rm_lite.tools_1d.rmsynth¶
RM-synthesis on 1D data
Attributes¶
Classes¶
Resulting arrays from RM-synthesis |
Functions¶
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Run RM-synthesis on 1D data with packed data |
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Run RM-synthesis on 1D data |
Module Contents¶
- class rm_lite.tools_1d.rmsynth.RMSynth1DResults¶
Bases:
NamedTupleResulting arrays from RM-synthesis
- fdf_arrs: polars.DataFrame¶
RMSynth arrays
- fdf_parameters: polars.DataFrame¶
FDF parameters
- rmsf_arrs: polars.DataFrame¶
RMSF arrays
- stokes_i_arrs: polars.DataFrame¶
Stokes I arrays
- rm_lite.tools_1d.rmsynth._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
- Parameters:
stokes_data (StokesData) – Frequency-dependent polarisation data
fdf_options (FDFOptions) – RM-synthesis options
fit_function ("log", "linear", optional) – Type of function to fit. Defaults to “log”.
fit_order (int, optional) – Polynomial fit order. Defaults to 2. Negative values will iterate until the fit is good.
- Returns:
fdf_parameters (pl.DataFrame): FDF parameters fdf_arrs (pl.DataFrame): RMSynth arrays rmsf_arrs (pl.DataFrame): RMSF arrays
- Return type:
- rm_lite.tools_1d.rmsynth.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
- Parameters:
freq_arr_hz (NDArray[np.float64]) – Frequencies in Hz
complex_pol_arr (NDArray[np.complex128]) – Complex polarisation values (Q + iU)
complex_pol_error (NDArray[np.float64]) – Complex polarisation errors (dQ + idU)
stokes_i_arr (NDArray[np.float64] | None, optional) – Total itensity values. Defaults to None.
stokes_i_error_arr (NDArray[np.float64] | None, optional) – Total intensity errors. Defaults to None.
stokes_i_model_arr (NDArray[np.float64] | None, optional) – Total intensity model array. Defaults to None.
stokes_i_model_error (NDArray[np.float64] | None, optional) – Total intensity model error. Defaults to None.
phi_max_radm2 (float | None, optional) – Maximum Faraday depth. Defaults to None.
d_phi_radm2 (float | None, optional) – Spacing in Faraday depth. Defaults to None.
n_samples (float | None, optional) – Number of samples across the RMSF. Defaults to 10.0.
weight_type ("variance", "uniform", optional) – Type of weighting. Defaults to “variance”.
do_fit_rmsf (bool, optional) – Fit the RMSF main lobe. Defaults to False.
do_fit_rmsf_real (bool, optional) – The the real part of the RMSF. Defaults to False.
fit_function ("log" | "linear", optional) – _description_. Defaults to “log”.
fit_order (int, optional) – Polynomial fit order. Defaults to 2. Negative values will iterate until the fit is good.
- Returns:
fdf_parameters (pl.DataFrame): FDF parameters fdf_arrs (pl.DataFrame): RMSynth arrays rmsf_arrs (pl.DataFrame): RMSF arrays
- Return type:
- 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¶