porereax.plot

Module for plotting sampled data.

The module provides functions to plot histograms, time series, and 2D density data from sampled data.

Functions

plot(→ tuple[matplotlib.figure.Figure | None, ...)

Plot sampled data from a data file.

Module Contents

porereax.plot.plot(link_data: str, axis: matplotlib.axes.Axes | None = None, identifiers: list = [], colors: list = [], std: bool = False, mean: bool = False, density: bool = False, dt: int = 50, transpose: bool = False, plot_kwargs_1d: dict = {}, plot_kwargs_2d: dict = {}) tuple[matplotlib.figure.Figure | None, matplotlib.axes.Axes][source]

Plot sampled data from a data file. All types of samplers are supported. Depending on the sampler type and dimension, different types of plots will be generated.

Parameters:
  • link_data (str) – Path to the data file created by a sampler instance.

  • axis (matplotlib.axes.Axes, optional) – Axis to plot on. If None, a new figure and axis will be created (default is None).

  • identifiers (list, optional) – List of identifiers to plot. If empty, all identifiers will be plotted (default is []).

  • colors (list, optional) – List of colors to use for plotting. If empty, default colors will be used (default is []).

  • std (bool, optional) – Whether to plot standard deviation shading (default is False).

  • mean (bool, optional) – Whether to plot mean values as vertical lines (default is False).

  • density (bool, optional) – Whether to normalize histograms to density (default is False).

  • dt (int, optional) – Time step in femtoseconds for time series plots (default is 50).

  • transpose (bool, optional) – Whether to transpose the axes for 2D density plots (default is False).

  • plot_kwargs_1d (dict, optional) – Additional keyword arguments for 1D plots (default is {}).

  • plot_kwargs_2d (dict, optional) – Additional keyword arguments for 2D plots (default is {}).

Returns:

A tuple containing the figure and axis objects. If an axis was provided, the figure will be None.

Return type:

tuple