def plot_galaxy_and_stars(galaxy, stars):
colors = get_distinct(3)
single_frame('X [pc]', 'Y [pc]')
xlim = 60
pyplot.xlim(-xlim, xlim)
pyplot.ylim(-xlim, xlim)
ax = pyplot.gca()
import numpy as np
import pandas as pd
from scipy import stats, integrate
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(color_codes=True)
p = galaxy.select(lambda x: x < 60 | units.parsec, ["x"])
p = p.select(lambda x: x > -60 | units.parsec, ["x"])
p = p.select(lambda y: y < 60 | units.parsec, ["y"])
p = p.select(lambda y: y > -60 | units.parsec, ["y"])
x = p.x.value_in(units.parsec)
y = p.y.value_in(units.parsec)
sns.kdeplot(x, y, ax=ax)
m = 100 * numpy.sqrt(stars.mass / stars.mass.max())
pyplot.scatter(stars.x.value_in(units.parsec),
stars.y.value_in(units.parsec),
c=colors[0],
s=m,
lw=0)
# pyplot.show()
pyplot.savefig("Fujii_Comparison_Figure")
def plot_galaxy_and_stars(galaxy, stars):
colors = get_distinct(3)
single_frame('X [pc]', 'Y [pc]')
xlim = 60
pyplot.xlim(-xlim, xlim)
pyplot.ylim(-xlim, xlim)
ax = pyplot.gca()
import numpy as np
import pandas as pd
from scipy import stats, integrate
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(color_codes=True)
p = galaxy.select(lambda x: x<60|units.parsec,["x"])
p = p.select(lambda x: x>-60|units.parsec,["x"])
p = p.select(lambda y: y<60|units.parsec,["y"])
p = p.select(lambda y: y>-60|units.parsec,["y"])
x = p.x.value_in(units.parsec)
y = p.y.value_in(units.parsec)
sns.kdeplot(x, y, ax=ax)
m = 100*numpy.sqrt(stars.mass/stars.mass.max())
pyplot.scatter(stars.x.value_in(units.parsec), stars.y.value_in(units.parsec), c=colors[0], s=m, lw=0)
# pyplot.show()
pyplot.savefig("Fujii_Comparison_Figure")
def plot_galaxy_and_stars(galaxy, stars):
colors = get_distinct(3)
single_frame('X [kpc]', 'Y [kpc]')
xlim = 10
pyplot.xlim(-xlim, xlim)
pyplot.ylim(-xlim, xlim)
ax = pyplot.gca()
import numpy as np
import pandas as pd
from scipy import stats, integrate
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(color_codes=True)
lim = 10 | units.kpc
p = galaxy.select(lambda x: x < lim, ["x"])
p = p.select(lambda x: x > -lim, ["x"])
p = p.select(lambda y: y < lim, ["y"])
p = p.select(lambda y: y > -lim, ["y"])
p = p.select(lambda r: r.length() > 5 | units.kpc, ["position"])
x = p.x.value_in(units.kpc)
y = p.y.value_in(units.kpc)
sns.kdeplot(x, y, ax=ax, shade=True, n_levels=20, shade_lowest=False)
m = 100 * numpy.sqrt(stars.mass / stars.mass.max())
pyplot.scatter(stars.x.value_in(units.kpc),
stars.y.value_in(units.kpc),
c=colors[0],
s=m,
lw=0)
pyplot.savefig("SolarSiblings_life_galaxy")
def energy_plot(time, E_kin, E_pot, E_therm, figname):
if not HAS_MATPLOTLIB:
return
x_label = 'Time [hour]'
y_label = 'Energy [foe]'
single_frame(x_label,
y_label,
logx=False,
logy=False,
xsize=14,
ysize=10,
ymin=-1,
ymax=-1)
cols = get_distinct(4)
FOE = 1.e+51 | units.erg
hour = 1 | units.hour
pyplot.plot(time / hour, E_kin / FOE, label='E_kin', c=cols[0])
pyplot.plot(time / hour, E_pot / FOE, label='E_pot', c=cols[1])
pyplot.plot(time / hour, E_therm / FOE, label='E_therm', c=cols[2])
pyplot.plot(time / hour, (E_kin + E_pot + E_therm) / FOE,
label='E_total',
c=cols[3])
pyplot.legend(loc='best')
pyplot.savefig(figname)
print('\nSaved energy evolution figure in file', figname, '\n')
pyplot.show()
pyplot.close()
def plot_galaxy_and_stars(galaxy, stars):
colors = get_distinct(3)
single_frame('X [kpc]', 'Y [kpc]')
xlim = 10
pyplot.xlim(-xlim, xlim)
pyplot.ylim(-xlim, xlim)
ax = pyplot.gca()
import numpy as np
import pandas as pd
from scipy import stats, integrate
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(color_codes=True)
lim = 10|units.kpc
p = galaxy.select(lambda x: x<lim,["x"])
p = p.select(lambda x: x>-lim,["x"])
p = p.select(lambda y: y<lim,["y"])
p = p.select(lambda y: y>-lim,["y"])
p = p.select(lambda r: r.length()>5|units.kpc,["position"])
x = p.x.value_in(units.kpc)
y = p.y.value_in(units.kpc)
sns.kdeplot(x, y, ax=ax, shade=True, n_levels=20, shade_lowest=False)
m = 100*numpy.sqrt(stars.mass/stars.mass.max())
pyplot.scatter(stars.x.value_in(units.kpc), stars.y.value_in(units.kpc), c=colors[0], s=m, lw=0)
pyplot.savefig("SolarSiblings_life_galaxy")
def main(N, t_end, z, C="SeBa", plot=False):
if "SeBa" not in C:
x_label = "T [K]"
y_label = "L [L$_\odot$]"
figure = single_frame(x_label, y_label, logx=True, logy=True, xsize=14, ysize=10)
color = get_distinct(4)
pyplot.xlim(1.e+5, 1.e+3)
pyplot.ylim(1.e-4, 1.e+4)
filename = "Stellar_"+"SeBa"+".h5"
plot_HRD(filename, color[0])
filename = "Stellar_"+C+".h5"
plot_HRD(filename, color[1])
pyplot.savefig("HRD_N3000at4500Myr")
elif not plot:
numpy.random.seed(1)
masses = new_salpeter_mass_distribution(N)
stars = Particles(mass=masses)
get_stellar_temperature_and_luminosity(stars, C=C, z=z, t_end=t_end, write=True)
else:
x_label = "T [K]"
y_label = "L [L$_\odot$]"
figure = single_frame(x_label, y_label, logx=True, logy=True, xsize=14, ysize=10)
color = get_distinct(4)
pyplot.xlim(1.e+5, 1.e+3)
pyplot.ylim(1.e-4, 1.e+4)
filename = "Stellar_"+C+".h5"
plot_HRD(filename, color[0])
# pyplot.show()
pyplot.savefig("HRD_N3000at4500Myr")
def plot_ionization_fraction(pos, xion):
r = [] | units.parsec
x = []
for pi, xi in zip(pos, xion):
r.append(pi.length())
x.append(xi)
r, x = list(zip(*sorted(zip(r.value_in(units.parsec), x))))
R, X = binned_mean_data(r, x)
from matplotlib import pyplot
x_label = "r [pc]"
y_label = r'$\xi_{\rm ion}$'
figure = single_frame(x_label,
y_label,
logx=False,
logy=False,
xsize=14,
ysize=8)
pyplot.scatter(r, x, c=get_distinct(1), lw=0, s=100)
pyplot.plot(R, X, c=get_distinct(2)[1], lw=2)
pyplot.xlim(0, 6)
pyplot.ylim(-0.04, 1.19)
pyplot.savefig("fig_ionization_of_GMC")
pyplot.show()
def main(N, t_end):
t_end = t_end | nbody_system.time
Q_init = 0.2
particles = new_plummer_model(N)
codes = [ph4, Huayno, BHTree]
cols = get_distinct(3)
ci = 0
x_label = "time [N-body units]"
# y_label = "$Q [\equiv -E_{\rm kin}/E_{\rm pot}]$"
y_label = "virial ratio $Q$"
figure = single_frame(x_label, y_label, xsize=14, ysize=10)
ax1 = pyplot.gca()
ax1.set_xlim(0, t_end.value_in(t_end.unit))
ax1.set_ylim(0, 0.65)
pyplot.plot([0, t_end.value_in(t_end.unit)], [0.5, 0.5],
lw=1,
ls='--',
c='k')
for code in codes:
time, Q = virial_ratio_evolution(code, particles, Q_init, t_end)
pyplot.plot(time.value_in(t_end.unit), Q, c=cols[ci])
ci += 1
# pyplot.show()
pyplot.savefig("gravity_to_virial")
def plot_hydro(time, sph, i, L=10):
x_label = "x [pc]"
y_label = "y [pc]"
fig = single_frame(x_label, y_label, logx=False, logy=False,
xsize=12, ysize=12)
rho = make_map(sph,N=200,L=L)
cax = pyplot.imshow(numpy.log10(1.e-5+rho.value_in(units.amu/units.cm**3)),
cmap="jet",
extent=[-L/2,L/2,-L/2,L/2],vmin=2,vmax=5)
if i==5:
cbar = fig.colorbar(cax, ticks=[2, 3, 4, 5], orientation='vertical', fraction=0.05)
cbar.ax.set_yticklabels([2, " ", " ", 5]) # horizontal colorbar
cbar.set_label('log projected density [$amu/cm^3$]', rotation=270)
"""
rhomin = numpy.log10(rho.value_in(units.amu/units.cm**3)).min()
rhomax = numpy.log10(rho.value_in(units.amu/units.cm**3)).max()
cax = pyplot.imshow(numpy.log10(1.e-5+rho.value_in(units.amu/units.cm**3)),
extent=[-L/2,L/2,-L/2,L/2],vmin=rhomin,vmax=rhomax)
rhomid = 0.5*(rhomin + rhomax)
print rhomin, rhomid, rhomax
cbar = fig.colorbar(cax, ticks=[rhomin, rhomid, rhomax], orientation='vertical', fraction=0.045)
# cbar.ax.set_yticklabels(['Low', ' ', 'High']) # horizontal colorbar
low = "%.2f" % rhomin
mid = "%.1f" % rhomid
mx = "%.2f" % rhomax
cbar.ax.set_yticklabels([low, mid, mx]) # horizontal colorbar
cbar.set_label('projected density [$amu/cm^3$]', rotation=270)
"""
pyplot.savefig("GMC_"+str(i)+".png")
def plot_sph(time, sph, gas, i=1, L=10):
x_label = "x [R$_\odot$]"
y_label = "y [R$_\odot$]"
fig = single_frame(x_label,
y_label,
logx=False,
logy=False,
xsize=12,
ysize=12)
# rho=make_map(sph,N=200,L=L)
rho_e = make_e_map(sph, N=200, L=L)
# pyplot.hist(numpy.log10(rho_e.value_in(units.erg/units.RSun**3)))
# pyplot.show()
print "extrema:", rho_e.value_in(
units.erg / units.RSun**3).min(), rho_e.value_in(units.erg /
units.RSun**3).max()
# pyplot.imshow(numpy.log10(1.e-8+rho.value_in(units.amu/units.cm**3)), extent=[-L/2,L/2,-L/2,L/2],vmin=1,vmax=5)
pyplot.imshow(numpy.log10(rho_e.value_in(units.erg / units.RSun**3)),
extent=[-L / 2, L / 2, -L / 2, L / 2],
vmin=23,
vmax=40)
# pyplot.imshow(numpy.log10(1.e-5+rho.value_in(units.amu/units.cm**3)), extent=[-L/2,L/2,-L/2,L/2],vmin=1,vmax=5)
#pyplot.scatter(gas.x.value_in(units.RSun), gas.y.value_in(units.RSun))#, alpha=0.05)
t = int(0.5 + sph.model_time.value_in(units.s))
filename = "supernova_sph_T" + str(t) + ".pdf"
pyplot.savefig(filename)
def main(M1, M2, M3, ain, aout, ein, eout, t_end, nsteps):
from matplotlib import pyplot
x_label = "$a/a_{0}$"
# x_label = "$t [Myr]$"
y_label = "ecc, $a/a_{0}$"
fig = single_frame(x_label,
y_label,
logx=False,
logy=False,
xsize=14,
ysize=12)
color = get_distinct(4)
time, ain, ein, aout, eout = evolve_triple_with_wind(
M1, M2, M3, ain, aout, ein, eout, t_end, nsteps)
pyplot.plot(ain, ein, c=color[0], label='inner')
pyplot.plot(aout, eout, c=color[1], label='outer')
"""
pyplot.plot(time, ein, c=color[0], label= '$e_{inner}$')
pyplot.plot(time, ain, c=color[1], label= '$a_{inner}$')
pyplot.plot(time, eout, c=color[2], label= '$e_{outer}$')
pyplot.plot(time, aout, c=color[3], label= '$a_{outer}$')
"""
pyplot.legend(loc="upper left", ncol=1, shadow=False, fontsize=24)
# pyplot.show()
pyplot.savefig("evolve_triple_with_wind")
def main(filename=None, lim=-1):
if filename is None: return
try:
amusedir = os.environ['AMUSE_DIR']
dir = amusedir + '/examples/textbook/'
except:
print('Environment variable AMUSE_DIR not set')
dir = './'
filename = dir + filename
from matplotlib import pyplot, rc
x_label = "N"
y_label = "$t_{wall} [s]$"
figure = single_frame(x_label,
y_label,
logx=True,
logy=True,
xsize=14,
ysize=10)
npp = [12, 512]
ntc = [1024, 2000 * 1024]
tpp = [0.01 * x * x for x in npp]
ttc = [1.e-6 * (x * math.log(x)) for x in ntc]
pyplot.plot(npp, tpp, c='k', ls='-', lw=4)
pyplot.plot(ntc, ttc, c='k', ls='-', lw=4)
pyplot.text(12, 8, '$N^2$')
pyplot.text(2.e+3, 0.005, '$N \log (N)$')
for ii, I in enumerate(Integrator):
# sample line: I= Hermite T= 1 time N= 4 M= 1.0 mass \
# E= -0.250000002735 mass * length**2 * time**-2 \
# Q= -0.451489790632 dE= -1.09402279371e-08 \
# Time= 2.04415297508 0.000992059707642
x = read_file(filename, 6, I)
y1 = read_file(filename, 22, I)
y2 = read_file(filename, 23, I)
for i in range(len(y1)):
y1[i] *= 0.1
y2[i] *= 0.1
if len(x) > 0:
pyplot.plot(x,
y2,
label=I,
c=color[ii],
lw=lwidth[ii],
ls=lstyles[ii])
pyplot.scatter(x, y2, c=color[ii], lw=0, s=200)
pyplot.legend(loc="lower right", fontsize=18)
save_file = "Nbody_performance.png"
pyplot.savefig(save_file)
print("\nSaved figure in file", save_file, '\n')
pyplot.show()
def plot_hydro(time, sph, L=10):
x_label = "x [pc]"
y_label = "y [pc]"
fig = single_frame(x_label,
y_label,
logx=False,
logy=False,
xsize=12,
ysize=12)
gas = sph.code.gas_particles
dmp = sph.code.dm_particles
rho = make_map(sph, N=200, L=L)
pyplot.imshow(numpy.log10(1.e-5 + rho.value_in(units.amu / units.cm**3)),
extent=[-L / 2, L / 2, -L / 2, L / 2],
vmin=1,
vmax=5,
origin="lower")
if len(dmp):
m = 10.0 * dmp.mass / dmp.mass.max()
pyplot.scatter(-dmp.x.value_in(units.parsec),
-dmp.y.value_in(units.parsec),
c='k',
s=m)
pyplot.show()
def evolve_cluster_in_galaxy(N, W0, Rinit, tend, timestep, M, R):
Rgal=1. | units.kpc
Mgal=1.6e10 | units.MSun
alpha=1.2
galaxy_code=GalacticCenterGravityCode(Rgal, Mgal, alpha)
cluster_code=make_king_model_cluster(BHTree,N,W0, M,R,
parameters=[("epsilon_squared", (0.01 | units.parsec)**2)])
stars=cluster_code.particles.copy()
stars.x += Rinit
stars.vy = 0.8*galaxy_code.circular_velocity(Rinit)
channel=stars.new_channel_to(cluster_code.particles)
channel.copy_attributes(["x","y","z","vx","vy","vz"])
system=bridge(verbose=False)
system.add_system(cluster_code, (galaxy_code,))
times=numpy.arange(0|units.Myr, tend, timestep)
for i,t in enumerate(times):
system.evolve_model(t,timestep=timestep)
x=system.particles.x.value_in(units.parsec)
y=system.particles.y.value_in(units.parsec)
cluster_code.stop()
from prepare_figure import single_frame, get_distinct
colors = get_distinct(1)
f = single_frame('X [pc]', 'Y [pc]')
pyplot.xlim(-60, 60)
pyplot.ylim(-60, 60)
pyplot.scatter(x,y, c=colors[0], s=50, lw=0)
pyplot.savefig("Arches")
def plot_tracks(temperatures_original, luminosities_original,
temperatures_helium, luminosities_helium):
x_label = "T [K]"
y_label = "L [$L_\odot$]"
figure = single_frame(x_label, y_label, logx=True, logy=True,
xsize=14, ysize=10)
colors = get_distinct(2)
loglog(temperatures_original, luminosities_original, label='progenitor',
c=colors[0])
loglog(temperatures_helium, luminosities_helium, label='helium star',
c=colors[1])
scatter(temperatures_helium[-1], luminosities_helium[-1], marker='*',
s=400, c=colors[1])
xlabel('Effective Temperature')
ylabel('Luminosity')
pyplot.xlim(1.0e5, 4000)
pyplot.ylim(1.0,1.0e5)
pyplot.legend(loc=4, fontsize=24)
save_file = 'HertzsprungRussel_HeliumStar.png'
pyplot.savefig(save_file)
print '\nSaved figure in file', save_file,'\n'
pyplot.show()
def make_hydromap_and_show_picture(sph_particles, N=100, L=10):
x_label = "x [R$_\odot$]"
y_label = "y [R$_\odot$]"
fig = single_frame(x_label,
y_label,
logx=False,
logy=False,
xsize=12,
ysize=12)
hydro = Gadget2(converter)
hydro.gas_particles.add_particles(sph_particles)
x, y, z, vx, vy, vz = setup_grid(N, L)
rho, rhovx, rhovy, rhovz, rhoe = hydro.get_hydro_state_at_point(
x, y, z, vx, vy, vz)
rho = rhoe.reshape((N + 1, N + 1))
rho_e = make_map(hydro, N=50, L=L)
hydro.stop()
print("extrema:",
rho_e.value_in(units.erg / units.RSun**3).min(),
rho_e.value_in(units.erg / units.RSun**3).max())
cax = pyplot.imshow(numpy.log10(rho_e.value_in(units.erg / units.RSun**3)),
extent=[-L / 2, L / 2, -L / 2, L / 2],
vmin=4,
vmax=11)
cbar = fig.colorbar(cax,
ticks=[4, 7.5, 11],
orientation='vertical',
fraction=0.045)
cbar.ax.set_yticklabels(['Low', ' ', 'High']) # horizontal colorbar
cbar.set_label('mid-plane energy-density', rotation=270)
t = int(0.5 + gas.get_timestamp().value_in(units.s))
filename = "supernova_sph_T" + str(t) + ".pdf"
pyplot.savefig(filename)
def plot_tracks(temperatures_original, luminosities_original,
temperatures_helium, luminosities_helium):
x_label = "T [K]"
y_label = "L [$L_\odot$]"
figure = single_frame(x_label, y_label, logx=True, logy=True,
xsize=14, ysize=10)
colors = get_distinct(2)
loglog(temperatures_original, luminosities_original, label='progenitor',
c=colors[0])
loglog(temperatures_helium, luminosities_helium, label='helium star',
c=colors[1])
scatter(temperatures_helium[-1], luminosities_helium[-1], marker='*',
s=400, c=colors[1])
xlabel('Effective Temperature')
ylabel('Luminosity')
pyplot.xlim(1.0e5, 4000)
pyplot.ylim(1.0,1.0e5)
pyplot.legend(loc=4, fontsize=24)
save_file = 'HertzsprungRussel_HeliumStar.png'
pyplot.savefig(save_file)
print('\nSaved figure in file', save_file,'\n')
pyplot.show()
def plummer_model(N, x_label = 'x [length]', y_label='y [length]'):
fig = single_frame(x_label, y_label, xsize=8, ysize=8)
model = new_plummer_model(N)
plot_projected_density(model, col=0)
file = "plummer_model.png"
pyplot.savefig(file)
print('Saved figure in file', file)
def plummer_model(N, x_label = 'x [length]', y_label='y [length]'):
fig = single_frame(x_label, y_label, xsize=8, ysize=8)
model = new_plummer_model(N)
plot_projected_density(model, col=0)
file = "plummer_model.png"
pyplot.savefig(file)
print 'Saved figure in file', file
def plot_sph(time, sph, gas, i=1, L=10):
max_dens = sph.rho.max()
x_label = "X [R$_\odot$]"
y_label = "Y [R$_\odot$]"
fig = single_frame(x_label, y_label, logx=False, logy=False, xsize=12, ysize=12)
# rho=make_map(sph,N=200,L=L)
rho_e=make_e_map(sph,N=200,L=L)
print "extrema:", rho_e.value_in(units.erg/units.RSun**3).min(), rho_e.value_in(units.erg/units.RSun**3).max()
# pyplot.imshow(numpy.log10(rho_e.value_in(units.erg/units.RSun**3)), extent=[-L/2,L/2,-L/2,L/2],vmin=23,vmax=40)
pyplot.imshow(numpy.log10(rho_e.value_in(units.erg/units.RSun**3)), extent=[-L/2,L/2,-L/2,L/2],vmin=23,vmax=40, interpolation='bicubic', origin = 'lower', cmap="hot")
# cax = plot.imshow(rho, interpolation='bicubic', origin = 'lower', extent=[-5, 5, -5, 5], cmap="hot")
cbar = figure.colorbar(cax, ticks=[1.e-8, 0.5*max_dens, max_dens], orientation='vertical', fraction=0.045)
rmin = 0.0
rmid = "%.1f" % (0.5*max_dens)
rmax = "%.1f" % (max_dens)
cbar.ax.set_yticklabels([rmin, ' ', rmax]) # horizontal colorbar
cbar.set_label('mid-plane density [$g/cm^3$]', rotation=270)
pyplot.xlabel("x [R$_\odot$]")
pyplot.ylabel("y [R$_\odot$]")
t = int(0.5+sph.model_time.value_in(units.s))
filename = "supernova_sph_T"+str(t)+".pdf"
pyplot.savefig(filename)
def plot_hydro(time, sph, i, L=10):
x_label = "x [pc]"
y_label = "y [pc]"
fig = single_frame(x_label, y_label, logx=False, logy=False,
xsize=12, ysize=12)
rho = make_map(sph,N=200,L=L)
cax = pyplot.imshow(numpy.log10(1.e-5+rho.value_in(units.amu/units.cm**3)),
cmap="jet",
extent=[-L/2,L/2,-L/2,L/2],vmin=2,vmax=5)
if i==5:
cbar = fig.colorbar(cax, ticks=[2, 3, 4, 5], orientation='vertical', fraction=0.05)
cbar.ax.set_yticklabels([2, " ", " ", 5]) # horizontal colorbar
cbar.set_label('log projected density [$amu/cm^3$]', rotation=270)
"""
rhomin = numpy.log10(rho.value_in(units.amu/units.cm**3)).min()
rhomax = numpy.log10(rho.value_in(units.amu/units.cm**3)).max()
cax = pyplot.imshow(numpy.log10(1.e-5+rho.value_in(units.amu/units.cm**3)),
extent=[-L/2,L/2,-L/2,L/2],vmin=rhomin,vmax=rhomax)
rhomid = 0.5*(rhomin + rhomax)
print rhomin, rhomid, rhomax
cbar = fig.colorbar(cax, ticks=[rhomin, rhomid, rhomax], orientation='vertical', fraction=0.045)
# cbar.ax.set_yticklabels(['Low', ' ', 'High']) # horizontal colorbar
low = "%.2f" % rhomin
mid = "%.1f" % rhomid
mx = "%.2f" % rhomax
cbar.ax.set_yticklabels([low, mid, mx]) # horizontal colorbar
cbar.set_label('projected density [$amu/cm^3$]', rotation=270)
"""
pyplot.savefig("GMC_"+str(i)+".png")
def main(N, W0, t_end, Rvir, Mmin, Mmax):
bodies = generate_initial_conditions(N, W0, Rvir, Mmin, Mmax)
x_label = "t [Myr]"
y_label = "R [pc]"
fig = single_frame(x_label, y_label, logx=False, logy=False, xsize=14, ysize=12)
color = get_distinct(4)
time, Lr25, Lr50, Lr75 = run_only_gravity(bodies.copy(), t_end)
pyplot.plot(time.value_in(units.Myr), Lr25.value_in(units.parsec), c=color[0], label= 'without mass loss')
pyplot.plot(time.value_in(units.Myr), Lr50.value_in(units.parsec), c=color[0])
pyplot.plot(time.value_in(units.Myr), Lr75.value_in(units.parsec), c=color[0])
time, Lr25, Lr50, Lr75 = run_sequential_gravity_and_stellar(bodies.copy(), t_end)
pyplot.plot(time.value_in(units.Myr), Lr25.value_in(units.parsec), c=color[1], label= 'with mass loss')
pyplot.plot(time.value_in(units.Myr), Lr50.value_in(units.parsec), c=color[1])
pyplot.plot(time.value_in(units.Myr), Lr75.value_in(units.parsec), c=color[1])
time, Lr25, Lr50, Lr75 = run_event_driven_gravity_and_stellar(bodies.copy(), t_end)
pyplot.plot(time.value_in(units.Myr), Lr25.value_in(units.parsec), c=color[2], label= 'Event driven')
pyplot.plot(time.value_in(units.Myr), Lr50.value_in(units.parsec), c=color[2])
pyplot.plot(time.value_in(units.Myr), Lr75.value_in(units.parsec), c=color[2])
pyplot.legend(loc="upper left", ncol=1, shadow=False, fontsize=24)
#pyplot.show()
pyplot.savefig("gravity_stellar_comparison")
def plot_sph(sph, time):
L = 10
unit = units.g/units.cm**3
max_dens = sph.gas_particles.rho.value_in(unit).max()
print "Density extrema:", max_dens
x_label = "X [R$_\odot$]"
y_label = "Y [R$_\odot$]"
figure = single_frame(x_label, y_label, logx=False, logy=False, xsize=12, ysize=12)
rho_e=make_map(sph,N=50,L=L)
max_dens = rho_e.value_in(unit).max()
print "extrema:", rho_e.value_in(unit).min(), max_dens
cax = pyplot.imshow(rho_e.value_in(unit), extent=[-L/2,L/2,-L/2,L/2], interpolation='bicubic', origin='lower', cmap="hot", vmin=0.0, vmax=max_dens)
# cbar = figure.colorbar(cax, ticks=[-0.4*max_dens, 0.0*max_dens, 0.5*max_dens], orientation='vertical', fraction=0.045)
cbar = figure.colorbar(cax, ticks=[0.0, 0.5*max_dens, 0.99*max_dens], orientation='vertical', fraction=0.045)
rmin = "0.0"
rmid = "%.1f" % (0.5*max_dens)
rmax = "%.1f" % (max_dens)
print "min/max=", rmin, rmid, rmax
cbar.ax.set_yticklabels([rmin, ' ', rmax]) # horizontal colorbar
# cbar.ax.set_yticklabels(['a', 'b', 'c']) # horizontal colorbar
cbar.set_label('mid-plane density [$g/cm^3$]', rotation=270)
pyplot.xlabel("x [R$_\odot$]")
pyplot.ylabel("y [R$_\odot$]")
t = int(0.5+time.value_in(units.s))
filename = "supernova_sph_T"+str(t)+".pdf"
pyplot.savefig(filename)
pyplot.show()
def plot_e_sph(sph, time):
# pyplot.rcParams.update({'font.size': 30})
# figure = pyplot.figure(figsize=(12, 12))
L = 10
max_dens = sph.gas_particles.rho.value_in(units.g/units.cm**3).max()
print "Density extrema:", max_dens
x_label = "X [R$_\odot$]"
y_label = "Y [R$_\odot$]"
figure = single_frame(x_label, y_label, logx=False, logy=False, xsize=12, ysize=12)
rho_e=make_e_map(sph,N=20,L=L)
cax = pyplot.imshow(rho_e.value_in(units.erg/units.MSun**3), extent=[-L/2,L/2,-L/2,L/2], interpolation='bicubic', origin = 'lower', cmap="hot")
cbar = figure.colorbar(cax, ticks=[1.e-8, 0.5*max_dens, max_dens], orientation='vertical', fraction=0.045)
rmin = 0.0
rmid = "%.1f" % (0.5*max_dens)
rmax = "%.1f" % (max_dens)
cbar.ax.set_yticklabels([rmin, ' ', rmax]) # horizontal colorbar
cbar.set_label('mid-plane density [$erg/M_\odot^3$]', rotation=270)
pyplot.xlabel("x [R$_\odot$]")
pyplot.ylabel("y [R$_\odot$]")
t = int(0.5+time.value_in(units.s))
filename = "supernova_sph_T"+str(t)+".pdf"
pyplot.savefig(filename)
pyplot.show()
def main():
x_label = "$log_{10}[(t_{end}-t)/t_{MS}]$"
y_label = "$\zeta$"
figure = single_frame(x_label, y_label, logx=False, logy=False, xsize=14, ysize=10)
color = get_distinct(12)
pyplot.text(-2.2, 0.8, "giant branch")
pyplot.text(-0.1, 0.8, "main sequence")
pyplot.xlim(0.5, -4.)
pyplot.ylim(-0.6, 1.2)
fii = 0
ti=0
for dmi in dmdt:
for fi in filenames:
f = open(fi)
for line in f:
t, z, tms = process_file(f, dmi)
#print t, z, tms
for i in range(len(t)):
if z[i]<0:
ti = i
break
for i in range(len(t)):
t[i] = numpy.log10((t[-1]-t[i])/tms)
# pyplot.scatter(t, z)
pyplot.plot(t[ti:], z[ti:], c=color[fii], ls=ls[fii], lw=lw[fii])
f.close()
fii += 1
pyplot.show()
def main(N, t_end):
t_end = t_end | nbody_system.time
Q_init = 0.2
particles = new_plummer_model(N)
codes = [ph4, Huayno, BHTree]
cols = get_distinct(3)
ci = 0
x_label = "time [N-body units]"
y_label = "virial ratio $Q$"
figure = single_frame(x_label, y_label, xsize=14, ysize=10)
ax1 = pyplot.gca()
ax1.set_xlim(0, t_end.value_in(t_end.unit))
ax1.set_ylim(0, 0.65)
pyplot.plot([0, t_end.value_in(t_end.unit)], [0.5, 0.5],
lw=1,
ls='--',
c='k')
for code in codes:
time, Q = virial_ratio_evolution(code, particles, Q_init, t_end)
pyplot.plot(time.value_in(t_end.unit), Q, c=cols[ci])
ci += 1
save_file = 'gravity_to_virial.png'
pyplot.savefig(save_file)
print("\nOutput saved in", save_file, '\n')
pyplot.show()
def fractal_model(N, F=1.6, x_label='x [length]', y_label='y [length]'):
fig = single_frame(x_label, y_label, xsize=8, ysize=8)
ax = pyplot.gca()
model = new_fractal_cluster_model(N=N,
fractal_dimension=1.6,
random_seed=42)
plot_projected_density(model, col=2)
pyplot.savefig("fractal_model")
def king_model(N, W=9, x_label = 'x [length]', y_label='y [length]'):
fig = single_frame(x_label, y_label, xsize=8, ysize=8)
ax = pyplot.gca()
model = new_king_model(N, W)
plot_projected_density(model, col=1)
file = "king_model.png"
pyplot.savefig(file)
print('Saved figure in file', file)
def galaxy_model(N, x_label = 'x [length]', y_label='y [length]'):
fig = single_frame(x_label, y_label, xsize=8, ysize=8)
ax = pyplot.gca()
model = new_halogen_model(N, alpha=1., beta=5., gamma=0.5)
plot_projected_density(model, col=3)
file = "galaxy_model.png"
pyplot.savefig(file)
print 'Saved figure in file', file
def galaxy_model(N, x_label = 'x [length]', y_label='y [length]'):
fig = single_frame(x_label, y_label, xsize=8, ysize=8)
ax = pyplot.gca()
model = new_halogen_model(N, alpha=1., beta=5., gamma=0.5)
plot_projected_density(model, col=3)
file = "galaxy_model.png"
pyplot.savefig(file)
print('Saved figure in file', file)
def king_model(N, W=9, x_label = 'x [length]', y_label='y [length]'):
fig = single_frame(x_label, y_label, xsize=8, ysize=8)
ax = pyplot.gca()
model = new_king_model(N, W)
plot_projected_density(model, col=1)
file = "king_model.png"
pyplot.savefig(file)
print 'Saved figure in file', file
def main(N, W0, t_end, Rvir, Mmin, Mmax):
bodies = generate_initial_conditions(N, W0, Rvir, Mmin, Mmax)
print(numpy.sort(bodies.mass.value_in(units.MSun)))
x_label = "t [Myr]"
y_label = "R [pc]"
fig = single_frame(x_label,
y_label,
logx=False,
logy=False,
xsize=14,
ysize=12)
color = get_distinct(4)
time, Lr25, Lr50, Lr75 = run_only_gravity(bodies.copy(), t_end)
pyplot.plot(time.value_in(units.Myr),
Lr25.value_in(units.parsec),
c=color[0],
label='without mass loss')
pyplot.plot(time.value_in(units.Myr),
Lr50.value_in(units.parsec),
c=color[0])
pyplot.plot(time.value_in(units.Myr),
Lr75.value_in(units.parsec),
c=color[0])
time, Lr25, Lr50, Lr75 \
= run_sequential_gravity_and_stellar(bodies.copy(), t_end)
pyplot.plot(time.value_in(units.Myr),
Lr25.value_in(units.parsec),
c=color[1],
label='with mass loss')
pyplot.plot(time.value_in(units.Myr),
Lr50.value_in(units.parsec),
c=color[1])
pyplot.plot(time.value_in(units.Myr),
Lr75.value_in(units.parsec),
c=color[1])
time, Lr25, Lr50, Lr75 \
= run_event_driven_gravity_and_stellar(bodies.copy(), t_end)
pyplot.plot(time.value_in(units.Myr),
Lr25.value_in(units.parsec),
c=color[2],
label='event driven')
pyplot.plot(time.value_in(units.Myr),
Lr50.value_in(units.parsec),
c=color[2])
pyplot.plot(time.value_in(units.Myr),
Lr75.value_in(units.parsec),
c=color[2])
pyplot.legend(loc="upper left", ncol=1, shadow=False, fontsize=24)
save_file = 'gravity_stellar_comparison.png'
pyplot.savefig(save_file)
print('\nSaved figure in file', save_file, '\n')
pyplot.show()
def fractal_model(N, F=1.6, x_label = 'x [length]', y_label='y [length]'):
fig = single_frame(x_label, y_label, xsize=8, ysize=8)
ax = pyplot.gca()
model = new_fractal_cluster_model(N=N, fractal_dimension=1.6,
random_seed=42)
plot_projected_density(model, col=2)
file = "fractal_model.png"
pyplot.savefig(file)
print 'Saved figure in file', file
def fractal_model(N, F=1.6, x_label = 'x [length]', y_label='y [length]'):
fig = single_frame(x_label, y_label, xsize=8, ysize=8)
ax = pyplot.gca()
model = new_fractal_cluster_model(N=N, fractal_dimension=1.6,
random_seed=42)
plot_projected_density(model, col=2)
file = "fractal_model.png"
pyplot.savefig(file)
print('Saved figure in file', file)
def main(**options):
print("calculating shock using exact solution")
exact = CalculateExactSolutionIn1D()
xpositions, rho, p, u = exact.get_solution_at_time(0.12 | time)
print("calculating shock using code")
model = CalculateSolutionIn3D(**options)
grids = model.get_solution_at_time(0.12 | time)
print("sampling grid")
if model.name_of_the_code in model.sph_hydro_codes:
samples = grids
else:
samplepoints = [(x, 0.5, 0.5) | length
for x in numpy.linspace(0.0, 1.0, 2000)]
print(len(grids))
samples = SamplePointsOnMultipleGrids(grids, samplepoints,
SamplePointOnCellCenter)
print(len(samples))
samples.filterout_duplicate_indices()
print(len(samples))
print("saving data")
filename = "riemann_shock_tube_rho_" + model.name_of_the_code
store_attributes(xpositions, rho, u, p, filename=filename + "_exact.csv")
store_attributes(samples.x,
samples.rho,
samples.rhovx,
samples.energy,
filename=filename + ".csv")
if IS_PLOT_AVAILABLE:
print("plotting solution")
from prepare_figure import single_frame
from distinct_colours import get_distinct
x_label = "[length]"
y_label = "[mass/length$^3$]"
figure = single_frame(x_label,
y_label,
logx=False,
logy=True,
xsize=14,
ysize=10)
color = get_distinct(2)
plot.plot(xpositions, rho, c=color[0])
plot.scatter(samples.x, samples.rho, c=color[1], s=100)
# pyplot.xlim(0.3,0.7)
# pyplot.ylim(0.5,4.5)
pyplot.xlim(0.0, 1.0)
# pyplot.ylim(0.5,4.5)
pyplot.xlabel("[length]")
pyplot.ylabel("[mass/length$^3$]")
# pyplot.savefig("riemann_shock_tube_rho_"+model.name_of_the_code+".png")
pyplot.savefig(filename)
pyplot.show()
def energy_plot(time, E_kin, E_pot, E_therm, figname):
if not HAS_MATPLOTLIB:
return
x_label = 'Time [hour]'
y_label = 'Energy [foe]'
single_frame(x_label, y_label, logx=False, logy=False, xsize=14, ysize=10, ymin=-1, ymax=-1)
cols = get_distinct(4)
FOE = 1.e+51 | units.erg
hour = 1|units.hour
pyplot.plot(time/hour, E_kin/FOE, label='E_kin', c=cols[0])
pyplot.plot(time/hour, E_pot/FOE, label='E_pot', c=cols[1])
pyplot.plot(time/hour, E_therm/FOE, label='E_therm', c=cols[2])
pyplot.plot(time/hour, (E_kin+E_pot+E_therm)/FOE, label='E_total', c=cols[3])
pyplot.legend(loc=4)
pyplot.savefig(figname)
print "\nPlot of energy evolution was saved to: ", figname
pyplot.close()
def plot_hydro(time, sph, i, L=10):
x_label = "x [pc]"
y_label = "y [pc]"
fig = single_frame(x_label, y_label, logx=False, logy=False, xsize=12, ysize=12)
# fig=pyplot.figure(figsize=(12,12))
rho=make_map(sph,N=200,L=L)
pyplot.imshow(numpy.log10(1.e-5+rho.value_in(units.amu/units.cm**3)), extent=[-L/2,L/2,-L/2,L/2],vmin=1,vmax=5)
pyplot.savefig("GMC_"+str(i)+".png")
def plot_cluster(x, y):
from prepare_figure import single_frame, get_distinct
colors = get_distinct(1)
f = single_frame('X [kpc]', 'Y [kpc]')
pyplot.xlim(-10, 10)
pyplot.ylim(-10, 10)
pyplot.scatter(x,y, c=colors[0], s=50, lw=0)
pyplot.show()
def plot_cluster(x, y):
from prepare_figure import single_frame, get_distinct
colors = get_distinct(1)
f = single_frame('X [kpc]', 'Y [kpc]')
pyplot.xlim(-10, 10)
pyplot.ylim(-10, 10)
pyplot.scatter(x, y, c=colors[0], s=50, lw=0)
pyplot.show()
def main():
"""
Mb = (2. + 1.) | units.MSun
Mb = 2. | units.MSun
a0 = 10. | units.AU
# vs = 35. | units.kms
vs = 30. | units.kms
Mdot_donor = 0.11 |units.MSun/units.Myr
Mdot = Bondi_Hoyle_Littleton_accretion_rate(Mb, vs, a0, Mdot_donor)
print Mdot.in_(units.MEarth/units.yr)
t = numpy.arange(0, 3, 0.1) | units.yr
mdot = Mdot*t
t += 4 | units.yr
"""
Mb = (2. + 1.) | units.MSun
Mb = 2. | units.MSun
a0 = 10. | units.AU
#vs = 30. | units.kms
# vs = 18. | units.kms
vs = 17.26 | units.kms
vorb = numpy.sqrt(constants.G*Mb/a0)
print "vorb=", vorb.in_(units.kms)
k = vorb/vs
m1 = 1.924785833858|units.MSun
m2 = 1.|units.MSun
mu = m2/(m1+m2)
Mdot_donor = 0.11 |units.MSun/units.Myr
cvw = 0.
print "k and mu:", k, mu
Mdot = Mdot_donor * mu**2 * k**4/(1 + k**2 + cvw**2)**(3./2.)
# print "Mdot:", Mdot.in_(units.MEarth/units.yr)
print "Mdot:", Mdot.in_(units.MSun/units.Myr)
t = numpy.arange(0, 3, 0.1) | units.yr
mdot = Mdot*t
t += 4.2 | units.yr
c = get_distinct(3)
x_label = 't [yr]'
y_label = 'M [$10^{-9}$M$_{\odot}$]'
figure = single_frame(x_label, y_label, logy=False, xsize=14, ysize=10)
filename = "hydro_give_or_take.data"
print t, mdot.value_in(units.MSun)
mdot /= (1.e-9|units.MSun)
pyplot.plot(t.value_in(units.yr), mdot, c=c[2])
plot_accretion_from_wind(filename, c[0])
filename = "hydro_give_or_take_gravity_NoG.data"
plot_accretion_from_wind(filename, c[1])
pyplot.savefig("hydro_accretion_from_windy_star")
def hierarchical_king_model(N, W=9, x_label = 'x [length]', y_label='y [length]'):
fig = single_frame(x_label, y_label, xsize=8, ysize=8)
ax = pyplot.gca()
model_com = new_king_model(6, W/3.)
for i in range(6):
model = new_king_model(int(N/4.), W)
model.position += model_com[i].position
plot_projected_density(model, col=1)
file = "hierarchical_king_model.png"
pyplot.savefig(file)
print('Saved figure in file', file)
def hierarchical_king_model(N, W=9, x_label = 'x [length]', y_label='y [length]'):
fig = single_frame(x_label, y_label, xsize=8, ysize=8)
ax = pyplot.gca()
model_com = new_king_model(6, W/3.)
for i in range(6):
model = new_king_model(int(N/4.), W)
model.position += model_com[i].position
plot_projected_density(model, col=1)
file = "hierarchical_king_model.png"
pyplot.savefig(file)
print 'Saved figure in file', file
def main():
"""
Mb = (2. + 1.) | units.MSun
Mb = 2. | units.MSun
a0 = 10. | units.AU
# vs = 35. | units.kms
vs = 30. | units.kms
Mdot_donor = 0.11 |units.MSun/units.Myr
Mdot = Bondi_Hoyle_Littleton_accretion_rate(Mb, vs, a0, Mdot_donor)
print Mdot.in_(units.MEarth/units.yr)
t = numpy.arange(0, 3, 0.1) | units.yr
mdot = Mdot*t
t += 4 | units.yr
"""
Mb = (2. + 1.) | units.MSun
Mb = 2. | units.MSun
a0 = 10. | units.AU
#vs = 30. | units.kms
# vs = 18. | units.kms
vs = 17.26 | units.kms
vorb = numpy.sqrt(constants.G * Mb / a0)
print "vorb=", vorb.in_(units.kms)
k = vorb / vs
m1 = 1.924785833858 | units.MSun
m2 = 1. | units.MSun
mu = m2 / (m1 + m2)
Mdot_donor = 0.11 | units.MSun / units.Myr
cvw = 0.
print "k and mu:", k, mu
Mdot = Mdot_donor * mu**2 * k**4 / (1 + k**2 + cvw**2)**(3. / 2.)
# print "Mdot:", Mdot.in_(units.MEarth/units.yr)
print "Mdot:", Mdot.in_(units.MSun / units.Myr)
t = numpy.arange(0, 3, 0.1) | units.yr
mdot = Mdot * t
t += 4.2 | units.yr
c = get_distinct(3)
x_label = 't [yr]'
y_label = 'M [$10^{-9}$M$_{\odot}$]'
figure = single_frame(x_label, y_label, logy=False, xsize=14, ysize=10)
filename = "hydro_give_or_take.data"
print t, mdot.value_in(units.MSun)
mdot /= (1.e-9 | units.MSun)
pyplot.plot(t.value_in(units.yr), mdot, c=c[2])
plot_accretion_from_wind(filename, c[0])
filename = "hydro_give_or_take_gravity_NoG.data"
plot_accretion_from_wind(filename, c[1])
pyplot.savefig("hydro_accretion_from_windy_star")
def main(filename=None, lim=-1):
if filename is None: return
try:
amusedir = os.environ['AMUSE_DIR']
dir = amusedir+'/examples/textbook/'
except:
print 'Environment variable AMUSE_DIR not set'
dir = './'
filename = dir+filename
from matplotlib import pyplot, rc
x_label = "N"
y_label = "$t_{wall} [s]$"
figure = single_frame(x_label, y_label, logx=True, logy=True,
xsize=14, ysize=10)
npp = [12, 512]
ntc = [1024, 2000*1024]
tpp = map(lambda x: 0.01*x*x, npp)
ttc = map(lambda x: 1.e-6*(x*math.log(x)), ntc)
pyplot.plot(npp, tpp, c='k', ls='-', lw=4)
pyplot.plot(ntc, ttc, c='k', ls='-', lw=4)
pyplot.text(12, 8, '$N^2$')
pyplot.text(2.e+3, 0.005, '$N \log (N)$')
for ii, I in enumerate(Integrator):
# sample line: I= Hermite T= 1 time N= 4 M= 1.0 mass \
# E= -0.250000002735 mass * length**2 * time**-2 \
# Q= -0.451489790632 dE= -1.09402279371e-08 \
# Time= 2.04415297508 0.000992059707642
x = read_file(filename, 6, I)
y1 = read_file(filename, 22, I)
y2 = read_file(filename, 23, I)
for i in range(len(y1)):
y1[i] *= 0.1
y2[i] *= 0.1
if len(x) > 0:
pyplot.plot(x, y2, label=I, c=color[ii],
lw=lwidth[ii], ls=lstyles[ii])
pyplot.scatter(x, y2, c=color[ii], lw=0, s=200)
pyplot.legend(loc="lower right", fontsize=18)
save_file = "Nbody_performance.png"
pyplot.savefig(save_file)
print "\nSaved figure in file", save_file,'\n'
pyplot.show()
def plot_cluster(x, y):
from prepare_figure import single_frame, get_distinct
colors = get_distinct(1)
f = single_frame('X [pc]', 'Y [pc]')
pyplot.xlim(-60, 60)
pyplot.ylim(-60, 60)
pyplot.scatter(x,y, c=colors[0], s=50, lw=0)
save_file = 'Arches Fig. 7.1.png'
pyplot.savefig(save_file)
print '\nSaved figure in file', save_file, '\n'
pyplot.show()
def plot_cluster(x, y):
from prepare_figure import single_frame, get_distinct
colors = get_distinct(1)
f = single_frame('X [pc]', 'Y [pc]')
pyplot.xlim(-60, 60)
pyplot.ylim(-60, 60)
pyplot.scatter(x, y, c=colors[0], s=50, lw=0)
save_file = 'Arches Fig. 7.1.png'
pyplot.savefig(save_file)
print('\nSaved figure in file', save_file, '\n')
pyplot.show()
def main(filename="NbodyAMUSE.test", lim=-1):
#I= Hermite T= 1 time N= 4 M= 1.0 mass E= -0.250000002735 mass * length**2 * time**-2 Q= -0.451489790632 dE= -1.09402279371e-08 Time= 2.04415297508 0.000992059707642
from matplotlib import pyplot, rc
x_label = "N"
y_label = "$t_{wall} [s]$"
figure = single_frame(x_label,
y_label,
logx=True,
logy=True,
xsize=12,
ysize=10)
npp = [12, 512]
ntc = [1024, 2000 * 1024]
tpp = map(lambda x: 0.01 * x * x, npp)
ttc = map(lambda x: 1.e-6 * (x * math.log(x)), ntc)
pyplot.plot(npp, tpp, c='k', ls='-', lw=4)
pyplot.plot(ntc, ttc, c='k', ls='-', lw=4)
pyplot.text(12, 8, '$N^2$')
pyplot.text(2.e+3, 0.005, '$N \log (N)$')
for ii, I in enumerate(Integrator):
x = read_file(filename, 6, I)
y1 = read_file(filename, 22, I)
y2 = read_file(filename, 23, I)
for i in range(len(y1)):
y1[i] *= 0.1
y2[i] *= 0.1
# pyplot.plot(x, y1, label=I, c=color[ii], lw=1,ls=lstyles[ii])
# pyplot.scatter(x, y1, c=color[ii])
if len(x) > 0:
pyplot.plot(x,
y2,
label=I,
c=color[ii],
lw=lwidth[ii],
ls=lstyles[ii])
pyplot.scatter(x, y2, c=color[ii], lw=0, s=200)
# pyplot.plot(x, y1, label=I, c=color[ii], lw=2,ls=lstyles[ii])
# pyplot.plot(x, y2, c=color[ii], lw=3.0,ls=lstyles[ii])
# pyplot.legend(loc="upper left")
###### pyplot.legend(loc="lower right")
# pyplot.xlabel("N")
# pyplot.ylabel("t$_{wall}$ [s]")
# pyplot.loglog()
# pyplot.show()
pyplot.savefig("Nbody_performance")
def make_plot(disk1, disk2, filename):
x_label = "X [kpc]"
y_label = "Y [kpc]"
figure = single_frame(x_label, y_label, logy=False, xsize=14, ysize=14)
from distinct_colours import get_distinct
c = get_distinct(2)
pyplot.xlim(-300, 300)
pyplot.ylim(-300, 300)
pyplot.scatter(disk1.x.value_in(units.kpc), disk1.y.value_in(units.kpc),
c=c[0], alpha=1, s=1, lw=0)
pyplot.scatter(disk2.x.value_in(units.kpc), disk2.y.value_in(units.kpc),
c=c[1], alpha=1, s=1, lw=0)
pyplot.savefig(filename)
def plot_cloud(x, y):
from prepare_figure import single_frame, get_distinct
colors = get_distinct(1)
frame = single_frame('X [pc]', 'Y [pc]')
pyplot.title('Cloud particle positions')
pyplot.xlim(-200, 200)
pyplot.ylim(-200, 200)
pyplot.scatter(x, y, c=colors[0], s=50, lw=0)
save_file = 'positions_M1e5.png'
pyplot.savefig(save_file)
print '\nSaved figure in file', save_file, '\n'
pyplot.show()
def main(filename="hydro.hdf5", lim=None, image_id=-1, nice_plot=1):
x_label = 'x'
y_label = 'y'
figure = single_frame(x_label, y_label, logy=False, xsize=14, ysize=10)
stars = read_set_from_file(filename, "hdf5")
print stars
snapshot_id = 0
isgas = True
snapshot_id = 0
sinks = Particles(0)
for si in stars.history:
if isgas:
gas = si
isgas = False
else:
sinks = si
isgas = True
if not isgas:
snapshot_id += 1
time = gas.get_timestamp()
if image_id < 0 or image_id == snapshot_id:
pyplot.hist2d(gas.x.value_in(units.AU),
gas.y.value_in(units.AU), (200, 200),
cmap=plt.cm.jet)
pyplot.scatter(gas.x.value_in(units.AU),
gas.y.value_in(units.AU),
c='y',
s=100)
if False:
for gi in gas:
pyplot.arrow(gi.x.value_in(units.AU),
gi.y.value_in(units.AU),
gi.vx.value_in(units.AU / units.yr),
gi.vy.value_in(units.AU / units.yr),
head_width=0.05,
head_length=0.1)
# sph_particles_plot(gas, u_range=[min(gas.u), max(gas.u)], width=lim, alpha = 1)
# if len(sinks):
# scatter(sinks.x.value_in(units.AU), sinks.y.value_in(units.AU), c='y', s=100)
if image_id == snapshot_id:
break
pyplot.xlabel("X [pc]")
pyplot.ylabel("Y [pc]")
pyplot.show()
def main(t_end, mass, z, Tstar, Lstar):
stellar_evolution_codes = [SeBa(), SSE(), MESA(), EVtwin()]
label = ["SeBa", "SSE", "MESA", "EVtwin"]
marker = ["o", "v", "<", ">"]
# color = [0, 1, 2, 3, 4]
x_label = "$(T-T_\odot)/T_\odot)$"
y_label = "$(L-L_\odot)/L_\odot)$"
figure = single_frame(x_label, y_label, logy=False, xsize=14, ysize=10)
pyplot.xlim(-0.008, 0.004)
color = get_distinct(6)
pyplot.scatter([0], [0], marker="o", c=color[3], label="Sun", s=400, lw=0)
for si in range(len(stellar_evolution_codes)):
stellar = stellar_evolution_codes[si]
stellar.parameters.metallicity = z
star = Particles(1)
star.mass = mass
stellar.particles.add_particles(star)
stellar.evolve_model(t_end)
T = (stellar.particles.temperature - Tstar) / Tstar
L = (stellar.particles.luminosity - Lstar) / Lstar
if si == 3:
pyplot.scatter(T,
L,
marker=marker[si],
color=color[0],
label=label[si],
s=300,
lw=0)
else:
pyplot.scatter(T,
L,
marker=marker[si],
color=color[si],
label=label[si],
s=300,
lw=0)
stellar.stop()
pyplot.legend(scatterpoints=1, loc=2)
# pyplot.show()
pyplot.savefig("fig_SunComparison")
def XX_plot_sph(time, sph, gas, i=1, L=10):
x_label = "x [R$_\odot$]"
y_label = "y [R$_\odot$]"
fig = single_frame(x_label, y_label, logx=False, logy=False, xsize=12, ysize=12)
# rho=make_map(sph,N=200,L=L)
rho_e=make_e_map(sph,N=200,L=L)
# pyplot.hist(numpy.log10(rho_e.value_in(units.erg/units.RSun**3)))
# pyplot.show()
print "extrema:", rho_e.value_in(units.erg/units.RSun**3).min(), rho_e.value_in(units.erg/units.RSun**3).max()
# pyplot.imshow(numpy.log10(1.e-8+rho.value_in(units.amu/units.cm**3)), extent=[-L/2,L/2,-L/2,L/2],vmin=1,vmax=5)
pyplot.imshow(numpy.log10(rho_e.value_in(units.erg/units.RSun**3)), extent=[-L/2,L/2,-L/2,L/2],vmin=23,vmax=40)
# pyplot.imshow(numpy.log10(1.e-5+rho.value_in(units.amu/units.cm**3)), extent=[-L/2,L/2,-L/2,L/2],vmin=1,vmax=5)
#pyplot.scatter(gas.x.value_in(units.RSun), gas.y.value_in(units.RSun))#, alpha=0.05)
t = int(0.5+sph.model_time.value_in(units.s))
filename = "supernova_sph_T"+str(t)+".pdf"
pyplot.savefig(filename)
def main(M1, M2, M3, Pora, Pin, ain, aout, ein, eout,
t_end, nsteps, scheme, dtse_fac):
from matplotlib import pyplot
x_label = "$a/a_{0}$"
y_label = "$e/e_{0}$"
fig = single_frame(x_label, y_label, logx=False, logy=False,
xsize=10, ysize=8)
color = get_distinct(4)
if scheme == 0:
srange = [1,2,3]
else:
srange = [scheme]
i = 0
for s in srange:
time, ai, ei, ao, eo = evolve_triple_with_wind(M1, M2, M3,
Pora, Pin,
ain, aout,
ein, eout,
t_end, nsteps,
s, dtse_fac)
if i == 0:
pyplot.plot(ai, ei, c=color[0], label='inner')
pyplot.plot(ao, eo, c=color[1], label='outer')
i = 1
else:
pyplot.plot(ai, ei, c=color[0])
pyplot.plot(ao, eo, c=color[1])
pyplot.legend(loc='best', ncol=1, shadow=False, fontsize=20)
#save_file = 'evolve_triple_with_wind.png'
save_file = 'evolve_triple_with_wind' \
+'_s={:d}_dtse={:.3f}'.format(scheme, dtse_fac) \
+'.png'
pyplot.savefig(save_file)
print '\nSaved figure in file', save_file,'\n'
pyplot.show()
def main(N, t_end):
t_end = t_end | nbody_system.time
Q_init = 0.2
particles = new_plummer_model(N)
codes = [ph4, Huayno, BHTree]
cols = get_distinct(3)
ci = 0
x_label = "time [N-body units]"
# y_label = "$Q [\equiv -E_{\rm kin}/E_{\rm pot}]$"
y_label = "virial ratio $Q$"
figure = single_frame(x_label, y_label, xsize=14, ysize=10)
ax1 = pyplot.gca()
ax1.set_xlim(0, t_end.value_in(t_end.unit))
ax1.set_ylim(0, 0.65)
pyplot.plot([0, t_end.value_in(t_end.unit)], [0.5, 0.5], lw=1, ls='--', c='k')
for code in codes:
time, Q = virial_ratio_evolution(code, particles, Q_init, t_end)
pyplot.plot(time.value_in(t_end.unit), Q, c=cols[ci])
ci+=1
# pyplot.show()
pyplot.savefig("gravity_to_virial")
def make_hydromap_and_show_picture(sph_particles, N=100, L=10):
x_label = "x [R$_\odot$]"
y_label = "y [R$_\odot$]"
fig = single_frame(x_label, y_label, logx=False, logy=False, xsize=12, ysize=12)
hydro = Gadget2(converter)
hydro.gas_particles.add_particles(sph_particles)
x, y, z, vx, vy, vz = setup_grid(N, L)
rho,rhovx,rhovy,rhovz,rhoe=hydro.get_hydro_state_at_point(x,y,z,vx,vy,vz)
rho=rhoe.reshape((N+1,N+1))
rho_e=make_map(hydro,N=50,L=L)
hydro.stop()
print "extrema:", rho_e.value_in(units.erg/units.RSun**3).min(), rho_e.value_in(units.erg/units.RSun**3).max()
cax = pyplot.imshow(numpy.log10(rho_e.value_in(units.erg/units.RSun**3)), extent=[-L/2,L/2,-L/2,L/2],vmin=4,vmax=11)
cbar = fig.colorbar(cax, ticks=[4, 7.5, 11], orientation='vertical', fraction=0.045)
cbar.ax.set_yticklabels(['Low', ' ', 'High']) # horizontal colorbar
cbar.set_label('mid-plane energy-density', rotation=270)
t = int(0.5+gas.get_timestamp().value_in(units.s))
filename = "supernova_sph_T"+str(t)+".pdf"
pyplot.savefig(filename)
def plot_ionization_fraction(pos, xion):
r = [] | units.parsec
x = []
for pi, xi in zip(pos, xion):
r.append(pi.length())
x.append(xi)
r, x = zip(*sorted(zip(r.value_in(units.parsec), x)))
R, X = binned_mean_data(r, x)
from matplotlib import pyplot
x_label = "r [pc]"
y_label = r'$\xi_{\rm ion}$'
figure = single_frame(x_label, y_label, logx=False, logy=False,
xsize=14, ysize=8)
pyplot.scatter(r, x, c=get_distinct(1), lw=0, s=100)
pyplot.plot(R, X, c=get_distinct(2)[1], lw=2)
pyplot.xlim(0, 6)
pyplot.ylim(-0.04, 1.19)
pyplot.savefig("fig_ionization_of_GMC")
pyplot.show()
def plot_hydro(time, sph, i, L=10):
x_label = "x [pc]"
y_label = "y [pc]"
fig = single_frame(x_label, y_label, logx=False, logy=False, xsize=12, ysize=12)
gas = sph.code.gas_particles
dmp = sph.code.dm_particles
#rho=make_map(sph,N=200,L=L)
# pyplot.imshow(numpy.log10(1.e-5+rho.value_in(units.amu/units.cm**3)), extent=[-L/2,L/2,-L/2,L/2],vmin=1,vmax=5, origin="lower")
# pyplot.hist2d(gas.x.value_in(units.parsec),
# gas.y.value_in(units.parsec),
# (100, 100), cmap=pyplot.cm.jet)
# pyplot.scatter(gas.x.value_in(units.parsec),
# gas.y.value_in(units.parsec), s=500, lw=0, alpha=0.1, c='r')
x = gas.x.value_in(units.parsec)
y = gas.y.value_in(units.parsec)
z = gas.rho.value_in(units.g/units.cm**3)
#z = gas.u.value_in(units.g/units.cm**3),
#cax = pyplot.tripcolor(gas.x.value_in(units.parsec),
# gas.y.value_in(units.parsec),
# z,
# shading='flat') #, cmap=plt.cm.rainbow)
# #shading='gouraud') #, cmap=plt.cm.rainbow)
import matplotlib.tri as tri
triang = tri.Triangulation(x, y)
xmid = x[triang.triangles].mean(axis=1)
ymid = y[triang.triangles].mean(axis=1)
min_radius = 0.01
mask = numpy.where(xmid*xmid + ymid*ymid < min_radius*min_radius, 1, 0)
triang.set_mask(mask)
# pyplot.tripcolor(triang, z, shading='gouraud', cmap=pyplot.cm.rainbow)
pyplot.tripcolor(triang, z, cmap=pyplot.cm.rainbow)
pyplot.xlim(-1, 1)
pyplot.ylim(-1, 1)
if len(dmp):
m = 2.0*dmp.mass/dmp.mass.max()
print m
pyplot.scatter(dmp.x.value_in(units.parsec), dmp.y.value_in(units.parsec), c='k', s=m)
pyplot.savefig("GMCsink_"+str(i)+".png")
def main(filename = "NbodyAMUSE.test", lim=-1):
#I= Hermite T= 1 time N= 4 M= 1.0 mass E= -0.250000002735 mass * length**2 * time**-2 Q= -0.451489790632 dE= -1.09402279371e-08 Time= 2.04415297508 0.000992059707642
from matplotlib import pyplot, rc
x_label = "N"
y_label = "$t_{wall} [s]$"
figure = single_frame(x_label, y_label, logx=True, logy=True, xsize=12, ysize=10)
npp = [12, 512]
ntc = [1024, 2000*1024]
tpp = map(lambda x: 0.01*x*x, npp)
ttc = map(lambda x: 1.e-6*(x*math.log(x)), ntc)
pyplot.plot(npp, tpp, c='k', ls='-', lw=4)
pyplot.plot(ntc, ttc, c='k', ls='-', lw=4)
pyplot.text(12, 8, '$N^2$')
pyplot.text(2.e+3, 0.005, '$N \log (N)$')
for ii, I in enumerate(Integrator):
x = read_file(filename, 6, I)
y1 = read_file(filename, 22, I)
y2 = read_file(filename, 23, I)
for i in range(len(y1)):
y1[i] *= 0.1
y2[i] *= 0.1
# pyplot.plot(x, y1, label=I, c=color[ii], lw=1,ls=lstyles[ii])
# pyplot.scatter(x, y1, c=color[ii])
if len(x)>0:
pyplot.plot(x, y2, label=I, c=color[ii], lw=lwidth[ii], ls=lstyles[ii])
pyplot.scatter(x, y2, c=color[ii], lw=0, s=200)
# pyplot.plot(x, y1, label=I, c=color[ii], lw=2,ls=lstyles[ii])
# pyplot.plot(x, y2, c=color[ii], lw=3.0,ls=lstyles[ii])
# pyplot.legend(loc="upper left")
###### pyplot.legend(loc="lower right")
# pyplot.xlabel("N")
# pyplot.ylabel("t$_{wall}$ [s]")
# pyplot.loglog()
# pyplot.show()
pyplot.savefig("Nbody_performance")
