API reference

The plotting defaults are set up such that the user is not expected to modify them in order to get publication-ready plots. However, because there is no “right way” to make a figure, it is impossible to create a set of defaults that satisfy everyone. These defaults are made accessible so that users can easily modify the figures in a single location, if desired.

These defaults are provided as immutable dataclasses and are intended to:

Ensure consistent visual styling across plots
Provide sensible, publication-ready defaults
Allow users to override behavior in a controlled and explicit way

class ampy.defaults.plotting.BandColorMap(colors=<factory>, aliases=<factory>, default='black')

Bases: object

Default color mapping for photometric bands.

This class maps band or filter names to colors used when plotting photometric data. It also supports alias names that map to canonical band identifiers.

colors: Mapping[str, str]

aliases: Mapping[str, str]

default: str: Fallback color used when a band is not recognized.

get(band)

Return the plotting color for a given band name.

Parameters:: band (str) – Band or filter identifier.
Returns:: Color associated with the band. If the band is unknown, the default color is returned.
Return type:: str

class ampy.defaults.plotting.CornerPlotDefaults(label_size=16, show_titles=True, color='mediumblue', plot_datapoints=False, quantiles=(0.16, 0.5, 0.84), label_kwargs=<factory>, title_kwargs=<factory>, fill_contours=True, smooth=0.7, smooth1d=0.7)

Bases: object

Default configuration for corner plots.

This class defines the default keyword arguments passed to corner.corner() when visualizing posterior samples.

label_size: int: Base label size used by the corner plot (if supported by the caller).

show_titles: bool: Whether to show summary statistics in titles on the diagonal.

color: str: Primary contour/line color used for the corner plot.

plot_datapoints: bool: Whether to draw individual sample points (can be slow/overplotted).

quantiles: tuple[float, float, float]: Quantiles shown in titles (e.g., 16th/50th/84th percentiles).

label_kwargs: dict[str, Any]: Keyword arguments forwarded to label text creation.

title_kwargs: dict[str, Any]: Keyword arguments forwarded to title text creation.

fill_contours: bool: Whether to fill contour levels.

smooth: float: Smoothing applied to 2D histograms (KDE-ish; see corner docs).

smooth1d: float: Smoothing applied to 1D histograms (diagonal panels).

kwargs()

Return keyword arguments compatible with corner.corner().

Returns:: Suitable for unpacking into corner.corner(..., **kwargs).
Return type:: dict

class ampy.defaults.plotting.ObservedIndexStyle(fmt='o', linestyle='none', capsize=3.0, color='black', zorder=999)

Bases: object

Default styling for observed spectral index points.

This class defines the default keyword arguments passed to matplotlib.axes.Axes.errorbar() when plotting observed spectral indices.

fmt: str: Marker style used for the observed points.

linestyle: str: Line style connecting points (typically disabled).

capsize: float: Size of the error bar caps, in points.

color: str: Color used for the observed data points.

zorder: int: Z-order of the observed points (drawn above most elements).

kwargs()

Return the style as a dictionary of keyword arguments.

Returns:: Dictionary suitable for unpacking into a Matplotlib plotting call (e.g., ax.errorbar(**kwargs)).
Return type:: dict

class ampy.defaults.plotting.SpectralLegendStyle(mode='expand', loc='upper center', bbox_to_anchor=(0.09, 0.97, 0.9, 0.01), frameon=True, fancybox=False, edgecolor='black')

Bases: object

Default configuration for spectral plot legends.

This style is intended for figure-level legends placed above the multi-panel spectral plot.

mode: str: If mode is set to “expand” the legend will be horizontally expanded to fill the Axes area (or bbox_to_anchor if defines the legend’s size).

loc: str: Legend location string passed to Matplotlib.

bbox_to_anchor: tuple[float, float, float, float]: Bounding box anchor for the legend in figure coordinates.

frameon: bool: Whether to draw a frame around the legend.

fancybox: bool: Whether to use a rounded legend box.

edgecolor: str: Color of the legend frame.

kwargs()

Return legend keyword arguments.

Return type:: dict

class ampy.defaults.plotting.SpectralLayout(figsize=(8.0, 10.0), height_ratios=(3.0, 1.0), sharex=True)

Bases: object

Default configuration for spectral subplots.

figsize: tuple[float, float]: The (width, height) in inches.

height_ratios: tuple[float, float]: Ratio of the subplot heights.

sharex: bool: Whether to share the x-axis between subplots.

kwargs()

Matplotlib wants gridspec_kw as a dict.

Return type:: dict

class ampy.defaults.plotting.SpectralColors(nu_a='tab:green', nu_m='tab:blue', nu_c='tab:orange')

Bases: object

Default configuration for the frequency curve colors.

nu_a: str: Color of the synchrotron self-absorption curves.

nu_m: str: Color of the synchrotron frequency curves.

nu_c: str: Color of the cooling frequency curves.

mapping()

Return type:: Mapping[str, str]

class ampy.defaults.plotting.DensityDistributionStyle(alpha=0.3, linewidth=0.5, linestyle='-', color='tab:purple')

Bases: object

Default styling for sampled or distribution density profiles.

This style is used when plotting an ensemble of density profiles (e.g., posterior samples or uncertainty bands).

alpha: float: Transparency applied to individual density profile curves.

linewidth: float: Line width of individual density profile curves.

linestyle: str: Line style used for distribution curves.

color: str: Color used for the density profile distribution.

kwargs()

Return the style as Matplotlib keyword arguments.

Returns:: Dictionary suitable for unpacking into a Matplotlib line plotting call (e.g., ax.plot(**kwargs)).
Return type:: dict

class ampy.defaults.plotting.DensityBestStyle(linewidth=2.0, linestyle='-', color='tab:orange', label='Most Likely')

Bases: object

Default styling for the most-likely (best-fit) density profile.

This style is intended to visually distinguish the best-fit density profile from the broader distribution.

linewidth: float: Line width of the best-fit density profile curve.

linestyle: str: Line style used for the best-fit density profile.

color: str: Color used for the best-fit density profile.

label: str: Legend label for the best-fit density profile.

kwargs()

Return the style as Matplotlib keyword arguments.

Returns:: Dictionary suitable for unpacking into a Matplotlib line plotting call (e.g., ax.plot(**kwargs)).
Return type:: dict

class ampy.defaults.plotting.SpectralPlotDefaults(observed=<factory>, legend=<factory>, layout=<factory>, colors=<factory>)

Bases: object

Default plotting configuration for spectral figures.

This class groups all default styling and layout options used when generating spectral plots in AMPy. Users may override any subset of these defaults by constructing a new instance.

observed: ObservedIndexStyle: Defaults for observed spectral index markers.

legend: SpectralLegendStyle: Defaults for the figure-level legend.

layout: SpectralLayout: Defaults for subplot layout and sizing.

colors: SpectralColors: Default colors for spectral break curves.

class ampy.defaults.plotting.DensityProfileDefaults(distribution=<factory>, best=<factory>)

Bases: object

Default plotting configuration for density profile figures.

This class groups all default styling options used when plotting circumburst density profiles in AMPy.

distribution: DensityDistributionStyle: Defaults for sampled or distribution density profile curves.

best: DensityBestStyle: Defaults for the most-likely (best-fit) density profile curve.