pysersic.multiband
==================

.. py:module:: pysersic.multiband


Classes
-------

.. autoapisummary::

   pysersic.multiband.BaseMultiBandFitter
   pysersic.multiband.FitMultiBandPoly
   pysersic.multiband.FitMultiBandBSpline


Module Contents
---------------

.. py:class:: BaseMultiBandFitter(fitter_list: Union[List[pysersic.pysersic.FitSingle], List[pysersic.pysersic.FitMulti]], wavelengths: jax.Array, linked_params: List[str], const_params: Optional[List[str]] = [], band_names: Optional[List[str]] = None, linked_params_range: Optional[dict] = {}, wv_to_save: Optional[jax.Array] = None, rescale_unlinked_priors: Optional[bool] = False)

   Bases: :py:obj:`pysersic.pysersic.BaseFitter`


   Base class for multi-band fitter, for new classes only need to add a `sample_param_at_bands` function specifying the linking of parameters between bands.


   .. py:attribute:: fitter_list


   .. py:attribute:: n_bands


   .. py:attribute:: wavelengths


   .. py:attribute:: param_names


   .. py:attribute:: wv_av


   .. py:attribute:: wv_range


   .. py:attribute:: wv_normed


   .. py:attribute:: wv_to_save
      :value: None



   .. py:attribute:: linked_params


   .. py:attribute:: const_params
      :value: []



   .. py:attribute:: unlinked_params


   .. py:attribute:: reparam_dict


   .. py:attribute:: linked_params_mean


   .. py:attribute:: linked_params_scale


   .. py:attribute:: linked_params_range


   .. py:attribute:: const_prior_dict


   .. py:attribute:: data


   .. py:attribute:: rms


   .. py:attribute:: psf


   .. py:attribute:: mask


   .. py:attribute:: loss_func


   .. py:attribute:: renderer


   .. py:attribute:: prior


   .. py:method:: sample_param_at_bands(name: str) -> jax.Array
      :abstractmethod:


      Function used to sample linked parameters at each band

      :param name: parameter name
      :type name: str

      :returns: **params_at_bands** -- parameter values sampled at bands
      :rtype: jax.Array



   .. py:method:: build_model(return_model: bool = False) -> callable

      build numpyro model for multi-band inference

      :param return_model: wether or not to save and return observed images, by default False
      :type return_model: bool, optional

      :returns: numpyro model
      :rtype: callable



.. py:class:: FitMultiBandPoly(fitter_list: List[pysersic.pysersic.FitSingle], wavelengths: jax.Array, linked_params: List[str], const_params: Optional[List[str]] = [], band_names: Optional[List[str]] = None, linked_params_range: Optional[dict] = {}, wv_to_save: Optional[jax.Array] = None, rescale_unlinked_priors: Optional[bool] = False, poly_order: Optional[int] = 2)

   Bases: :py:obj:`BaseMultiBandFitter`


   Base class for multi-band fitter, for new classes only need to add a `sample_param_at_bands` function specifying the linking of parameters between bands.


   .. py:attribute:: poly_order
      :value: 3



   .. py:method:: restrict_func(x, hi, low)


   .. py:method:: sample_param_at_bands(name)

      Function used to sample linked parameters at each band

      :param name: parameter name
      :type name: str

      :returns: **params_at_bands** -- parameter values sampled at bands
      :rtype: jax.Array



.. py:class:: FitMultiBandBSpline(fitter_list: List[pysersic.pysersic.FitSingle], wavelengths: jax.Array, linked_params: List[str], const_params: Optional[List[str]] = [], band_names: Optional[List[str]] = None, linked_params_range: Optional[dict] = {}, wv_to_save: Optional[jax.Array] = None, rescale_unlinked_priors: Optional[bool] = False, N_knots: Optional[int] = 4, spline_k: Optional[int] = 2, pad_knots: Optional[bool] = True)

   Bases: :py:obj:`BaseMultiBandFitter`


   Base class for multi-band fitter, for new classes only need to add a `sample_param_at_bands` function specifying the linking of parameters between bands.


   .. py:attribute:: N_knots
      :value: 4



   .. py:attribute:: spline_k
      :value: 2



   .. py:attribute:: dmat_bands


   .. py:attribute:: dmat_save


   .. py:method:: sample_param_at_bands(name)

      Function used to sample linked parameters at each band

      :param name: parameter name
      :type name: str

      :returns: **params_at_bands** -- parameter values sampled at bands
      :rtype: jax.Array