radis.misc package¶

Submodules¶

Module contents¶

Misc. and support functions

exception DatabankNotFound[source]¶

Bases: FileNotFoundError

Used when a line database is not found in radis.rc.

class DatabaseProgressPrinter(database_name: str, molecule: str, verbose: int = 1, version: str = '')[source]¶

Bases: object

Unified progress output for database fetch operations.

Provides consistent formatting across all database operations (HITRAN, HITEMP, ExoMol, GEISA) with configurable verbose levels.

Parameters:

database_name (str) – Name of the database (e.g., “HITEMP”, “ExoMol”, “HITRAN”, “GEISA”)
molecule (str) – Molecule being fetched (e.g., “CO2”, “H2O”)
verbose (int or bool) – Verbosity level: - 0 or False: Silent (no output) - 1 or True: Normal output (default) - 2+: Detailed/debug output

Example

printer = DatabaseProgressPrinter("HITEMP", "CO2", verbose=1)
printer.header("Fetching 2024 database")
printer.section("Downloading")
printer.info("3 files needed, 2 cached")
with printer.progress_bar(3, "Downloading chunks") as pbar:
    for i in range(3):
        # download work
        pbar.update(1)
printer.success("Complete: Added HITEMP-CO2-2024 to radis.json")

HEADER_WIDTH = 80[source]¶

complete(database_entry: str = '')[source]¶

Print completion message.

Parameters:: database_entry (str) – Name of database entry added to radis.json

download_progress(total_bytes: int, desc: str = 'Downloading') → tqdm[source]¶

Return a progress bar configured for download operations.

Parameters:

total_bytes (int) – Total download size in bytes
desc (str) – Description text

Returns:

Progress bar configured for byte downloads

Return type:

tqdm

download_summary(files_needed: int, files_total: int, files_cached: int = 0)[source]¶

Print download summary.

Parameters:

files_needed (int) – Number of files that need to be downloaded
files_total (int) – Total number of files
files_cached (int) – Number of files already cached

header(action: str = '', details: str = '')[source]¶

Print operation header with visual separator.

Parameters:

action (str) – Action being performed (e.g., “Fetching”, “Downloading”)
details (str, optional) – Additional details for the header

info(message: str, level: int = 1, indent: int = 0)[source]¶

Print info message if verbose >= level.

Parameters:

message (str) – Message to display
level (int) – Minimum verbose level required to show message
indent (int) – Indentation level (0=none, 1=bullet, 2=sub-bullet)

lines_progress(total_lines: int | None, desc: str = 'Parsing lines') → tqdm[source]¶

Return a progress bar configured for line parsing operations.

Parameters:

total_lines (int or None) – Total number of lines expected (None if unknown)
desc (str) – Description text

Returns:

Progress bar configured for line parsing

Return type:

tqdm

parsing_progress(total_files: int, desc: str = 'Processing files') → tqdm[source]¶

Return a progress bar configured for file parsing operations.

Parameters:

total_files (int) – Total number of files to process
desc (str) – Description text

Returns:

Progress bar configured for file processing

Return type:

tqdm

parsing_summary(lines_loaded: int, time_elapsed: float | None = None)[source]¶

Print parsing summary.

Parameters:

lines_loaded (int) – Number of lines loaded
time_elapsed (float, optional) – Time taken in seconds

progress_bar(total: int, desc: str = '', unit: str = 'file', unit_scale: bool = False, unit_divisor: int = 1024, leave: bool = True, position: int = 0, disable: bool | None = None) → tqdm[source]¶

Return a configured tqdm progress bar.

Parameters:

total (int) – Total number of iterations
desc (str) – Description text for the progress bar
unit (str) – Unit name (e.g., “file”, “line”, “B” for bytes)
unit_scale (bool) – If True, scale units automatically (useful for bytes)
unit_divisor (int) – Divisor for unit scaling (default 1024 for bytes)
leave (bool) – If True, keep progress bar after completion
position (int) – Position for nested progress bars
disable (bool or None) – If True, disable progress bar. If None, use verbose level.

Returns:

Configured progress bar instance

Return type:

tqdm

section(title: str, level: int = 1)[source]¶

Start a new section (Download, Parse, etc.).

Parameters:

title (str) – Section title (e.g., “Download”, “Parsing”, “Processing”)
level (int) – Minimum verbose level to show this section

success(message: str)[source]¶

Print success message.

Parameters:: message (str) – Success message to display

warning(message: str)[source]¶

Print warning message.

Parameters:: message (str) – Warning message to display

class NotInstalled(name, info='')[source]¶

Bases: object

A class to deal with optional packages. Will raise an error only if the package is used (but not if imported only)

Examples

some function = NotInstalled("you should install C drivers")
a = some_function   # no error
a()             # will raise the NotInstalled error and display the message

class ProgressBar(N, active=True, t0=None)[source]¶

Bases: object

Writes completion status and expended time.

Set it up by creating the object, then calling update() and done().

Parameters:

N (int) – (expected) number of iterations
active (bool) – if False, do not show anything (tip : feed it a verbose argument)

Other Parameters:

t0 (float) – initializes starting time at t0 (useful for successive loops)

Example

add a progress bar in a loop:

pb = ProgressBar(N)
for i, ... in enumerate(...):
    (...)
    pb.update(i)
pb.done()

See test in progress_bar.py

done()[source]¶: Close the Progress bar.

set_active(active=True)[source]¶

Option to activate/deactivate the ProgressBar.

Used not to make it appear on small processes (based on a condition) without changing most of the code

update(i, modulo=1, message='')[source]¶

Update the completion status i/N and time spent.

Parameters:

i (int) – current iteration
modulo (int) – if higher than 1, skip some iterations.
message (str) – add a custom message. Tip: evaluate your own variables with f’{my_variable}’ strings

Example

array_allclose(a, b, rtol=1e-05, atol=1e-08, equal_nan=True)[source]¶

Returns whether a and b are all close (element wise). If not the same size, returns False (instead of crashing like the numpy version). Cf numpy.allclose docs for more information.

Parameters:

a, b (arrays)
rtol (float)
atol (float)
equal_nan (bool) – whether to consider NaN’s as equal. Contrary to the numpy version this one is set to True by default

autoturn(data, key=-1)[source]¶

Turns array data. key value:

0 don’t transpose
1 : transpose
-1 : auto : make sure the vectors are along the longest dimension

bining(I, ymin=None, ymax=None, axis=1)[source]¶

Averages a I multi-dimensional array (typically an image) along the y axis bining(I) corresponds to I.mean(axis=1) NaN are not taken into account.

Parameters:

I (numpy array) – intensity
ymin (int [0-I.shape[1]]) – If None, 0 is used. Default None.
ymax (int [0-I.shape[1]]) – If None, I.shape[1] is used. Default None.
axis (int) – Default 1

calc_diff(t1, v1, t2, v2)[source]¶

Subtract two vectors that may have slightly offset abscissa interpolating the correct values.

Parameters:

t1, v1 (array_like) – first vector and its abscissa
t2, v2 (array_like) – second vector and its abscissa

Returns:

tdiff, vdiff – subtracted vector and its abscissa

Return type:

array_like

centered_diff(w)[source]¶

Return w[i+1]-w[i-1]/2, same size as w.

Similar to numpy.diff(), but does not change the array size.

compare_dict(d1, d2, verbose='if_different', compare_as_paths=[], compare_as_close=[], return_string=False, df1_str='Left', df2_str='Right', ignore_keys=[])[source]¶

Returns ratio of equal keys [0-1] If verbose, also print all keys and values on 2 columns :Parameters: d1, d2 (dict) – two dictionaries to compare

Other Parameters:

compare_as_paths (list of keys) – compare the values corresponding to given keys as path (irrespective of forward / backward slashes, or case )
compare_as_close (list of keys) – compare with np.isclose(a,b) rather than a==b
verbose (boolean, or 'if_different') – 'if_different' means results will be shown only if there is a difference.
return_string (boolean) – if True, returns message instead of just printing it (useful in error messages) Default False
ignore_keys (list) – do not compare these keys

Returns:

out (float [0-1]) – ratio of matching keys
if return_string
out, string (float [0-1], str) – ratio of matching keys and comparison message

compare_lists(l1, l2, verbose='if_different', return_string=False, l1_str='Left', l2_str='Right', print_index=False)[source]¶

Compare 2 lists of elements that may not be of the same length, irrespective of order. Returns the ratio of elements [0-1] present in both lists. If verbose, prints the differences

Parameters:

l1, l2 (list-like)
verbose (boolean, or ‘if_different’) – ‘if_different’ means results will be shown only if there is a difference. function is called twice

Other Parameters:

verbose (boolean, or 'if_different') – 'if_different' means results will be shown only if there is a difference.
return_string (boolean) – if True, returns message instead of just printing it (useful in error messages) Default False

Returns:

out – ratio of matching keys

Return type:

float [0-1]

compare_paths(p1, p2)[source]¶: Compare 2 paths p1 and p2.

count_nans(a)[source]¶: NaN are good but only in India.

curve_add(w1, I1, w2, I2, is_sorted=False, kind='linear')[source]¶

Add curve (w2, I2) from (w1, I1) Linearly interpolates if the two ranges dont match. Fills out of bound parameters with nan.

Similar to OriginPro’s “Simple Curve Math Subtract”

Note

for higher accuracy, choose (w2, I2) has the curve with the highest resolution

Parameters:

w1, I1 (array) – range and values for first curve
w2, I2 (array) – range and values for 2nd curve
is_sorted (boolean) – (optional) if True, doesnt sort input arrays
kind (str) – interpolation kind. Default ‘linear’. See scipy.interpolate.interp1d

Returns:

w1, Iadd – sum I1 + I2 interpolated on the first range w1

Return type:

array

curve_distance(w1, I1, w2, I2, discard_out_of_bounds=True)[source]¶

Get a regularized euclidian distance from curve (w1, I1) to curve (w2, I2)

\[D(w_1)[i] = \sqrt{ \sum_j (\hat{I_1}[i] - \hat{I_2}[j] )^2 + (\hat{w_1}[i] - \hat{w_2}[j])^2}\]

Where values are normalized as:

\[\hat{A} = \frac{A}{max(A) - min(A)}\]

This regularized Euclidian distance minimizes the effect of a small shift in between the two curves in case of stiff curves (like a spectrum bandhead can be)

No interpolation needed neither.

Distances for out of bounds values is set to nan

Warning

This is a distance on both the waverange and the intensity axis. It may be used to compensate for a small offset in your experimental spectrum (due to wavelength calibration, for instance) but can lead to wrong fits easily. Plus, it is very cost-intensive!

Parameters:

w1, I1 (array) – range and values for first curve
w2, I2 (array) – range and values for 2nd curve
discard_out_of_bounds (boolean) – if True, distance for out of bound values is set to nan. Else, it will be the distance from the last point.

Returns:

w1, Idist – minimal distance from I1 to I2, for each point in (w1, I1)

Return type:

array

curve_divide(w1, I1, w2, I2, is_sorted=False, kind='linear', interpolation=1)[source]¶

Divides curve (w1, I1) by (w2, I2) Linearly interpolates if the two ranges dont match. Fills out of bound parameters with nan.

Similar to OriginPro’s “Simple Curve Math Subtract”

Note

for higher accuracy, choose (w2, I2) has the curve with the highest resolution

Parameters:

w1, I1 (array) – range and values for first curve
w2, I2 (array) – range and values for 2nd curve

Other Parameters:

is_sorted (boolean) – (optional) if True, assumes that both input arrays are sorted already. Default False.
kind (str) – interpolation kind. Default ‘linear’. See scipy.interpolate.interp1d
interpolation (int, optional) – If 1, interpolate on w1, I1. Else, on w2, I2. Default 1

Returns:

w1, Idiv – Division I1 / I2 interpolated on the first or second range according to reverseInterpolation

Return type:

array

curve_multiply(w1, I1, w2, I2, is_sorted=False, kind='linear')[source]¶

Multiply curve (w2, I2) with (w1, I1) Linearly interpolates if the two ranges dont match. Fills out of bound parameters with nan.

Similar to OriginPro’s “Simple Curve Math Subtract”

Note

for higher accuracy, choose (w2, I2) has the curve with the highest resolution

Parameters:

w1, I1 (array) – range and values for first curve
w2, I2 (array) – range and values for 2nd curve
is_sorted (boolean) – (optional) if True, doesnt sort input arrays
kind (str) – interpolation kind. Default ‘linear’. See scipy.interpolate.interp1d

Returns:

w1, Iproduct – product I1 * I2 interpolated on the first range w1

Return type:

array

curve_substract(w1, I1, w2, I2, is_sorted=False, kind='linear')[source]¶

Subtracts curve (w2, I2) from (w1, I1) Linearly interpolates if the two ranges dont match. Fills out of bound parameters with nan.

Similar to OriginPro’s “Simple Curve Math Subtract”

Note

for higher accuracy, choose (w2, I2) has the curve with the highest resolution

Parameters:

w1, I1 (array) – range and values for first curve
w2, I2 (array) – range and values for 2nd curve
is_sorted (boolean) – (optional) if True, doesnt sort input arrays
kind (str) – interpolation kind. Default ‘linear’. See scipy.interpolate.interp1d

Returns:

w1, Idiff – difference I1 - I2 interpolated on the first range w1

Return type:

array

evenly_distributed(w, atolerance=1e-05)[source]¶

Make sure array w is evenly distributed.

Parameters:

w (numpy array) – array to test
atolerance (float) – absolute tolerance

Returns:

out – True or False if w is evenly distributed.

Return type:

bool

See also

evenly_distributed_fast()

exec_file(afile, globalz=None, localz=None)[source]¶

export(var={'__builtins__': {'ArithmeticError': <class 'ArithmeticError'>, 'AssertionError': <class 'AssertionError'>, 'AttributeError': <class 'AttributeError'>, 'BaseException': <class 'BaseException'>, 'BaseExceptionGroup': <class 'BaseExceptionGroup'>, 'BlockingIOError': <class 'BlockingIOError'>, 'BrokenPipeError': <class 'BrokenPipeError'>, 'BufferError': <class 'BufferError'>, 'BytesWarning': <class 'BytesWarning'>, 'ChildProcessError': <class 'ChildProcessError'>, 'ConnectionAbortedError': <class 'ConnectionAbortedError'>, 'ConnectionError': <class 'ConnectionError'>, 'ConnectionRefusedError': <class 'ConnectionRefusedError'>, 'ConnectionResetError': <class 'ConnectionResetError'>, 'DeprecationWarning': <class 'DeprecationWarning'>, 'EOFError': <class 'EOFError'>, 'Ellipsis': Ellipsis, 'EncodingWarning': <class 'EncodingWarning'>, 'EnvironmentError': <class 'OSError'>, 'Exception': <class 'Exception'>, 'ExceptionGroup': <class 'ExceptionGroup'>, 'False': False, 'FileExistsError': <class 'FileExistsError'>, 'FileNotFoundError': <class 'FileNotFoundError'>, 'FloatingPointError': <class 'FloatingPointError'>, 'FutureWarning': <class 'FutureWarning'>, 'GeneratorExit': <class 'GeneratorExit'>, 'IOError': <class 'OSError'>, 'ImportError': <class 'ImportError'>, 'ImportWarning': <class 'ImportWarning'>, 'IndentationError': <class 'IndentationError'>, 'IndexError': <class 'IndexError'>, 'InterruptedError': <class 'InterruptedError'>, 'IsADirectoryError': <class 'IsADirectoryError'>, 'KeyError': <class 'KeyError'>, 'KeyboardInterrupt': <class 'KeyboardInterrupt'>, 'LookupError': <class 'LookupError'>, 'MemoryError': <class 'MemoryError'>, 'ModuleNotFoundError': <class 'ModuleNotFoundError'>, 'NameError': <class 'NameError'>, 'None': None, 'NotADirectoryError': <class 'NotADirectoryError'>, 'NotImplemented': NotImplemented, 'NotImplementedError': <class 'NotImplementedError'>, 'OSError': <class 'OSError'>, 'OverflowError': <class 'OverflowError'>, 'PendingDeprecationWarning': <class 'PendingDeprecationWarning'>, 'PermissionError': <class 'PermissionError'>, 'ProcessLookupError': <class 'ProcessLookupError'>, 'PythonFinalizationError': <class 'PythonFinalizationError'>, 'RecursionError': <class 'RecursionError'>, 'ReferenceError': <class 'ReferenceError'>, 'ResourceWarning': <class 'ResourceWarning'>, 'RuntimeError': <class 'RuntimeError'>, 'RuntimeWarning': <class 'RuntimeWarning'>, 'StopAsyncIteration': <class 'StopAsyncIteration'>, 'StopIteration': <class 'StopIteration'>, 'SyntaxError': <class 'SyntaxError'>, 'SyntaxWarning': <class 'SyntaxWarning'>, 'SystemError': <class 'SystemError'>, 'SystemExit': <class 'SystemExit'>, 'TabError': <class 'TabError'>, 'TimeoutError': <class 'TimeoutError'>, 'True': True, 'TypeError': <class 'TypeError'>, 'UnboundLocalError': <class 'UnboundLocalError'>, 'UnicodeDecodeError': <class 'UnicodeDecodeError'>, 'UnicodeEncodeError': <class 'UnicodeEncodeError'>, 'UnicodeError': <class 'UnicodeError'>, 'UnicodeTranslateError': <class 'UnicodeTranslateError'>, 'UnicodeWarning': <class 'UnicodeWarning'>, 'UserWarning': <class 'UserWarning'>, 'ValueError': <class 'ValueError'>, 'Warning': <class 'Warning'>, 'ZeroDivisionError': <class 'ZeroDivisionError'>, '_IncompleteInputError': <class '_IncompleteInputError'>, '__annotations__': {}, '__build_class__': <built-in function __build_class__>, '__debug__': True, '__doc__': "Built-in functions, types, exceptions, and other objects.\n\nThis module provides direct access to all 'built-in'\nidentifiers of Python; for example, builtins.len is\nthe full name for the built-in function len().\n\nThis module is not normally accessed explicitly by most\napplications, but can be useful in modules that provide\nobjects with the same name as a built-in value, but in\nwhich the built-in of that name is also needed.", '__import__': <built-in function __import__>, '__loader__': <class '_frozen_importlib.BuiltinImporter'>, '__name__': 'builtins', '__package__': '', '__spec__': ModuleSpec(name = 'builtins', loader=<class '_frozen_importlib.BuiltinImporter'>, origin='built-in'), 'abs': <built-in function abs>, 'aiter': <built-in function aiter>, 'all': <built-in function all>, 'anext': <built-in function anext>, 'any': <built-in function any>, 'ascii': <built-in function ascii>, 'bin': <built-in function bin>, 'bool': <class 'bool'>, 'breakpoint': <built-in function breakpoint>, 'bytearray': <class 'bytearray'>, 'bytes': <class 'bytes'>, 'callable': <built-in function callable>, 'chr': <built-in function chr>, 'classmethod': <class 'classmethod'>, 'compile': <built-in function compile>, 'complex': <class 'complex'>, 'copyright': Copyright (c) 2001 Python Software Foundation. All Rights Reserved. Copyright (c) 2000 BeOpen.com. All Rights Reserved. Copyright (c) 1995-2001 Corporation for National Research Initiatives. All Rights Reserved. Copyright (c) 1991-1995 Stichting Mathematisch Centrum, Amsterdam. All Rights Reserved., 'credits': Thanks to CWI, CNRI, BeOpen, Zope Corporation, the Python Software Foundation, and a cast of thousands for supporting Python development. See www.python.org for more information., 'delattr': <built-in function delattr>, 'dict': <class 'dict'>, 'dir': <built-in function dir>, 'divmod': <built-in function divmod>, 'enumerate': <class 'enumerate'>, 'eval': <built-in function eval>, 'exec': <built-in function exec>, 'exit': Use exit() or Ctrl-D (i.e. EOF) to exit, 'filter': <class 'filter'>, 'float': <class 'float'>, 'format': <built-in function format>, 'frozenset': <class 'frozenset'>, 'getattr': <built-in function getattr>, 'globals': <built-in function globals>, 'hasattr': <built-in function hasattr>, 'hash': <built-in function hash>, 'help': Type help() for interactive help, or help(object) for help about object., 'hex': <built-in function hex>, 'id': <built-in function id>, 'input': <built-in function input>, 'int': <class 'int'>, 'isinstance': <built-in function isinstance>, 'issubclass': <built-in function issubclass>, 'iter': <built-in function iter>, 'len': <built-in function len>, 'license': Type license() to see the full license text, 'list': <class 'list'>, 'locals': <built-in function locals>, 'map': <class 'map'>, 'max': <built-in function max>, 'memoryview': <class 'memoryview'>, 'min': <built-in function min>, 'next': <built-in function next>, 'object': <class 'object'>, 'oct': <built-in function oct>, 'open': <built-in function open>, 'ord': <built-in function ord>, 'pow': <built-in function pow>, 'print': <built-in function print>, 'property': <class 'property'>, 'quit': Use quit() or Ctrl-D (i.e. EOF) to exit, 'range': <class 'range'>, 'repr': <built-in function repr>, 'reversed': <class 'reversed'>, 'round': <built-in function round>, 'set': <class 'set'>, 'setattr': <built-in function setattr>, 'slice': <class 'slice'>, 'sorted': <built-in function sorted>, 'staticmethod': <class 'staticmethod'>, 'str': <class 'str'>, 'sum': <built-in function sum>, 'super': <class 'super'>, 'tuple': <class 'tuple'>, 'type': <class 'type'>, 'vars': <built-in function vars>, 'zip': <class 'zip'>}, '__cached__': '/home/docs/checkouts/readthedocs.org/user_builds/radis/checkouts/latest/radis/misc/__pycache__/debug.cpython-314.pyc', '__doc__': 'Created on Sun Jan 3 17:52:04 2016.\n\n@author: Erwan\n\nDebug functions\n', '__file__': '/home/docs/checkouts/readthedocs.org/user_builds/radis/checkouts/latest/radis/misc/debug.py', '__loader__': <_frozen_importlib_external.SourceFileLoader object>, '__name__': 'radis.misc.debug', '__package__': 'radis.misc', '__spec__': ModuleSpec(name = 'radis.misc.debug', loader=<_frozen_importlib_external.SourceFileLoader object>, origin='/home/docs/checkouts/readthedocs.org/user_builds/radis/checkouts/latest/radis/misc/debug.py'), 'export': <function export>, 'printdbg': <function printdbg>})[source]¶

Export local variables. Useful for debugging.

Debugging inside a function may be tedious because you can’t access the local variables. One of the option is to use the ipython magic:

%debug

Or the pdb equivalent:

import pdb
pdb.pm()

Another option is to insert this export() call in the troubled function, before the exception occurs.

Examples

debug_export(locals())

Note: you can also use ‘globals().update(locals())’ directly in your function to debug

Note

seems not to work for functions nested in functions
01/05 : doesn’t seem to work at all.. @Erwan

find_first(arr, threshold)[source]¶: Return the index of the first element of the array arr whose value is more than the threshold.

find_nearest(array, searched, return_bool=False)[source]¶

Return the closest elements in array for each element in ‘searched’ array. In case of multiple elements in array having equal difference with searched element, one with least index is returned. Also returns a boolean array with indices of elements occurring in output list set to true.

Examples

from numpy import array
find_nearest(array([1,2,3,4]), array([2.1,2]), True)

>>> (array([2, 2]), array([False, True, False, False]))

find_nearest(np.array([1,2,3,4]), np.array([2.6,2]), True)

>>> (array([3, 2]), array([False,  True,  True, False]))

find_nearest(np.array([1, 3]), np.array([2]))

>>> array([1])

find_nearest(np.array([3, 1]), np.array([2]))

>>> array([3])

getDatabankEntries(dbname, get_extra_keys=[], configpath='/home/docs/radis.json')[source]¶

Read ~/radis.json config file and returns a dictionary of entries.

Parameters:

dbname (str) – database name in ~/radis.json config file
get_extra_keys (list) – read additional parameters on top of the usual Databank format keys :

Notes

Databank format:

"MY-HITEMP-CO2": {              # your databank name: use this in calc_spectrum()
                                # or SpectrumFactory.load_databank()
"info": "HITEMP 2010 databank"  # whatever you want
"path": [                       # no "", multipath allowed
    "D:\Databases\HITEMP-CO2\hitemp_07",
    "D:\Databases\HITEMP-CO2\hitemp_08",
    "D:\Databases\HITEMP-CO2\hitemp_09"
],
"format": "hitemp"              # 'hitran' (HITRAN / HITEMP), 'cdsd-hitemp', 'cdsd-4000'
                                # Databank text file format. More info in
                                # SpectrumFactory.load_databank function.

# Optional:

"parfunc":                      # path or 'USE_HAPI'
                                # path to tabulated partition functions. If
                                # `USE_HAPI`, then HAPI (HITRAN Python
                                interface) [1]_ is used to retrieve them (valid
                                if your databank is HITRAN data). HAPI
                                is embedded into RADIS. Check the version.

"levels_iso1":                  # path to energy levels (needed for non-eq)
                                # calculations.
"levels_iso2":                  # etc
"levels_iso4":                  # etc

"levelsfmt":                    # 'cdsd'
}                               # how to read the previous file.

References

getDatabankList(configpath='/home/docs/radis.json')[source]¶: Get all databanks available in :ref:`~/radis.json

getProjectRoot()[source]¶: Return the full path of the project root.

get_progress_printer(database_name: str, molecule: str, verbose: int = 1, version: str = '') → DatabaseProgressPrinter[source]¶

Create a DatabaseProgressPrinter instance.

Parameters:

database_name (str) – Name of the database
molecule (str) – Molecule being fetched
verbose (int) – Verbosity level
version (str) – Database version

Returns:

Configured printer instance

Return type:

DatabaseProgressPrinter

is_float(a)[source]¶: Returns True if a has float-like type: float, np.float64, np.int64, etc.)

is_sorted(a)[source]¶

Returns whether a is sorted in ascending order.

From B.M. answer on StackOverflow: https://stackoverflow.com/a/47004533/5622825

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