def test_programmatic():
# Test a single inversion in non-iterator mode
mod = hazel.Model(working_mode='synthesis')
mod.add_spectral({'Name': 'spec1', 'Wavelength': [10826, 10833, 150], 'topology': 'ch1', 'LOS': [0.0,0.0,90.0], 'Boundary condition': [1.0,0.0,0.0,0.0]})
mod.add_chromosphere({'Name': 'ch1', 'Spectral region': 'spec1', 'Height': 3.0, 'Line': '10830', 'Wavelength': [10826, 10833]})
mod.setup()
mod.atmospheres['ch1'].set_parameters([0.0,0.0,100.0,1.0,0.0,8.0,1.0,0.0],1.0)
mod.synthesize()
assert mod.spectrum['spec1'].stokes.shape == (4,150), "incorrect dimensions in synthesis"
def test_single_syn():
# Test a single inversion in non-iterator mode
mod = hazel.Model('test/configurations/conf_single.ini',
working_mode='synthesis',
verbose=3)
mod.open_output()
mod.synthesize()
mod.write_output()
mod.close_output()
assert mod.spectrum['spec1'].stokes.shape == (
4, 150), "incorrect dimensions in synthesis"
def test_nonmpi_syn1d():
# Test iterator with a single observation in synthesis
iterator = hazel.Iterator(use_mpi=False)
rank = iterator.get_rank()
mod = hazel.Model('test/configurations/conf_nonmpi_syn1d.ini', working_mode='synthesis', verbose=2)
iterator.use_model(model=mod)
iterator.run_all_pixels()
if (rank == 0):
f = h5py.File('output.h5', 'r')
assert f['spec1']['stokes'].shape == (1,1,1,4,150), "incorrect dimensions in inversion"
f.close()
def test_single_inv():
# Test a single inversion in non-iterator mode without randomization
mod = hazel.Model('test/configurations/conf_single.ini', working_mode='inversion', verbose=2)
mod.read_observation()
mod.open_output()
mod.invert()
mod.write_output()
mod.close_output()
f = h5py.File('output.h5')
assert f['spec1']['stokes'].shape == (1,1,2,4,150), "incorrect dimensions in inversion"
f.close()
import numpy as np
import matplotlib.pyplot as pl
import hazel
import h5py
from ipdb import set_trace as stop
iterator = hazel.Iterator(use_mpi=True)
rank = iterator.get_rank()
mod = hazel.Model('configurations/conf_mpi_invh5.ini',
working_mode='inversion',
rank=rank,
randomization=2)
iterator.use_model(model=mod)
iterator.run_all_pixels()
import numpy as np
import matplotlib.pyplot as pl
import hazel
import h5py
from scipy.optimize import minimize
import gc
# Test a single inversion in non-iterator mode
mod = hazel.Model('conf_single.ini', working_mode='inversion', verbose=2)
mod.read_observation()
mod.open_output()
mod.invert()
mod.write_output()
mod.close_output()
final = np.loadtxt('photospheres/model_photosphere.1d', skiprows=4)
start = np.loadtxt('photospheres/model_photosphere_200.1d', skiprows=4)
f = h5py.File('output.h5')
pl.plot(f['ph1']['T'][0, 0, :], label='inverted')
pl.plot(final[:, 1], label='target')
pl.plot(start[:, 1], 'x', label='initial')
f.close()
pl.legend()
mod = hazel.Model('conf_single.ini', working_mode='inversion', verbose=2)
mod.read_observation()
mod.open_output()
mod.invert_external(minimize, method='Nelder-Mead')
mod.write_output()
mod.close_output()
import numpy as np
import matplotlib.pyplot as pl
import hazel
# Test a single inversion in non-iterator mode
mod = hazel.Model('configurations/conf_single.ini',
working_mode='synthesis',
verbose=3)
mod.open_output()
mod.synthesize()
mod.write_output()
mod.close_output()
f, ax = pl.subplots()
ax.plot(mod.spectrum['spec1'].stokes[0, :])
pl.show()
for i, l in enumerate(tmp):
t = np.array(l.split()).astype('float64')
stokes[:,i] = t[0:4]
noise[:,i] = t[4:]
mu = np.cos(los[0] * np.pi / 180.0)
return stokes, noise, los, mu, boundary
if __name__ == '__main__':
#-------------------------------------------
# Synthesize a sample profile with some default configuration given in conf_syn.ini
# The observed files will be used later as observations for the inversions
#-------------------------------------------
mod = hazel.Model('configurations/conf_syn.ini')
mod.synthesize()
noise = 1e-4 * np.ones((150,4))
spec = mod.spectrum['spec1'].stokes.T + 1e-4 * np.random.randn(150,4)
# Generate wavelength axis
np.savetxt('observations/10830.wavelength', mod.spectrum['spec1'].wavelength_axis, header='lambda')
# Generate output Stokes parameters
f = open('observations/10830_stokes.1d', 'w')
f.write('# LOS theta_LOS, phi_LOS, gamma_LOS\n')
f.write('0.0 0.0 90.0\n')
f.write('\n')
f.write('# Boundary condition I/Ic(mu=1), Q/Ic(mu=1), U/Ic(mu=1), V/Ic(mu=1)\n')
for i, l in enumerate(tmp):
t = np.array(l.split()).astype('float64')
stokes[:,i] = t[0:4]
noise[:,i] = t[4:]
mu = np.cos(los[0] * np.pi / 180.0)
return stokes, noise, los, mu, boundary
if __name__ == '__main__':
#-------------------------------------------
# Synthesize a sample profile with some default configuration given in conf_syn.ini
# The observed files will be used later as observations for the inversions
#-------------------------------------------
mod = hazel.Model('conf_syn.ini')
mod.synthesize()
noise = 1e-4 * np.ones((150,4))
spec = mod.spectrum['spec1'].stokes.T + 1e-4 * np.random.randn(150,4)
# Generate wavelength axis
np.savetxt('observations/10830.wavelength', mod.spectrum['spec1'].wavelength_axis, header='lambda')
# Generate output Stokes parameters
f = open('observations/10830_stokes.1d', 'w')
f.write('# LOS theta_LOS, phi_LOS, gamma_LOS\n')
f.write('0.0 0.0 90.0\n')
f.write('\n')
f.write('# Boundary condition I/Ic(mu=1), Q/Ic(mu=1), U/Ic(mu=1), V/Ic(mu=1)\n')
import numpy as np
import matplotlib.pyplot as pl
import hazel
print(hazel.__version__)
label = ['I', 'Q', 'U', 'V']
mod = hazel.Model(working_mode='synthesis')
mod.add_spectral({
'Name': 'spec1',
'Wavelength': [10825, 10835, 150],
'topology': 'ph1->ch1->te1',
'LOS': [0.0, 0.0, 90.0],
'Boundary condition': [1.0, 0.0, 0.0, 0.0]
})
mod.add_chromosphere({
'Name': 'ch1',
'Spectral region': 'spec1',
'Height': 3.0,
'Line': '10830',
'Wavelength': [10826, 10835]
})
mod.add_photosphere({
'Name':
'ph1',
'Spectral region':
'spec1',
'Spectral lines': [300],
'Wavelength': [10825, 10835],
'Reference atmospheric model':
'../../models/photospheres/model_photosphere.1d'
import numpy as np
import matplotlib.pyplot as pl
import hazel
import h5py
from ipdb import set_trace as stop
# Test iterator with a single observation in synthesis
iterator = hazel.Iterator(use_mpi=False)
rank = iterator.get_rank()
mod = hazel.Model('configurations/conf_nonmpi_syn1d.ini', working_mode='synthesis', verbose=2)
iterator.use_model(model=mod)
iterator.run_all_pixels()
if (rank == 0):
fig, ax = pl.subplots(nrows=2, ncols=2)
ax = ax.flatten()
f = h5py.File('output.h5', 'r')
for i in range(4):
ax[i].plot(f['spec1']['stokes'][0,0,0,i,:])
pl.show()
f.close()
import numpy as np
import matplotlib.pyplot as pl
import hazel
import h5py
from ipdb import set_trace as stop
# Test iterator with a single observation in synthesis
iterator = hazel.iterator(use_mpi=False)
rank = iterator.get_rank()
mod = hazel.Model('conf_nonmpi_inv1d.ini', working_mode='inversion', verbose=2)
iterator.use_model(model=mod)
iterator.run_all_pixels()
if (rank == 0):
fig, ax = pl.subplots(nrows=2, ncols=2)
ax = ax.flatten()
f = h5py.File('output.h5', 'r')
for i in range(4):
ax[i].plot(f['spec1']['stokes'][0, 0, i, :])
pl.show()
pl.pause(0.001)
input("Press [enter] to continue.")
import hazel
import h5py
import sys
conf_file = sys.argv[1]
iterator = hazel.Iterator(use_mpi=True)
mod = hazel.Model(conf_file,
rank=iterator.get_rank(),
working_mode='inversion')
iterator.use_model(model=mod)
iterator.run_all_pixels()
import hazel
iterator = hazel.Iterator(use_mpi=True)
mod = hazel.Model('conf_synth_parallel.ini', working_mode='synthesis')
iterator.use_model(model=mod)
iterator.run_all_pixels()
import numpy as np
import matplotlib.pyplot as pl
import hazel
import h5py
from ipdb import set_trace as stop
iterator = hazel.iterator(use_mpi=True)
rank = iterator.get_rank()
if (rank == 0):
mod = hazel.Model('conf_mpi_synh5.ini', working_mode='synthesis')
iterator.use_model(model=mod)
else:
iterator.use_model()
iterator.run_all_pixels()
np.savetxt(f, tmp.T)
f.close()
# ######################
# # And now we do the inversion using the appropriate configuration file
#mod = hazel.Model('conf_firs.ini', working_mode='inversion', verbose=3, randomization=5)
#mod.read_observation()
#mod.open_output()
#mod.invert()
#mod.write_output()
#mod.close_output()
iterator = hazel.Iterator(use_mpi=False)
mod = hazel.Model('conf_firs.ini',
working_mode='inversion',
verbose=3,
rank=iterator.get_rank(),
randomization=5)
iterator.use_model(model=mod)
iterator.run_all_pixels()
# Do some plots
# Open the file
f = h5py.File('output_onepixel.h5', 'r')
# Check the sizes of the output
npix, nrand, nstokes, nlambda = f['spec1']['stokes'].shape
print('(npix,nrand,nstokes,nlambda) -> {0}'.format(f['spec1']['stokes'].shape))
fig, ax = pl.subplots(nrows=2, ncols=2, figsize=(10, 10))
import hazel
import numpy as np
import matplotlib.pyplot as pl
# Define LOS theta angle
theta_los = 25.0
# Atmosphere with vertical/cartesian
mod = hazel.Model(working_mode='synthesis')
mod.add_spectral({'Name': 'spec1', 'Wavelength': [10826, 10833, 150], 'topology': 'ch1',
'LOS': [theta_los,0.0,90.0], 'Boundary condition': [1.0,0.0,0.0,0.0]})
mod.add_chromosphere({'Name': 'ch1', 'Spectral region': 'spec1', 'Height': 3.0, 'Line': '10830',
'Wavelength': [10826, 10833], 'Reference frame' : 'vertical', 'Coordinates for magnetic field vector': 'cartesian'})
mod.setup()
# Atmosphere with vertical/spherical
mod2 = hazel.Model(working_mode='synthesis')
mod2.add_spectral({'Name': 'spec1', 'Wavelength': [10826, 10833, 150], 'topology': 'ch1',
'LOS': [theta_los,0.0,90.0], 'Boundary condition': [1.0,0.0,0.0,0.0]})
mod2.add_chromosphere({'Name': 'ch1', 'Spectral region': 'spec1', 'Height': 3.0, 'Line': '10830',
'Wavelength': [10826, 10833], 'Reference frame' : 'vertical', 'Coordinates for magnetic field vector': 'spherical'})
mod2.setup()
# Atmosphere with line-of-sight/cartesian
mod3 = hazel.Model(working_mode='synthesis')
mod3.add_spectral({'Name': 'spec1', 'Wavelength': [10826, 10833, 150], 'topology': 'ch1',
'LOS': [theta_los,0.0,90.0], 'Boundary condition': [1.0,0.0,0.0,0.0]})
mod3.add_chromosphere({'Name': 'ch1', 'Spectral region': 'spec1', 'Height': 3.0, 'Line': '10830',
'Wavelength': [10826, 10833], 'Reference frame' : 'line-of-sight', 'Coordinates for magnetic field vector': 'cartesian'})
mod3.setup()
import numpy as np
import matplotlib.pyplot as pl
import hazel
iterator = hazel.Iterator(use_mpi=True)
rank = iterator.get_rank()
mod = hazel.Model('configurations/conf_mpi_invh5_mask.ini', working_mode='inversion', rank=rank, verbose=3)
iterator.use_model(model=mod)
iterator.run_all_pixels()
import numpy as np
import matplotlib.pyplot as pl
import hazel
import h5py
from ipdb import set_trace as stop
iterator = hazel.Iterator(use_mpi=True)
rank = iterator.get_rank()
mod = hazel.Model('configurations/conf_mpi_synh5.ini',
working_mode='synthesis',
rank=rank)
iterator.use_model(model=mod)
iterator.run_all_pixels()
f.write(
b'# Boundary condition I/Ic(mu=1), Q/Ic(mu=1), U/Ic(mu=1), V/Ic(mu=1)\n')
f.write(b'1.0 0.0 0.0 0.0\n')
f.write(b'\n')
f.write(b'# SI SQ SU SV sigmaI sigmaQ sigmaU sigmaV\n')
tmp = np.vstack([
stokes[x_coordinate, y_coordinate, :, l_left:l_right] / norm,
noise * np.ones((4, n_wvl))
])
np.savetxt(f, tmp.T)
f.close()
# ######################
# # And now we do the inversion using the appropriate configuration file
mod = hazel.Model('conf.ini',
working_mode='inversion',
verbose=3,
randomization=1)
mod.read_observation()
mod.open_output()
mod.invert()
mod.write_output()
mod.close_output()
# Do some plots
# Open the file
f = h5py.File('output_onepixel.h5', 'r')
# Check the sizes of the output
npix, nrand, ncycle, nstokes, nlambda = f['spec1']['stokes'].shape
print('(npix,nrand,ncycle,nstokes,nlambda) -> {0}'.format(
import numpy as np
import matplotlib.pyplot as pl
import hazel
import h5py
from ipdb import set_trace as stop
iterator = hazel.iterator(use_mpi=True)
rank = iterator.get_rank()
if (rank == 0):
mod = hazel.Model('conf_mpi_invh5.ini', working_mode='inversion')
iterator.use_model(model=mod)
else:
iterator.use_model()
iterator.run_all_pixels()
import numpy as np
import matplotlib.pyplot as pl
import hazel
import h5py
from ipdb import set_trace as stop
print(hazel.__version__)
label = ['I', 'Q', 'U', 'V']
# Instantiate the model
mod_syn = hazel.Model(working_mode='synthesis')
# Add spectral region
mod_syn.add_spectral({'Name': 'spec1', 'Wavelength': [10826, 10833, 150], 'topology': 'ch1',
'LOS': [0.0,0.0,90.0], 'Boundary condition': [1.0,0.0,0.0,0.0]})
# Add chromosphere
mod_syn.add_chromosphere({'Name': 'ch1', 'Spectral region': 'spec1', 'Height': 3.0,
'Line': '10830', 'Wavelength': [10826, 10833]})
# Finalize setup
mod_syn.setup()
# Define parameters for the chromosphere
tau = 0.5
v = 10.0
deltav = 8.0
beta = 1.0
a = 0.0
Bx = 100.0
By = 100.0
import numpy as np
import matplotlib.pyplot as pl
import hazel
# Test a single inversion in non-iterator mode
mod = hazel.Model('conf_single.ini', working_mode='synthesis')
mod.open_output()
mod.synthesize()
mod.write_output()
mod.close_output()
f, ax = pl.subplots()
ax.plot(mod.spectrum['spec1'].stokes[0, :])
pl.show()
import numpy as np
import matplotlib.pyplot as pl
import hazel
import h5py
# Test a single inversion in non-iterator mode without randomization
mod = hazel.Model('configurations/conf_inv_D3_10830.ini',
working_mode='inversion',
verbose=4)
mod.read_observation()
mod.open_output()
mod.invert()
mod.write_output()
mod.close_output()
fig, ax = pl.subplots(nrows=1, ncols=2)
f = h5py.File('output.h5', 'r')
obs1 = np.loadtxt('observations/multi_10830_stokes.1d', skiprows=7)
obs2 = np.loadtxt('observations/multi_D3_stokes.1d', skiprows=7)
ax[0].plot(obs1[:, 0])
ax[0].plot(f['spec1']['stokes'][0, 0, 0, 0, :])
ax[1].plot(obs2[:, 0])
ax[1].plot(f['spec2']['stokes'][0, 0, 0, 0, :])
pl.show()
import numpy as np
import matplotlib.pyplot as pl
import hazel
import h5py
tmp = hazel.tools.File_photosphere(mode='single')
tmp.set_default(n_pixel=1)
tmp.save('photospheres/init')
tmp = hazel.tools.File_chromosphere(mode='single')
tmp.set_default(n_pixel=1)
tmp.save('chromospheres/init')
mod = hazel.Model('conf_spot.ini', working_mode='inversion', verbose=3)
mod.read_observation()
mod.open_output()
mod.invert()
mod.write_output()
mod.close_output()
f = h5py.File('output.h5', 'r')
stokes = np.loadtxt('10830_spot.1d', skiprows=7).T
print('(npix,nrand,ncycle,nstokes,nlambda) -> {0}'.format(f['spec1']['stokes'].shape))
fig, ax = pl.subplots(nrows=2, ncols=2, figsize=(10,10))
ax = ax.flatten()
for i in range(4):
ax[i].plot(f['spec1']['wavelength'][:] - 10830, stokes[i,:])
for j in range(2):
import numpy as np
import matplotlib.pyplot as pl
import hazel
import h5py
# Test iterator with a single observation in synthesis
iterator = hazel.Iterator(use_mpi=False)
rank = iterator.get_rank()
mod = hazel.Model('configurations/conf_nonmpi_inv1d.ini',
working_mode='inversion',
verbose=4,
randomization=2)
iterator.use_model(model=mod)
iterator.run_all_pixels()
if (rank == 0):
fig, ax = pl.subplots(nrows=2, ncols=2)
ax = ax.flatten()
f = h5py.File('output.h5', 'r')
obs = np.loadtxt('observations/10830_stokes.1d', skiprows=7)
for i in range(4):
ax[i].plot(obs[:, i])
ax[i].plot(f['spec1']['stokes'][0, 0, 0, i, :])
ax[i].plot(f['spec1']['stokes'][0, 1, 0, i, :])
pl.show()
pl.pause(0.001)
f.close()
tmp = hazel.tools.File_observation(mode='single')
tmp.set_size(n_lambda=250, n_pixel=1)
tmp.obs['stokes'] = np.array([np.transpose(stokes)])
tmp.obs['sigma'] = np.array([
np.std(stokes[0, 0:15]) * np.ones((250, 1)),
np.std(stokes[1, 0:15]) * np.ones((250, 1)),
np.std(stokes[2, 0:15]) * np.ones((250, 1)),
np.std(stokes[3, 0:15]) * np.ones((250, 1))
]).transpose()
tmp.obs['los'][:] = np.full((1, 3), [90, 0, 90])
tmp.obs['boundary'][:] = np.full((1, 250, 4), [0, 0, 0, 0])
tmp.save('data/tmp_r')
# CHROMOSPHERE
tmp = hazel.tools.File_chromosphere(mode='single')
tmp.set_default(n_pixel=1, default='offlimb')
tmp.save('configurations/model_chromosphere_r')
# REMOVE USELESS FILES
os.remove('data/tmp_r.wavelength')
os.remove('data/tmp_r.weights')
# WITHOUT RANDOMIZATION
mod = hazel.Model('configurations/1d_r.ini',
working_mode='inversion',
verbose=3)
mod.read_observation()
mod.open_output()
mod.invert()
mod.write_output()
mod.close_output()
def test_coordinates():
"""
Test for magnetic fields given in spherical/cartesian geometries
and vertical/line-of-sight reference frames
"""
# Define LOS theta angle
theta_los = 25.0
# Atmosphere with vertical/cartesian
mod = hazel.Model(working_mode='synthesis')
mod.add_spectral({
'Name': 'spec1',
'Wavelength': [10826, 10833, 150],
'topology': 'ch1',
'LOS': [theta_los, 0.0, 90.0],
'Boundary condition': [1.0, 0.0, 0.0, 0.0]
})
mod.add_chromosphere({
'Name': 'ch1',
'Spectral region': 'spec1',
'Height': 3.0,
'Line': '10830',
'Wavelength': [10826, 10833],
'Reference frame': 'vertical',
'Coordinates for magnetic field vector': 'cartesian'
})
mod.setup()
# Atmosphere with vertical/spherical
mod2 = hazel.Model(working_mode='synthesis')
mod2.add_spectral({
'Name': 'spec1',
'Wavelength': [10826, 10833, 150],
'topology': 'ch1',
'LOS': [theta_los, 0.0, 90.0],
'Boundary condition': [1.0, 0.0, 0.0, 0.0]
})
mod2.add_chromosphere({
'Name': 'ch1',
'Spectral region': 'spec1',
'Height': 3.0,
'Line': '10830',
'Wavelength': [10826, 10833],
'Reference frame': 'vertical',
'Coordinates for magnetic field vector': 'spherical'
})
mod2.setup()
# Atmosphere with line-of-sight/cartesian
mod3 = hazel.Model(working_mode='synthesis')
mod3.add_spectral({
'Name': 'spec1',
'Wavelength': [10826, 10833, 150],
'topology': 'ch1',
'LOS': [theta_los, 0.0, 90.0],
'Boundary condition': [1.0, 0.0, 0.0, 0.0]
})
mod3.add_chromosphere({
'Name': 'ch1',
'Spectral region': 'spec1',
'Height': 3.0,
'Line': '10830',
'Wavelength': [10826, 10833],
'Reference frame': 'line-of-sight',
'Coordinates for magnetic field vector': 'cartesian'
})
mod3.setup()
# Atmosphere with line-of-sight/spherical
mod4 = hazel.Model(working_mode='synthesis')
mod4.add_spectral({
'Name': 'spec1',
'Wavelength': [10826, 10833, 150],
'topology': 'ch1',
'LOS': [theta_los, 0.0, 90.0],
'Boundary condition': [1.0, 0.0, 0.0, 0.0]
})
mod4.add_chromosphere({
'Name': 'ch1',
'Spectral region': 'spec1',
'Height': 3.0,
'Line': '10830',
'Wavelength': [10826, 10833],
'Reference frame': 'line-of-sight',
'Coordinates for magnetic field vector': 'spherical'
})
mod4.setup()
# Magnetic field points along the LOS
B = 0.5
thB = 25.0
phiB = 0.0
mod2.atmospheres['ch1'].set_parameters(
[B, thB, phiB, 1.0, 0.0, 8.0, 1.0, 0.0], 1.0)
mod2.synthesize()
# Transform to cartesian and check that they are the same
Bx = B * np.sin(thB * np.pi / 180) * np.cos(phiB * np.pi / 180)
By = B * np.sin(thB * np.pi / 180) * np.sin(phiB * np.pi / 180)
Bz = B * np.cos(thB * np.pi / 180)
mod.atmospheres['ch1'].set_parameters(
[Bx, By, Bz, 1.0, 0.0, 8.0, 1.0, 0.0], 1.0)
mod.synthesize()
# Compute now in LOS/spherical and check that they are the same
# We use thetaB=0 in this case because LOS is pointing along the field.
mod4.atmospheres['ch1'].set_parameters(
[B, 0.0, phiB, 1.0, 0.0, 8.0, 1.0, 0.0], 1.0)
mod4.synthesize()
np.testing.assert_allclose(mod.spectrum['spec1'].stokes,
mod2.spectrum['spec1'].stokes,
rtol=1e-5,
atol=0)
np.testing.assert_allclose(mod.spectrum['spec1'].stokes,
mod4.spectrum['spec1'].stokes,
rtol=1e-5,
atol=0)
I, Q, U, V = np.array(fits.open('data/5876_m1_20100316.fits')[0].data)
I_I_max = np.divide(I, np.transpose([np.max(I, axis=1)]))
Q_I_max = np.divide(Q, np.transpose([np.max(I, axis=1)]))
U_I_max = np.divide(U, np.transpose([np.max(I, axis=1)]))
V_I_max = np.divide(V, np.transpose([np.max(I, axis=1)]))
I_mean = np.mean(np.transpose(I_I_max[6:54]), axis=1)[300:550]
Q_mean = np.mean(np.transpose(Q_I_max[6:54]), axis=1)[300:550]
U_mean = np.mean(np.transpose(U_I_max[6:54]), axis=1)[300:550]
V_mean = np.mean(np.transpose(V_I_max[6:54]), axis=1)[300:550]
stokes = np.array([I_mean, Q_mean, U_mean, V_mean])
mod = hazel.Model(working_mode='synthesis', verbose=True)
dict = {
'Name': 'spec1',
'Wavelength': [5874.699, 5876.807, 250],
'topology': 'ch1',
'LOS': [90.0, 0.0, 90.0],
'Boundary condition': [0.0, 0.0, 0.0, 0.0]
}
mod.add_spectral(dict)
mod.add_chromosphere({
'Name': 'ch1',
'Spectral region': 'spec1',
'Height': 29.5,
'Line': '5876',
