spyctral

Spyctral.

Implementation of astronomical objects spectral analisys.

class spyctral.SpectralPlotter(summary)[source]

A class for generating plots from spectral data provided by a ‘SpectralSummary’ object. It offers methods for visualizing one or multiple spectra in a customizable manner.

_summary

An object containing the spectral data and additional information about the observed object.

Type:

SpectralSummary

all_spectra(ax=None, **kwargs)[source]

Plots all spectra stored in the ‘spectra’ attribute of the associated object. Each spectrum is represented on the same plot with a legend.

Parameters:

  • ax (matplotlib.axes.Axes or None) – The axis where the spectra will be plotted. If None, the current axis (‘plt.gca()’) is used.

  • **kwargs – Additional parameters to customize the plot style (e.g., color, line type, etc.).

Returns:

The axis containing the plot of all spectra.

Return type:

matplotlib.axes.Axes

__call__()[source]

Calls a plotting method based on the specified type.

all_spectra()[source]

Plots all spectra together.

single()[source]

Plots a specific spectrum.

split()[source]

Plots spectra with an offset.

subplots()[source]

Divides spectra into individual subplots.

single(spectrum_name, ax=None, **kwargs)[source]

Plots a single spectrum identified by its name. The spectrum is retrieved from the ‘spectra’ attribute and displayed on the specified axis.

Parameters:

  • spectrum_name (str) – The name of the spectrum to be plotted.

  • ax (matplotlib.axes.Axes or None) – The axis where the spectrum will be plotted. If None, the current axis (‘plt.gca()’) is used.

  • **kwargs –

    Additional parameters to customize the plot style

    (e.g., color, line type, etc.).

Returns:

The axis containing the plot of the requested spectrum.

Return type:

matplotlib.axes.Axes

split(offset=0.1, ax=None, **kwargs)[source]

Plots multiple spectra, applying an incremental vertical offset to each spectrum (except for residual spectra) to facilitate comparative visualization.

Parameters:

  • offset (float, optional) – The vertical offset applied between spectra. Default is 0.1.

  • ax (matplotlib.axes.Axes or None) – The axis where the spectra will be plotted. If None, the current axis (‘plt.gca()’) is used.

  • **kwargs – Additional parameters to customize the plot style (e.g., color, line type, etc.).

Returns:

The axis containing the plotted offset spectra.

Return type:

matplotlib.axes.Axes

Notes

This method is useful for highlighting differences between spectra by reducing overlapping curves.

subplots(ax=None, **kwargs)[source]

Creates individual subplots for each spectrum, allowing separate visualization for each one. All subplots share the same x-axis (wavelength).

Parameters:

  • ax (matplotlib.axes.Axes or None) – The set of axes where the spectra will be plotted. If None, new subplots are automatically created.

  • **kwargs –

    Additional parameters to customize the plot style

    (e.g., color, line type, etc.).

Returns:

An array of ‘Axes’ objects corresponding to the subplots.

Return type:

numpy.ndarray

Notes

This method enables the individual analysis of each spectrum in separate plots, which is useful for examining specific details without overlapping others.

class spyctral.SpectralSummary(obj_name, header, data, age, err_age, reddening, av_value, normalization_point, z_value, spectra, extra_info)[source]

Class that encapsulates all the data obtained from an input file.

obj_name

Object name.

Type:

str

header

Header information from the input file.

Type:

dict

data

Spectra information in QTable format.

Type:

dict

age

Object’s age.

Type:

float

err_age

Error associated with the age.

Type:

float

reddening

Value of reddening

Type:

float

av_value

Extinction value.

Type:

float

normalization_point

Value of the normalization point.

Type:

float

z_value

Metallicity value.

Type:

float

spectra

Set of spectra extracted from the input file.

Type:

dict

extra_info

Additional information.

Type:

dict

property feh_ratio

Calculates the metallicity ratio [Fe/H] using the instance’s Z value and the solar constant (‘Z_SUN’).

Returns:

Metallicity ratio [Fe/H].

Return type:

float

property get_all_properties: DataFrame

Creates a DataFrame containing all relevant parameters of the instance. Numerical values are formatted to display in scientific notation where necessary.

Returns:

A DataFrame with two columns: “Property” and “Value”.

Return type:

pandas.DataFrame

get_spectrum(name: str)[source]

Retrieves a specific spectrum from the ‘spectra’ attribute.

Parameters:

name (str) – The Name of the spectrum to retrieve.

Returns:

The spectrum corresponding to the specified name.

Return type:

Spectrum

property header_info_df: DataFrame

Converts the information stored in the ‘header’ attribute into a pandas DataFrame.

Returns:

A DataFrame containing the header information, where the header keys are the index and the values are stored in a column named “value”.

Return type:

pandas.DataFrame

property plot

Generates a ‘SpectralPlotter’ object for plotting the spectra stored in the instance. Uses the ‘SpectralPlotter’ class to handle plotting functionalities.

Returns:

Object that enables generating plots of the spectra.

Return type:

SpectralPlotter

spyctral.read_fisa(path_or_buffer, *, age_map=None, error_age_map=None, rv=3.1, z_map=None, object_name='object_1')[source]

Reads a FISA file and extracts the spectral data, including the header and data columns.

Parameters:

  • path_or_buffer (str) – Path and name of the FISA file to read.

  • age_map (dict or None, optional) – Mapping dictionary for age values. If None, defaults to FISA_DEFAULT_AGE_MAP. (default: None)

  • rv (float, optional) – Reddening value to use for calculations. (default: 3.1)

  • z_map (dict or None, optional) – Mapping dictionary for metallicity values. If None, defaults to FISA_DEFAULT_Z_MAP. (default: None)

Returns:

  • SpectralSummary – An object containing encapsulated data extracted from the FISA file.

  • dict – A dictionary with the following keys:

    • ’header’ (list): Lines of the file’s header.

    • ’data’ (ndarray): Spectral data in NumPy array format.

    • ’reddening’ (float): Reddening value extracted from the header.

    • ’template’ (str): Path of the template used, extracted from the

      header.

    • ’norm_point’* (float): Normalization point extracted from the

      header.

Notes

Function that processes a FISA file, extracting header information and spectral blocks. It computes age, reddening, AV value, normalization point, and metallicity values based on the provided or default mappings.

spyctral.read_starlight(path, *, xj_percent=5, age_decimals=2, rv=3.1, z_decimals=3, object_name='object_1')[source]

Processes a Starlight file, extracting the header, data tables, and key values such as age, metallicity, and reddening. Returns a spectral summary with all processed information.

Parameters:

  • path (str) – Path to the Starlight file to process.

  • xj_percent (float, optional) – Minimum SSP contribution percentage to include in the calculation. Default: 5.

  • age_decimals (int, optional) – Number of decimals to round age calculations. Default: 2.

  • rv (float, optional) – Reddening parameter (R_v). Default: 3.1.

  • z_decimals (int, optional) – Number of decimal places to round metallicity calculations. Default: 3.

  • object_name (str, optional) – Name of the analyzed object. Default: “object_1”.

Returns:

An object encapsulating the spectral summary, including:

  • Processed header.

  • Generated ‘Spectrum1D’ spectra.

  • Key values such as age, metallicity, and reddening.

  • Processed tables with results.

Return type:

core.SpectralSummary