larvaworld.lib.plot.scape

Sensory landscape plotting

Functions

plot_odorscape(→ None)	Plot 3D odorscape surfaces for multiple odor layers.
odorscape_isocontours(→ None)	Plot odorscape as filled contour isocontours.
odorscape_with_sample_tracks(→ Any)	Plot odorscape with sample trajectory tracks overlaid.
plot_3pars(→ dict)	Create multiple plots for 3-parameter relationships.
plot_heatmap_PI(→ Any)	Create heatmap of Preference Index (PI) values.
plot_2d(→ Any)	Create 2D scatter plot of parameter vs result.

Module Contents

larvaworld.lib.plot.scape.plot_odorscape(odor_layers: dict, scale: float = 1.0, idx: int = 0, **kwargs: Any) → None

Plot 3D odorscape surfaces for multiple odor layers.

Creates 3D surface plots showing spatial distribution of odor concentrations across the environment arena.

Args:

odor_layers: Dictionary of odor layer objects with grid and meshgrid scale: Spatial scale factor. Defaults to 1.0 idx: Index for file naming. Defaults to 0 **kwargs: Additional arguments passed to plot_surface

Example:

>>> plot_odorscape(odor_layers={'odor1': layer1}, scale=1.0, idx=0)

larvaworld.lib.plot.scape.odorscape_isocontours(intensity: float = 2, spread: float = 0.0002, radius: float = 0.05) → None

Plot odorscape as filled contour isocontours.

Creates 2D contour plot showing odor concentration gradients from a point source using multivariate normal distribution.

Args:

intensity: Peak odor intensity. Defaults to 2 spread: Odor spread parameter. Defaults to 0.0002 radius: Plot radius in meters. Defaults to 0.05

Example:

>>> odorscape_isocontours(intensity=2, spread=0.0002, radius=0.05)

larvaworld.lib.plot.scape.odorscape_with_sample_tracks(datasets: Sequence[Any], unit: str = 'mm', fig: Any = None, axs: Any = None, show: bool = False, save_to: str | None = None, **kwargs: Any) → Any

Plot odorscape with sample trajectory tracks overlaid.

Creates 2D odorscape visualization with individual trajectory tracks from multiple datasets shown as colored paths.

Args:

datasets: List of datasets containing trajectory data unit: Distance unit (‘mm’ or ‘m’). Defaults to ‘mm’ fig: Matplotlib figure. Creates new if None axs: Matplotlib axes. Creates new if None show: Whether to display plot. Defaults to False save_to: Directory to save plot. Defaults to None **kwargs: Additional arguments passed to odorscape_from_config

Returns:

Matplotlib figure object

Example:

>>> fig = odorscape_with_sample_tracks(datasets=[d1, d2], unit='mm', show=True)

larvaworld.lib.plot.scape.plot_3pars(df: pandas.DataFrame, vars: Sequence[str], target: str, z0: float | None = None, **kwargs: Any) → dict

Create multiple plots for 3-parameter relationships.

Generates 3D plot, heatmap, and surface plot showing relationship between two independent variables and a target variable.

Args:

df: DataFrame containing parameter data vars: List of 2 independent variable names target: Target variable name z0: Reference z-value for horizontal plane. Defaults to None **kwargs: Additional arguments passed to plotting functions

Returns:

Dictionary of figure objects keyed by plot type

Example:

>>> figs = plot_3pars(df, vars=['param1', 'param2'], target='result')

larvaworld.lib.plot.scape.plot_heatmap_PI(z: pandas.DataFrame | None = None, csv_filepath: str = 'PIs.csv', save_as: str = 'PI_heatmap.pdf', **kwargs: Any) → Any

Create heatmap of Preference Index (PI) values.

Generates color-coded heatmap showing PI values across left and right odor gain combinations, with red-yellow-green colormap.

Args:

z: DataFrame with PI values. Loads from csv_filepath if None csv_filepath: Path to CSV file with PI data. Defaults to ‘PIs.csv’ save_as: Filename for saved plot. Defaults to ‘PI_heatmap.pdf’ **kwargs: Additional arguments passed to plot_heatmap

Returns:

Plot output (figure object or None based on return_fig setting)

Example:

>>> fig = plot_heatmap_PI(z=pi_data, save_as='preference_heatmap.pdf')

larvaworld.lib.plot.scape.plot_2d(df: pandas.DataFrame, labels: Sequence[str], **kwargs: Any) → Any

Create 2D scatter plot of parameter vs result.

Simple scatter plot showing relationship between a parameter and a result variable.

Args:

df: DataFrame containing data labels: List of 2 labels [parameter, result] **kwargs: Additional arguments passed to AutoBasePlot

Returns:

Plot output (figure object or None based on return_fig setting)

Example:

>>> fig = plot_2d(df, labels=['temperature', 'velocity'])