19 Commits
Author SHA1 Message Date
yosata f4e77ffaf7 Ready for v1.4 release. 2021-03-10 11:52:14 +01:00
yosata 7771c59268 Added TPH dependency to Edlen and BonschPotulski functions. 2021-03-10 11:50:00 +01:00
yosata 160818cdf7 Merge of local branch with master branch - readying for 1.3.1 release. 2020-11-15 18:05:37 +01:00
yosata a3521a2426 Small bugfixes in refractionModels.py 2020-11-15 18:04:39 +01:00
Joost van den Born f4b37bd9bf Update README.md 2020-09-08 10:38:24 +02:00
Joost van den Born b804b15405 Update README.md 2020-09-08 10:33:28 +02:00
yosata 7a084d1635 Upated setup.py for v1.3 release 2020-09-07 21:29:56 +02:00
Joost van den Born f1aa2ee903 Update README.md 2020-09-07 21:24:43 +02:00
yosata 8f9a0bbbea Added Filippenko model, updated B&S refractivity 2020-09-07 21:20:09 +02:00
yosata cce60766fc included data files into installation 2020-08-07 13:32:24 +02:00
yosata 2b1835c814 fixed minor bug 2020-08-05 15:59:25 +02:00
yosata 1abb7af4e9 updated README 2020-08-05 11:39:48 +02:00
yosata c1f94e4d95 ported slalib.sla_refro, some refactoring 2020-08-05 11:37:49 +02:00
yosata 83d0c9ea45 Fixed typo in setup.py 2020-08-03 11:14:10 +02:00
yosata 502183889b Refactored some variable names and updated descriptions 2020-08-03 11:07:42 +02:00
yosata e9e4b4ccd6 Fixed merging conflict 2020-07-29 15:26:42 +02:00
yosata b024ae5d3a Added Mathars exponential refraction model 2020-07-29 15:21:14 +02:00
Joost van den Born a21288554b Update README.md with publication reference 2020-07-01 11:35:28 +02:00
yosata e5e20e3584 Updated setup.py for v1.0 release. 2020-06-24 17:05:04 +02:00
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+3 -2
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@@ -5,6 +5,7 @@ from .ciddorModel import *
from .dispersionModels import * from .dispersionModels import *
from .refractionModels import * from .refractionModels import *
from .refractionModels import * from .refractionModels import *
from .examples import * from .misc import *
from .refractivityModels import * from .refractivityModels import *
from .neoslalib import *
from .observatories import *
+493 -360
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@@ -14,6 +14,7 @@ from .ciddorModel import Observatory
The actual refraction is calculated by any of the following models: The actual refraction is calculated by any of the following models:
- Plane parallel atmosphere - Plane parallel atmosphere
- Cassini spherical homogeneous atmosphere - Cassini spherical homogeneous atmosphere
- Mathar's Barometric exponential model
- Other methods described in Corbard et al., 2019. - Other methods described in Corbard et al., 2019.
''' '''
@@ -38,39 +39,45 @@ class dispersion(Observatory):
Methods Methods
------- -------
setReducedHeight(p, rho)
Sets the reduced atmospheric height.
planeParallel(n1, n2, zenith)
Returns the atmospheric dispersion assuming a plane parallel
atmosphere
cassini(n1, n2, zenith, reduced_height=None) cassini(n1, n2, zenith, reduced_height=None)
Returns the atmospheric dispersion asusming Cassini's homegeneous Returns the atmospheric dispersion assuming Cassini's homegeneous
atmosphere model atmosphere model.
tan5(n1, n2, zenith, reduced_height=None)
Returns the atmospheric dispersion following Oriani's theorem,
including a fifth order term in the expansion.
oriani(n1, n2, zenith, reduced_height=None)
Returns the atmospheric dispersion following the classic version
of Oriani's theorem.
corbard(n1, n2, zenith, reduced_height=None)
Returns the atmospheric dispersion following the method described
in Corbard et al., 2019.
refractionIntegral(n1, n2, z0, R0=None, useStandardAtmosphere=True, heightData=None, rhoData=None)
Returns the atmospheric dispersion following the refraction integral.
psi(x)
Submethod for corbard()
set_rc()
Sets the local radius of curvature of the Earth at the observer.
set_H(p, rho)
Sets the reduced height for the conditions at the observer, assuming
an adiabatic atmosphere.
H_isotherm(T)
Sets the reduced height for the conditions at the observer, assuming
an isothermal atmosphere.
cassiniError(z, l1, l2, T, p, RH, xc, dl1=0, dl2=0, dT=0.2, dP=20, cassiniError(z, l1, l2, T, p, RH, xc, dl1=0, dl2=0, dT=0.2, dP=20,
dRH=0.02, dCO2=20, dz=0, lat=None, h=None) dRH=0.02, dCO2=20, dz=0, lat=None, h=None)
Returns the uncertainty in the atmospheric dispersion, assuming Returns the uncertainty in the atmospheric dispersion, assuming
Cassini's homegeneous atmosphere model and the given parameters. Cassini's homegeneous atmosphere model and the given parameters.
corbard(n1, n2, zenith, reduced_height=None)
Returns the atmospheric dispersion following the method described
in Corbard et al., 2019.
gammaCoefficients(n1, reduced_height=None)
Helper function for matharExponential(), that calculates the gamma
coefficients.
H_isotherm(T)
Sets the reduced height for the conditions at the observer, assuming
an isothermal atmosphere.
matharExponential(n1, n2, zenith, reduced_height=None)
Returns the atmospheric dispersion assuming Mathar's barometric
exponential model.
oriani(n1, n2, zenith, reduced_height=None)
Returns the atmospheric dispersion following the classic version
of Oriani's theorem.
planeParallel(n1, n2, zenith)
Returns the atmospheric dispersion assuming a plane parallel
atmosphere.
psi(x)
Submethod for corbard().
refractionIntegral(n1, n2, zenith, R0=None, useStandardAtmosphere=True, heightData=None, rhoData=None)
Returns the atmospheric dispersion following the refraction integral.
setReducedHeight(p, rho)
Sets the reduced atmospheric height.
set_H(p, rho)
Sets the reduced height for the conditions at the observer, assuming
an adiabatic atmosphere.
set_rc()
Sets the local radius of curvature of the Earth at the observer.
tan5(n1, n2, zenith, reduced_height=None)
Returns the atmospheric dispersion following Oriani's theorem,
including a fifth order term in the expansion.
Other Observatory() methods Other Observatory() methods
''' '''
def __init__(self, lat, h): def __init__(self, lat, h):
@@ -79,44 +86,6 @@ class dispersion(Observatory):
self.lat = lat # Latitude of the observer in degrees self.lat = lat # Latitude of the observer in degrees
self.rc = self.set_rc() * 1000 # Radius of curvature of the earth at the observer self.rc = self.set_rc() * 1000 # Radius of curvature of the earth at the observer
def setReducedHeight(self, p, rho):
'''
Sets the reduced atmospheric height.
Parameters
----------
p : float
Atmospheric pressure in Pascal
rho : float
Density of the atmospheric air at the observer
'''
self.H = self.set_H(p, rho) # Reduced height of the atmosphere assuming ideal gas law
def planeParallel(self, n1, n2, zenith):
'''
Refraction based on a flat atmosphere, easily derived from Snell's law.
Parameters
----------
n1 : float
Refractive index at the shortest wavelength of interest
n2 : float
Refractive index at the longest wavelength of interest
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
Returns
-------
dR : float
Atmospheric dispersion in degrees
'''
_R1 = np.arcsin(n1 * np.sin( np.deg2rad(zenith) )) - np.deg2rad(zenith)
_R2 = np.arcsin(n2 * np.sin( np.deg2rad(zenith) )) - np.deg2rad(zenith)
return np.degrees(_R1) - np.degrees(_R2)
def cassini(self, n1, n2, zenith, reduced_height=None): def cassini(self, n1, n2, zenith, reduced_height=None):
''' '''
@@ -150,297 +119,7 @@ class dispersion(Observatory):
return np.degrees(_R1) - np.degrees(_R2) return np.degrees(_R1) - np.degrees(_R2)
def cassiniError(self, zenith, l1, l2, T, p, RH, xc, dl1=0, dl2=0, dT=0.2, dP=20,
def tan5(self, n1, n2, zenith, reduced_height=None):
'''
Same as oriani's theorem, but including a higher order term.
Found in Corbard et al., 2019.
Parameters
----------
n1 : float
Refractive index at the shortest wavelength of interest
n2 : float
Refractive index at the longest wavelength of interest
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
reduced_height : float (optional)
Reduced height of the atmosphere. Default value is calculated
from the object attributes.
Returns
-------
dR : float
Atmospheric dispersion in degrees
'''
if reduced_height:
H = reduced_height
else:
H = self.H
_rList = []
for _n in [n1, n2]:
_a = _n - 1
_b = H / self.rc
_R = _a * (1 - _b) * np.tan( np.deg2rad(zenith) ) - _a * (_b - _a/2) * np.tan( np.deg2rad(zenith) )**3 + 3 * _a * (_b - _a/2)**2 * np.tan( np.deg2rad(zenith) )**5
_rList.append(np.degrees(_R))
return _rList[0] - _rList[1]
def oriani(self, n1, n2, zenith, reduced_height=None):
'''
Classic refraction formula with two tan(z) terms.
This does not assume any information about the structure
of the atmosphere. Found with Oriani's theorem.
Parameters
----------
n1 : float
Refractive index at the shortest wavelength of interest
n2 : float
Refractive index at the longest wavelength of interest
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
reduced_height : float (optional)
Reduced height of the atmosphere. Default value is calculated
from the object attributes.
Returns
-------
dR : float
Atmospheric dispersion in degrees
'''
if reduced_height:
H = reduced_height
else:
H = self.H
_rList = []
for _n in [n1, n2]:
_a = _n - 1
_b = H / self.rc
_R = _a * (1 - _b) * np.tan( np.deg2rad(zenith) ) - _a * (_b - _a/2) * np.tan( np.deg2rad(zenith) )**3
_rList.append(np.degrees(_R))
return _rList[0] - _rList[1]
def corbard(self, n1, n2, zenith, reduced_height=None):
'''
Corbard et al., 2019, mention an additional formula based on
the error function. Oriani's theorem can be derived from this
equation by 'keeping only the three first terms of its
asymptotic expansion'.
Parameters
----------
n1 : float
Refractive index at the shortest wavelength of interest
n2 : float
Refractive index at the longest wavelength of interest
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
reduced_height : float (optional)
Reduced height of the atmosphere. Default value is calculated
from the object attributes.
Returns
-------
dR : float
Atmospheric dispersion in degrees
'''
if reduced_height:
H = reduced_height
else:
H = self.H
_rList = []
for _n in [n1, n2]:
_a = _n - 1
_b = H / self.rc
_R = _a * ( (2 - _a) / (np.sqrt( 2*_b - _a )) ) * np.sin( np.deg2rad(zenith) ) * self.psi( (np.cos(np.deg2rad(zenith))) / np.sqrt(2*_b - _a) )
_rList.append(np.degrees(_R))
return _rList[0] - _rList[1]
def refractionIntegral(self, n1, n2, z0, R0=None, useStandardAtmosphere=True,
heightData=None, rhoData=None):
'''
Using data that gives temperature, pressure and density as a
function of height, the gladstone-dale relation is invoked to
calculate the path of a light ray along the atmosphere.
This is allows us to also include atmospheric activity in
different atmosphere layers.
Recommended use with the US Standard Atmosphere from 1976.
USSA1976 data generated from code supplied by http://www.pdas.com/atmos.html
The method described in eq. 3 in Auer & Standish (2000) is used for the
calculation.
Parameters
----------
n1 : float
Refractive index at the shortest wavelength of interest
n2 : float
Refractive index at the longest wavelength of interest
z0 : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
R0 : float (optional)
Local radius of curvature of the Earth in km.
useStandardAtmosphere : bool
Flag to use the included USSA1976 data
heightData : 1D Array
If "useStandardAtmosphere" is False, the function will ask
for alternative atmospheric data to integrate over. This
gives the altitudinal points
rhoData : 1D Array
If useStandardAtmosphere is False, the function will ask
for alternative atmospheric data to integrate over. This
gives the atmospheric density at the points defined by
"heightData".
Returns
-------
dR : float
Atmospheric dispersion in degrees
'''
if not R0:
R0 = self.rc
if useStandardAtmosphere:
_datafileLocation = os.path.join(os.path.dirname(__file__), 'data/1976USSA.txt')
_h, _, _, _, _Temp, _Press, _Dens,_,_,_ = np.genfromtxt(_datafileLocation, unpack=True, skip_header=6)
else:
_Dens = rhoData
_h = heightData
_rList = []
z0 = np.deg2rad(z0)
# Integration of the refraction integral over the atmosphere layers.
for _n in [n1, n2]:
_Dens = np.asarray(_Dens)
_h = np.asarray(_h)
_R = R0 + _h * 1000
# Gladstone-Dale relation between refractive index and density
_n_h = 1 + (_n - 1) / _Dens[0] * _Dens
# Calculation of the zenith angle for given height and refractive index, from the refractive invariant
_z = np.arcsin( (_n * R0) / (_n_h * _R) * np.sin(z0) )
# Calculation of log space derivative of n and r
_lnn = np.log(_n_h)
_lnr = np.log(_R)
_dlnn = np.asarray([_lnn[i+1] - _lnn[i] for i in range(len(_lnn)-1)])
_dlnr = np.asarray([_lnr[i+1] - _lnr[i] for i in range(len(_lnr)-1)])
_dz = np.asarray([(_z[i] - _z[i+1]) for i in range(len(_z)-1)])
# Calculation of the integrand in eq. 3 in Auer & Standish
_Integrand = -1*(_dlnn/_dlnr) / (1 + _dlnn/_dlnr) * _dz
_rList.append(np.degrees(np.sum(_Integrand)))
return _rList[0] - _rList[1]
def psi(self, x):
'''
Submethod for corbard(). Described explicitly in Corbard et al.,2019.
Parameters
----------
x : float
Input of the function
Returns
-------
y : float
Output of the function
'''
_f = lambda a: np.exp(-a**2)
_int = integrate.quad(_f, x, np.inf)
return np.exp(x**2) * _int[0]
def set_rc(self):
'''
Returns the radius of the curvature at the observer in km,
taking into account the latitude of the observer and the corresponding
ellipsoidality of the earth.
Returns
-------
rc : float
Local radius of curvature of the Earth in kilometers.
'''
_A = 6378.137 # km
_B = 6356.752 # km
_phi = np.deg2rad(self.lat)
_rc0 = (_A*_B)**2 / (_A**2 * np.cos(_phi)**2 + _B**2 * np.sin(_phi)**2)**(3/2)
return _rc0 + self.h/1000
def set_H(self, p, rho):
'''
Calculates the reduced height of the atmosphere, assuming ideal gas law.
Parameters
----------
p : float
Atmospheric pressure in Pascal
rho : float
Density of the atmospheric air at the observer
Returns
-------
H : float
Reduced height of the atmosphere in meters
'''
_phi = np.deg2rad(self.lat)
_c1 = 5.2790414e-3
_c2 = 2.32718e-5
_c3 = 1.262e-7
_c4 = 7e-10
_g0 = 9.780327 # m/s^2
_g0_local = _g0 * (1 + _c1 * np.sin(_phi)**2 + _c2 * np.sin(_phi)**4 + _c3 * np.sin(_phi)**6 + _c4 * np.sin(_phi)**8)
_g = _g0_local - (3.0877e-6 - 4.3e-9 * np.sin(_phi)**2) * self.h + 7.2e-13 * self.h**2
return p / (rho * _g)
def H_isotherm(self, T):
'''
Calculates the reduced height of the atmosphere,
assuming an isotherm distribution.
Parameters
----------
T : float
Atmospheric temperature in Kelvin
Returns
-------
H : float
Reduced height of the atmosphere in meters
'''
_kb = 1.38064852e-23 # kg m2 s-2 K-1
_m = 4.809651698e-26 # kg (weight per molecule of air, assuming dry air)
_phi = np.deg2rad(self.lat)
_c1 = 5.2790414e-3
_c2 = 2.32718e-5
_c3 = 1.262e-7
_c4 = 7e-10
_g0 = 9.780327 # m/s^2
_g0_local = _g0 * (1 + _c1 * np.sin(_phi)**2 + _c2 * np.sin(_phi)**4 + _c3 * np.sin(_phi)**6 + _c4 * np.sin(_phi)**8)
return (_kb*T) / (_m * _g0_local)
def cassiniError(self, z, l1, l2, T, p, RH, xc, dl1=0, dl2=0, dT=0.2, dP=20,
dRH=0.02, dCO2=20, dz=0, lat=None, h=None): dRH=0.02, dCO2=20, dz=0, lat=None, h=None):
''' '''
Calculates the uncertainty in the atmospheric dispersion, Calculates the uncertainty in the atmospheric dispersion,
@@ -455,7 +134,7 @@ class dispersion(Observatory):
Parameters Parameters
---------- ----------
z : float zenith : float
Angle of observation in degrees. Angle of observation in degrees.
zenith = 0 means the observation is directly overhead. zenith = 0 means the observation is directly overhead.
l1 : float l1 : float
@@ -549,7 +228,7 @@ class dispersion(Observatory):
_rho_obs = self.rho(p, T, RH, xc) _rho_obs = self.rho(p, T, RH, xc)
self.rc = self.set_rc() * 1000 self.rc = self.set_rc() * 1000
self.H = self.set_H(p, _rho_obs) self.H = self.set_H(p, _rho_obs)
_alpha = self.rc * np.sin(np.deg2rad(z)) / (self.rc + self.H) _alpha = self.rc * np.sin(np.deg2rad(zenith)) / (self.rc + self.H)
_p_a = p - RH*self.svp(T) _p_a = p - RH*self.svp(T)
_p_w = RH*self.svp(T) _p_w = RH*self.svp(T)
_x_w_a = self.xw(_p_a, T, _RH_a) _x_w_a = self.xw(_p_a, T, _RH_a)
@@ -696,7 +375,7 @@ class dispersion(Observatory):
# Partial derivatives for derivation to z # Partial derivatives for derivation to z
_zenith = np.deg2rad(z) _zenith = np.deg2rad(zenith)
_dz = np.deg2rad(dz) _dz = np.deg2rad(dz)
_R = self.rc _R = self.rc
_H = self.H _H = self.H
@@ -706,3 +385,457 @@ class dispersion(Observatory):
_dispersionError = np.sqrt( (_dddl1 * dl1)**2 + (_dddl2 * dl2)**2 + (_dddT * dT)**2 + (_dddP * dP)**2 + (_dddRH * dRH)**2 + (_dddCO2 * dCO2)**2 + (_dddz * _dz)**2) _dispersionError = np.sqrt( (_dddl1 * dl1)**2 + (_dddl2 * dl2)**2 + (_dddT * dT)**2 + (_dddP * dP)**2 + (_dddRH * dRH)**2 + (_dddCO2 * dCO2)**2 + (_dddz * _dz)**2)
return np.degrees(_dispersionError) return np.degrees(_dispersionError)
def corbard(self, n1, n2, zenith, reduced_height=None):
'''
Corbard et al., 2019, mention an additional formula based on
the error function. Oriani's theorem can be derived from this
equation by 'keeping only the three first terms of its
asymptotic expansion'.
Parameters
----------
n1 : float
Refractive index at the shortest wavelength of interest
n2 : float
Refractive index at the longest wavelength of interest
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
reduced_height : float (optional)
Reduced height of the atmosphere. Default value is calculated
from the object attributes.
Returns
-------
dR : float
Atmospheric dispersion in degrees
'''
if reduced_height:
H = reduced_height
else:
H = self.H
_rList = []
for _n in [n1, n2]:
_a = _n - 1
_b = H / self.rc
_R = _a * ( (2 - _a) / (np.sqrt( 2*_b - _a )) ) * np.sin( np.deg2rad(zenith) ) * self.psi( (np.cos(np.deg2rad(zenith))) / np.sqrt(2*_b - _a) )
_rList.append(np.degrees(_R))
return _rList[0] - _rList[1]
def gammaCoefficients(self, n1, reduced_height=None):
'''
Submethod for matharExponential(). Calculates the gamma
coefficients.
Parameters
----------
n1 : float
Refractive index at the wavelength of interest at the observer
reduced_height : float (optional)
Reduced height of the atmosphere. Default value is calculated
from the object attributes.
Returns
-------
g : array
List of values, corresponding to the gamma coefficients.
g[0] corresponds to g_1, g[1] to g_3, g[2] to g_5, and so on.
'''
if reduced_height:
H = reduced_height
else:
H = self.H
_chi0 = n1**2 - 1
_Khat = H / self.rc
_g1 = (1 - 5/24 * _Khat * _chi0**2 - 3/4 * _chi0 - 3/8 * _Khat**2 * _chi0 \
- _Khat - 6 * _Khat**3 + 5/8 * _chi0**2 + 63/128 * _chi0**4 + 3/8 \
* _Khat * _chi0 + 35/256 * _Khat * _chi0**3 + 2 * _Khat**2 + 5/36 \
* _Khat**2 * _chi0**2 - 35/64 * _chi0**3 + 9/16 * _Khat**3 * _chi0 \
- 120 * _Khat**5 + 24 * _Khat**4 - 231 / 512 * _chi0**5 - 63 / 640 \
* _Khat * _chi0**4 - 35 / 512 * _Khat**2 * _chi0**3 - 5 / 36 * _Khat**3\
* _chi0**2 - 9 / 8 * _Khat**4 * _chi0 )
_g3 = (35/96 * _chi0**3 - 5/12 * _chi0**2 + 333 * _Khat**4 * _chi0 - 2400 \
* _Khat**5 + 3605/4608 * _Khat**2 * _chi0**3 + 63/256 * _Khat * _chi0**4\
- 819/16 * _Khat**3 * _chi0 - 35/18 * _Khat**2 * _chi0**2 - 35/96 \
* _Khat * _chi0**3 + 69/8 * _Khat**2 * _chi0 + 5/8 * _Khat * _chi0**2 \
- 3/2 * _Khat * _chi0 + 1355/216 * _Khat**3 * _chi0**2 + 10 * _Khat**2 \
+ 336 * _Khat**4 - 2 * _Khat + _chi0/2 - 21/64 * _chi0**4 - 54 * _Khat**3 \
+ 77/256 * _chi0**5 ) * 1/2
_g5 = (-96 * _Khat**3 + 8 * _Khat**2 - 7/24 * _chi0**3 + 65/4 * _Khat**2 \
* _chi0**2 + 35/48 * _Khat * _chi0**3 + 30 * _Khat**2 * _chi0 - 5/3 \
* _Khat * _chi0**2 - 3 * _Khat * _chi0 + 20091/8 * _Khat**4 * _chi0 \
- 32605/216 * _Khat**3 * _chi0**2 - 35/9 * _Khat**2 * _chi0**3 + 984 \
* _Khat**4 + _chi0**2/3 - 10200 * _Khat**5 - 77/320 * _chi0**5 + 21/80 \
* _chi0**4 - 1089/4 * _Khat**3 * _chi0 - 7/16 * _Khat * _chi0**4 ) * 3/8
_g7 = (-17520 * _Khat**5 - 9/40 * _chi0**4 - 8755/12 * _Khat**3 * _chi0**2 \
+ 1056 * _Khat**4 + _chi0**3/4 + 23517/4 * _Khat**4 * _chi0 - 11/3 \
* _Khat * _chi0**2 + 21 * _Khat**2 * _chi0 - 7/4 * _Khat * _chi0**3 \
+ 505/9 * _Khat**2 * _chi0**2 - 801/2 * _Khat**3 * _chi0 + 33/160 \
* _chi0**5 - 48 * _Khat**3 + 63/80 * _Khat * _chi0**4 + 2345/96 \
* _Khat**2 * _chi0**3) * 5/16
_g9 = (_chi0**4 / 5 + 384 * _Khat**4 - 13440 * _Khat**5 + 5562 * _Khat**4 \
* _chi0 + 3125/36 * _Khat**2 * _chi0**3 - 11/60 * _chi0**5 - 25/6 \
* _Khat * _chi0**3 - 26950/27 * _Khat**3 * _chi0**2 + 340/9 * _Khat**2 \
* _chi0**2 - 180 * _Khat**3 * _chi0 - 9/5 * _Khat * _chi0**4) * 35/128
g = np.array([_g1, _g3, _g5, _g7, _g9])
g*= n1*_chi0/2
return g
def H_isotherm(self, T):
'''
Calculates the reduced height of the atmosphere,
assuming an isotherm distribution.
Parameters
----------
T : float
Atmospheric temperature in Kelvin
Returns
-------
H : float
Reduced height of the atmosphere in meters
'''
_kb = 1.38064852e-23 # kg m2 s-2 K-1
_m = 4.809651698e-26 # kg (weight per molecule of air, assuming dry air)
_phi = np.deg2rad(self.lat)
_c1 = 5.2790414e-3
_c2 = 2.32718e-5
_c3 = 1.262e-7
_c4 = 7e-10
_g0 = 9.780327 # m/s^2
_g0_local = _g0 * (1 + _c1 * np.sin(_phi)**2 + _c2 * np.sin(_phi)**4 + _c3 * np.sin(_phi)**6 + _c4 * np.sin(_phi)**8)
return (_kb*T) / (_m * _g0_local)
def matharExponential(self, n1, n2, zenith, reduced_height=None):
'''
Model on atmospheric refraction described by Richard Mathar in
"A Barometric Exponential Model of the Atmosphere’s Refractive Index: ZenithAngles and Second Order Aberration in the Entrance Pupil" (2020)
ArXiv id: 2004.11808 (https://arxiv.org/abs/2004.11808)
The code in this function is adapted from eqs 3, 16, 17 and 18 in this
work. It is an adaptation of the RefrExpo.cxx C++ file written by Mathar.
This model assumes the refractive index, n, is related to the susceptibility,
chi, following: n(r) = sqrt(1+chi(r)) (eq. 9).
R. Mathar then assumes that the susceptibility is proportional to the
air density and reduced height, following eq. 10:
chi(r) = chi0 * exp(-(r-rho)/K).
The refraction is described using a Taylor expansion; R in terms of
the odd powers of the tangent of the observed zenith angle (eq. 3), not
unlike Oriani's theorem. This requires coefficients g_i.
Parameters
----------
n1 : float
Refractive index at the wavelength of interest at the observer
n2 : float
Refractive index at the longest wavelength of interest at the
observer
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
reduced_height : float (optional)
Reduced height of the atmosphere. Default value is calculated
from the object attributes.
Returns
-------
dR : float
Atmospheric refraction in degrees
'''
if reduced_height:
_H = reduced_height
else:
_H = self.H
_zenith = np.deg2rad(zenith)
_rc = self.rc # rho
# Atmospheric refraction for the first wavelength
_gamma1 = self.gammaCoefficients(n1, reduced_height=_H)
_R1 = sum([_gamma1[i]*np.tan(_zenith)**(2*i+1) for i in range(len(_gamma1))])
# Atmospheric refraction for the second wavelength
_gamma2 = self.gammaCoefficients(n2, reduced_height=_H)
_R2 = sum([_gamma2[i]*np.tan(_zenith)**(2*i+1) for i in range(len(_gamma2))])
# The atmospheric dispersion in radians
_dR = _R1 - _R2
return np.degrees(_dR)
def oriani(self, n1, n2, zenith, reduced_height=None):
'''
Classic refraction formula with two tan(z) terms.
This does not assume any information about the structure
of the atmosphere. Found with Oriani's theorem.
Parameters
----------
n1 : float
Refractive index at the shortest wavelength of interest
n2 : float
Refractive index at the longest wavelength of interest
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
reduced_height : float (optional)
Reduced height of the atmosphere. Default value is calculated
from the object attributes.
Returns
-------
dR : float
Atmospheric dispersion in degrees
'''
if reduced_height:
H = reduced_height
else:
H = self.H
_rList = []
for _n in [n1, n2]:
_a = _n - 1
_b = H / self.rc
_R = _a * (1 - _b) * np.tan( np.deg2rad(zenith) ) - _a * (_b - _a/2) * np.tan( np.deg2rad(zenith) )**3
_rList.append(np.degrees(_R))
return _rList[0] - _rList[1]
def planeParallel(self, n1, n2, zenith):
'''
Refraction based on a flat atmosphere, easily derived from Snell's law.
Parameters
----------
n1 : float
Refractive index at the shortest wavelength of interest
n2 : float
Refractive index at the longest wavelength of interest
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
Returns
-------
dR : float
Atmospheric dispersion in degrees
'''
_R1 = np.arcsin(n1 * np.sin( np.deg2rad(zenith) )) - np.deg2rad(zenith)
_R2 = np.arcsin(n2 * np.sin( np.deg2rad(zenith) )) - np.deg2rad(zenith)
return np.degrees(_R1) - np.degrees(_R2)
def psi(self, x):
'''
Submethod for corbard(). Described explicitly in Corbard et al.,2019.
Parameters
----------
x : float
Input of the function
Returns
-------
y : float
Output of the function
'''
_f = lambda a: np.exp(-a**2)
_int = integrate.quad(_f, x, np.inf)
return np.exp(x**2) * _int[0]
def refractionIntegral(self, n1, n2, zenith, R0=None, useStandardAtmosphere=True,
heightData=None, rhoData=None):
'''
Using data that gives temperature, pressure and density as a
function of height, the gladstone-dale relation is invoked to
calculate the path of a light ray along the atmosphere.
This is allows us to also include atmospheric activity in
different atmosphere layers.
Recommended use with the US Standard Atmosphere from 1976.
USSA1976 data generated from code supplied by http://www.pdas.com/atmos.html
The method described in eq. 3 in Auer & Standish (2000) is used for the
calculation.
Parameters
----------
n1 : float
Refractive index at the shortest wavelength of interest
n2 : float
Refractive index at the longest wavelength of interest
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
R0 : float (optional)
Local radius of curvature of the Earth in km.
useStandardAtmosphere : bool
Flag to use the included USSA1976 data
heightData : 1D Array
If "useStandardAtmosphere" is False, the function will ask
for alternative atmospheric data to integrate over. This
gives the altitudinal points
rhoData : 1D Array
If useStandardAtmosphere is False, the function will ask
for alternative atmospheric data to integrate over. This
gives the atmospheric density at the points defined by
"heightData".
Returns
-------
dR : float
Atmospheric dispersion in degrees
'''
if not R0:
R0 = self.rc
if useStandardAtmosphere:
_datafileLocation = os.path.join(os.path.dirname(__file__), 'data/1976USSA.txt')
_h, _, _, _, _Temp, _Press, _Dens,_,_,_ = np.genfromtxt(_datafileLocation, unpack=True, skip_header=6)
else:
_Dens = rhoData
_h = heightData
_rList = []
zenith = np.deg2rad(zenith)
# Integration of the refraction integral over the atmosphere layers.
for _n in [n1, n2]:
_Dens = np.asarray(_Dens)
_h = np.asarray(_h)
_R = R0 + _h * 1000
# Gladstone-Dale relation between refractive index and density
_n_h = 1 + (_n - 1) / _Dens[0] * _Dens
# Calculation of the zenith angle for given height and refractive index, from the refractive invariant
_z = np.arcsin( (_n * R0) / (_n_h * _R) * np.sin(zenith) )
# Calculation of log space derivative of n and r
_lnn = np.log(_n_h)
_lnr = np.log(_R)
_dlnn = np.asarray([_lnn[i+1] - _lnn[i] for i in range(len(_lnn)-1)])
_dlnr = np.asarray([_lnr[i+1] - _lnr[i] for i in range(len(_lnr)-1)])
_dz = np.asarray([(_z[i] - _z[i+1]) for i in range(len(_z)-1)])
# Calculation of the integrand in eq. 3 in Auer & Standish
_Integrand = -1*(_dlnn/_dlnr) / (1 + _dlnn/_dlnr) * _dz
_rList.append(np.degrees(np.sum(_Integrand)))
return _rList[0] - _rList[1]
def setReducedHeight(self, p, rho):
'''
Sets the reduced atmospheric height.
Parameters
----------
p : float
Atmospheric pressure in Pascal
rho : float
Density of the atmospheric air at the observer
'''
self.H = self.set_H(p, rho) # Reduced height of the atmosphere assuming ideal gas law
def set_H(self, p, rho):
'''
Calculates the reduced height of the atmosphere, assuming ideal gas law.
Parameters
----------
p : float
Atmospheric pressure in Pascal
rho : float
Density of the atmospheric air at the observer
Returns
-------
H : float
Reduced height of the atmosphere in meters
'''
_phi = np.deg2rad(self.lat)
_c1 = 5.2790414e-3
_c2 = 2.32718e-5
_c3 = 1.262e-7
_c4 = 7e-10
_g0 = 9.780327 # m/s^2
_g0_local = _g0 * (1 + _c1 * np.sin(_phi)**2 + _c2 * np.sin(_phi)**4 + _c3 * np.sin(_phi)**6 + _c4 * np.sin(_phi)**8)
_g = _g0_local - (3.0877e-6 - 4.3e-9 * np.sin(_phi)**2) * self.h + 7.2e-13 * self.h**2
return p / (rho * _g)
def set_rc(self):
'''
Returns the radius of the curvature at the observer in km,
taking into account the latitude of the observer and the corresponding
ellipsoidality of the earth.
Returns
-------
rc : float
Local radius of curvature of the Earth in kilometers.
'''
_A = 6378.137 # km
_B = 6356.752 # km
_phi = np.deg2rad(self.lat)
_rc0 = (_A*_B)**2 / (_A**2 * np.cos(_phi)**2 + _B**2 * np.sin(_phi)**2)**(3/2)
return _rc0 + self.h/1000
def tan5(self, n1, n2, zenith, reduced_height=None):
'''
Same as oriani's theorem, but including a higher order term.
Found in Corbard et al., 2019.
Parameters
----------
n1 : float
Refractive index at the shortest wavelength of interest
n2 : float
Refractive index at the longest wavelength of interest
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
reduced_height : float (optional)
Reduced height of the atmosphere. Default value is calculated
from the object attributes.
Returns
-------
dR : float
Atmospheric dispersion in degrees
'''
if reduced_height:
H = reduced_height
else:
H = self.H
_rList = []
for _n in [n1, n2]:
_a = _n - 1
_b = H / self.rc
_R = _a * (1 - _b) * np.tan( np.deg2rad(zenith) ) - _a * (_b - _a/2) * np.tan( np.deg2rad(zenith) )**3 + 3 * _a * (_b - _a/2)**2 * np.tan( np.deg2rad(zenith) )**5
_rList.append(np.degrees(_R))
return _rList[0] - _rList[1]
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@@ -1,205 +0,0 @@
#!/usr/bin/env Python3
from .ciddorModel import Observatory
from .refractionModels import refraction
from .dispersionModels import dispersion
'''
@ Author: Joost van den Born
@ Contact: born@astron.nl
@ Description: Some functions for quick testing.
'''
def quick_refractive_index(l, conditions='STANDARD', T=288.15, p=101325,
H=0.0, xc=450, lat=0, h=0):
'''
Function to quickly calculate the refractive index
of atmospheric air at reference conditions, given
a wavelength l.
Parameters
----------
l : float
Wavelength in microns
conditions: string
'STANDARD' or 'CERRO_ARMAZONES', refers
to the standard atmospheric conditions.
T : float (optional)
Temperature in Kelvin
p : float (optional)
Atmospheric pressure in Pa
H : float (optional)
Relative humidity
xc : float (optional)
CO2 density in parts per million
lat : float (optional)
Latitude of the observer in degrees
h : float (optional)
Altitude of the observer in meters
Returns
-------
n : float
Refractive index for the given conditions.
'''
if conditions == 'STANDARD':
# Parameters at Cerro Armazones
T = 288.15 # k
p = 101325 # Pa
H = 0.0
xc = 450 # ppm
lat = 0 # degrees
h = 0 # m
elif conditions == 'CERRO_ARMAZONES':
# Parameters at Cerro Armazones
T = 279.65 # k
p = 71200 # Pa
H = 0.22
xc = 450 # ppm
lat = -24.5983 # degrees
h = 3064 # m
# Initializing dispersion model
at = Observatory()
# Calculating indices of refraction for l
n = at.n_tph(l=l, T=T, p=p, RH=H, xc=xc)
return n
def quick_refraction(l, z, conditions='STANDARD', T=288.15, p=101325,
H=0.0, xc=450, lat=0, h=0):
'''
Function to quickly calculate the refraction
of atmospheric air at reference conditions,
given a wavelength l.
Parameters
----------
l : float
Wavelength in microns
z : float
Zenith angle of the observation
conditions : string
'STANDARD' or 'CERRO_ARMAZONES', refers
to the standard atmospheric conditions.
T : float (optional)
Temperature in Kelvin
p : float (optional)
Atmospheric pressure in Pa
H : float (optional)
Relative humidity
xc : float (optional)
CO2 density in parts per million
lat : float (optional)
Latitude of the observer in degrees
h : float (optional)
Altitude of the observer in meters
Returns
-------
R : float
Refraction in degrees
'''
if conditions == 'STANDARD':
# Parameters at Cerro Armazones
T = 288.15 # k
p = 101325 # Pa
H = 0.0
xc = 450 # ppm
lat = 0 # degrees
h = 0 # m
elif conditions == 'CERRO_ARMAZONES':
# Parameters at Cerro Armazones
T = 279.65 # k
p = 71200 # Pa
H = 0.22
xc = 450 # ppm
lat = -24.5983 # degrees
h = 3064 # m
# Initializing dispersion model
at = Observatory()
# Calculating indices of refraction for l
n = at.n_tph(l=l, T=T, p=p, RH=H, xc=xc)
# Density of the atmosphere (following CIPM-81/91 equations)
rho = at.rho(p=p, T=T, RH=H, xc=xc)
# Initializing refraction model and setting the reduced height
ref = refraction(lat, h)
ref.setReducedHeight(p, rho)
return ref.cassini(n, z)
def quick_dispersion(l1, l2, z, conditions='STANDARD', T=288.15,
p=101325, H=0.0, xc=450, lat=0, h=0):
'''
Function to quickly calculate the dispersion
of atmospheric air at reference conditions,
given a wavelength l.
Parameters
----------
l1 : float
Shortest wavelength of interest in micron.
l2 : float
Longest wavelength of interest in micron.
z : float
Zenith angle of the observation
conditions : string
'STANDARD' or 'CERRO_ARMAZONES', refers
to the standard atmospheric conditions.
T : float (optional)
Temperature in Kelvin
p : float (optional)
Atmospheric pressure in Pa
H : float (optional)
Relative humidity
xc : float (optional)
CO2 density in parts per million
lat : float (optional)
Latitude of the observer in degrees
h : float (optional)
Altitude of the observer in meters
Returns
-------
dR : float
Atmospheric dispersion in degrees
'''
if conditions == 'STANDARD':
# Parameters at Cerro Armazones
T = 288.15 # k
p = 101325 # Pa
H = 0.0
xc = 450 # ppm
lat = 0 # degrees
h = 0 # m
elif conditions == 'CERRO_ARMAZONES':
# Parameters at Cerro Armazones
T = 279.65 # k
p = 71200 # Pa
H = 0.22
xc = 450 # ppm
lat = -24.5983 # degrees
h = 3064 # m
# Initializing dispersion model
at = Observatory()
# Calculating indices of refraction for l1 and l2
n1 = at.n_tph(l=l1, T=T, p=p, RH=H, xc=xc)
n2 = at.n_tph(l=l2, T=T, p=p, RH=H, xc=xc)
# Density of the atmosphere (following CIPM-81/91 equations)
rho = at.rho(p=p, T=T, RH=H, xc=xc)
# Initializing refraction model and setting the reduced height
disp = dispersion(lat, h)
disp.setReducedHeight(p, rho)
return disp.cassini(n1, n2, z)
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@@ -0,0 +1,395 @@
#!/usr/bin/env Python3
from .ciddorModel import Observatory
from .refractionModels import refraction
from .dispersionModels import dispersion
from .neoslalib import sla_refro
from .observatories import observatories
from .refractivityModels import Edlen1953
import numpy as np
'''
@ Author: Joost van den Born
@ Contact: born@astron.nl
@ Description: Some functions for quick testing.
'''
def get_conditions(location):
'''
Returns the mean conditions at various site. Currently
supported locations:
- 'STANDARD'
- 'CERRO_ARMAZONES'
- 'CERRO_PARANAL'
- 'LA_PALMA'
- 'LA_SILLA'
- 'LAS_CAMPANAS'
- 'MAUNA_KEA'
Parameters
----------
location : string
String denoting the desired location
Returns
-------
observatory : dict
Dictionary containing the atmospheric parameters
'''
observatory = observatories[location]
return observatory
def Filippenko1982(l1, l2, zenith, conditions='STANDARD', T=288.15, p=101325,
RH=0.0, xc=450, lat=0, h=0, f=None):
'''
Calculates the refraction following the 1982 paper by
Alexei V. Filippenko.
The refraction is based on a flat atmosphere and the refractivity
values are calculated from a modified Edlen (1953) equation.
Parameters
----------
l1 : float
Shortest wavelength of interest in micron.
l2 : float
Longest wavelength of interest in micron.
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
conditions : string
Refers to the standard conditions of the
observatory. See get_conditions() for more info.
If set to 'None', the conditions specified
after will be used.
T : float (optional)
Temperature in Kelvin
p : float (optional)
Atmospheric pressure in Pa
RH : float (optional)
Relative humidity
xc : float (optional)
CO2 density in parts per million
lat : float (optional)
Latitude of the observer in degrees
h : float (optional)
Altitude of the observer in meters
f : float
Water vapour pressure (default=None). If None, it is
calculated automatically.
Returns
-------
R : float
Atmospheric refraction in degrees
'''
if conditions is not None:
T, p, RH, xc, lat, h, _ = get_conditions(conditions).values()
n1 = Edlen1953(l1, T=T, p=p, RH=RH, f=f)
n2 = Edlen1953(l2, T=T, p=p, RH=RH, f=f)
dR = (n1 - n2) * np.tan(np.deg2rad(zenith))
return np.degrees(dR)
def quick_refractive_index(l, conditions='STANDARD', T=288.15, p=101325,
RH=0.0, xc=450, lat=0, h=0):
'''
Function to quickly calculate the refractive index
of atmospheric air at reference conditions, given
a wavelength l.
Parameters
----------
l : float
Wavelength in microns
conditions: string
Refers to the standard conditions of the
observatory. See get_conditions() for more info.
If set to 'None', the conditions specified
after will be used.
T : float (optional)
Temperature in Kelvin
p : float (optional)
Atmospheric pressure in Pa
RH : float (optional)
Relative humidity
xc : float (optional)
CO2 density in parts per million
lat : float (optional)
Latitude of the observer in degrees
h : float (optional)
Altitude of the observer in meters
Returns
-------
n : float
Refractive index for the given conditions.
'''
if conditions is not None:
T, p, RH, xc, lat, h, _ = get_conditions(conditions).values()
# Initializing dispersion model
at = Observatory()
# Calculating indices of refraction for l
n = at.n_tph(l=l, T=T, p=p, RH=RH, xc=xc)
return n
def quick_refraction(l, zenith, conditions='STANDARD', T=288.15, p=101325,
RH=0.0, xc=450, lat=0, h=0):
'''
Function to quickly calculate the refraction
of atmospheric air at reference conditions,
given a wavelength l.
Parameters
----------
l : float
Wavelength in microns
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
conditions : string
Refers to the standard conditions of the
observatory. See get_conditions() for more info.
If set to 'None', the conditions specified
after will be used.
T : float (optional)
Temperature in Kelvin
p : float (optional)
Atmospheric pressure in Pa
RH : float (optional)
Relative humidity
xc : float (optional)
CO2 density in parts per million
lat : float (optional)
Latitude of the observer in degrees
h : float (optional)
Altitude of the observer in meters
Returns
-------
R : float
Refraction in degrees
'''
if conditions is not None:
T, p, RH, xc, lat, h, _ = get_conditions(conditions).values()
# Initializing dispersion model
at = Observatory()
# Calculating indices of refraction for l
n = at.n_tph(l=l, T=T, p=p, RH=RH, xc=xc)
# Density of the atmosphere (following CIPM-81/91 equations)
rho = at.rho(p=p, T=T, RH=RH, xc=xc)
# Initializing refraction model and setting the reduced height
ref = refraction(lat, h)
ref.setReducedHeight(p, rho)
return ref.cassini(n, zenith)
def quick_dispersion(l1, l2, zenith, conditions='STANDARD', T=288.15,
p=101325, RH=0.0, xc=450, lat=0, h=0):
'''
Function to quickly calculate the dispersion
of atmospheric air at reference conditions,
given a wavelength l.
Parameters
----------
l1 : float
Shortest wavelength of interest in micron.
l2 : float
Longest wavelength of interest in micron.
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
conditions : string
Refers to the standard conditions of the
observatory. See get_conditions() for more info.
If set to 'None', the conditions specified
after will be used.
T : float (optional)
Temperature in Kelvin
p : float (optional)
Atmospheric pressure in Pa
RH : float (optional)
Relative humidity
xc : float (optional)
CO2 density in parts per million
lat : float (optional)
Latitude of the observer in degrees
h : float (optional)
Altitude of the observer in meters
Returns
-------
dR : float
Atmospheric dispersion in degrees
'''
if conditions is not None:
T, p, RH, xc, lat, h, _ = get_conditions(conditions).values()
# Initializing dispersion model
at = Observatory()
# Calculating indices of refraction for l1 and l2
n1 = at.n_tph(l=l1, T=T, p=p, RH=RH, xc=xc)
n2 = at.n_tph(l=l2, T=T, p=p, RH=RH, xc=xc)
# Density of the atmosphere (following CIPM-81/91 equations)
rho = at.rho(p=p, T=T, RH=RH, xc=xc)
# Initializing refraction model and setting the reduced height
disp = dispersion(lat, h)
disp.setReducedHeight(p, rho)
return disp.cassini(n1, n2, zenith)
def slalib_refraction(l, zenith, conditions='STANDARD', T=288.15, p=101325,
RH=0.0, xc=450, lat=0, h=0, tlr=0.0065, eps=1e-8, use_pyslalib=False):
'''
Calculates the atmospheric refraction assuming the SLALIB
package. SLALIB uses the same atmospheric model as ZEMAX
based on the works of Hohenkerk & Sinclair and Seidelmann.
They take the B&S refraction formula as a basis.
The pySLALIB FORTRAN has been ported, so pyslalib is not
needed, but can still be used. There are minor numerical
differences, likely due to precision or declaration issues.
Parameters
----------
l : float
Wavelength in microns
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
conditions : string
Refers to the standard conditions of the
observatory. See get_conditions() for more info.
If set to 'None', the conditions specified
after will be used.
T : float (optional)
Temperature in Kelvin
p : float (optional)
Atmospheric pressure in Pa
RH : float (optional)
Relative humidity
xc : float (optional)
CO2 density in parts per million
lat : float (optional)
Latitude of the observer in degrees (default=0)
h : float (optional)
Altitude of the observer in meters
tlr : float
Temperature lapse rate (default=0.0065)
eps : float
Precision at which the calculation is aborted (default=1e-8)
use_pyslalib : bool
Flag that indicates that the user wants to use the pySlalib
package. If False, the internal python port of the original
FORTRAN code will be used. (default=False).
Returns
-------
R : float
Refraction in degrees
'''
if conditions is not None:
T, p, RH, xc, lat, h, _ = get_conditions(conditions).values()
# Converting units to the units that sla_refro() requires.
_zenith = np.deg2rad(zenith) # From degrees to radians
_P = p / 100 # From Pa to mbar
_phi = np.deg2rad(lat) # From degrees to radians
R = []
if type(l) == float or type(l) == int:
l = [l]
if use_pyslalib:
try:
from pyslalib import slalib
except ImportError as e:
print('pySLALIB package not found! Try installing it first.')
for wl in l:
# If using original slalib (e.g. PySLALIB)
Refrac = slalib.sla_refro(_zenith, h, T, _P, RH, wl, phi, tlr, eps)
R.append(np.degrees(Refrac))
# If using internal slalib port
else:
for wl in l:
Refrac = sla_refro(_zenith, h, T, _P, RH, wl, phi, tlr, eps)
R.append(np.degrees(Refrac))
if len(l) == 1:
return R[0]
else:
return np.asarray(R)
def slalib_dispersion(l1, l2, zenith, conditions='STANDARD', T=288.15, p=101325,
RH=0.0, xc=450, lat=0, h=0, tlr=0.0065, eps=1e-8, use_pyslalib=False):
'''
Calculates the atmospheric refraction assuming the SLALIB
package. SLALIB uses the same atmospheric model as ZEMAX
based on the works of Hohenkerk & Sinclair and Seidelmann.
They take the B&S refraction formula as a basis.
The pySLALIB FORTRAN has been ported, so pyslalib is not
needed, but can still be used. There are minor numerical
differences, likely due to precision or declaration issues.
Parameters
----------
l1 : float
Shortest wavelength of interest in micron.
l2 : float
Longest wavelength of interest in micron.
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
conditions : string
Refers to the standard conditions of the
observatory. See get_conditions() for more info.
If set to 'None', the conditions specified
after will be used.
T : float (optional)
Temperature in Kelvin
p : float (optional)
Atmospheric pressure in Pa
RH : float (optional)
Relative humidity
xc : float (optional)
CO2 density in parts per million
lat : float (optional)
Latitude of the observer in degrees (default=0)
h : float (optional)
Altitude of the observer in meters
tlr : float
Temperature lapse rate (default=0.0065)
eps : float
Precision at which the calculation is aborted (default=1e-8)
use_pyslalib : bool
Flag that indicates that the user wants to use the pySlalib
package. If False, the internal python port of the original
FORTRAN code will be used. (default=False).
Returns
-------
dR : float
Refraction in degrees
'''
R1 = slalib_refraction(l1, zenith, conditions, T, p, RH, xc,\
lat, h, tlr, eps, use_pyslalib)
R2 = slalib_refraction(l2, zenith, conditions, T, p, RH, xc,\
lat, h, tlr, eps, use_pyslalib)
dR = R1 - R2
return dR
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#!/usr/bin/env Python3
import numpy as np
def sla_atms(RT, TT, DNT, GAMAL, R):
'''
Internal routine used by sla_refro(), ported from the SLALIB
FORTRAN code (Copyright P.T.Wallace. All rights reserved.)
The method is also described in "Explanatory Supplement
Astronomical Almanac" by P.K. Seidelmann, 1992, section 3.281.
Refractive index and derivative with respect to height for the
stratosphere.
Parameters
----------
RT : float
Height of tropopause from center of the Earth (meters)
TT : float
Temperature at the tropopause (K)
DNT : float
Refractive index at the tropopause
GAMAL : float
Constant of the atmospheric model = G*MD/R
R : float
Current distance from the centre of the Earth (metre)
Returns
-------
DN : float
Refractive index at R
RDNDR : float
R * rate the refractive index is changing at R
'''
_B = GAMAL / TT
_W = (DNT - 1) * np.exp( -_B * (R - RT) )
DN = 1+_W
RDNDR = -R * _B * _W
return DN, RDNDR
def sla_atmt(R0, T0, ALPHA, GAMM2, DELM2, C1, C2, C3, C4, C5, C6, R):
'''
Internal routine used by sla_refro(), ported from the SLALIB
FORTRAN code (Copyright P.T.Wallace. All rights reserved.)
The method is also described in "Explanatory Supplement
Astronomical Almanac" by P.K. Seidelmann, 1992, section 3.281.
Refractive index and derivative with respect to height for the
troposphere.
Parameters
----------
R0 : float
Height of observer from center of the Earth (meter)
T0 : float
Temperature at the observer (K)
ALPHA : float
Alpha
GAMM2 : float
Gamma minus 2 - see HMNAO paper
DELM2 : float
Delta minus 2
C1 : float
Useful term
C2 : float
Useful term
C3 : float
Useful term
C4 : float
Useful term
C5 : float
Useful term
C6 : float
Useful term
R : float
Current distance from the center of the Earth (meters)
Returns
-------
T : float
Temperature at R (K)
DN : float
Refractive index at R
RDNDR : float
R * rate the refractive index is changing at R
Note that in the optical case C5 and C6 are zero.
'''
T = max(min(T0 - ALPHA * (R - R0), 320), 100)
TT0 = T / T0
TT0GM2 = TT0**GAMM2
TT0DM2 = TT0**DELM2
DN = 1 + ( C1 * TT0GM2 - (C2 - C5 / T) * TT0DM2) * TT0
RDNDR = R * (-C3 * TT0GM2 + (C4 - C6 / TT0) * TT0DM2)
return T, DN, RDNDR
def sla_drange(a):
'''
Helper function for sla_refro().
'''
drange = a % (2*np.pi)
if drange >= np.pi:
drange -= np.abs(2*np.pi)*np.sign(a)
return drange
def sla_refi(dn, rdndr):
'''
Helper function for sla_refro(), that calculates
the refraction integrand.
'''
return rdndr/(dn+rdndr)
def sla_refro(ZOBS, HM, TDK, PMB, RH, WL, PHI, TLR, EPS):
'''
This is a direct port from the original FORTRAN SLA_REFRO()
routine.
Calculates Atmospheric refraction for radio and
optical/IR wavelengths, ported from the original SLALIB
FORTRAN code (Copyright P.T.Wallace. All rights reserved.).
The method is also described in "Explanatory Supplement
Astronomical Almanac" by P.K. Seidelmann, 1992, section 3.281.
Parameters
----------
ZOBS : float
Observed zenith distance of the source (radian)
HM : float
Height of the observer above sea level (meter)
TDK : float
Ambient temperature at the observer (K)
PMB : float
Pressure at the observer (millibar)
RH : float
Relative humidity at the observer (range 0-1)
WL : float
Effective wavelength of the source (micrometre)
PHI : float
Latitude of the observer (radian, astronomical)
TLR : float
Temperature lapse rate in the troposphere (K/metre)
EPS : float
Precision required to terminate iteration (radian)
Returns
-------
REF : float
Refraction: in vacuo ZD minus observed ZD (radian)
Notes
-----
1 A suggested value for the TLR argument is 0.0065D0. The
refraction is significantly affected by TLR, and if studies
of the local atmosphere have been carried out a better TLR
value may be available. The sign of the supplied TLR value
is ignored.
2 A suggested value for the EPS argument is 1D-8. The result is
usually at least two orders of magnitude more computationally
precise than the supplied EPS value.
3 The routine computes the refraction for zenith distances up
to and a little beyond 90 deg using the method of Hohenkerk
and Sinclair (NAO Technical Notes 59 and 63, subsequently adopted
in the Explanatory Supplement, 1992 edition - see section 3.281).
4 The code is a development of the optical/IR refraction subroutine
AREF of C.Hohenkerk (HMNAO, September 1984), with extensions to
support the radio case. Apart from merely cosmetic changes, the
following modifications to the original HMNAO optical/IR refraction
code have been made:
. The angle arguments have been changed to radians.
. Any value of ZOBS is allowed (see note 6, below).
. Other argument values have been limited to safe values.
. Murray's values for the gas constants have been used
(Vectorial Astrometry, Adam Hilger, 1983).
. The numerical integration phase has been rearranged for
extra clarity.
. A better model for Ps(T) has been adopted (taken from
Gill, Atmosphere-Ocean Dynamics, Academic Press, 1982).
. More accurate expressions for Pwo have been adopted
(again from Gill 1982).
. The formula for the water vapour pressure, given the
saturation pressure and the relative humidity, is from
Crane (1976), expression 2.5.5.
. Provision for radio wavelengths has been added using
expressions devised by A.T.Sinclair, RGO (private
communication 1989). The refractivity model currently
used is from J.M.Rueger, "Refractive Index Formulae for
Electronic Distance Measurement with Radio and Millimetre
Waves", in Unisurv Report S-68 (2002), School of Surveying
and Spatial Information Systems, University of New South
Wales, Sydney, Australia.
. The optical refractivity for dry air is from Resolution 3 of
the International Association of Geodesy adopted at the XXIIth
General Assembly in Birmingham, UK, 1999.
. Various small changes have been made to gain speed.
5 The radio refraction is chosen by specifying WL > 100 micrometres.
Because the algorithm takes no account of the ionosphere, the
accuracy deteriorates at low frequencies, below about 30 MHz.
6 Before use, the value of ZOBS is expressed in the range +/- pi.
If this ranged ZOBS is -ve, the result REF is computed from its
absolute value before being made -ve to match. In addition, if
it has an absolute value greater than 93 deg, a fixed REF value
equal to the result for ZOBS = 93 deg is returned, appropriately
signed.
7 As in the original Hohenkerk and Sinclair algorithm, fixed values
of the water vapour polytrope exponent, the height of the
tropopause, and the height at which refraction is negligible are
used.
8 The radio refraction has been tested against work done by
Iain Coulson, JACH, (private communication 1995) for the
James Clerk Maxwell Telescope, Mauna Kea. For typical conditions,
agreement at the 0.1 arcsec level is achieved for moderate ZD,
worsening to perhaps 0.5-1.0 arcsec at ZD 80 deg. At hot and
humid sea-level sites the accuracy will not be as good.
9 It should be noted that the relative humidity RH is formally
defined in terms of "mixing ratio" rather than pressures or
densities as is often stated. It is the mass of water per unit
mass of dry air divided by that for saturated air at the same
temperature and pressure (see Gill 1982).
10 The algorithm is designed for observers in the troposphere. The
supplied temperature, pressure and lapse rate are assumed to be
for a point in the troposphere and are used to define a model
atmosphere with the tropopause at 11km altitude and a constant
temperature above that. However, in practice, the refraction
values returned for stratospheric observers, at altitudes up to
25km, are quite usable.
'''
# Fixed parameters
D93 = np.deg2rad(93)# 93 degrees in radians
GCR = 8314.32 # Universal gas constant
DMD = 28.9644 # Molecular weight of dry air
DMW = 18.0152 # Molecular weight of water vapour
S = 6378120 # Mean Earth radius (metre)
DELTA = 18.36 # Exponent of temperature dependence of water vapour pressure
HT = 11000 # Height of tropopause (metre)
HS = 80000 # Upper limit for refractive effects (metre)
ISMAX = 16384 # Numerical integration: maximum number of strips.
# Transform ZOBS into the normal range.
ZOBS1 = sla_drange(ZOBS)
ZOBS2 = min(abs(ZOBS1),D93)
# Keep other arguments within safe bounds.
HMOK = min(max(HM,-1E3),HS)
TDKOK = min(max(TDK,100),500)
PMBOK = min(max(PMB,0),10000)
RHOK = min(max(RH,0),1)
WLOK = max(WL,0.1)
ALPHA = min(max(abs(TLR),0.001),0.01)
# Tolerance for iteration.
TOL = min(max(abs(EPS),1E-12),0.1)/2
# Decide whether optical/IR or radio case - switch at 100 microns.
OPTIC = (WLOK<=100)
# Set up model atmosphere parameters defined at the observer.
WLSQ = WLOK*WLOK
# Local gravity, can be made consistent with AstroAtmosphere
GB = 9.784*(1-0.0026*np.cos(PHI+PHI)-0.00000028*HMOK)
if OPTIC:
# Refractivity from Barrell & Sears (1939)!
A = (287.6155+(1.62887+0.01360/WLSQ)/WLSQ)*273.15E-6/1013.25
else:
A = 77.6890E-6
GAMAL = (GB*DMD)/GCR
GAMMA = GAMAL/ALPHA
GAMM2 = GAMMA-2
DELM2 = DELTA-2
TDC = TDKOK-273.15
PSAT = 10**((0.7859+0.03477*TDC)/(1+0.00412*TDC))\
*(1+PMBOK*(4.5E-6+6E-10*TDC*TDC))
if PMBOK > 0:
PWO = RHOK*PSAT/(1-(1-RHOK)*PSAT/PMBOK)
else:
PWO = 0
W = PWO*(1-DMW/DMD)*GAMMA/(DELTA-GAMMA)
C1 = A*(PMBOK+W)/TDKOK
if OPTIC:
C2 = (A*W+11.2684E-6*PWO)/TDKOK
else:
C2 = (A*W+6.3938E-6*PWO)/TDKOK
C3 = (GAMMA-1)*ALPHA*C1/TDKOK
C4 = (DELTA-1)*ALPHA*C2/TDKOK
if OPTIC:
C5 = 0
C6 = 0
else:
C5 = 375463E-6*PWO/TDKOK
C6 = C5*DELM2*ALPHA/(TDKOK*TDKOK)
# Conditions at the observer.
R0 = S+HMOK
TEMPO, DN0, RDNDR0 = sla_atmt(R0,TDKOK,ALPHA,GAMM2,DELM2,C1,C2,C3,C4,C5,C6,R0)
SK0 = DN0*R0*np.sin(ZOBS2)
F0 = sla_refi(DN0,RDNDR0)
# Conditions in the troposphere at the tropopause.
RT = S+max(HT,HMOK)
TT, DNT, RDNDRT = sla_atmt(R0,TDKOK,ALPHA,GAMM2,DELM2,C1,C2,C3,C4,C5,C6,RT)
SINE = SK0/(RT*DNT)
ZT = np.arctan2(SINE,np.sqrt(max(1-SINE*SINE,0)))
FT = sla_refi(DNT,RDNDRT)
# Conditions in the stratosphere at the tropopause.
DNTS,RDNDRP = sla_atms(RT,TT,DNT,GAMAL,RT)
SINE = SK0/(RT*DNTS)
ZTS = np.arctan2(SINE,np.sqrt(max(1-SINE*SINE,0)))
FTS = sla_refi(DNTS,RDNDRP)
# Conditions at the stratosphere limit.
RS = S+HS
DNS,RDNDRS = sla_atms(RT,TT,DNT,GAMAL,RS)
SINE = SK0/(RS*DNS)
ZS = np.arctan2(SINE,np.sqrt(max(1-SINE*SINE,0)))
FS = sla_refi(DNS,RDNDRS)
# Variable initialization to avoid compiler warning.
REFT = 0
# Integrate the refraction integral in two parts; first in the
# troposphere (K=1), then in the stratosphere (K=2).
for K in [1,2]:
# Initialize previous refraction to ensure at least two iterations.
REFOLD = 1
# Start off with 8 strips.
IS = 8
# Start Z, Z range, and start and end values.
if K==1:
Z0 = ZOBS2
ZRANGE = ZT-Z0
FB = F0
FF = FT
else:
Z0 = ZTS
ZRANGE = ZS-Z0
FB = FTS
FF = FS
# Sums of odd and even values.
FO = 0
FE = 0
# First time through the loop we have to do every point.
N = 1
# Start of iteration loop (terminates at specified precision).
LOOP = True
while LOOP:
# Strip width.
H = ZRANGE/IS
# Initialize distance from Earth centre for quadrature pass.
if K==1:
R = R0
else:
R = RT
# One pass (no need to compute evens after first time).
# DO I=1,IS-1,N
for I in np.arange(1, IS-1, N):
# Sine of observed zenith distance.
SZ = np.sin(Z0+H*I)
# Find R (to the nearest metre, maximum four iterations).
if (SZ>1E-20):
W = SK0/SZ
RG = R
DR = 1E6
J = 0
while (abs(DR)>1 and J<4):
J+=1
if K==1:
TG,DN,RDNDR = sla_atmt(R0,TDKOK,ALPHA,GAMM2,DELM2,C1,C2,C3,C4,C5,C6,RG)
else:
DN,RDNDR = sla_atms(RT,TT,DNT,GAMAL,RG)
DR = (RG*DN-W)/(DN+RDNDR)
RG = RG-DR
R = RG
# Find the refractive index and integrand at R.
if K==1:
T,DN,RDNDR = sla_atmt(R0,TDKOK,ALPHA,GAMM2,DELM2,C1,C2,C3,C4,C5,C6,R)
else:
DN,RDNDR = sla_atms(RT,TT,DNT,GAMAL,R)
F = sla_refi(DN,RDNDR)
# Accumulate odd and (first time only) even values.
if N==1 and (I%2)==0:
FE = FE+F
else:
FO = FO+F
# Evaluate the integrand using Simpson's Rule.
REFP = H*(FB+4*FO+2*FE+FF)/3
# Has the required precision been achieved (or can't be)?
if (abs(REFP-REFOLD)>TOL and IS<ISMAX):
# No: prepare for next iteration.
# Save current value for convergence test.
REFOLD = REFP
# Double the number of strips.
IS = IS+IS
# Sum of all current values = sum of next pass's even values.
FE = FE+FO
# Prepare for new odd values.
FO = 0
# Skip even values next time.
N = 2
else:
# Yes: save troposphere component and terminate the loop.
if (K==1):
REFT = REFP
LOOP = False
# Result.
REF = REFT+REFP
if (ZOBS1<0):
REF = -REF
return REF
# =============================================================================
# WORK IN PROGRESS; Implementation of the slalib model for
# any refractive index model.
# Main issue is in the calculation of dn/dr for any model
# of the refractive index. One possibility is following
# the Corbard error function model, which assumes the
# atmospheric density follows the equation rho(r)=exp(-u/a).
# But then the SLA_REFRO routine would not have to be modified
# and one would simply use the refraction.corbard() function.
# =============================================================================
#
# def get_rc(lat):
# '''
# Returns the radius of the curvature at the observer in km,
# taking into account the latitude of the observer and the corresponding
# ellipsoidality of the earth.
# Returns
# -------
# rc : float
# Local radius of curvature of the Earth in kilometers.
# '''
# _A = 6378.137 # km
# _B = 6356.752 # km
# _phi = np.deg2rad(lat)
# _rc0 = (_A*_B)**2 / (_A**2 * np.cos(_phi)**2 + _B**2 * np.sin(_phi)**2)**(3/2)
# return _rc0*1000
# def get_local_g(lat, h):
# '''
# Returns the local gravitic acceleration for a given latitude
# and altitude.
# Parameters
# ----------
# lat : float
# Latitude in degrees
# h : float
# Altitude above sea level in meters
# Returns
# -------
# g : float
# Local acceleration due to gravity in m/s^2
# '''
# _phi = np.deg2rad(lat)
# _c1 = 5.2790414e-3
# _c2 = 2.32718e-5
# _c3 = 1.262e-7
# _c4 = 7e-10
# _g0 = 9.780327 # m/s^2
# _g0_local = _g0 * (1 + _c1 * np.sin(_phi)**2 + _c2 * np.sin(_phi)**4 + _c3 * np.sin(_phi)**6 + _c4 * np.sin(_phi)**8)
# _g = _g0_local - (3.0877e-6 - 4.3e-9 * np.sin(_phi)**2) * h + 7.2e-13 * h**2
# return _g
# def aa_refro(zenith, l, h, T, p, RH, xc, lat, TLR, EPS):
# '''
# Modified version of sla_refro(), updating some constants
# and changing the units on input and output parameters.
# The function calculates the atmospheric refraction
# optical/IR wavelengths (not radio!), ported from the original
# SLALIB FORTRAN code (Copyright P.T.Wallace. All rights
# reserved.).
# The method is also described in "Explanatory Supplement
# Astronomical Almanac" by P.K. Seidelmann, 1992, section 3.281.
# See also the description of sla_refro().
# Parameters
# ----------
# zenith : float
# Observed zenith distance of the source (degrees)
# l : float
# Effective wavelength of the source (micrometre)
# h : float
# Height of the observer above sea level (meter)
# T : float
# Ambient temperature at the observer (K)
# p : float
# Pressure at the observer (Pascal)
# RH : float
# Relative humidity at the observer (range 0-1)
# xc : float
# CO2 density in parts per million
# lat : float
# Latitude of the observer (degrees)
# TLR : float
# Temperature lapse rate in the troposphere (K/metre)
# EPS : float
# Precision required to terminate iteration (radian)
# Returns
# -------
# REF : float
# Refraction: in vacuo ZD minus observed ZD (radian)
# '''
# # Converting some units for use later
# ZOBS = np.deg2rad(zenith)
# HM = h
# TDK = T
# PMB = p / 100
# WL = l
# PHI = np.deg2rad(lat)
# # Fixed parameters
# D93 = np.deg2rad(93)# 93 degrees in radians
# GCR = 8314.510 # Universal gas constant
# DMD = 28.9635 + 12.011e-6 * (xc - 400) # Molar mass in g/mol of dry air containing xc ppm of CO2
# DMW = 18.0152 # Molecular weight of water vapour
# S = get_rc(lat) # Mean Earth radius (meters)
# DELTA = 18.36 # Exponent of temperature dependence of water vapour pressure
# HT = 11000 # Height of tropopause (metre)
# HS = 80000 # Upper limit for refractive effects (meters)
# ISMAX = 16384 # Numerical integration: maximum number of strips.
# # Transform ZOBS into the normal range.
# ZOBS1 = sla_drange(ZOBS)
# ZOBS2 = min(abs(ZOBS1),D93)
# # Keep other arguments within safe bounds.
# HMOK = min(max(HM,-1E3),HS)
# TDKOK = min(max(TDK,100),500)
# PMBOK = min(max(PMB,0),10000)
# RHOK = min(max(RH,0),1)
# WLOK = max(WL,0.1)
# ALPHA = min(max(abs(TLR),0.001),0.01)
# # Tolerance for iteration.
# TOL = min(max(abs(EPS),1E-12),0.1)/2
# # Set up model atmosphere parameters defined at the observer.
# WLSQ = WLOK*WLOK
# # Local gravity
# GB = get_local_g(lat, h)
# # Refractivity of air
# A = (287.6155+(1.62887+0.01360/WLSQ)/WLSQ)*273.15E-6/1013.25
# GAMAL = (GB * DMD) / GCR
# GAMMA = GAMAL / ALPHA
# GAMM2 = GAMMA - 2
# DELM2 = DELTA - 2
# TDC = TDKOK - 273.15
# PSAT = 10**( (0.7859+0.03477*TDC) / (1+0.00412*TDC) )\
# * (1 + PMBOK * (4.5E-6 + 6E-10 * TDC*TDC) )
# if PMBOK > 0:
# PWO = RHOK*PSAT/(1-(1-RHOK)*PSAT/PMBOK)
# else:
# PWO = 0
# W = PWO*(1-DMW/DMD)*GAMMA/(DELTA-GAMMA)
# C1 = A*(PMBOK+W)/TDKOK
# C2 = (A*W+11.2684E-6*PWO)/TDKOK
# C3 = (GAMMA-1)*ALPHA*C1/TDKOK
# C4 = (DELTA-1)*ALPHA*C2/TDKOK
# C5 = 0
# C6 = 0
# # Conditions at the observer.
# R0 = S+HMOK
# TEMPO, DN0, RDNDR0 = sla_atmt(R0,TDKOK,ALPHA,GAMM2,DELM2,C1,C2,C3,C4,C5,C6,R0)
# SK0 = DN0*R0*np.sin(ZOBS2)
# F0 = sla_refi(DN0,RDNDR0)
# # Conditions in the troposphere at the tropopause.
# RT = S+max(HT,HMOK)
# TT, DNT, RDNDRT = sla_atmt(R0,TDKOK,ALPHA,GAMM2,DELM2,C1,C2,C3,C4,C5,C6,RT)
# SINE = SK0/(RT*DNT)
# ZT = np.arctan2(SINE,np.sqrt(max(1-SINE*SINE,0)))
# FT = sla_refi(DNT,RDNDRT)
# # Conditions in the stratosphere at the tropopause.
# DNTS,RDNDRP = sla_atms(RT,TT,DNT,GAMAL,RT)
# SINE = SK0/(RT*DNTS)
# ZTS = np.arctan2(SINE,np.sqrt(max(1-SINE*SINE,0)))
# FTS = sla_refi(DNTS,RDNDRP)
# # Conditions at the stratosphere limit.
# RS = S+HS
# DNS,RDNDRS = sla_atms(RT,TT,DNT,GAMAL,RS)
# SINE = SK0/(RS*DNS)
# ZS = np.arctan2(SINE,np.sqrt(max(1-SINE*SINE,0)))
# FS = sla_refi(DNS,RDNDRS)
# # Variable initialization to avoid compiler warning.
# REFT = 0
# # Integrate the refraction integral in two parts; first in the
# # troposphere (K=1), then in the stratosphere (K=2).
# for K in [1,2]:
# # Initialize previous refraction to ensure at least two iterations.
# REFOLD = 1
# # Start off with 8 strips.
# IS = 8
# # Start Z, Z range, and start and end values.
# if K==1:
# Z0 = ZOBS2
# ZRANGE = ZT-Z0
# FB = F0
# FF = FT
# else:
# Z0 = ZTS
# ZRANGE = ZS-Z0
# FB = FTS
# FF = FS
# # Sums of odd and even values.
# FO = 0
# FE = 0
# # First time through the loop we have to do every point.
# N = 1
# # Start of iteration loop (terminates at specified precision).
# LOOP = True
# while LOOP:
# # Strip width.
# H = ZRANGE/IS
# # Initialize distance from Earth centre for quadrature pass.
# if K==1:
# R = R0
# else:
# R = RT
# # One pass (no need to compute evens after first time).
# # DO I=1,IS-1,N
# for I in np.arange(1, IS-1, N):
# # Sine of observed zenith distance.
# SZ = np.sin(Z0+H*I)
# # Find R (to the nearest metre, maximum four iterations).
# if (SZ>1E-20):
# W = SK0/SZ
# RG = R
# DR = 1E6
# J = 0
# while (abs(DR)>1 and J<4):
# J+=1
# if K==1:
# TG,DN,RDNDR = sla_atmt(R0,TDKOK,ALPHA,GAMM2,DELM2,C1,C2,C3,C4,C5,C6,RG)
# else:
# DN,RDNDR = sla_atms(RT,TT,DNT,GAMAL,RG)
# DR = (RG*DN-W)/(DN+RDNDR)
# RG = RG-DR
# R = RG
# # Find the refractive index and integrand at R.
# if K==1:
# T,DN,RDNDR = sla_atmt(R0,TDKOK,ALPHA,GAMM2,DELM2,C1,C2,C3,C4,C5,C6,R)
# else:
# DN,RDNDR = sla_atms(RT,TT,DNT,GAMAL,R)
# F = sla_refi(DN,RDNDR)
# # Accumulate odd and (first time only) even values.
# if N==1 and (I%2)==0:
# FE = FE+F
# else:
# FO = FO+F
# # Evaluate the integrand using Simpson's Rule.
# REFP = H*(FB+4*FO+2*FE+FF)/3
# # Has the required precision been achieved (or can't be)?
# if (abs(REFP-REFOLD)>TOL and IS<ISMAX):
# # No: prepare for next iteration.
# # Save current value for convergence test.
# REFOLD = REFP
# # Double the number of strips.
# IS = IS+IS
# # Sum of all current values = sum of next pass's even values.
# FE = FE+FO
# # Prepare for new odd values.
# FO = 0
# # Skip even values next time.
# N = 2
# else:
# # Yes: save troposphere component and terminate the loop.
# if (K==1):
# REFT = REFP
# LOOP = False
# # Result.
# REF = REFT+REFP
# if (ZOBS1<0):
# REF = -REF
# return REF
+85
View File
@@ -0,0 +1,85 @@
observatories = {
'STANDARD': {
'T': 288.15,
'p': 101325,
'RH': 0.0,
'xc': 450,
'latitude': 0,
'altitude': 0,
'comment': 'Standard atmospheric conditions'
},
'CERRO_ARMAZONES': {
'T': 279.65,
'p': 71200,
'RH': 0.22,
'xc': 450,
'latitude': -24.5983,
'altitude': 3064,
'comment': 'Default conditions for Cerro Armazones, site of the ELT.\nValues are taken from the optical model of MICADO.'
},
'CERRO_PARANAL': {
'T': 285.95,
'p': 74300,
'RH': 0.15,
'xc': 450,
'latitude': -24.6230,
'altitude': 2635,
'comment': 'Average conditions at Cerro Paranal, site of the VLT.\nValues are taken from https://www.eso.org/sci/facilities/paranal/astroclimate/site.html and https://academic.oup.com/mnras/article/399/2/783/1061377'
},
'LA_SILLA': {
'T': 284.65,
'p': 77220,
'RH': 0.44,
'xc': 450,
'latitude': -29.25,
'altitude': 2400,
'comment': 'Average conditions of the La Silla Observatory.\nValues based on https://www.eso.org/gen-fac/pubs/astclim/lasilla/diffrefr.html'
},
'LAS_CAMPANAS': {
'T': 285.85,
'p': 76400,
'RH': 0.0,
'xc': 450,
'latitude': -29.016,
'altitude': 2380,
'comment': 'Mean conditions at Las Campanas observatory, site of the GMT.\nValues based on https://www.gmto.org/Resources/GMT-ID-01466-Chapter_5_Site_Evaluation.pdf and http://weather.lco.cl/'
},
'LA_PALMA': {
'T': 281.95,
'p': 77500,
'RH': 0.36,
'xc': 450,
'latitude': 28.764,
'altitude': 2396,
'comment': 'Average conditions for Roque de los Muchachos Observatory on La Palma, Spain.\nValues taken from https://academic.oup.com/mnras/article/399/2/783/1061377'
},
'MAUNA_KEA': {
'T': 274.45,
'p': 61400,
'RH': 0.48,
'xc': 450,
'latitude': 19.826,
'altitude': 4205,
'comment': 'Average conditions at the Mauna Kea Observatory.\nValues taken from http://www.soest.hawaii.edu/MET/Faculty/businger/mauna_kea/daSilvaThesisFinal.pdf, Ch. 3. and https://www.eso.org/gen-fac/pubs/astclim/espas/espas_reports/ESPAS-MaunaKea.pdf'
}
# 'MT_GRAHAM': {
# 'T': 278.15,
# 'p': 68500,
# 'RH': 0.0,
# 'xc': 450,
# 'latitude': 32.701,
# 'altitude': 3191,
# 'comment': 'Mean conditions at Mount Graham International Observatory,\
# site of the LBT. Values are estimates.'
# },
# 'FRED_LAWRENCE_WHIPPLE': {
# 'T': 288.15,
# 'p': 74300,
# 'RH': 0.0,
# 'xc': 450,
# 'latitude': 31.681,
# 'altitude': 2616,
# 'comment': 'Mean conditions at Fred Lawrence Whipple Observatory, site of\
# the MMT. Values are estimates.'
# }
}
+338 -214
View File
@@ -9,11 +9,11 @@ from .ciddorModel import Observatory
@ Contact: born@astron.nl @ Contact: born@astron.nl
@ Description: This script offers a complete model of the atmospheric refraction @ Description: This script offers a complete model of the atmospheric refraction
and dispersion. It uses the Ciddor1996 paper to calculate the and dispersion. It uses the Ciddor1996 paper to calculate the
index of refraction for a wide range of conditions, with corresponding index of refraction for a wide range of conditions, with corresponding error propagation if needed.
error propagation if needed.
The actual refraction is calculated by any of the following models: The actual refraction is calculated by any of the following models:
- Plane parallel atmosphere - Plane parallel atmosphere
- Cassini spherical homogeneous atmosphere - Cassini spherical homogeneous atmosphere
- Mathar's Barometric exponential model
- Other methods described in Corbard et al., 2019. - Other methods described in Corbard et al., 2019.
''' '''
@@ -38,39 +38,45 @@ class refraction(Observatory):
Methods Methods
------- -------
setReducedHeight(p, rho)
Sets the reduced atmospheric height.
planeParallel(n1, n2, zenith)
Returns the atmospheric refraction assuming a plane parallel
atmosphere
cassini(n1, n2, zenith, reduced_height=None) cassini(n1, n2, zenith, reduced_height=None)
Returns the atmospheric refraction asusming Cassini's homegeneous Returns the atmospheric refraction assuming Cassini's homegeneous
atmosphere model atmosphere model.
tan5(n1, n2, zenith, reduced_height=None)
Returns the atmospheric refraction following Oriani's theorem,
including a fifth order term in the expansion.
oriani(n1, n2, zenith, reduced_height=None)
Returns the atmospheric refraction following the classic version
of Oriani's theorem.
corbard(n1, n2, zenith, reduced_height=None)
Returns the atmospheric refraction following the method described
in Corbard et al., 2019.
refractionIntegral(n1, n2, z0, R0=None, useStandardAtmosphere=True, heightData=None, rhoData=None)
Returns the atmospheric refraction following the refraction integral.
psi(x)
Submethod for corbard()
set_rc()
Sets the local radius of curvature of the Earth at the observer.
set_H(p, rho)
Sets the reduced height for the conditions at the observer, assuming
an adiabatic atmosphere.
H_isotherm(T)
Sets the reduced height for the conditions at the observer, assuming
an isothermal atmosphere.
cassiniError(z, l1, l2, T, p, RH, xc, dl1=0, dl2=0, dT=0.2, dP=20, cassiniError(z, l1, l2, T, p, RH, xc, dl1=0, dl2=0, dT=0.2, dP=20,
dRH=0.02, dCO2=20, dz=0, lat=None, h=None) dRH=0.02, dCO2=20, dz=0, lat=None, h=None)
Returns the uncertainty in the atmospheric refraction, assuming Returns the uncertainty in the atmospheric refraction, assuming
Cassini's homegeneous atmosphere model and the given parameters. Cassini's homegeneous atmosphere model and the given parameters.
corbard(n1, n2, zenith, reduced_height=None)
Returns the atmospheric refraction following the method described
in Corbard et al., 2019.
gammaCoefficients(n1, reduced_height=None)
Helper function for matharExponential(), that calculates the gamma
coefficients.
H_isotherm(T)
Sets the reduced height for the conditions at the observer, assuming
an isothermal atmosphere.
matharExponential(n1, zenith, reduced_height=None)
Returns the atmospheric refraction assuming Mathar's barometric
exponential model.
oriani(n1, n2, zenith, reduced_height=None)
Returns the atmospheric refraction following the classic version
of Oriani's theorem.
planeParallel(n1, n2, zenith)
Returns the atmospheric refraction assuming a plane parallel
atmosphere.
psi(x)
Submethod for corbard().
refractionIntegral(n1, n2, zenith, R0=None, useStandardAtmosphere=True, heightData=None, rhoData=None)
Returns the atmospheric refraction following the refraction integral.
setReducedHeight(p, rho)
Sets the reduced atmospheric height.
set_H(p, rho)
Sets the reduced height for the conditions at the observer, assuming
an adiabatic atmosphere.
set_rc()
Sets the local radius of curvature of the Earth at the observer.
tan5(n1, n2, zenith, reduced_height=None)
Returns the atmospheric refraction following Oriani's theorem,
including a fifth order term in the expansion.
Other Observatory() methods Other Observatory() methods
''' '''
def __init__(self, lat, h): def __init__(self, lat, h):
@@ -80,41 +86,6 @@ class refraction(Observatory):
self.rc = self.set_rc() * 1000 # Radius of curvature of the earth at the observer self.rc = self.set_rc() * 1000 # Radius of curvature of the earth at the observer
# self.H2 = self.H_isotherm(T) # Reduced height of isotherm atmosphere # self.H2 = self.H_isotherm(T) # Reduced height of isotherm atmosphere
def setReducedHeight(self, p, rho):
'''
Sets the reduced atmospheric height.
Parameters
----------
p : float
Atmospheric pressure in Pascal
rho : float
Density of the atmospheric air at the observer
'''
self.H = self.set_H(p, rho) # Reduced height of the atmosphere assuming ideal gas law
def planeParallel(self, n1, zenith):
'''
Refraction based on a flat atmosphere, easily derived from Snell's law.
Parameters
----------
n1 : float
Refractive index at the wavelength of interest
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
Returns
-------
R : float
Atmospheric refraction in degrees
'''
_R = np.arcsin(n * np.sin( np.deg2rad(zenith) )) - np.deg2rad(zenith)
return np.degrees(_R)
def cassini(self, n1, zenith, reduced_height=None): def cassini(self, n1, zenith, reduced_height=None):
''' '''
@@ -145,72 +116,46 @@ class refraction(Observatory):
return np.degrees(_R1) return np.degrees(_R1)
def cassiniError(self, n, dn, zenith, dz=0, reduced_height=None):
def tan5(self, n1, zenith, reduced_height=None):
''' '''
Same as oriani's theorem, but including a higher order term. Calculates the uncertainty in the refraction angle in degrees.
Found in Corbard et al., 2019. See Observatory().n_tph() and Observatory().dn_tph() on how to
calculate the refractive index and it's uncertainty.
Parameters Parameters
---------- ----------
n1 : float n : float
Refractive index at the wavelength of interest Refractive index of air
zenith : float dn : float
Angle of observation in degrees. Uncertainty in the refractive index of air
zenith = 0 means the observation is directly overhead. zenith : float
reduced_height : float (optional) Angle of observation in degrees.
Reduced height of the atmosphere. Default value is calculated zenith = 0 means the observation is directly overhead.
from the object attributes. dz : float (optional)
Uncertainty in the zenith angle, in degrees.
reduced_height : float (optional)
Reduced height of the atmosphere. Default value is calculated
from the object attributes.
Returns Returns
------- -------
R : float dR : float
Atmospheric refraction in degrees Uncertainty in the atmospheric refraction in degrees.
''' '''
if reduced_height: if reduced_height:
H = reduced_height _H = reduced_height
else: else:
H = self.H _H = self.H
_zenith = np.deg2rad(zenith)
_dz = np.deg2rad(dz)
_R = self.rc
_dRdn = (_R * np.sin(_zenith)) / ((_R + _H) * np.sqrt(1 - ((n**2 * _R**2 * np.sin(_zenith)**2)/(_R + _H)**2)))
_a = n1 - 1 _dRdz = (_R * np.cos(_zenith)) / (_R + _H) * ( n / np.sqrt(1-(n**2 * _R**2 * np.sin(_zenith)**2)/(_R + _H)**2) - 1 / np.sqrt(1-(_R**2 * np.sin(_zenith)**2)/(_R + _H)**2) )
_b = H / self.rc
_R = _a * (1 - _b) * np.tan( np.deg2rad(zenith) ) - _a * (_b - _a/2) * np.tan( np.deg2rad(zenith) )**3 + 3 * _a * (_b - _a/2)**2 * np.tan( np.deg2rad(zenith) )**5
return np.degrees(_R)
_dR = np.sqrt( (_dRdn * dn)**2 + (_dRdz * _dz)**2)
return np.degrees(_dR)
def oriani(self, n1, zenith, reduced_height=None):
'''
Classic refraction formula with two tan(z) terms. This does not
assume any information about the structure of the atmosphere.
Found with Oriani's theorem.
Parameters
----------
n1 : float
Refractive index at the wavelength of interest
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
reduced_height : float (optional)
Reduced height of the atmosphere. Default value is calculated
from the object attributes.
Returns
-------
R : float
Atmospheric refraction in degrees
'''
if reduced_height:
H = reduced_height
else:
H = self.H
_a = n1 - 1
_b = H / self.rc
_R = _a * (1 - _b) * np.tan( np.deg2rad(zenith) ) - _a * (_b - _a/2) * np.tan( np.deg2rad(zenith) )**3
return np.degrees(_R)
def corbard(self, n1, zenith, reduced_height=None): def corbard(self, n1, zenith, reduced_height=None):
@@ -246,8 +191,231 @@ class refraction(Observatory):
return np.degrees(_R) return np.degrees(_R)
def gammaCoefficients(self, n1, reduced_height=None):
'''
Submethod for matharExponential(). Calculates the gamma
coefficients.
def refractionIntegral(self, n1, z0, R0=None, useStandardAtmosphere=True, heightData=None, rhoData=None): Parameters
----------
n1 : float
Refractive index at the wavelength of interest at the observer
reduced_height : float (optional)
Reduced height of the atmosphere. Default value is calculated
from the object attributes.
Returns
-------
g : array
List of values, corresponding to the gamma coefficients.
g[0] corresponds to g_1, g[1] to g_3, g[2] to g_5, and so on.
'''
if reduced_height:
H = reduced_height
else:
H = self.H
_chi0 = n1**2 - 1
_Khat = H / self.rc
_g1 = (1 - 5/24 * _Khat * _chi0**2 - 3/4 * _chi0 - 3/8 * _Khat**2 * _chi0 \
- _Khat - 6 * _Khat**3 + 5/8 * _chi0**2 + 63/128 * _chi0**4 + 3/8 \
* _Khat * _chi0 + 35/256 * _Khat * _chi0**3 + 2 * _Khat**2 + 5/36 \
* _Khat**2 * _chi0**2 - 35/64 * _chi0**3 + 9/16 * _Khat**3 * _chi0 \
- 120 * _Khat**5 + 24 * _Khat**4 - 231 / 512 * _chi0**5 - 63 / 640 \
* _Khat * _chi0**4 - 35 / 512 * _Khat**2 * _chi0**3 - 5 / 36 * _Khat**3\
* _chi0**2 - 9 / 8 * _Khat**4 * _chi0 )
_g3 = (35/96 * _chi0**3 - 5/12 * _chi0**2 + 333 * _Khat**4 * _chi0 - 2400 \
* _Khat**5 + 3605/4608 * _Khat**2 * _chi0**3 + 63/256 * _Khat * _chi0**4\
- 819/16 * _Khat**3 * _chi0 - 35/18 * _Khat**2 * _chi0**2 - 35/96 \
* _Khat * _chi0**3 + 69/8 * _Khat**2 * _chi0 + 5/8 * _Khat * _chi0**2 \
- 3/2 * _Khat * _chi0 + 1355/216 * _Khat**3 * _chi0**2 + 10 * _Khat**2 \
+ 336 * _Khat**4 - 2 * _Khat + _chi0/2 - 21/64 * _chi0**4 - 54 * _Khat**3 \
+ 77/256 * _chi0**5 ) * 1/2
_g5 = (-96 * _Khat**3 + 8 * _Khat**2 - 7/24 * _chi0**3 + 65/4 * _Khat**2 \
* _chi0**2 + 35/48 * _Khat * _chi0**3 + 30 * _Khat**2 * _chi0 - 5/3 \
* _Khat * _chi0**2 - 3 * _Khat * _chi0 + 20091/8 * _Khat**4 * _chi0 \
- 32605/216 * _Khat**3 * _chi0**2 - 35/9 * _Khat**2 * _chi0**3 + 984 \
* _Khat**4 + _chi0**2/3 - 10200 * _Khat**5 - 77/320 * _chi0**5 + 21/80 \
* _chi0**4 - 1089/4 * _Khat**3 * _chi0 - 7/16 * _Khat * _chi0**4 ) * 3/8
_g7 = (-17520 * _Khat**5 - 9/40 * _chi0**4 - 8755/12 * _Khat**3 * _chi0**2 \
+ 1056 * _Khat**4 + _chi0**3/4 + 23517/4 * _Khat**4 * _chi0 - 11/3 \
* _Khat * _chi0**2 + 21 * _Khat**2 * _chi0 - 7/4 * _Khat * _chi0**3 \
+ 505/9 * _Khat**2 * _chi0**2 - 801/2 * _Khat**3 * _chi0 + 33/160 \
* _chi0**5 - 48 * _Khat**3 + 63/80 * _Khat * _chi0**4 + 2345/96 \
* _Khat**2 * _chi0**3) * 5/16
_g9 = (_chi0**4 / 5 + 384 * _Khat**4 - 13440 * _Khat**5 + 5562 * _Khat**4 \
* _chi0 + 3125/36 * _Khat**2 * _chi0**3 - 11/60 * _chi0**5 - 25/6 \
* _Khat * _chi0**3 - 26950/27 * _Khat**3 * _chi0**2 + 340/9 * _Khat**2 \
* _chi0**2 - 180 * _Khat**3 * _chi0 - 9/5 * _Khat * _chi0**4) * 35/128
g = np.array([_g1, _g3, _g5, _g7, _g9])
g*= n1*_chi0/2
return g
def H_isotherm(self, T):
'''
Calculates the reduced height of the atmosphere,
assuming an isotherm distribution.
Parameters
----------
T : float
Atmospheric temperature in Kelvin
Returns
-------
H : float
Reduced height of the atmosphere in meters
'''
_kb = 1.38064852e-23 # kg m2 s-2 K-1
_m = 4.809651698e-26 # kg (weight per molecule of air, assuming dry air)
_phi = np.deg2rad(self.lat)
_c1 = 5.2790414e-3
_c2 = 2.32718e-5
_c3 = 1.262e-7
_c4 = 7e-10
_g0 = 9.780327 # m/s^2
_g0_local = _g0 * (1 + _c1 * np.sin(_phi)**2 + _c2 * np.sin(_phi)**4 + _c3 * np.sin(_phi)**6 + _c4 * np.sin(_phi)**8)
return (_kb*T) / (_m * _g0_local)
def matharExponential(self, n1, zenith, reduced_height=None):
'''
Model on atmospheric refraction described by Richard Mathar in
"A Barometric Exponential Model of the Atmosphere’s Refractive Index: ZenithAngles and Second Order Aberration in the Entrance Pupil" (2020)
ArXiv id: 2004.11808 (https://arxiv.org/abs/2004.11808)
The code in this function is adapted from eqs 3, 16, 17 and 18 in this
work. It is an adaptation of the RefrExpo.cxx C++ file written by Mathar.
This model assumes the refractive index, n, is related to the susceptibility,
chi, following: n(r) = sqrt(1+chi(r)) (eq. 9).
R. Mathar then assumes that the susceptibility is proportional to the
air density and reduced height, following eq. 10:
chi(r) = chi0 * exp(-(r-rho)/K).
The refraction is described using a Taylor expansion; R in terms of
the odd powers of the tangent of the observed zenith angle (eq. 3), not
unlike Oriani's theorem. This requires coefficients g_i.
Parameters
----------
n1 : float
Refractive index at the wavelength of interest at the observer
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
reduced_height : float (optional)
Reduced height of the atmosphere. Default value is calculated
from the object attributes.
Returns
-------
R : float
Atmospheric refraction in degrees
'''
if reduced_height:
_H = reduced_height
else:
_H = self.H
_zenith = np.deg2rad(zenith)
_rc = self.rc # rho
# Atmospheric refraction in radians
_gamma = self.gammaCoefficients(n1, reduced_height=_H)
_R = sum([_gamma[i]*np.tan(_zenith)**(2*i+1) for i in range(len(_gamma))])
return np.degrees(_R)
def oriani(self, n1, zenith, reduced_height=None):
'''
Classic refraction formula with two tan(z) terms. This does not
assume any information about the structure of the atmosphere.
Found with Oriani's theorem.
Parameters
----------
n1 : float
Refractive index at the wavelength of interest
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
reduced_height : float (optional)
Reduced height of the atmosphere. Default value is calculated
from the object attributes.
Returns
-------
R : float
Atmospheric refraction in degrees
'''
if reduced_height:
H = reduced_height
else:
H = self.H
_a = n1 - 1
_b = H / self.rc
_R = _a * (1 - _b) * np.tan( np.deg2rad(zenith) ) - _a * (_b - _a/2) * np.tan( np.deg2rad(zenith) )**3
return np.degrees(_R)
def planeParallel(self, n1, zenith):
'''
Refraction based on a flat atmosphere, easily derived from Snell's law.
Parameters
----------
n1 : float
Refractive index at the wavelength of interest
zenith : float
Angle of observation in degrees.
zenith = 0 means the observation is directly overhead.
Returns
-------
R : float
Atmospheric refraction in degrees
'''
_R = np.arcsin(n1 * np.sin( np.deg2rad(zenith) )) - np.deg2rad(zenith)
return np.degrees(_R)
def psi(self, x):
'''
Submethod for corbard(). Described explicitly in Corbard et al.,2019.
Parameters
----------
x : float
Input of the function
Returns
-------
y : float
Output of the function
'''
_f = lambda a: np.exp(-a**2)
_int = integrate.quad(_f, x, np.inf)
return np.exp(x**2) * _int[0]
def refractionIntegral(self, n1, zenith, R0=None, useStandardAtmosphere=True,
heightData=None, rhoData=None):
''' '''
Using data that gives temperature, pressure and density as a Using data that gives temperature, pressure and density as a
function of height, the gladstone-dale relation is invoked to function of height, the gladstone-dale relation is invoked to
@@ -262,8 +430,8 @@ class refraction(Observatory):
Parameters Parameters
---------- ----------
n1 : float n1 : float
Refractive index at the wavelength of interest Refractive index at the wavelength of interest at the observer
z0 : float zenith : float
Angle of observation in degrees. Angle of observation in degrees.
zenith = 0 means the observation is directly overhead. zenith = 0 means the observation is directly overhead.
R0 : float (optional) R0 : float (optional)
@@ -295,16 +463,16 @@ class refraction(Observatory):
_Dens = rhoData _Dens = rhoData
_h = heightData _h = heightData
z0 = np.deg2rad(z0) zenith = np.deg2rad(zenith)
_Dens = np.asarray(_Dens) _Dens = np.asarray(_Dens)
_h = np.asarray(_h) _h = np.asarray(_h)
_R = R0 + _h * 1000 _R = R0 + _h * 1000
# Gladstone-Dale relation between refractive index and density # Gladstone-Dale relation between refractive index and density
_n_h = 1 + (n0 - 1) / _Dens[0] * _Dens _n_h = 1 + (n1 - 1) / _Dens[0] * _Dens
# Calculation of the zenith angle for given height and refractive index, from the refractive invariant # Calculation of the zenith angle for given height and refractive index, from the refractive invariant
_z = np.arcsin( (n0 * R0) / (_n_h * _R) * np.sin(z0) ) _z = np.arcsin( (n1 * R0) / (_n_h * _R) * np.sin(zenith) )
# Calculation of log space derivative of n and r # Calculation of log space derivative of n and r
_lnn = np.log(_n_h) _lnn = np.log(_n_h)
@@ -320,45 +488,18 @@ class refraction(Observatory):
return np.degrees(np.sum(_Integrand)) return np.degrees(np.sum(_Integrand))
def setReducedHeight(self, p, rho):
def psi(self, x):
''' '''
Submethod for corbard(). Described explicitly in Corbard et al.,2019. Sets the reduced atmospheric height.
Parameters Parameters
---------- ----------
x : float p : float
Input of the function Atmospheric pressure in Pascal
rho : float
Returns Density of the atmospheric air at the observer
-------
y : float
Output of the function
''' '''
_f = lambda a: np.exp(-a**2) self.H = self.set_H(p, rho) # Reduced height of the atmosphere assuming ideal gas law
_int = integrate.quad(_f, x, np.inf)
return np.exp(x**2) * _int[0]
def set_rc(self):
'''
Returns the radius of the curvature at the observer in km,
taking into account the latitude of the observer and the corresponding
ellipsoidality of the earth.
Returns
-------
rc : float
Local radius of curvature of the Earth in kilometers.
'''
_A = 6378.137 # km
_B = 6356.752 # km
_phi = np.deg2rad(self.lat)
_rc0 = (_A*_B)**2 / (_A**2 * np.cos(_phi)**2 + _B**2 * np.sin(_phi)**2)**(3/2)
return _rc0 + self.h/1000
def set_H(self, p, rho): def set_H(self, p, rho):
@@ -387,71 +528,54 @@ class refraction(Observatory):
_g = _g0_local - (3.0877e-6 - 4.3e-9 * np.sin(_phi)**2) * self.h + 7.2e-13 * self.h**2 _g = _g0_local - (3.0877e-6 - 4.3e-9 * np.sin(_phi)**2) * self.h + 7.2e-13 * self.h**2
return p / (rho * _g) return p / (rho * _g)
def H_isotherm(self, T):
'''
Calculates the reduced height of the atmosphere,
assuming an isotherm distribution.
Parameters def set_rc(self):
---------- '''
T : float Returns the radius of the curvature at the observer in km,
Atmospheric temperature in Kelvin taking into account the latitude of the observer and the corresponding
ellipsoidality of the earth.
Returns Returns
------- -------
H : float rc : float
Reduced height of the atmosphere in meters Local radius of curvature of the Earth in kilometers.
''' '''
_kb = 1.38064852e-23 # kg m2 s-2 K-1 _A = 6378.137 # km
_m = 4.809651698e-26 # kg (weight per molecule of air, assuming dry air) _B = 6356.752 # km
_phi = np.deg2rad(self.lat) _phi = np.deg2rad(self.lat)
_c1 = 5.2790414e-3
_c2 = 2.32718e-5
_c3 = 1.262e-7
_c4 = 7e-10
_g0 = 9.780327 # m/s^2
_g0_local = _g0 * (1 + _c1 * np.sin(_phi)**2 + _c2 * np.sin(_phi)**4 + _c3 * np.sin(_phi)**6 + _c4 * np.sin(_phi)**8)
return (_kb*T) / (_m * _g0_local) _rc0 = (_A*_B)**2 / (_A**2 * np.cos(_phi)**2 + _B**2 * np.sin(_phi)**2)**(3/2)
return _rc0 + self.h/1000
def cassiniError(self, n, dn, zenith, dz=0, reduced_height=None):
def tan5(self, n1, zenith, reduced_height=None):
''' '''
Calculates the uncertainty in the refraction angle in degrees. Same as oriani's theorem, but including a higher order term.
See Observatory().n_tph() and Observatory().dn_tph() on how to Found in Corbard et al., 2019.
calculate the refractive index and it's uncertainty.
Parameters Parameters
---------- ----------
n : float n1 : float
Refractive index of air Refractive index at the wavelength of interest
dn : float zenith : float
Uncertainty in the refractive index of air Angle of observation in degrees.
zenith : float zenith = 0 means the observation is directly overhead.
Angle of observation in degrees. reduced_height : float (optional)
zenith = 0 means the observation is directly overhead. Reduced height of the atmosphere. Default value is calculated
dz : float (optional) from the object attributes.
Uncertainty in the zenith angle, in degrees.
reduced_height : float (optional)
Reduced height of the atmosphere. Default value is calculated
from the object attributes.
Returns Returns
------- -------
dR : float R : float
Uncertainty in the atmospheric refraction in degrees. Atmospheric refraction in degrees
''' '''
if reduced_height: if reduced_height:
_H = reduced_height H = reduced_height
else: else:
_H = self.H H = self.H
_zenith = np.deg2rad(zenith)
_dz = np.deg2rad(dz)
_R = self.rc
_dRdn = (_R * np.sin(_zenith)) / ((_R + _H) * np.sqrt(1 - ((n**2 * _R**2 * np.sin(_zenith)**2)/(_R + _H)**2)))
_dRdz = (_R * np.cos(_zenith)) / (_R + _H) * ( n / np.sqrt(1-(n**2 * _R**2 * np.sin(_zenith)**2)/(_R + _H)**2) - 1 / np.sqrt(1-(_R**2 * np.sin(_zenith)**2)/(_R + _H)**2) ) _a = n1 - 1
_b = H / self.rc
_R = _a * (1 - _b) * np.tan( np.deg2rad(zenith) ) - _a * (_b - _a/2) * np.tan( np.deg2rad(zenith) )**3 + 3 * _a * (_b - _a/2)**2 * np.tan( np.deg2rad(zenith) )**5
return np.degrees(_R)
_dR = np.sqrt( (_dRdn * dn)**2 + (_dRdz * _dz)**2)
return np.degrees(_dR)
+215 -28
View File
@@ -9,7 +9,7 @@ import numpy as np
atmospheric dispersion, given a set of conditions. atmospheric dispersion, given a set of conditions.
''' '''
def BarrellAndSears(l, T=288.15, p=101325, H=0): def BarrellAndSears(l, T=288.15, p=101325, RH=0, f=None):
''' '''
From Barrell & Sears, 1939 From Barrell & Sears, 1939
Equation 7.7, page 52 Equation 7.7, page 52
@@ -24,20 +24,26 @@ def BarrellAndSears(l, T=288.15, p=101325, H=0):
Temperature in Kelvin Temperature in Kelvin
p : float p : float
Atmospheric pressure in Pascal Atmospheric pressure in Pascal
H : float RH : float
Relative humidity (0=<H=<1) Relative humidity (0=<H=<1)
f : float
Water vapour pressure in Pascal
Returns Returns
------- -------
n : float n : float
Refractive index of atmospheric air at the given conditions Refractive index of atmospheric air at the given conditions
''' '''
if f is None:
f = RH * svp(T)
f_mmHg = hPa2mmHg(f/100)
T = K2C(T) T = K2C(T)
P = hPA2mmHg(p/100) P = hPa2mmHg(p/100)
R = (0.378125 + 0.0021414 / l**2 + 0.00001793 / l**4) * (P*(1 + (1.049 - 0.0157*T) * P * 1e-6)/(1 + 0.003661*T)) - (0.0624 - 0.000680 / l**2) * H / (1 + 0.003661*T) R = (0.378125 + 0.0021414 / l**2 + 0.00001793 / l**4) * (P*(1 + (1.049 - 0.0157*T) * P * 1e-6)/(1 + 0.003661*T)) - (0.0624 - 0.000680 / l**2) * f_mmHg / (1 + 0.003661*T)
n = R/1e6 + 1 n = R/1e6 + 1
return n return n
def Ciddor(l, CO2=450): def Ciddor(l, CO2=450):
''' '''
From Ciddor, 1996 From Ciddor, 1996
@@ -49,6 +55,8 @@ def Ciddor(l, CO2=450):
---------- ----------
l : float l : float
Wavelength in microns Wavelength in microns
CO2 : float
CO2 density in parts per million
Returns Returns
------- -------
@@ -62,17 +70,28 @@ def Ciddor(l, CO2=450):
n = R/1e8 + 1 n = R/1e8 + 1
return n return n
def Edlen1953(l):
def Edlen1953(l, T=288.15, p=101325, RH=0, f=None):
''' '''
From Edlen, 1953 From Edlen, 1953
Equation 2 Equation 2
At standard conditions only At standard conditions only.
Following Filippenko (1982), eqs. 2 & 3 we also include
the modification proposed by Barrell in 1951.
Parameters Parameters
---------- ----------
l : float l : float
Wavelength in microns Wavelength in microns
T : float
Temperature in Kelvin
p : float
Atmospheric pressure in Pascal
RH : float
Relative humidity (0=<H=<1)
f : float
Water vapor pressure in Pascal
Returns Returns
------- -------
@@ -81,13 +100,27 @@ def Edlen1953(l):
''' '''
s = 1 / l s = 1 / l
R = 6432.8 + 2949810 / (146 - s**2) + 25540/(41-s**2) R = 6432.8 + 2949810 / (146 - s**2) + 25540/(41-s**2)
n = R/1e8 + 1 n_standard = R/1e8 + 1
pHg = hPa2mmHg(p/100)
Tc = K2C(T)
if f is None:
f = RH * svp(T)
f_mmHg = hPa2mmHg(f/100)
# Changes in temperature and pressure, from Barrell (1951)
n_tp = R/1e8 * (pHg * (1 + (1.049 - 0.0157*Tc) * 1e-6 * pHg ) ) / ( 720.883 * (1 + 0.003661 * Tc)) + 1
# Correction for water vapour pressure
n_svp = (n_tp - 1) * 1e6 - ( 0.0624 - 0.000680 * s**2 ) / (1 + 0.003661 * Tc) * f_mmHg
n = n_svp/1e6 + 1
return n return n
def Edlen1966(l):
def Edlen1966(l, T=288.15, p=101325, RH=0, CO2=300, f=None):
''' '''
From Edlen, 1966 From Edlen, 1966
Equation 1 Equations 1, 12, 17, 22
At standard conditions only At standard conditions only
@@ -95,6 +128,16 @@ def Edlen1966(l):
---------- ----------
l : float l : float
Wavelength in microns Wavelength in microns
T : float
Temperature in Kelvin
p : float
Atmospheric pressure in Pascal
RH : float
Relative humidity (0=<H=<1)
CO2 : float
CO2 density in parts per million
f : float
Water vapor pressure in Pascal
Returns Returns
------- -------
@@ -104,9 +147,31 @@ def Edlen1966(l):
s = 1 / l s = 1 / l
R = 8342.13 + 2406030 / (130 - s**2) + 15997 / (38.9 - s**2) R = 8342.13 + 2406030 / (130 - s**2) + 15997 / (38.9 - s**2)
n = R/1e8 + 1 n = R/1e8 + 1
# Influence of temperature and pressure, eq. 12
Tc = K2C(T)
Ptorr = Pa2Torr(p)
R_tp = ( Ptorr * R/1e8 ) / 720.775 * (1 + Ptorr * (0.817 - 0.0133 * Tc) * 1e-6) / ( 1 + 0.0036610 * Tc)
# Allow for a CO2 fraction, eq. 17, but we include T and P dependence.
# This is okay from "Asthe refractivity of CO, is about 50% higher than
# that of air this CO,-content increases the refractivity over that of
# CO2-free air by approximately 0.5 x 0.0003 x (n-1)s" and "As the
# density factor of CO, is not much different from that of air this ratio r
# can be taken as independent of t and p ."
R_x = R_tp * (1 + 0.540 * (CO2/1e6 - 0.0003))
n_x = R_x + 1
# Correction for water vapour, eq. 22
if f is None:
f = RH * svp(T)
ftorr = Pa2Torr(f)
n = n_x - ftorr * (5.7224 - 0.0457 * s**2) * 1e-8
return n return n
def Owens(l, T=288.15, p=101325, H=0):
def Owens(l, T=288.15, p=101325, RH=0):
''' '''
From Owens, 1967 From Owens, 1967
Equation 32 Equation 32
@@ -121,25 +186,26 @@ def Owens(l, T=288.15, p=101325, H=0):
Temperature in Kelvin Temperature in Kelvin
p : float p : float
Atmospheric pressure in Pa Atmospheric pressure in Pa
H : float RH : float
Humdity (0<=H<=1) Relative humdity (0<=H<=1)
Returns Returns
------- -------
n : float n : float
Refractive index of atmospheric air at the given conditions Refractive index of atmospheric air at the given conditions
''' '''
P = hPA2mmHg(p/100) P = hPa2mmHg(p/100)
T = K2C(T) T = K2C(T)
s = 1 / l s = 1 / l
R = 8342.13 + 2406030 / (130 - s**2) + 15997 / (38.9 - s**2) * (P/720.775) * ((1 + P * (0.817 - 0.0133) * 1e-6)/(1 + 0.0036610*T)) - H * (5.722 - 0.0457*s**2) R = 8342.13 + 2406030 / (130 - s**2) + 15997 / (38.9 - s**2) * (P/720.775) * ((1 + P * (0.817 - 0.0133) * 1e-6)/(1 + 0.0036610*T)) - RH * (5.722 - 0.0457*s**2)
n = R/1e8 + 1 n = R/1e8 + 1
return n return n
def BonschPotulski(l, T=288.15, p=101325, CO2=450):
def BonschPotulski(l, T=288.15, p=101325, RH=0, CO2=400, f=None):
''' '''
From Bonsch & Potulski, 1998 From Bonsch & Potulski, 1998
Equations 6, 7, 8 Equations 6, 7, 8 and 9a
Parameters Parameters
---------- ----------
@@ -149,8 +215,12 @@ def BonschPotulski(l, T=288.15, p=101325, CO2=450):
Temperature in Kelvin Temperature in Kelvin
p : float p : float
Atmospheric pressure in Pa Atmospheric pressure in Pa
RH : float
Relative humidity (0<=H<=1)
CO2 : float CO2 : float
Particles per million of CO2 Particles per million of CO2
f : float
Water vapor pressure in Pascal
Returns Returns
------- -------
@@ -158,16 +228,22 @@ def BonschPotulski(l, T=288.15, p=101325, CO2=450):
Refractive index of atmospheric air at the given conditions Refractive index of atmospheric air at the given conditions
''' '''
x = CO2 / 1e6 x = CO2 / 1e6
T = K2C(T) Tc = K2C(T)
s = 1 / l s = 1 / l
# Rs = 8092.33 + 2333983 / (130 - s**2) + 15518 / (38.9 - s**2)
Rs = 8091.37 + 2333983 / (130 - s**2) + 15518 / (38.9 - s**2) Rs = 8091.37 + 2333983 / (130 - s**2) + 15518 / (38.9 - s**2)
Rs = Rs / 1e8 Rs = Rs / 1e8
Rx = Rs * (1 + 0.5327 * (x - 0.0004)) Rx = Rs * (1 + 0.5327 * (x - 0.0004))
Rtp = Rx * p / 93214.60 * (1 + 1e-8 * (0.5953 - 0.009876 * T)*p) / (1 + 0.0036610 * T) Rtp = Rx * p / 93214.60 * (1 + 1e-8 * (0.5953 - 0.009876 * Tc)*p) / (1 + 0.0036610 * Tc)
n = Rtp + 1
if f is None:
f = RH * svp(T)
n_tp = Rtp + 1
n = n_tp - f * (3.8020 - 0.0384 * s**2) * 1e-10
return n return n
def BirchDowns(l): def BirchDowns(l):
''' '''
From Birch & Downs, 1993 and 1994 (correction) From Birch & Downs, 1993 and 1994 (correction)
@@ -190,6 +266,7 @@ def BirchDowns(l):
n = R/1e8 + 1 n = R/1e8 + 1
return n return n
def PeckReeder(l): def PeckReeder(l):
''' '''
From Peck & Reeder, 1972 From Peck & Reeder, 1972
@@ -213,8 +290,70 @@ def PeckReeder(l):
return n return n
def slalib(l, T=288.15, p=101325, H=0, h=0, lat=-24, tlr=0.0065, eps=1e-10): def HohenkerkAndSinclair(l, T=288.15, p=101325, RH=0, h=0, lat=0):
''' '''
Calcalation of the refractive index following Hohenkerk & Sinclair
(1985), which is the same one as used in SLALIB.
This equation is based on the Barrell & Sears equation, but with
slightly different values. The refractive index values here seem
to be a bit higher than the original Barrel and Sears values.
Parameters
----------
l : float
Wavelength in microns
T : float
Temperature in Kelvin
p : float
Atmospheric pressure in Pa
RH : float
fractional humidity (0=<H=<1)
h : float
Altitude of the observer (default=0 m)
lat : float
Latitude of the observer (default=-24)
Returns
-------
n : float
Refractive index of atmospheric air at the given conditions
'''
# Some constants
alpha = 0.0065
delta = 18.36
R = 8314.36
Md = 28.966
Mw = 18.016
# Pressure in millibars
P0 = p/100
# Local acceleration due to gravity
g_local = 9.784 * (1 - 0.0026 * np.cos(2*np.deg2rad(lat))) - 0.00000028*h
gamma = g_local * Md / (R * alpha)
# Partial pressure of water vapour at observer
Pw = RH * (T/247.1)**18.36
# Refractivity * 1e6 at reference conditions
A = (287.604 + 1.6288*l**-2 + 0.0136*l**-4) * 273.15/1013.25
# A = (287.5522 + 1.6288*l**-2 + 0.0136*l**-4) * 273.15/1013.25
P = (P0 + (1 - Mw/Md) * gamma/(delta - gamma) * Pw )\
- (1 - Mw/Md) * gamma / (delta-gamma) * Pw
# Refractive index at given conditions
n = 1 + 1e-6 * (A * P - 11.2684*Pw)/T
return n
def slalib(l, T=288.15, p=101325, RH=0, h=0, lat=-24, tlr=0.0065, eps=1e-10):
'''
NOTE: This function still works for now, but is considered DEPRECATED.
Use BarrellAndSears() or HohenkerkAndSinclair() instead.
SLALIB uses the same atmospheric model as ZEMAX SLALIB uses the same atmospheric model as ZEMAX
based on the works of Hohenkerk & Sinclair and Seidelmann. based on the works of Hohenkerk & Sinclair and Seidelmann.
They take the B&S refraction formula as a basis. They take the B&S refraction formula as a basis.
@@ -228,8 +367,8 @@ def slalib(l, T=288.15, p=101325, H=0, h=0, lat=-24, tlr=0.0065, eps=1e-10):
Temperature in Kelvin Temperature in Kelvin
p : float p : float
Atmospheric pressure in Pa Atmospheric pressure in Pa
H : float RH : float
fractional humidity (0=<H=<1) Relative humidity (0=<H=<1)
h : float h : float
Altitude of the observer (default=0 m) Altitude of the observer (default=0 m)
lat : float lat : float
@@ -243,6 +382,14 @@ def slalib(l, T=288.15, p=101325, H=0, h=0, lat=-24, tlr=0.0065, eps=1e-10):
------- -------
n : float n : float
Refractive index of atmospheric air at the given conditions Refractive index of atmospheric air at the given conditions
Notes
-----
1. I don't understand why this function works. It calculates the
refraction and somehow returns the refractive index. Perhaps
this is a very particular set of input parameters that make it
work. It does closely follow BarrellAndSears() for standard
conditions.
''' '''
try: try:
from pyslalib import slalib from pyslalib import slalib
@@ -256,14 +403,14 @@ def slalib(l, T=288.15, p=101325, H=0, h=0, lat=-24, tlr=0.0065, eps=1e-10):
if type(l) == float: if type(l) == float:
l = [l] l = [l]
for wl in l: for wl in l:
R.append(slalib.sla_refro(zObs, h, T, p, H, wl, lat, tlr, eps)) R.append(slalib.sla_refro(zObs, h, T, p, RH, wl, lat, tlr, eps))
if len(l) == 1: if len(l) == 1:
return R[0]+1 return R[0]+1
else: else:
return np.asarray(R)+1 return np.asarray(R)+1
def Mathar(l, T=288.15, p=101325, H=0): def Mathar(l, T=288.15, p=101325, RH=0):
''' '''
Refractivity model by Mathar (2007), valid above 1.4 microns Refractivity model by Mathar (2007), valid above 1.4 microns
Code taken from Code taken from
@@ -387,12 +534,12 @@ def Mathar(l, T=288.15, p=101325, H=0):
σref = 1e4/20 # cm^−1, reference wavenumber σref = 1e4/20 # cm^−1, reference wavenumber
Tref = 273.15+17.5 # K, reference temperature Tref = 273.15+17.5 # K, reference temperature
pref = 75000 # Pa, reference pressure pref = 75000 # Pa, reference pressure
Href = 10 #%, reference humdity in percent Href = 10 # %, reference humdity in percent
######################################################################## ########################################################################
s = 1e4/l # cm^-1 s = 1e4/l # cm^-1
n = 1 n = 1
H = H*100 H = RH*100
for j in range(0, 6): for j in range(0, 6):
n += ( cref[j] + cT[j]*(1/T-1/Tref) + cTT[j]*(1/T-1/Tref)**2 n += ( cref[j] + cT[j]*(1/T-1/Tref) + cTT[j]*(1/T-1/Tref)**2
@@ -404,6 +551,7 @@ def Mathar(l, T=288.15, p=101325, H=0):
return n return n
# Other necessary conversion or calculations
def K2C(K): def K2C(K):
''' '''
Kelvin to Celsius conversion Kelvin to Celsius conversion
@@ -420,7 +568,8 @@ def K2C(K):
''' '''
return K - 273.15 return K - 273.15
def hPA2mmHg(hPa):
def hPa2mmHg(hPa):
''' '''
hPa to mmHg conversion hPa to mmHg conversion
@@ -436,3 +585,41 @@ def hPA2mmHg(hPa):
''' '''
return 0.7500616827 * hPa return 0.7500616827 * hPa
def Pa2Torr(Pa):
'''
Pa to Torr conversion
Parameters
----------
Pa : float
Atmospheric pressure in Pa (Pascal)
Returns
-------
Torr : float
Atmospheric pressure in Torr
'''
return Pa * 760/101325
def svp(T):
'''
Saturation vapour pressure in Pa.
Parameters
----------
T : float
Atmospheric temperature in Kelvin
Returns
-------
svp : float
Saturation vapour pressure in Pa
'''
_A = 1.2378847e-5 # K^-2
_B = -1.9121316e-2 # K^-2
_C = 33.93711047
_D = -6.3431645e3 # K^-2
return np.exp(_A*T**2 + _B*T + _C + _D/T)
+1
View File
@@ -0,0 +1 @@
include AstroAtmosphere/data/1976USSA.txt
+33 -10
View File
@@ -2,7 +2,7 @@
**Note:** **Note:**
It would be appreciated if a reference to the following work, for which this package was originally build, is included whenever this code is used for a publication: It would be appreciated if a reference to the following work, for which this package was originally build, is included whenever this code is used for a publication:
*Quantification of the expected residual dispersion of the MICADO Near-IR imaging instrument*, van den Born & Jellema, 2020, MNRAS. Accepted 2020 June 23. Received 2020 June 23; in original form 2020 January 24. *Quantification of the expected residual dispersion of the MICADO Near-IR imaging instrument*, van den Born & Jellema, 2020, MNRAS, DOI: [10.1093/mnras/staa1870](https://doi.org/10.1093/mnras/staa1870).
**Author info**: *Joost van den Born*, *born@astron.nl* **Author info**: *Joost van den Born*, *born@astron.nl*
@@ -41,7 +41,7 @@ disp = dispersion(lat, h)
disp.setReducedHeight(P, rho) disp.setReducedHeight(P, rho)
# Calculation of the atmopheric dipsersion # Calculation of the atmopheric dipsersion
atm_dispersion = ref.cassini(n1, z0) * 3.6e6 atm_dispersion = disp.cassini(n1, n2, z0) * 3.6e6
print ('The dispersion is %.03f milli arc seconds' %(atm_dispersion)) print ('The dispersion is %.03f milli arc seconds' %(atm_dispersion))
``` ```
@@ -60,11 +60,14 @@ The package contains the following files:
- `/data/1976USSA.txt` : Data file of the 1976 US Standard Atmosphere. - `/data/1976USSA.txt` : Data file of the 1976 US Standard Atmosphere.
- `ciddorModel.py` : Contains the `Observatory()` class to calculate the refractive index of atmospheric air, using the Ciddor (1996) model. - `ciddorModel.py` : Contains the `Observatory()` class to calculate the refractive index of atmospheric air, using the Ciddor (1996) model.
- `dispersionModels.py` : Contains various atmospheric models that can be used to calculate the atmospheric dispersion - `dispersionModels.py` : Contains various atmospheric models that can be used to calculate the atmospheric dispersion
- `examples.py` : Contains several quick functions, e.g. to quickly calculate the refractive index. - `misc.py` : Contains several miscellaneous functions, e.g. to quickly calculate the refractive index.
- `refractionModels.py` : Contains various atmospheric models that can be used to calculate the atmospheric refraction - `neoslalib.py` : Contains a Python native port of the `pyslalib.SLA_REFRO()` routine, translated from the original FORTRAN code.
- `observatories.py` : Contains a dictionary with the average atmospheric conditions for various large observatories around the world.
- `refractionModels.py` : Contains various atmospheric models that can be used to calculate the atmospheric refraction
- `refractivityModels.py` : Contains various functions from literature to calculate the refractive index. Some examples of works included are Ciddor (1996), Barrell & Sears (1939), SLALIB, Owens (1967) and Edlen (1966). - `refractivityModels.py` : Contains various functions from literature to calculate the refractive index. Some examples of works included are Ciddor (1996), Barrell & Sears (1939), SLALIB, Owens (1967) and Edlen (1966).
## The Ciddor refractivity model ## The Ciddor refractivity model
The refractivity model from Ciddor, 1996, calculates the index of refraction of air using the following parameters: The refractivity model from Ciddor, 1996, calculates the index of refraction of air using the following parameters:
@@ -85,7 +88,7 @@ Basic functionality of other refractivity models is included as well and is disc
## The atmospheric refraction and atmospheric dispersion models ## The atmospheric refraction and atmospheric dispersion models
If the atmospheric refraction is denoted as R(n), then atmospheric dispersion is defined as R(n1) - R(n2). Thus they are very similar in function and also in use. If the atmospheric refraction is denoted as R(n), then atmospheric dispersion is defined as R(n1) - R(n2). Thus they are very similar in function and use.
The available models in this package: The available models in this package:
@@ -95,6 +98,9 @@ The available models in this package:
- `oriani()` - Oriani's theorem ( Atan(z) + Btan^3(z) ) - `oriani()` - Oriani's theorem ( Atan(z) + Btan^3(z) )
- `tan5()` - Oriani's theorem expanded ( Atan(z) + Btan^3(z) + Ctan^5(z) ) - `tan5()` - Oriani's theorem expanded ( Atan(z) + Btan^3(z) + Ctan^5(z) )
- `corbard()` - Error function refraction model - `corbard()` - Error function refraction model
- `matharExponential()` - Barometric exponential model by R. Mathar.
The package also includes a python native port of the `SLA_REFRO()` FORTRAN routine, ported from pyslalib. See below for more information.
Input parameters for the spherical atmosphere models (all but the first): Input parameters for the spherical atmosphere models (all but the first):
@@ -115,7 +121,7 @@ rho = at.rho(p=101325, T=273.15, RH=0.2, xc=300)
# Initializing refraction model and setting the reduced height # Initializing refraction model and setting the reduced height
ref = refraction(lat=30, h=2200) ref = refraction(lat=30, h=2200)
ref.setReducedHeight(p=101325, rho) ref.setReducedHeight(p=101325, rho=rho)
# Calculating the atmospheric refraction # Calculating the atmospheric refraction
atm_ref = ref.cassini(n, zenith=30) atm_ref = ref.cassini(n, zenith=30)
@@ -183,21 +189,21 @@ Included are
| ---------- | -------- | ------- | | ---------- | -------- | ------- |
| Barrell & Sears (1939) | `BarrellAndSears()` | Outdated model, especially poor for short wavelengths. | | Barrell & Sears (1939) | `BarrellAndSears()` | Outdated model, especially poor for short wavelengths. |
| Ciddor (1996) | `Ciddor()` | Only at standard atmosphere. CO2 density can be changed. | | Ciddor (1996) | `Ciddor()` | Only at standard atmosphere. CO2 density can be changed. |
| Edlen (1953) | `Edlen1953()` | Only at standard atmosphere. Function requires wavelength only. | | Edlen (1953) | `Edlen1953()` | The equation by Edlèn, 1953, combined with modification from Barrel (1951), to include temperature, pressure and humidity dependence. |
| Edlen (1966) | `Edlen1966()` | Only at standard atmosphere. Function requires wavelength only. | | Edlen (1966) | `Edlen1966()` | Only at standard atmosphere. Function requires wavelength only. |
| Owens (1967) | `Owens()` | - | | Owens (1967) | `Owens()` | - |
| Bonsch & Potulski (1998) | `BonschPotulski()` | Function does not include humidity | | Bonsch & Potulski (1998) | `BonschPotulski()` | Function does not include humidity |
| Birch & Downs (1994) | `BirchDowns()` | Only at standard atmosphere. Function requires wavelength only. | | Birch & Downs (1994) | `BirchDowns()` | Only at standard atmosphere. Function requires wavelength only. |
| Peck & Reeder (1972) | `PeckReeder()` | Only at standard atmosphere. Function requires wavelength only. | | Peck & Reeder (1972) | `PeckReeder()` | Only at standard atmosphere. Function requires wavelength only. |
| Hohenkerk & Sinclair (1985) | `slalib()` | Only at standard atmosphere. Function requires wavelength only. | | Hohenkerk & Sinclair (1985) | `HohenkerkAndSinclair()` | Based on Barrell & Sears equation. Generally, gives slightly larger values.|
| Hohenkerk & Sinclair (1985) | `slalib()` | Uses pySLALIB to retrieve the refractive index at standard atmospheric conditions.|
The last function extracts the refractive index from the `pyslalib.sla_refro()` function and thus requires [pyslalib](https://pypi.org/project/pySLALIB/). This is an optional dependency for the setup of AstroAtmosphere. The last function extracts the refractive index from the `pyslalib.sla_refro()` function and thus requires [pyslalib](https://pypi.org/project/pySLALIB/). This is an optional dependency for the setup of AstroAtmosphere.
## Quick functions ## Quick functions
Some functions that assume default conditions for the atmosphere. Then only the wavelength and zenith angle are required to calculate the refraction and dispersion. Some functions can make use of the `observatories` dictionary as input. These include default average conditions of the atmosphere at these locations. When these are used, only the wavelength and zenith angle are required to calculate the refraction and dispersion.
Presently, only the `'STANDARD'` and `'CERRO_ARMAZONES'` flags are known. Contact the author to add additional standard conditions.
```python ```python
# Quick refractive index # Quick refractive index
@@ -209,3 +215,20 @@ rq = quick_refraction(l1, zenith_obs, conditions='STANDARD')
# Quick dispersion # Quick dispersion
dq = quick_dispersion(l1, l2, zenith_obs, conditions='STANDARD') dq = quick_dispersion(l1, l2, zenith_obs, conditions='STANDARD')
``` ```
Presently, several observatories are known. These can all be found in the `observatories` dictionary. Contact the author to add additional standard conditions.
| Observatory | Flag | Notes |
| --------------------------------------------- | ----------------- | --------------------------------------------- |
| Standard conditions | `STANDARD` | |
| Cerro Armazones | `CERRO_ARMAZONES` | Location of the future ELT |
| Cerro Paranal | `CERRO_PARANAL` | Location of the VLT, VISTA, VST, NGTS and SSO |
| Roque de los Muchachos Observatory (La Palma) | `LA_PALMA` | GTC, INT, WHT, NOT, and others. |
| La Silla Observatory | `LA_SILLA` | ESO 3.6m telescope, NTG, BlackGEM and others. |
| Las Campanas Observatory | `LAS_CAMPANAS` | Site of the future GMT. |
## Other
This package also contains a python native port of the `SLA_REFRO()` routine of the pyslalib package, which was originally written in FORTRAN by P.T. Wallace. It can be called directly using `sla_refro()`. When using the same units as the other refraction functions, you might prefer using `slalib_refraction()` or `slalib_dispersion()`.
Finally, the dispersion model used by Alexei Filippenko in 1982 is also included. This model is a combination of the (modified) Edlèn equation and a plane-parallel atmospheric geometry. This calculation can be accessed by calling the `Filippenko1982()` function.
+7 -2
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@@ -9,9 +9,11 @@ class ADC:
self.p2 = prism('S-FPL51', 15, wedge[1], wedge[2]) self.p2 = prism('S-FPL51', 15, wedge[1], wedge[2])
self.p3 = prism('S-FPL51', 15, wedge[2], wedge[1]) self.p3 = prism('S-FPL51', 15, wedge[2], wedge[1])
self.p4 = prism('S-LAH71', 15, wedge[1], wedge[0]) self.p4 = prism('S-LAH71', 15, wedge[1], wedge[0])
self.theta = 90 self.theta = 90
self.FR = 0
def setOrientation(self, theta): def setOrientation(self, theta):
theta = float(theta)
self.p1.setPrismOrientation(theta) self.p1.setPrismOrientation(theta)
self.p2.setPrismOrientation(theta) self.p2.setPrismOrientation(theta)
self.p3.setPrismOrientation(180-1*theta) self.p3.setPrismOrientation(180-1*theta)
@@ -19,10 +21,12 @@ class ADC:
self.theta = theta self.theta = theta
def setFieldRotation(self, FR): def setFieldRotation(self, FR):
FR = float(FR)
self.p1.setPrismOrientation(self.theta-FR) self.p1.setPrismOrientation(self.theta-FR)
self.p2.setPrismOrientation(self.theta-FR) self.p2.setPrismOrientation(self.theta-FR)
self.p3.setPrismOrientation(180-1*self.theta-FR) self.p3.setPrismOrientation(180-1*self.theta-FR)
self.p4.setPrismOrientation(180-1*self.theta-FR) self.p4.setPrismOrientation(180-1*self.theta-FR)
self.FR = FR
def calculateDispersion(self, l1, l2, hx=0, hy=0, refraction=False): def calculateDispersion(self, l1, l2, hx=0, hy=0, refraction=False):
''' '''
@@ -96,6 +100,7 @@ class prism:
self.tilt1y = 0 self.tilt1y = 0
self.tilt2x = tilt2 self.tilt2x = tilt2
self.tilt2y = 0 self.tilt2y = 0
self.theta = 90
# Remember original tilts for reset: # Remember original tilts for reset:
self.tilt1x_OG = tilt1 self.tilt1x_OG = tilt1
@@ -116,7 +121,7 @@ class prism:
def setPrismOrientation(self, theta): def setPrismOrientation(self, theta):
self.tilt1x, self.tilt1y = tiltRotation(self.tilt1x_OG, self.tilt1y_OG, theta) self.tilt1x, self.tilt1y = tiltRotation(self.tilt1x_OG, self.tilt1y_OG, theta)
self.tilt2x, self.tilt2y = tiltRotation(self.tilt2x_OG, self.tilt2y_OG, theta) self.tilt2x, self.tilt2y = tiltRotation(self.tilt2x_OG, self.tilt2y_OG, theta)
self.theta = theta
def tiltRotation(tx,ty, theta): def tiltRotation(tx,ty, theta):
+35 -4
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@@ -13,7 +13,8 @@ import AstroAtmosphere
@ Description: A comparison of various atmospheric refraction models. @ Description: A comparison of various atmospheric refraction models.
Also these are used to calculate the difference in Also these are used to calculate the difference in
atmospheric dispersion, given a set of conditions. atmospheric dispersion, given a set of conditions.
This is a reproduction of Figure 1 of Spàno (2014). This is a reproduction of and expansion on Figure 1 of
Spàno (2014).
''' '''
@@ -54,7 +55,7 @@ class atmosphericModel:
def Owens(self, l=None): def Owens(self, l=None):
if not l: if not l:
l = self.lrange l = self.lrange
return (AstroAtmosphere.Owens(l, T=self.T, p=self.P, H=self.H)-1) return (AstroAtmosphere.Owens(l, T=self.T, p=self.P, RH=self.H)-1)
def BonschPotulski(self, l=None): def BonschPotulski(self, l=None):
@@ -72,10 +73,34 @@ class atmosphericModel:
l = self.lrange l = self.lrange
return (AstroAtmosphere.PeckReeder(l)-1) return (AstroAtmosphere.PeckReeder(l)-1)
def HohenkerkAndSinclair(self, l=None):
if not l:
l = self.lrange
return (AstroAtmosphere.HohenkerkAndSinclair(l, T=self.T, p=self.P, RH=self.H)-1)
def slalib(self, l=None): def slalib(self, l=None):
if not l: if not l:
l = self.lrange l = self.lrange
return(AstroAtmosphere.slalib(l, T=self.T, p=self.P, H=self.H)-1) try:
from pyslalib import slalib
return(AstroAtmosphere.slalib(l, T=self.T, p=self.P, RH=self.H)-1)
except ImportError as e:
print('Could not import pyslalib.slalib. Using slower Python native function sla_refro().')
h=0
lat=-24
tlr=0.0065
eps=1e-10
zObs = np.deg2rad(45.07182)
p = self.P/100
R = []
if type(l) == float:
l = [l]
for wl in l:
R.append(AstroAtmosphere.sla_refro(zObs, h, self.T, p, self.H, wl, lat, tlr, eps))
if len(l) == 1:
return R[0]
else:
return np.asarray(R)
if __name__ == '__main__': if __name__ == '__main__':
@@ -92,6 +117,7 @@ if __name__ == '__main__':
BonschPotulskiData = 1e8 * at.BonschPotulski() BonschPotulskiData = 1e8 * at.BonschPotulski()
BirchDownsData = 1e8 * at.BirchDowns() BirchDownsData = 1e8 * at.BirchDowns()
PeckReederData = 1e8 * at.PeckReeder() PeckReederData = 1e8 * at.PeckReeder()
HSdata = 1e8 * at.HohenkerkAndSinclair()
slalibData = 1e8 * at.slalib() slalibData = 1e8 * at.slalib()
# Plotting the results # Plotting the results
@@ -106,13 +132,14 @@ if __name__ == '__main__':
ax2.plot(at.lrange, BonschPotulskiData - CiddorData, 'g-.', label='Bonsch & Potulski (1998)') ax2.plot(at.lrange, BonschPotulskiData - CiddorData, 'g-.', label='Bonsch & Potulski (1998)')
ax2.plot(at.lrange, BirchDownsData - CiddorData, 'r-.', label='Birch & Downs (1993, 1994)') ax2.plot(at.lrange, BirchDownsData - CiddorData, 'r-.', label='Birch & Downs (1993, 1994)')
ax2.plot(at.lrange, PeckReederData - CiddorData, 'b--', label='Peck & Reeder (1972)') ax2.plot(at.lrange, PeckReederData - CiddorData, 'b--', label='Peck & Reeder (1972)')
ax2.plot(at.lrange, HSdata - CiddorData, 'y--', label='Hohenkerk & Sinclair (1985)')
ax2.plot(at.lrange, slalibData - CiddorData, 'y-', label='ZEMAX / SLALIB') ax2.plot(at.lrange, slalibData - CiddorData, 'y-', label='ZEMAX / SLALIB')
box = ax2.get_position() box = ax2.get_position()
ax2.set_position([box.x0, box.y0, box.width, box.height]) ax2.set_position([box.x0, box.y0, box.width, box.height])
ax2.legend(loc='center left', bbox_to_anchor=(1, 0.5)) ax2.legend(loc='center left', bbox_to_anchor=(1, 0.5))
ax2.set_xlabel('Wavelength ($\mu m$)') ax2.set_xlabel('Wavelength ($\mu m$)')
ax2.set_ylabel('$\Delta$n $\\times$ $10^{8}$') ax2.set_ylabel('$\Delta$n $\\times$ $10^{8}$')
ax2.set_ylim([-3,3]) ax2.set_ylim([-3,7])
plt.tight_layout() plt.tight_layout()
plt.show() plt.show()
@@ -128,6 +155,7 @@ if __name__ == '__main__':
at.BonschPotulski, at.BonschPotulski,
at.BirchDowns, at.BirchDowns,
at.PeckReeder, at.PeckReeder,
at.HohenkerkAndSinclair,
at.slalib at.slalib
] ]
@@ -166,11 +194,14 @@ if __name__ == '__main__':
'Ciddor (1996)', 'Ciddor (1996)',
'Edlen (1953)', 'Edlen (1953)',
'Edlen (1966)', 'Edlen (1966)',
'Owens (1967)',
'Bonsch & Potulski (1998)', 'Bonsch & Potulski (1998)',
'Birch & Downs (1993, 1994)', 'Birch & Downs (1993, 1994)',
'Peck & Reeder (1972)', 'Peck & Reeder (1972)',
'Hohenkerk & Sinclair (1985)',
'slalib'] 'slalib']
tableData = [] tableData = []
for i in range(len(methodStringList)): for i in range(len(methodStringList)):
tableData.append([methodStringList[i], filterDispersion[0][i], filterDispersion[1][i], filterDispersion[2][i], filterDispersion[3][i]]) tableData.append([methodStringList[i], filterDispersion[0][i], filterDispersion[1][i], filterDispersion[2][i], filterDispersion[3][i]])
print(tabulate(tableData, headers=['Model', 'I-band\n(0.8 - 0.934)', 'J-band\n(1.15 - 1.345)', 'H-band\n(1.49 - 1.78)', 'K-band\n(1.97 - 2.32)'])) print(tabulate(tableData, headers=['Model', 'I-band\n(0.8 - 0.934)', 'J-band\n(1.15 - 1.345)', 'H-band\n(1.49 - 1.78)', 'K-band\n(1.97 - 2.32)']))
+2 -2
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@@ -21,14 +21,14 @@ def setup_package():
# write_version_py() # write_version_py()
setup(name='AstroAtmosphere', setup(name='AstroAtmosphere',
version='1.0', version='1.4',
description='Collection of equations for refractive index, refraction and dispersion calculations of atmospheric air.', description='Collection of equations for refractive index, refraction and dispersion calculations of atmospheric air.',
long_description=__readme__, long_description=__readme__,
long_description_content_type='text/markdown', long_description_content_type='text/markdown',
author='Joost van den Born', author='Joost van den Born',
author_email='born@astron.nl', author_email='born@astron.nl',
url='https://gitlab.astro-wise.org/micado/atmosphericmodel', url='https://gitlab.astro-wise.org/micado/atmosphericmodel',
download_url='https://gitlab.astro-wise.org/micado/atmosphericmodel/-/archive/v_10/atmosphericmodel-v_10.tar.gz', download_url='https://gitlab.astro-wise.org/micado/atmosphericmodel/-/archive/v1.4/atmosphericmodel-v1.4.tar.gz',
license='GNU General Public License v3', license='GNU General Public License v3',
data_files = [('',['LICENSE.txt'])], data_files = [('',['LICENSE.txt'])],
package_dir={'AstroAtmosphere': 'AstroAtmosphere'}, package_dir={'AstroAtmosphere': 'AstroAtmosphere'},