Plotting

The plotting module provides visualization functions for ecological data.

Ordination Plots

nuee.plotting.plot_ordination(result: OrdinationResult, axes: Tuple[int, int] = (0, 1), display: str = 'sites', choices: List[int] | None = None, type: str = 'points', groups: ndarray | Series | None = None, colors: List[str] | None = None, figsize: Tuple[int, int] = (8, 6), scaling: int | str | None = None, title: str | None = None, **kwargs) → Figure[source]

Plot ordination results.

Parameters:

  • result – OrdinationResult object

  • axes – Which axes to plot

  • display – What to display (“sites”, “species”, “both”)

  • choices – Alternative way to specify axes

  • type – Plot type (“points”, “text”, “none”)

  • groups – Grouping factor for coloring points

  • colors – Colors for groups

  • figsize – Figure size

  • **kwargs – Additional plotting arguments

Returns:

matplotlib Figure object

nuee.plotting.biplot(result: OrdinationResult, axes: Tuple[int, int] = (0, 1), scaling: str | int = 'species', correlation: bool = False, figsize: Tuple[int, int] = (10, 8), title: str | None = None, arrow_mul: float | None = None, n_species: int | None = 15, show_site_labels: bool = True, show_species_labels: bool = True, repel: bool = True, fontsize: int = 8, site_kw: Dict[str, Any] | None = None, species_kw: Dict[str, Any] | None = None, env_kw: Dict[str, Any] | None = None, groups: ndarray | Series | list | None = None, color_by: ndarray | Series | list | None = None, cmap: str | None = None, **kwargs) → Figure[source]

Create a biplot for ordination results.

For unconstrained ordination (PCA, CA, LDA), species loadings are drawn as arrows from the origin. For constrained ordination (RDA / CCA), species are shown as points and environmental variables as arrows.

Parameters:

  • result (OrdinationResult) – Ordination result object.

  • axes (tuple of int) – Which ordination axes to plot (0-indexed).

  • scaling (str or int) – Scaling mode: 1/”sites”, 2/”species”, 3/”symmetric”.

  • correlation (bool) – If True, use raw correlation values without auto-scaling.

  • figsize (tuple of int) – Figure size in inches.

  • title (str, optional) – Plot title.

  • arrow_mul (float, optional) – Manual multiplier for arrow length.

  • n_species (int or None) – Show only the top n_species by loading magnitude. None shows all species.

  • show_site_labels (bool) – Whether to display site name labels.

  • show_species_labels (bool) – Whether to display species name labels.

  • repel (bool) – Use adjustText for ggrepel-style label placement.

  • fontsize (int) – Base font size for labels.

  • site_kw (dict, optional) – Extra keyword arguments for site scatter points.

  • species_kw (dict, optional) – Extra keyword arguments for species scatter/arrows.

  • env_kw (dict, optional) – Extra keyword arguments for environmental arrows.

  • groups (array-like, optional) – Categorical group labels (one per site) for coloured scatter. Auto-detected from LDA results.

  • color_by (array-like, optional) – Continuous values (one per site) for colour-mapped scatter with a colourbar. Mutually exclusive with groups.

  • cmap (str, optional) – Matplotlib colormap name. Default is the colour cycle for groups (up to 10) and "viridis" for color_by.

  • **kwargs – Additional keyword arguments passed to site scatter.

nuee.plotting.ordiplot(result: OrdinationResult, axes: Tuple[int, int] = (0, 1), display: str = 'sites', figsize: Tuple[int, int] = (8, 6), scaling: int | str | None = None, **kwargs) → Figure[source]

Basic ordination plot.

Parameters:

  • result – OrdinationResult object

  • axes – Which axes to plot

  • display – What to display (“sites”, “species”, “both”)

  • figsize – Figure size

  • **kwargs – Additional plotting arguments

Returns:

matplotlib Figure object

Diversity Plots

nuee.plotting.plot_diversity(diversity_data: ndarray | Series | DataFrame | DiversityResult, figsize: tuple = (8, 6), **kwargs) → Figure[source]

Plot diversity indices.

Parameters:

  • diversity_data – Diversity values

  • figsize – Figure size

  • **kwargs – Additional plotting arguments

Returns:

matplotlib Figure object

nuee.plotting.plot_rarecurve(rarecurve_data: Dict[str, Dict[str, ndarray]], figsize: tuple = (10, 6), **kwargs) → Figure[source]

Plot rarefaction curves.

Parameters:

  • rarecurve_data – Rarefaction curve data

  • figsize – Figure size

  • **kwargs – Additional plotting arguments

Returns:

matplotlib Figure object

Dissimilarity Plots

nuee.plotting.plot_dissimilarity(distance_matrix: ndarray | DataFrame, figsize: tuple = (8, 6), **kwargs) → Figure[source]

Plot dissimilarity matrix as heatmap.

Parameters:

  • distance_matrix – Distance/dissimilarity matrix

  • figsize – Figure size

  • **kwargs – Additional plotting arguments

Returns:

matplotlib Figure object