tud_lbm.io.plotting.base

Abstract base class for plot operators.

Classes

PlotOperator	Base class for a single-panel plotting operator.
AnalysisPlot	Base class for analysis plots computed from saved snapshot history.

Module Contents

class tud_lbm.io.plotting.base.PlotOperator(config: tud_lbm.config.SimulationConfig, data_dir: str | pathlib.Path | None = None)

Bases: abc.ABC

Base class for a single-panel plotting operator.

name: str

config

data_dir

abstractmethod __call__(ax: matplotlib.axes.Axes, data: dict[str, numpy.ndarray], timestep: int) → None

Draw this operator on the provided axes.

is_available(data: dict[str, numpy.ndarray]) → bool

Whether this operator has enough data to render.

class tud_lbm.io.plotting.base.AnalysisPlot(config: tud_lbm.config.SimulationConfig | None = None)

Bases: abc.ABC

Base class for analysis plots computed from saved snapshot history.

name: str

is_multi_panel: bool = False

config = None

abstractmethod compute(files: list[pathlib.Path]) → dict[str, numpy.ndarray]

Compute time-series arrays from snapshot files.

abstractmethod render(ax: matplotlib.axes.Axes, precomputed: dict[str, numpy.ndarray]) → None

Render the full analysis plot from precomputed arrays.

abstractmethod render_figure(files: list[pathlib.Path]) → matplotlib.figure.Figure

Build and return a complete standalone figure.

Only called when is_multi_panel is True; overrides the compute()/render(ax) flow used by single-panel analysis plots.

prime(files: list[pathlib.Path]) → None

Cache axis limits from the full dataset so animation frames use fixed axes.

update(ax: matplotlib.axes.Axes, files: list[pathlib.Path]) → None

Render a prefix of snapshot files with fixed (primed) axis limits.