larvaworld.lib.plot.bar
=======================

.. py:module:: larvaworld.lib.plot.bar

.. autoapi-nested-parse::

   Barplots



Functions
---------

.. autoapisummary::

   larvaworld.lib.plot.bar.error_barplot
   larvaworld.lib.plot.bar.intake_barplot
   larvaworld.lib.plot.bar.barplot
   larvaworld.lib.plot.bar.auto_barplot


Module Contents
---------------

.. py:function:: error_barplot(error_dict: Dict[str, Any], evaluation: Dict[str, Any], labels: Optional[Dict[str, str]] = None, name: str = 'error_barplots', titles: Sequence[str] = ('$\\bf{endpoint}$ $\\bf{metrics}$', '$\\bf{timeseries}$ $\\bf{metrics}$'), **kwargs: Any) -> Any

   Create bar plots comparing error metrics across models.

   Generates multi-panel bar plots showing endpoint and timeseries error metrics
   for different model configurations with statistical comparisons.

   Args:
       error_dict: Dictionary of error DataFrames by metric type
       evaluation: Dictionary of evaluation metadata with group labels and colors
       labels: Custom labels for metric types. Defaults to metric keys
       name: Plot name for saving. Defaults to 'error_barplots'
       titles: Panel titles. Defaults to endpoint and timeseries labels
       **kwargs: Additional arguments passed to AutoBasePlot

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

   Example:
       >>> fig = error_barplot(error_dict, evaluation, labels={'endpoint': 'Endpoints'})


.. py:function:: intake_barplot(**kwargs: Any) -> Any

   Create bar plot of food intake amounts.

   Convenience wrapper for barplot() specifically for food amount ('f_am')
   parameter visualization across datasets.

   Args:
       **kwargs: Arguments passed to barplot()

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

   Example:
       >>> fig = intake_barplot(datasets=[d1, d2], labels=['Control', 'Test'])


.. py:function:: barplot(ks: Sequence[str], coupled_labels: Optional[Sequence[str]] = None, xlabel: Optional[str] = None, leg_cols: Optional[Sequence[str]] = None, **kwargs: Any) -> Any

   Create bar plots with statistical comparisons across datasets.

   Generates bar plots for specified parameters showing mean values with
   error bars and p-values from t-tests between dataset pairs.

   Args:
       ks: Parameter keys to plot
       coupled_labels: Labels for paired comparisons. If provided, datasets
           are grouped into pairs
       xlabel: Custom x-axis label. Defaults to None
       leg_cols: Colors for legend items. Auto-generated if None
       **kwargs: Additional arguments passed to AutoPlot

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

   Example:
       >>> fig = barplot(ks=['v', 'a'], datasets=[d1, d2], labels=['Control', 'Test'])


.. py:function:: auto_barplot(ks: Sequence[str], coupled_labels: Optional[Sequence[str]] = None, xlabel: Optional[str] = None, leg_cols: Optional[Sequence[str]] = None, **kwargs: Any) -> Any

   Create automatic bar plots with enhanced statistical annotations.

   Similar to barplot() but with enhanced automatic layout and statistical
   significance markers for paired comparisons. Shows asterisks for p <= 0.05.

   Args:
       ks: Parameter keys to plot
       coupled_labels: Labels for paired comparisons. If provided, datasets
           are grouped into pairs
       xlabel: Custom x-axis label. Defaults to None
       leg_cols: Colors for legend items. Auto-generated if None
       **kwargs: Additional arguments passed to AutoPlot

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

   Example:
       >>> fig = auto_barplot(ks=['run_count'], coupled_labels=['Control', 'Treatment'])