443478E+000 0.16797385E+000 0.42085829E+001 -0.60149631E+000 0.16642821E+001
0.10000000E+001 0.84774005E+003 0.42198443E+002 0.22429648E+001 0.70371180E-001 0.11588879E+001 0.35278454E+001 -0.13266922E+001 0.14180780E+001
0.10000000E+001 0.85037974E+003 0.42209047E+002 0.28418560E+001 0.33747305E+000 0.39819202E+001 0.69050238E+000 -0.16220914E+001 0.14633316E+001
0.10000000E+001 0.85035834E+003 0.41976577E+002 0.29478898E+001 0.22364989E+000 0.13913067E+001 0.33277452E+001 -0.55489364E+000 0.13735627E+001
0.10000000E+001 0.85031791E+003 0.42063188E+002 0.22549281E+001 0.22849990E+000 0.16939507E+001 0.29924284E+001 -0.10990872E+001 0.11390073E+001
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0.10000000E+001 0.84067048E+003 0.42255861E+002 0.26448685E+001 0.35078709E+000 0.56432112E+000 0.43436649E+001 0.31037459E-001 0.13444772E+001
0.10000000E+001 0.84064360E+003 0.42036984E+002 0.25520665E+001 0.41590787E+000 0.91800818E+000 0.37827966E+001 -0.15600248E+000 0.13847338E+001
0.10000000E+001 0.84060606E+003 0.42067592E+002 0.29016384E+001 0.38913774E+000 0.66224719E+000 0.41415027E+001 -0.81817726E+000 0.13168900E+001
0.10000000E+001 0.84056178E+003 0.42115622E+002 0.25469648E+001 0.32896419E+000 0.11757872E+001 0.35766525E+001 -0.22922450E+000 0.14640980E+001
0.10000000E+001 0.84055298E+003 0.42002170E+002 0.27543159E+001 0.34828117E+000 0.31676843E+000 0.42862137E+001 -0.10265944E+001 0.14814842E+001
0.10000000E+001 0.84054576E+003 0.42028020E+002 0.27733689E+001 0.38103357E+000 0.54185206E+000 0.41786314E+001 -0.10273172E+001 0.15009171E+001
0.10000000E+001 0.84049025E+003 0.42132237E+002 0.25708604E+001 0.28374602E+000 0.44101724E+000 0.42433797E+001 -0.12487299E+001 0.13497809E+001
0.10000000E+001 0.84034173E+003 0.42143011E+002 0.25841618E+001 0.28456674E+000 0.58964360E+000 0.42786339E+001 -0.20124436E+000 0.12995670E+001
0.10000000E+001 0.84033287E+003 0.42188838E+002 0.28152011E+001 0.42085980E+000 0.59267832E+000 0.41118679E+001 -0.48635281E+000 0.14723504E+001
0.10000000E+001 0.84027492E+003 0.42095443E+002 0.25798189E+001 0.35339994E+000 0.67665512E+000 0.40882246E+001 -0.10702025E+001 0.15187840E+001
0.10000000E+001 0.84018600E+003 0.42007248E+002 0.23829641E+001 0.33650625E+000 0.72926008E+000 0.39179699E+001 -0.10799483E+001 0.13942107E+001
0.10000000E+001 0.84018032E+003 0.42148941E+002 0.28661374E+001 0.39150359E+000 0.54995199E+000 0.42278156E+001 -0.97915176E+000 0.15072947E+001
0.10000000E+001 0.84017300E+003 0.41947486E+002 0.26471465E+001 0.34025577E+000 0.46828259E+000 0.41751791E+001 -0.87183812E+000 0.14451507E+001
0.10000000E+001 0.84014991E+003 0.42199608E+002 0.25887774E+001 0.35162790E+000 0.50160690E+000 0.42196129E+001 -0.65741036E+000 0.13052351E+001
0.10000000E+001 0.84010087E+003 0.42086096E+002 0.24619408E+001 0.33101148E+000 0.11198781E+001 0.36078899E+001 -0.97275119E+000 0.13019178E+001
0.10000000E+001 0.84007147E+003 0.42151055E+002 0.26672473E+001 0.43074217E+000 0.10202645E+001 0.38043635E+001 -0.63037109E+000 0.13499836E+001
0.10000000E+001 0.84086475E+003 0.41904932E+002 0.27264101E+001 0.48780285E+000 0.40329390E+001 0.56638411E+000 -0.50602123E+000 0.13164572E+001
0.10000000E+001 0.84082981E+003 0.41951976E+002 0.26943224E+001 0.32409505E+000 0.39280178E+001 0.58420760E+000 -0.65083017E+000 0.12624673E+001
0.10000000E+001 0.84081942E+003 0.42072672E+002 0.24957480E+001 0.39965006E+000 0.41335456E+001 0.52862429E+000 -0.13392122E+001 0.13435895E+001
0.10000000E+001 0.84079211E+003 0.42012850E+002 0.23844659E+001 0.30140704E+000 0.38826365E+001 0.72409573E+000 -0.20090613E+000 0.14255487E+001
0.10000000E+001 0.84077390E+003 0.42083463E+002 0.23453442E+001 0.34676516E+000 0.40376896E+001 0.68017812E+000 -0.60602757E+000 0.14434913E+001
0.10000000E+001 0.84068355E+003 0.42053453E+002 0.25449358E+001 0.25704673E+000 0.42136033E+001 0.41797927E+000 -0.80335672E+000 0.13840908E+001
0.10000000E+001 0.84061973E+003 0.42046756E+002 0.25705306E+001 0.41768729E+000 0.40862206E+001 0.55104656E+000 -0.13392908E+001 0.12835593E+001
0.10000000E+001 0.84048963E+003 0.42131024E+002 0.25250206E+001 0.43126329E+000 0.41464427E+001 0.60371560E+000 -0.69014343E+000 0.14266677E+001
0.10000000E+001 0.84041999E+003 0.41948645E+002 0.28034763E+001 0.36653109E+000 0.41721120E+001 0.40020889E+000 -0.96978074E+000 0.14231530E+001
0.10000000E+001 0.84041047E+003 0.41990958E+002 0.28125856E+001 0.42197150E+000 0.39465948E+001 0.60526716E+000 0.13100774E+000 0.13216116E+001
0.10000000E+001 0.84036708E+003 0.41956517E+002 0.25613811E+001 0.28744606E+000 0.42039801E+001 0.44287790E+000 -0.99645909E+000 0.13638336E+001
0.10000000E+001 0.84029574E+003 0.42090006E+002 0.26827995E+001 0.38015859E+000 0.41722688E+001 0.63194768E+000 -0.10340366E+001 0.13368787E+001
0.10000000E+001 0.84018799E+003 0.41892536E+002 0.27840643E+001 0.42798402E+000 0.40545121E+001 0.43507867E+000 -0.71853068E+000 0.14330437E+001
0.10000000E+001 0.84014882E+003 0.41993466E+002 0.29395223E+001 0.47628697E+000 0.40690493E+001 0.51992741E+000 -0.11387363E+001 0.13900451E+001
0.10000000E+001 0.84009326E+003 0.42057204E+002 0.26725673E+001 0.36347563E+000 0.40570509E+001 0.55060327E+000 -0.84392004E+000 0.12550336E+001
0.10000000E+001 0.84003218E+003 0.42104715E+002 0.26200181E+001 0.22384509E+000 0.98381559E+000 0.37657051E+001 -0.10711247E+001 0.13166124E+001
0.10000000E+001 0.84002189E+003 0.42080421E+002 0.26369558E+001 0.27389333E+000 0.87752095E+000 0.37812425E+001 -0.11580294E+001 0.13111539E+001
0.10000000E+001 0.84000017E+003 0.42226933E+002 0.25833446E+001 0.28402173E+000 0.98834136E+000 0.38112702E+001 -0.41054308E+000 0.12924988E+001
0.10000000E+001 0.83998299E+003 0.42069035E+002 0.24112123E+001 0.14879879E+000 0.40594445E+000 0.43260901E+001 -0.63666247E+000 0.13384634E+001
0.10000000E+001 0.83996286E+003 0.42177488E+002 0.24705461E+001 0.18428623E+000 0.72393325E+000 0.41188491E+001 -0.19465643E+000 0.13462484E+001
0.10000000E+001 0.83989815E+003 0.42155357E+002 0.27394094E+001 0.31442831E+000 0.76159053E+000 0.41253829E+001 -0.39437869E+000 0.13791720E+001
0.10000000E+001 0.83987055E+003 0.42125315E+002 0.23230249E+001 0.18357401E+000 0.10615202E+001 0.37445593E+001 -0.77367969E+000 0.13386470E+001
0.10000000E+001 0.83982034E+003 0.42125164E+002 0.23502027E+001 0.23651785E+000 0.42706519E+000 0.43673395E+001 -0.35404837E+000 0.14012821E+001
0.10000000E+001 0.83979221E+003 0.42056340E+002 0.26212096E+001 0.19993825E+000 0.79553860E+000 0.39182259E+001 -0.47001707E+000 0.14345812E+001
0.10000000E+001 0.83974324E+003 0.42227096E+002 0.26840359E+001 0.29912473E+000 0.65725100E+000 0.40959965E+001 -0.46573287E+000 0.13693721E+001
0.10000000E+001 0.83972092E+003 0.42172016E+002 0.25948923E+001 0.29608900E+000 0.79165826E+000 0.39600718E+001 -0.12869136E+001 0.13395350E+001
0.10000000E+001 0.83971319E+003 0.42073989E+002 0.23465768E+001 0.15171668E+000 0.61838919E+000 0.40739551E+001 -0.43467011E+000 0.13787455E+001
0.10000000E+001 0.83960189E+003 0.42107026E+002 0.23792235E+001 0.26319939E+000 0.85150832E+000 0.38890657E+001 -0.28913697E+000 0.14791872E+001
0.10000000E+001 0.83959921E+003 0.42125731E+002 0.23979815E+001 0.24341547E+000 0.10891169E+001 0.37094889E+001 -0.95885215E+000 0.14167708E+001
0.10000000E+001 0.83948984E+003 0.42075895E+002 0.25078883E+001 0.28215634E+000 0.76602951E+000 0.39599814E+001 -0.11773266E+001 0.14684900E+001
0.10000000E+001 0.83947130E+003 0.42029957E+002 0.25042639E+001 0.21542056E+000 0.76434531E+000 0.39308658E+001 -0.35743162E+000 0.12726799E+001
0.10000000E+001 0.83941697E+003 0.42117790E+002 0.24642739E+001 0.22700334E+000 0.68496130E+000 0.40721578E+001 -0.60183718E+000 0.14933356E+001
0.10000000E+001 0.83992830E+003 0.42078587E+002 0.25692660E+001 0.32510916E+000 0.47349373E+000 0.43381881E+001 -0.54860468E+000 0.13869896E+001
0.10000000E+001 0.83988384E+003 0.42187497E+002 0.27409138E+001 0.29239909E+000 0.40857427E+000 0.43387557E+001 -0.75272006E+000 0.13724854E+001
0.10000000E+001 0.83983142E+003 0.42036649E+002 0.26928140E+001 0.35624354E+000 0.31436550E+000 0.42797734E+001 -0.13191589E+000 0.14046809E+001
0.10000000E+001 0.83970060E+003 0.42064260E+002 0.27191641E+001 0.34549734E+000 0.46555657E+000 0.41624347E+001 -0.64784087E-001 0.14744450E+001
0.10000000E+001 0.83962259E+003 0.42200807E+002 0.27395392E+001 0.34133245E+000 0.83814851E+000 0.39629478E+001 -0.12764943E+001 0.13502574E+001
0.10000000E+001 0.83957142E+003 0.42122284E+002 0.26302482E+001 0.32858407E+000 0.43813917E+000 0.43742783E+001 -0.90203741E+000 0.13159105E+001
0.10000000E+001 0.83952646E+003 0.42023113E+002 0.25907698E+001 0.33341512E+000 0.31947044E+000 0.42973044E+001 -0.10097959E+000 0.13475368E+001
0.10000000E+001 0.84004456E+003 0.41993779E+002 0.29549816E+001 0.43898642E+000 0.39476628E+001 0.60090232E+000 -0.26727051E+000 0.14257579E+001
0.10000000E+001 0.84003144E+003 0.42127030E+002 0.26918257E+001 0.37858146E+000 0.41910302E+001 0.52465794E+000 -0.10704128E+000 0.13475748E+001
0.10000000E+001 0.84002586E+003 0.42063735E+002 0.25527510E+001 0.26593908E+000 0.41842763E+001 0.48733675E+000 -0.61863303E+000 0.12911792E+001
0.10000000E+001 0.83971100E+003 0.42092651E+002 0.25685738E+001 0.40209949E+000 0.43081572E+001 0.41587470E+000 -0.46786756E+000 0.13668886E+001
0.10000000E+001 0.83932872E+003 0.42207255E+002 0.24909480E+001 0.27135820E+000 0.84509699E+000 0.40599555E+001 -0.33951803E+000 0.13538716E+001
0.10000000E+001 0.83921748E+003 0.42009520E+002 0.26330715E+001 0.26717004E+000 0.45260795E+000 0.41758148E+001 -0.76141142E+000 0.12877895E+001
0.10000000E+001 0.83915869E+003 0.42151718E+002 0.25542015E+001 0.25108695E+000 0.68321831E+000 0.41765779E+001 -0.62484500E+000 0.13757279E+001
0.10000000E+001 0.83907452E+003 0.42012210E+002 0.24497084E+001 0.23016159E+000 0.65118175E+000 0.40574402E+001 -0.62084302E+000 0.13831906E+001
0.10000000E+001 0.83887320E+003 0.42121087E+002 0.25845349E+001 0.28147516E+000 0.10003201E+001 0.37013696E+001 -0.40137315E+000 0.13607430E+001
0.10000000E+001 0.83879837E+003 0.42065851E+002 0.25604394E+001 0.26318034E+000 0.59933234E+000 0.41674427E+001 -0.45671856E+000 0.14169712E+001
0.10000000E+001 0.83936128E+003 0.42151292E+002 0.28317868E+001 0.36352875E+000 0.92721889E+000 0.39350327E+001 -0.55673219E+000 0.14029835E+001
0.10000000E+001 0.83928582E+003 0.42055779E+002 0.27964919E+001 0.31985410E+000 0.82285083E+000 0.38424068E+001 -0.95974017E+000 0.14560891E+001
0.10000000E+001 0.83924849E+003 0.41961493E+002 0.25803182E+001 0.32140535E+000 0.41590929E+000 0.42062890E+001 -0.71637791E+000 0.14095310E+001
0.10000000E+001 0.83900838E+003 0.42169227E+002 0.24602576E+001 0.31533289E+000 0.65426787E+000 0.41071576E+001 -0.19049658E+000 0.14359342E+001
0.10000000E+001 0.83890016E+003 0.42133938E+002 0.27113158E+001 0.36140660E+000 0.52187795E+000 0.41715404E+001 -0.10059135E+001 0.14228351E+001
0.10000000E+001 0.83874609E+003 0.42108729E+002 0.28789883E+001 0.38782431E+000 0.61509438E+000 0.40779474E+001 -0.33000715E+000 0.12459061E+001
0.10000000E+001 0.83871793E+003 0.42180599E+002 0.27084361E+001 0.39295625E+000 0.72671988E+000 0.40395134E+001 -0.85281068E-001 0.14198995E+001
0.10000000E+001 0.83867665E+003 0.42163270E+002 0.27623760E+001 0.33563088E+000 0.94496186E+000 0.38047924E+001 -0.50050578E+000 0.12992933E+001
0.10000000E+001 0.83854754E+003 0.42068488E+002 0.27211165E+001 0.30078859E+000 0.67035473E+000 0.40198756E+001 -0.26959546E+000 0.14620769E+001
0.10000000E+001 0.83850201E+003 0.42037000E+002 0.25510455E+001 0.24705543E+000 0.76002949E+000 0.39449073E+001 -0.64202240E+000 0.14230306E+001
0.10000000E+001 0.83836156E+003 0.42010684E+002 0.26403407E+001 0.29243500E+000 0.73942101E+000 0.39166907E+001 -0.30277871E+000 0.14109420E+001
0.10000000E+001 0.83854837E+003 0.42155463E+002 0.28026846E+001 0.37269509E+000 0.85168461E+000 0.39597901E+001 -0.41721091E+000 0.12543246E+001
0.10000000E+001 0.83843326E+003 0.42082546E+002 0.24912192E+001 0.33162394E+000 0.65862922E+000 0.40538759E+001 -0.10132679E+001 0.13106484E+001
0.10000000E+001 0.83840554E+003 0.42079060E+002 0.28312322E+001 0.31544184E+000 0.68382233E+000 0.40555258E+001 -0.81065055E+000 0.13927297E+001
0.10000000E+001 0.83833964E+003 0.42189130E+002 0.28158609E+001 0.34177510E+000 0.72297389E+000 0.41233606E+001 -0.39985343E+000 0.13567983E+001
0.10000000E+001 0.83828570E+003 0.42046943E+002 0.25187444E+001 0.25264487E+000 0.67561791E+000 0.40179276E+001 -0.45420884E+000 0.14284301E+001
0.10000000E+001 0.83794270E+003 0.42142536E+002 0.24604622E+001 0.30105567E+000 0.80445986E+000 0.39802448E+001 -0.65931652E+000 0.13058972E+001
0.10000000E+001 0.83764230E+003 0.42108282E+002 0.25938793E+001 0.27260344E+000 0.69181921E+000 0.40218805E+001 -0.34195713E+000 0.13652636E+001
0.10000000E+001 0.83763523E+003 0.42092899E+002 0.26593899E+001 0.33000000E+000 0.68204678E+000 0.39812251E+001 -0.58485890E+000 0.13165703E+001
In [145]:
n_mixture = 7
samples = np.genfromtxt('chains/1pd0001a_equal_weights.txt')
#z=!sed -n '38p' chains/0pd0001.resume
#z=np.float(z[0])
mus1p001 = np.mean(samples[:, 2:], axis=0)
mus1p001[3] = 0.634549677541
mus1p001[4] = 4.17185735339
#sigs = np.std(samples[:, 2:], axis=0)
fig = corner.corner(samples[:, 2:], ranges=[[0, 1]*(3*n_mixture-1)],labels=['P','K','e','w','M','C','J'],truths=mus1p001)
print(mus1p001)
#print('The values of C and J, and evidence', mus0p001,z)
[ 42.0815377 2.48336249 0.24126625 0.63454968 4.17185735
-0.60731763 1.37822456]
In [29]:
x = data[:,0]
xm = np.arange(0,data[-1,0],data[-1,0]/1000)
y = data[:,1]
y0 = model(mus1p001,xm,1)
yerr = data[:,2]
# First illustrate basic pyplot interface, using defaults where possible.
plt.figure(figsize=(15,8))
#plt.xlabel('teste')
plt.xlabel('Time (s)', fontsize=20)
plt.ylabel('Star Radial velocity (m/s)', fontsize=20)
plt.errorbar(x, y, yerr=yerr,fmt='o')
plt.plot(xm,y0)
plt.tick_params(labelsize=20)
plt.title("Data0001",fontsize=30)
#plt.plot(x,y,'o')
Out[29]:
<matplotlib.text.Text at 0x7f583407c0b8>
In [132]:
z=!sed -n '38p' chains/1pd0001a.resume
z1pd0001a=np.float(z[0])*np.log10(np.e)
print('Nominal value:',z1pd0001a)
print('Relative value:', np.power(10,z1pd0001a-z0pd0001a))
Nominal value: -194.085600293
Relative value: 2.87810882107e+17
In [54]:
n_plan = 2
samples_runtime = np.genfromtxt('chains/2pd0001a_phys_live.txt')
samples_dead = np.genfromtxt('chains/2pd0001a_dead.txt')
plt.figure(1,figsize=(15,8))
plt.subplot(121)
plt.tick_params(labelsize=20)
plt.plot(samples_dead[:,5*n_plan+1],samples_dead[:,5*n_plan+2], 'bo')
plt.plot(samples_runtime[:,5*n_plan],samples_runtime[:,5*n_plan+1], 'ro')
plt.subplot(122)
plt.tick_params(labelsize=20)
plt.plot(samples_runtime[:,5*n_plan],samples_runtime[:,5*n_plan+1], 'ro');
In [180]:
n_plan = 2
n_mixture = 2+n_plan*5
label=[]
samples2 = np.genfromtxt('chains/2pd0001a_equal_weights.txt')
#z=!sed -n '38p' chains/0pd0001.resume
#z=np.float(z[0])
mus2p001 = np.mean(samples2[:, 2:], axis=0)
for ene in range(n_plan):
fac = 5*ene
sen=np.mean(np.sin(samples2[:,5+fac:7+fac]),axis=0)
cos=np.mean(np.cos(samples2[:,5+fac:7+fac]),axis=0)
ang=np.arctan2(sen,cos)
mus2p001[3+fac]=ang[0]%(2*np.pi)
mus2p001[4+fac]=ang[1]%(2*np.pi)
label=np.append(label,['P'+str(ene+1),'K'+str(ene+1),'e'+str(ene+1),'w'+str(ene+1),'M'+str(ene+1)])
label=np.append(label,['C','J'])
fig = corner.corner(samples2[:, 2:], ranges=[[0, 1]*(3*n_mixture-1)],labels=['P1','K1','e1','w1','M1',\
'P2','K2','e2','w2','M2','C','J'],truths=mus2p001)
print(mus2p001)
#print('The values of C and J, and evidence', mus0p001,z)
[ 1.21088616e+01 1.75825681e+00 1.09271853e-01 9.06742319e-01
2.04046948e-02 4.21960074e+01 2.26894474e+00 2.04789008e-01
1.27898080e+00 3.64255512e+00 -4.62429696e-01 6.71065008e-01]
In [109]:
x = data[:,0]
xm = np.arange(0,data[-1,0],data[-1,0]/1000)
y = data[:,1]
y0 = model(mus2p001,xm,2)
yerr = data[:,2]
# First illustrate basic pyplot interface, using defaults where possible.
plt.figure(figsize=(15,8))
#plt.xlabel('teste')
plt.xlabel('Time (s)', fontsize=20)
plt.ylabel('Star Radial velocity (m/s)', fontsize=20)
plt.errorbar(x, y, yerr=yerr,fmt='o')
plt.plot(xm,y0)
plt.tick_params(labelsize=20)
plt.title("Data0001",fontsize=30)
#plt.plot(x,y,'o')
Out[109]:
<matplotlib.text.Text at 0x7f582e8b6a90>
In [165]:
z=!sed -n '38p' chains/2pd0001a.resume
z2pd0001a=np.float(z[0])*np.log10(np.e)+np.log10(2)
print('Nominal value:',z2pd0001a)
print('Relative value:', np.power(10,z2pd0001a-z0pd0001a))
Nominal value: -176.033395705
Relative value: 3.24572558397e+35
In [186]:
n_plan = 3
samples_runtime = np.genfromtxt('chains/3pd0001a_phys_live.txt')
samples_dead = np.genfromtxt('chains/3pd0001a_dead.txt')
plt.figure(1,figsize=(15,8))
plt.subplot(121)
plt.tick_params(labelsize=20)
plt.plot(samples_dead[:,5*n_plan+1],samples_dead[:,5*n_plan+2], 'bo')
plt.plot(samples_runtime[:,5*n_plan],samples_runtime[:,5*n_plan+1], 'ro')
plt.subplot(122)
plt.tick_params(labelsize=20)
plt.plot(samples_runtime[:,5*n_plan],samples_runtime[:,5*n_plan+1], 'ro');
In [4]:
n_plan = 3
n_mixture = 2+n_plan*5
label=[]
samples3 = np.genfromtxt('chains/3pd0001a_equal_weights.txt')
#z=!sed -n '38p' chains/0pd0001.resume
#z=np.float(z[0])
mus3p001 = np.mean(samples3[:, 2:], axis=0)
for ene in range(n_plan):
fac = 5*ene
sen=np.mean(np.sin(samples3[:,5+fac:7+fac]),axis=0)
cos=np.mean(np.cos(samples3[:,5+fac:7+fac]),axis=0)
ang=np.arctan2(sen,cos)
mus3p001[3+fac]=ang[0]%(2*np.pi)
mus3p001[4+fac]=ang[1]%(2*np.pi)
label=np.append(label,['P'+str(ene+1),'K'+str(ene+1),'e'+str(ene+1),'w'+str(ene+1),'M'+str(ene+1)])
label=np.append(label,['C','J'])
fig = corner.corner(samples3[:, 2:], ranges=[[0, 1]*(3*n_mixture-1)],labels=label,truths=mus3p001)
print(mus3p001)
#print('The values of C and J, and evidence', mus0p001,z)
WARNING:root:Too few points to create valid contours
[ 1.21103576e+01 1.77942573e+00 1.11374447e-01 5.09331992e-01
4.29728698e-01 4.21920560e+01 2.18157864e+00 1.37615763e-01
5.51492953e+00 5.65231381e+00 2.58517844e+03 1.63215853e+00
2.45716652e-01 5.51766827e+00 5.64668054e+00 -3.18808568e-01
6.61112545e-01]
In [5]:
x = data[:,0]
xm = np.arange(0,data[-1,0],data[-1,0]/1000)
y = data[:,1]
y0 = model(mus3p001,xm,3)
yerr = data[:,2]
# First illustrate basic pyplot interface, using defaults where possible.
plt.figure(figsize=(15,8))
#plt.xlabel('teste')
plt.xlabel('Time (s)', fontsize=20)
plt.ylabel('Star Radial velocity (m/s)', fontsize=20)
plt.errorbar(x, y, yerr=yerr,fmt='o')
plt.plot(xm,y0)
plt.tick_params(labelsize=20)
plt.title("Data0001",fontsize=30)
#plt.plot(x,y,'o')
Out[5]:
<matplotlib.text.Text at 0x7f7a90d72eb8>
In [9]:
z=!sed -n '38p' chains/3pd0001a.resume
z3pd0001a=np.float(z[0])*np.log10(np.e)+np.log10(6)
print('Nominal value:',z3pd0001a)
print('Relative value:', np.power(10,z3pd0001a-z0pd0001a))
Nominal value: -173.766316714
Relative value: 6.00331026814e+37
In [ ]:
bfa=[]
Content source: isphus1973/StarPlanets
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