def semi_circular_loop(length: u.m, theta0: u.deg = 0 * u.deg):
"""
Return a Heliographic Stonyhurst coordinate object with points of a semi circular loop in it.
"""
r_sun = const.R_sun
def r_2_func(x):
return np.arccos(0.5 * x / r_sun.to(u.cm).value) - np.pi + length.to(
u.cm).value / 2. / x
r_2 = scipy.optimize.bisect(r_2_func,
length.to(u.cm).value / (2 * np.pi),
length.to(u.cm).value / np.pi) * u.cm
alpha = np.arccos(0.5 * (r_2 / r_sun).decompose())
phi = np.linspace(-np.pi * u.rad + alpha, np.pi * u.rad - alpha, 2000)
# Quadratic formula to find r
a = 1.
b = -2 * (r_sun.to(u.cm) * np.cos(phi.to(u.radian)))
c = r_sun.to(u.cm)**2 - r_2.to(u.cm)**2
r = (-b + np.sqrt(b**2 - 4 * a * c)) / 2 / a
# Choose only points above the surface
i_r = np.where(r > r_sun)
r = r[i_r]
phi = phi[i_r]
hcc_frame = frames.Heliocentric(
observer=SkyCoord(lon=0 * u.deg,
lat=theta0,
radius=r_sun,
frame='heliographic_stonyhurst'))
return SkyCoord(x=r.to(u.cm) * np.sin(phi.to(u.radian)),
y=u.Quantity(r.shape[0] * [0 * u.cm]),
z=r.to(u.cm) * np.cos(phi.to(u.radian)),
frame=hcc_frame).transform_to('heliographic_stonyhurst')
def semi_circular_loop(length: u.m, theta0: u.deg=0*u.deg):
"""
Return a Heliographic Stonyhurst coordinate object with points of a semi circular loop in it.
"""
r_sun = const.R_sun
def r_2_func(x):
return np.arccos(0.5 * x / r_sun.to(u.cm).value) - np.pi + length.to(u.cm).value / 2. / x
r_2 = scipy.optimize.bisect(r_2_func,
length.to(u.cm).value / (2 * np.pi),
length.to(u.cm).value / np.pi) * u.cm
alpha = np.arccos(0.5 * (r_2 / r_sun).decompose())
phi = np.linspace(-np.pi * u.rad + alpha, np.pi * u.rad - alpha, 2000)
# Quadratic formula to find r
a = 1.
b = -2 * (r_sun.to(u.cm) * np.cos(phi.to(u.radian)))
c = r_sun.to(u.cm)**2 - r_2.to(u.cm)**2
r = (-b + np.sqrt(b**2 - 4 * a * c)) / 2 / a
# Choose only points above the surface
i_r = np.where(r > r_sun)
r = r[i_r]
phi = phi[i_r]
hcc_frame = frames.Heliocentric(
observer=SkyCoord(lon=0 * u.deg, lat=theta0, radius=r_sun, frame='heliographic_stonyhurst'))
return SkyCoord(
x=r.to(u.cm) * np.sin(phi.to(u.radian)),
y=u.Quantity(r.shape[0] * [0 * u.cm]),
z=r.to(u.cm) * np.cos(phi.to(u.radian)),
frame=hcc_frame).transform_to('heliographic_stonyhurst')
def fwd(self, lat: u.deg, lon: u.deg, azimuth: u.deg, distance: u.m):
"""Solve forward geodetic problem.
Returns latitudes, longitudes and back azimuths of terminus points
given latitudes `lat` and longitudes `lon` of initial points, plus
forward `azimuth`s and `distance`s.
This method use `pyproj.Geod.fwd` as a backend.
Parameters
----------
lat : ~astropy.units.Quantity
Geodetic latitude of the initial point.
lon : ~astropy.units.Quantity
Longitude of the initial point.
azimuth : ~astropy.units.Quantity
Geodetic azimuth.
distance : ~astropy.units.Quantity
Distance.
Returns
-------
lat : ~astropy.units.Quantity
Geodetic latitude of the terminus point.
lon : ~astropy.units.Quantity
Longitude of the terminus point.
back_azimuth : ~astropy.units.Quantity
Back geodetic azimuth.
"""
out_lon, out_lat, out_baz = self.geod.fwd(lon.to('radian').value,
lat.to('radian').value,
azimuth.to('radian').value,
distance.to('m').value,
radians=True)
return out_lat * u.rad, out_lon * u.rad, out_baz * u.rad
def enu_to_ecef(x: u.m,
y: u.m,
z: u.m,
origin: tuple[u.deg, u.deg, u.m],
ell=None):
"""Convert local cartesian to geocentric cartesian coordinates.
Convert local east-north-up (ENU) local cartesian
coordinate system with the origin in (`lat0`, `lon0`, `height0`)
to the Earth Centered Earth Fixed (ECEF) cartesian coordinates.
Parameters
----------
x, y, z : ~astropy.units.Quantity
Local east-north-uo cartesian coordinates.
origin : tuple of ~astropy.units.Quantity
Ggeocentric (spherical) or geodetic coordinates of the origin
(`lat0`, `lon0`, `r0`) or (`lat0`, `lon0`, `h0`).
ell : instance of the `pygeoid.coordinates.ellipsoid.Ellipsoid`
Reference ellipsoid to which geodetic coordinates are referenced to.
Default is None, meaning spherical coordinates instead of geodetic.
Returns
-------
x, y, z : ~astropy.units.Quantity
Geocentric cartesian coordinates, in metres.
"""
rotation_matrix = _ecef_to_enu_rotation_matrix(origin[0], origin[1]).T
out_shape = x.shape
x, y, z = _np.dot(
rotation_matrix,
_np.array([
_np.asarray(x.to('m').value).flatten(),
_np.asarray(y.to('m').value).flatten(),
_np.asarray(z.to('m').value).flatten()
])) * u.m
if ell is None:
x0, y0, z0 = spherical_to_cartesian(*origin)
else:
x0, y0, z0 = geodetic_to_cartesian(*origin, ell=ell)
return ((x + x0).reshape(out_shape), (y + y0).reshape(out_shape),
(z + z0).reshape(out_shape))
def rms(diameter: u.m,
wavelength: u.nm,
fried_param: u.m,
outer_scale: u.m,
freqs=None):
'''
Von Karman wavefront rms value over a circular aperture
Parameters
----------
diameter: `~astropy.units.quantity.Quantity` equivalent to meter
Aperture diameter
wavelength: `~astropy.units.quantity.Quantity` equivalent to nanometer
wavelength
fried_param: `~astropy.units.quantity.Quantity` equivalent to meter
Fried parameter r0 defined at the specified wavelength
outer_scale: `~astropy.units.quantity.Quantity` equivalent to meter
Outer scale L0. Use np.inf for Kolmogorov spectrum
Other Parameters
----------
freqs: array of `~astropy.units.quantity.Quantity` equivalent to 1/meter
spatial frequencies array. Default logspace(-8, 4, 1000) m^-1
Returns
-------
rms: `~astropy.units.quantity.Quantity` equivalent to nm
wavefront rms for the specified von Karman turbulence
'''
R = 0.5 * diameter.to(u.m).value
wl = wavelength.to(u.nm).value
r0 = fried_param.to(u.m).value
L0 = outer_scale.to(u.m).value
psd = VonKarmanPsd(r0, L0)
if freqs is None:
freqs = np.logspace(-8, 4, 1000) / u.m
freqs = freqs.to(1 / u.m).value
bess = jv(1, 2 * np.pi * R * freqs)
psdTotal = psd.spatial_psd(freqs)
psdPistonRem = psdTotal * (1 - (bess / (np.pi * R * freqs))**2)
varInRad2 = np.trapz(psdPistonRem * 2 * np.pi * freqs, freqs)
return np.sqrt(varInRad2) * wl / 2 / np.pi * u.nm
def __init__(self, normal, center: u.m, radius: u.m, current: u.A, n=300):
self.normal = normal / np.linalg.norm(normal)
self.center = center.to(u.m).value
if radius > 0:
self.radius = radius.to(u.m).value
else:
raise ValueError("Radius should bu larger than 0")
self.current = current.to(u.A).value
# parametric equation
# find other two axises in the disc plane
z = np.array([0, 0, 1])
axis_x = np.cross(z, self.normal)
axis_y = np.cross(self.normal, axis_x)
if np.linalg.norm(axis_x) == 0:
axis_x = np.array([1, 0, 0])
axis_y = np.array([0, 1, 0])
else:
axis_x = axis_x / np.linalg.norm(axis_x)
axis_y = axis_y / np.linalg.norm(axis_y)
self.axis_x = axis_x
self.axis_y = axis_y
def curve(t):
if isinstance(t, np.ndarray):
t = np.expand_dims(t, 0)
axis_x_mat = np.expand_dims(axis_x, 1)
axis_y_mat = np.expand_dims(axis_y, 1)
return self.radius*(np.matmul(axis_x_mat, np.cos(t))
+ np.matmul(axis_y_mat, np.sin(t))) \
+ np.expand_dims(self.center, 1)
else:
return self.radius * (np.cos(t) * axis_x +
np.sin(t) * axis_y) + self.center
self.curve = curve
self.roots_legendre = roots_legendre(n)
self.n = n
def cartesian_to_geodetic(x: u.m, y: u.m, z: u.m, ell):
"""Convert 3D cartesian to geodetic coordinates.
Parameters
----------
x, y, z : ~astropy.units.Quantity
Cartesian coordinates.
ell : instance of the `pygeoid.coordinates.ellipsoid.Ellipsoid`
Reference ellipsoid to which geodetic coordinates are referenced to.
Returns
-------
lat : ~astropy.units.Quantity
Geodetic latitude.
lon : ~astropy.units.Quantity
Geodetic longitude.
height : float or array_like of floats
Geodetic height.
Notes
-----
The algorithm of H. Vermeille is used for this transformation [1]_.
References
----------
.. [1] Vermeille, H., 2011. An analytical method to transform geocentric
into geodetic coordinates. Journal of Geodesy, 85(2), pp.105-117.
"""
lat, lon, height = _cartesian_to_geodetic(x.to('m').value,
y.to('m').value,
z.to('m').value,
ell=ell,
degrees=True)
return lat * u.deg, lon * u.deg, height * u.m
def pz90_atm_corr(height: u.m) -> u.mGal:
"""Return PZ-90 atmospheric correction, in mGal.
Parameters
----------
height : ~astropy.units.Quantity
Height above sea level.
Returns
-------
~astropy.units.Quantity
Atmospheric correction.
"""
height = height.to('km').value
return 0.87 * np.exp(-0.116 * (height)**(1.047)) * u.mGal
def grs80_atm_corr_interp(height: u.m, kind: str = 'linear') -> u.mGal:
"""Return GRS 80 atmospheric correction, in mGal.
Interpolated from the table data [1]_.
Note: If height < 0 m or height > 40000 m, then correction is extrapolated
Parameters
----------
height : ~astropy.units.Quantity
Height above sea level.
kind : str or int, optional
Specifies the kind of interpolation as a string
('linear', 'nearest', 'zero', 'slinear', 'quadratic', 'cubic'
where 'zero', 'slinear', 'quadratic' and 'cubic' refer to a spline
interpolation of zeroth, first, second or third order) or as an
integer specifying the order of the spline interpolator to use.
Default is 'linear'.
Returns
-------
~astropy.units.Quantity
Atmospheric correction.
References
----------
.. [1] Moritz, H. (1980). Geodetic reference system 1980.
Bulletin Géodésique, 54(3), 395-405
"""
fname = os.path.join(os.path.dirname(__file__),
'data/IAG_atmosphere_correction_table.txt')
table_heights, corr = np.loadtxt(fname,
unpack=True,
delimiter=',',
skiprows=4,
dtype=float)
interp = interp1d(table_heights * 1000,
corr,
kind=kind,
fill_value='extrapolate',
assume_sorted=True)
return interp(height.to('m').value) * u.mGal
def wenzel_atm_corr(height: u.m) -> u.mGal:
"""Return atmospheric correction by Wenzel, in mGal.
Parameters
----------
height : ~astropy.units.Quantity
Height above sea level.
Returns
-------
~astropy.units.Quantity
Atmospheric correction.
References
----------
.. [1] Wenzel, H., 1985, Hochauflosende Kugelfunktionsmodelle fur des
Gravitationspotential der Erde [1]: Wissenschaftliche arbeiten der
Fachrichtung Vermessungswesen der Universitat Hannover, 137
"""
height = height.to('m').value
return (0.874 - 9.9e-5 * height + 3.56e-9 * height**2) * u.mGal
def semi_circular_loop(length: u.m, latitude: u.deg = 0 * u.deg):
"""
Return a Heliographic Stonyhurst coordinate object with points of a semi circular loop in it.
"""
r_sun = constants.radius
def r_2_func(x):
return np.arccos(0.5 * x / r_sun.to(u.cm).value) - np.pi + length.to(
u.cm).value / 2. / x
# Find the loop radius corresponding to the loop length
r_2 = scipy.optimize.bisect(r_2_func,
length.to(u.cm).value / (2 * np.pi),
length.to(u.cm).value / np.pi) * u.cm
alpha = np.arccos(0.5 * (r_2 / r_sun))
phi = np.linspace(-np.pi * u.rad + alpha, np.pi * u.rad - alpha, 2000)
hcc_frame = frames.Heliocentric(observer=frames.HeliographicStonyhurst(
lon=0 * u.deg, lat=latitude, radius=1 * u.AU))
return SkyCoord(x=r_2 * np.sin(phi),
y=0 * u.cm,
z=r_2 * np.cos(phi) + r_sun,
frame=hcc_frame).transform_to('heliographic_stonyhurst')
def __init__(self, moment: u.A * u.m**2, p0: u.m):
self.moment = moment.to(u.A * u.m * u.m).value
self.p0 = p0.to(u.m).value
def __init__(self, direction, p0: u.m, current: u.A):
self.direction = direction / np.linalg.norm(direction)
self.p0 = p0.to(u.m).value
self.current = current.to(u.A).value
def __init__(self, p1: u.m, p2: u.m, current: u.A):
self.p1 = p1.to(u.m).value
self.p2 = p2.to(u.m).value
if np.all(p1 == p2):
raise ValueError("p1, p2 should not be the same point.")
self.current = current.to(u.A).value
def __init__(
self,
# scalars
pixel_diameter: u.m,
pixel_fill_factor,
focal_length: u.m / u.radian,
mirror_area: u.m**2,
# arrays (vs wavelength)
telescope_transmissivity,
mirror_reflectivity,
window_transmissivity,
pde,
):
"""
Calculate parameters related to the camera efficiency
Formulae and data obtained from the excel files at:
https://www.mpi-hd.mpg.de/hfm/CTA/MC/Prod4/Config/Efficiencies
Credit: Konrad Bernloehr
"""
self.wavelength = np.arange(200, 1000) << u.nm
size = self.wavelength.size
if not telescope_transmissivity.size == size:
raise ValueError(
"All arrays must specify values over full wavelength range")
if not mirror_reflectivity.size == size:
raise ValueError(
"All arrays must specify values over full wavelength range")
if not window_transmissivity.size == size:
raise ValueError(
"All arrays must specify values over full wavelength range")
if not pde.size == size:
raise ValueError(
"All arrays must specify values over full wavelength range")
self.pixel_diameter = pixel_diameter.to('m')
self.pixel_fill_factor = pixel_fill_factor
self.focal_length = focal_length.to("m/radian")
self.mirror_area = mirror_area.to("m2")
self.telescope_transmissivity = telescope_transmissivity
self.mirror_reflectivity = mirror_reflectivity
self.window_transmissivity = window_transmissivity
self._pde = pde
self._pde_scale = 1
self._cherenkov_scale = 1
# Read environment arrays
df_env = pd.read_csv(PATH_ENV)
diff_flux_unit = u.Unit('10^9 / (nm s m^2 sr)')
self._nsb_diff_flux = df_env['nsb_site'].values << diff_flux_unit
self._moonlight_diff_flux = df_env['moonlight'].values << diff_flux_unit
self._atmospheric_transmissivity = df_env[
'atmospheric_transmissivity'].values << 1 / u.nm
# Scale cherenkov spectrum to match normalisation
# scaled to 100 photons/m2 in the wavelength range from 300–600 nm
# a value typical for γ-ray showers of about 500 GeV viewed at small core distances
# (from https://jama.cta-observatory.org/perspective.req#/items/28666)
# TODO: check wrt area
cherenkov_integral = self._integrate_cherenkov(
self._cherenkov_diff_flux_on_ground, u.Quantity(300, u.nm),
u.Quantity(600, u.nm))
self._cherenkov_scale = 100 / cherenkov_integral
self._nsb_flux_300_650 = self._integrate_nsb(
self._nsb_diff_flux_on_ground, u.Quantity(300, u.nm),
u.Quantity(650, u.nm))
self._moonlight_flux_300_650 = self._integrate_nsb(
self._moonlight_diff_flux_on_ground, u.Quantity(300, u.nm),
u.Quantity(650, u.nm))
