Neural Output Visualization and Analysis
Aggregate Data by Groups
Analyze and Visualize PCA Variable Importance
Apply Enhanced Scaling Methods
Clean Heatmap Matrix
Create Enhanced Annotations for Heatmaps
Create Enhanced Color Palettes
Create Enhanced Heatmaps for Multi-Electrode Array (MEA) Data Analysis
Discover MEA Data Structure
Handle Missing Values in MEA Data
Package-level imports
NOVA: package-level imports and global variables
Null Coalescing Operator
Enhanced PCA Analysis for MEA Data
Enhanced PCA Plotting for Neural and Omics Data
Perform MEA PCA Analysis
Plot PCA Trajectories for Time Series Data
Print Detailed PCA Variable Summary
Process MEA Data Flexibly
Filter Data by Quality Metrics
Setup Color Scheme
A comprehensive toolkit for analyzing and visualizing neural data outputs, including Principal Component Analysis (PCA) trajectory plotting, Multi-Electrode Array (MEA) heatmap generation, and variable importance analysis. Provides publication-ready visualizations with flexible customization options for neuroscience research applications.