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
#******************
#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)
#------------------------------------
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)
x,y,z = GRID.XYZ
ind_rand = np.random.choice(np.arange(len(x)), size=10)
vel = np.zeros((3,10)) + 1000*np.sin([np.linspace(0,2*np.pi,10) for i in range(3)])#np.random.random(size=(3,10))
vp = canvas3d.vectors(x[ind_rand], y[ind_rand], z[ind_rand], vel[0], vel[1], vel[2], GRID_unit=u.au, length=1.0, linewidths=2, color='k')
cbar = plt.colorbar(sp)
cbar.ax.set_ylabel(r'$n_{e^-}$ ($\times$ 10$^5$) cm$^{-3}$')
ax.set_xlabel('X')
ax.set_ylabel('Y')
colorlabel=r'$T_{\rm e}$ [K]',
output='3Dtemp_%s.png' % tag,
show=True)
#********************************************
#CUSTOMISABLE PLOTS USING Plot_model.Canvas3d
#********************************************
fig = plt.figure(figsize=(8, 6))
#ax = plt.axes(projection='3d')
lims = (-3000, 3000)
#DENSITY
canvas3d = Plot_model.Canvas3d(fig=fig,
ax_kw={
'xlim': lims,
'ylim': lims,
'zlim': lims,
'azim': 50,
'elev': 10
})
ax = canvas3d.ax #generated with fig.add_axes from matplotlib, hence all the matplotlib functions are available
sp = canvas3d.scatter_random(
GRID,
density.total,
weight,
GRID_unit=u.au,
power=0.4,
NRand=4000,
prop_color=density.total / 1e6,
prop_min=1e2, #function arguments
marker='.',
cmap='nipy_spectral',
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()
#--------------------
#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
#******************
lims = np.array([-100, 100])
weight = 1.0
ax_kw = {
'projection': '3d'
} #, 'xlim': lims, 'ylim': lims, 'zlim': lims, 'azim': -50, 'elev': 30}
canvas3d = Pm.Canvas3d(ax_kw=ax_kw)
sp = canvas3d.scatter_random(
GRID,
density,
weight,
GRID_unit=u.au,
power=0,
NRand=10000,
prop_min=1.0, #function arguments
marker='+',
cmap='jet',
s=3,
edgecolors='none',
vmin=1,
norm=colors.LogNorm()) #Scatter kwargs
cbar = plt.colorbar(sp)