MStar = 34 * u.MSun
r_max = 2530 * u.au #H II sphere size
r_min = r_max / 200 #Minimum distance (!= 0 to avoid indeterminations)
r_s = r_max #Normalization distance
rho_s = 1.4e5 * 1e6 #from cgs to SI. Density at r_s
q = 1.3 #Density powerlaw
t_e = 1.e4 #K
#---------------
#GRID Definition
#---------------
sizex = sizey = sizez = 2600 * u.au
Nx = Ny = Nz = 63 #Number of divisions for each axis
GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz], rt_code='radmc3d')
NPoints = GRID.NPoints #Final number of nodes in the grid
#-------------------
#PHYSICAL PROPERTIES
#-------------------
density = Model.density_Powerlaw_HII(r_min, r_max, r_s, rho_s, q, GRID)
temperature = Model.temperature_Constant(density,
GRID,
envTemp=t_e,
backTemp=2.725)
Model.PrintProperties(density, temperature, GRID)
#-------
#TIMING
dx_grid = 40*u.au
#rho = lambda R: dens0
#T = lambda R: 10000.
T0 = 10000.
qT = 0.
temp = [T0, qT]
dens0 = 0.14*2.6e13
qn = -0.15 #-0.4
dens = [dens0, qn]
a = 2.05*np.sqrt(300*u.au)
b = 2.05*np.sqrt(300*u.au)
GRID, props = make_paraboloid(z_min, z_max, dx_grid, a, b, dens, T0, width = 20*u.au)
shift = Model.ChangeGeometry(GRID, center = np.array([dx+20, dy-20, 0])*u.au,
rot_dict = { 'angles': [-np.pi/2,
1*np.pi/180*(posang+90 + 8),
-np.pi/12],
'axis': ['y','z','y'] })
GRID.XYZ = shift.newXYZ
prop_dict = {'dens_e': props[0],
'dens_ion': props[0],
'temp_gas': props[1]}
shell = rt.Radmc3d(GRID)
shell.submodel(prop_dict, output=tag)
print ('Columns written into file:', shell.columns)
rho_s = 1.0e6 * 1e6 / 5 #from cgs to SI. Density at sonic radius q = 1.3 #Density powerlaw t_e = 1.e4 #K #------------------------------- #Parameters for the Pringle disc #------------------------------- MRate = 3e-4 * u.MSun_yr RStar = u.RSun * ( MStar/u.MSun )**0.8 #--------------- #GRID Definition #--------------- sizex = sizey = sizez = 2600 * u.au Nx = Ny = Nz = 63 #Number of divisions for each axis GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz], rt_code = 'radmc3d') NPoints = GRID.NPoints #Final number of nodes in the grid #------------------- #PHYSICAL PROPERTIES #------------------- #-------- #ENVELOPE #-------- densEnv = Model.density_Keto_HII(MStar, r_min, r_max, rho_s, t_e, GRID, q = 1.5) #------- #DISC #------- Rd = 10*densEnv.rs #10 times the sonic radius, just to make it visible Rho0 = Res.Rho0(MRate, Rd, MStar)
import time
t0 = time.time()
#--------------------
#**************
#GRID AND MODEL
#**************
r_max = 0.1 * u.pc #H II sphere size
r_min = 0.02 * u.pc
rho0 = 28 * 1e6 * u.pc**2
q = -2
sizex = sizey = sizez = 1.2 * r_max
Nx = Ny = Nz = 100 #Number of divisions along each axis
GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz], rt_code='radmc3d')
NPoints = GRID.NPoints #Number of nodes in the grid
density = Model.density_Powerlaw2(r_max, r_min, rho0, q, GRID, rho_min=1.)
temperature = Model.temperature_Constant(density,
GRID,
envTemp=10000.,
backTemp=2.725)
vel = Model.velocity_random(15000, GRID.NPoints)
#********************
#WRITING FOR RADMC-3D
#********************
prop = {
'vel_x': vel.x,
'vel_y': vel.y,
MStar / u.MSun
)**0.8 #Multiply by 10 Main Sequence relationship to account for bloated protostar
LStar = 9 * u.LSun #u.LSun * ( MStar/u.MSun )**4 # 9Lsun from Li+2017
TStar = u.TSun * ((LStar / u.LSun) / (RStar / u.RSun)**2)**0.25
Rd = 68. * u.au
print('RStar:', RStar / u.RSun, ', LStar:', LStar / u.LSun, ', TStar:', TStar)
#---------------
#GRID Definition
#---------------
#Cubic grid, each edge ranges [-100, 100] au.
sizex = sizey = sizez = 100 * u.au
Nx = Ny = Nz = 200 #Number of divisions for each axis
GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz])
NPoints = GRID.NPoints #Number of nodes in the grid
#-------------
#DENSITY
#-------------
#-------
#DISC
#-------
if args.Arho: Arho = float(args.Arho)
else: Arho = 150.0 # (Mdisk=0.106*1.4=Msun=0.149Msun)
H0sf = 0.04 #Disc scale-height factor (H0 = H0sf * RStar)
Rdisc = 1.0 * Rd
Rho0 = Res.Rho0(MRate, Rd, MStar) #Normalization density
RStar = 26 * u.RSun * (MStar / u.MSun)**0.27 * (MRate /
(1e-3 * u.MSun_yr))**0.41
LStar = 3.2e4 * u.LSun
TStar = u.TSun * ((LStar / u.LSun) / (RStar / u.RSun)**2)**0.25
Rd = 152. * u.au
print('RStar:', RStar / u.RSun, ', LStar:', LStar / u.LSun, ', TStar:', TStar)
#---------------
#GRID Definition
#---------------
#Cubic grid, each edge ranges [-500, 500] au.
sizex = sizey = sizez = 500 * u.au
Nx = Ny = Nz = 200 #Number of divisions for each axis
GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz])
NPoints = GRID.NPoints #Number of nodes in the grid
#--------
#DENSITY
#--------
Rho0 = Res.Rho0(MRate, Rd, MStar)
Arho = 24.1 #Disc-envelope density factor
Renv = 500 * u.au #Envelope radius
Cavity = 40 * np.pi / 180 #Cavity opening angle
density = Model.density_Env_Disc(RStar,
Rd,
Rho0,
Arho,
GRID,
discFlag=True,
rho0 = 1e8 * 1e6 #[part/m3] Number density at r_min r_rho = [r_min, 200 * u.au, 300 * u.au, r_max] #r frontiers for density q_rho = [-2.0, -1.5, -2.5] #Powerlaws for density T0 = 1000. #[K] Temperature at r_min r_T = [r_min, 250 * u.au, r_max] #r frontiers for temperature q_T = [-0.5, -1.0] #Powerlaws for temperature #--------------- #GRID Definition #--------------- sizex = sizey = sizez = r_max Nx = Ny = Nz = 95 #Number of divisions for each axis GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz], rt_code='lime') NPoints = GRID.NPoints #Final number of nodes in the grid #------------------- #PHYSICAL PROPERTIES #------------------- density = Model.density_PowerlawShells(r_rho, q_rho, rho0, GRID, rho_min=1.0e4) temperature = Model.temperature_PowerlawShells(r_T, q_T, T0, GRID, T_min=25.) #-------- #VELOCITY #-------- vel = Model.velocity_random(1800, GRID.NPoints) #------------------------------- #ABUNDANCE and GAS-to-DUST RATIO
RStar = 26 * u.RSun * (MStar / u.MSun)**0.27 * (MRate /
(1e-3 * u.MSun_yr))**0.41
LStar = 3.2e4 * u.LSun
TStar = u.TSun * ((LStar / u.LSun) / (RStar / u.RSun)**2)**0.25
Rd = 152. * u.au
print('RStar:', RStar / u.RSun, ', LStar:', LStar / u.LSun, ', TStar:', TStar)
#---------------
#GRID Definition
#---------------
#Cubic grid, each edge ranges [-500, 500] au.
sizex = sizey = sizez = 500 * u.au
Nx = Ny = Nz = 100 #Number of divisions for each axis
GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz])
NPoints = GRID.NPoints #Number of nodes in the grid
#--------
#DENSITY
#--------
Rho0 = Res.Rho0(MRate, Rd, MStar)
Arho = 24.1 #Disc-envelope density factor
Renv = 500 * u.au #Envelope radius
Cavity = 40 * np.pi / 180 #Cavity opening angle
density = Model.density_Env_Disc(RStar,
Rd,
Rho0,
Arho,
GRID,
discFlag=True,
MRate = 5.e-6 * u.MSun_yr
RStar = u.RSun * (MStar / u.MSun)**0.8
LStar = u.LSun * (MStar / u.MSun)**4
TStar = u.TSun * ((LStar / u.LSun) / (RStar / u.RSun)**2)**0.25
Rd = 264. * u.au
print('RStar:', RStar / u.RSun, ', LStar:', LStar / u.LSun, ', TStar:', TStar)
#---------------
#GRID Definition
#---------------
#Cubic grid, each edge ranges [-500, 500] au.
sizex = sizey = sizez = 500 * u.au
Nx = Ny = Nz = 200 #Number of divisions for each axis
GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz])
NPoints = GRID.NPoints #Number of nodes in the grid
#-------------
#DENSITY
#-------------
#--------
#ENVELOPE
#--------
Rho0 = Res.Rho0(MRate, Rd, MStar)
Arho = None
Renv = 2.5 * Rd
densEnv = Model.density_Env_Disc(RStar,
Rd,
Rho0,
RStar = None #26 * U.RSun * ( MStar/U.MSun )**0.27 * ( MRate / (1e-3*U.MSun_yr) )**0.41
LStar = None #8.6e4 * U.LSun # 4
TStar = None #U.TSun * ( (LStar/U.LSun) / (RStar/U.RSun)**2 )**0.25
BT = None
Rd = None #centrifugal radius
Tmin_disc = None
#---------------
#GRID Definition
#---------------
sizex = sizey = sizez = r_max
Nx = Ny = Nz = 128 #Number of divisions for each axis
GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz], rt_code='lime')
NPoints = GRID.NPoints #Final number of nodes in the grid
#-------------------
#PHYSICAL PROPERTIES
#-------------------
density = Model.density_Powerlaw(r_max, rho_mean, q, GRID, rho_min=1.0e4)
temperature = Model.temperature(TStar,
Rd,
T10Env,
RStar,
MStar,
MRate,
BT,
density,
MRate = 5.e-6 * u.MSun_yr
RStar = u.RSun * (MStar / u.MSun)**0.8
LStar = u.LSun * (MStar / u.MSun)**4
TStar = u.TSun * ((LStar / u.LSun) / (RStar / u.RSun)**2)**0.25
Rd = 264. * u.au
print('RStar:', RStar / u.RSun, ', LStar:', LStar / u.LSun, ', TStar:', TStar)
#---------------
#GRID Definition
#---------------
#Cubic grid, each edge ranges [-500, 500] au.
sizex = sizey = sizez = 500 * u.au
Nx = Ny = Nz = 100 #Number of divisions for each axis
GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz])
NPoints = GRID.NPoints #Number of nodes in the grid
#-------------
#DENSITY
#-------------
#--------
#ENVELOPE
#--------
Rho0 = Res.Rho0(MRate, Rd, MStar)
Arho = None
Renv = 2.5 * Rd
densEnv = Model.density_Env_Disc(RStar,
Rd,
Rho0,
#********************
import numpy as np
import time
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as colors
t0 = time.time()
#********
#GRIDDING
#********
sizex = 100 * u.au
sizey = sizez = 100 * u.au
Nx = Ny = Nz = 100
GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz], rt_code='lime')
#********
#MERGING
#********
files = ['disc.dat', 'outflow.dat']
#Old style
#outflows = BGG.overlap(GRID, submodels = data2merge, rho_min = 1e6)
#New style
columns = [
'id', 'x', 'y', 'z', 'dens_H2', 'dens_Hplus', 'temp_gas', 'vel_x', 'vel_y',
'vel_z', 'abundance', 'gtdratio'
]
overlap = Overlap(GRID)
finalprop = overlap.fromfiles(columns, submodels=files, rt_code='lime')
rho0 = 5e8 * 1e6 #[part/m3] Number density at r_min
r_rho = [r_min, r_stellar, r_max] #r frontiers for density
q_rho = [-1.5, -1.7] #Powerlaws for density
T0 = 1000. #[K] Temperature at r_min
r_T = [r_min, r_stellar, r_max] #r frontiers for temperature
q_T = [-0.5, -1.0] #Powerlaws for temperature
#---------------
#GRID Definition
#---------------
sizex = sizey = sizez = r_max
Nx = Ny = Nz = 95 #Number of divisions for each axis
GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz], rt_code='lime')
NPoints = GRID.NPoints #Final number of nodes in the grid
#-------------------
#PHYSICAL PROPERTIES
#-------------------
density = Model.density_PowerlawShells(r_rho, q_rho, rho0, GRID, rho_min=1.0e4)
temperature = Model.temperature_PowerlawShells(r_T, q_T, T0, GRID, T_min=25.)
#--------
#VELOCITY
#--------
dens_dict = {'dens_H': density.total}
ff_factor = 1.
vel = Model.velocity_infall(dens_dict, ff_factor, MStar, r_stellar, GRID)
from sf3dmodels.grid import Overlap #Overlap submodels #******************** #Extra libraries #******************** import numpy as np import time t0 = time.time() #******** #GRIDDING #******** sizex = 500 * u.au sizey = sizez = 500 * u.au Nx = Ny = Nz = 150 GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz], rt_code='radmc3d') #******** #MERGING #******** files = ['datatab_outflow1.dat', 'datatab_outflow2.dat'] #Old style #outflows = BGG.overlap(GRID, submodels = data2merge, rho_min = 1e6) #New style columns = ['id', 'x', 'y', 'z', 'dens_e', 'dens_ion', 'temp_gas'] outflows = Overlap(GRID) finalprop = outflows.fromfiles(columns, submodels = files, rt_code = 'radmc3d') radmc = rt.Radmc3dDefaults(GRID) radmc.freefree(finalprop)
#------------------ from sf3dmodels import Model, Plot_model as Pm import sf3dmodels.utils.units as u import sf3dmodels.rt as rt from sf3dmodels.grid import Overlap #----------------- #Extra libraries #----------------- import numpy as np #******** #GRIDDING #******** sizex = sizey = sizez = 1000 * u.au Nx = Ny = Nz = 200 GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz]) #********** #OVERLAPING #********** columns = ['id', 'x', 'y', 'z', 'dens_H2', 'temp_gas', 'vel_x', 'vel_y', 'vel_z', 'abundance_0', 'gtdratio'] data2merge = ['Main.dat', 'Burger.dat'] overlap = Overlap(GRID) finalprop = overlap.fromfiles(columns, submodels = data2merge) #********** #WRITING #********** lime = rt.Lime(GRID) lime.finalmodel(finalprop)
import matplotlib.pyplot as plt
import time
#------------------
#General Parameters
#------------------
r_max = 2530 * u.au #H II sphere size
dens_e = 1.4e5 * 1e6 #Electron number density, from cgs to SI
t_e = 1.e4 #K
#---------------
#GRID Definition
#---------------
sizex = sizey = sizez = 2600 * u.au
Nx = Ny = Nz = 63 #Number of divisions for each axis
GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz], rt_code='radmc3d')
NPoints = GRID.NPoints #Final number of nodes in the grid
#-------------------
#PHYSICAL PROPERTIES
#-------------------
density = Model.density_Constant(r_max, GRID, envDens = dens_e)
temperature = Model.temperature_Constant(density, GRID, envTemp = t_e, backTemp = 2.725)
Model.PrintProperties(density, temperature, GRID) #Printing resultant properties (mass, mean temperature, etc)
#----------------------
#WRITING RADMC-3D FILES
#----------------------
prop = {'dens_e': density.total,
'dens_ion': density.total,
def do_overlap():
#******************************
#PATH AND TAG
#******************************
cwd = os.getcwd()
cloud_kind = cwd.split('Lime-arepo/')[-1].split('-Lime')
cloud_kind = cloud_kind[0] + cloud_kind[1]
home = os.environ['HOME']
base = home + '/Downloads/Manchester_2018/Rowan-data/Andres/data/datasets/'
base += cloud_kind
base_content = os.popen('ls ' + base).readlines()
snapshot = ''
for file in base_content:
if 'Restest' in file: snapshot = '/' + file.split('\n')[0]
#******************************
#AREPO 3D-grids (not projected)
#******************************
rsnap.io_flags['mc_tracer'] = True
rsnap.io_flags['time_steps'] = True
rsnap.io_flags['sgchem'] = True
rsnap.io_flags['variable_metallicity'] = False
#rsnap.io_flags['MHD']=True #There is no magnetic field information
#******************************
#READING SNAPSHOT
#******************************
f = base + snapshot
data, header = rsnap.read_snapshot(f)
nparts = header['num_particles']
ngas = nparts[0]
nsinks = nparts[5]
for key in data:
print(key, np.shape(data[key]))
#****************************
#GLOBAL GRID
#****************************
pos_max = np.max(data['pos'], axis=0)
pos_min = np.min(data['pos'], axis=0)
pos_mean = 0.5 * (pos_max + pos_min) * ulength / 100.
sizex = sizey = sizez = 0.5 * np.max(pos_max - pos_min) * ulength / 100.
#print (sizex, sizey, sizez)
Nx = Ny = Nz = 200
GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz],
include_zero=False) #, rt_code='radmc3d')
columns = [
'id', 'x', 'y', 'z', 'dens_H2', 'dens_H', 'dens_Hplus', 'temp_gas',
'temp_dust', 'vel_x', 'vel_y', 'vel_z', 'abundance', 'gtdratio',
'doppler'
]
"""
overlap = grid.Overlap(GRID)
overlap.min_values['dens_H2'] = 0.0
newprop = overlap.fromfiles(columns, submodels=['datatab.dat'])
"""
props2use = ['dens_H', 'dens_H2', 'abundance', 'dens_Hplus']
newprop = {}
datatab = np.loadtxt('./Subgrids/datatab.dat') #[:-30000]
header_tab = np.loadtxt('./Subgrids/header.dat')
coords = np.array(GRID.XYZ).T
data_prop = {}
Lime = rt.Lime(GRID)
for prop in props2use:
column, = np.where(Lime.sf3d_header[prop] == header_tab)
data_prop[prop] = datatab[:, column]
subgrid = Model.Struct(XYZ=[datatab[:, i] for i in range(1, 4)],
NPoints=len(datatab))
fill = grid.fillgrid.Random(subgrid)
fill_rand = fill.spherical(
data_prop,
#prop_fill = {'dens_H2': 1.0},
r_min=10 * pc,
r_max=np.max(subgrid.XYZ) * np.sqrt(3),
n_dummy=subgrid.NPoints / 3)
coords_sub = np.array(subgrid.XYZ).T
for prop in props2use:
print('Merging %s ...' % prop)
ind_nodummie = data_prop[prop] > 2 * data_prop[prop][-1]
min_val = data_prop[prop][ind_nodummie].min()
newprop[prop] = griddata(coords_sub,
data_prop[prop],
coords,
fill_value=0.0) #, method='nearest')
newprop[prop][
newprop[prop] <
min_val] = min_val #very low value, just to get rid of zeroes
#newprop[prop][np.isnan(newprop[prop])] = datatab[:,column].min() #newprop[prop][np.isnan(newprop[prop])].min()
sink_pos = data['pos'][ngas:] * ulength / 100 - pos_mean
dummy_pos.append(coords_sub[-int(subgrid.NPoints / 2):])
return GRID, sizex, newprop, sink_pos, nsinks
offset = n_neighbours * np.dtype(struct_dtypes['i']).itemsize
if n % 1000 == 0: progress(int(100 * n / npoints))
progress(100)
sys.stdout.write('\n')
data['xyz'] = np.array(data['xyz'])
data['props'] = np.array(data['props'])
return prop_tags, npoints, data
t0 = time.time()
filename = "grid_temp.dat"
prop_tags, npoints, data = read_temp(filename)
grid = Model.Struct(XYZ=data['xyz'].T, NPoints=npoints)
prop = {
'dens_H2': data['props'][:, 0],
'temp_dust': data['props'][:, 1],
'temp_gas': data['props'][:, 2],
}
lime = rt.Lime(grid)
lime.submodel(prop,
output='datatab.dat',
folder='./',
lime_npoints=True,
lime_header=True)
print('Output columns', lime.columns)
print('Ellapsed time:', time.time() - t0)
r_min = r_max / 256 #Minimum distance to the centre (!= 0 to avoid indeterminations)
rho0 = 1e8 * 1e6 #[part/m3] Number density at r_min
r_rho = [r_min, 200 * u.au, 300 * u.au, r_max] #r frontiers for density
q_rho = [-2.0, -1.5, -2.5] #Powerlaws for density
T0 = 1000. #[K] Temperature at r_min
r_T = [r_min, 250 * u.au, r_max] #r frontiers for temperature
q_T = [-0.5, -1.0] #Powerlaws for temperature
#---------------
#GRID Definition
#---------------
sizex = sizey = sizez = r_max
Nx = Ny = Nz = 95 #Number of divisions for each axis
GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz], rt_code='radmc3d')
NPoints = GRID.NPoints #Final number of nodes in the grid
#-------------------
#PHYSICAL PROPERTIES
#-------------------
density = Model.density_PowerlawShells(r_rho, q_rho, rho0, GRID, rho_min=1.0e4)
temperature = Model.temperature_PowerlawShells(r_T, q_T, T0, GRID, T_min=25.)
gtd0 = 100. #Gas to dust ratio
gtdratio = Model.gastodust(gtd0, NPoints)
#--------------------
#PRINTING and WRITING
#--------------------
prop = {
ngas = len(data_gas)
if nfrac and nfrac < ngas:
ids_rand = np.random.choice(np.arange(0, ngas), size=nfrac, replace=False)
data_gas = data_gas[ids_rand]
print(data_gas.shape)
data_gas[:, 0:3] *= u.au #a0
data_r = np.linalg.norm(data_gas[:, 0:3], axis=1)
data_gas = data_gas[data_r <= 100 * u.au]
data_gas[:,
5] *= 5.941031250291510E-07 * 1e3 / (2 * ct.mH) #0.05*Ms/a0**3/ct.mH
#data_gas[:,5] = np.where(data_gas[:,5]<1.0, 1.0, data_gas[:,5])
data_gas[:, 6:9] *= 2.978460638675013E+06 * 0.01 #a0/P
grid = Model.Struct(XYZ=data_gas[:, 0:3].T, NPoints=len(data_gas))
prop = {
'dens_H2': data_gas[:, 5],
'vel_x': data_gas[:, 6],
'vel_y': data_gas[:, 7],
'vel_z': data_gas[:, 8]
}
"""
unique_cells = UniqueCells(prop,None)
id_pos = unique_cells.getuniques(grid).astype(np.int)
grid.XYZ = grid.XYZ.T[id_pos].T
grid.NPoints = len(id_pos)
for key in prop: prop[key] = prop[key][id_pos]
"""
fill = fillgrid.Random(grid)
#------------------
from sf3dmodels import Model, Plot_model as Pm
import sf3dmodels.utils.units as u
import sf3dmodels.rt as rt
from sf3dmodels.grid import Overlap
#-----------------
#Extra libraries
#-----------------
import numpy as np
#********
#GRIDDING
#********
sizex = sizey = sizez = 0.3 * u.pc
Nx = Ny = Nz = 145
GRID = Model.grid([sizex, sizey, sizez], [Nx, Ny, Nz], include_zero=False)
#**********
#OVERLAPING
#**********
columns = [
'id', 'x', 'y', 'z', 'dens_H', 'temp_gas', 'vel_x', 'vel_y', 'vel_z',
'abundance', 'gtdratio'
]
data2merge = ['filament.dat', 'envelope.dat']
overlap = Overlap(GRID)
finalprop = overlap.fromfiles(columns, submodels=data2merge)
#**********
#WRITING
#**********
