redback.plotting.LuminosityOpticalPlotter

class redback.plotting.LuminosityOpticalPlotter(transient: Transient | None, **kwargs)

Bases: IntegratedFluxPlotter

__init__(transient: Transient | None, **kwargs) → None

Parameters:

• transient – An instance of redback.transient.Transient. Contains the data to be plotted.

• kwargs – Additional kwargs the plotter uses. ——-

Keyword Arguments:

• capsize – Same as matplotlib capsize.

• bands_to_plot – List of bands to plot in plot lightcurve and multiband lightcurve. Default is active bands.

• legend_location – Same as matplotlib legend location.

• legend_cols – Same as matplotlib legend columns.

• color – Color of the data points.

• band_colors – A dictionary with the colors of the bands.

• band_labels – List with the names of the bands.

• band_scaling – Dict with the scaling for each band. First entry should be {type: ‘+’ or ‘x’} for different types.

• dpi – Same as matplotlib dpi.

• elinewidth – same as matplotlib elinewidth

• errorbar_fmt – ‘fmt’ argument of ax.errorbar.

• model – str or callable, the model to plot.

• ms – Same as matplotlib markersize.

• axis_tick_params_pad – pad argument in calls to ax.tick_params when setting the axes.

• max_likelihood_alpha – alpha argument, i.e. transparency, when plotting the max likelihood curve.

• random_sample_alpha – alpha argument, i.e. transparency, when plotting random sample curves.

• uncertainty_band_alpha – alpha argument, i.e. transparency, when plotting a credible band.

• max_likelihood_color – Color of the maximum likelihood curve.

• random_sample_color – Color of the random sample curves.

• bbox_inches – Setting for saving plots. Default is ‘tight’.

• linewidth – Same as matplotlib linewidth

• zorder – Same as matplotlib zorder

• xy – For `ax.annotate’ x and y coordinates of the point to annotate.

• xycoords – The coordinate system xy is given in. Default is ‘axes fraction’

• horizontalalignment – Horizontal alignment of the annotation. Default is ‘right’

• annotation_size – size argument of of ax.annotate.

• fontsize_axes – Font size of the x and y labels.

• fontsize_legend – Font size of the legend.

• fontsize_figure – Font size of the figure. Relevant for multiband plots. Used on supxlabel and supylabel.

• fontsize_ticks – Font size of the axis ticks.

• hspace – Argument for subplots_adjust, sets horizontal spacing between panels.

• wspace – Argument for subplots_adjust, sets horizontal spacing between panels.

• plot_others – Whether to plot additional bands in the data plot, all in the same colors

• random_models – Number of random draws to use to calculate credible bands or to plot.

• uncertainty_mode – ‘random_models’: Plot random draws from the available parameter sets. ‘credible_intervals’: Plot a credible interval that is calculated based on the available parameter sets.

• reference_mjd_date – Date to use as reference point for the x axis. Default is the first date in the data.

• credible_interval_level – 0.9: Plot the 90% credible interval.

• plot_max_likelihood – Plots the draw corresponding to the maximum likelihood. Default is ‘True’.

• set_same_color_per_subplot – Sets the lightcurve to be the same color as the data per subplot. Default is ‘True’.

• xlim_high_multiplier – Adjust the maximum xlim based on available x values.

• xlim_low_multiplier – Adjust the minimum xlim based on available x values.

• ylim_high_multiplier – Adjust the maximum ylim based on available x values.

• ylim_low_multiplier – Adjust the minimum ylim based on available x values.

• show_grid – Whether to show grid lines. Default is False.

• grid_alpha – Transparency of grid lines. Default is 0.3.

• grid_color – Color of grid lines. Default is ‘gray’.

• grid_linestyle – Line style of grid lines. Default is ‘–‘.

• grid_linewidth – Line width of grid lines. Default is 0.5.

• save_format – Format for saving plots (e.g., ‘png’, ‘pdf’, ‘svg’, ‘eps’). Default is ‘png’.

• transparent – Whether to save plots with transparent background. Default is False.

• xscale – X-axis scale (‘linear’, ‘log’, ‘symlog’, ‘logit’). Default is None (auto-determined).

• yscale – Y-axis scale (‘linear’, ‘log’, ‘symlog’, ‘logit’). Default is None (auto-determined).

• title – Title for the plot. Default is None (no title).

• title_fontsize – Font size for the title. Default is 20.

• linestyle – Line style for model curves. Default is ‘-‘.

• max_likelihood_linestyle – Line style for max likelihood curve. Default is ‘-‘.

• random_sample_linestyle – Line style for random sample curves. Default is ‘-‘.

• markerfillstyle – Fill style for markers (‘full’, ‘left’, ‘right’, ‘bottom’, ‘top’, ‘none’). Default is ‘full’.

• markeredgecolor – Edge color for markers. Default is None (same as face color).

• markeredgewidth – Edge width for markers. Default is 1.0.

• legend_frameon – Whether to draw a frame around the legend. Default is True.

• legend_shadow – Whether to draw a shadow behind the legend. Default is False.

• legend_fancybox – Whether to use rounded corners for legend frame. Default is True.

• legend_framealpha – Transparency of legend frame. Default is 0.8.

• tick_direction – Direction of tick marks (‘in’, ‘out’, ‘inout’). Default is ‘in’.

• tick_length – Length of tick marks. Default is None (matplotlib default).

• tick_width – Width of tick marks. Default is None (matplotlib default).

• show_spines – Whether to show plot spines (borders). Default is True.

• spine_linewidth – Width of plot spines. Default is None (matplotlib default).

__call__(**kwargs)

Call self as a function.

Methods

__init__(transient, **kwargs)
get_filename(default)
plot_data([axes, save, show])	Plots the Integrated flux data and returns Axes.
plot_lightcurve([axes, save, show])	Plots the Integrated flux data and the lightcurve and returns Axes.
plot_residuals([axes, save, show])	Plots the residual of the Integrated flux data returns Axes.

Attributes

keyword_docstring

plot_data(axes: Axes = None, save: bool = True, show: bool = True) → Axes

Plots the Integrated flux data and returns Axes.

Parameters:

• axes (Union[matplotlib.axes.Axes, None], optional) – Matplotlib axes to plot the data into. Useful for user specific modifications to the plot.

• save (bool) – Whether to save the plot. (Default value = True)

• show (bool) – Whether to show the plot. (Default value = True)

Returns:

The axes with the plot.

Return type:

matplotlib.axes.Axes

plot_lightcurve(axes: Axes = None, save: bool = True, show: bool = True) → Axes

Plots the Integrated flux data and the lightcurve and returns Axes.

Parameters:

• axes (Union[matplotlib.axes.Axes, None], optional) – Matplotlib axes to plot the lightcurve into. Useful for user specific modifications to the plot.

• save (bool) – Whether to save the plot. (Default value = True)

• show (bool) – Whether to show the plot. (Default value = True)

Returns:

The axes with the plot.

Return type:

matplotlib.axes.Axes

plot_residuals(axes: Axes = None, save: bool = True, show: bool = True) → Axes

Plots the residual of the Integrated flux data returns Axes.

Parameters:

• axes – Matplotlib axes to plot the lightcurve into. Useful for user specific modifications to the plot.

• save – Whether to save the plot. (Default value = True)

• show – Whether to show the plot. (Default value = True)

Returns:

The axes with the plot.

Return type:

matplotlib.axes.Axes