streamsim.src.core.config module

Configuration of plotting setup for the streaming framework.

class streamsim.src.core.config.PlottingSetup(fig: Any, ax: Any, artists: Dict[str, Any] = None, xlim: Tuple[float, float] = None, ylim: Tuple[float, float] = None, title: str = 'Streaming Data Visualization')[source]

Bases: object

Encapsulates matplotlib figure and axes configuration for streaming visualizations.

This class serves as a centralized container for managing plot setup state, including figure/axes references, artist collections, and axis limits. It provides a clean interface for initializing and configuring matplotlib plots used in real-time streaming applications.

fig

Matplotlib Figure instance. Typically created via plt.figure() or plt.subplots() before passing to this class.

Type:: Any

ax

Matplotlib Axes instance where data will be rendered. This is the primary plotting surface for streaming visualizations.

Type:: Any

artists

Dictionary mapping names to matplotlib artists (lines, markers, patches, etc.) managed by this setup. Enables organized retrieval and updates during animation loops. Defaults to empty dict.

Type:: Dict[str, Any]

xlim

Optional x-axis bounds as (min, max). If None, axes auto-scale. Defaults to None.

Type:: Tuple[float, float] | None

ylim

Optional y-axis bounds as (min, max). If None, axes auto-scale. Defaults to None.

Type:: Tuple[float, float] | None

title

Plot title displayed above the axes. Defaults to “Streaming Data Visualization”.

Type:: str

configure()[source]: Applies the configured title and axis limits to the axes instance. Should be called once during initialization.

Example

>>> import matplotlib.pyplot as plt
>>> fig, ax = plt.subplots()
>>> setup = PlottingSetup(
...     fig=fig,
...     ax=ax,
...     xlim=(0, 100),
...     ylim=(-1, 1),
...     title="Real-time ECG Monitor"
... )
>>> setup.configure()
>>> # Later, store artists for tracking
>>> setup.artists['signal'] = ax.plot([], [])[0]

Note

The Any type hints for fig and ax are used for flexibility across matplotlib backends. In practice, these should be matplotlib.figure.Figure and matplotlib.axes.Axes instances respectively.