def project(snapshot, scale, view, **kwargs):
pps = kwargs.pop('pps', 500)
sm = kwargs.pop('sm', 1.7)
shiftx = kwargs.pop('shiftx', None)
shifty = kwargs.pop('shifty', None)
shiftz = kwargs.pop('shiftz', None)
dens_lim = kwargs.pop('dens_lim', None)
boxsize = float("".join(ch if ch.isdigit() else "" for ch in scale))
unit = "".join(ch if not ch.isdigit() else "" for ch in scale)
dens = snapshot.gas.get_number_density()
xyz = snapshot.gas.get_coords(unit)
uvw = snapshot.gas.get_velocities()
hsml = snapshot.gas.get_smoothing_length(unit)
print 'Calculating...'
xyz = analyze.center_box(xyz, velocity=uvw, density=dens, **kwargs)
xyz = set_view(view, xyz)
x = xyz.x
y = xyz.y
z = xyz.z
if shiftx:
x += shiftx
if shifty:
y += shifty
if shiftz:
z += shiftz
snapshot.update_sink_coordinates(x, y, z)
# Artificially shrink sink smoothing lengths.
for s in snapshot.sinks:
hsml[s.index] *= .5
data = snap.gas['x', 'y', 'z', 'ndensity',
'smoothing_length'].copy(deep=True)
data = trim_view(boxsize, data, **kwargs)
if dens_lim:
arrs = [scalar, x, y, z, hsml]
scalar, x, y, z, hsml = analyze.data_slice(scalar > dens_lim, *arrs)
hsml = numpy.fmax(sm * hsml, boxsize / pps / 2)
xi, yi = build_grid(boxsize, pps)
zi = scalar_map(x, y, scalar, hsml, boxsize, pps, xi.shape)
print '%s:: min: %.3e max: %.3e' % (loadable, zi.min(), zi.max())
imscale = kwargs.pop('imscale', 'log')
if imscale == 'log':
zi = numpy.log10(zi)
print 'log(%s):: min: %.3e max: %.3e' % (loadable, zi.min(), zi.max())
else:
print 'Returning raw (non-log) values!'
return xi, yi, zi
def project(snapshot, scale, view, **kwargs):
pps = kwargs.pop('pps',500)
sm = kwargs.pop('sm',1.7)
shiftx = kwargs.pop('shiftx',None)
shifty = kwargs.pop('shifty',None)
shiftz = kwargs.pop('shiftz',None)
dens_lim = kwargs.pop('dens_lim', None)
boxsize = float("".join(ch if ch.isdigit() else "" for ch in scale))
unit = "".join(ch if not ch.isdigit() else "" for ch in scale)
dens = snapshot.gas.get_number_density()
xyz = snapshot.gas.get_coords(unit)
uvw = snapshot.gas.get_velocities()
hsml = snapshot.gas.get_smoothing_length(unit)
print 'Calculating...'
xyz = analyze.center_box(xyz, velocity=uvw, density=dens, **kwargs)
xyz = set_view(view, xyz)
x = xyz.x
y = xyz.y
z = xyz.z
if shiftx:
x += shiftx
if shifty:
y += shifty
if shiftz:
z += shiftz
snapshot.update_sink_coordinates(x,y,z)
# Artificially shrink sink smoothing lengths.
for s in snapshot.sinks:
hsml[s.index] *= .5
data = snap.gas['x', 'y', 'z', 'ndensity', 'smoothing_length'].copy(deep=True)
data = trim_view(boxsize, data, **kwargs)
if dens_lim:
arrs = [scalar,x,y,z,hsml]
scalar,x,y,z,hsml = analyze.data_slice(scalar > dens_lim, *arrs)
hsml = numpy.fmax(sm * hsml, boxsize/pps/2)
xi,yi = build_grid(boxsize,pps)
zi = scalar_map(x,y,scalar,hsml,boxsize,pps,xi.shape)
print '%s:: min: %.3e max: %.3e' %(loadable, zi.min(),zi.max())
imscale = kwargs.pop('imscale','log')
if imscale == 'log':
zi = numpy.log10(zi)
print 'log(%s):: min: %.3e max: %.3e' %(loadable, zi.min(),zi.max())
else:
print 'Returning raw (non-log) values!'
return xi,yi,zi
def disk_properties(snapshot, sink_id, **kwargs):
r_start = kwargs.pop('r_start', 50*1.49597871e13)
r_step = kwargs.pop('r_step', 1.49597871e14)
r_multiplier = kwargs.pop('multiplier', 1.2)
verbose = kwargs.pop('verbose', True)
n_min = kwargs.pop('n_min', 32)
dens_lim = kwargs.pop('dens_lim', 1e6)
orb_crit = kwargs.pop('orb_crit', 1.)
disky_crit = kwargs.pop('disky_crit', .9)
kepler_crit = kwargs.pop('kepler_crit', .8)
redshift = snapshot.header.Redshift
length_unit = 'cm'
mass_unit = 'g'
velocity_unit = 'cgs'
snapshot.gas.units.set_velocity(velocity_unit)
xyz = snapshot.gas.get_coords(length_unit)
uvw = snapshot.gas.get_velocities()
snapshot.update_sink_frame_ofR(xyz, uvw)
dens = snapshot.gas.get_number_density('cgs')
mass = snapshot.gas.get_masses(mass_unit)
temp = snapshot.gas.get_temperature()
csound = snapshot.gas.get_sound_speed()
i = 0
try:
while snapshot.sinks[i].pid != sink_id:
i += 1
except IndexError:
raise IndexError("Sink {} has not yet formed!".format(sink_id))
else:
sink = snapshot.sinks[i]
sinkpos = (sink.x, sink.y, sink.z)
sinkvel = (sink.vx, sink.vy, sink.vz)
pos = snapshot.gas.get_coords(system='spherical',view='face',
center=sinkpos, vcenter=sinkvel)
vel = snapshot.gas.get_velocities(system='spherical')
xyz = snapshot.gas.get_coords()
uvw = snapshot.gas.get_velocities()
snapshot.update_sink_frame_ofR(xyz, uvw)
pos = numpy.nan_to_num(pos)
vel = numpy.nan_to_num(vel)
L9 = analyze.total_angular_momentum(*analyze.data_slice(dens > 1e9,
xyz,uvw,mass))
uL9 = L9 / numpy.linalg.norm(L9)
if dens_lim:
arrs = [dens,pos,vel,xyz,uvw,mass,temp,csound]
dslice = dens > dens_lim
dens,pos,vel,xyz,uvw,mass,temp,csound = analyze.data_slice(dslice,
*arrs)
L = analyze.angular_momentum(xyz,uvw,mass)
uL = L / numpy.linalg.norm(L, axis=1)[:, numpy.newaxis]
disky = numpy.where((numpy.abs(vel[:,2])/numpy.abs(vel[:,0]) > orb_crit)
& (uL.dot(uL9) > disky_crit))[0]
print disky.size, '"disky" particles',
print '({}) percent'.format(float(disky.size)/dens.size * 100)
inf = numpy.where(numpy.abs(vel[:,0])
/ numpy.linalg.norm(vel, axis=1) > .5)[0]
print inf.size, 'infalling particles',
print '({}) percent'.format(float(inf.size)/dens.size * 100)
orb = numpy.where((numpy.abs(vel[:,2])/numpy.abs(vel[:,0]) > orb_crit)
& (uL.dot(uL9) < disky_crit))[0]
print orb.size, '"orbiting" particles',
print '({}) percent'.format(float(orb.size)/dens.size * 100)
notorb = numpy.where(numpy.abs(vel[:,2]) < numpy.abs(vel[:,0]))[0]
print notorb.size, '"not orbiting" particles',
print '({}) percent'.format(float(notorb.size)/dens.size * 100)
print 'Data loaded. Analyzing...'
disk_properties = []
vrot = vk = 1.
n = old_n = r0 = 0
r1 = r_start
print "Starting at {:.2e} AU".format(r1/1.49e13)
r2d = numpy.sqrt(xyz[:,0]**2 + xyz[:,1]**2)
data = []
while vrot/vk > kepler_crit and n < disky.size:
inR = numpy.where(pos[disky,0] <= r1)[0]
n = inR.size
if n > old_n and n > n_min:
annulus = numpy.where((r2d[disky] > r0) & (r2d[disky] <= r1))[0]
annulus = disky[annulus]
radii = r2d[annulus]
radius = radii.mean()
vrot = vel[annulus, 2].mean()
T = analyze.reject_outliers(temp[annulus]).mean()
cs = analyze.reject_outliers(csound[annulus]).mean()
H = cs * radius / vrot
Mcyl = mass[annulus].sum()
if annulus.size > 0:
zmax = numpy.abs(xyz[annulus,2]).max()
else:
zmax = 0.0
density = dens[annulus].mean()
if numpy.isnan(density):
density = dens.max()
mdensity = density * constants.m_H / constants.X_h
tff = numpy.sqrt(3 * numpy.pi / 32 / constants.GRAVITY / mdensity)
tavg = analyze.reject_outliers(temp[inR]).mean()
Mtot = mass[numpy.where(pos[:,0] <= radius)[0]].sum()
vk = numpy.sqrt(6.6726e-8 * Mtot / radius) / 1e5
Lj = cs*tff #Jeans Length
Mj = mdensity * (4*numpy.pi/3) * Lj**3 / 1.989e33 #Jeans Mass
H = cs * radius / vrot #Disk Scale Height
rau = radius/1.49597871e13
Msun = Mtot/1.989e33
vrot = vrot / 1e5
disk_properties.append((redshift,rau,density,Msun,Mcyl,
vrot,vk,tff,T,tavg,cs,H,Lj,Mj,n))
if verbose:
print 'R = %.2e AU' %rau,
print 'Mass enclosed: %.2e' %Msun,
print 'density: %.3e' %density,
print 'vrot: %.3e' %vrot,
print 'npart: {}'.format(n)
old_n = n
r0 = r1
r1 *= r_multiplier
print 'snapshot', snapshot.number, 'analyzed.'
return disk_properties