tardis.visualization.tools.sdec_plot module

Spectral element DEComposition (SDEC) Plot for TARDIS simulation models.

This plot is a spectral diagnostics plot similar to those originally proposed by M. Kromer (see, for example, Kromer et al. 2013, figure 4).

class tardis.visualization.tools.sdec_plot.SDECPlotter

Bases: object

Plotting interface for Spectral element DEComposition (SDEC) Plot.

It performs necessary calculations to generate SDEC Plot for a simulation model, and allows to plot it in matplotlib and plotly.

Initialize the SDECPlotter with required data of simulation model.

classmethod from_hdf(hdf_fpath)

Create an instance of SDECPlotter from a simulation HDF file.

Parameters:

hdf_fpathstr

Valid path to the HDF file where simulation is saved

packets_mode{‘virtual’, ‘real’}, optional

Mode of packets to be considered (default: ‘virtual’)

Returns:

SDECPlotter

classmethod from_simulation(sim)

Create an instance of SDECPlotter from a TARDIS simulation object.

Parameters:

simtardis.simulation.Simulation

TARDIS Simulation object produced by running a simulation

Returns:

SDECPlotter

generate_plot_mpl(packets_mode='virtual', packet_wvl_range=None, distance=None, observed_spectrum=None, show_modeled_spectrum=True, ax=None, figsize=(12, 7), cmapname='jet', nelements=None, species_list=None, blackbody_photosphere=True)

Generate Spectral element DEComposition (SDEC) Plot using matplotlib.

Parameters:

packets_mode{‘virtual’, ‘real’}, optional

Mode of packets to be considered, either real or virtual. Default value is ‘virtual’

packet_wvl_rangeastropy.Quantity or None, optional

Wavelength range to restrict the analysis of escaped packets. It should be a quantity having units of Angstrom, containing two values - lower lambda and upper lambda i.e. [lower_lambda, upper_lambda] * u.AA. Default value is None

distanceastropy.Quantity or None, optional

Distance used to calculate flux instead of luminosity in the plot. It should have a length unit like m, Mpc, etc. Default value is None

observed_spectrumtuple or list of astropy.Quantity, optional

Option to plot an observed spectrum in the SDEC plot. If given, the first element should be the wavelength and the second element should be flux, i.e. (wavelength, flux). The assumed units for wavelength and flux are angstroms and erg/(angstroms * s * cm^2), respectively. Default value is None.

show_modeled_spectrumbool, optional

Whether to show modeled spectrum in SDEC Plot. Default value is True

axmatplotlib.axes._subplots.AxesSubplot or None, optional

Axis on which to create plot. Default value is None which will create plot on a new figure’s axis.

figsizetuple, optional

Size of the matplotlib figure to display. Default value is (12, 7)

cmapnamestr, optional

Name of matplotlib colormap to be used for showing elements. Default value is “jet”

nelements: int

Number of elements to include in plot. Determined by the largest contribution to total luminosity absorbed and emitted. Other elements are shown in silver. Default value is None, which displays all elements

species_list: list of strings or None

list of strings containing the names of species that should be included in the SDEC plots. Must be given in Roman numeral format. Can include specific ions, a range of ions, individual elements, or any combination of these: e.g. [‘Si II’, ‘Ca II’, ‘C’, ‘Fe I-V’]

blackbody_photosphere: bool

Whether to include the blackbody photosphere in the plot. Default value is True

Returns:

matplotlib.axes._subplots.AxesSubplot

Axis on which SDEC Plot is created

generate_plot_ply(packets_mode='virtual', packet_wvl_range=None, distance=None, observed_spectrum=None, show_modeled_spectrum=True, fig=None, graph_height=600, cmapname='jet', nelements=None, species_list=None, blackbody_photosphere=True)

Generate interactive Spectral element DEComposition (SDEC) Plot using plotly.

Parameters:

packets_mode{‘virtual’, ‘real’}, optional

Mode of packets to be considered, either real or virtual. Default value is ‘virtual’

packet_wvl_rangeastropy.Quantity or None, optional

Wavelength range to restrict the analysis of escaped packets. It should be a quantity having units of Angstrom, containing two values - lower lambda and upper lambda i.e. [lower_lambda, upper_lambda] * u.AA. Default value is None

distanceastropy.Quantity or None, optional

Distance used to calculate flux instead of luminosity in the plot. It should have a length unit like m, Mpc, etc. Default value is None

observed_spectrumtuple or list of astropy.Quantity, optional

Option to plot an observed spectrum in the SDEC plot. If given, the first element should be the wavelength and the second element should be flux, i.e. (wavelength, flux). The assumed units for wavelength and flux are angstroms and erg/(angstroms * s * cm^2), respectively. Default value is None.

show_modeled_spectrumbool, optional

Whether to show modeled spectrum in SDEC Plot. Default value is True

figplotly.graph_objs._figure.Figure or None, optional

Figure object on which to create plot. Default value is None which will create plot on a new Figure object.

graph_heightint, optional

Height (in px) of the plotly graph to display. Default value is 600

cmapnamestr, optional

Name of the colormap to be used for showing elements. Default value is “jet”

nelements: int

Number of elements to include in plot. Determined by the largest contribution to total luminosity absorbed and emitted. Other elements are shown in silver. Default value is None, which displays all elements

species_list: list of strings or None

list of strings containing the names of species that should be included in the SDEC plots. Must be given in Roman numeral format. Can include specific ions, a range of ions, individual elements, or any combination of these: e.g. [‘Si II’, ‘Ca II’, ‘C’, ‘Fe I-V’]

blackbody_photosphere: bool

Whether to include the blackbody photosphere in the plot. Default value is True

Returns:

plotly.graph_objs._figure.Figure

Figure object on which SDEC Plot is created

process_luminosity_dataframe(df, keys_to_exclude, other_column_position=0)

Process a luminosity DataFrame by aggregating specified columns into an ‘other’ column.

Parameters:

dfpandas.DataFrame

The DataFrame containing luminosity data to be processed.

keys_to_excludelist of str

Column names in df whose data should be summed into the ‘other’ column and removed.

other_column_positionint, optional

The integer location (0-indexed) at which to insert the new ‘other’ column. Defaults to 0.

Returns:

pandas.DataFrame

A new DataFrame with the excluded columns summed into ‘other’ and removed from the original.