radis.tools package¶

Submodules¶

Module contents¶

Tools : database of spectra, line survey, interface with Cantera.

class SpecDatabase(path='.', filt='.spec', add_info=None, add_date='%Y%m%d', verbose=True, binary=True, nJobs=-2, batch_size='auto', lazy_loading=True, update_register_only=False)[source]¶

Bases: SpecList

A Spectrum Database class to manage them all.

It basically manages a list of Spectrum JSON files, adding a Pandas dataframe structure on top to serve as an efficient index to visualize the spectra input conditions, and slice through the Dataframe with easy queries

Similar to SpecList, but associated and synchronized with a folder

Parameters:

path (str) – a folder to initialize the database
filt (str) – only consider files ending with filt. Default .spec
binary (boolean) – if True, open Spectrum files as binary files. If False and it fails, try as binary file anyway. Default False.
lazy_loading (bool``) – If True, load only the data from the summary csv file and the spectra will be loaded when accessed by the get functions. If False, load all the spectrum files. If True and the summary .csv file does not exist, load all spectra

Other Parameters:

*input for :class:`~joblib.parallel.Parallel` loading of database*
nJobs (int) – Number of processors to use to load a database (useful for big databases). BE CAREFULL, no check is done on processor use prior to the execution ! Default -2: use all but 1 processors. Use 1 for single processor.
batch_size (int or 'auto') – The number of atomic tasks to dispatch at once to each worker. When individual evaluations are very fast, dispatching calls to workers can be slower than sequential computation because of the overhead. Batching fast computations together can mitigate this. Default: 'auto'
More information in :class:`joblib.parallel.Parallel`

Examples

>>> db = SpecDatabase(r"path/to/database")     # create or loads database

>>> db.update()  # in case something changed
>>> db.see(['Tvib', 'Trot'])   # nice print in console

>>> s = db.get('Tvib==3000')[0]  # get a Spectrum back
>>> db.add(s)  # update database (and raise error because duplicate!)

Note that SpectrumFactory can be configured to automatically look-up and update a database when spectra are calculated.

The function to auto retrieve a Spectrum from database on calculation time is a method of DatabankLoader class

You can see more examples on the Spectrum Database section of the website.

Spectrum Database

add(spectrum: Spectrum, store_name=None, if_exists_then='increment', **kwargs)[source]¶

Add Spectrum to database, whether it’s a Spectrum object or a file that stores one. Check it’s not in database already.

Parameters:

spectrum (Spectrum object, or path to a .spec file (str)) – if a Spectrum object: stores it in the database (using the store() method), then adds the file to the database folder. if a path to a file (str): first copy the file to the database folder, then loads the copied file to the database.

Other Parameters:

store_name (str, or None) – name of the file where the spectrum will be stored. If None, name is generated automatically from the Spectrum conditions (see add_info= and if_exists_then=)
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 (!). If 'ignore' the Spectrum is not added to the database and no file is created. If 'error' (or anything else) an error is raised. Default 'increment'.
**kwargs (**dict) – extra parameters used in the case where spectrum is a file and a .spec object has to be created (useless if spectrum is a file already). kwargs are forwarded to Spectrum.store() method. See the store() method for more information.

Note

Other store() parameters can be given as kwargs arguments. See below :
compress (0, 1, 2) – if True or 1, save the spectrum in a compressed form

if 2, removes all quantities that can be regenerated with update(), e.g, transmittance if abscoeff and path length are given, radiance if emisscoeff and abscoeff are given in non-optically thin case, etc. If not given, use the value of SpecDatabase.binary The performances are usually better if compress = 2. See https://github.com/radis/radis/issues/84.
add_info (list) – append these parameters and their values if they are in conditions example:
```
nameafter = ['Tvib', 'Trot']
```
discard (list of str) – parameters to exclude. To save some memory for instance Default ['lines', 'populations']: retrieved Spectrum will loose the line_survey() and plot_populations() methods (but it saves a ton of memory!).

Examples

from radis.tools import SpecDatabase
db = SpecDatabase(r"path/to/database")     # create or loads database
db.add(s, discard=['populations'])

You can see more examples on the Spectrum Database section of the website.

Spectrum Database

compress_to(new_folder, compress=True, if_exists_then='error')[source]¶

Saves the Database in a new folder with all Spectrum objects under compressed (binary) format. Read/write is much faster. After the operation, a new database should be initialized in the new_folder to access the new Spectrum.

Parameters:

new_folder (str) – folder where to store the compressed SpecDatabase. If doesn’t exist, it is created.
compress (boolean, or 2) – if True, saves under binary format. Faster and takes less space. If 2, additionally remove all redundant quantities.
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 (!). If 'ignore' the Spectrum is not added to the database and no file is created. If 'error' (or anything else) an error is raised. Default 'error'.

See also

find_duplicates()

find_duplicates(columns=None)[source]¶

Find spectra with same conditions. The first duplicated spectrum will be 'False', the following will be 'True' (see .duplicated()).

Parameters:: columns (list, or None) – columns to find duplicates on. If None, use all conditions.

Examples

db.find_duplicates(columns={'x_e', 'x_N_II'})

Out[34]:
file
20180710_101.spec    True
20180710_103.spec    True
dtype: bool

You can see more examples in the Spectrum Database section

fit_spectrum(s_exp, residual=None, normalize=False, normalize_how='max', conditions='', **kwconditions)[source]¶

Returns the Spectrum in the database that has the lowest residual with s_exp.

Parameters:

s_exp (Spectrum) – Spectrum to fit (typically: experimental spectrum)

Other Parameters:

residual (func, or None) – which residual function to use. If None, use get_residual() with option ignore_nan=True and options normalize and normalize_how as defined by the user.

get_residual should have the form:
```
lambda s_exp, s, normalize: func(s_exp, s, normalize=normalize)
```
where the output is a float. Default None
conditions, **kwconditions (str, **dict) – restrain fitting to only Spectrum that match the given conditions in the database. See get() for more information.
normalize (bool, or Tuple) – see get_residual()
normalize_how (‘max’, ‘area’) – see get_residual()

Returns:

s_best – closest Spectrum to s_exp

Return type:

Spectrum

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.

get_FWHM(w, I, return_index=False)[source]¶

Calculate full width half maximum (FWHM) by comparing amplitudes

Parameters:

w, I (arrays)
return_index (boolean) – if True, returns indexes for half width boundaries. Default False

Returns:

FWHM (float) – full width at half maximum
[xmin, xmax] (int)

get_effective_FWHM(w, I)[source]¶

Calculate full-width-at-half-maximum (FWHM) of a triangular slit of same area and height 1

Parameters:: w, I (arrays)
Returns:: fwhm – effective FWHM
Return type:: float

get_eq_mole_fraction(initial_mixture, T_K, p_Pa)[source]¶

Calculates chemical equilibrium mole fraction at temperature T, using the CANTERA equilibrate() function.

The calculation uses the default GRI3.0 mechanism, which was designed to model natural gas combustion, including NO formation and reburn chemistry. See GRI 3.0.

When using, cite the [CANTERA] package.

Parameters:

initial_mixture (str) –

Gas composition. Example:
```
'N2:0.79, O2:0.21, CO2:363e-6'
```
Or:
```
'CO2:1'
```
T_K (float (K)) – temperature (Kelvin) to calculate equilibrium
P_Pa (float (Pa)) – temperature (Pascal) to calculate equilibrium

Examples

Calculate equilibrium mixture of CO2 at 2000 K, 1 atm:

get_eq_mole_fraction('CO2:1', 2000, 101325)

>>> {'C': 1.7833953335281855e-19,
    'CO': 0.01495998583472384,
    'CO2': 0.9775311634424326,
    'O': 5.7715610124613225e-05,
    'O2': 0.007451135112719029}

References

[CANTERA]

load_spec(file, binary=True) → Spectrum[source]¶

Loads a .spec file into a Spectrum object. Adds file in the Spectrum file attribute.

Parameters:

file (str) – .spec file to load
binary (boolean) – set to True if the file is encoded as binary. Default True. Will autodetect if it fails, but that may take longer.

Returns:

Spectrum

Return type:

a Spectrum object

Examples

Load an experimental spectrum

Remove a baseline

Example #1: Temperature fit

Example #3: non-equilibrium spectrum (Tvib, Trot, x_CO)

Legacy #1: Temperature fit of CO2 spectrum

Legacy vs recommended fitting examples

See also

SpecDatabase, store()

plot_slit(w, I=None, wunit='', plot_unit='same', Iunit=None, warnings=True, ls='-', title=None, waveunit=None)[source]¶

Plot slit, calculate and display FWHM, and calculate effective FWHM. FWHM is calculated from the limits of the range above the half width, while FWHM is the equivalent width of a triangular slit with the same area

Parameters:

w, I (arrays or (str, None)) – if str, open file directly
waveunit ('nm', 'cm-1' or '') – unit of input w
plot_unit ('nm', 'cm-1' or 'same') – change plot unit (and FWHM units)
Iunit (str, or None) – give Iunit
warnings (boolean) – if True, test if slit is correctly centered and output a warning if it is not. Default True

Returns:

fix, ax – figure and ax

Return type:

matplotlib objects

Examples

Slit Function

plot_spec(file, what='radiance', title=True, **kwargs)[source]¶

Plot a .spec file. Uses the plot() method internally.

Parameters:: file (str, or Spectrum object) – .spec file to load, or Spectrum object directly
Other Parameters:: kwargs (dict) – arguments forwarded to plot()
Returns:: fig – where the Spectrum has been plotted
Return type:: matplotlib figure

See also

plot()

save(s: Spectrum, path, discard=[], compress=True, add_info=None, add_date=None, if_exists_then='increment', verbose=True, warnings=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:

s (Spectrum) – to save
path (str) – filename to save. No extension needed. If filename already exists then a digit is added. If filename is a directory then a new file is created within this directory.
discard (list of str) – parameters to discard. To save some memory.
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 False
add_info (list, or None/False) – append these parameters and their values if they are in conditions. e.g:
```
add_info = ['Tvib', 'Trot']
```
add_date (str, or None/False) – adds date in strftime format to the beginning of the filename. e.g:
```
add_date = '%Y%m%d'
```
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 (!). If 'ignore' the Spectrum is not added to the database and no file is created. If 'error' (or anything else) an error is raised. Default 'increment'.

Returns:

fout – filename used (may be different from given path as new info or incremental identifiers are added)

Return type:

str

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