f1.cylinder([0.1 * pc, 0.3 * pc],
1e-4 * pc,
abund_pars=[1e-6, 0.05 * pc, -0.15],
temp_pars=[200, 0.02 * pc, -0.15, -0.17 * pc],
dummy_frac=0.5)
lims = np.array([-0.3, 0.3]) * pc
pm.scatter3D(f1.GRID,
f1.density,
np.mean(f1.density),
axisunit=pc,
colordim=f1.temperature,
colorlabel='T [K]',
NRand=10000,
cmap='nipy_spectral_r',
xlim=lims,
ylim=lims,
zlim=lims,
azim=45,
elev=15,
output='fig_filament_temp.png',
show=True)
pm.scatter3D(f1.GRID,
f1.density,
np.min(f1.density),
axisunit=pc,
colordim=f1.abundance,
colorlabel='Molec. abund.',
NRand=10000,
#WRITING RADMC-3D FILES
#----------------------
prop = {'dens_e': density.total,
'dens_ion': density.total,
'temp_gas': temperature.total}
Rad = rt.Radmc3dDefaults(GRID)
Rad.freefree(prop)
#------------------------------------
#3D PLOTTING (weighting with density)
#------------------------------------
tag = 'ctsphere_HII'
weight = dens_e
"""
Plot_model.scatter3D(GRID, density.total, weight, power=0, NRand = 4000, colordim = density.total / 1e6 / 1e5, axisunit = u.au, cmap = 'winter',
marker = 'o', colorlabel = r'$n_{\rm e}$ [cm$^{-3}$] x $10^5$', output = '3Ddens_%s.png'%tag, show = True)
Plot_model.scatter3D(GRID, density.total, weight, power=0, NRand = 4000, colordim = temperature.total, axisunit = u.au, cmap = 'winter',
marker = 'o', colorlabel = r'$T_{\rm e}$ [Kelvin]', output = '3Dtemp_%s.png'%tag, show = True)
"""
fig = plt.figure(figsize=(6.4,4.8))
#ax = plt.axes(projection='3d')
lims = np.array([-sizex,sizex]) / u.au
canvas3d = Plot_model.Canvas3d(fig=fig, ax_kw={'xlim': lims, 'ylim': lims, 'zlim': lims, 'azim': -50, 'elev': 30})
ax = canvas3d.ax #generated with fig.add_axes from matplotlib. All the matplotlib functions are therefore available on ax.
sp = canvas3d.scatter_random(GRID, density.total/1e6/1e5, weight/1e6/1e5, GRID_unit=u.au, power=0, NRand=4000, prop_min=1.0, #function arguments
marker = 'o', cmap = 'winter', s = 3, edgecolors = 'none', vmin = None, vmax = None, norm = None) #Scatter kwargs
#ax.scatter(3000,0,0, c=[dens_e*1.2/1e6], norm=colors.Normalize(density.total.min()/1e6, vmax=density.total.max()/1e6), cmap=sp.cmap)
#-----------------------------
#PRINTING resultant PROPERTIES
#-----------------------------
Model.PrintProperties(density, temperature, GRID)
#-------
#TIMING
#-------
print('Ellapsed time: %.3fs' % (time.time() - t0))
print(
'-------------------------------------------------\n-------------------------------------------------\n'
)
#----------------------------------
#3D PLOTTING (weighting by density)
#----------------------------------
tag = 'Main'
weight = 10 * Rho0
r = GRID.rRTP[0] / u.au #GRID.rRTP hosts [r, R, Theta, Phi] --> Polar GRID
Plot_model.scatter3D(GRID,
density.total,
weight,
NRand=4000,
colordim=r,
axisunit=u.au,
cmap='jet',
colorscale='log',
colorlabel=r'${\rm log}_{10}(r$ $[au])$',
output='3Dpoints%s.png' % tag,
show=True)
outflows = Overlap(GRID)
finalprop = outflows.fromfiles(columns, submodels = files, rt_code = 'radmc3d')
radmc = rt.Radmc3dDefaults(GRID)
radmc.freefree(finalprop)
#********
#TIMING
#********
print ('Ellapsed time: %.3fs' % (time.time() - t0))
print ('-------------------------------------------------\n-------------------------------------------------\n')
#********
#PLOTTING
#********
density = finalprop['dens_e'] / 1e6 #dens. in cm^-3
temperature = finalprop['temp_gas']
weight = 100 * np.mean(density)
#-----------------
#Plot for DENSITY
#-----------------
Pm.scatter3D(GRID, density, weight, NRand = 4000, axisunit = u.au, colorscale = 'log', cmap = 'cool',
colorlabel = r'${\rm log}_{10}(n [cm^{-3}])$', output = 'global_grid_dens.png', vmin = 5, show=False)
#--------------------
#Plot for TEMPERATURE
#--------------------
Pm.scatter3D(GRID, density, weight, colordim = temperature, NRand = 4000, axisunit = u.au, colorscale = 'log',
cmap = 'brg', colorlabel = r'${\rm log}_{10}(T$ $[K])$', output = 'global_grid_temp.png', vmin = 2, show=False)
from sf3dmodels.utils.units import pc
import sf3dmodels.rt as rt
f1 = sf.FilamentModel([0, 0, 0], [0, 0, 1], -0.2 * pc, 0.2 * pc, 0.01 * pc)
f1.cylinder(0.1 * pc,
1e-3 * pc,
temp_pars=[500, 0.02 * pc, -0.3],
abund_pars=1e-4)
lims = [-0.3 * pc, 0.3 * pc]
pm.scatter3D(f1.GRID,
f1.density,
f1.density.min(),
axisunit=pc,
colordim=f1.temperature,
colorlabel='T [K]',
xlim=lims,
ylim=lims,
zlim=lims,
NRand=10000,
show=True)
prop = {
'dens_H': f1.density,
'temp_gas': f1.temperature,
'abundance': f1.abundance,
'gtdratio': f1.gtdratio,
'vel_x': f1.vel.x,
'vel_y': f1.vel.y,
'vel_z': f1.vel.z,
}
)
#----------------------------------------
#3D PLOTTING (weighting with temperature)
#----------------------------------------
tag = 'Burger_Tapering'
dens_plot = density.total / 1e6
weight = 5000. #Kelvin
norm = colors.LogNorm()
Plot_model.scatter3D(GRID,
temperature.total,
weight,
NRand=4000,
colordim=density.total / 1e6,
axisunit=u.au,
cmap='ocean_r',
norm=norm,
power=0.8,
colorlabel=r'$\rho [cm^{-3}]$',
output='3Dpoints%s.png' % tag,
show=False)
#----------------------------------------
#2D PLOTTING (Density and Temperature)
#----------------------------------------
vmin, vmax = np.array([9e15, 5e19]) / 1e6
norm = colors.LogNorm(vmin=vmin, vmax=vmax)
Plot_model.plane2D(GRID,
dens_plot,
)
#------------------------------------
#3D PLOTTING (weighting by density)
#------------------------------------
tag = 'Main'
dens_plot = density.total / 1e6
weight = 10 * Rho0
r = GRID.rRTP[0] / u.au #GRID.rRTP hosts [r, R, Theta, Phi] --> Polar GRID
Plot_model.scatter3D(GRID,
density.total,
weight,
NRand=4000,
colordim=r,
axisunit=u.au,
cmap='jet',
colorscale='log',
colorlabel=r'${\rm log}_{10}(r [au])$',
output='3Dpoints%s.png' % tag,
show=False)
#---------------------
#2D PLOTTING (Density)
#---------------------
vmin, vmax = np.array([2e13, 1e19]) / 1e6
norm = colors.LogNorm(vmin=vmin, vmax=vmax)
Plot_model.plane2D(GRID,
dens_plot,
data2merge = ['Main.dat', 'Burger.dat']
overlap = Overlap(GRID)
finalprop = overlap.fromfiles(columns, submodels = data2merge)
#**********
#WRITING
#**********
lime = rt.Lime(GRID)
lime.finalmodel(finalprop)
#--------
#PLOTTING
#--------
density = finalprop['dens_H2'] / 1e6 #1e6 to convert from m^-3 to cm^-3
temperature = finalprop['temp_gas']
weight = 400 * np.mean(density)
#-----------------
#Plot for DENSITY
#-----------------
Pm.scatter3D(GRID, density, weight, NRand = 7000, axisunit = u.au, colorscale = 'log', cmap = 'hot',
colorlabel = r'${\rm log}_{10}(\rho [cm^{-3}])$', output = 'global_grid_dens.png')
#--------------------
#Plot for TEMPERATURE
#--------------------
Pm.scatter3D(GRID, density, weight, colordim = temperature, NRand = 7000, axisunit = u.au, colorscale = 'log',
cmap = 'brg', colorlabel = r'${\rm log}_{10}(T$ $[K])$', output = 'global_grid_temp.png')
[-u.TSun]
], #flux --> if negative, radmc assumes the input number as the blackbody temperature of the star
lam=wavelength_intervals,
nxx=wavelength_divisions)
radmc.write_wavelength_micron(
lam=wavelength_intervals, nxx=wavelength_divisions
) #lam --> wavelengths in microns, nxx --> number of divisions in between wavelengths
Model.PrintProperties(density, temperature, GRID)
#---------------
#PLOTTING 2D z=0
#---------------
Plot_model.plane2D(GRID,
prop['dens_H2'],
axisunit=u.au,
plane={'z': 0},
norm=LogNorm(vmin=1e9, vmax=1e13),
output='densH2_2D.png')
Plot_model.plane2D(GRID,
prop['temp_gas'],
axisunit=u.au,
plane={'z': 0},
norm=LogNorm(vmin=1e1, vmax=1e3),
output='tempgas_2D.png')
#-------
#TIMING
#-------
print('Ellapsed time: %.3fs' % (time.time() - t0))
print(
'-------------------------------------------------\n-------------------------------------------------\n'
if plot_3d:
tags = iter(['A', 'B', 'C'])
npoints = iter([3000, 2000, 4000])
for density in [
prop_globalA['dens_e'], prop_globalB['dens_e'],
prop_globalC['dens_e']
]:
dens2plot = density / 1e6
weight = 10 * np.mean(dens2plot)
Pm.scatter3D(GRID,
dens2plot,
weight,
NRand=next(npoints),
axisunit=u.au,
colorscale='log',
cmap='cool',
colorlabel=r'${\rm log}_{10}(n_{e^-} [cm^{-3}])$',
output='global_grid%s.png' % next(tags),
vmin=5.5,
azim=10,
elev=30,
show=False)
#**********************************
#PLOTTING SEDS + FITS + CONVOLUTION
#**********************************
runpy.run_path('plot_sed_data.py')
runpy.run_path('generate_fits.py')
print(
'-------------------------------------------------\n-------------------------------------------------'
)
print('Output columns', lime.columns)
#******-
#TIMING
#******-
print ('Ellapsed time: %.3fs' % (time.time() - t0))
print ('-------------------------------------------------\n-------------------------------------------------\n')
#*******************************************
#3D PLOTTING
# The scatter points are randomly
# tracing the hydrogen (H) density.
# The colormap is associated to the
# molecular hydrogen (H2) density in cgs
#*******************************************
weight = 10*mean_dens
canvas3d = Plot_model.Canvas3d(ax_kw={'azim': -50, 'elev': 50})
ax = canvas3d.ax
sp = canvas3d.scatter_random(GRID, prop['dens_H'], weight, prop_color = prop['dens_H2']/1e6, GRID_unit=sfu.pc, power=0.5, NRand=20000, prop_min=None, #function arguments
marker = 'o', s = 3, cmap = 'nipy_spectral_r', edgecolors = 'none', vmin = 1.0, vmax = None, norm = colors.LogNorm()) #Scatter kwargs
cbar = plt.colorbar(sp)
cbar.ax.set_ylabel(r'$\rm n_{H_2} [\rm cm^{-3}]$')
ax.set_xlabel('X (pc)')
ax.set_ylabel('Y')
ax.set_zlabel('Z')
plt.savefig('3Dpoints_snap.png')#, dpi=200)
plt.show()
Model.PrintProperties(density, temperature, GRID)
#-------
#TIMING
#-------
print('Ellapsed time: %.3fs' % (time.time() - t0))
print(
'-------------------------------------------------\n-------------------------------------------------\n'
)
#--------------------------------------
#3D PLOTTING (weighting by temperature)
#--------------------------------------
tag = 'Burger'
weight = 10 * T10Env
vmin, vmax = np.array([5e11, 5e15]) / 1e6
norm = colors.LogNorm(vmin=vmin, vmax=vmax)
Plot_model.scatter3D(GRID,
temperature.total,
weight,
NRand=4000,
colordim=density.total / 1e6,
axisunit=u.au,
cmap='hot',
norm=norm,
colorlabel=r'$\rho$ $[cm^{-3}]$',
output='3Dpoints%s.png' % tag,
show=True)
#********
#TIMING
#********
print('Ellapsed time: %.3fs' % (time.time() - t0))
print(
'-------------------------------------------------\n-------------------------------------------------\n'
)
#********
#PLOTTING
#********
density = finalprop['dens_H2'] / 1e6 #dens. in cm^-3
temperature = finalprop['temp_gas']
weight = 1.0 #100 * np.mean(density)
"""
#-----------------
#Plot for DENSITY
#-----------------
Pm.scatter3D(GRID, density, weight, NRand = 4000, axisunit = u.au, colorscale = 'log', cmap = 'cool',
colorlabel = r'${\rm log}_{10}(n [cm^{-3}])$', output = 'global_grid_dens.png', vmin = 5)
#--------------------
#Plot for TEMPERATURE
#--------------------
Pm.scatter3D(GRID, density, weight, colordim = temperature, NRand = 4000, axisunit = u.au, colorscale = 'log',
cmap = 'brg', colorlabel = r'${\rm log}_{10}(T$ $[K])$', output = 'global_grid_temp.png', vmin = 2)
"""
#******************
#3D plotting
}
Model.PrintProperties(density, temperature, GRID)
print('Ellapsed time: %.3fs' % (time.time() - t0))
print(
'-------------------------------------------------\n-------------------------------------------------\n'
)
#---------------
#PLOTTING 2D z=0
#---------------
Plot_model.plane2D(GRID,
prop['dens_H'],
axisunit=u.au,
plane={'z': 0},
norm=LogNorm(vmin=1e9, vmax=1e14),
colorlabel=r'$n_{H}$ $\rm{[m^{-3}]}$',
cmap='cubehelix',
output='densH_2D.png',
show=True)
Plot_model.plane2D(GRID,
prop['temp_gas'],
axisunit=u.au,
plane={'z': 0},
norm=LogNorm(vmin=1e1, vmax=1e3),
colorlabel=r'T [K]',
cmap='hot',
output='tempgas_2D.png',
show=True)
f1 = sf.FilamentModel([0,0,0], [1,0,0], -0.2*pc, 0.2*pc, 4e-3*pc)
def new_temp(R,theta,z, *temp_pars):
TR, R0, pR, zh = temp_pars
cR = TR*R0**-pR
return cR*R**pR * np.exp(np.abs(z)/zh)
f1.func_temp = new_temp
f1.cylinder(0.1*pc, 1e-4*pc,
dens_pars = [7e10, 0.03*pc, 2.0],
temp_pars = [200, 0.02*pc, -0.15, -0.17*pc],
abund_pars = 1e-4)
pm.scatter3D(f1.GRID, f1.density, np.min(f1.density), axisunit = pc,
colordim = f1.density,
colorlabel = 'T [K]',
NRand = 10000, show=True)
prop = {'dens_H': f1.density,
'temp_gas': f1.temperature,
'abundance': f1.abundance,
'gtdratio': f1.gtdratio,
'vel_x': f1.vel.x,
'vel_y': f1.vel.y,
'vel_z': f1.vel.z,
}
lime = rt.Lime(f1.GRID)
lime.submodel(prop, output='filament.dat')
#-------
#TIMING
#-------
print ('Ellapsed time: %.3fs' % (time.time() - t0))
print ('-------------------------------------------------\n-------------------------------------------------\n')
#----------------------
#WRITING RADMC-3D FILES
#----------------------
prop = {'dens_e': density.total,
'dens_ion': density.total,
'temp_gas': temperature.total}
Rad = rt.Radmc3dDefaults(GRID)
Rad.freefree(prop)
#------------------------------------
#3D PLOTTING (weighting with density)
#------------------------------------
tag = 'keto+disc_HII'
weight = rho_s
norm = colors.LogNorm()
Plot_model.scatter3D(GRID, density.total, weight, NRand = 4000, colordim = density.total / 1e6, axisunit = u.au, cmap = 'jet',
colorscale = 'log', colorlabel = r'${\rm log}_{10}$($n_{\rm e}$ [cm$^{-3}$])', output = '3Ddens_%s.png'%tag, show = True)
Plot_model.scatter3D(GRID, density.total, weight, NRand = 4000, colordim = temperature.total, axisunit = u.au, cmap = 'jet', marker = 'o',
colorscale = 'uniform', colorlabel = r'$T_{\rm e}$ [Kelvin]', output = '3Dtemp_%s.png'%tag, show = True)
#******************
#3D plotting
#******************
lims = np.array([-70, 70])
weight = 1e10
ax_kw = {
'projection': '3d',
'xlim': lims,
'ylim': lims,
'zlim': lims,
'azim': -50,
'elev': 30
}
ax3 = fig.add_axes([0.03, 0.53, 0.43, 0.43], **ax_kw)
canvas3d = Plot_model.Canvas3d(fig=fig, ax=ax3)
sp = canvas3d.scatter_random(
grid,
density / 1e6,
weight,
GRID_unit=u.au,
power=0,
NRand=10000,
prop_min=1.0, #function arguments
marker='+',
cmap='jet',
s=3,
edgecolors='none',
vmin=1e6,
norm=colors.LogNorm()) #Scatter kwargs
cbar = plt.colorbar(sp)
'lam': [5e-1, 5e2, 2e4, 4e4]
}) #lambda in microns
#------------------------------------
#3D PLOTTING (weighting by density)
#------------------------------------
tag = 'plsphere_HII'
weight = 10 * rho_s
Plot_model.scatter3D(GRID,
density.total,
weight,
NRand=4000,
colordim=density.total / 1e6,
axisunit=u.au,
cmap='jet',
marker='.',
s=15,
colorscale='log',
colorlabel=r'${\rm log}_{10}$($n_{\rm e}$ [cm$^{-3}$])',
output='3Ddens_%s.png' % tag,
show=True)
Plot_model.scatter3D(GRID,
density.total,
weight,
NRand=4000,
colordim=temperature.total,
axisunit=u.au,
cmap='binary',
marker='.',
print('Ellapsed time:', time.time() - t0)
#******************
#3D plotting
#******************
lims = np.array([-100, 100])
weight = 1.
ax_kw = {
'projection': '3d',
'xlim': lims,
'ylim': lims,
'zlim': lims,
'azim': 30,
'elev': 13
}
canvas3d = Plot_model.Canvas3d(ax_kw=ax_kw)
ax = canvas3d.ax
sp = canvas3d.scatter_random(
grid,
prop['dens_H2'] / 1e6,
weight,
GRID_unit=u.au,
power=0,
NRand=10000,
prop_min=1.0, #function arguments
marker='+',
cmap='jet',
s=3,
edgecolors='none',
vmin=1e7,
norm=colors.LogNorm()) #Scatter kwargs
weight = 50 * np.mean(density)
#-----------------
#Plot for DENSITY
#-----------------
from matplotlib.colors import LogNorm
lims = np.array([-0.3, 0.3]) * u.pc
Pm.scatter3D(GRID,
density,
weight,
NRand=7000,
axisunit=u.pc,
norm=LogNorm(vmin=1e3, vmax=1e7),
cmap='nipy_spectral',
colorlabel=r'${\rm log}_{10}(\rho [cm^{-3}])$',
output='global_grid_dens.png',
xlim=lims,
ylim=lims,
zlim=lims)
#--------------------
#Plot for TEMPERATURE
#--------------------
Pm.scatter3D(GRID,
density,
weight,
colordim=temperature,
NRand=7000,
axisunit=u.pc,
