RADIS

Examples

Using a customized residual function (below: to get the transmittance):

from radis import get_residual
db = SpecDatabase('...')
db.fit_spectrum(s_exp, get_residual=lambda s_exp, s: get_residual(s_exp, s, var='transmittance'))

You can see more examples on the Spectrum Database section More advanced tools for interactive fitting of multi-dimensional, multi-slabs spectra can be found in fitroom.

See also

fitroom

interpolate(**kwconditions)[source]¶

Interpolate existing spectra from the database to generate a new spectrum with conditions kwargs

Examples

db.interpolate(Tgas=300, mole_fraction=0.3)

print_index(file=None)[source]¶

to_dict()[source]¶

Returns all Spectra in database under a dictionary, indexed by file.

Returns:: out – {path : Spectrum object} dictionary
Return type:: dict

Note

SpecList.items().values() is equivalent to SpecList.get()

update(force_reload=False, filt='.spec', update_register_only=False)[source]¶

Reloads database, updates internal index structure and export it in <database>.csv.

Parameters:

force_reload (boolean) – if True, reloads files already in database. Default False
filt (str) – only consider files ending with filt. Default .spec

Other Parameters:

update_register_only (bool) – if True, load files and update csv but do not keep the Spectrum in memory. Default False

Notes

Can be loaded in parallel using joblib by setting the nJobs and batch_size attributes of SpecDatabase. See joblib.parallel.Parallel for information on the arguments

update_conditions()[source]¶: Reloads conditions of all Spectrum in database.

class Spectrum(quantities, units=None, conditions=None, cond_units=None, populations=None, lines=None, wunit=None, name=None, references={}, check_wavespace=True, **kwargs)[source]¶

Bases: object

This class holds results calculated with the SpectrumFactory calculation, with other radiative codes, or experimental data. It can be used to plot different quantities a posteriori, or manipulate output units (for instance convert a spectral radiance per wavelength units to a spectral radiance per wavenumber).

See more information on how to generate, edit or combine Spectrum objects on the Spectrum object guide.

Parameters:

quantities (dict of tuples {'quantity':(w, a)} or dict {'wavelength/wavenumber': w, quantity': a}) – where quantities are spectral quantities (absorbance, radiance, etc.) and wavenum is in \(cm^{-1}\) or \(nm\) (see waveunit) Example:

# w, k, I are numpy arrays for wavenumbers, absorption coefficient, and radiance.
from radis import Spectrum
s = Spectrum({"wavenumber":w, "abscoeff":k, "radiance_noslit":I}, wunit='cm-1',
             units={"radiance_noslit":"mW/cm2/sr/nm", "abscoeff":"cm-1"})

Or:

s = Spectrum({"abscoeff":(w,k), "radiance_noslit":(w,I)},
             wunit="cm-1"
             units={"radiance_noslit":"mW/cm2/sr/nm", "abscoeff":"cm-1"})

See also: from_array() and from_txt()

units (dict) – units for quantities

Other Parameters:

conditions (dict) – physical conditions and calculation parameters
wunit ('nm', 'cm-1', 'nm_vac' or None) – wavelength in air ('nm'), wavenumber ('cm-1'), or wavelength in vacuum ('nm_vac'). If None, 'wavespace' must be defined in conditions. Quantities should be evenly distributed along this space for fast convolution with the slit function
cond_units (dict) – units for conditions

Other Parameters:

name (str, or None) – Give a name to this Spectrum object (automatically used in plots; useful for multislab configurations). Default None
populations (dict) – a dictionary of all species, and levels. Should be compatible with other radiative codes such as Specair output. Suggested format: {molecules: {isotopes: {elec state: rovib levels}}} e.g:
```
{'CO2':{1: 'X': df}}   # with df a Pandas Dataframe
```
lines (pandas Dataframe) – all lines in databank (necessary for using line_survey()). Warning if you want to play with the lines content: The signification of columns in lines may be specific to a database format. Plus, some additional columns may have been added by the calculation (e.g: Ei and S for emission integral and linestrength in SpectrumFactory). Refer to the code to know what they mean (and their units)

references (dict) – a dict of doi of references used to compute this object. Automatically returned with the full bibtex entry by cite() It can also be set a posteriori. Example

s = Spectrum()
s.references = {"10.1016/j.jqsrt.2010.05.001": "HITEMP-2010 database",
              "10.1016/j.jqsrt.2018.09.027":["calculation", "post-processing"],  # RADIS main paper. Automatically added
              "10.1016/j.jqsrt.2020.107476":"DIT algorithm"}
              )
s.cite()

Returns :

Used for DIT algorithm
----------------------
@article{van_den_Bekerom_2021,
    doi = {10.1016/j.jqsrt.2020.107476},
    url = {https://doi.org/10.1016%2Fj.jqsrt.2020.107476},
    year = 2021,
    month = {mar},
    publisher = {Elsevier {BV}},
    volume = {261},
    pages = {107476},
    author = {D.C.M. van den Bekerom and E. Pannier},
    title = {A discrete integral transform for rapid spectral synthesis},
    journal = {Journal of Quantitative Spectroscopy and Radiative Transfer}
}

Used for HITEMP-2010 database
-----------------------------
@article{Rothman_2010,
    doi = {10.1016/j.jqsrt.2010.05.001},
    url = {https://doi.org/10.1016%2Fj.jqsrt.2010.05.001},
    year = 2010,
    month = {oct},
    publisher = {Elsevier {BV}},
    volume = {111},
    number = {15},
    pages = {2139--2150},
    author = {L.S. Rothman and I.E. Gordon and R.J. Barber and H. Dothe and R.R. Gamache and A. Goldman and V.I. Perevalov and S.A. Tashkun and J. Tennyson},
    title = {{HITEMP}, the high-temperature molecular spectroscopic database},
    journal = {Journal of Quantitative Spectroscopy and Radiative Transfer}
}

Used for calculation, post-processing
-------------------------------------
@article{Pannier_2019,
    doi = {10.1016/j.jqsrt.2018.09.027},
    url = {https://doi.org/10.1016%2Fj.jqsrt.2018.09.027},
    year = 2019,
    month = {jan},
    publisher = {Elsevier {BV}},
    volume = {222-223},
    pages = {12--25},
    author = {Erwan Pannier and Christophe O. Laux},
    title = {{RADIS}: A nonequilibrium line-by-line radiative code for {CO}2 and {HITRAN}-like database species},
    journal = {Journal of Quantitative Spectroscopy and Radiative Transfer}
}

</details>

warnings (boolean) – if True, test if inputs are valid, e.g, spectra are evenly distributed in wavelength, and raise a warning if not. Note that this take ~ 3.5 ms for a 20k points spectrum, when the rest of the creation process is only ~ 1.8ms (makes it 3 times longer, and can be a problem if hundreds of spectra are created in a row). Default True

Examples

Manipulate a Spectrum calculated by RADIS:

s = calc_spectrum(2125, 2300, Tgas=2000, databank='CDSD')
s.print_conditions()
s.plot('absorbance')
s.line_survey(overlay='absorbance')
s.plot('radiance_noslit', wunits='cm-1', Iunits='W/m2/sr/cm-1')
s.apply_slit(5)
s.plot('radiance')
w, t = s.get('transmittance_noslit')  # for use in multi-slabs configs

Any tuple of numpy arrays (w, I) can also be converted into a Spectrum object from the Spectrum class directly, or using the calculated_spectrum() function. All the following methods are equivalent:

from radis import Spectrum, calculated_spectrum
s1 = calculated_spectrum(w, I, wunit='nm', Iunit='mW/cm2/sr/nm')
s2 = Spectrum.from_array(w, I, 'radiance_noslit',
                       wunit='nm', unit='mW/cm2/sr/nm')
s3 = Spectrum({'radiance_noslit': (w, I)},
              units={'radiance_noslit':'mW/cm2/sr/nm'},
              wunit='nm')

See more examples in the [Spectrum] page.

Spectrum objects can be stored, retrieved, rescaled, resampled:

from radis import load_spec
s = load_spec('co_calculation.spec')
s.rescale_path_length(0.5)                  # calculate for new path_length
s.rescale_mole_fraction(0.02)   # calculate for new mole fraction
s.resample(w_new)               # resample on new wavespace
s.store('co_calculation2.spec')

Notes

Implementation:

quantities are stored in the self._q dictionary. They are better accessed with the get() method that deals with units and wavespace

Wavebase:

quantities are stored either in wavenum or wavelength base, but this doesnt matter as they are retrieved / plotted with the get() and plot() methods which have units as input arguments

conditions[source]¶

Stores computation / measurement conditions

Type:: dict

c[source]¶

convenience wrapper to conditions:

s.c["calculation_time"] is s.conditions["calculation_time"]
>> True

Type:: dict

populations[source]¶

Stores molecules, isotopes, electronic states and vibrational or rovibrational populations

Type:: dict

References

[Spectrum]

See the Spectrum object page

apply_slit(slit_function, unit='nm', shape: ['triangular', 'trapezoidal', 'gaussian'] = 'triangular', center_wavespace=None, norm_by='area', mode='valid', plot_slit=False, store=True, slit_dispersion=None, slit_dispersion_threshold=0.01, auto_recenter_crop=True, assert_evenly_spaced=True, verbose=True, inplace=True, *args, **kwargs)[source]¶

Apply an instrumental slit function to all quantities in Spectrum. Slit function can be generated with usual shapes (see shape=) or imported from an experimental slit function (path to a text file or numpy array of shape n*2). Convoluted spectra are cut on the edge compared to non-convoluted spectra, to remove side effects. See mode= to change this behaviour.

Warning with units: read about 'unit' and 'return_unit' parameters.

Parameters:

slit_function (float or str or array) –

If float:
generate slit function with FWHM of slit function (in nm or cm-1 depending on unit=). A (top, base) tuple of (float, float) is required when asking for a trapezoidal slit function.

If .txt:
import experimental slit function from .txt file: format must be 2-columns with wavelengths and intensity (doesn’t have to be normalized)

If array:
format must be 2-columns with wavelengths and intensity (doesn’t have to be normalized) It is recommended to truncate the input slit function to its minimum useful spectral extension (see Notes of convolve_with_slit()).
unit ('nm' or 'cm-1') – unit of slit_function (FWHM, or imported file)
shape ('triangular', 'trapezoidal', 'gaussian', or any of SLIT_SHAPES) –

which shape to use when generating a slit. Will call,
respectively, triangular_slit(), trapezoidal_slit(), gaussian_slit(). Default ‘triangular’
center_wavespace (float, or None) – center of slit when generated (in unit). Not used if slit is imported.
norm_by ('area', 'max') – normalisation type: - 'area' normalizes the slit function to an area

of 1. It conserves energy, and keeps the same units.
- 'max' normalizes the slit function to a maximum of 1. The convoluted spectrum units change (they are multiplied by the spectrum waveunit, e.g: a radiance non convoluted in mW/cm2/sr/nm on a wavelength (nm). range will yield a convoluted radiance in mW/cm2/sr. Note that the slit is set to 1 in the Spectrum wavespace (i.e: a Spectrum calculated in cm-1 will have a slit set to 1 in cm-1).
Default 'area'
mode ('valid', 'same') –

'same' returns output of same length as initial spectra,
but boundary effects are still visible. 'valid' returns output of length len(spectra) - len(slit) + 1, for which lines outside of the calculated range have no impact. Default 'valid'.

Other Parameters:

assert_evenly_spaced (boolean, or 'resample') – for the convolution to be accurate, w should be evenly spaced. If assert_evenly_spaced=True, then we check this is the case, and raise an error if arrays is not evenly spaced. If 'resample', then we resample w and I if needed. Recommended, but it takes some time.
auto_recenter_crop (bool) – if True, recenter slit and crop zeros on the side when importing an experimental slit. Default True. See recenter_slit(), crop_slit()
plot_slit (boolean) – if True, plot slit
store (boolean) – if True, store slit in the Spectrum object so it can be retrieved with get_slit() and plot with plot_slit(). Default True
slit_dispersion (func of (lambda, in 'nm'), or None) – spectrometer reciprocal function : dÎ»/dx(Î») (in nm) If not None, then the slit_dispersion function is used to correct the slit function for the whole range. Can be important if slit function was measured far from the measured spectrum (e.g: a slit function measured at 632.8 nm will look broader at 350 nm because the spectrometer dispersion is higher at 350 nm. Therefore it should be corrected) Default None

Warning

slit dispersion function is assumed to be given in nm if your spectrum is stored in cm-1 the wavenumbers are converted to wavelengths before being forwarded to the dispersion function

See test_auto_correct_dispersion() for an example of the slit dispersion effect.

A Python implementation of the slit dispersion:
```
>>> def f(lbd):
>>>    return  w/(2*f)*(tan(Î¦)+sqrt((2*d/m/(w*1e-9)*cos(Î¦))^2-1))
```
Theoretical / References:
```
>>> dÎ»/dx ~ d/mf    # at first order
>>> dÎ»/dx = w/(2*f)*(tan(Î¦)+sqrt((2*d/m/(w)*cos(Î¦))^2-1))  # cf
```
with:
- Î¦: spectrometer angle (Â°)
- f: focal length (mm)
- m: order of dispersion
- d: grooves spacing (mm) = 1/gr with gr in (gr/mm)
See Laux 1999 “Experimental study and modeling of infrared air plasma radiation” for more information
slit_dispersion_warning_threshold (float) – if not None, check that slit dispersion is about constant (< threshold change) on the calculated range. Default 0.01 (1%). See offset_dilate_slit_function()
inplace (bool) – if True, adds convolved arrays directly in the Spectrum. If False, returns a new Spectrum with only the convolved arrays. Note: if you want a new Spectrum with both the convolved and non convolved quantities, use
```
s.copy().apply_slit()
```
*args, **kwargs – are forwarded to slit generation or import function
verbose (bool) – print stuff
energy_threshold (float) – tolerance fraction when resampling. Default 1e-3 (0.1%) If areas before and after resampling differ by more than that an error is raised.

Returns:

Spectrum – Allows chaining. If inplace=False, return a new Spectrum with the new spectral arrays only.

Return type:

same Spectrum, with new spectral arrays.

Notes

Units:

the slit function is first converted to the wavespace (wavelength/wavenumber) that the Spectrum is stored in, and applied to the spectral quantities in their native wavespace.

Implementation:

convolve_with_slit() is applied to all quantities in get_vars() that ends with _noslit. Generate a triangular instrumental slit function (or any other shape depending of shape=) with base slit_function_base (Uses the central wavelength of the spectrum for the slit function generation)

We deal with several special cases (which makes the code a little heavy, but the method very versatile):

when slit unit and spectrum unit arent the same
when spectrum is not evenly spaced

Examples

s.apply_slit(1.2, 'nm')

This applies the instrumental function to all available spectral arrays. To manually apply the slit to a particular spectral array, use take()

s.take('transmittance_noslit').apply_slit(1.2, 'nm')

See convolve_with_slit() for more details on Units and Normalization

The slit is made considering the “center wavelength” which is the mean wavelength of the full spectrum you are applying it to.

Examples using `radis.Spectrum.apply_slit`¶

Line Survey

Calculate non-LTE spectra of carbon-monoxide

Calculate a spectrum from ExoMol

c[source]¶

cite(format='bibentry')[source]¶

Prints bibliographic references used to compute this spectrum, as stored in the references dictionary. Default references known to RADIS are listed in radis.db.references.doi.

Parameters:: format (default 'bibentry'. See more in habanero.content_negotiation())

Examples

from radis import calc_spectrum
s = calc_spectrum(
    1900,
    2300,  # cm-1
    molecule="CO",
    isotope="1,2,3",
    pressure=1.01325,  # bar
    Tvib=2000,  #
    Trot=300,
    mole_fraction=0.1,
    path_length=1,  # cm
    databank="hitran",
)
s.cite()

Returns :

Used for algorithm
------------------
@article{van_den_Bekerom_2021,
    doi = {10.1016/j.jqsrt.2020.107476},
    url = {https://doi.org/10.1016%2Fj.jqsrt.2020.107476},
    year = 2021,
    month = {mar},
    publisher = {Elsevier {BV}},
    volume = {261},
    pages = {107476},
    author = {D.C.M. van den Bekerom and E. Pannier},
    title = {A discrete integral transform for rapid spectral synthesis},
    journal = {Journal of Quantitative Spectroscopy and Radiative Transfer}
}

Used for calculation, rovibrational energies
--------------------------------------------
@article{Pannier_2019,
    doi = {10.1016/j.jqsrt.2018.09.027},
    url = {https://doi.org/10.1016%2Fj.jqsrt.2018.09.027},
    year = 2019,
    month = {jan},
    publisher = {Elsevier {BV}},
    volume = {222-223},
    pages = {12--25},
    author = {Erwan Pannier and Christophe O. Laux},
    title = {{RADIS}: A nonequilibrium line-by-line radiative code for {CO}2 and {HITRAN}-like database species},
    journal = {Journal of Quantitative Spectroscopy and Radiative Transfer}
}

Used for data retrieval
-----------------------
@article{Ginsburg_2019,
    doi = {10.3847/1538-3881/aafc33},
    url = {https://doi.org/10.3847%2F1538-3881%2Faafc33},
    year = 2019,
    month = {feb},
    publisher = {American Astronomical Society},
    volume = {157},
    number = {3},
    pages = {98},
    author = {Adam Ginsburg and Brigitta M. Sip{\H{o}}cz and C. E. Brasseur and Philip S. Cowperthwaite and Matthew W. Craig and Christoph Deil and James Guillochon and Giannina Guzman and Simon Liedtke and Pey Lian Lim and Kelly E. Lockhart and Michael Mommert and Brett M. Morris and Henrik Norman and Madhura Parikh and Magnus V. Persson and Thomas P. Robitaille and Juan-Carlos Segovia and Leo P. Singer and Erik J. Tollerud and Miguel de Val-Borro and Ivan Valtchanov and Julien Woillez and},
    title = {astroquery: An Astronomical Web-querying Package in Python},
    journal = {The Astronomical Journal}
}

Used for line database
----------------------
@article{Gordon_2017,
    doi = {10.1016/j.jqsrt.2017.06.038},
    url = {https://doi.org/10.1016%2Fj.jqsrt.2017.06.038},
    year = 2017,
    month = {dec},
    publisher = {Elsevier {BV}},
    volume = {203},
    pages = {3--69},
    author = {I.E. Gordon and L.S. Rothman and C. Hill and R.V. Kochanov and Y. Tan and P.F. Bernath and M. Birk and V. Boudon and A. Campargue and K.V. Chance and B.J. Drouin and J.-M. Flaud and R.R. Gamache and J.T. Hodges and D. Jacquemart and V.I. Perevalov and A. Perrin and K.P. Shine and M.-A.H. Smith and J. Tennyson and G.C. Toon and H. Tran and V.G. Tyuterev and A. Barbe and A.G. Cs{\'{a}}sz{\'{a}}r and V.M. Devi and T. Furtenbacher and J.J. Harrison and J.-M. Hartmann and A. Jolly and T.J. Johnson and T. Karman and I. Kleiner and A.A. Kyuberis and J. Loos and O.M. Lyulin and S.T. Massie and S.N. Mikhailenko and N. Moazzen-Ahmadi and H.S.P. Müller and O.V. Naumenko and A.V. Nikitin and O.L. Polyansky and M. Rey and M. Rotger and S.W. Sharpe and K. Sung and E. Starikova and S.A. Tashkun and J. Vander Auwera and G. Wagner and J. Wilzewski and P. Wcis{\l}o and S. Yu and E.J. Zak},
    title = {The {HITRAN}2016 molecular spectroscopic database},
    journal = {Journal of Quantitative Spectroscopy and Radiative Transfer}
}

Used for partition function
---------------------------
@article{Gamache_2021,
    doi = {10.1016/j.jqsrt.2021.107713},
    url = {https://doi.org/10.1016%2Fj.jqsrt.2021.107713},
    year = 2021,
    month = {sep},
    publisher = {Elsevier {BV}},
    volume = {271},
    pages = {107713},
    author = {Robert R. Gamache and Bastien Vispoel and Michaël Rey and Andrei Nikitin and Vladimir Tyuterev and Oleg Egorov and Iouli E. Gordon and Vincent Boudon},
    title = {Total internal partition sums for the {HITRAN}2020 database},
    journal = {Journal of Quantitative Spectroscopy and Radiative Transfer}
}
@article{Kochanov_2016,
    doi = {10.1016/j.jqsrt.2016.03.005},
    url = {https://doi.org/10.1016%2Fj.jqsrt.2016.03.005},
    year = 2016,
    month = {jul},
    publisher = {Elsevier {BV}},
    volume = {177},
    pages = {15--30},
    author = {R.V. Kochanov and I.E. Gordon and L.S. Rothman and P. Wcis{\l}o and C. Hill and J.S. Wilzewski},
    title = {{HITRAN} Application Programming Interface ({HAPI}): A comprehensive approach to working with spectroscopic data},
    journal = {Journal of Quantitative Spectroscopy and Radiative Transfer}
}

Used for spectroscopic constants
--------------------------------
@article{Guelachvili_1983,
    doi = {10.1016/0022-2852(83)90203-5},
    url = {https://doi.org/10.1016%2F0022-2852%2883%2990203-5},
    year = 1983,
    month = {mar},
    publisher = {Elsevier {BV}},
    volume = {98},
    number = {1},
    pages = {64--79},
    author = {G. Guelachvili and D. de Villeneuve and R. Farrenq and W. Urban and J. Verges},
    title = {Dunham coefficients for seven isotopic species of {CO}},
    journal = {Journal of Molecular Spectroscopy}
}

Other Examples¶

Cite all references used

See also

RefTracker, doi

compare_with(other, spectra_only=False, plot=True, wunit='default', verbose=True, rtol=1e-05, ignore_nan=False, ignore_outliers=False, normalize=False, **kwargs)[source]¶

Compare Spectrum with another Spectrum object.

Parameters:

other (type Spectrum) – another Spectrum to compare with
spectra_only (boolean, or str) – if True, only compares spectral quantities (in the same waveunit) and not lines or conditions. If str, compare a particular quantity name. If False, compare everything (including lines and conditions and populations). Default False
plot (boolean) – if True, use plot_diff to plot all quantities for the 2 spectra and the difference between them. Default True.
wunit ("nm", "cm-1", "default") – in which wavespace to compare (and plot). If "default", natural wavespace of first Spectrum is taken.
rtol (float) – relative difference to use for spectral quantities comparison
ignore_nan (boolean) – if True, nans are ignored when comparing spectral quantities
ignore_outliers (boolean, or float) –

if not False, outliers are discarded. i.e, output is determined by:
```
out = (~np.isclose(I, Ie, rtol=rtol, atol=0)).sum()/len(I) < ignore_outliers
```
normalize (bool) – Normalize the spectra to be plotted

Other Parameters:

kwargs (dict) – arguments are forwarded to plot_diff()

Returns:

equals – return True if spectra are equal (respective to tolerance defined by rtol and other input conditions)

Return type:

boolean

Examples

Compare two Spectrum objects, or specifically the transmittance:

s1.compare_with(s2)
s1.compare_with(s2, 'transmittance')

Note that you can also simply use s1 == s2, that uses compare_with() internally:

s1 == s2       # will return True or False

See also

compare_spectra()

cond_units[source]¶

conditions[source]¶

computation conditions, or experimental parameters, or any metadata you need to store with the Spectrum object.

Type:: dict

copy(copy_lines=True, quantity='all', copy_arrays=True)[source]¶

Returns a copy of this Spectrum object (performs a smart deepcopy)

Parameters:

copy_lines (bool) – default True
quantity (‘all’, or one of ‘radiance_noslit’, ‘absorbance’, etc.) – if not ‘all’, copy only one quantity. Default 'all'
copy_arrays (bool) – if False, returned array’s quantity is a pointer to the original Spectrum. Faster, but warning, changing them will then change the original Spectrum. Default True

Examples

crop(wmin=None, wmax=None, wunit='default', inplace=True)[source]¶

Crop spectrum to wmin-wmax range in wunit (inplace)

Parameters:

wmin, wmax (float, or None) – boundaries of spectral range (in wunit)
wunit ('nm', 'cm-1', 'nm_vac') – which waveunit to use for wmin, wmax. If default: use the default Spectrum wavespace defined with get_waveunit().

Other Parameters:

inplace (bool) – if True, modifies the Spectrum object directly. Else, returns a copy. Default True.

Returns:

s – Cropped Spectrum. If inplace=True, Spectrum has been updated directly anyway. Allows chaining

Return type:

Load an experimental spectrum

Examples

Crop to experimental Spectrum, and compare:

from radis import calc_spectrum, load_spec, plot_diff
s = calc_spectrum(...)
s_exp = load_spec('typical_result.spec')
s.crop(s_exp.get_wavelength.min(), s_exp.get_wavelength.max(), 'nm')
plot_diff(s_exp, s)

See also

radis.spectrum.operations.crop()

MergeSlabs(): if used with ``resample=’full’,

out, this, to

file[source]¶

classmethod from_array(w, I, quantity, wunit=None, Iunit=None, waveunit=None, unit=None, *args, **kwargs)[source]¶

Construct Spectrum from 2 arrays.

Parameters:

w, I (array) – waverange and vector
quantity (str) – spectral quantity name
wunit ('nm', 'cm-1', 'nm_vac') – unit of waverange: wavelength in air ('nm' or 'nm_air'), wavenumber ('cm-1'), or wavelength in vacuum ('nm_vac'). If None, then w must be a dimensioned array.
Iunit (str) – spectral quantity unit (arbitrary). Ex: 'mW/cm2/sr/nm' for radiance_noslit If None, then I must be a dimensioned array.
*args, **kwargs – see Spectrum doc

Other Parameters:

conditions (dict) – physical conditions and calculation parameters
cond_units (dict) – units for conditions
populations (dict) – a dictionary of all species, and levels. Should be compatible with other radiative codes such as Specair output. Suggested format: {molecules: {isotopes: {elec state: rovib levels}}} e.g:
```
{'CO2':{1: 'X': df}}   # with df a Pandas Dataframe
```
lines (pandas Dataframe) – all lines in databank (necessary for using line_survey()). Warning if you want to play with the lines content: The signification of columns in lines may be specific to a database format. Plus, some additional columns may have been added by the calculation (e.g: Ei and S for emission integral and linestrength in SpectrumFactory). Refer to the code to know what they mean (and their units)

Returns:

creates a Spectrum object

Return type:

Examples

Create a spectrum:

from radis import Spectrum
s = Spectrum.from_array(w, I, 'radiance_noslit',
                       wunit='nm', unit='mW/cm2/sr/nm')

Dimensioned arrays can also be used directly

import astropy.units as u
w = np.linspace(200, 300) * u.nm
I = np.random.rand(len(w)) * u.mW/u.cm**2/u.sr/u.nm
s = Spectrum.from_array(w, I, 'radiance_noslit')

To create a spectrum with absorption and emission components (e.g: radiance_noslit and transmittance_noslit, or emisscoeff and abscoeff) call the Spectrum class directly. Ex:

from radis import Spectrum
s = Spectrum({'abscoeff': (w, A), 'emisscoeff': (w, E)},
             units={'abscoeff': 'cm-1', 'emisscoeff':'W/cm2/sr/nm'},
             wunit='nm')

classmethod from_hdf5(file, wmin=None, wmax=None, wunit=None, columns=None, engine='pytables')[source]¶

Generates a Spectrum from an HDF5 file. Uses hdf2spec()

Other Parameters:

wmin, wmax (float) – range of wmin, wmax to load , using wunit (if None, load everything)
columns (list of str) – spectral arrays to load (if None, load everything)

Examples

Spectrum.from_hdf5("rad_hdf.h5", wmin=2100, wmax=2200, columns=['abscoeff', 'emisscoeff'])

See also

to_hdf5()

classmethod from_spec(file)[source]¶: Generates a Spectrum from a .spec [json] file. Uses load_spec()

classmethod from_specutils(spectrum, var='radiance')[source]¶

Convert a specutils specutils.spectra.spectrum1d.Spectrum1D to a radis Spectrum object.

Parameters:

spectrum (a specutils specutils.spectra.spectrum1d.Spectrum1D)
var (str) – spectral array, default "radiance"

Examples

Taken from the Specutils website (https://specutils.readthedocs.io/en/stable/#getting-started-with-specutils)

from astropy.io import fits
from astropy import units as u
from specutils import Spectrum1D

f = fits.open('https://data.sdss.org/sas/dr16/sdss/spectro/redux/26/spectra/1323/spec-1323-52797-0012.fits')
# The spectrum is in the second HDU of this file.
specdata = f[1].data

lamb = 10**specdata['loglam'] * u.AA
flux = specdata['flux'] * 10**-17 * u.Unit('erg cm-2 s-1 AA-1')
spec = Spectrum1D(spectral_axis=lamb, flux=flux)

from radis import Spectrum
s = Spectrum.from_specutils(spec)
s.plot(wunit='nm')

See also

to_specutils()

classmethod from_txt(file, quantity, wunit, unit, waveunit=None, *args, **kwargs)[source]¶

Construct Spectrum from txt file.

Parameters:

file (str) – file name
quantity (str) – spectral quantity name
wunit ('nm', 'cm-1', 'nm_vac') – unit of waverange: wavelength in air ('nm'), wavenumber ('cm-1'), or wavelength in vacuum ('nm_vac').
unit (str) – spectral quantity unit
*args, **kwargs – the following inputs are forwarded to loadtxt: 'delimiter', 'skiprows' The rest if forwarded to Spectrum. see Spectrum doc

Other Parameters:

delimiter (',', etc.) – see numpy.loadtxt()
skiprows (int) – see numpy.loadtxt()
argsort (bool) – sorts the arrays in file by wavespace. Convenient way to load a file where points have been manually added at the end. Default False.
*Optional Spectrum parameters*
conditions (dict) – physical conditions and calculation parameters
cond_units (dict) – units for conditions
populations (dict) – a dictionary of all species, and levels. Should be compatible with other radiative codes such as Specair output. Suggested format: {molecules: {isotopes: {elec state: rovib levels}}} e.g:
```
{'CO2':{1: 'X': df}}   # with df a Pandas Dataframe
```
lines (pandas Dataframe) – all lines in databank (necessary for using line_survey()). Warning if you want to play with the lines content: The signification of columns in lines may be specific to a database format. Plus, some additional columns may have been added by the calculation (e.g: Ei and S for emission integral and linestrength in SpectrumFactory). Refer to the code to know what they mean (and their units)

Returns:

s – creates a Spectrum object

Return type:

Examples

Generate an experimental spectrum from txt. In that example the delimiter key is forwarded to loadtxt():

from radis import Spectrum
s = Spectrum.from_txt('spectrum.csv', 'radiance', wunit='nm',
                          unit='W/cm2/sr/nm', delimiter=',')

To create a spectrum with absorption and emission components (e.g: radiance_noslit and transmittance_noslit, or emisscoeff and abscoeff) call the Spectrum class directly. Ex:

from radis import Spectrum
s = Spectrum({'abscoeff': (w, A), 'emisscoeff': (w, E)},
             units={'abscoeff': 'cm-1', 'emisscoeff':'W/cm2/sr/nm'},
             wunit='nm')

Notes

Internally, the numpy loadtxt() function is used and transposed:

w, I = np.loadtxt(file).T

You can use 'delimiter' and ‘skiprows' as arguments.

generate_perf_profile()[source]¶

Generate a visual/interactive performance profile diagram using tuna

Examples

s = calc_spectrum(...)
s.generate_perf_profile()

See typical output in https://github.com/radis/radis/pull/325

https://user-images.githubusercontent.com/16088743/128018032-6049be72-1881-46ac-9d7c-1ed89f9c4f42.png

Note

You can also profile with tuna directly:

python -m cProfile -o program.prof your_radis_script.py
tuna your_radis_script.py

See also

print_perf_profile()

get(var: ['radiance'], wunit='default', Iunit='default', copy=True, trim_nan=False, return_units=False)[source]¶

Retrieve a spectral quantity from a Spectrum object. You can select wavespace unit, intensity unit, or propagation medium.

Parameters:

var (variable ('absorbance', 'transmittance', 'xsection' etc.)) – Should be a defined quantity among CONVOLUTED_QUANTITIES or NON_CONVOLUTED_QUANTITIES. To get the full list of spectral arrays defined in this Spectrum object use the get_vars() method.
wunit ('nm', 'cm', 'nm_vac'.) – wavespace unit: wavelength in air ('nm'), wavenumber ('cm-1'), or wavelength in vacuum ('nm_vac'). if "default", default unit for waveunit is used. See get_waveunit().
Iunit (unit for variable var) – if "default", default unit for quantity var is used. See the units attribute. For var="radiance", one can use per wavelength (~ ‘W/m2/sr/nm’) or per wavenumber (~ ‘W/m2/sr/cm-1’) units

Note

if using default, the returned unit may be different from Spectrum.units[var]. e.g, for a Spectrum with radiance stored in ‘mW/cm2/sr/nm’, getting it with wunit='cm-1', Iunit='default' will return Iunit in ‘mW/cm2/sr/cm-1’ for consistency. Use return_units to be sure about which units are used.

Other Parameters:

copy (bool) – if True, returns a copy of the stored quantity (modifying it wont change the Spectrum object). Default True.
trim_nan (bool) – if True, removes nan on the sides of the spectral array (and corresponding wavespace). Default False.
return_units (bool) – if True, return dimensioned Astropy arrays. Is using return_units = 'as_str', return wunit and Iunit as extra variables, i.e, w, I, wunit, Iunit = s.get(..., return_units='as_str') Default False

Returns:

w, I – wavespace, quantity (ex: wavelength, radiance_noslit). For numpy users, note that these are copies (values) of the Spectrum quantity and not a view (reference): if you modify them the Spectrum is not changed

Return type:

array-like

Examples

Get transmittance in cm-1:

w, I = s.get('transmittance_noslit', wunit='cm-1')

Get radiance (in wavelength in air):

_, R = s.get('radiance_noslit', wunit='nm', Iunit='W/cm2/sr/nm')

Use with return_units to get dimensioned Astropy Quantities

w, R  = s.get('radiance_noslit', return_units=True)

get_baseline(algorithm='als', **kwargs)[source]¶

Calculate and returns a baseline

Parameters:

s (Spectrum) – Spectrum which needs a baseline
var (str) – on which spectral quantity to read the baseline. Default 'radiance'. See SPECTRAL_QUANTITIES
algorithm (‘als’, ‘polynomial’) – Asymmetric least square or Polynomial fit
**kwargs (dict) – additional parameters to send to the algorithm. By default, for ‘polynomial’:

**kwargs = **{“deg”: 1, “max_it”:500}

for ‘als’:

**kwargs = {“asymmetry_param”: 0.05,
“smoothness_param”: 1e6}

Returns:

baseline – Spectrum object where intensity is the baseline of s

Return type:

get_power(), the Spectrum page

Examples

See also

get_baseline()

get_conditions()[source]¶: Get all physical / computational parameters.

See also

print_conditions(), the Spectrum page

get_integral(var, wunit='default', Iunit='default', **kwargs)[source]¶

Returns integral of variable ‘var’ over waverange.

Parameters:

var (str) – spectral quantity to integrate
wunit (str) – over which waverange to integrated. If default, use the default Spectrum wavespace defined with get_waveunit().
Iunit (str) – default 'default'

Warning

this is the unit of the quantity, not the unit of the integral. Don’t forget to multiply by wunit

Other Parameters:

kwargs (**dict) – forwarded to get()

Returns:

integral – integral in [Iunit]*[wunit]

Return type:

float

See also

get_name()[source]¶

Return Spectrum name.

If not defined, returns either the file name if Spectrum was loaded from a file, or the 'spectrum{id}' with the Python id object

get_populations(molecule=None, isotope=None, electronic_state=None, show_warning=True)[source]¶

Return populations that are featured in the spectrum, either as upper or lower levels.

Parameters:

molecule (str, or None) – if None, only one molecule must be defined. Else, an error is raised
isotope (int, or None) – isotope number. if None, only one isotope must be defined. Else, an error is raised
electronic_state (str) – if None, only one electronic state must be defined. Else, an error is raised
show_warning (bool) – if False, turns off warning about meaning of populations, see Notes and discussion on https://github.com/radis/radis/issues/508.

Returns:

pandas dataframe of levels, where levels are the index,
and ‘Evib’ and ‘nvib’ are featured

Notes

Structure:

{molecule: {isotope: {electronic_state: {'vib': pandas Dataframe,    # (copy of) vib levels
                                         'rovib': pandas Dataframe,  # (copy of) rovib levels
                                         'Ia': float    # isotopic abundance
                                         }}}}

(If Spectrum generated with RADIS, structure should match that of SpectrumFactory.get_populations())

Examples

An example on how different are populations used for partition function and spectrum calculations

#%% CO2 example
# For instance, plot populations of a given vibrational level, v1,v2,v3=(0,1,0)
import radis
s = radis.test_spectrum(molecule="CO2", Tvib=3000, Trot=1000,
                        export_lines=True,
                        export_populations="rovib",
                        isotope=1)
pops = s.get_populations("CO2")["rovib"]

import matplotlib.pyplot as plt
pops.query("v1==0 & v2==1 & v3==0").plot("j", "n",
                                         label="pops. used to compute partition functions")
s.lines.query("v1l==0 & v2l==1 & v3l==0").plot("jl", "nl", ax=plt.gca(), kind="scatter", color="r",
                                               label="pops. of visible absorbing lines")
plt.legend()
plt.xlim((0,70))

See populations of computed levels

See also

plot_populations(), line_survey()

get_power(unit='mW/cm2/sr')[source]¶

Returns integrated radiance (no slit) power density.

Parameters:: Iunit (str) – power unit.
Returns:: P – radiated power in unit
Return type:: float

Examples

s.get_power('W/cm2/sr')

See also

get_integral(), the Spectrum page

get_quantities(which=None)[source]¶: Returns all spectral quantities stored in this object (convoluted or non convoluted). Wrapper to get_vars()

get_radiance(Iunit='mW/cm2/sr/nm', copy=True)[source]¶

Return radiance in whatever unit, and can even convert from ~1/nm to ~1/cm-1 (and the other way round)

Other Parameters:: copy (boolean) – if True, returns a copy of the stored waverange (modifying it wont change the Spectrum object). Default True.

get_radiance_noslit(Iunit='mW/cm2/sr/nm', copy=True)[source]¶

Return radiance (non convoluted) in whatever unit, and can even convert from ~1/nm to ~1/cm-1 (and the other way round)

Other Parameters:: copy (boolean) – if True, returns a copy of the stored waverange (modifying it wont change the Spectrum object). Default True.

get_rovib_levels(molecule=None, isotope=None, electronic_state=None, first=None)[source]¶

Return rovibrational levels calculated in the spectrum (energies, populations)

Parameters:

molecule (str, or None) – if None, only one molecule must be defined. Else, an error is raised
isotope (int, or None) – isotope number. if None, only one isotope must be defined. Else, an error is raised
electronic_state (str) – if None, only one electronic state must be defined. Else, an error is raised
first (int, or ‘all’ or None) – only show the first N levels. If None or ‘all’, all levels are shown

Returns:

out – pandas dataframe of levels, where levels are the index, and ‘Evib’ and ‘nvib’ are featured

Return type:

pandas DataFrame

get_slit(wunit='same')[source]¶

Get slit function that was applied to the Spectrum.

Returns:: wslit, Islit – slit function with wslit in Spectrum waveunit. See get_waveunit()
Return type:: array

get_vars(which=None)[source]¶: Returns all spectral quantities stored in this object (convoluted or non convoluted)

get_vib_levels(molecule=None, isotope=None, electronic_state=None, first=None)[source]¶

Return vibrational levels in the spectrum (energies, populations)

Parameters:

molecule (str, or None) – if None, only one molecule must be defined. Else, an error is raised
isotope (int, or None) – isotope number. if None, only one isotope must be defined. Else, an error is raised
electronic_state (str) – if None, only one electronic state must be defined. Else, an error is raised
first (int, or ‘all’ or None) – only show the first N levels. If None or ‘all’, all levels are shown

Returns:

out – pandas dataframe of levels, where levels are the index, and ‘Evib’ and ‘nvib’ are featured

Return type:

pandas DataFrame

get_wavelength(medium='air', which=None, copy=True)[source]¶

Return wavelength in defined medium.

Parameters:: medium ('air', 'vacuum') – returns wavelength as seen in air, or vacuum. Default 'air'. See vacuum2air(), air2vacuum()
Other Parameters:: copy (boolean) – if True, returns a copy of the stored waverange (modifying it wont change the Spectrum object). Default True.
Returns:: w – (a copy of) spectrum wavelength for convoluted or non convoluted quantities
Return type:: array_like

See also

LineSurvey(), the Spectrum page

get_wavenumber(which=None, copy=True)[source]¶

Return wavenumber (if the same for all quantities)

Other Parameters:: copy (boolean) – if True, returns a copy of the stored waverange (modifying it wont change the Spectrum object). Default True.
Returns:: w – (a copy of) spectrum wavenumber for convoluted or non convoluted quantities
Return type:: array_like

get_waveunit()[source]¶: Returns whether this spectrum is defined in wavelength (nm) or wavenumber (cm-1)

has_nan(ignore_wavespace=True) → bool[source]¶

Parameters:: s (Spectrum) – radis Spectrum.
Returns:: b – returns whether Spectrum has nan
Return type:: bool

Note

print(s) will also show which spectral quantities have ````nan.

is_at_equilibrium(check='warn', verbose=False)[source]¶

Returns whether this spectrum is at (thermal) equilibrium. Reads the thermal_equilibrium key in Spectrum conditions. It does not imply chemical equilibrium (mole fractions are still arbitrary)

If they are defined, also check that the following assertions are True:

Tvib = Trot = Tgas self_absorption = True overpopulation = None

If they are not, still trust the value in Spectrum conditions, but raise a warning.

Other Parameters:

check ('warn', 'error', 'ignore') – what to do if Spectrum conditions dont match the given equilibrium state: raise a warning, raise an error, or just ignore and dont even check. Default 'warn'.
verbose (bool) – if True, print why is the spectrum is not at equilibrium, if applicable.

is_optically_thin()[source]¶

Returns whether the spectrum is optically thin, based on the value on the self_absorption key in conditions.

If not given, raises an error

line_survey(overlay=None, wunit='cm-1', Iunit='hitran', medium='air', cutoff=None, plot='S', lineinfo=['int', 'A', 'El'], barwidth='hwhm_voigt', yscale='log', writefile=None, *args, **kwargs)[source]¶

Plot Line Survey (all linestrengths used for calculation) Output in: Plotly (html)

Parameters:

overlay (tuple (w, I, [name], [units]), or list or tuples) – plot (w, I) on a secondary axis. Useful to compare linestrength with calculated / measured data:
```
LineSurvey(overlay='abscoeff')
```
wunit ('nm', 'cm-1') – wavelength / wavenumber units
Iunit ('hitran', 'splot') – Linestrength output units:
- 'hitran': (cm-1/(molecule/cm-2))
- 'splot' : (cm-1/atm) (Spectraplot units [2]_)
Note: if not None, cutoff criteria is applied in this unit. Not used if plot is not ‘S’
medium ('air', 'vacuum') – show wavelength either in air or vacuum. Default 'air'
plot (str) – what to plot. Default 'S' (scaled line intensity). But it can be any key in the lines, such as population ('nu'), or Einstein coefficient ('Aul')
lineinfo (list, or 'all') – extra line information to plot. Should be a column name in the databank (s.lines). For instance: 'int', 'selbrd', etc… Default ['int']

Other Parameters:

writefile (str) – if not None, a valid filename to save the plot under .html format.
If None, use the fig object returned to show the plot.
- yscale ('log', 'linear') – Default 'log'
- barwidth (float or str) –
  
  if float, width of bars, in wunit, as a fraction of full-range; i.e.
  barwidth=0.01
  makes bars span 1% of the full range. if str, uses the column as width. Example
  barwidth = 'hwhm_voigt'
  returns:
  
  fig (a Plotly figure.) – If using a Jupyter Notebook, the plot will appear. Else, use writefile to export to an html file.
  
  Plot in Plotly. See Output in [1]_

An example using the SpectrumFactory to generate a spectrum:

from radis import SpectrumFactory
sf = SpectrumFactory(
                     wavenum_min=2380,
                     wavenum_max=2400,
                     mole_fraction=400e-6,
                     path_length=100,  # cm
                     isotope=[1],
                     export_lines=True,    # required for LineSurvey!
                     db_use_cached=True)
sf.load_databank('HITRAN-CO2-TEST')
s = sf.eq_spectrum(Tgas=1500)
s.apply_slit(0.5)
s.line_survey(overlay='radiance_noslit', barwidth=0.01, lineinfo="all")  # or barwidth='hwhm_voigt'

See the output in Examples

Line Survey

lines[source]¶

informations on emitting or absorbing lines that contribute to the spectrum.

plot(var: ['radiance'] = None, wunit='default', Iunit='default', show_points=False, nfig=None, yscale='linear', show_medium='vacuum_only', normalize=False, force=False, plot_by_parts=False, show=True, show_ruler=False, **kwargs)[source]¶

Plot a Spectrum object.

Note

default plotting library and templates can be edited in radis.config [“plot”]

Parameters:

var (variable (absorbance, transmittance, transmittance_noslit, xsection, etc.)) – For full list see get_vars(). If None, plot the first thing in the Spectrum. Default None.
wunit ('default', 'nm', 'cm-1', 'nm_vac',) – wavelength air, wavenumber, or wavelength vacuum. If 'default', Spectrum get_waveunit() is used.
Iunit (unit for variable) – if default, default unit for quantity var is used. for radiance, one can use per wavelength (~ W/m2/sr/nm) or per wavenumber (~ W/m2/sr/cm-1) units

Other Parameters:

show_points (boolean) – show calculated points. Default True.
nfig (int, None, or ‘same’) – plot on a particular figure. ‘same’ plots on current figure. For instance:
```
s1.plot()
s2.plot(nfig='same')
```
show_medium (bool, 'vacuum_only') – if True and wunit are wavelengths, plot the propagation medium in the xaxis label ([air] or [vacuum]). If 'vacuum_only', plot only if wunit=='nm_vac'. Default 'vacuum_only' (prevents from inadvertently plotting spectra with different propagation medium on the same graph).
yscale (‘linear’, ‘log’) – plot yscale
normalize (boolean, or tuple.) – option to normalize quantity to 1 (ex: for radiance). Default False
plot_by_parts (bool) – if True, look for discontinuities in the wavespace and plot the different parts without connecting lines. Useful for experimental spectra produced by overlapping step-and-glue. Additional parameters read from kwargs : split_threshold and cutwings. See more in split_and_plot_by_parts().
force (bool) – plotting on an existing figure is forbidden if labels are not the same. Use force=True to ignore that.
show (bool) – show figure. Default False. Will still show the figure in interactive mode, e.g, %matplotlib inline in a Notebook.
show_ruler (bool) – if True, add a ruler tool to the Matplotlib toolbar. Convenient to measure distances between peaks, etc.

Warning

still experimental in 0.9.30 ! Try it, feedback welcome !
**kwargs (**dict) – kwargs forwarded as argument to plot (e.g: lineshape attributes: lw=3, color='r')

Returns:

line plot

Return type:

line

Examples

Plot an experimental_spectrum() in arbitrary units:

s = experimental_spectrum(..., Iunit='mW/cm2/sr/nm')
s.plot(Iunit='W/cm2/sr/cm-1')

See more examples in the plot Spectral quantities page.

Load an experimental spectrum

Remove a baseline

Calculate non-LTE spectra of carbon-monoxide

Use different plot themes

Calculate a large spectrum by part

Calculate a spectrum from ExoMol

Post-process using Specutils

See also

plot_diff(), the Spectrum page

plot_populations(what=None, nunit='', correct_for_abundance=False, **kwargs)[source]¶

Plots vib populations if given and format is valid.

Parameters:

what (‘vib’, ‘rovib’, None) – if None plot everything
nunit (‘’, ‘cm-3’) – plot either in a fraction of vibrational levels, or a molecule number in in cm-3
correct_for_abundance (boolean) – if True, multiplies each population by the isotopic abundance (as it is done during the calculation of emission integral)
kwargs (**dict) – are forwarded to the plot

Examples

See populations of computed levels

See also

get_populations(), line_survey()

plot_slit(wunit=None, waveunit=None)[source]¶

Plot slit function that was applied to the Spectrum.

If dispersion was used (see apply_slit()) the different slits are built again and plotted too (dotted).

Parameters:

wunit ('nm', 'cm-1', or None) – plot slit in wavelength or wavenumber. If None, use the unit the slit in which the slit function was given. Default None

Returns:

fix, ax (matplotlib objects) – figure and ax
.. minigallery:: radis.spectrum.spectrum.Spectrum.plot_slit

See also

generate_perf_profile()

populations[source]¶

populations of rovibrational levels used to compute partition functions of the spectrum

print_conditions(**kwargs)[source]¶

Prints all physical / computational parameters.

Parameters:: kwargs (dict) – refer to print_conditions()

Examples

::: s.print_conditions()

You can also simply print the Spectrum object directly:

print(s)

print_perf_profile(number_format='{:.3f}', precision=16)[source]¶

Prints Profiler output dictionary in a structured manner.

Example

Spectrum.print_perf_profile()

# output >>
    spectrum_calculation      0.189s ████████████████
        check_line_databank              0.000s
        check_non_eq_param               0.042s ███
        fetch_energy_5                   0.015s █
        calc_weight_trans                0.008s
        reinitialize                     0.002s
            copy_database                    0.000s
            memory_usage_warning             0.002s
            reset_population                 0.000s
        calc_noneq_population            0.041s ███
            part_function                    0.035s ██
            population                       0.006s
        scaled_non_eq_linestrength       0.005s
            map_part_func                    0.001s
            corrected_population_se          0.003s
        calc_emission_integral           0.006s
        applied_linestrength_cutoff      0.002s
        calc_lineshift                   0.001s
        calc_hwhm                        0.007s
        generate_wavenumber_arrays       0.001s
        calc_line_broadening             0.074s ██████
            precompute_LDM_lineshapes        0.012s
            LDM_Initialized_vectors          0.000s
            LDM_closest_matching_line        0.001s
            LDM_Distribute_lines             0.001s
            LDM_convolve                     0.060s █████
            others                           0.001s
        calc_other_spectral_quan         0.003s
        generate_spectrum_obj            0.000s
        others                           -0.016s

Other Parameters:: precision (int, optional) – total number of blocks. Default 16.

See also

references[source]¶

resample(w_new, unit='same', out_of_bounds='nan', energy_threshold='default', print_conservation=False, inplace=True, if_conflict_drop=None, **kwargs)[source]¶

Resample spectrum over a new wavelength/wavenumber range.

Warning

This may result in information loss. Resampling is done with oversampling and spline interpolation. These parameters can be adjusted, and energy conservation ensured with the appropriate parameters.

To minimize information loss, always resample the high-resolution spectrum over the low-resolution spectrum, i.e.

s_highres.resample(s_lowres)

Fills with 'nan' or transparent medium (transmittance 1, radiance 0) when out of bound (see out_of_bounds)

Parameters:

w_new (array, or Spectrum) – new wavespace to resample the spectrum on. Must be inclosed in the current wavespace (we won’t extrapolate) One can also give a Spectrum directly:
```
s1.resample(s2.get_wavenumber())
s1.resample(s2)            # also valid
```
unit ('same', 'nm', 'cm-1', 'nm_vac') – unit of new wavespace. It 'same' it is assumed to be the current waveunit. Default 'same'. The spectrum waveunit is changed to this unit after resampling (i.e: a spectrum calculated and stored in cm-1 but resampled in nm will be stored in nm from now on). If 'nm', wavelength in air. If 'nm_vac', wavelength in vacuum.
out_of_bounds ('transparent', 'nan', 'error') – what to do if resampling is out of bounds. 'transparent': fills with transparent medium. ‘nan’: fill with nan. 'error': raises an error. Default 'nan'
medium ('air', 'vacuum', or 'default') – in which medium is the new waverange is calculated if it is given in ‘nm’. Ignored if unit=’cm-1’

Other Parameters:

energy_threshold (float or None or 'default') -- if energy conservation (integrals on the intersecting range) is above this threshold, raise an error. If ``None, dont check for energy conservation. If 'default', look up the value in radis.config [“RESAMPLING_TOLERANCE_THRESHOLD”] Default 'default'
print_conservation (boolean) – if True, prints energy conservation. Default False.
inplace (boolean) – if True, modifies the Spectrum object directly. Else, returns a copy. Default True.
**kwargs (**dict) – all other arguments are sent to radis.misc.signal.resample()

Returns:

Spectrum – object has been modified anyway.

Return type:

resampled Spectrum object. If using inplace=True, the Spectrum

Examples

Convert a Spectrum in wavenumber to wavelengths:

s_nm = s.resample(s.get_wavelength(), "nm", inplace=False)

resample_even(energy_threshold=0.005, print_conservation=False, inplace=True)[source]¶

Resample spectrum over the same waverange, but evenly spaced.

Warning

This may result in information loss. Resampling is done with oversampling and spline interpolation. These parameters can be adjusted, and energy conservation ensured with the appropriate parameters.

Parameters:

energy_threshold (float or None) – if energy conservation (integrals on the intersecting range) is above this threshold, raise an error. If None, dont check for energy conservation Default 5e-3 (0.5%)
print_conservation (boolean) – if True, prints energy conservation. Default False.
inplace (boolean) – if True, modifies the Spectrum object directly. Else, returns a copy. Default True.
**kwargs (**dict) – all other arguments are sent to radis.misc.signal.resample()

Returns:

Spectrum – object has been modified anyway.

Return type:

resampled Spectrum object. If using inplace=True, the Spectrum

Examples

rescale_mole_fraction(new_mole_fraction, old_mole_fraction=None, inplace=True, ignore_warnings=False, force=False, verbose=True)[source]¶

Update spectrum with new molar fraction Convoluted values (with slit) are dropped in the process.

Parameters:

new_mole_fraction (float) – new mole fraction
old_mole_fraction (float, or None) – if None, current mole fraction (conditions[‘mole_fraction’]) is used

Other Parameters:

inplace (boolean) – if True, modifies the Spectrum object directly. Else, returns a copy. Default True.
force (boolean) – if False, won’t allow rescaling to 0 (not to loose information). Default False

Returns:

s – Cropped Spectrum. If inplace=True, Spectrum has been updated directly anyway. Allows chaining

Return type:

Examples

s.rescale_mole_fraction(0.2)

Notes

Implementation:

similar to rescale_path_length() but we have to scale abscoeff & emisscoeff Note that this is valid only for small changes in mole fractions. Then, the change in line broadening becomes significant

See also

rescale_path_length(new_path_length, old_path_length=None, inplace=True, force=False)[source]¶

Rescale spectrum to new path length. Starts from absorption coefficient and emission coefficient, and solves the RTE again for the new path length Convoluted values (with slit) are dropped in the process.

Parameters:

new_path_length (float) – new path length
old_path_length (float, or None) – if None, current path length (conditions[‘path_length’]) is used

Other Parameters:

inplace (boolean) – if True, modifies the Spectrum object directly. Else, returns a copy. Default True.
force (boolean) – if False, won’t allow rescaling to 0 (not to loose information). Default False

Returns:

s – Cropped Spectrum. If inplace=True, Spectrum has been updated directly anyway. Allows chaining

Return type:

Examples

for path in [0.1, 10, 100]:
    s.rescale_path_length(10, inplace=False).plot(nfig='same')

Additionally, you can also use astropy units in the input arguments, for example:

# preparing a test spectrum :
import radis
s = radis.test_spectrum()

# rescaling :
import astropy.units as u
s.rescale_path_length(1 * u.km).plot()

Notes

Implementation:

To deal with all the input cases, we first make a list of what has to be recomputed, and what has to be recalculated

See also

New fitting module introduction - simple 1-temperature LTE case

save(*args, **kwargs)[source]¶

Alias to Spectrum.store.

See Spectrum.store for documentation

savetxt(filename, var, wunit='default', Iunit='default')[source]¶

Export spectral quantity var to filename.

(note that by doing this you will loose additional information, such: as the calculation conditions or the units. You better save a Spectrum object under a .spec file with store() and load it afterwards with load_spec())

Parameters:

filename (str) – file name
var (str) – which spectral variable ot export

Other Parameters:

wunit, Iunit, medium (str) – see get() for more information

Notes

Export variable as:

np.savetxt(filename, np.vstack(self.get(var, wunit=wunit, Iunit=Iunit,
                                    medium=medium)).T, header=header)

See also

store(), save(), the Spectrum page

sort(inplace=True)[source]¶

Sort the Spectrum by wavelength / wavenumber.

Parameters:: inplace (bool, optional) – if True, modifies the Spectrum object directly. The default is True.
Returns:: s – sorted Spectrum. If inplace=True, Spectrum has been updated directly anyway. Allows chaining.
Return type:: Spectrum

Examples

store(path, discard=['lines', 'populations'], compress=True, add_info=None, add_date=None, if_exists_then='error', verbose=True)[source]¶

Save a Spectrum object in JSON format. Object can be recovered with load_spec(). If many Spectrum are saved in a same folder you can view their properties with the SpecDatabase structure.

Parameters:

path (path to folder (database) or file) – if a folder, file is saved to database and name is generated automatically. if a file name, then Spectrum is saved to this file and the later formatting options dont apply
file (str) – explicitly give a filename to save
compress (boolean) – if False, save under text format, readable with any editor. if True, saves under binary format. Faster and takes less space. If 2, removes all quantities that can be regenerated with s.update(), e.g, transmittance if abscoeff and path length are given, radiance if emisscoeff and abscoeff are given in non-optically thin case, etc. Default True.
add_info (list) – append these parameters and their values if they are in conditions example:
```
add_info = ['Tvib', 'Trot']
```
discard (list of str) – parameters to exclude, for instance to save some memory for instance Default [lines, populations]: retrieved Spectrum looses the line_survey() ability, and plot_populations() (but it saves tons of memory!)
if_exists_then ('increment', 'replace', 'error', 'ignore') – what to do if file already exists. If increment an incremental digit is added. If replace file is replaced (yeah). If 'ignore' no file is created. If error (or anything else) an error is raised. Default error

Return type:

Returns filename used

Notes

If many spectra are stored in a folder, it may be time to set up a SpecDatabase structure to easily see all Spectrum conditions and get Spectrum that suits specific parameters.

Examples

Store a spectrum in compressed mode, regenerate quantities after loading:

from radis import load_spec
s.store('test.spec', compress=True)   # s is a Spectrum
s2 = load_spec('test.spec')
s2.update()                           # regenerate missing quantities

Examples using `radis.spectrum.spectrum.Spectrum.store`¶

take(var, copy_lines=False, copy_arrays=True)[source]¶

Parameters:

var (str) – spectral quantity ('absorbance', 'transmittance', 'xsection' etc.)

Other Parameters:

copy_lines (bool) – if True, export s.lines. Default False
copy_arrays (bool) – if False, returned array’s quantity is a pointer to the original Spectrum. Faster, but warning, changing them will then change the original Spectrum. Default True

Returns:

s – same Spectrum with only the var spectral quantity

Return type:

Examples

Use take to chain other commands

s.take('radiance').normalize().plot()

to_hdf5(file, engine='pytables')[source]¶

Stores the Spectrum under HDF5 format. Uses spec2hdf()

Examples

s.to_hdf5('spec01.h5')

See also

from_hdf5()

to_json(*args, **kwargs)[source]¶

Alias to Spectrum.store(compress=False).

See Spectrum. store() for documentation

to_pandas(copy=True)[source]¶

Convert a Spectrum to a Pandas DataFrame

Returns:: pd.DataFrame – units are stored in attributes df.attrs
Return type:: pandas DataFrame where columns are spectral arrays, and

Notes

Pandas does not support units yet. pint-pandas is an advanced project but not fully working. See discussion in https://github.com/pandas-dev/pandas/issues/10349

For the moment, we store units as metadata

to_specutils(var=None, wunit='default', Iunit='default')[source]¶

Convert a radis Spectrum object to specutils specutils.spectra.spectrum1d.Spectrum1D

Parameters:

var (‘radiance’, ‘radiance_noslit’, etc.) – which spectral array to convert. If None and only one spectral array is defined, use it.
wunit ('nm', 'cm', 'nm_vac'.) – wavespace unit: wavelength in air ('nm'), wavenumber ('cm-1'), or wavelength in vacuum ('nm_vac'). if "default", default unit for waveunit is used. See get_waveunit().

Note

specutils handles wavelengths in vacuum only. If using 'nm' wavelengths will be converted to wavelengths in vacuum. We recommend using 'nm_air' or 'nm_vac' to avoid any confusion.
Iunit (unit for variable var) – if "default", default unit for quantity var is used. See the units attribute. For var="radiance", one can use per wavelength (~ ‘W/m2/sr/nm’) or per wavenumber (~ ‘W/m2/sr/cm-1’) units
.. note:: – nan, that may have been added on the wings of the spectra if a slit has been applied, are removed using trim_nan parameter of get() . The waverange in the 1DSpectrum object may therefore be cropped.

Examples

spectrum = s.to_specutils()

Add uncertainties by reading a spectrum noise region with SpectralRegion and noise_region_uncertainty()

from specutils import SpectralRegion
from specutils.manipulation import noise_region_uncertainty
noise_region = SpectralRegion(2012 / u.cm, 2009 / u.cm)
spectrum = noise_region_uncertainty(spectrum, noise_region)

Find lines out of the noise using find_lines_threshold()

from specutils.fitting import find_lines_threshold
lines = find_lines_threshold(spectrum)

See also

from_specutils()

trim(inplace=True)[source]¶

Remove nan common to all arrays on each side of the Spectrum.

Returns a smaller Spectrum (inplace or not).

Returns:: s – directly anyway. Allows chaining.
Return type:: Spectrum : trimmed Spectrum. If inplace=True, Spectrum has been updated

units[source]¶

units for spectral quantities.

Type:: dict

update(quantity='all', optically_thin='default', verbose=True)[source]¶

Calculate missing quantities: ex: if path_length and emisscoeff are given, recalculate radiance_noslit.

Parameters:

spec (Spectrum)
quantity (str) – name of the spectral quantity to recompute. If ‘same’, only the quantities in the Spectrum are recomputed. If ‘all’, then all quantities that can be derived are recomputed. Default ‘all’.
optically_thin (True, False, or ‘default’) – determines whether to calculate radiance with or without self absorption. If ‘default’, the value is determined from the self_absorption key in Spectrum.conditions. If not given, False is taken. Default ‘default’ Also updates the self_absorption value in conditions (creates it if doesnt exist

Examples

Initialize a spectrum from the absorption coefficient, retrieve the transmittance or the emission coefficient :

s = Spectrum.from_array([1900.  , 1900.01, 1900.02, 1900.03, 1900.04, 1900.05, 1900.06,
                         1900.07, 1900.08, 1900.09],
                        [2.71414065e-06, 2.88341489e-06, 3.06942277e-06, 3.27445689e-06,
                         3.50121831e-06, 3.75290756e-06, 4.03334037e-06, 4.34709612e-06,
                         4.69971017e-06, 5.09792551e-06],
                        'abscoeff',
                        wunit='cm-1',
                        Iunit='cm-1',
                        conditions={'path_length':1, # cm
                                    'thermal_equilibrium':True,
                                    'Tgas':700,  # K
                                    })
s.update('transmittance_noslit')
s.update('emisscoeff')

See also

class SpectrumFactory(wmin=None, wmax=None, wunit=cm - 1, wavenum_min=None, wavenum_max=None, wavelength_min=None, wavelength_max=None, Tref=296, pressure=1.01325, mole_fraction=1, path_length=1, wstep=0.01, molecule=None, isotope='all', medium='air', truncation=50, neighbour_lines=0, pseudo_continuum_threshold=0, self_absorption=True, chunksize=None, optimization='simple', folding_thresh=1e-06, zero_padding=-1, broadening_method='voigt', cutoff=0, parsum_mode='full summation', verbose=True, warnings=True, save_memory=False, export_populations=None, export_lines=False, emulate_gpu=False, diluent='air', **kwargs)[source]¶

Bases: BandFactory

A class to put together all functions related to loading CDSD / HITRAN databases, calculating the broadenings, and summing over all the lines.

Parameters:

wmin, wmax (float or Quantity) – a hybrid parameter which can stand for minimum (maximum) wavenumber or minimum (maximum) wavelength depending upon the unit accompanying it. If dimensionless, wunit is considered as the accompanying unit.
wunit ('nm', 'cm-1') – the unit accompanying wmin and wmax. Can only be passed with wmin and wmax. Default is "cm-1".
wavenum_min, wavenum_max (float(cm^-1) or Quantity) – minimum (maximum) wavenumber to be processed in \(cm^{-1}\). use astropy.units to specify arbitrary inverse-length units.
wavelength_min, wavelength_max (float(nm) or Quantity) – minimum (maximum) wavelength to be processed in \(nm\). This wavelength can be in 'air' or 'vacuum' depending on the value of the parameter medium=. use astropy.units to specify arbitrary length units.
pressure (float(bar) or Quantity) – partial pressure of gas in bar. Default 1.01325 (1 atm). use astropy.units to specify arbitrary pressure units. For example, 1013.25 * u.mbar.
mole_fraction (float [ 0 - 1]) – species mole fraction. Default 1. Note that the rest of the gas is considered to be air for collisional broadening.
path_length (float(cm) or Quantity) – path length in cm. Default 1. use astropy.units to specify arbitrary length units.
molecule (int, str, or None) – molecule id (HITRAN format) or name. If None, the molecule can be inferred from the database files being loaded. See the list of supported molecules in MOLECULES_LIST_EQUILIBRIUM and MOLECULES_LIST_NONEQUILIBRIUM. Default None.
isotope (int, list, str of the form '1,2', or 'all') – isotope id (sorted by relative density: (eg: 1: CO2-626, 2: CO2-636 for CO2). See HITRAN documentation for isotope list for all species. If ‘all’, all isotopes in database are used (this may result in larger computation times!). Default 'all'
medium ('air', 'vacuum') – propagating medium when giving inputs with 'wavenum_min', 'wavenum_max'. Does not change anything when giving inputs in wavenumber. Default 'air'
diluent (str or dictionary) – can be a string of a single diluent or a dictionary containing diluent name as key and its mole_fraction as value. Default air.

Other Parameters:

Tref (K) – Reference temperature for calculations (linestrength temperature correction). HITRAN database uses 296 Kelvin. Default 296 K
self_absorption (boolean) – Compute self absorption. If False, spectra are optically thin. Default True.
truncation (float (\(cm^{-1}\))) – Half-width over which to compute the lineshape, i.e. lines are truncated on each side after truncation (\(cm^{-1}\)) from the line center. If None, use no truncation (lineshapes spread on the full spectral range). Default is 300 \(cm^{-1}\)

Note

Large values (> 50) can induce a performance drop (computation of lineshape typically scale as \(~truncation ^2\) ). The default 300 was chosen to maintain a good accuracy, and still exhibit the sub-Lorentzian behavior of most lines far (few hundreds \(cm^{-1}\)) from the line center.
neighbour_lines (float (\(cm^{-1}\))) – The calculated spectral range is increased (by neighbour_lines cm-1 on each side) to take into account overlaps from out-of-range lines. Default is 0 \(cm^{-1}\).
wstep (float (cm-1) or 'auto') – Resolution of wavenumber grid. Default 0.01 cm-1. If 'auto', it is ensured that there are slightly more points for each linewidth than the value of "GRIDPOINTS_PER_LINEWIDTH_WARN_THRESHOLD" in radis.config (~/radis.json)

Note

wstep = ‘auto’ is optimized for performances while ensuring accuracy, but is still experimental in 0.9.30. Feedback welcome!
cutoff (float (~ unit of Linestrength: cm-1/(#.cm-2))) – discard linestrengths that are lower that this, to reduce calculation times. 1e-27 is what is generally used to generate databases such as CDSD. If 0, no cutoff. Default 1e-27.
parsum_mode (‘full summation’, ‘tabulation’) – how to compute partition functions, at nonequilibrium or when partition function are not already tabulated. 'full summation' : sums over all (potentially millions) of rovibrational levels. 'tabulation' : builds an on-the-fly tabulation of rovibrational levels (500 - 4000x faster and usually accurate within 0.1%). Default full summation'

Note

parsum_mode= ‘tabulation’ is new in 0.9.30, and makes nonequilibrium calculations of small spectra extremely fast. Will become the default after 0.9.31.
pseudo_continuum_threshold (float) – if not 0, first calculate a rough approximation of the spectrum, then moves all lines whose linestrength intensity is less than this threshold of the maximum in a semi-continuum. Values above 0.01 can yield significant errors, mostly in highly populated areas. 80% of the lines can typically be moved in a continuum, resulting in 5 times faster spectra. If 0, no semi-continuum is used. Default 0.
save_memory (boolean) – if True, removes databases calculated by intermediate functions (for instance, delete the full database once the linestrength cutoff criteria was applied). This saves some memory but requires to reload the database & recalculate the linestrength for each new parameter. Default False.
export_populations ('vib', 'rovib', None) – if not None, store populations in Spectrum. Either store vibrational populations (‘vib’) or rovibrational populations (‘rovib’). Default None
export_lines (boolean) – if True, saves details of all calculated lines in Spectrum. This is necessary to later use line_survey(), but can take some space. Default False.
chunksize (int, or None) – Splits the lines database in several chunks during calculation, else the multiplication of lines over all spectral range takes too much memory and slows the system down. Chunksize let you change the default chunk size. If None, all lines are processed directly. Usually faster but can create memory problems. Default None
optimization ("simple", "min-RMS", None) – If either "simple" or "min-RMS" LDM optimization for lineshape calculation is used: - "min-RMS" : weights optimized by analytical minimization of the RMS-error (See: [Spectral-Synthesis-Algorithm]) - "simple" : weights equal to their relative position in the grid

If using the LDM optimization, broadening method is automatically set to 'fft'. If None, no lineshape interpolation is performed and the lineshape of all lines is calculated.

Refer to [Spectral-Synthesis-Algorithm] for more explanation on the LDM method for lineshape interpolation.

Default "min-RMS"
folding_thresh (float) – Folding is a correction procedure that is applied when the lineshape is calculated with the fft broadening method and the linewidth is comparable to wstep, that prevents sinc(v) modulation of the lineshape. Folding continues until the lineshape intensity is below folding_threshold. Setting to 1 or higher effectively disables folding correction.

Range: 0.0 < folding_thresh <= 1.0 Default: 1e-6
zero_padding (int) – Zero padding is used in conjunction with the fft broadening method to prevent circular convolution at the cost of performance. When set to -1, padding is set equal to the spectrum length, which guarantees a linear convolution.

Range: 0 <= zero_padding <= len(w), or zero_padding = -1 Default: -1
broadening_method ("voigt", "convolve", "fft") – Calculates broadening with a direct voigt approximation (‘voigt’) or by convoluting independently calculated Doppler and collisional broadening (‘convolve’). First is much faster, 2nd can be used to compare results. This SpectrumFactory parameter can be manually adjusted a posteriori with:
```
sf = SpectrumFactory(...)
sf.params.broadening_method = 'voigt'
```
Fast fourier transform 'fft' is only available if using the LDM lineshape calculation optimization. Because the LDM convolves all lines at the same time, and thus operates on large arrays, 'fft' becomes more appropriate than convolutions in real space ('voigt', 'convolve' )

By default, use "fft" for any optimization, and "voigt" if optimization is None .
warnings (bool, or one of ['warn', 'error', 'ignore'], dict) – If one of ['warn', 'error', 'ignore'], set the default behaviour for all warnings. Can also be a dictionary to set specific warnings only. Example:
```
warnings = {'MissingSelfBroadeningWarning':'ignore',
            'NegativeEnergiesWarning':'ignore',
            'HighTemperatureWarning':'ignore'}
```
See default_warning_status for more information.
verbose (boolean, or int) – If False, stays quiet. If True, tells what is going on. If >=2, gives more detailed messages (for instance, details of calculation times). Default True.

Examples

An example using SpectrumFactory, load_databank(), the Spectrum methods, and units

from radis import SpectrumFactory
from astropy import units as u
sf = SpectrumFactory(wavelength_min=4165 * u.nm,
                     wavelength_max=4200 * u.nm,
                     isotope='1,2',
                     truncation=10,  # cm-1
                     optimization=None,
                     medium='vacuum',
                     verbose=1,    # more for more details
                     )
sf.load_databank('HITRAN-CO2-TEST')        # predefined in ~/radis.json
s = sf.eq_spectrum(Tgas=300 * u.K, path_length=1 * u.cm)
s.rescale_path_length(0.01)    # cm
s.plot('radiance_noslit', Iunit='µW/cm2/sr/nm')

Refer to the online Examples for more cases.

Examples using `radis.SpectrumFactory`¶

Real-time GPU Accelerated Spectra (Interactive)

Use Custom Abundances

Spectrum Database

Multi-temperature Fit

1 temperature fit

Compare performance between old 1T fitting example and new fitting module

Notes

digraph inheritanceb7d785f131 { bgcolor=transparent; rankdir=LR; size="8.0, 12.0"; "BandFactory" [URL="radis.lbl.bands.html#radis.lbl.bands.BandFactory",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="See Also"]; "BroadenFactory" -> "BandFactory" [arrowsize=0.5,style="setlinewidth(0.5)"]; "BaseFactory" [URL="radis.lbl.base.html#radis.lbl.base.BaseFactory",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top"]; "DatabankLoader" -> "BaseFactory" [arrowsize=0.5,style="setlinewidth(0.5)"]; "BroadenFactory" [URL="radis.lbl.broadening.html#radis.lbl.broadening.BroadenFactory",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="A class that holds all broadening methods."]; "BaseFactory" -> "BroadenFactory" [arrowsize=0.5,style="setlinewidth(0.5)"]; "DatabankLoader" [URL="radis.lbl.loader.html#radis.lbl.loader.DatabankLoader",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip=".. inheritance-diagram:: radis.lbl.factory.SpectrumFactory"]; "SpectrumFactory" [URL="radis.lbl.factory.html#radis.lbl.factory.SpectrumFactory",fillcolor=white,fontname="Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans",fontsize=10,height=0.25,shape=box,style="setlinewidth(0.5),filled",target="_top",tooltip="A class to put together all functions related to loading CDSD / HITRAN"]; "BandFactory" -> "SpectrumFactory" [arrowsize=0.5,style="setlinewidth(0.5)"]; }

High-level wrapper to SpectrumFactory:

calc_spectrum()

Main Methods:

For advanced use:

Inputs and parameters can be accessed a posteriori with :

input : physical input
params : computational parameters
misc : miscellaneous parameters (don’t change output)

See also

calc_spectrum()

eq_spectrum(Tgas, mole_fraction=None, path_length=None, diluent=None, pressure=None, name=None) → Spectrum[source]¶

Generate a spectrum at equilibrium.

Parameters:

Tgas (float or Quantity) – Gas temperature (K)
mole_fraction (float) – database species mole fraction. If None, Factory mole fraction is used.
diluent (str or dictionary) – can be a string of a single diluent or a dictionary containing diluent name as key and its mole_fraction as value
path_length (float or Quantity) – slab size (cm). If None, the default Factory path_length is used.
pressure (float or Quantity) – pressure (bar). If None, the default Factory pressure is used.
name (str) – output Spectrum name (useful in batch)

Returns:

s –

Returns a Spectrum object

Use the get() method to get something among ['radiance', 'radiance_noslit', 'absorbance', etc...]

Or directly the plot() method to plot it. See [1]_ to get an overview of all Spectrum methods

Return type:

Examples

::

from radis import SpectrumFactory sf = SpectrumFactory( wavenum_min=2900, wavenum_max=3200, molecule=”OH”, wstep=0.1, ) sf.fetch_databank(“hitemp”)

s1 = sf.eq_spectrum(Tgas=300, path_length=1, pressure=0.1) s2 = sf.eq_spectrum(Tgas=500, path_length=1, pressure=0.1)

References

See also

non_eq_spectrum()

eq_spectrum_gpu(Tgas, mole_fraction=None, diluent=None, path_length=None, pressure=None, name=None, emulate=False) → Spectrum[source]¶

Generate a spectrum at equilibrium with calculation of lineshapes and broadening done on the GPU.

Note

This method requires CUDA compatible hardware to execute. For more information on how to setup your system to run GPU-accelerated methods using CUDA and Cython, check GPU Spectrum Calculation on RADIS

Parameters:

Tgas (float or Quantity) – Gas temperature (K)
mole_fraction (float) – database species mole fraction. If None, Factory mole fraction is used.
path_length (float or Quantity) – slab size (cm). If None, the default Factory path_length is used.
pressure (float or Quantity) – pressure (bar). If None, the default Factory pressure is used.
name (str) – output Spectrum name (useful in batch)

Other Parameters:

emulate (bool) – if True, execute the GPU code on the CPU (useful for development)

Returns:

s –

Returns a Spectrum object

Use the get() method to get something among ['radiance', 'radiance_noslit', 'absorbance', etc...]

Or directly the plot() method to plot it. See [1]_ to get an overview of all Spectrum methods

Return type:

Examples

Examples using `radis.lbl.SpectrumFactory.eq_spectrum_gpu`¶

Real-time GPU Accelerated Spectra (Interactive)

eq_spectrum_gpu_interactive(var='transmittance', slit_FWHM=0.0, plotkwargs={}, *vargs, **kwargs) → Spectrum[source]¶

Parameters:

var (TYPE, optional) – DESCRIPTION. The default is “transmittance”.
slit_FWHM (TYPE, optional) – DESCRIPTION. The default is 0.0.
*vargs (TYPE) – arguments forwarded to eq_spectrum_gpu()
**kwargs (dict) – arguments forwarded to eq_spectrum_gpu() In particular, see emulate=.
plotkwargs (dict) – arguments forwarded to plot()

Returns:

s – DESCRIPTION.

Return type:

TYPE

Examples

from radis import SpectrumFactory
from radis.tools.plot_tools import ParamRange

sf = SpectrumFactory(2200, 2400, # cm-1
                  molecule='CO2',
                  isotope='1,2,3',
                  wstep=0.002,
                  )

sf.fetch_databank('hitemp')

s = sf.eq_spectrum_gpu_interactive(Tgas=ParamRange(300.0,2000.0,1200.0), #K
                               pressure=0.2, #bar
                               mole_fraction=0.1,
                               path_length=ParamRange(0,10,2.0), #cm
                               slit_FWHM=ParamRange(0,1,0), #cm
                               emulate=False,  # if True, execute the GPU code on the CPU
                               )

fit_spectrum(s_exp, model, fit_parameters, bounds={}, plot=False, solver_options={'maxiter': 300}, **kwargs) → Spectrum | OptimizeResult[source]¶

Fit an experimental spectrum with an arbitrary model and an arbitrary number of fit parameters.

Parameters:

s_exp (Spectrum) – experimental spectrum. Should have only spectral array only. Use take(), e.g:
```
sf.fit_spectrum(s_exp.take('transmittance'))
```
model (func -> Spectrum) – a line-of-sight model returning a Spectrum. Example : Tvib12Tvib3Trot_NonLTEModel()
fit_parameters (dict) –

example:
```
{fit_parameter:initial_value}
```
bounds (dict, optional) –

example:
```
{fit_parameter:[min, max]}
```
fixed_parameters (dict) –

fixed parameters given to the model. Example:
```
fit_spectrum(fixed_parameters={"vib_distribution":"treanor"})
```

Other Parameters:

plot (bool) – if True, plot spectra as they are computed; and plot the convergence of the residual. Default False
solver_options (dict) – parameters forwarded to the solver. More info in minimize Example:
```
{"maxiter": (int)  max number of iteration default ``300``,
 }
```
kwargs (dict) – forwarded to fit_spectrum()

Returns:

s_best (Spectrum) – best spectrum
res (OptimizeResults) – output of minimize

Examples

See a one-temperature fit example and a non-LTE fit example

Multi-temperature Fit

1 temperature fit

More advanced tools for interactive fitting of multi-dimensional, multi-slabs spectra can be found in fitroom.

generate_perf_profile()[source]¶

Generate a visual/interactive performance profile diagram for the last calculated spectrum, with tuna.

Requires a profiler key with in Spectrum.conditions, and tuna installed.

Note

print_perf_profile() is an ascii-version which does not require tuna.

Examples

sf = SpectrumFactory(...)
sf.eq_spectrum(...)
sf.generate_perf_profile()

See typical output in https://github.com/radis/radis/pull/325

Note

You can also profile with tuna directly:

python -m cProfile -o program.prof your_radis_script.py
tuna your_radis_script.py

See also

print_perf_profile()

non_eq_spectrum(Tvib, Trot, Ttrans=None, mole_fraction=None, path_length=None, diluent=None, pressure=None, vib_distribution='boltzmann', rot_distribution='boltzmann', overpopulation=None, name=None) → Spectrum[source]¶

Calculate emission spectrum in non-equilibrium case. Calculates absorption with broadened linestrength and emission with broadened Einstein coefficient.

Parameters:

Tvib (float) – vibrational temperature [K] can be a tuple of float for the special case of more-than-diatomic molecules (e.g: CO2)
Trot (float) – rotational temperature [K]
Ttrans (float) – translational temperature [K]. If None, translational temperature is taken as rotational temperature (valid at 1 atm for times above ~ 2ns which is the RT characteristic time)
mole_fraction (float) – database species mole fraction. If None, Factory mole fraction is used.
diluent (str or dictionary) – can be a string of a single diluent or a dictionary containing diluent name as key and its mole_fraction as value
path_length (float or Quantity) – slab size (cm). If None, the default Factory path_length is used.
pressure (float or Quantity) – pressure (bar). If None, the default Factory pressure is used.

Other Parameters:

vib_distribution ('boltzmann', 'treanor') – vibrational distribution
rot_distribution ('boltzmann') – rotational distribution
overpopulation (dict, or None) –

add overpopulation factors for given levels:
```
{level:overpopulation_factor}
```
name (str) – output Spectrum name (useful in batch)

Returns:

s –

Returns a Spectrum object

Use the get() method to get something among ['radiance', 'radiance_noslit', 'absorbance', etc...]

Or directly the plot() method to plot it. See [1]_ to get an overview of all Spectrum methods

Return type: