ratansunpy.visualization package

Submodules

ratansunpy.visualization.colormaps module

ratansunpy.visualization.colormaps.cmap_from_file(file_name: str, cmap_name: str) → LinearSegmentedColormap[source]

Create a colormap from a CSV file containing RGB values.

Parameters:

  • file_name (str) – Name of the CSV file (without extension) containing RGB data.

  • cmap_name (str) – The name to assign to the generated colormap.

Returns:

A LinearSegmentedColormap object based on the RGB data.

Return type:

matplotlib.colors.LinearSegmentedColormap

ratansunpy.visualization.colormaps.std_gamma_2()[source]

ratansunpy.visualization.visualization module

ratansunpy.visualization.visualization.plot_ratan_fits_data(pr_data: str | HDUList, is_calibrated: bool = False, plot_V: bool | None = True, plot_I: bool | None = True) → None[source]

Plot RATAN-600 FITS data for Stokes I and/or V parameters.

Parameters:

  • pr_data (Union[str, fits.hdu.hdulist.HDUList]) – Path to FITS file, URL, or FITS HDUList with the RATAN-600 data.

  • is_calibrated (bool) – Indicates whether the data is already calibrated. Defaults to False.

  • plot_V (Optional[bool]) – Whether to plot Stokes V data. Defaults to True.

  • plot_I (Optional[bool]) – Whether to plot Stokes I data. Defaults to True.

Returns:

None

Return type:

None

Raises:

ValueError – If both plot_I and plot_V are set to False.

Module contents