larvaworld.lib.plot.grid

Composite grid-structured figure

Functions

calibration_plot(→ Any)	Create calibration summary figure from existing plots.
model_summary(→ Any)	Create comprehensive model summary grid figure.
velocity_definition(→ None)	Create velocity definition comparison figure.
exploration_summary(, **kwargs)	Create exploration behavior summary grid figure.
dsp_summary(, **kwargs)	Create dispersal behavior summary grid figure.
RvsS_summary(→ Any)	Create Rover vs Sitter comparison summary grid figure.
DoublePatch_summary(→ Any)	Create double-patch assay summary grid figure.
chemo_summary(→ Any)	Create chemotaxis assay summary grid figure.
result_summary(→ Any)	Create experiment result summary grid figure.
model_sample_track(→ Any)	Create sample trajectory tracks from model simulation.
eval_summary(→ Any)	Create model evaluation summary grid figure.

Module Contents

larvaworld.lib.plot.grid.calibration_plot(save_to: str | None = None, files: Sequence[str] | None = None) → Any

Create calibration summary figure from existing plots.

Combines multiple calibration plots (interference, bouts, orientation, angular parameters, bend) into a single composite figure.

Args:

save_to: Directory to save plot. Defaults to current directory files: List of image file paths to combine. Auto-generated if None

Returns:

Matplotlib figure object

Example:

>>> fig = calibration_plot(save_to='./calibration', files=['plot1.png', 'plot2.png'])

larvaworld.lib.plot.grid.model_summary(mID: str, refID: str | None = None, refDataset: Any = None, Nids: int = 1, model_table: bool = False, **kwargs: Any) → Any

Create comprehensive model summary grid figure.

Generates multi-panel figure showing model configuration, parameter histograms, stride cycles, behavioral epochs, and sample tracks compared to reference data.

Args:

mID: Model ID to summarize refID: Reference dataset ID. Defaults to None refDataset: Pre-loaded reference dataset. Loads from refID if None Nids: Number of sample individuals to plot. Defaults to 1 model_table: Whether to include parameter table. Defaults to False **kwargs: Additional arguments passed to GridPlot

Returns:

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

Example:

>>> fig = model_summary(mID='model_01', refID='reference', Nids=3)

larvaworld.lib.plot.grid.velocity_definition(dataset: Any, save_to: str | None = None, save_as: str = 'vel_definition.pdf', component_vels: bool = True, **kwargs: Any) → None

Create velocity definition comparison figure.

Generates panel showing different velocity calculation methods with visual comparison of component velocities and their definitions.

Args:

dataset: Dataset containing velocity data save_to: Directory to save plot. Uses dataset plot dir if None save_as: Filename for saved plot. Defaults to ‘vel_definition.pdf’ component_vels: Whether to show component velocities. Defaults to True **kwargs: Additional plotting arguments

Example:

>>> velocity_definition(dataset, save_to='./figures', component_vels=True)

larvaworld.lib.plot.grid.exploration_summary(datasets: Sequence[Any], target: Any = None, range: Tuple[int, int] = (0, 40), **kwargs: Any) → Any

Create exploration behavior summary grid figure.

Generates comprehensive grid showing exploration metrics, spatial distributions, and trajectories over specified time range.

Args:

datasets: List of datasets to compare target: Target dataset for comparison. Defaults to None range: Time range (start, end) in minutes. Defaults to (0, 40) **kwargs: Additional arguments passed to GridPlot

Returns:

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

Example:

>>> fig = exploration_summary(datasets=[d1, d2], range=(0, 60))

larvaworld.lib.plot.grid.dsp_summary(datasets: Sequence[Any], target: Any = None, range: Tuple[int, int] = (0, 40), **kwargs: Any) → Any

Create dispersal behavior summary grid figure.

Generates comprehensive grid showing dispersal metrics, spatial spread, and movement patterns over specified time range.

Args:

datasets: List of datasets to compare target: Target dataset for comparison. Defaults to None range: Time range (start, end) in minutes. Defaults to (0, 40) **kwargs: Additional arguments passed to GridPlot

Returns:

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

Example:

>>> fig = dsp_summary(datasets=[d1, d2], range=(0, 60))

larvaworld.lib.plot.grid.RvsS_summary(entrylist: Sequence[Dict[str, Any]], title: str, mdiff_df: Any, **kwargs: Any) → Any

Create Rover vs Sitter comparison summary grid figure.

Generates multi-panel figure comparing rover and sitter behavioral phenotypes with statistical comparison table and multiple plot types.

Args:

entrylist: List of plot entry dictionaries with plotID, args, and name keys title: Main figure title mdiff_df: DataFrame with statistical comparison metrics **kwargs: Additional arguments passed to GridPlot

Returns:

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

Example:

>>> fig = RvsS_summary(entrylist=[...], title='Phenotype Comparison', mdiff_df=df)

larvaworld.lib.plot.grid.DoublePatch_summary(datasets: Dict[str, Sequence[Any]], title: str, mdiff_df: Any, ks: Sequence[str] | None = None, name: str | None = None, **kwargs: Any) → Any

Create double-patch assay summary grid figure.

Generates comprehensive figure showing trajectories and behavioral metrics for double-patch food choice experiments across conditions.

Args:

datasets: Dictionary mapping condition names to dataset lists title: Main figure title mdiff_df: DataFrame with statistical comparison metrics ks: Parameter keys to plot. Uses default set if None name: Plot name for saving. Auto-generated if None **kwargs: Additional arguments passed to GridPlot

Returns:

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

Example:

>>> fig = DoublePatch_summary(datasets={'control': [d1], 'test': [d2]}, title='Food Choice', mdiff_df=df)

larvaworld.lib.plot.grid.chemo_summary(datasets: Dict[str, Sequence[Any]], mdiff_df: Any, title: str, **kwargs: Any) → Any

Create chemotaxis assay summary grid figure.

Generates comprehensive figure showing chemotaxis behavior including trajectories, orientation metrics, and statistical comparisons.

Args:

datasets: Dictionary mapping condition names to dataset lists mdiff_df: DataFrame with statistical comparison metrics title: Main figure title **kwargs: Additional arguments passed to GridPlot

Returns:

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

Example:

>>> fig = chemo_summary(datasets={'control': [d1], 'odor': [d2]}, mdiff_df=df, title='Chemotaxis')

larvaworld.lib.plot.grid.result_summary(datasets: Sequence[Any], target: Any, **kwargs: Any) → Any

Create experiment result summary grid figure.

Generates comprehensive grid showing experiment results with multiple panels for trajectories, metrics, and comparisons to target data.

Args:

datasets: List of datasets to summarize target: Target dataset for comparison **kwargs: Additional arguments passed to GridPlot

Returns:

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

Example:

>>> fig = result_summary(datasets=[d1, d2], target=ref_dataset)

larvaworld.lib.plot.grid.model_sample_track(mID: str | None = None, m: Any = None, dur: float = 2 / 3, dt: float = 1 / 16, Nids: int = 1, min_turn_amp: float = 20, d: Any = None, **kwargs: Any) → Any

Create sample trajectory tracks from model simulation.

Simulates and plots sample individual tracks showing trajectory, turns, and behavioral details for model validation.

Args:

mID: Model ID to simulate. Required if m is None m: Pre-loaded model object. Loads from mID if None dur: Simulation duration in minutes. Defaults to 2/3 (40 seconds) dt: Time step in seconds. Defaults to 1/16 Nids: Number of individuals to simulate. Defaults to 1 min_turn_amp: Minimum turn amplitude to highlight. Defaults to 20 degrees d: Pre-loaded dataset for comparison. Defaults to None **kwargs: Additional arguments passed to GridPlot

Returns:

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

Example:

>>> fig = model_sample_track(mID='model_01', dur=1.0, Nids=3)

larvaworld.lib.plot.grid.eval_summary(error_dict: Dict[str, Any], evaluation: Any, norm_mode: str = 'raw', eval_mode: str = 'pooled', **kwargs: Any) → Any

Create model evaluation summary grid figure.

Generates comprehensive evaluation figure with error bar plots, statistical tables, and comparison metrics for model-data fit assessment.

Args:

error_dict: Dictionary containing error metrics by type evaluation: Evaluation metadata with model labels and colors norm_mode: Normalization mode (‘raw’, ‘normalized’). Defaults to ‘raw’ eval_mode: Evaluation mode (‘pooled’, ‘1:1’). Defaults to ‘pooled’ **kwargs: Additional arguments passed to GridPlot

Returns:

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

Example:

>>> fig = eval_summary(error_dict=errors, evaluation=eval_meta, eval_mode='pooled')