AFL.double_agent.plotting module#

Visualization tools for materials composition and phase data.

This module provides plotting utilities for visualizing compositional data and phase diagrams. It supports both 2D and ternary plots using matplotlib, with special handling for labeled data and phase regions.

Key features: - Support for both 2D and ternary plots - Surface and scatter plot styles - Automatic handling of phase labels - Flexible customization through matplotlib parameters - Integration with xarray data structures

AFL.double_agent.plotting.plot_scatter_mpl(dataset: Dataset, component_variable: str, component_dim: str = 'component', labels: str | None | List = None, discrete_labels: bool = True, set_axes_labels: bool = True, ternary: bool = True, **mpl_kw) → List[Artist]#

Create a scatter plot of compositional data using matplotlib.

Generates a scatter plot of compositional data, supporting both 2D Cartesian and ternary plots. Points can be colored and marked according to phase labels or other values.

Parameters:

dataset (xr.Dataset) – Dataset containing compositional data and optional labels
component_variable (str) – Name of the variable containing component coordinates
component_dim (str, default='component') – Name of the dimension containing component names
labels (Union[Optional[str], List], default=None) – Labels for coloring points. Can be: - None: Will try to use ‘labels’ from dataset - str: Name of variable in dataset containing labels - List: Direct list of label values
discrete_labels (bool, default=True) – Whether to treat labels as discrete categories (True) or continuous values (False)
set_axes_labels (bool, default=True) – Whether to set axis labels using component names
ternary (bool, default=True) – Whether to create a ternary plot for 3-component data
**mpl_kw (dict) – Additional keyword arguments passed to matplotlib’s scatter

Returns:

List of created matplotlib artists

Return type:

List[plt.Artist]

Raises:

ValueError – If number of components is not 2 or 3
ImportError – If mpltern is not installed for ternary plots

Notes

When discrete_labels is True, different marker styles are used for each unique label value, cycling through a predefined set of markers.

AFL.double_agent.plotting.plot_surface_mpl(dataset: Dataset, component_variable: str, component_dim: str = 'component', labels: str | None | List = None, set_axes_labels: bool = True, ternary: bool = True, **mpl_kw) → List[Artist]#

Create a surface plot of compositional data using matplotlib.

Generates a filled surface plot of compositional data, supporting both 2D Cartesian and ternary plots. The surface is colored according to phase labels or other specified values.