Data.md•3.94 kB
---
title: Data Processing & Signal Analysis Tool
kind: reference
header_svg:
src: "/assets/svg/tool-data-hero.svg"
static: "/assets/svg/tool-data-hero-static.svg"
title: "Data Processing & Signal Analysis Tool"
animate: true
theme_variant: "auto"
reduced_motion: "auto"
---
{% assign header_svg = page.header_svg %}
{% include header-svg.html %}
# Data Processing & Signal Analysis Tool
The Data Processing tool provides comprehensive capabilities for importing, analyzing, and processing scientific data from various formats. It includes advanced signal processing capabilities with GPU acceleration.
## Core Capabilities
### Data Import/Export
- **HDF5**: Hierarchical data format for large datasets
- **FITS**: Astronomy data format
- **ROOT**: High-energy physics data format
- **CSV/JSON**: Standard tabular data formats
### Signal Processing
- **FFT Analysis**: Fast Fourier transforms with windowing
- **Filtering**: Low-pass, high-pass, band-pass, band-stop filters
- **Spectrograms**: Time-frequency analysis
- **Wavelets**: Advanced time-frequency decomposition
## Usage Examples
### Import HDF5 Data
```json
{
"tool": "data",
"params": {
"action": "import_hdf5",
"file_path": "/path/to/data.h5",
"dataset_path": "/experiment/measurements"
}
}
```
### FFT Analysis
```json
{
"tool": "data",
"params": {
"action": "fft",
"signal_data": [1, 2, 3, 4, 5, 6, 7, 8],
"sample_rate": 1000,
"window": "hann"
}
}
```
### Signal Filtering
```json
{
"tool": "data",
"params": {
"action": "filter",
"signal_data": [/* array of data points */],
"filter_type": "lowpass",
"cutoff_freq": 50,
"sample_rate": 1000,
"filter_order": 4
}
}
```
### Spectrogram Generation
```json
{
"tool": "data",
"params": {
"action": "spectrogram",
"signal_data": [/* time series data */],
"sample_rate": 44100,
"window_size": 1024,
"overlap": 0.5
}
}
```
## Advanced Features
### GPU Acceleration
- Automatic GPU detection and utilization
- CUDA/HIP/MPS support for different platforms
- Memory-efficient processing for large datasets
- Automatic fallback to CPU when GPU unavailable
### Window Functions
- **Hann**: Good frequency resolution
- **Hamming**: Reduced sidelobe leakage
- **Blackman**: Excellent sidelobe suppression
- **Bartlett**: Triangular window
- **None**: Rectangular window
### Filter Types
- **Low-pass**: Remove high-frequency noise
- **High-pass**: Remove low-frequency drift
- **Band-pass**: Isolate specific frequency range
- **Band-stop**: Remove specific frequency range
## Educational Applications
### Physics Laboratory Data
- Analyze pendulum period measurements
- Process voltage/current data from circuits
- Extract resonance frequencies from oscillating systems
- Filter noise from experimental measurements
### Signal Analysis Examples
- **Chirp Signal**: Analyze frequency-swept signals
- **Pulse Analysis**: Extract pulse characteristics
- **Noise Characterization**: Analyze background noise
- **Modulation Detection**: Identify AM/FM signals
## Integration with Other Tools
### Plot Integration
```json
{
"tool": "plot",
"params": {
"plot_type": "function_2d",
"f": "sin(2*pi*50*t) + 0.1*sin(2*pi*120*t)",
"x_min": 0,
"x_max": 1
}
}
```
### CAS Integration
```json
{
"tool": "cas",
"params": {
"expr": "fft_result",
"vars": {"fft_result": /* from data tool output */}
}
}
```
## Performance Considerations
- **Large Datasets**: Automatic chunking for files >1GB
- **Memory Management**: Efficient buffer handling
- **GPU Utilization**: Automatic batch size optimization
- **Caching**: Results cached for repeated operations
## Error Handling
- **File Format Validation**: Automatic format detection
- **Data Type Checking**: Ensures compatible data types
- **Memory Limits**: Prevents system overload
- **GPU Fallback**: Graceful degradation to CPU processing