Visualization Module

Visualization module for organizing analysis results and creating plots.

This module provides tools to aggregate, organize, and visualize the outputs of the neurodent.core analysis pipeline across animals and experiments.

Typical Workflow:

from neurodent import visualization as viz
from neurodent.core import LongRecordingAnalyzer

# 1. Wrap analysis results for easier access
war = viz.WindowAnalysisResult.load('analysis_results.pkl')

# 2. Aggregate across sessions for one animal
organizer = viz.AnimalOrganizer([war1, war2, war3])
combined_df = organizer.get_combined_features()

# 3. Plot temporal heatmaps
plotter = viz.AnimalPlotter(organizer)
fig = plotter.plot_temporal_heatmap(feature='psdband', band='theta')

# 4. Experiment-wide comparisons (multiple animals)
exp_plotter = viz.ExperimentPlotter([animal1_org, animal2_org])
fig = exp_plotter.plot_genotype_comparison(feature='cohere')

Output Types:

• Temporal heatmaps: Feature values over time (x) and channels (y)

• Band comparisons: Power across frequency bands

• Statistical plots: Genotype/condition comparisons with error bars

• Export to CSV/TIF: Publication-ready outputs

See Also:

• Visualization Tutorial - Plotting examples

• Windowed Analysis Tutorial - Understanding result structure

• neurodent.constants.plotting - Color palettes and styling

Classes

AnimalOrganizer	Organizes and analyzes recording data from a single animal across multiple sessions.
WindowAnalysisResult	Wrapper for output of windowed analysis.
FrequencyDomainSpikeAnalysisResult	Wrapper for frequency-domain spike detection results.
AnimalPlotter	Class for plotting results from an AnimalOrganizer/WindowAnalysisResult.
ExperimentPlotter	A class for creating various plots from a list of multiple experimental datasets.