rm_lite.tools_1d.rmsynth
========================

.. py:module:: rm_lite.tools_1d.rmsynth

.. autoapi-nested-parse::

   RM-synthesis on 1D data



Attributes
----------

.. autoapisummary::

   rm_lite.tools_1d.rmsynth.rmsf_arrs_schema
   rm_lite.tools_1d.rmsynth.rmsf_arrs_schema_df
   rm_lite.tools_1d.rmsynth.rmsyth_arrs_schema
   rm_lite.tools_1d.rmsynth.rmsyth_arrs_schema_df
   rm_lite.tools_1d.rmsynth.stokes_i_arrs_schema
   rm_lite.tools_1d.rmsynth.stokes_i_arrs_schema_df


Classes
-------

.. autoapisummary::

   rm_lite.tools_1d.rmsynth.RMSynth1DResults


Functions
---------

.. autoapisummary::

   rm_lite.tools_1d.rmsynth._run_rmsynth
   rm_lite.tools_1d.rmsynth.run_rmsynth


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

.. py:class:: RMSynth1DResults

   Bases: :py:obj:`NamedTuple`


   Resulting arrays from RM-synthesis


   .. py:attribute:: fdf_arrs
      :type:  polars.DataFrame

      RMSynth arrays


   .. py:attribute:: fdf_parameters
      :type:  polars.DataFrame

      FDF parameters


   .. py:attribute:: rmsf_arrs
      :type:  polars.DataFrame

      RMSF arrays


   .. py:attribute:: stokes_i_arrs
      :type:  polars.DataFrame

      Stokes I arrays


.. py:function:: _run_rmsynth(stokes_data: rm_lite.utils.synthesis.StokesData, fdf_options: rm_lite.utils.synthesis.FDFOptions, fit_function: Literal['log', 'linear'] = 'log', fit_order: int = 2, ignore_stokes_i: bool = False) -> RMSynth1DResults

   Run RM-synthesis on 1D data with packed data

   :param stokes_data: Frequency-dependent polarisation data
   :type stokes_data: StokesData
   :param fdf_options: RM-synthesis options
   :type fdf_options: FDFOptions
   :param fit_function: Type of function to fit. Defaults to "log".
   :type fit_function: "log", "linear", optional
   :param fit_order: Polynomial fit order. Defaults to 2. Negative values will iterate until the fit is good.
   :type fit_order: int, optional

   :returns:     fdf_parameters (pl.DataFrame): FDF parameters
                 fdf_arrs (pl.DataFrame): RMSynth arrays
                 rmsf_arrs (pl.DataFrame): RMSF arrays
   :rtype: RMSynth1DResults


.. py:function:: run_rmsynth(freq_arr_hz: numpy.typing.NDArray[numpy.float64], complex_pol_arr: numpy.typing.NDArray[numpy.complex128], complex_pol_error: numpy.typing.NDArray[numpy.complex128], stokes_i_arr: numpy.typing.NDArray[numpy.float64] | None = None, stokes_i_error_arr: numpy.typing.NDArray[numpy.float64] | None = None, stokes_i_model_arr: numpy.typing.NDArray[numpy.float64] | None = None, stokes_i_model_error: numpy.typing.NDArray[numpy.float64] | None = None, phi_max_radm2: float | None = None, d_phi_radm2: float | None = None, n_samples: float | None = 10.0, weight_type: Literal['variance', 'uniform'] = 'variance', do_fit_rmsf: bool = False, do_fit_rmsf_real: bool = False, fit_function: Literal['log', 'linear'] = 'log', fit_order: int = 2, ignore_stokes_i: bool = False) -> RMSynth1DResults

   Run RM-synthesis on 1D data

   :param freq_arr_hz: Frequencies in Hz
   :type freq_arr_hz: NDArray[np.float64]
   :param complex_pol_arr: Complex polarisation values (Q + iU)
   :type complex_pol_arr: NDArray[np.complex128]
   :param complex_pol_error: Complex polarisation errors (dQ + idU)
   :type complex_pol_error: NDArray[np.float64]
   :param stokes_i_arr: Total itensity values. Defaults to None.
   :type stokes_i_arr: NDArray[np.float64] | None, optional
   :param stokes_i_error_arr: Total intensity errors. Defaults to None.
   :type stokes_i_error_arr: NDArray[np.float64] | None, optional
   :param stokes_i_model_arr: Total intensity model array. Defaults to None.
   :type stokes_i_model_arr: NDArray[np.float64] | None, optional
   :param stokes_i_model_error: Total intensity model error. Defaults to None.
   :type stokes_i_model_error: NDArray[np.float64] | None, optional
   :param phi_max_radm2: Maximum Faraday depth. Defaults to None.
   :type phi_max_radm2: float | None, optional
   :param d_phi_radm2: Spacing in Faraday depth. Defaults to None.
   :type d_phi_radm2: float | None, optional
   :param n_samples: Number of samples across the RMSF. Defaults to 10.0.
   :type n_samples: float | None, optional
   :param weight_type: Type of weighting. Defaults to "variance".
   :type weight_type: "variance", "uniform", optional
   :param do_fit_rmsf: Fit the RMSF main lobe. Defaults to False.
   :type do_fit_rmsf: bool, optional
   :param do_fit_rmsf_real: The the real part of the RMSF. Defaults to False.
   :type do_fit_rmsf_real: bool, optional
   :param fit_function: _description_. Defaults to "log".
   :type fit_function: "log" | "linear", optional
   :param fit_order: Polynomial fit order. Defaults to 2. Negative values will iterate until the fit is good.
   :type fit_order: int, optional

   :returns:     fdf_parameters (pl.DataFrame): FDF parameters
                 fdf_arrs (pl.DataFrame): RMSynth arrays
                 rmsf_arrs (pl.DataFrame): RMSF arrays
   :rtype: RMSynth1DResults


.. py:data:: rmsf_arrs_schema

.. py:data:: rmsf_arrs_schema_df

.. py:data:: rmsyth_arrs_schema

.. py:data:: rmsyth_arrs_schema_df

.. py:data:: stokes_i_arrs_schema

.. py:data:: stokes_i_arrs_schema_df