Tutorial

Stub for tutorials. Add Jupyter notebooks here

Dataelab

• Data Analysis Framework (dataelab) Tutorial
  • Overview
  • 1. Import Required Libraries
  • 2. Generate Synthetic Time Series Data
  • 3. Save Data to FITS File
  • 4. Define Custom FileWalker and Analyzer
  • 5. Initialize the Analyzer and Load Data
  • 6. Time-Domain Statistics
  • 7. Ensemble Statistics
  • 8. Power Spectral Density Analysis
  • 9. Visualize Time Series Data
  • 10. Time Filtering
  • Summary
    • Key Concepts
    • Next Steps

Atmo

• Von Karman turbulence spectrum
  • Total phase variance for Kolmogorov spectrum
  • Kolmogorov and Von Karman spectra
• Von Karman spatio-temporal covariance
  • Spatial frequencies’ sampling for the CPSD
  • Test against alternative code
  • Test the comparison between covariance and integrated CPSD
  • Zernike correlation and residuals as a function of off-axis guide star angular distance
  • Cutoff frequency of Zernike CPSD using one source at infinity and one aperture
  • Slope of Zernike CPSD at high temporal frequencies
  • Slope of Zernike CPSD at low temporal frequencies

Utils

• Bidimensional Fourier Transform
  • Direct transform of 2D functions
  • Inverse Transform
  • Normalization
  • Non centered domain
  • Direct transform on rectangular, unevenly spaced domain
  • Units
  • Transform of numpy array

Time Series

• TimeSeries Fluent API Examples
  • Overview
  • Creating a Concrete TimeSeries Implementation
  • Creating Sample Data
  • Basic Chainable Operations
    • Ensemble Operations
    • Time Operations
  • Chaining Operations
  • Using .value to Extract Final Results
  • Filtering with filter()
  • Visualization Example
  • Multiple Statistical Operations
  • Available Chainable Properties
    • Ensemble Operations (reduce across spatial dimension):
    • Time Operations (reduce across temporal dimension):
    • Other Operations:
  • Migration from Legacy API
  • Summary