Planck Model

class rapoc.Planck(input_data)[source]

Planck model class. This class implements the Planck Opacity model:

\[k = \frac{\int_{\nu_1}^{\nu_2} k_{\nu} B_\nu(T) d\nu} {\int_{\nu_1}^{\nu_2} B_\nu(T) d\nu}\]

where \(\nu_1\) and \(\nu_2\) are the investigated frequency band edges, \(k_{\nu}\) is the input data opacity at a given frequency, and \(B_\nu(T)\) is the black body radiation energy distribution computed at a certain temperature:

\[B_\nu(T) = \frac{2h \nu^3}{c^2} \frac{1}{e^{\frac{h\nu}{k_B T}-1}}\]
Variables:

  • input_data (str or dict) – data file name or data dictionary

  • model_name (str) – model name

  • band (tuple) – investigated band. Is initialised only after the use of map()

  • selected_grid (astropy.units.Quantity) – investigated grid. Is initialised only after the use of map()

  • mol (str) – molecule name

  • mol_mass (astropy.units.Quantity) – molecular mass

  • pressure_grid (astropy.units.Quantity) – data pressure grid in si units

  • temperature_grid (astropy.units.Quantity) – data temperature grid in si units

  • wavenumber_grid (astropy.units.Quantity) – data wavenumber grid

  • opacities (astropy.units.Quantity) – data opacities grid in si units

  • frequency_grid (astropy.units.Quantity) – data frequency grid

  • wavelength_grid (astropy.units.Quantity) – data wavelength grid

Parameters:

input_data (str or dict) – data file name or input_data dictionary. If the input is a str, the correspondent loader is used (ExoMolFileLoader) if the file format is supported. If is dict, then DictLoader is used.

Raises:

IOError – if data format is not supported:

Examples

First we prepare a data dictionary:

>>> import numpy as np
>>> data_dict = {'mol': 'H2O',
>>>              'pressure': np.array([1.00000000e+00, 1.00000000e+01, 1.00000000e+02, 1.00000000e+03,
>>>                                   1.00000000e+04, 1.00000000e+05, 1.00000000e+06, 1.00000000e+07]),
>>>              'temperature': np.array([500, 1000, 1500, 2000, 3000]),
>>>              'wavenumber': np.array([100000, 1000])}
>>> ktab = np.ones((data_dict['pressure'].size,data_dict['temperature'].size,data_dict['wavenumber'].size,))
>>> data_dict['opacities'] = ktab

Let’s build the Planck method using an Exomol file as input

>>> from rapoc import Planck
>>> dict_data = 'example.TauREx.h5'
>>> model = Planck(input_data=data_dict)

Now the model is ready to be used

opacity_model(opacities, nu, T_input)[source]

This function computes the Planck Opacity model:

\[k = \frac{\int_{\nu_1}^{\nu_2} k_{\nu} B_\nu(T) d\nu} {\int_{\nu_1}^{\nu_2} B_\nu(T) d\nu}\]

where \(\nu_1\) and \(\nu_2\) are the investigated frequency band edges, \(k_{\nu}\) is the input data opacity at a given frequency, and \(B_\nu(T)\) is the black body radiation energy distribution computed at a certain temperature:

\[B_\nu(T) = \frac{2h \nu^3}{c^2} \frac{1}{e^{\frac{h\nu}{k_B T}-1}}\]
Parameters:

  • opacities (np.array) – opacity array. Has the same dimension of the frequency grid nu

  • nu (np.array) – frequency grid

  • T_input (float) – temperature

Returns:

mean opacity computed from the model

Return type:

float