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92 lines
2.7 KiB
Python
92 lines
2.7 KiB
Python
#!/usr/bin/env Python3
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import numpy as np
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from pdb import set_trace
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import matplotlib.pyplot as plt
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from matplotlib.lines import Line2D
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import sys
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from AstroAtmosphere import *
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'''
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@ Author: Joost van den Born
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@ Contact: born@astron.nl
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@ Description: We plot the total refraction as a function of height.
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We find that most refraction happens in the lower atmosphere
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i.e. <10 km.
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'''
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def refractionIntegral2(n, R, z0, n0, R0):
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z0 = np.deg2rad(z0)
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return (n0 * R0 * np.sin(z0))/(n*np.sqrt((n*R)**2 - (n0 * R0 * np.sin(z0))**2 ))
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def n_for_heights(n0, z0, R0=None, useStandardAtmosphere=True, heightData=None, rhoData=None):
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'''
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Using data that gives temperature, pressure and density as a function of height,
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the gladstone-dale relation is invoked to calculate the path of a light ray
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along the atmosphere. This is allows us to also include atmospheric activity in
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different atmosphere layers.
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Recommended use with the US Standard Atmosphere from 1976.
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USSA1976 data generated from code supplied by http://www.pdas.com/atmos.html
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'''
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if useStandardAtmosphere:
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_h, _, _, _, _Temp, _Press, _Dens,_,_,_ = np.genfromtxt('si1py_modified.txt', unpack=True, skip_header=6)
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else:
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_Dens = rhoData
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_h = heightData
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z0 = np.deg2rad(z0)
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_Dens = np.asarray(_Dens)
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_h = np.asarray(_h)
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_R = R0 + _h * 1000
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# Gladstone-Dale relation between refractive index and density
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_n_h = 1 + (n0 - 1) / _Dens[0] * _Dens
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_z_h = np.arcsin( (n0 * R0) / (_n_h * _R) * np.sin(z0) )
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return _h, _n_h, np.degrees(_z_h)
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h, _, _, _, Temp, Press, Dens, vSound, _,_ = np.genfromtxt('si1py_modified.txt', unpack=True, skip_header=6)
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# Conditions
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T = 288.15 # k
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P = 101324 # Pa
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H = 0.0
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xc = 314 # ppm
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lat = -24.5983 # degrees
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h0 = 0 # m
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l1 = 1.49 # micron
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l2 = 1.78 # micron
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zenith = 60 # degrees
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# Calculate the index of refraction
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at = Observatory()
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n1 = at.n_tph(l=l1, T=T, p=P, RH=H, xc=xc)
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n2 = at.n_tph(l=l2, T=T, p=P, RH=H, xc=xc)
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rho = at.rho(p=P, T=T, RH=H, xc=xc)
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refr = refraction(lat, h0)
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refr.setReducedHeight(P, rho)
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disp = dispersion(lat, h0)
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disp.setReducedHeight(P, rho)
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fig = plt.figure(figsize=(5,4))
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ax = fig.add_subplot(111)
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ax.grid(True, alpha=0.3)
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ax.set_xlabel('Height (km)')
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ax.set_ylabel('Normalized cumulative refraction')
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ax.set_xlim([0, h[-1]])
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for z in [30]:
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refList = []
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dispList = []
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for i in range(len(h)):
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refList.append(refr.refractionIntegral(n1, z, useStandardAtmosphere=False, heightData=h[:i+1], rhoData=Dens[:i+1])*3600)
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dispList.append(disp.refractionIntegral(n1, n2, z, useStandardAtmosphere=False, heightData=h[:i+1], rhoData=Dens[:i+1])*3.6e6)
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ax.plot(h, np.asarray(refList)/refList[-1], 'k-', label='$\lambda=1.49$ $\mu$m, z=%i$^{\\circ}$' %z)
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ax.set_ylim([0,1.1])
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plt.tight_layout()
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plt.show()
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