In [1]:

    

#All libraries necesary:
%matplotlib inline
import matplotlib
matplotlib.rcParams['figure.figsize'] = (10, 6)
import matplotlib.pyplot as plt
import numpy as np
from math import pi, sin, cos
from copy import deepcopy
from mutils2 import *
import time
from milne import *


    

In [2]:

    

# PARAMETROS:
nlinea = 3                      # Numero linea en fichero
x = np.arange(-2.0,2.0,20e-3)   # Array Longitud de onda
B = 620.                        # Campo magnetico
thetaB = 2.45                   # Inclinacion
phiB = 1.50                     # Angulo azimutal
vlos = -0.25                    # velocidad km/s
eta0 = 4.26                     # Cociente de abs linea-continuo
a = 0.9                         # Parametro de amortiguamiento
ddop = 0.05                     # Anchura Doppler
# Sc = 4.0                      # Cociente Gradiente y Ordenada de la funcion fuente
S_0=0.4                         # Ordenada de la funcion fuente
S_1=0.5                         # Gradiente de la funcion fuente

param = paramLine(nlinea)
stokes = stokesSyn(param,x,B,thetaB,phiB,vlos,eta0,a,ddop,S_0,S_1)
for i in range(4):
    plt.subplot(2,2,i+1)
    if i == 0: plt.ylim(0,1.1)
    plt.plot(x,stokes[i])
    plt.plot([0,0],[min(stokes[i]),max(stokes[i])],'k--')


    

    




----------------------------------------------------
Element = SI1
lambda0 = 10827.089
ju=2.0, lu=1, su=1
jl=2.0, ll=1, sl=1
g_u  = 1.50
g_l  = 1.50
geff = 1.50






    

In [3]:

    

print('Valores iniciales:', B, thetaB*180/np.pi, phiB*180/np.pi)


    

    




('Valores iniciales:', 620.0, 140.3746598070517, 85.94366926962348)

In [4]:

    

iB, ithetaB, iphiB = initialConditions(stokes,nlinea,x,param)
print(iB, ithetaB*180/np.pi, iphiB*180/np.pi)


    

    




(587.75248108225981, 144.2969185249845, 78.463560735754172)

In [5]:

    

campoArray= np.arange(10, 2000, 10)


    

In [6]:

    

outArray = []
for B in (campoArray):
    stokes = stokesSyn(param,x,B,thetaB,phiB,vlos,eta0,a,ddop,S_0,S_1)
    iB, igamma, ixi = initialConditions(stokes,nlinea,x,param)
    outArray.append(iB)

plt.plot(campoArray,outArray,'r-')
plt.plot(campoArray,campoArray,'k--')
plt.xlabel('B Input')
plt.ylabel('B Output')


    

    
Out[6]:





<matplotlib.text.Text at 0x7fb7912db350>