def make_map(sph, L=200):
'''Makes 2D-projected density map of the gas particles in the sph code'''
N = L
x, y = np.indices((N + 1, N + 1))
x = L * (x.flatten() - N / 2.) / N
y = L * (y.flatten() - N / 2.) / N
z = x * 0.
vx = 0. * x
vy = 0. * x
vz = 0. * x
x = units.parsec(x)
y = units.parsec(y)
z = units.parsec(z)
vx = units.kms(vx)
vy = units.kms(vy)
vz = units.kms(vz)
rho, rhovx, rhovy, rhovz, rhoe = sph.get_hydro_state_at_point(
x, y, z, vx, vy, vz)
rho = rho.reshape((N + 1, N + 1))
return rho
def make_map(sph, L=200):
N = L
x, y = np.indices((N + 1, N + 1))
x = L * (x.flatten() - N / 2.) / N
y = L * (y.flatten() - N / 2.) / N
z = x * 0.
vx = 0. * x
vy = 0. * x
vz = 0. * x
x = units.parsec(x)
y = units.parsec(y)
z = units.parsec(z)
vx = units.kms(vx)
vy = units.kms(vy)
vz = units.kms(vz)
rho, rhovx, rhovy, rhovz, rhoe = sph.get_hydro_state_at_point(
x, y, z, vx, vy, vz)
rho = rho.reshape((N + 1, N + 1))
return rho
def make_map(sph, N=100, L=1, offset_x=None, offset_y=None):
"Create a density map from an SPH code"
x, y = numpy.indices((N + 1, N + 1))
x = L * (x.flatten() - N / 2.) / N
y = L * (y.flatten() - N / 2.) / N
z = x * 0.
vx = 0. * x
vy = 0. * x
vz = 0. * x
x = units.parsec(x)
if offset_x is not None:
x += offset_x
y = units.parsec(y)
if offset_y is not None:
y += offset_y
z = units.parsec(z)
vx = units.kms(vx)
vy = units.kms(vy)
vz = units.kms(vz)
rho, rhovx, rhovy, rhovz, rhoe = sph.get_hydro_state_at_point(
x, y, z, vx, vy, vz)
rho = rho.reshape((N + 1, N + 1))
return rho
def new_cluster(number_of_stars=1000):
masses = new_salpeter_mass_distribution(number_of_stars,
mass_min=0.1 | units.MSun,
mass_max=125.0 | units.MSun,
alpha=-2.35)
particles = Particles(number_of_stars)
particles.mass = masses
particles.x = units.parsec(random.gamma(2.0, 1.0, number_of_stars))
particles.y = units.parsec(random.gamma(1.0, 1.0, number_of_stars))
particles.z = units.parsec(random.random(number_of_stars))
return particles
def new_cluster(number_of_stars = 1000):
masses = new_salpeter_mass_distribution(
number_of_stars,
mass_min = 0.1 | units.MSun,
mass_max = 125.0 | units.MSun,
alpha = -2.35
)
particles = Particles(number_of_stars)
particles.mass = masses
particles.x = units.parsec(random.gamma(2.0, 1.0, number_of_stars))
particles.y = units.parsec(random.gamma(1.0, 1.0, number_of_stars))
particles.z = units.parsec(random.random(number_of_stars))
return particles
def get_mass_via_number_density(cluster):
# progressbar
import sys
pbwidth = 42
# TODO: find different method to calculate M(<r)
print "Counting particles for which radii < r to obtain M(<r)"
radii = VectorQuantity.arange(units.kpc(1), units.kpc(10000),
units.parsec(1000))
M_gas_below_r = numpy.zeros(len(radii))
M_dm_below_r = numpy.zeros(len(radii))
N = len(radii)
for i, r in enumerate(radii):
M_gas_below_r[i] = ((numpy.where(cluster.gas.r < r)[0]).size)
M_dm_below_r[i] = ((numpy.where(cluster.dm.r < r)[0]).size)
if i % 1000 == 0:
# update the bar
progress = float(i + 1000) / N
block = int(round(pbwidth * progress))
text = "\rProgress: [{0}] {1:.1f}%".format(
"#" * block + "-" * (pbwidth - block), progress * 100)
sys.stdout.write(text)
sys.stdout.flush()
sys.stdout.write("\n")
print "Done counting particles :-)... TODO: improve this method?!"
M_gas_below_r *= cluster.M_gas / cluster.raw_data.Ngas
M_dm_below_r *= cluster.M_dm / cluster.raw_data.Ndm
amuse_plot.scatter(radii, M_gas_below_r, c="g", label="Gas")
amuse_plot.scatter(radii, M_dm_below_r, c="b", label="DM")
def __init__(self,
parms,
dm_parms=None,
radius=None,
z=0,
free_beta=False):
""" parms = ne0, rc, [rcut], [ne0_fac, rc_fac]
dm_parms = M_DM, a """
# TODO: implement without need for dm_parms
if radius is None:
self.radius = VectorQuantity.arange(units.kpc(1), units.kpc(1e5),
units.parsec(100))
else:
if type(radius) == numpy.ndarray:
self.radius = radius | units.kpc
else:
self.radius = radius
self.z = z
self.ne0 = parms[0]
self.rho0 = convert.ne_to_rho(self.ne0, self.z) | units.g / units.cm**3
self.ne0 = self.ne0 | units.cm**-3
self.rc = parms[1] | units.kpc
self.model = 0
self.rcut = None
self.ne0_cc = None
self.rho0_cc = None
self.rc_cc = None
self.free_beta = free_beta
if len(parms) == 3 and not free_beta:
self.model = 1
self.rcut = parms[2] | units.kpc
if len(parms) == 3 and free_beta:
self.model = 3
self.beta = parms[2]
if len(parms) == 4 and free_beta:
self.model = 4
self.rcut = parms[2] | units.kpc
self.beta = parms[3]
if len(parms) == 5:
self.model = 2
ne0_fac = parms[3]
rc_fac = parms[4]
self.ne0_cc = ne0 * ne0_fac
self.rho0_cc = self.ne0_cc * globals.mu * (globals.m_p | units.g)
self.rc_cc = rc / rc_fac
modelnames = {
0: r"$\beta=2/3$",
1: r"cut-off $\beta=2/3$",
2: r"cut-off double $\beta (2/3)$",
3: r"free $\beta$",
4: r"cut-off free $\beta$"
}
self.modelname = modelnames[self.model]
if dm_parms:
self.M_dm = dm_parms[0]
self.a = dm_parms[1]
def make_map(sph,N=100,L=1):
x,y=numpy.indices( ( N+1,N+1 ))
x=L*(x.flatten()-N/2.)/N
y=L*(y.flatten()-N/2.)/N
z=x*0.
vx=0.*x
vy=0.*x
vz=0.*x
x=units.parsec(x)
y=units.parsec(y)
z=units.parsec(z)
vx=units.kms(vx)
vy=units.kms(vy)
vz=units.kms(vz)
rho,rhovx,rhovy,rhovz,rhoe=sph.get_hydro_state_at_point(x,y,z,vx,vy,vz)
rho=rho.reshape((N+1,N+1))
return rho
def plot_individual_cluster_mass(cluster):
pyplot.figure(figsize=(24, 18))
# TODO: use different method :-)...
get_mass_via_number_density(cluster)
# get_mass_via_number_density_parallel(cluster)
# get_mass_via_density(cluster)
pyplot.gca().set_xscale("log")
pyplot.gca().set_yscale("log")
# M_gas = (cluster.gas.mass.value_in(units.MSun))
# M_dm = (cluster.dm.mass.value_in(units.MSun))
# amuse_plot.scatter(cluster.gas.r, units.MSun(M_gas), c="g", label="Gas")
# amuse_plot.scatter(cluster.dm.r, units.MSun(M_dm), c="b", label="DM")
# Analytical solutions. Sample radii and plug into analytical expression.
r = VectorQuantity.arange(units.kpc(1), units.kpc(10000),
units.parsec(100))
# Plot analytical Hernquist model for the DM mass M(<r)
amuse_plot.plot(r,
cluster.dm_cummulative_mass(r),
ls="solid",
c="k",
label="DM")
# Plot analytical beta model (Donnert 2014) for the gas mass M(<r)
amuse_plot.plot(r,
cluster.gas_cummulative_mass_beta(r),
ls="dotted",
c="k",
label=r"$\beta$-model")
# Plot analytical double beta model (Donnert et al. 2016, in prep) gas M(<r)
amuse_plot.plot(r,
cluster.gas_cummulative_mass_double_beta(r),
ls="dashed",
c="k",
label=r"double $\beta$-model")
pyplot.xlabel(r"$r$ [kpc]")
pyplot.ylabel(r"$M (<r)$ [MSun]")
pyplot.gca().set_xscale("log")
pyplot.gca().set_yscale("log")
pyplot.legend(loc=4)
def donnert_2014_figure1(analytical_P500=False):
# Well, I will just eyeball the value of rho_0 in Figure 1 in Donnert (2014) and adopt this value, I suppose...
# disturbed = InitialCluster(rho_0=(9e-27 | units.g/units.cm**3),
# plot=False, do_print=False,
# disturbed_cluster=True, cool_core_cluster=False)
# coolcore = InitialCluster(rho_0=(3e-25 | units.g/units.cm**3),
# plot=False, do_print=False,
# disturbed_cluster=False, cool_core_cluster=True)
# rickersarazin = InitialCluster(plot=False, do_print=False, disturbed_cluster=False, cool_core_cluster=False)
r = VectorQuantity.arange(units.kpc(1), units.kpc(10000),
units.parsec(100))
#fig, ((ax1, ax2), (ax3, ax4)) = pyplot.subplots(2, 2, figsize=(20, 20), dpi=500)
fig, ((ax1, ax2), (ax3, ax4)) = pyplot.subplots(2, 2)
# Plot the density situation
pyplot.sca(ax1)
amuse_plot.hist(r, bins=int(numpy.sqrt(len(r))), label="Hanky")
# amuse_plot.loglog(coolcore.r, coolcore.rho_gas.as_quantity_in(units.g / units.cm**3),
# c='k', ls='dotted', label="Gas, cool core")
# amuse_plot.loglog(disturbed.r, disturbed.rho_gas.as_quantity_in(units.g / units.cm**3),
# c='k', ls='dashed', label="Gas, disturbed")
# amuse_plot.loglog(disturbed.r, disturbed.rho_dm.as_quantity_in(units.g / units.cm**3),
# c='k', ls='solid', label="Dark Matter")
amuse_plot.ylabel(r'$\rho$')
amuse_plot.xlabel(r'$r$')
pyplot.legend(loc=3, frameon=False, fontsize=12)
ax1.set_ylim(ymin=1e-28, ymax=1e-23)
# pyplot.axvline(x=disturbed.r_200.value_in(units.kpc), lw=2, c='k')
# pyplot.text(disturbed.r_200.value_in(units.kpc), 7e-24, r'$r_{200}$', fontsize=12)
# pyplot.axvline(x=disturbed.r_500.value_in(units.kpc), lw=2, c='k')
# pyplot.text(disturbed.r_500.value_in(units.kpc), 7e-24, r'$r_{500}$', fontsize=12)
# # a_hernq
# intersect = disturbed.dm_density(disturbed.a)
# ymin, ymax = ax1.get_ylim()
# ymin = (numpy.log(intersect.value_in(units.g/units.cm**3)/ymin)) / (numpy.log(ymax/ymin))
# pyplot.axvline(x=disturbed.a.value_in(units.kpc), ymin=ymin, ymax=1, lw=2, c='k')
# pyplot.text(disturbed.a.value_in(units.kpc), 5e-24, r'$a_{\rm Hernq}$', fontsize=12)
# # r_core,dist
# intersect = disturbed.gas_density(disturbed.r_c)
# ymin, ymax = ax1.get_ylim()
# ymin = (numpy.log(intersect.value_in(units.g/units.cm**3)/ymin)) / (numpy.log(ymax/ymin))
# pyplot.axvline(x=disturbed.r_c.value_in(units.kpc), ymin=ymin, ymax=1, lw=2, ls='--', c='k')
# pyplot.text(disturbed.r_c.value_in(units.kpc), 5e-24, r'$r_{\rm core,dist}$', fontsize=12)
# # r_core,cc
# intersect = coolcore.gas_density(coolcore.r_c)
# ymin, ymax = ax1.get_ylim()
# ymin = (numpy.log(intersect.value_in(units.g/units.cm**3)/ymin)) / (numpy.log(ymax/ymin))
# pyplot.axvline(x=coolcore.r_c.value_in(units.kpc), ymin=ymin, ymax=1, lw=2, ls=':', c='k')
# pyplot.text(coolcore.r_c.value_in(units.kpc), 5e-24, r'$r_{\rm core,cc}$', fontsize=12)
# Plot the mass situation
pyplot.sca(ax2)
amuse_plot.hist(r, bins=int(numpy.sqrt(len(r))), label="Hanky")
# amuse_plot.loglog(coolcore.r, coolcore.M_gas_below_r.as_quantity_in(units.MSun),
# c='k', ls='dotted', label="Gas, cool core")
# amuse_plot.loglog(disturbed.r, disturbed.M_gas_below_r.as_quantity_in(units.MSun),
# c='k', ls='dashed', label="Gas, disturbed")
# amuse_plot.loglog(disturbed.r, disturbed.M_dm_below_r.as_quantity_in(units.MSun),
# c='k', ls='solid', label="Dark Matter")
amuse_plot.ylabel(r'$M(<r)$')
amuse_plot.xlabel(r'$r$')
pyplot.legend(loc=8, frameon=False, fontsize=12)
ax2.set_ylim(ymin=1e10, ymax=5e15)
# pyplot.axvline(x=disturbed.r_200.value_in(units.kpc), lw=2, c='k')
# pyplot.text(disturbed.r_200.value_in(units.kpc), 3e15, r'$r_{200}$', fontsize=12)
# pyplot.axvline(x=disturbed.r_500.value_in(units.kpc), lw=2, c='k')
# pyplot.text(disturbed.r_500.value_in(units.kpc), 3e15, r'$r_{500}$', fontsize=12)
# # a_hernq
# intersect = disturbed.dm_cummulative_mass(disturbed.a)
# ymin, ymax = ax2.get_ylim()
# ymin = (numpy.log(intersect.value_in(units.MSun)/ymin)) / (numpy.log(ymax/ymin))
# pyplot.axvline(x=disturbed.a.value_in(units.kpc), ymin=ymin, ymax=1, lw=2, c='k')
# pyplot.text(disturbed.a.value_in(units.kpc), 2e15, r'$a_{\rm Hernq}$', fontsize=12)
# # r_core,dist
# intersect = disturbed.dm_cummulative_mass(disturbed.r_c)
# ymin, ymax = ax2.get_ylim()
# ymin = (numpy.log(intersect.value_in(units.MSun)/ymin)) / (numpy.log(ymax/ymin))
# pyplot.axvline(x=disturbed.r_c.value_in(units.kpc), ymin=ymin, ymax=1, lw=2, ls='--', c='k')
# pyplot.text(disturbed.r_c.value_in(units.kpc), 2e15, r'$r_{\rm core,dist}$', fontsize=12)
# # r_core,cc
# intersect = coolcore.dm_cummulative_mass(coolcore.r_c)
# ymin, ymax = ax2.get_ylim()
# ymin = (numpy.log(intersect.value_in(units.MSun)/ymin)) / (numpy.log(ymax/ymin))
# pyplot.axvline(x=coolcore.r_c.value_in(units.kpc), ymin=ymin, ymax=1, lw=2, ls=':', c='k')
# pyplot.text(coolcore.r_c.value_in(units.kpc), 2e15, r'$r_{\rm core,cc}$', fontsize=12)
# Plot the temperature situation
pyplot.sca(ax3)
amuse_plot.hist(r, bins=int(numpy.sqrt(len(r))), label="Hanky")
# amuse_plot.loglog(disturbed.r, disturbed.T_r.as_quantity_in(units.K),
# c='k', ls='solid', label="disturbed")
# amuse_plot.loglog(disturbed.r, disturbed.T_r_dm.as_quantity_in(units.K),
# c='k', ls='dashdot', label="from DM, disturbed")
# amuse_plot.loglog(disturbed.r, disturbed.T_r_gas.as_quantity_in(units.K),
# c='k', ls='dashed', label="from Gas, disturbed")
# amuse_plot.loglog(coolcore.r, coolcore.T_r.as_quantity_in(units.K),
# c='k', ls='dotted', label="cool core")
amuse_plot.ylabel(r'$T$')
amuse_plot.xlabel(r'$r$')
pyplot.legend(loc=10, frameon=False, fontsize=12)
ax3.set_ylim(ymin=6e6, ymax=3e8)
# pyplot.axvline(x=disturbed.r_200.value_in(units.kpc), lw=2, c='k')
# pyplot.text(disturbed.r_200.value_in(units.kpc), 2.6e8, r'$r_{200}$', fontsize=12)
# pyplot.axvline(x=disturbed.r_500.value_in(units.kpc), lw=2, c='k')
# pyplot.text(disturbed.r_500.value_in(units.kpc), 2.6e8, r'$r_{500}$', fontsize=12)
# pyplot.axvline(x=disturbed.a.value_in(units.kpc), lw=2, c='k')
# pyplot.text(disturbed.a.value_in(units.kpc), 2.4e8, r'$a_{\rm Hernq}$', fontsize=12)
# # r_core,dist
# intersect = disturbed.temperature(disturbed.r_c)
# ymin, ymax = ax3.get_ylim()
# ymin = (numpy.log(intersect.value_in(units.K)/ymin)) / (numpy.log(ymax/ymin))
# pyplot.axvline(x=disturbed.r_c.value_in(units.kpc), ymin=ymin, ymax=1, lw=2, ls='--', c='k')
# pyplot.text(disturbed.r_c.value_in(units.kpc), 2.4e8, r'$r_{\rm core,dist}$', fontsize=12)
# # r_core,cc
# intersect = coolcore.temperature(coolcore.r_c)
# ymin, ymax = ax3.get_ylim()
# ymin = (numpy.log(intersect.value_in(units.K)/ymin)) / (numpy.log(ymax/ymin))
# pyplot.axvline(x=coolcore.r_c.value_in(units.kpc), ymin=ymin, ymax=1, lw=2, ls=':', c='k')
# pyplot.text(coolcore.r_c.value_in(units.kpc), 2.4e8, r'$r_{\rm core,cc}$', fontsize=12)
# TODO: pressure situation
pyplot.sca(ax4)
amuse_plot.hist(r, bins=int(numpy.sqrt(len(r))), label="Hanky")
colours = [(255. / 255, 127. / 255, 0. / 255),
(152. / 255, 78. / 255, 163. / 255),
(77. / 255, 175. / 255, 74. / 255),
(52. / 255, 126. / 255, 184. / 255),
(228. / 255, 26. / 255, 28. / 255)]
# print "Warning, the pressure plots make little sense because for each M_DM is the same but M_200 differs"
# for i, M_200 in enumerate(VectorQuantity([3e15, 1.5e15, 1e15, 0.5e15, 0.1e15], units.MSun)):
# disturbed = InitialCluster(rho_0=(9e-27 | units.g/units.cm**3), M_200=M_200,
# plot=False, do_print=False,
# disturbed_cluster=True, cool_core_cluster=False)
# coolcore = InitialCluster(rho_0=(3e-25 | units.g/units.cm**3), M_200=M_200,
# plot=False, do_print=False,
# disturbed_cluster=False, cool_core_cluster=True)
# if analytical_P500:
# amuse_plot.loglog(disturbed.r/disturbed.r_500, (disturbed.P_gas/disturbed.find_p500_analytically()),
# c=colours[i], ls='solid', label=r'{0} $M_\odot$'.format(disturbed.M_200.value_in(units.MSun)))
# amuse_plot.loglog(coolcore.r/coolcore.r_500, (coolcore.P_gas/coolcore.find_p500_analytically()),
# c=colours[i], ls='dashed')
# else:
# amuse_plot.loglog(disturbed.r/disturbed.r_500, (disturbed.P_gas/disturbed.P_500),
# c=colours[i], ls='solid', label=r'{0} $M_\odot$'.format(disturbed.M_200.value_in(units.MSun)))
# amuse_plot.loglog(coolcore.r/coolcore.r_500, (coolcore.P_gas/coolcore.P_500),
# c=colours[i], ls='dashed')
amuse_plot.ylabel(r'$P(r)/P_{500}$')
amuse_plot.xlabel(r'$r/r_{500}$')
legend = pyplot.legend(loc=3, frameon=False, fontsize=16)
# Set the color situation
# for colour, text in zip(colours, legend.get_texts()):
# text.set_color(colour)
ax4.set_ylim(ymin=1e-2, ymax=1e3)
ax4.set_xticks((0.01, 0.10, 1.00))
ax4.set_xticklabels(("0.01", "0.10", "1.00"))
ax4.set_xlim(xmin=0.01, xmax=2.0)
ax4.minorticks_on()
ax4.tick_params('both', length=10, width=2, which='major')
ax4.tick_params('both', length=5, width=1, which='minor')
ax4.text(0.015, 4, "disturbed", color="grey", fontsize=15)
ax4.text(0.02, 110, "cool cores", color="grey", fontsize=15)
ax4.text(0.2, 50, "Arnaud et al. 2010", color="black", fontsize=15)
# Set the xticks situation
for ax in [ax1, ax2, ax3]:
ax.set_xscale("log")
ax.set_yscale("log")
ax.set_xticks((10, 100, 1000))
ax.set_xticklabels(("10", "100", "1000"))
ax.set_xlim(xmin=10, xmax=5000)
ax.minorticks_on()
ax.tick_params('both', length=10, width=2, which='major')
ax.tick_params('both', length=5, width=1, which='minor')
# pyplot.savefig("../img/Donnert2014_Figure1_by_TLRH.pdf", format="pdf", dpi=1000)
pyplot.show()
def plot_individual_cluster_density(cluster):
""" Plot the particles' density radial profile and compare to model """
pyplot.figure(figsize=(24, 18))
# AMUSE datamodel particles. Gas has RHO and RHOm; dm rho from model.
amuse_plot.scatter(cluster.gas.r,
cluster.gas.rho,
c="g",
edgecolor="face",
s=1,
label=r"Generated IC: gas $\rho$")
# amuse_plot.scatter(cluster.gas.r,
# cluster.gas.rhom,
# c="r", edgecolor="face", s=1, label=r"Generated IC: gas $\rho_{\rm model}$")
amuse_plot.scatter(cluster.dm.r,
cluster.dm.rho,
c="b",
edgecolor="none",
label=r"Generated IC: DM $\rho$")
# Analytical solutions. Sample radii and plug into analytical expression.
r = VectorQuantity.arange(units.kpc(1), units.kpc(10000),
units.parsec(100))
# Plot analytical beta model (Donnert 2014) for the gas density
amuse_plot.plot(r,
cluster.gas_density_double_beta(r),
c="k",
ls="dashed",
label=r"Analytical, $\beta$-model:"
"\n"
r"$\rho_0$ = {0} g/cm$^3$; $rc = ${1} kpc".format(
cluster.rho0gas.number, cluster.rc.number))
# Plot analytical double beta model (Donnert et al. 2016, in prep) for gas
amuse_plot.plot(
r,
cluster.gas_density_beta(r),
c="k",
ls="dotted",
label=r"Analytical, double $\beta$-model:"
"\n"
r"$\rho_0$ = {0} g/cm$^3$; $rc =$ {1} kpc; $r_{{\rm cut}}$ = {2} kpc".
format(cluster.rho0gas.number, cluster.rc.number, cluster.rcut.number))
# Plot analytical Hernquist model for the DM density
amuse_plot.plot(r,
cluster.dm_density(r),
c="k",
ls="solid",
label=r"Analytical, Hernquist-model"
"\n"
r"$M_{{\rm dm}}= ${0:.2e} MSun; $a = $ {1} kpc".format(
cluster.M_dm.number, cluster.a.number))
pyplot.legend(loc=3)
amuse_plot.xlabel(r"$r$")
amuse_plot.ylabel(r"$\rho$")
pyplot.gca().set_xlim(xmin=10, xmax=1e4)
pyplot.gca().set_ylim(ymin=1e-30, ymax=9e-24)
pyplot.gca().set_xscale("log")
pyplot.gca().set_yscale("log")
pyplot.axvline(x=cluster.R200.value_in(units.kpc), lw=1, c="grey")
pyplot.text(cluster.R200.value_in(units.kpc), 5e-24,
r"$r_{{cut}} =$ {0}".format(cluster.rcut))
pyplot.axvline(x=cluster.rc.value_in(units.kpc), lw=1, c="grey")
pyplot.text(cluster.rc.value_in(units.kpc), 5e-24,
r"$rc =$ {0}".format(cluster.rc))
pyplot.axvline(x=cluster.a.value_in(units.kpc), lw=1, c="grey")
pyplot.text(cluster.a.value_in(units.kpc), 1e-24,
r"$a =$ {0}".format(cluster.a))
def merge_clusters_with_gas(sfeff=[0.3, 0.3],
Nstar=[1000, 1000],
totalNgas=40000,
t_end=30. | units.Myr,
dt_plot=0.05 | units.Myr,
Rscale=units.parsec([0.25, 0.25]),
tmerge=2.5 | units.Myr,
eps_star=0.001 | units.parsec,
runid="runtest",
feedback_efficiency=0.01,
subvirialfac=1.):
try:
os.mkdir(runid)
except:
pass
print "Nstar, Ngas:", Nstar, totalNgas
eps = 0.05 * Rscale.mean()
IMF = SalpeterIMF(mass_max=100. | units.MSun)
mean_star_mass = IMF.mass_mean()
approx_gas_mass = 0. * mean_star_mass
for e, N in zip(sfeff, Nstar):
approx_gas_mass += (1 - e) * N * mean_star_mass / e
mgas = approx_gas_mass / totalNgas
print "gas particle mass:", mgas.in_(units.MSun)
stars = []
gas = []
total_mass = 0. | units.MSun
total_gas_mass = 0. | units.MSun
total_star_mass = 0. | units.MSun
for e, Ns, r in zip(sfeff, Nstar, Rscale):
s, g = generate_cluster_with_gas(IMF,
e,
Ns,
r,
mgas,
subvirialfac=subvirialfac,
t_end=t_end)
stars.append(s)
gas.append(g)
total_mass += s.mass.sum() + g.mass.sum()
total_star_mass += s.mass.sum()
total_gas_mass += g.mass.sum()
print "total mass:", total_mass.in_(units.MSun)
print "total star mass:", total_star_mass.in_(units.MSun)
print "total gas mass:", total_gas_mass.in_(units.MSun)
print "t_end:", t_end
Rsep = (constants.G * total_mass * tmerge**2)**(1. / 3)
stars[0].x = stars[0].x - Rsep / 2
stars[1].x = stars[1].x + Rsep / 2
gas[0].x = gas[0].x - Rsep / 2
gas[1].x = gas[1].x + Rsep / 2
conv = nbody_system.nbody_to_si(total_mass, Rsep)
print "tmerge:", tmerge
print "Rsep:", Rsep.in_(units.parsec)
allgas = datamodel.Particles(0)
allstars = datamodel.Particles(0)
allgas.add_particles(gas[0])
allgas.add_particles(gas[1])
allstars.add_particles(stars[0])
allstars.add_particles(stars[1])
allgas.h_smooth = 0. | units.parsec
allstars.radius = eps_star
mu = 1.4 | units.amu
gamma1 = 1.6667 - 1
# print 'min Temp:', (gamma1*min(allgas.u)*(1.4*units.amu)/constants.kB).in_(units.K)
print 'min Temp:', (gamma1 * min(allgas.u) * mu / constants.kB).in_(
units.K)
print max(allgas.u)**0.5
dt = smaller_nbody_power_of_two(dt_plot, conv)
dt_star = smaller_nbody_power_of_two(0.001 | units.Myr, conv) #0.001
dt_sph = dt_star
dt_fast = dt_star # 8
dt_feedback = dt_fast * 4 # 2
if not dt_star <= dt_fast <= dt_feedback:
raise Exception
print 'dt_plot:', conv.to_nbody(dt_plot), dt_plot.in_(units.Myr)
print 'dt:', conv.to_nbody(dt), dt.in_(units.Myr)
print 'dt_feedback:', conv.to_nbody(dt_feedback), dt_feedback.in_(
units.Myr)
print 'dt_fast:', conv.to_nbody(dt_fast), dt_fast.in_(units.Myr)
print 'dt_star:', conv.to_nbody(dt_star), dt_star.in_(units.Myr)
print 'dt_sph:', conv.to_nbody(dt_sph), dt_sph.in_(units.Myr)
sys = grav_gas_sse(
PhiGRAPE,
Gadget2,
SSEplus,
Octgrav,
conv,
mgas,
allstars,
allgas,
dt_feedback,
dt_fast,
grav_parameters=(["epsilon_squared",
eps_star**2], ["timestep_parameter", 0.001]),
# ["timestep", dt_star]),
gas_parameters=(
["time_max", 32. | units.Myr],
# ["courant", 0.15 | units.none],
["n_smooth", 64 | units.none],
# ["artificial_viscosity_alpha",1.| units.none],
["n_smooth_tol", 0.005 | units.none],
## NB
# ["max_size_timestep",7500. | units.yr],
## NB
["time_limit_cpu", 3600000 | units.s]),
couple_parameters=(["epsilon_squared", eps**2], ["opening_angle",
0.5]),
feedback_efficiency=feedback_efficiency,
feedback_radius=0.025 * Rscale)
nsnap = 0
sys.synchronize_model()
t = sys.model_time
tout = t.value_in(units.Myr)
ek = sys.kinetic_energy.value_in(1.e51 * units.erg)
ep = sys.potential_energy.value_in(1.e51 * units.erg)
eth = sys.thermal_energy.value_in(1.e51 * units.erg)
ef = sys.feedback_energy.value_in(1.e51 * units.erg)
print 't Ek Ep Eth Ef:', tout, ek, ep, eth, ef, ek + ep + eth - ef
sys.dump_system_state(runid + "/dump-%6.6i" % nsnap)
print 'max smooth:', max(sys.sph.gas_particles.radius).in_(units.parsec)
print 'mean smooth:', sys.sph.gas_particles.radius.mean().in_(units.parsec)
print 'min smooth:', min(sys.sph.gas_particles.radius).in_(units.parsec)
print 'eps:', eps.in_(units.parsec)
print 'feedback radius:', (0.01 * Rscale).in_(units.parsec)
while (t < t_end - dt / 2):
sys.evolve_model(t + dt)
sys.synchronize_model()
t = sys.model_time
tout = t.value_in(units.Myr)
ek = sys.kinetic_energy.value_in(1.e51 * units.erg)
ep = sys.potential_energy.value_in(1.e51 * units.erg)
eth = sys.thermal_energy.value_in(1.e51 * units.erg)
ef = sys.feedback_energy.value_in(1.e51 * units.erg)
print 't Ek Ep Eth Ef:', tout, ek, ep, eth, ef, ek + ep + eth - ef
nsnap += 1
sys.dump_system_state(runid + "/dump-%6.6i" % nsnap)
