Tutorials

The tutorials’ goal is to show the general usage of DISSTANS, fully using synthetic data. Building on this knowledge, the Examples then show how to use real data with DISSTANS.

Tutorials

• Tutorial 1: The first synthetic station
  • Building a Model collection
  • Creating Timeseries objects
  • Fitting the models
  • Plotting the fit and residuals
• Tutorial 2: Advanced Models and Fitting
  • Creating more complex synthetic data
  • Spline models for transients
  • Building a Network
  • Fitting an entire network
  • Advanced plotting
  • Repeat with L2 regularization
  • Repeat with L1 regularization
  • Repeat with L0 regularization
  • Comparing specific parameters
• Tutorial 3: Incorporating Spatial Coherence
  • Preparations
  • Dreaming up a network
  • Fantasizing data
  • Removing the Common Mode Error
  • Fitting the data using reweighted L1 regularization
  • Fitting the data using a spatially-aware L1 reweighting
  • Finding unmodeled jumps
  • Statistics of spatial reweighting
  • Model parameter correlations
  • Transient visualization with worm plots
  • Secular velocity comparisons
• Tutorial 4: The use and estimation of covariance
  • Making a noisy network
  • Fitting the models with the spatial L0 solver
  • Quality of the fits
  • Correlation of parameters
  • Simple linear regression with restricted spline set
  • Empirical covariance estimation
• Tutorial 5: Signal Recovery at Low SNR
  • Preparations
  • Defining the variables and hyperparameter space
  • Running test cases
  • Results
• Tutorial 6: Spatially-variable Strain Field
  • Preparations
  • Average strain and rotation
  • Spatially-variable velocity, strain, and rotation