Package: fmristore 0.1.0

What is H5ParcellatedMultiScan? | Simple Example: From Data to Storage | Step 1: Create Brain Data | Step 2: Create Brain Regions (Clusters) | Step 3: Create Some fMRI Data | Step 4: Save Using the New Simple Interface | Step 5: Load Using the New Simple Interface | Step 6: Extract and Visualize Data | Understanding Single Scan vs Multi-Scan Containers | Single Scan: H5ParcellatedScanSummary | Multi-Scan: H5ParcellatedMultiScan | Converting ClusteredNeuroVec Objects | When to Use Each Format | Advanced Example: Multiple Runs with Summary Data | Create Multiple Runs | Save Multiple Runs | Automatic Type Detection | Working with Multiple Runs | Creating Summary Data | Key Functions Summary | write_dataset() - Save Your Data | read_dataset() - Load Your Data | detect_h5_type() - Identify File Contents | Memory Efficiency Tips | When to Use H5ParcellatedMultiScan | Cleanup | Next Steps

Why fmristore? | Quick Start: Choose Your Storage Format | Data Conversion Workflows | 1. Converting neuroim2 ClusteredNeuroVec | 2. Converting Regular NeuroVec to HDF5 | 3. Creating Multi-Scan Experiments | Performance Comparison | Best Practices | 1. Memory Management | 2. Choosing Between Single and Multi-Scan | 3. Data Access Patterns | Common Use Cases | Use Case 1: Single Subject, Multiple Runs | Use Case 2: Storing Subject Maps with LabeledVolumeSet | Use Case 3: Resting State Connectivity from Parcellated Data | Advanced Features | Latent Representations | Working with Atlas Labels | Troubleshooting | Common Issues and Solutions | Next Steps | Format Chooser

Why Use HDF5 for Neuroimaging? | Quick Start: 3D Brain Volumes | Working with fMRI Time Series (4D Data) | Loading Existing HDF5 Files | Best Practices | 1. Always Close Your Files | 2. Use Chunk Sizes Wisely | 3. Memory vs Speed Trade-off | Common Use Cases | Preprocessing Large Datasets | Region of Interest Analysis | Summary

How are individual scans organized? | The Data Hierarchy | Step 1: Create Sample Data Using the New Interface | Create Multiple fMRI Runs with Different Characteristics | Save Mixed Full and Summary Data | Converting neuroim2 ClusteredNeuroVec Objects | Creating a ClusteredNeuroVec | Converting to HDF5: Single Scan (Default) | Converting to HDF5: Multi-Scan Container | Step 2: Load the Data with read_dataset() | Step 3: Accessing Individual Scans from the Container | Understanding Individual Scan Properties | H5ParcellatedScan: Operations on Individual Full Scans | Extract Time Series from Individual Voxels | Extract Time Series for All Voxels in a Cluster | Compare Task vs Rest Scans (Individual Scan Analysis) | H5ParcellatedScanSummary: Operations on Individual Summary Scans | Extract and Analyze Summary Data | Compute Cluster-to-Cluster Correlations | Practical Usage Guidelines | Choose H5ParcellatedScan when you need: | Choose H5ParcellatedScanSummary when you need: | Key Individual Scan Operations Summary | Memory and Performance Considerations | Clean Up | Key Takeaways | Next Steps

What is a LabeledVolumeSet? | Quick Example: Storing Statistical Maps | Step 1: Create Example Data | Step 2: Create Brain Mask | Step 3: Save with Labels | Step 4: Load and Access | Real-World Use Case: Group Analysis Results | Working with Subject-Specific Maps | Create Subject Data | Add Activation Patterns | Save Subject Maps | Compute Group Statistics | Advanced: Efficient Access Patterns | Best Practices | 1. Use Meaningful Labels | 2. Organize Your Analysis | 3. Remember to Close | Summary