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# University of Ljubljana.
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import numpy as np
from .base import Scale, Normalize, Model
[docs]class Conrady_1(Model):
def __init__(self, params, pp: Scale or Normalize = None, **kwargs):
'''
Conrady 1 model of the refractive index.
:math:`n^{2} = A_{1} + A_{2}/\\lambda + A_{3}/\\lambda^{3.5}`
Parameters
----------
params: np.ndarray
Default model parameters.
pp: xopto.materials.ri.util.model.base.Scale or xopto.materials.ri.util.model.base.Normalize
Wavelength preprocessor instance.
kwargs: dict
Parameters passed to the baseclass.
'''
formatstr = 'n = {:.8e} + {:.8e}/wn +{:.8e}/wn**3.5'
super().__init__(formatstr, params, pp, **kwargs)
[docs] def guess(self, wavelengths: np.ndarray, n: np.ndarray) -> list:
'''
Returns an initial guess of the model parameters for optimization/fit.
Parameters
----------
wavelengths: np.ndarray
The wavelengths of light at which the values of refractive index
are defined.
n: np.ndarray
The values of refractive index at the given wavelengths of light.
Returns
-------
params0: np.ndarray
Initial guess for the values of the model parameters
'''
return [n[0], 0.0, 0.0]
[docs] def ri(self, params: np.ndarray, wavelengths: np.ndarray):
'''
Compute the refractive index for the given model parameters
and wavelengths of light.
Parameters
----------
params: np.ndarray
Model parameters.
wavelengths: np.ndarray
Wavelengths of light (m).
Returns
-------
n: np.ndarray
Refractive index estimated for the given model parameters and
at the given wavelengths of light.
'''
wn = self.pp(wavelengths)
return params[0] + params[1]/wn + params[2]/wn**3.5
[docs]class ConradyEx_1(Model):
def __init__(self, params, pp: Scale or Normalize = None, **kwargs):
'''
Extended Conrady 1 model of the refractive index.
:math:`n^{2} = A_{1} + A_{2}/\\lambda + A_{3}/\\lambda^{A_{4}}`
Parameters
----------
params: np.ndarray
Default model parameters.
pp: xopto.materials.ri.util.model.base.Scale or xopto.materials.ri.util.model.base.Normalize
Wavelength preprocessor instance.
kwargs: dict
Parameters passed to the baseclass.
'''
formatstr = 'n = {:.8e} + {:.8e}/wn +{:.8e}/wn**{:.8e}'
super().__init__(formatstr, params, pp, **kwargs)
[docs] def guess(self, wavelengths: np.ndarray, n: np.ndarray) -> list:
'''
Returns an initial guess of the model parameters for optimization/fit.
Parameters
----------
wavelengths: np.ndarray
The wavelengths of light at which the values of refractive index
are defined.
n: np.ndarray
The values of refractive index at the given wavelengths of light.
Returns
-------
params0: np.ndarray
Initial guess for the values of the model parameters
'''
return [n[0], 0.0, 0.0, 3.5]
[docs] def ri(self, params: np.ndarray, wavelengths: np.ndarray):
'''
Compute the refractive index for the given model parameters
and wavelengths of light.
Parameters
----------
params: np.ndarray
Model parameters.
wavelengths: np.ndarray
Wavelengths of light (m).
Returns
-------
n: np.ndarray
Refractive index estimated for the given model parameters and
at the given wavelengths of light.
'''
wn = self.pp(wavelengths)
return params[0] + params[1]/wn + params[2]/wn**params[3]
[docs]class Conrady_2(Model):
def __init__(self, params, pp: Scale or Normalize = None, **kwargs):
'''
Conrady 2 model of the refractive index.
:math:`n^{2} = A_{1} + A_{2}/\\lambda^{2} + A_{3}/\\lambda^{3.5}`
Parameters
----------
params: np.ndarray
Default model parameters.
pp: xopto.materials.ri.util.model.base.Scale or xopto.materials.ri.util.model.base.Normalize
Wavelength preprocessor instance.
kwargs: dict
Parameters passed to the baseclass.
'''
formatstr = 'n = {:.8e} + {:.8e}/wn**2 +{:.8e}/wn**3.5'
super().__init__(formatstr, params, pp, **kwargs)
[docs] def guess(self, wavelengths: np.ndarray, n: np.ndarray) -> list:
'''
Returns an initial guess of the model parameters for optimization/fit.
Parameters
----------
wavelengths: np.ndarray
The wavelengths of light at which the values of refractive index
are defined.
n: np.ndarray
The values of refractive index at the given wavelengths of light.
Returns
-------
params0: np.ndarray
Initial guess for the values of the model parameters
'''
return [n[0], 0.0, 0.0]
[docs] def ri(self, params: np.ndarray, wavelengths: np.ndarray):
'''
Compute the refractive index for the given model parameters
and wavelengths of light.
Parameters
----------
params: np.ndarray
Model parameters.
wavelengths: np.ndarray
Wavelengths of light (m).
Returns
-------
n: np.ndarray
Refractive index estimated for the given model parameters and
at the given wavelengths of light.
'''
wn = self.pp(wavelengths)
return params[0] + params[1]/wn**2 + params[2]/wn**3.5
[docs]class ConradyEx_2(Model):
def __init__(self, params, pp: Scale or Normalize = None, **kwargs):
'''
Extended Conrady 2 model of the refractive index.
:math:`n^{2} = A_{1} + A_{2}/\\lambda^{2} + A_{3}/\\lambda^{A_{4}}`
Parameters
----------
params: np.ndarray
Default model parameters.
pp: xopto.materials.ri.util.model.base.Scale or xopto.materials.ri.util.model.base.Normalize
Wavelength preprocessor instance.
kwargs: dict
Parameters passed to the baseclass.
'''
formatstr = 'n = {:.8e} + {:.8e}/wn**2 +{:.8e}/wn**{:.8e}'
super().__init__(formatstr, params, pp, **kwargs)
[docs] def guess(self, wavelengths: np.ndarray, n: np.ndarray) -> list:
'''
Returns an initial guess of the model parameters for optimization/fit.
Parameters
----------
wavelengths: np.ndarray
The wavelengths of light at which the values of refractive index
are defined.
n: np.ndarray
The values of refractive index at the given wavelengths of light.
Returns
-------
params0: np.ndarray
Initial guess for the values of the model parameters
'''
return [n[0], 0.0, 0.0, 3.5]
[docs] def ri(self, params: np.ndarray, wavelengths: np.ndarray):
'''
Compute the refractive index for the given model parameters
and wavelengths of light.
Parameters
----------
params: np.ndarray
Model parameters.
wavelengths: np.ndarray
Wavelengths of light (m).
Returns
-------
n: np.ndarray
Refractive index estimated for the given model parameters and
at the given wavelengths of light.
'''
wn = self.pp(wavelengths)
return params[0] + params[1]/wn**2 + params[2]/wn**params[3]