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@@ -1,3 +1,6 @@
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.DS_Store
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__pychache__/
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.ipynb_checkpoints/
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dist/
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AstroAtmosphere.egg-info/
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@@ -387,6 +387,73 @@ class dispersion(Observatory):
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return np.degrees(_dispersionError)
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def independentCassiniError(self, n1, n2, zenith, dn1=0, dn2=0, dz=0,
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lat=None, h=None):
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'''
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Calculates the uncertainty in the atmospheric dispersion,
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following the Cassini model, without assumptions about the
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refractivity model.
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This involves a much shorter use the chain rule.
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Not taken into account is the errror propagation in the scale height
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of the atmosphere, from my results this should give a small or even
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negligible difference.
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Parameters
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----------
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n1 : float
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Refractive index at the first wavelength of interest at the
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observer
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n2 : float
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Refractive index at the second wavelength of interest at the
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observer
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zenith : float
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Angle of observation in degrees.
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zenith = 0 means the observation is directly overhead.
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dn1 : float
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Uncertainty in the provided value of the refractive index
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at the first wavelength
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dn2 : float
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Uncertainty in the provided value of the refractive index
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at the second wavelength
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dz : float (default: 0)
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Uncertainty in the zenith angle, in degrees.
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lat : float (default: None)
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If entered, overrides the latitude attribute of the class.
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h : float (default=None)
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If entered, overrides the altitude attribute of the class.
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Returns
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-------
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dRR : float
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Uncertainty in the atmospheric dispersion in degrees.
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'''
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if lat == None:
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lat = self.lat
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else:
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self.lat = lat
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if h == None:
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h = self.h
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else:
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self.h = h
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# Some precalculation and variable setting
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_zenith = np.deg2rad(zenith)
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_dz = np.deg2rad(dz)
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_R = self.rc
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_H = self.H
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# Partial derivatives for derivation to n1, n2, and z
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_dddn1 = - _R * np.sin(_zenith) / ( (_R + _H) * np.sqrt(1 - (n1 * _R * np.sin(_zenith) / (_R + _H))**2 ) )
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_dddn2 = _R * np.sin(_zenith) / ( (_R + _H) * np.sqrt(1 - (n2 * _R * np.sin(_zenith) / (_R + _H))**2 ) )
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_dddz = (_R * np.cos(_zenith)) / (_R + _H) * ( n1 / np.sqrt(1-(n1**2 * _R**2 * np.sin(_zenith)**2)/(_R + _H)**2) - n2 / np.sqrt(1-(n2**2 * _R**2 * np.sin(_zenith)**2)/(_R + _H)**2) )
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# Combining the partial derivatives
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_dispersionError = np.sqrt( (_dddn1 * dn1)**2 + (_dddn2 * dn2)**2 + (_dddz * dz)**2)
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return np.degrees(_dispersionError)
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def corbard(self, n1, n2, zenith, reduced_height=None):
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'''
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Corbard et al., 2019, mention an additional formula based on
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@@ -336,7 +336,7 @@ def slalib_refraction(l, zenith, conditions='STANDARD', T=288.15, p=101325,
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_phi = np.deg2rad(lat) # From degrees to radians
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R = []
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if type(l) == float or type(l) == int:
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if isinstance(l, float) or isinstance(l, int):
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l = [l]
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if use_pyslalib:
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try:
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@@ -345,13 +345,13 @@ def slalib_refraction(l, zenith, conditions='STANDARD', T=288.15, p=101325,
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print('pySLALIB package not found! Try installing it first.')
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for wl in l:
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# If using original slalib (e.g. PySLALIB)
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Refrac = slalib.sla_refro(_zenith, h, T, _P, RH, wl, phi, tlr, eps)
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Refrac = slalib.sla_refro(_zenith, h, T, _P, RH, wl, _phi, tlr, eps)
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R.append(np.degrees(Refrac))
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# If using internal slalib port
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else:
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for wl in l:
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Refrac = sla_refro(_zenith, h, T, _P, RH, wl, phi, tlr, eps)
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Refrac = sla_refro(_zenith, h, T, _P, RH, wl, _phi, tlr, eps)
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R.append(np.degrees(Refrac))
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if len(l) == 1:
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@@ -174,9 +174,10 @@ def Edlen1966(l, T=288.15, p=101325, RH=0, CO2=300, f=None):
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def Owens(l, T=288.15, p=101325, RH=0):
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'''
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From Owens, 1967
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Equation 32
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Note that the pressure P and H are in torricelli (Torr),
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however, this is almost precisely 1 Torr = 1 mmHg
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Equations 29 to 31
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Code heavily based on ScopeSIM (https://scopesim.readthedocs.io/)
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and http://www.caha.es/newsletter/news03b/pedraz/newslet.html
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Parameters
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----------
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@@ -194,10 +195,27 @@ def Owens(l, T=288.15, p=101325, RH=0):
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n : float
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Refractive index of atmospheric air at the given conditions
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'''
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P = hPa2mmHg(p/100)
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T = K2C(T)
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s = 1 / l
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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)
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# Calculation from ScopeSIM.effects.atmospheric_refraction()
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pres = p / 100 # from mbar to Pa
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Ps = -10474. + 116.43 * T - 0.43284 * T**2 + 0.0005384 * T**3
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Pw = Ps * RH / 100.
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Pa = pres - Pw
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# Wavenumber s
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s = 1. / l
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# Density factor of dry air, eq. 30
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Da = (Pa / T) * (1. + Pa * (57.9E-8 - 0.0009325 / T + 0.25844 / T**2))
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# Density factor of moist air, eq. 31
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Dw = (Pw / T) * (1. + Pw * (1. + 3.7E-4 * Pw) *
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(-2.37321E-3 + 2.23366 / T - 710.792 / T**2 +
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77514.1 / T**3))
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# Combining the two into eq. 29
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na = Da * (2371.34 + 683939.7 / (130. - s**2) + 4547.3 / (38.9 - s**2))
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nw = Dw * (6487.31 + 58.058 * s**2 - 0.7115 * s**4 + 0.08851 * s**6)
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R = na + nw
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n = R/1e8 + 1
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return n
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@@ -409,10 +427,10 @@ def slalib(l, T=288.15, p=101325, RH=0, h=0, lat=-24, tlr=0.0065, eps=1e-10):
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conditions.
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'''
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try:
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from pyslalib import slalib
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from pyslalib import slalib
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except ImportError as e:
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print('pySLALIB package not found! Try installing it first.\nReturning n=1.')
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return 1
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print('pySLALIB package not found! Try installing it first.\nReturning n=1.')
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return 1
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zObs = np.deg2rad(45.06563)
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p = p/100
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@@ -110,7 +110,7 @@ Input parameters for the spherical atmosphere models (all but the first):
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- xc - CO2 density [ppm]
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- lat - Latitude [deg]
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- h - Height above sea level [m]
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- l - Wavelength(s) [um]
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- l - Wavelength(s) [μm]
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- z - Zenith angle [deg]
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An example - To calculate the atmospheric refraction we set up a `refraction()` object. This requires the latitude and altitude of the observer. The atmospheric dispersion is calculated similarly, but by exchanging the `refraction()` object by a `dispersion()` object and parsing two refractive indices into the `cassini()` function.
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@@ -195,6 +195,7 @@ Included are
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| Bonsch & Potulski (1998) | `BonschPotulski()` | Allows for any temperature, pressure, humidity and CO2 density. |
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| Birch & Downs (1994) | `BirchDowns()` | Only at standard atmosphere. Function requires wavelength only. |
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| Peck & Reeder (1972) | `PeckReeder()` | Only at standard atmosphere. Function requires wavelength only. |
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| Mathar (2006) | `Mathar()` | Allows for temperature, pressure and humidity specification. Works best at wavelengths above 1.4 μm. |
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| Hohenkerk & Sinclair (1985) | `HohenkerkAndSinclair()` | Based on Barrell & Sears equation. Generally, gives slightly larger values.|
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| Hohenkerk & Sinclair (1985) | `slalib()` | Uses pySLALIB to retrieve the refractive index at standard atmospheric conditions.|
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@@ -226,6 +227,7 @@ Presently, several observatories are known. These can all be found in the `obser
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| Roque de los Muchachos Observatory (La Palma) | `LA_PALMA` | GTC, INT, WHT, NOT, and others. |
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| La Silla Observatory | `LA_SILLA` | ESO 3.6m telescope, NTG, BlackGEM and others. |
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| Las Campanas Observatory | `LAS_CAMPANAS` | Site of the future GMT. |
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| Mauna Kea Observatory (Hawaii) | `MAUNA_KEA` | Location of Keck, Subaru, Gemini North and others.|
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## Other
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# write_version_py()
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setup(name='AstroAtmosphere',
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version='1.4.1',
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version='1.6',
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description='Collection of equations for refractive index, refraction and dispersion calculations of atmospheric air.',
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long_description=__readme__,
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long_description_content_type='text/markdown',
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author='Joost van den Born',
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author_email='born@astron.nl',
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url='https://gitlab.astro-wise.org/micado/atmosphericmodel',
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download_url='https://gitlab.astro-wise.org/micado/atmosphericmodel/-/archive/v1.4.1/atmosphericmodel-v1.4.1.tar.gz',
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download_url='https://gitlab.astro-wise.org/micado/atmosphericmodel/-/archive/v1.6/atmosphericmodel-v1.6.tar.gz',
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license='GNU General Public License v3',
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data_files = [('',['LICENSE.txt'])],
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package_dir={'AstroAtmosphere': 'AstroAtmosphere'},
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