def read_pop_fromhdf5(self, filename):
"""
Read from an hdf5 file the cloud population. the :class:`Cloud_Population` is thus initialized by :func:`initialize_cloud_population_from_output`
"""
f = h5.File(filename, 'r')
g = f["Cloud_Population"]
self.r = g["R"][...]
self.phi = g["Phi"][...]
self.L = g["Sizes"][...]
self.W = g["Emissivity"][...]
coord_array = np.zeros(self.n)
if self.models[self.model] == 1:
self.theta = g["Theta"][...]
coord_array = coord.PhysicsSphericalRepresentation(
self.phi * u.rad, self.theta * u.rad, self.r * u.kpc)
elif self.models[self.model] >= 2:
self.zeta = g["Z"][...]
coord_array = coord.CylindricalRepresentation(
self.r * u.kpc, self.phi * u.rad, self.zeta * u.kpc)
self.d_sun = g["D_sun"][...]
self.long = g["Gal_longitude"][...]
self.lat = g["Gal_Latitude"][...]
self.healpix_vecs = g["Healpix_Vec"][...]
self.cartesian_galactocentric = self.cartesianize_coordinates(
coord_array)
from utilities.utilities_functions import bash_colors
cols = bash_colors()
f.close()
print(cols.bold("////// \t read from " + filename + "\t ////////"))
pass
gc3 = c1.transform_to(gc_frame2)
print(gc3.v_x, gc3.v_y, gc3.v_z)
##############################################################################
# The transformations also work in the opposite direction. This can be useful
# for transforming simulated or theoretical data to observable quantities. As
# an example, we'll generate 4 theoretical circular orbits at different
# Galactocentric radii with the same circular velocity, and transform them to
# Heliocentric coordinates:
ring_distances = np.arange(10, 25 + 1, 5) * u.kpc
circ_velocity = 220 * u.km / u.s
phi_grid = np.linspace(90, 270, 512) * u.degree # grid of azimuths
ring_rep = coord.CylindricalRepresentation(
rho=ring_distances[:, np.newaxis],
phi=phi_grid[np.newaxis],
z=np.zeros_like(ring_distances)[:, np.newaxis])
angular_velocity = (-circ_velocity / ring_distances).to(
u.mas / u.yr, u.dimensionless_angles())
ring_dif = coord.CylindricalDifferential(
d_rho=np.zeros(phi_grid.shape)[np.newaxis] * u.km / u.s,
d_phi=angular_velocity[:, np.newaxis],
d_z=np.zeros(phi_grid.shape)[np.newaxis] * u.km / u.s)
ring_rep = ring_rep.with_differentials(ring_dif)
gc_rings = coord.SkyCoord(ring_rep, frame=coord.Galactocentric)
##############################################################################
# First, let's visualize the geometry in Galactocentric coordinates. Here are
# the positions and velocities of the rings; note that in the velocity plot,
def __call__(self):
self.clouds = []
np.random.seed(11 + self.random_seed)
a = np.random.uniform(low=0., high=1., size=self.n)
self.phi = 2. * np.pi * a
if self.model == 'Spherical':
self.r = norm.rvs(loc=self.R_params[0],
scale=self.R_params[1],
size=self.n)
v = np.random.uniform(low=0., high=1., size=self.n)
self.theta = np.arccos(2. * v - 1.)
coord_array = coord.PhysicsSphericalRepresentation(
self.phi * u.rad, self.theta * u.rad, self.r * u.kpc)
self.cartesian_galactocentric = self.cartesianize_coordinates(
coord_array)
self.heliocentric_coordinates()
for i, x, p, t, d, latit, longit in zip(np.arange(self.n), self.r,
self.phi, self.theta,
self.d_sun, self.lat,
self.long):
if x <= 0.:
self.r[i] = np.random.uniform(low=0., high=1., size=1)
x = self.r[i]
c = Cloud(i, x, p, t, size=None, em=None)
c.assign_sun_coord(d, latit, longit)
self.clouds.append(c)
else:
self.r = self.phi * 0.
rbar = self.R_params[2]
if self.model == 'Axisymmetric':
np.random.seed(self.random_seed + 29)
self.r = norm.rvs(loc=self.R_params[0],
scale=self.R_params[1],
size=self.n)
negs = np.ma.masked_less(self.r, 0.)
#central molecular zone
self.r[negs.mask] = 0.
elif self.model == 'LogSpiral':
#the bar is assumed axisymmetric and with an inclination angle phi0~25 deg as
#it has been measured by F*x et al. 1999
phi_0 = np.deg2rad(25.)
self.phi += phi_0
subsize = np.int(self.n / 10)
self.r[0:subsize] = norm.rvs(loc=self.R_params[0],
scale=self.R_params[1],
size=subsize)
#np.random.uniform(low=0.,high=8.,size=self.n/4)
rscale = rbar / 1.5
self.r[subsize:self.n],self.phi[subsize:self.n]=log_spiral_radial_distribution2(\
rbar,phi_0,self.n-subsize,self.R_params[0],self.R_params[1])
#self.r[subsize:self.n]=log_spiral_radial_distribution(self.phi[subsize:self.n],rbar,phi_0)
#simulate the bar
arr = np.ma.masked_less(self.r, rbar)
self.r[arr.mask] = abs(
np.random.normal(loc=0.,
scale=rscale,
size=len(self.r[arr.mask])))
negs = np.ma.masked_less(self.r, 0.)
#central molecular zone
self.r[negs.mask] = 0.
#the thickness of the Galactic plane is function of the Galactic Radius roughly as ~ 100 pc *cosh((x/R0) ), with R0~10kpc
# for reference see fig.6 of Heyer and Dame, 2015
sigma_z0 = self.z_distr[0]
R_z0 = self.z_distr[1]
sigma_z = lambda R: sigma_z0 * np.cosh((R / R_z0))
self.zeta = self.phi * 0.
np.random.seed(self.random_seed + 19)
for i, x, p in zip(np.arange(self.n), self.r, self.phi):
self.zeta[i] = np.random.normal(loc=0., scale=sigma_z(x))
self.clouds.append(
Cloud(i, x, p, self.zeta[i], size=None, em=None))
coord_array = coord.CylindricalRepresentation(
self.r * u.kpc, self.phi * u.rad, self.zeta * u.kpc)
self.cartesian_galactocentric = self.cartesianize_coordinates(
coord_array)
self.heliocentric_coordinates()
for c, d, latit, longit in zip(self.clouds, self.d_sun, self.lat,
self.long):
c.assign_sun_coord(d, latit, longit)
self.L = np.array(self.sizes)
self.healpix_vecs = self.compute_healpix_vec()
self.W = self.get_pop_emissivities_sizes()[0]
def test__fix_branch_cuts(self):
"""Test method ``_fix_branch_cuts``.
.. todo::
graphical proof via mpl_test that the point hasn't moved.
"""
# -------------------------------
# no angular units
rep = coord.CartesianRepresentation(
x=[1, 2] * u.kpc,
y=[3, 4] * u.kpc,
z=[5, 6] * u.kpc,
)
array = rep._values.view(dtype=np.float64).reshape(rep.shape[0], -1).T
got = self.inst._fix_branch_cuts(array, rep.__class__, rep._units)
assert got is array
# -------------------------------
# UnitSphericalRepresentation
# 1) all good
rep = coord.UnitSphericalRepresentation(
lon=[1, 2] * u.deg,
lat=[3, 4] * u.deg,
)
array = rep._values.view(dtype=np.float64).reshape(rep.shape[0], -1).T
got = self.inst._fix_branch_cuts(
array.copy(),
rep.__class__,
rep._units,
)
assert np.allclose(got, array)
# 2) needs correction
array = np.array([[-360, 0, 360], [-91, 0, 91]])
got = self.inst._fix_branch_cuts(
array.copy(),
rep.__class__,
rep._units,
)
assert np.allclose(got, np.array([[-180, 0, 540], [-89, 0, 89]]))
# -------------------------------
# SphericalRepresentation
# 1) all good
rep = coord.SphericalRepresentation(
lon=[1, 2] * u.deg,
lat=[3, 4] * u.deg,
distance=[5, 6] * u.kpc,
)
array = rep._values.view(dtype=np.float64).reshape(rep.shape[0], -1).T
got = self.inst._fix_branch_cuts(
array.copy(),
rep.__class__,
rep._units,
)
assert np.allclose(got, array)
# 2) needs correction
array = np.array([[-360, 0, 360], [-91, 0, 91], [5, 6, 7]])
got = self.inst._fix_branch_cuts(
array.copy(),
rep.__class__,
rep._units,
)
assert np.allclose(
got,
np.array([[-180, 0, 540], [-89, 0, 89], [5, 6, 7]]),
)
# 3) needs correction
array = np.array([[-360, 0, 360], [-91, 0, 91], [-5, 6, -7]])
got = self.inst._fix_branch_cuts(
array.copy(),
rep.__class__,
rep._units,
)
assert np.allclose(
got,
np.array([[0, 0, 720], [89, 0, -89], [5, 6, 7]]),
)
# -------------------------------
# CylindricalRepresentation
# 1) all good
rep = coord.CylindricalRepresentation(
rho=[5, 6] * u.kpc,
phi=[1, 2] * u.deg,
z=[3, 4] * u.parsec,
)
array = rep._values.view(dtype=np.float64).reshape(rep.shape[0], -1).T
got = self.inst._fix_branch_cuts(
array.copy(),
rep.__class__,
rep._units,
)
assert np.allclose(got, array)
# 2) needs correction
array = np.array([[-5, 6, -7], [-180, 0, 180], [-4, 4, 4]])
got = self.inst._fix_branch_cuts(
array.copy(),
rep.__class__,
rep._units,
)
assert np.allclose(got, np.array([[5, 6, 7], [0, 0, 360], [-4, 4, 4]]))
# -------------------------------
# NotImplementedError
with pytest.raises(NotImplementedError):
rep = coord.PhysicsSphericalRepresentation(
phi=[1, 2] * u.deg,
theta=[3, 4] * u.deg,
r=[5, 6] * u.kpc,
)
array = (rep._values.view(dtype=np.float64).reshape(
rep.shape[0], -1).T)
self.inst._fix_branch_cuts(
array.copy(),
coord.PhysicsSphericalRepresentation,
rep._units,
)
