oimParam

Model parameter and parameter interpolators.

Classes:

`oimParam`([name, value, mini, maxi, ...])	Class of model parameters
`oimParamLinker`(param[, operator, fact])
`oimParamNorm`(params[, norm])
`oimInterp`(name, **kwargs)	Macro to directly create oimParamInterpolator-derived class in a oimComponent object.
`oimParamInterpolator`(param, **kwargs)
`oimParamInterpolatorKeyframes`(param, **kwargs)
`oimParamInterpolatorWl`(param, **kwargs)
`oimParamInterpolatorTime`(param, **kwargs)
`oimParamCosineTime`(param, **kwargs)
`oimParamGaussian`(param, **kwargs)
`oimParamGaussianWl`(param, **kwargs)
`oimParamGaussianTime`(param, **kwargs)
`oimParamMultipleGaussian`(param, **kwargs)
`oimParamMultipleGaussianWl`(param, **kwargs)
`oimParamMultipleGaussianTime`(param, **kwargs)
`oimParamPolynomial`(param, **kwargs)
`oimParamPolynomialWl`(param, **kwargs)
`oimParamPolynomialTime`(param, **kwargs)
`oimParamPowerLaw`(param, **kwargs)	Power-law interpolation, i.e. A(x/x0)*p.
`oimParamPowerLawTime`(param, **kwargs)
`oimParamPowerLawWl`(param, **kwargs)
`oimParamLinearRangeWl`(param, **kwargs)

class oimodeler.oimParam.oimParam(name=None, value=None, mini=-inf, maxi=inf, description='', unit=Unit(dimensionless), free=True, error=0)

Class of model parameters

Parameters:

name (string, optional) – Name of the Parameter. The default is None.
value (float, optional) – Value of the parameter. The default is None.
mini (float, optional) – Mininum value allowed for the parameter. The default is -1*np.inf.
maxi (float, optional) – maximum value allowed for the parameter. The default is np.inf.
description (string, optional) – Description of the parameter. The default is “”.
unit (1 or astropy.unit, optional) – Unit of the parameter. The default is 1.

Methods:

set(**kwargs)

set(**kwargs)

class oimodeler.oimParam.oimParamLinker(param, operator='add', fact=0)

Attributes:

unit

Methods:

`_setOperator`(operator)
`_add`(val)
`_mult`(val)

property unit

_setOperator(operator)

_add(val)

_mult(val)

class oimodeler.oimParam.oimParamNorm(params, norm=1)

Attributes:

unit

property unit

class oimodeler.oimParam.oimInterp(name, **kwargs)

Macro to directly create oimParamInterpolator-derived class in a oimComponent object.

Parameters:

name (str) – Keyname for the interpolators registered in the _interpolators dictionary.
**kwargs (dict) – Parameters from the create oimParamInterpolator-derived class.

Variables:

kwargs (dict) – Parameters from the create oimParamInterpolator-derived class.
type (oimParamInterpolator) – A param interpolator contained in the _interpolators dictionary. For the local definition in the oimParam module, strings can be used. To redefine the dictionary elements from outside, use the class variables, otherwise the local definition will be used.

class oimodeler.oimParam.oimParamInterpolator(param, **kwargs)

Methods:

`_init`(param, **kwargs)
`_interpFunction`(wl, t)

Attributes:

params

_init(param, **kwargs)

_interpFunction(wl, t)

property params

class oimodeler.oimParam.oimParamInterpolatorKeyframes(param, **kwargs)

Methods:

`_init`(param[, dependence, keyframes, ...])
`_interpFunction`(wl, t)
`_getParams`()

_init(param, dependence='wl', keyframes=[], keyvalues=[], kind='linear', fixedRef=True, extrapolate=False, **kwargs)

_interpFunction(wl, t)

_getParams()

class oimodeler.oimParam.oimParamInterpolatorWl(param, **kwargs)

Methods:

_init(param[, wl, values])

_init(param, wl=[], values=[], **kwargs)

class oimodeler.oimParam.oimParamInterpolatorTime(param, **kwargs)

Methods:

_init(param[, mjd, values])

_init(param, mjd=[], values=[], **kwargs)

class oimodeler.oimParam.oimParamCosineTime(param, **kwargs)

Methods:

`_init`(param[, T0, P, values, x0])
`_interpFunction`(wl, t)
`_getParams`()

_init(param, T0=0, P=1, values=[0, 1], x0=None, **kwargs)

_interpFunction(wl, t)

_getParams()

class oimodeler.oimParam.oimParamGaussian(param, **kwargs)

Methods:

`_init`(param[, dependence, val0, value, x0, fwhm])
`_interpFunction`(wl, t)
`_getParams`()

_init(param, dependence='wl', val0=0, value=0, x0=0, fwhm=0, **kwargs)

_interpFunction(wl, t)

_getParams()

class oimodeler.oimParam.oimParamGaussianWl(param, **kwargs)

Methods:

_init(param[, val0, value, x0, fwhm])

_init(param, val0=0, value=0, x0=0, fwhm=0, **kwargs)

class oimodeler.oimParam.oimParamGaussianTime(param, **kwargs)

Methods:

_init(param[, val0, value, x0, fwhm])

_init(param, val0=0, value=0, x0=0, fwhm=0, **kwargs)

class oimodeler.oimParam.oimParamMultipleGaussian(param, **kwargs)

Methods:

`_init`(param[, dependence, val0, values, x0, ...])
`_interpFunction`(wl, t)
`_getParams`()

_init(param, dependence='wl', val0=0, values=[], x0=[], fwhm=[], **kwargs)

_interpFunction(wl, t)

_getParams()

class oimodeler.oimParam.oimParamMultipleGaussianWl(param, **kwargs)

Methods:

_init(param[, val0, values, x0, fwhm])

_init(param, val0=0, values=[], x0=[], fwhm=[], **kwargs)

class oimodeler.oimParam.oimParamMultipleGaussianTime(param, **kwargs)

Methods:

_init(param[, val0, values, x0, fwhm])

_init(param, val0=0, values=[], x0=[], fwhm=[], **kwargs)

class oimodeler.oimParam.oimParamPolynomial(param, **kwargs)

Methods:

`_init`(param[, dependence, order, coeffs, x0])
`_interpFunction`(wl, t)
`_getParams`()

_init(param, dependence='wl', order=2, coeffs=None, x0=None, **kwargs)

_interpFunction(wl, t)

_getParams()

class oimodeler.oimParam.oimParamPolynomialWl(param, **kwargs)

Methods:

_init(param[, order, coeffs, x0])

_init(param, order=2, coeffs=None, x0=None, **kwargs)

class oimodeler.oimParam.oimParamPolynomialTime(param, **kwargs)

Methods:

_init(param[, order, coeffs, x0])

_init(param, order=2, coeffs=None, x0=None)

class oimodeler.oimParam.oimParamPowerLaw(param, **kwargs)

Power-law interpolation, i.e. A*(x/x0)**p.

Methods:

`_init`(param, dependence, x0, A, p, **kwargs)
`_interpFunction`(wl, t)
`_getParams`()

_init(param, dependence, x0, A, p, **kwargs)

_interpFunction(wl, t)

_getParams()

class oimodeler.oimParam.oimParamPowerLawTime(param, **kwargs)

Methods:

_init(param, x0, A, p)

_init(param, x0, A, p)

class oimodeler.oimParam.oimParamPowerLawWl(param, **kwargs)

Methods:

_init(param, x0, A, p)

_init(param, x0, A, p)

class oimodeler.oimParam.oimParamLinearRangeWl(param, **kwargs)

Methods:

`_init`(param[, wlmin, wlmax, values, kind])
`_interpFunction`(wl, t)
`_getParams`()

_init(param, wlmin=2e-06, wlmax=3e-06, values=[], kind='linear', **kwargs)

_interpFunction(wl, t)

_getParams()