oimUtils

Various utilities for optical interferometry

Functions:

`attach_methods`(functions)	Class decorator that attaches function(s) to a class as methods.
`_pickle`(self, f, **kwargs)	Save the pickled representation of the object into an already open file or opens a file from a string or pathlib.Path.
`_unpickle`(cls, f, **kwargs)	Read the pickled representation from an open file or reads a string or pathlib.Path into a file to return the reconstituted object.
`load_toml`(toml_file)	Loads a toml file into a dictionary.
`getDataTypeIsAnalysisComplex`(dataType)	Get the data type and if it is complex.
`getDataArrname`(dataType)	Returns the dataArrname for a given datatype.
`getDataType`(dataArrname)	Returns the datatype for a given dataArrname.
`getDataTypeError`(dataArrname)	Returns the error datatype for a given dataArrname.
`compare_angles`(phi, psi)	Subtracts two angles and makes sure the are between -π and +π.
`blackbody`(temperature[, nu])	Planck's law in CGS.
`compute_intensity`(wavelengths, temperature)	Calculates the blackbody_profile via Planck's law and the emissivity_factor for a given wavelength, temperature- and dust surface density profile.
`compute_photometric_slope`(data, temperature)	Computes the photometric slope of the data from the effective temperature of the star.
`pad_image`(image[, padfact])	Pads an image with additional zeros for Fourier transform.
`get_next_power_of_two`(number)	Returns the next power of two for an integer or float input.
`angular_to_linear`(radius, distance)	Converts angular radius, using the object's distance, to linear radius.
`linear_to_angular`(radius, distance)	Converts linear radius, using the object's distance, to angular radius.
`getBaselineName`(oifits[, hduname, length, ...])	Gets the baseline names (i.e., telescopes names separated by minus sign) in an extension of a oifits file.
`getConfigName`(oifits[, hduname, extver, squeeze])	Gets the configuration names in an extension of a oifits file.
`getBaselineLengthAndPA`(oifits[, arr, ...])	Return a tuple (B, PA) of the baseline lengths and orientation (position angles) from a fits extension within an opened oifits file.
`get2DSpaFreq`(oifits[, arr, unit, extver, ...])	Get the spatial two dimensional frequencies.
`getSpaFreq`(oifits[, arr, unit, extver, squeeze])	Get the spatial dimensional frequencies.
`getWlFromOifits`(oifits[, arr, extver, ...])	Get the wavelength
`hdulistDeepCopy`(hdulist)	Deep copy of a fits HDUList.
`cutWavelengthRange`(oifits[, wlRange, addCut])	Cut the wavelength range of an oifits file.
`getWlFromFitsImageCube`(header[, outputUnit])	Returns the wavelength law from a chromatic cube image in the fits format.
`_createOiTab`(extname, keywords_def, ...)	Create a OIFITS table from a dictionary of data.
`createOiTarget`(**kwargs)	Create a OI_TARGET table from a dictionary of data.
`createOiArray`(**kwargs)	Create a OI_ARRAY table from a dictionary of data.
`createOiWavelength`(**kwargs)	Create a OI_WAVELENGTH table from a dictionary of data.
`createOiVis`(**kwargs)	Create a OI_VIS table from a dictionary of data.
`createOiVis2`(**kwargs)	Create a OI_VIS2 table from a dictionary of data.
`createOiT3`(**kwargs)	Create a OI_T3 table from a dictionary of data.
`createOiFlux`(**kwargs)	Create a OI_FLUX table from a dictionary of data.
`createOiTargetFromSimbad`(names)	Create a OI_TARGET table from a dictionary of data.
`shiftWavelength`(oifits, shift[, verbose])	Shift the wavelength of an oifits file.
`spectralSmoothing`(oifits, kernel_size[, ...])	Smooth the spectral data of an oifits file.
`_intpBinning`(array, binMasks, binEdgeValues)	Interpolates the edges of the binning window and bins all values in the mask.
`_interpolateBinHDU`(hdu, binGrid, binMasks, ...)	Bin an HDU via interpolation.
`intpBinWavelength`(oifits, binGrid, **kwargs)	Bin the wavelength of an oifits file.
`rebin_image`(image[, binning_factor, rdim])	Bins a 2D-image down according.
`_rebin`(array, binsize[, median, circular])	Rebin an array.
`_rebinHDU`(hdu, binsize[, exception])	Rebin an HDU.
`binWavelength`(oifits[, binsize, normalizeError])	Bin the wavelength of an oifits file.
`oifitsFlagWithExpression`(data, arr, extver0, ...)	Flag the data with an expression.
`oifitsKeepBaselines`(data, arr, baselines_to_keep)
`oifitsRemoveBaselines`(data, arr, ...[, ...])
`oifitsKeepTelescopes`(data, arr, ...[, ...])
`oifitsRemoveTelescopes`(data, arr, ...[, ...])
`computeDifferentialError`(oifits[, ranges, ...])	Compute the differential error.
`setMinimumError`(oifits, dataTypes, values[, ...])	Set the minimum error of a given data type to a given value.
`_listFeatures`(baseClass, featureToTextFunction)
`listComponents`([details, save2csv, ...])
`listDataFilters`([details, save2csv])
`listFitters`([details, save2csv])
`listParamInterpolators`([details, save2csv])
`windowed_linspace`(start, end, window)	Creates bins centred around points with half-window spacing on each side.
`colorPrint`(text, color)
`oimWarning`(myclass, warningName, text[, color])
`oimAckWarning`(myclass, text)

Classes:

_terminalColor()

oimodeler.oimUtils.attach_methods(functions: Callable | _Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str] | Dict[str, Callable]) → Callable: Class decorator that attaches function(s) to a class as methods.

oimodeler.oimUtils._pickle(self, f: str | Path | BufferedWriter, **kwargs) → None: Save the pickled representation of the object into an already open file or opens a file from a string or pathlib.Path.

oimodeler.oimUtils._unpickle(cls, f: Path | TextIOWrapper, **kwargs) → object: Read the pickled representation from an open file or reads a string or pathlib.Path into a file to return the reconstituted object.

oimodeler.oimUtils.load_toml(toml_file: Path) → Dict[str, Any]: Loads a toml file into a dictionary.

oimodeler.oimUtils.getDataTypeIsAnalysisComplex(dataType: str) → str: Get the data type and if it is complex.

oimodeler.oimUtils.getDataArrname(dataType: str) → str: Returns the dataArrname for a given datatype.

oimodeler.oimUtils.getDataType(dataArrname: str) → List[str]: Returns the datatype for a given dataArrname.

oimodeler.oimUtils.getDataTypeError(dataArrname: str) → List[str]: Returns the error datatype for a given dataArrname.

oimodeler.oimUtils.compare_angles(phi: float, psi: float) → float: Subtracts two angles and makes sure the are between -π and +π.

Planck’s law in CGS.

Parameters:

temperature (float or numpy.typing.ArrayLike) – The temperature (K).
nu (float or numpy.typing.ArrayLike, optional) – The frequency (Hz).

Returns:

blackbody – The blackbody (erg / (cm² s Hz sr)).

Return type:

np.ndarray

oimodeler.oimUtils.compute_intensity(wavelengths: Unit('um'), temperature: Unit('K'), pixel_size: float | None = None) → ndarray

Calculates the blackbody_profile via Planck’s law and the emissivity_factor for a given wavelength, temperature- and dust surface density profile.

Parameters:

wavelengths (astropy.units.um) – Wavelength value(s).
temp_profile (astropy.units.K) – Temperature profile.
pixSize (float, optional) – The pixel size [rad].

Returns:

intensity – Intensity per pixel.

Return type:

numpy.ndarray

oimodeler.oimUtils.compute_photometric_slope(data: ndarray, temperature: Unit('K')) → ndarray

Computes the photometric slope of the data from the effective temperature of the star.

Parameters:

data (oimData.oimData) – The observed data.
temperature (astropy.units.K) – The effective temperature of the star.

Returns:

photometric_slope

Return type:

numpy.ndarray

oimodeler.oimUtils.pad_image(image: ndarray, padfact: int | float | None = None) → ndarray

Pads an image with additional zeros for Fourier transform.

Parameters:

image (numpy.ndarray) – The image to be padded.
Results
——-
padded_image (numpy.ndarray) – The padded image.

oimodeler.oimUtils.get_next_power_of_two(number: int | float) → int

Returns the next power of two for an integer or float input.

Parameters:: number (int or float) – An input number.
Returns:: closest_power_of_two – The, to the input, closest power of two.
Return type:: int

oimodeler.oimUtils.angular_to_linear(radius: float | ndarray, distance: float) → float | ndarray

Converts angular radius, using the object’s distance, to linear radius.

Parameters:

radius (float or numpy.ndarray) – The (angular) radius of the object (arcsec/”).
distance (float) – The object’s distance to the observer (pc).

Returns:

radius – The radius of the object around the star (au).

Return type:

float or numpy.ndarray

Notes

The formula for the angular diameter (in small angle approximation) is

\[\delta = \frac{d}{2D}\]

where d is the linear diameter from the star and D is the distance from the star to the observer and ..math::delta is the angular diameter.

oimodeler.oimUtils.linear_to_angular(radius: float | ndarray, distance: float) → float | ndarray

Converts linear radius, using the object’s distance, to angular radius.

Parameters:

radius (float or numpy.ndarray) – The (linear) radius of the object (au).
distance (float) – The star’s distance to the observer (pc).

Returns:

radius – The radius of the object around the star (arcsec/”).

Return type:

float or numpy.ndarray

Notes

The formula for the angular diameter small angle approximation is

\[\delta = \frac{d}{D}\]

where d is the distance from the star and D is the distance from the star to the observer and ..math::delta is the angular diameter.

oimodeler.oimUtils.getBaselineName(oifits: HDUList, hduname: str = 'OI_VIS2', length: bool = False, angle: bool = False, extver: int | None = None, squeeze: bool = True) → List[str]

Gets the baseline names (i.e., telescopes names separated by minus sign) in an extension of a oifits file.

By default it is reading the ‘OI_VIS’ extension.

Parameters:

oifits (astropy.io.fits.HDUList) – An oifits file structure already opened with astropy.io.fits
hduname (str, optional) – The fits extension name. The default is “OI_VIS2”.
length (bool, optional) – Add baseline length to the returned result. The default is False.
angle (bool, optional) – Add baseline position angle ((in deg)à=) to the returned result. The default is False
extver (int, optional) – The extension version. The default is None.
squeeze (bool, optional) – If True and only one extension is found, the result is squeezed.

Returns:

names – The array containing the baseline names (or triplet) and optionally the baseline length and orientation.

Return type:

list of str

oimodeler.oimUtils.getConfigName(oifits: HDUList, hduname: str = 'OI_VIS2', extver: int | None = None, squeeze: bool = True) → List[str]

Gets the configuration names in an extension of a oifits file.

Parameters:

oifits (astropy.io.fits.HDUList) – An oifits file structure already opened with astropy.io.fits
hduname (str, optional) – The fits extension name. The default is “OI_VIS2”.
extver (int, optional) – The extension version. The default is None.
squeeze (bool, optional) – If True and only one extension is found, the result is squeezed.
Results
——-
names (list of str) – The array containing the configuration names.

oimodeler.oimUtils.getBaselineLengthAndPA(oifits: HDUList, arr: str = 'OI_VIS2', extver: int | None = None, squeeze: bool = True, returnUV: bool = False, T3Max: bool = False, showFlagged: bool = True) → Tuple[ndarray]

Return a tuple (B, PA) of the baseline lengths and orientation (position angles) from a fits extension within an opened oifits file.

By default it is reading the OI_VIS extension.

Parameters:

oifits (astropy.io.fits.HDUList) – An oifits file structure already opened with astropy.io.fits.
arr (str, optional) – The fits extension name. The default is “OI_VIS2”.
returnUV (bool, optional) – If True also return the u,v coordinates in m the default is False

Returns:

B (numpy.ndarray) – The array containing the baselines length.
PA (numpy.ndarray) – The array containing the baselines orientation (in deg).
ucoord (numpy.ndarray) – The array containing the u coordinate (in m)(optional)
ucoord (numpy.ndarray) – The array containing the u coordinate (in m)(optional)

oimodeler.oimUtils.get2DSpaFreq(oifits: HDUList, arr: str = 'OI_VIS2', unit: str | None = None, extver: int | None = None, squeeze: bool = True) → Tuple[ndarray]

Get the spatial two dimensional frequencies.

Parameters:

oifits (astropy.io.fits.HDUList) – An oifits file structure already opened with astropy.io.fits.
arr (str, optional) – The fits extension name. The default is “OI_VIS2”.
unit (str, optional) – The unit of the spatial frequency. The default is None.
extver (int, optional) – The extension version. The default is None.
squeeze (bool, optional) – If True and only one extension is found, the result is squeezed.

Returns:

spaFreq

Return type:

tuple of numpy.ndarray

oimodeler.oimUtils.getSpaFreq(oifits: HDUList, arr: str = 'OI_VIS2', unit: str | None = None, extver: int | None = None, squeeze: bool = True) → Tuple[ndarray]

Get the spatial dimensional frequencies.

Parameters:

oifits (astropy.io.fits.HDUList) – An oifits file structure already opened with astropy.io.fits.
arr (str, optional) – The fits extension name. The default is “OI_VIS2”.
unit (str, optional) – The unit of the spatial frequency. The default is None.
extver (int, optional) – The extension version. The default is None.
squeeze (bool, optional) – If True and only one extension is found, the result is squeezed.

Returns:

spaFreq

Return type:

tuple of numpy.ndarray

oimodeler.oimUtils.getWlFromOifits(oifits: HDUList, arr: str = 'OI_VIS2', extver: int | None = None, returnBand: bool = False) → Tuple[ndarray]

Get the wavelength

Parameters:

oifits (astropy.io.fits.HDUList) – An oifits file structure already opened with astropy.io.fits.
arr (str, optional) – The fits extension name. The default is “OI_VIS2”.
unit (str, optional) – The unit of the spatial frequency. The default is None.
extver (int, optional) – The extension version. The default is None.
returnBand (bool, optional) – If True return the bandwith. The default is False.

Returns:

wavelength (numpy.ndarray) – The wavelength.
dwl (numpy.ndarray) – The bandwith.

oimodeler.oimUtils.hdulistDeepCopy(hdulist: HDUList) → HDUList: Deep copy of a fits HDUList.

oimodeler.oimUtils.cutWavelengthRange(oifits: HDUList, wlRange: List[float] | None = None, addCut: List[float] = []) → HDUList

Cut the wavelength range of an oifits file.

Parameters:

oifits (astropy.io.fits.HDUList) – An oifits file structure already opened with astropy.io.fits.
wlRange (list of float, optional) – The wavelength range to keep. The default is None.
addCut (list of float, optional) – Additional columns to cut. The default is [].

Returns:

data – The new oifits file with the cut wavelength range.

Return type:

fits.HDUList

oimodeler.oimUtils.getWlFromFitsImageCube(header: Header, outputUnit: str | None = None) → float

Returns the wavelength law from a chromatic cube image in the fits format.

Parameters:

header (astropy.io.fits.header) – The header of the fits cube.
outputUnit (astropy.unit, optional) – If set convert the result to the proper unit. The default is None.

Returns:

wavelength – The wavelength in the given unit of the fits cube or the user-specified if outputUnit is set.

Return type:

float

oimodeler.oimUtils._createOiTab(extname: str, keywords_def: Tuple[Any], colums_def: Tuple[Any], dataTypeFromShape: str, **kwargs) → BinTableHDU

Create a OIFITS table from a dictionary of data.

Parameters:

extname (str) – The extension name.
keywords_def (tuple of any) – The keywords definition.
colums_def (tuple of any) – The columns definition.
dataTypeFromShape (str) – The key in kwargs to get the data type from.

Returns:

hdu

Return type:

astropy.io.fits.BinTableHDU

oimodeler.oimUtils.createOiTarget(**kwargs): Create a OI_TARGET table from a dictionary of data.

oimodeler.oimUtils.createOiArray(**kwargs): Create a OI_ARRAY table from a dictionary of data.

oimodeler.oimUtils.createOiWavelength(**kwargs): Create a OI_WAVELENGTH table from a dictionary of data.

oimodeler.oimUtils.createOiVis(**kwargs): Create a OI_VIS table from a dictionary of data.

oimodeler.oimUtils.createOiVis2(**kwargs): Create a OI_VIS2 table from a dictionary of data.

oimodeler.oimUtils.createOiT3(**kwargs): Create a OI_T3 table from a dictionary of data.

oimodeler.oimUtils.createOiFlux(**kwargs): Create a OI_FLUX table from a dictionary of data.

oimodeler.oimUtils.createOiTargetFromSimbad(names: str | List[str]) → BinTableHDU

Create a OI_TARGET table from a dictionary of data.

Parameters:

names (str or list of str) – The name of the targets.
Results
——-
hdu (astropy.io.fits.BinTableHDU)

oimodeler.oimUtils.shiftWavelength(oifits: HDUList, shift: float, verbose: bool = False) → None

Shift the wavelength of an oifits file.

Parameters:

oifits (astropy.io.fits.HDUList) – An oifits file structure already opened with astropy.io.fits.
shift (float) – The wavelength shift to apply.
verbose (bool, optional) – If True print the tables index. The default is False.

oimodeler.oimUtils.spectralSmoothing(oifits: HDUList, kernel_size: float, cols2Smooth: str | List[str] = 'all', normalizeError: bool = True) → None

Smooth the spectral data of an oifits file.

Parameters:

oifits (astropy.io.fits.HDUList) – An oifits file structure already opened with astropy.io.fits.
kernel_size (float) – The kernel size.
cols2Smooth (str or list of str, optional) – The columns to smooth. The default is “all”.
normalizeError (bool, optional) – If True normalize the error. The default is True.

Interpolates the edges of the binning window and bins all values in the mask.

Parameters:

array (array_like) – The pre-bin values.
binMasks (array_like) – Mask of the old grid for the bins.
binEdgeValues (array_like) – The interpolated values at the edge of the bins.
values (array_like, optional) – If provided will treat the “array” as errors and use the values for error propagation. Default is “None”.
spectralChannels (int, optional) – The number of channels of the set bin resolution. Will be used to calculate the divisor within the error propagation. Default is 1.0.

\[divisor = bin_elements / spectralChannels\]
circular (bool, optional) – If True, treats the values periodically. Default is “False”.

Returns:

binned_values

Return type:

array_like

Bin an HDU via interpolation.

Parameters:

hdu (astropy.io.fits.BinTableHDU) – The HDU to rebin.
binGrid (array_like) – The binned grid.
binMasks (array_like) – The masks for the bin contents.
binEdgeGrid (array_like) – The window edges of the binned grid.
grid (array_like) – The pre-bin grid.
exception (list of str) – The exceptions.
spectralChannels (int, optional) – The number of channels of the set bin resolution. Will be used to calculate the divisor within the error propagation. Default is 1.0.

\[divisor = bin_elements / spectralChannels\]

Returns:

newhdu – The rebinned HDU.

Return type:

astropy.io.fits.BinTableHDU

Bin the wavelength of an oifits file.

Parameters:

oifits (astropy.io.fits.HDUList) – An oifits file structure already opened with astropy.io.fits.
binGrid (array_like) – The binned wavelength grid.
binWindow (array_like, optional) – The bin windows that correspond to the binGrid elements. If None, computes the bin windows from the distance between two elements in the binGrid. Default is None.
resetFlags (bool, optional) – If True, resets the flags after binning. Default is True.
averageError (bool, optional) – If True, forgoes error propagation and simply averages the errors for each bin. Default is False.
spectralChannels (int, optional) – The number of channels of the set bin resolution. Will be used to calculate the divisor within the error propagation. Default is 1.0.

\[divisor = bin_elements / spectralChannels\]

oimodeler.oimUtils.rebin_image(image: ndarray, binning_factor: int | None = None, rdim: bool = False) → ndarray

Bins a 2D-image down according.

The down binning is according to the binning factor in oimOptions.ft.binning. Only accounts for square images.

Parameters:

image (numpy.ndarray) – The image to be rebinned.
binning_factor (int, optional) – The binning factor. The default is 0
rdim (bool) – If toggled, returns the dimension

Returns:

rebinned_image (numpy.ndarray) – The rebinned image.
dimension (int, optional) – The new dimension of the image.

Rebin an array.

Parameters:

array (numpy.ndarray) – The array to rebin.
binsize (int, optiona) – The bin size.
median (bool, optional) – If True return the median.
circular (bool, optional) – Treats the data as periodic if toggled.

Returns:

res – The rebinned array.

Return type:

numpy.ndarray

oimodeler.oimUtils._rebinHDU(hdu: BinTableHDU, binsize: int, exception: List[str] = []) → BinTableHDU

Rebin an HDU.

Parameters:

hdu (astropy.io.fits.BinTableHDU) – The HDU to rebin.
binsize (int) – The bin size.
exception (list of str) – The exceptions.

Returns:

newhdu – The rebinned HDU.

Return type:

astropy.io.fits.BinTableHDU

oimodeler.oimUtils.binWavelength(oifits: HDUList, binsize: int | None = None, normalizeError: bool = True) → None

Bin the wavelength of an oifits file.

Parameters:

oifits (astropy.io.fits.HDUList) – An oifits file structure already opened with astropy.io.fits.
binsize (int, optional) – The bin size.
normalizeError (bool, optional) – If True normalize the error.

oimodeler.oimUtils.oifitsFlagWithExpression(data, arr, extver0, expr, keepOldFlag: bool = False)

Flag the data with an expression.

Parameters:

data (astropy.io.fits.HDUList) – An oifits file structure already opened with astropy.io.fits.
arr (str or list of str) – The fits extension name.
extver (int) – The extension version.
expr (str) – The expression to evaluate.
keepOldFlag (bool) – If True keep the old flag.

Returns:

flags – The flags.

Return type:

numpy.ndarray

oimodeler.oimUtils.oifitsKeepBaselines(data, arr, baselines_to_keep, extver=None, keepOldFlag: bool = True)

oimodeler.oimUtils.oifitsRemoveBaselines(data, arr, baselines_to_remove, extver=None, keepOldFlag: bool = True)

oimodeler.oimUtils.oifitsKeepTelescopes(data, arr, telescopes_to_keep, extver=None, keepOldFlag: bool = True)

oimodeler.oimUtils.oifitsRemoveTelescopes(data, arr, telescopes_to_remove, extver=None, keepOldFlag: bool = True)

oimodeler.oimUtils.computeDifferentialError(oifits: HDUList, ranges: List[int] = [[0, 5]], excludeRange: bool = False, rangeType: str = 'index', dataType: str = 'VISPHI', extver: List[int | None] = [None]) → None

Compute the differential error.

Parameters:

oifits (astropy.io.fits.HDUList) – An oifits file structure already opened with astropy.io.fits.
ranges (list of int, optional) – The ranges to compute the differential error. The default is [[0, 5]].
excludeRange (bool, optional) – If True exclude the range. The default is False.
rangeType (str, optional) – The range type. The default is “index”.
dataType (str, optional) – The data type. The default is “VISPHI”.
extver (list of int, optional) – The extension version. The default is [None].

oimodeler.oimUtils.setMinimumError(oifits: HDUList, dataTypes: str | List[str], values: float | List[float], extver: int | List[int] | None = None) → None

Set the minimum error of a given data type to a given value.

Parameters:

oifits (astropy.io.fits.HDUList) – An oifits file structure already opened with astropy.io.fits.
dataTypes (str or list of str) – The data types.
values (float or list of float) – The minimum error value.
extver (int or list of int, optional) – The extension version. The default is None.

oimodeler.oimUtils._listFeatures(baseClass, featureToTextFunction, details: bool = False, save2csv: bool = False, header=None)

oimodeler.oimUtils.listComponents(details: bool = False, save2csv: bool = False, componentType: str = 'all')

oimodeler.oimUtils.listDataFilters(details: bool = False, save2csv: bool = False)

oimodeler.oimUtils.listFitters(details: bool = False, save2csv: bool = False)

oimodeler.oimUtils.listParamInterpolators(details: bool = False, save2csv: bool = False)

oimodeler.oimUtils.windowed_linspace(start: float, end: float, window: float) → ndarray

Creates bins centred around points with half-window spacing on each side.

Parameters:

start (float) – Centre of the first bin.
end (float) – Centre of the last bin.
window (float) – Total width of each bin.

Returns:

bin_array

Return type:

array_like

class oimodeler.oimUtils._terminalColor

BACKGROUND_BLACK = '\x1b[40m'

BACKGROUND_RED = '\x1b[41m'

BACKGROUND_GREEN = '\x1b[42m'

BACKGROUND_YELLOW = '\x1b[43m'

BACKGROUND_BLUE = '\x1b[44m'

BACKGROUND_MAGENTA = '\x1b[45m'

BACKGROUND_CYAN = '\x1b[46m'

BACKGROUND_LIGHT_GRAY = '\third-party033[47m'

BACKGROUND_DARK_GRAY = '\x1b[100m'

BACKGROUND_BRIGHT_RED = '\x1b[101m'

BACKGROUND_BRIGHT_GREEN = '\x1b[102m'

BACKGROUND_BRIGHT_YELLOW = '\x1b[103m'

BACKGROUND_BRIGHT_BLUE = '\x1b[104m'

BACKGROUND_BRIGHT_MAGENTA = '\x1b[105m'

BACKGROUND_BRIGHT_CYAN = '\x1b[106m'

BACKGROUND_WHITE = '\x1b[107m'

BLACK = '\x1b[30m'

RED = '\x1b[31m'

GREEN = '\x1b[32m'

YELLOW = '\x1b[33m'

BLUE = '\x1b[34m'

MAGENTA = '\x1b[35m'

CYAN = '\x1b[36m'

LIGHT_GRAY = '\x1b[37m'

DARK_GRAY = '\x1b[90m'

BRIGHT_RED = '\x1b[91m'

BRIGHT_GREEN = '\x1b[92m'

BRIGHT_YELLOW = '\x1b[93m'

BRIGHT_BLUE = '\x1b[94m'

BRIGHT_MAGENTA = '\x1b[95m'

BRIGHT_CYAN = '\x1b[96m'

WHITE = '\x1b[97m'

getCode(text)

oimodeler.oimUtils.colorPrint(text, color)

oimodeler.oimUtils.oimWarning(myclass, warningName, text, color='red')

oimodeler.oimUtils.oimAckWarning(myclass, text)