class ArrAtLast:
x = uttr.ib(unit=u.kpc)
y = uttr.ib(unit=u.kpc)
z = uttr.ib(init=False, unit=u.kpc)
arr_ = uttr.array_accessor()
@z.default
def _z_default(self):
return self.arr_.x * self.arr_.y
def test_dimensionless_access(self, make_cls):
Cls = make_cls(foo=uttr.ib(unit=u.kg), arr_=uttr.array_accessor())
instance = Cls(foo=1)
assert instance.foo == 1 * u.kg
assert instance.arr_.foo == 1
assert instance.arr_["foo"] == 1
def test_equivalent_access(self, make_cls):
Cls = make_cls(foo=uttr.ib(unit=u.kg), arr_=uttr.array_accessor())
instance = Cls(foo=1 * u.g)
assert instance.foo == 1 * u.g
assert instance.arr_.foo == 0.001
assert instance.arr_["foo"] == 0.001
def test_same_unit_access(self, make_cls):
Cls = make_cls(foo=uttr.ib(unit=u.kg))
instance = Cls(foo=1 * u.kg)
arr_ = uttr.ArrayAccessor(instance)
assert instance.foo == 1 * u.kg
assert arr_.foo == 1
assert arr_["foo"] == 1
def test_dir(self, make_cls):
Cls = make_cls(foo=uttr.ib(unit=u.kg))
instance = Cls(foo=1 * u.kg)
arr_ = uttr.ArrayAccessor(instance)
dir_arr = dir(arr_)
expected = super(uttr.ArrayAccessor, arr_).__dir__() + ["foo"]
assert set(dir_arr) == set(expected)
def test_metadata(self, make_cls):
Cls = make_cls(foo=uttr.ib(unit=u.kg))
attribute = attr.fields(Cls).foo
assert uttr.UTTR_METADATA in attribute.metadata
ucav = attribute.metadata[uttr.UTTR_METADATA]
assert isinstance(ucav, uttr.UnitConverterAndValidator)
assert ucav.unit is u.kg
def test_validator(self, make_cls):
with mock.patch(
"uttr.UnitConverterAndValidator.validate_is_equivalent_unit"
) as validator:
Cls = make_cls(foo=uttr.ib(unit=u.kg))
attribute = attr.fields(Cls).foo
validator.assert_not_called()
instance = Cls(foo=1)
validator.assert_called_once_with(instance, attribute, 1 * u.kg)
def test_converter(self, make_cls):
with mock.patch(
"uttr.UnitConverterAndValidator.convert_if_dimensionless"
) as asunit:
Cls = make_cls(foo=uttr.ib(unit=u.kg))
# check the converter
asunit.assert_not_called()
Cls(foo="foo")
asunit.assert_called_once_with("foo")
def test_attrs_quantity(self, make_cls):
Cls = make_cls(foo=uttr.ib(unit=u.kg), faa=attr.ib())
instance = Cls(foo=1 * u.kg, faa=1 * u.kg)
arr_ = uttr.ArrayAccessor(instance)
assert instance.foo == 1 * u.kg
assert arr_.foo == 1
assert instance.faa == 1 * u.kg
with pytest.raises(AttributeError):
arr_.faa
def test_no_uttr_quantity(self, make_cls):
Cls = make_cls(foo=uttr.ib(unit=u.kg))
instance = Cls(foo=1 * u.kg)
instance.faa = 1 * u.kpc
arr_ = uttr.ArrayAccessor(instance)
assert instance.faa == 1 * u.kpc
with pytest.raises(AttributeError):
assert arr_.faa
with pytest.raises(KeyError):
assert arr_["faa"]
class Foo:
a = uttr.ib(default=None, unit=u.Msun)
arr_ = uttr.array_accessor()
class Foo:
fatt = uttr.ib(unit=u.K)
arr_ = "foo"
class Foo:
fatt = uttr.ib(unit=u.K)
def test_auto_conversion(self, make_cls):
Cls = make_cls(foo=uttr.ib(unit=u.kg))
instance = Cls(foo=1)
assert instance.foo == 1 * u.kg
def test_equivalent_unit(self, make_cls):
Cls = make_cls(foo=uttr.ib(unit=u.kg))
instance = Cls(foo=1 * u.g)
assert instance.foo == 1 * u.g
def test_invalid_unit(self, make_cls):
Cls = make_cls(foo=uttr.ib(unit=u.kg))
with pytest.raises(ValueError):
Cls(foo=1 * u.m)
def test_unit_None(self, make_cls):
Cls = make_cls(foo=uttr.ib(unit=None), faa=uttr.ib(unit=u.kg))
fields = attr.fields_dict(Cls)
assert uttr.UTTR_METADATA not in fields["foo"].metadata
assert uttr.UTTR_METADATA in fields["faa"].metadata
class Foo:
x = uttr.ib(unit=u.kpc)
y = uttr.ib(unit=u.kpc)
z = attr.ib()
arr_ = uttr.array_accessor()
def test_repr(self, make_cls):
Cls = make_cls(foo=uttr.ib(unit=u.kg))
instance = Cls(foo=1 * u.kg)
arr_ = uttr.ArrayAccessor(instance)
assert repr(arr_) == f"ArrayAccessor({repr(instance)})"
class Galaxy:
"""
Galaxy class.
Builds a galaxy object from masses, positions, and
velocities of particles (stars, dark matter and gas).
Parameters
----------
m_s : `Quantity`
Star masses. Shape: (n_s,1). Default unit: M_sun
x_s, y_s, z_s : `Quantity`
Star positions. Shape: (n_s,1). Default unit: kpc.
vx_s, vy_s, vz_s : `Quantity`
Star velocities. Shape: (n_s,1). Default unit: km/s.
m_dm : `Quantity`
Dark matter masses. Shape: (n_dm,1). Default unit: M_sun
x_dm, y_dm, z_dm : `Quantity`
Dark matter positions. Shape: (n_dm,1). Default unit: kpc.
vx_dm, vy_dm, vz_dm : `Quantity`
Dark matter velocities. Shape: (n_dm,1). Default unit: km/s.
m_g : `Quantity`
Gas masses. Shape: (n_g,1). Default unit: M_sun
x_g, y_g, z_g : `Quantity`
Gas positions. Shape: (n_g,1). Default unit: kpc.
vx_g, vy_g, vz_g : `Quantity`
Gas velocities. Shape: (n_g,1). Default unit: km/s.
pot_s : `Quantity`, default value = 0
Specific potential energy of star particles.
Shape: (n_s,1). Default unit: (km/s)**2.
pot_dm : `Quantity`, default value = 0
Specific potential energy of dark matter particles.
Shape: (n_dm,1). Default unit: (km/s)**2.
pot_g : `Quantity`, default value = 0
Specific potential energy of gas particles.
Shape: (n_g,1). Default unit: (km/s)**2.
eps_s : `Quantity`, default value = 0
Softening radius of star particles. Shape: (1,). Default unit: kpc.
eps_dm : `Quantity`, default value = 0
Softening radius of dark matter particles.
Shape: (1,). Default unit: kpc.
eps_g : `Quantity`, default value = 0
Softening radius of gas particles. Shape: (1,). Default unit: kpc.
J_part : `Quantity`
Total specific angular momentum of all particles (stars, dark matter
and gas).
Shape: (n,3). Default units: kpc*km/s
J_star : `Quantity`
Total specific angular momentum of stars.
Shape: (n_s,1). Default unit: kpc*km/s
Jr_part : `Quantity`
Projection of the total specific angular momentum in the xy plane for
all particles.
Shape: (n,1). Default unit: kpc*km/s
Jr_star : `Quantity`
Projection of the specific angular momentum of stars in the xy plane.
Shape: (n_s,1). Default unit: kpc*km/s
x : `Quantity`
Normalized specific energy for the particle with the maximum
z-component of the normalized specific angular momentum per bin.
Default unit: dimensionless
y : `Quantity`
Maximum value of the z-component of the normalized specific angular
momentum per bin.
Default units: dimensionless
Attributes
----------
arr_: `uttr.ArrayAccessor`
Original array accessor object create by the *uttr* library.
Array accesor: it converts uttr attributes to the default unit and
afterward to a `numpy.ndarray`.
For more information see: https://pypi.org/project/uttrs/
"""
m_s = uttr.ib(unit=u.Msun)
x_s = uttr.ib(unit=u.kpc)
y_s = uttr.ib(unit=u.kpc)
z_s = uttr.ib(unit=u.kpc)
vx_s = uttr.ib(unit=(u.km / u.s))
vy_s = uttr.ib(unit=(u.km / u.s))
vz_s = uttr.ib(unit=(u.km / u.s))
m_dm = uttr.ib(unit=u.Msun)
x_dm = uttr.ib(unit=u.kpc)
y_dm = uttr.ib(unit=u.kpc)
z_dm = uttr.ib(unit=u.kpc)
vx_dm = uttr.ib(unit=(u.km / u.s))
vy_dm = uttr.ib(unit=(u.km / u.s))
vz_dm = uttr.ib(unit=(u.km / u.s))
m_g = uttr.ib(unit=u.Msun)
x_g = uttr.ib(unit=u.kpc)
y_g = uttr.ib(unit=u.kpc)
z_g = uttr.ib(unit=u.kpc)
vx_g = uttr.ib(unit=(u.km / u.s))
vy_g = uttr.ib(unit=(u.km / u.s))
vz_g = uttr.ib(unit=(u.km / u.s))
pot_s = uttr.ib(default=np.zeros(1), unit=(u.km / u.s) ** 2)
pot_dm = uttr.ib(default=np.zeros(1), unit=(u.km / u.s) ** 2)
pot_g = uttr.ib(default=np.zeros(1), unit=(u.km / u.s) ** 2)
eps_s = uttr.ib(default=0.0, unit=u.kpc)
eps_dm = uttr.ib(default=0.0, unit=u.kpc)
eps_g = uttr.ib(default=0.0, unit=u.kpc)
J_part = uttr.ib(default=None, unit=(u.kpc * u.km / u.s))
J_star = uttr.ib(default=None, unit=(u.kpc * u.km / u.s))
Jr_part = uttr.ib(default=None, unit=(u.kpc * u.km / u.s))
Jr_star = uttr.ib(default=None, unit=(u.kpc * u.km / u.s))
x = uttr.ib(default=None, unit=u.dimensionless_unscaled)
y = uttr.ib(default=None, unit=u.dimensionless_unscaled)
arr_ = uttr.array_accessor()
# components_s = attr.ib(default=None)
# components_g = attr.ib(default=None)
# metadata = attr.ib(default=None)
def __attrs_post_init__(self):
"""
Validate attrs with units.
Units length validator.
This method determines that the length of the different particles
families are the same.
Potential energy input validator.
This method determines the validation of input of the specific
potential energy.
"""
if np.all(self.arr_.pot_s) != 0.0:
length_s = np.array(
[
len(self.arr_.x_s),
len(self.arr_.y_s),
len(self.arr_.z_s),
len(self.arr_.vx_s),
len(self.arr_.vy_s),
len(self.arr_.vz_s),
len(self.arr_.pot_s),
]
)
else:
length_s = np.array(
[
len(self.arr_.x_s),
len(self.arr_.y_s),
len(self.arr_.z_s),
len(self.arr_.vx_s),
len(self.arr_.vy_s),
len(self.arr_.vz_s),
]
)
if np.any(len(self.arr_.m_s) != length_s):
raise ValueError("Stars inputs must have the same length")
if np.all(self.arr_.pot_dm) != 0.0:
length_dm = np.array(
[
len(self.arr_.x_dm),
len(self.arr_.y_dm),
len(self.arr_.z_dm),
len(self.arr_.vx_dm),
len(self.arr_.vy_dm),
len(self.arr_.vz_dm),
len(self.arr_.pot_dm),
]
)
else:
length_dm = np.array(
[
len(self.arr_.x_dm),
len(self.arr_.y_dm),
len(self.arr_.z_dm),
len(self.arr_.vx_dm),
len(self.arr_.vy_dm),
len(self.arr_.vz_dm),
]
)
if np.any(len(self.arr_.m_dm) != length_dm):
raise ValueError("Dark matter inputs must have the same length")
if np.all(self.arr_.pot_g) != 0.0:
length_g = np.array(
[
len(self.arr_.x_g),
len(self.arr_.y_g),
len(self.arr_.z_g),
len(self.arr_.vx_g),
len(self.arr_.vy_g),
len(self.arr_.vz_g),
len(self.arr_.pot_g),
]
)
else:
length_g = np.array(
[
len(self.arr_.x_g),
len(self.arr_.y_g),
len(self.arr_.z_g),
len(self.arr_.vx_g),
len(self.arr_.vy_g),
len(self.arr_.vz_g),
]
)
if np.any(len(self.arr_.m_g) != length_g):
raise ValueError("Gas inputs must have the same length")
# Potential energy input validator.
if np.any(self.arr_.pot_s != 0.0) and (
np.all(self.arr_.pot_dm == 0.0) or np.all(self.arr_.pot_g == 0.0)
):
raise ValueError(
"Potential energy must be instanced for all type particles"
)
if np.any(self.arr_.pot_dm != 0.0) and (
np.all(self.arr_.pot_s == 0.0) or np.all(self.arr_.pot_g == 0.0)
):
raise ValueError(
"Potential energy must be instanced for all type particles"
)
if np.any(self.arr_.pot_g != 0.0) and (
np.all(self.arr_.pot_s == 0.0) or np.all(self.arr_.pot_dm == 0.0)
):
raise ValueError(
"Potential energy must be instanced for all type particles"
)
@property
def kinetic_energy(self):
"""
Specific kinetic energy calculation.
Calculates the specific kinetic energy
of stars, dark matter and gas particles.
Returns
-------
tuple : `Quantity`
(k_s, k_dm, k_g): Specific kinetic energy of stars, dark matter and
gas respectively. Shape(n_s, n_dm, n_g). Unit: (km/s)**2
Examples
--------
This returns the specific kinetic energy of stars, dark matter and gas
particles respectively.
>>> import galaxychop as gc
>>> galaxy = gc.Galaxy(...)
>>> k_s, k_dm, k_g = galaxy.kinetic_energy
"""
vx_s = self.arr_.vx_s
vy_s = self.arr_.vy_s
vz_s = self.arr_.vz_s
vx_dm = self.arr_.vx_dm
vy_dm = self.arr_.vy_dm
vz_dm = self.arr_.vz_dm
vx_g = self.arr_.vx_g
vy_g = self.arr_.vy_g
vz_g = self.arr_.vz_g
k_s = 0.5 * (vx_s ** 2 + vy_s ** 2 + vz_s ** 2)
k_dm = 0.5 * (vx_dm ** 2 + vy_dm ** 2 + vz_dm ** 2)
k_g = 0.5 * (vx_g ** 2 + vy_g ** 2 + vz_g ** 2)
k_s = k_s * (u.km / u.s) ** 2
k_dm = k_dm * (u.km / u.s) ** 2
k_g = k_g * (u.km / u.s) ** 2
return (k_s, k_dm, k_g)
def potential_energy(self):
"""
Specific potential energy calculation.
Calculates the specific potencial energy
of dark matter, star and gas particles.
Returns
-------
gx : `galaxy object`
New instanced galaxy specific potencial energy calculated for
stars, dark matter and gas particles.
Examples
--------
This returns the specific potential energy of stars, dark matter and
gas particles.
>>> import galaxychop as gc
>>> galaxy = gc.Galaxy(...)
>>> gpot = galaxy.potential_energy()
>>> pot_s, pot_dm, pot_g = gpot.pot_s, gpot.pot_dm, gpot.pot_g
Note
----
If the potentials are entered when the `galaxy` object is instanced,
then, the calculation of `potential_energy` will raise a `ValueError`.
"""
m_s = self.arr_.m_s
x_s = self.arr_.x_s
y_s = self.arr_.y_s
z_s = self.arr_.z_s
m_dm = self.arr_.m_dm
x_dm = self.arr_.x_dm
y_dm = self.arr_.y_dm
z_dm = self.arr_.z_dm
m_g = self.arr_.m_g
x_g = self.arr_.x_g
y_g = self.arr_.y_g
z_g = self.arr_.z_g
pot_s = self.arr_.pot_s
pot_dm = self.arr_.pot_dm
pot_g = self.arr_.pot_g
pot_s = self.arr_.pot_s
pot_dm = self.arr_.pot_dm
pot_g = self.arr_.pot_g
eps_s = self.arr_.eps_s
eps_dm = self.arr_.eps_dm
eps_g = self.arr_.eps_g
potential = np.concatenate([pot_s, pot_dm, pot_g])
if np.all(potential == 0.0):
x = np.hstack((x_s, x_dm, x_g))
y = np.hstack((y_s, y_dm, y_g))
z = np.hstack((z_s, z_dm, z_g))
m = np.hstack((m_s, m_dm, m_g))
eps = np.max([eps_s, eps_dm, eps_g])
pot = utils.potential(
da.asarray(x, chunks=100),
da.asarray(y, chunks=100),
da.asarray(z, chunks=100),
da.asarray(m, chunks=100),
da.asarray(eps),
)
num_s = len(m_s)
num = len(m_s) + len(m_dm)
pot_s = pot[:num_s]
pot_dm = pot[num_s:num]
pot_g = pot[num:]
new = attr.asdict(self, recurse=False)
del new["arr_"]
new.update(
pot_s=-pot_s * (u.km / u.s) ** 2,
pot_dm=-pot_dm * (u.km / u.s) ** 2,
pot_g=-pot_g * (u.km / u.s) ** 2,
)
return Galaxy(**new)
else:
raise ValueError("Potentials are already calculated")
@property
def energy(self):
"""
Specific energy calculation.
Calculates the specific energy of dark matter, star and gas particles.
Returns
-------
tuple : `Quantity`
(Etot_s, Etot_dm, Etot_g): Specific total energy of stars, dark
matter and gas respectively.
Shape(n_s, n_dm, n_g). Unit: (km/s)**2
Examples
--------
This returns the specific total energy of stars, dark matter and gas
particles respectively.
>>> import galaxychop as gc
>>> galaxy = gc.Galaxy(...)
>>> E_s, E_dm, E_g = galaxy.energy
"""
potential = np.concatenate(
[
self.arr_.pot_s,
self.arr_.pot_dm,
self.arr_.pot_s,
]
)
k_s = self.kinetic_energy[0].value
k_dm = self.kinetic_energy[1].value
k_g = self.kinetic_energy[2].value
if np.all(potential == 0.0):
pot_s = self.potential_energy().arr_.pot_s
pot_dm = self.potential_energy().arr_.pot_dm
pot_g = self.potential_energy().arr_.pot_g
else:
pot_s = self.arr_.pot_s
pot_dm = self.arr_.pot_dm
pot_g = self.arr_.pot_g
Etot_s = (k_s + pot_s) * (u.km / u.s) ** 2
Etot_dm = (k_dm + pot_dm) * (u.km / u.s) ** 2
Etot_g = (k_g + pot_g) * (u.km / u.s) ** 2
return (Etot_s, Etot_dm, Etot_g)
def angular_momentum(self, r_cut=None):
"""
Specific angular momentum.
Centers the particles with respect to the one with the lower specific
potential, then, calculates the specific angular momentum of
dark matter, stars and gas particles.
Parameters
----------
r_cut : `float`, optional
The default is ``None``; if provided, it must be
positive and the rotation matrix `A` is calculated
from the particles with radii smaller than r_cut.
Returns
-------
gx : `galaxy object`
New instanced galaxy with all particles centered respect to the
lowest specific energy one and the addition of J_part, J_star,
Jr_part and Jr_star.
Examples
--------
This returns the specific potential energy of stars, dark matter and
gas particles.
>>> import galaxychop as gc
>>> galaxy = gc.Galaxy(...)
>>> g_J = galaxy.angular_momentum()
>>> J_part, J_star= g_J.J_part, g_J.J_star
>>> Jr_part, Jr_star = g_J.Jr_part, g_J.Jr_star
"""
m_s = self.arr_.m_s
x_s = self.arr_.x_s
y_s = self.arr_.y_s
z_s = self.arr_.z_s
vx_s = self.arr_.vx_s
vy_s = self.arr_.vy_s
vz_s = self.arr_.vz_s
m_dm = self.arr_.m_dm
x_dm = self.arr_.x_dm
y_dm = self.arr_.y_dm
z_dm = self.arr_.z_dm
vx_dm = self.arr_.vx_dm
vy_dm = self.arr_.vy_dm
vz_dm = self.arr_.vz_dm
m_g = self.arr_.m_g
x_g = self.arr_.x_g
y_g = self.arr_.y_g
z_g = self.arr_.z_g
vx_g = self.arr_.vx_g
vy_g = self.arr_.vy_g
vz_g = self.arr_.vz_g
pot_s = self.arr_.pot_s
pot_dm = self.arr_.pot_dm
pot_g = self.arr_.pot_g
xs, ys, zs, xdm, ydm, zdm, xg, yg, zg = utils.center(
m_s,
x_s,
y_s,
z_s,
m_dm,
x_dm,
y_dm,
z_dm,
m_g,
x_g,
y_g,
z_g,
pot_s,
pot_dm,
pot_g,
)
(
pos_rot_s_x,
pos_rot_s_y,
pos_rot_s_z,
vel_rot_s_x,
vel_rot_s_y,
vel_rot_s_z,
pos_rot_dm_x,
pos_rot_dm_y,
pos_rot_dm_z,
vel_rot_dm_x,
vel_rot_dm_y,
vel_rot_dm_z,
pos_rot_g_x,
pos_rot_g_y,
pos_rot_g_z,
vel_rot_g_x,
vel_rot_g_y,
vel_rot_g_z,
) = utils.align(
m_s,
xs,
ys,
zs,
vx_s,
vy_s,
vz_s,
xdm,
ydm,
zdm,
vx_dm,
vy_dm,
vz_dm,
xg,
yg,
zg,
vx_g,
vy_g,
vz_g,
r_cut=r_cut,
)
J_star = np.array(
[
pos_rot_s_y * vel_rot_s_z - pos_rot_s_z * vel_rot_s_y,
pos_rot_s_z * vel_rot_s_x - pos_rot_s_x * vel_rot_s_z,
pos_rot_s_x * vel_rot_s_y - pos_rot_s_y * vel_rot_s_x,
]
)
J_dark = np.array(
[
pos_rot_dm_y * vel_rot_dm_z - pos_rot_dm_z * vel_rot_dm_y,
pos_rot_dm_z * vel_rot_dm_x - pos_rot_dm_x * vel_rot_dm_z,
pos_rot_dm_x * vel_rot_dm_y - pos_rot_dm_y * vel_rot_dm_x,
]
)
J_gas = np.array(
[
pos_rot_g_y * vel_rot_g_z - pos_rot_g_z * vel_rot_g_y,
pos_rot_g_z * vel_rot_g_x - pos_rot_g_x * vel_rot_g_z,
pos_rot_g_x * vel_rot_g_y - pos_rot_g_y * vel_rot_g_x,
]
)
J_part = np.concatenate([J_gas, J_dark, J_star], axis=1)
Jr_star = np.sqrt(J_star[0, :] ** 2 + J_star[1, :] ** 2)
Jr_part = np.sqrt(J_part[0, :] ** 2 + J_part[1, :] ** 2)
new = attr.asdict(self, recurse=False)
del new["arr_"]
new.update(
J_part=J_part * u.kpc * u.km / u.s,
J_star=J_star * u.kpc * u.km / u.s,
Jr_part=Jr_part * u.kpc * u.km / u.s,
Jr_star=Jr_star * u.kpc * u.km / u.s,
)
return Galaxy(**new)
def jcirc(self, bin0=0.05, bin1=0.005):
"""
Circular angular momentum.
Calculation of the points to build the function of the circular
angular momentum.
Parameters
----------
bin0 : `float`. Default=0.05
Size of the specific energy bin of the inner part of the galaxy,
in the range of (-1, -0.1) of the normalized energy.
bin1 : `float`. Default=0.005
Size of the specific energy bin of the outer part of the galaxy,
in the range of (-0.1, 0) of the normalized energy.
Returns
-------
gx : `galaxy object`
New instanced galaxy with `x`, being the normalized specific
energy for the particle with the maximum z-specific angular
momentum component per the bin, and `y` beign the maximum of
z-specific angular momentum component.
See section Notes for more details.
Notes
-----
The `x` and `y` are calculated from the binning in the
normalized specific energy. In each bin, the particle with the
maximum value of z-component of standardized specific angular
momentum is selected. This value is assigned to the `y` parameter
and its corresponding normalized specific energy pair value to
`x`.
Examples
--------
This returns the normalized specific energy for the particle with
the maximum z-component of the normalized specific angular momentum
per bin (`x`) and the maximum value of the z-component of the
normalized specific angular momentum per bin (`y`)
>>> import galaxychop as gc
>>> galaxy = gc.Galaxy(...)
>>> g_Jcirc = galaxy.jcirc()
>>> x, y = g_Jcirc.x, g_Jcirc.y
"""
Etot_s = self.energy[0].value
Etot_dm = self.energy[1].value
Etot_g = self.energy[2].value
E_tot = np.hstack([Etot_s, Etot_dm, Etot_g])
# Remove the particles that are not bound: E > 0.
(neg,) = np.where(E_tot <= 0.0)
(neg_star,) = np.where(Etot_s <= 0.0)
# Remove the particles with E = -inf.
(fin,) = np.where(E_tot[neg] != -np.inf)
(fin_star,) = np.where(Etot_s[neg_star] != -np.inf)
# Normalize the two variables: E between 0 and 1; Jz between -1 and 1.
E = E_tot[neg][fin] / np.abs(np.min(E_tot[neg][fin]))
kk = self.angular_momentum().arr_.J_part[2, :][neg][fin]
Jz = kk / np.max(np.abs(kk))
# Build the specific energy binning and select the Jz values to
# calculate J_circ.
aux0 = np.arange(-1.0, -0.1, bin0)
aux1 = np.arange(-0.1, 0.0, bin1)
aux = np.concatenate([aux0, aux1], axis=0)
x = np.zeros(len(aux) + 1)
y = np.zeros(len(aux) + 1)
x[0] = -1.0
y[0] = np.abs(Jz[np.argmin(E)])
for i in range(1, len(aux)):
(mask,) = np.where((E <= aux[i]) & (E > aux[i - 1]))
s = np.argsort(np.abs(Jz[mask]))
# We take into account whether or not there are particles in the
# specific energy bins.
if len(s) != 0:
if len(s) == 1:
x[i] = E[mask][s]
y[i] = np.abs(Jz[mask][s])
else:
if (
1.0
- (np.abs(Jz[mask][s][-2]) / np.abs(Jz[mask][s][-1]))
) >= 0.01:
x[i] = E[mask][s][-2]
y[i] = np.abs(Jz[mask][s][-2])
else:
x[i] = E[mask][s][-1]
y[i] = np.abs(Jz[mask][s][-1])
else:
pass
# Mask to complete the last bin, in case there are no empty bins.
(mask,) = np.where(E > aux[len(aux) - 1])
if len(mask) != 0:
x[len(aux)] = E[mask][np.abs(Jz[mask]).argmax()]
y[len(aux)] = np.abs(Jz[mask][np.abs(Jz[mask]).argmax()])
# In case there are empty bins, we get rid of them.
else:
i = len(np.where(y == 0)[0]) - 1
if i == 0:
x = x[:-1]
y = y[:-1]
else:
x = x[:-i]
y = y[:-i]
# In case some intermediate bin does not have points.
(zero,) = np.where(x != 0.0)
x = x[zero]
y = y[zero]
new = attr.asdict(self, recurse=False)
del new["arr_"]
new.update(x=u.Quantity(x), y=u.Quantity(y))
return Galaxy(**new)
@property
def paramcirc(self):
"""
Circularity parameter calculation.
Return
------
tuple : `float`
(E_star, eps, eps_r): Normalized specific energy of the stars,
circularity parameter (J_z/J_circ), J_p/J_circ.
Shape(n_s, 1). Unit: dimensionless
Notes
-----
J_z : z-component of normalized specific angular momentum.
J_circ : Specific circular angular momentum.
J_p : Projection on the xy plane of the normalized specific angular
momentum.
Examples
--------
This returns the normalized specific energy of stars (E_star), the
circularity parameter (eps : J_z/J_circ) and
eps_r: (J_p/J_circ).
>>> import galaxychop as gc
>>> galaxy = gc.Galaxy(...)
>>> E_star, eps, eps_r = galaxy.paramcirc
"""
Etot_s = self.energy[0].value
Etot_dm = self.energy[1].value
Etot_g = self.energy[2].value
E_tot = np.hstack([Etot_s, Etot_dm, Etot_g])
E_star_ = np.full(len(Etot_s), np.nan)
eps_ = np.full(len(Etot_s), np.nan)
eps_r_ = np.full(len(Etot_s), np.nan)
# Remove the particles that are not bound: E > 0.
(neg,) = np.where(E_tot <= 0.0)
(neg_star,) = np.where(Etot_s <= 0.0)
# Remove the particles with E = -inf.
(fin,) = np.where(E_tot[neg] != -np.inf)
(fin_star,) = np.where(Etot_s[neg_star] != -np.inf)
# Normalize E, Lz and Lr for the stars.
up1 = Etot_s[neg_star][fin_star]
down1 = np.abs(np.min(E_tot[neg][fin]))
E_star = up1 / down1
ang_momentum = self.angular_momentum().arr_
up2 = ang_momentum.J_star[2, :][neg_star][fin_star]
down2 = np.max(np.abs(ang_momentum.J_part[2, :][neg][fin]))
Jz_star_norm = up2 / down2
up3 = ang_momentum.Jr_star[neg_star][fin_star]
down3 = np.max(np.abs(ang_momentum.Jr_part[neg][fin]))
Jr_star_norm = up3 / down3
# We do the interpolation to calculate the J_circ.
# spl = InterpolatedUnivariateSpline(
# self.jcirc().arr_.x,
# self.jcirc().arr_.y,
# k=1,
# )
# Calculates of the circularity parameter Lz/Lc.
# eps = J_star_ / spl(E_star)
jcir = self.jcirc().arr_
eps = Jz_star_norm / np.interp(E_star, jcir.x, jcir.y)
# Calculates the same for Lp/Lc.
# eps_r = Jr_star_ / spl(E_star)
eps_r = Jr_star_norm / np.interp(E_star, jcir.x, jcir.y)
# We remove particles that have circularity < -1 and circularity > 1.
(mask,) = np.where((eps <= 1.0) & (eps >= -1.0))
E_star_[neg_star[fin_star[mask]]] = E_star[mask]
eps_[neg_star[fin_star[mask]]] = eps[mask]
eps_r_[neg_star[fin_star[mask]]] = eps_r[mask]
return (E_star_, eps_, eps_r_)
def values(self):
"""
2D and 1D inputs converter.
Builds two arrays: one 2D listing all the parameters of each
particle and other 1D showing whether the particle is a star,
gas or dark matter one.
Returns
-------
X : `np.ndarray(n,10)`
2D array where each file it is a diferent stellar particle and
each column is a parameter of the particles:
(m_s, x_s, y_s, z_s, vx_s, vy_s, vz_z, E_s, eps_s, eps_r_s)
y : `np.ndarray(n)`
1D array where is identified the nature of each particle
0=star.
"""
X = np.empty((0, 10))
y = np.empty(0, int)
star = True
if star:
n_s = len(self.paramcirc[1])
X_s = np.hstack(
(
self.arr_.m_s.reshape(n_s, 1),
self.arr_.x_s.reshape(n_s, 1),
self.arr_.y_s.reshape(n_s, 1),
self.arr_.z_s.reshape(n_s, 1),
self.arr_.vx_s.reshape(n_s, 1),
self.arr_.vy_s.reshape(n_s, 1),
self.arr_.vz_s.reshape(n_s, 1),
self.paramcirc[0].reshape(n_s, 1),
self.paramcirc[1].reshape(n_s, 1),
self.paramcirc[2].reshape(n_s, 1),
)
)
y_s = np.zeros(n_s)
X = np.vstack((X, X_s))
y = np.hstack((y, y_s))
return X, y
