def radial_density(r, mass, N=100, dim=3):
""" Took this from amuse.ext.radial_profile and changed it so that
it returns a VectorQuantity."""
if dim == 3:
volfac = numpy.pi * 4. / 3.
elif dim == 2:
volfac = numpy.pi
else:
volfac = 1
n = len(r)
a = r.argsort()
i = 0
r_a = []
dens = []
oldrshell = 0. * r[0]
while i != n - 1:
i1 = i + N
if (n - i1 < N): i1 = n - 1
rshell = (r[a[i1]] + r[a[i1 - 1]]) / 2
ra = r[a[i:i1]].sum() / (i1 - i) / 2 + (oldrshell + rshell) / 4
da = mass[a[i:i1]].sum() / (rshell**dim - oldrshell**dim)
oldrshell = rshell
r_a.append(ra)
dens.append(da)
i = i1
radii = numpy.array(r_a)
densities = numpy.array(dens) / volfac
radii_vq = VectorQuantity.new_from_scalar_quantities(*radii)
densities_vq = VectorQuantity.new_from_scalar_quantities(*densities)
return (radii_vq, densities_vq)
def radial_density(r,mass,N=100,dim=3):
""" Took this from amuse.ext.radial_profile and changed it so that
it returns a VectorQuantity."""
if dim==3:
volfac=numpy.pi*4./3.
elif dim==2:
volfac=numpy.pi
else:
volfac=1
n=len(r)
a=r.argsort()
i=0
r_a=[]
dens=[]
oldrshell=0.*r[0]
while i != n-1:
i1=i+N
if( n-i1 < N ): i1=n-1
rshell=(r[a[i1]]+r[a[i1-1]])/2
ra=r[a[i:i1]].sum()/(i1-i)/2+(oldrshell+rshell)/4
da=mass[a[i:i1]].sum()/(rshell**dim-oldrshell**dim)
oldrshell=rshell
r_a.append(ra)
dens.append(da)
i=i1
radii = numpy.array(r_a)
densities = numpy.array(dens)/volfac
radii_vq = VectorQuantity.new_from_scalar_quantities(*radii)
densities_vq = VectorQuantity.new_from_scalar_quantities(*densities)
return (radii_vq, densities_vq)
def tidal_tensor(t, x, y, z, galaxy):
Fxx, Fyx, Fzx, Fxy, Fyy, Fzy, Fxz, Fyz, Fzz = galaxy.get_tidal_tensor(
t, x, y, z)
return VectorQuantity.new_from_scalar_quantities(
Fxx, Fyx, Fzx,
Fxy, Fyy, Fzy,
Fxz, Fyz, Fzz)
def _get_array_of_positions_from_arguments(axes_names, **kwargs):
if kwargs.get('pos',None):
return kwargs['pos']
if kwargs.get('position',None):
return kwargs['position']
coordinates=[kwargs[x] for x in axes_names]
if numpy.ndim(coordinates[0])==0:
return VectorQuantity.new_from_scalar_quantities(*coordinates)
return column_stack(coordinates)
def _get_array_of_positions_from_arguments(axes_names, **kwargs):
if kwargs.get('pos',None):
return kwargs['pos']
if kwargs.get('position',None):
return kwargs['position']
coordinates=[kwargs[x] for x in axes_names]
ndim=numpy.ndim(coordinates[0])
if ndim==0:
return VectorQuantity.new_from_scalar_quantities(*coordinates)
result=stack(coordinates)
order=tuple(range(1,ndim+1))+(0,)
return result.transpose(order)
def densitycentre_coreradius_coredens(particles,
unit_converter=None,
number_of_neighbours=7,
reuse_hop=False,
hop=HopContainer()):
"""
calculate position of the density centre, coreradius and coredensity
>>> import numpy
>>> from amuse.ic.plummer import new_plummer_sphere
>>> numpy.random.seed(1234)
>>> particles=new_plummer_sphere(100)
>>> pos,coreradius,coredens=particles.densitycentre_coreradius_coredens()
>>> print coreradius
0.404120092331 length
"""
if isinstance(hop, HopContainer):
hop.initialize(unit_converter)
hop = hop.code
try:
hop.particles.add_particles(particles)
except Exception as ex:
hop.stop()
raise exceptions.AmuseException(
str(ex) + " (note: check whether Hop needs a converter here)")
hop.parameters.density_method = 2
hop.parameters.number_of_neighbors_for_local_density = number_of_neighbours
hop.calculate_densities()
density = hop.particles.density
x = hop.particles.x
y = hop.particles.y
z = hop.particles.z
rho = density.amax()
total_density = numpy.sum(density)
x_core = numpy.sum(density * x) / total_density
y_core = numpy.sum(density * y) / total_density
z_core = numpy.sum(density * z) / total_density
rc = (density * ((x - x_core)**2 + (y - y_core)**2 +
(z - z_core)**2).sqrt()).sum() / total_density
if not reuse_hop:
hop.stop()
return VectorQuantity.new_from_scalar_quantities(x_core, y_core,
z_core), rc, rho
def densitycentre_coreradius_coredens(
particles, unit_converter=None, number_of_neighbours=7, reuse_hop=False, hop=HopContainer()
):
"""
calculate position of the density centre, coreradius and coredensity
>>> import numpy
>>> from amuse.ic.plummer import new_plummer_sphere
>>> numpy.random.seed(1234)
>>> particles=new_plummer_sphere(100)
>>> pos,coreradius,coredens=particles.densitycentre_coreradius_coredens()
>>> print coreradius
0.404120092331 length
"""
if isinstance(hop, HopContainer):
hop.initialize(unit_converter)
hop = hop.code
hop.particles.add_particles(particles)
hop.parameters.density_method = 2
hop.parameters.number_of_neighbors_for_local_density = number_of_neighbours
hop.calculate_densities()
density = hop.particles.density
x = hop.particles.x
y = hop.particles.y
z = hop.particles.z
rho = density.amax()
total_density = numpy.sum(density)
x_core = numpy.sum(density * x) / total_density
y_core = numpy.sum(density * y) / total_density
z_core = numpy.sum(density * z) / total_density
rc = (density * ((x - x_core) ** 2 + (y - y_core) ** 2 + (z - z_core) ** 2).sqrt()).sum() / total_density
if not reuse_hop:
hop.stop()
return VectorQuantity.new_from_scalar_quantities(x_core, y_core, z_core), rc, rho
def eigen_values(t, x, y, z, galaxy):
l1, l2, l3 = galaxy.get_eigen_values(t, x, y, z)
return VectorQuantity.new_from_scalar_quantities(l1, l2, l3)
x = hop.particles.x
y = hop.particles.y
z = hop.particles.z
rho = density.amax()
total_density = numpy.sum(density)
x_core = numpy.sum(density * x) / total_density
y_core = numpy.sum(density * y) / total_density
z_core = numpy.sum(density * z) / total_density
rc = (density * ((x - x_core)**2 + (y - y_core)**2 +
(z - z_core)**2).sqrt()).sum() / total_density
if not reuse_hop:
hop.stop()
return VectorQuantity.new_from_scalar_quantities(x_core, y_core,
z_core), rc, rho
def new_particle_from_cluster_core(particles,
unit_converter=None,
density_weighting_power=2,
cm=None,
reuse_hop=False,
hop=HopContainer()):
"""
Uses Hop to find the density centre (core) of a particle distribution
and stores the properties of this core on a particle:
position, velocity, (core) radius and (core) density.
Particles are assigned weights that depend on the density (as determined by
Hop) to a certain power.
def eigen_values(t, x, y, z, galaxy):
l1, l2, l3 = galaxy.get_eigen_values(t, x, y, z)
return VectorQuantity.new_from_scalar_quantities(l1, l2, l3)
def tidal_tensor(t, x, y, z, galaxy):
Fxx, Fyx, Fzx, Fxy, Fyy, Fzy, Fxz, Fyz, Fzz = galaxy.get_tidal_tensor(
t, x, y, z)
return VectorQuantity.new_from_scalar_quantities(Fxx, Fyx, Fzx, Fxy, Fyy,
Fzy, Fxz, Fyz, Fzz)
