pastas_plugins

Contents:

  • Plugins
    • Cross-correlation
      • Example
      • API
        • plot_ccf_overview
        • plot_corr
    • Modflow
      • Example
      • API
    • Reservoirs
      • Example
      • API
        • Reservoir1
        • Reservoir2
        • ReservoirBase
        • ReservoirModel
    • Responses
      • Example
      • API
        • Edelman
        • Theis
    • PEST
      • Example
      • API
  • Examples
    • Response function plugin for Pastas
      • The Theis response function
      • The Edelman response function
    • Response function parameters
      • 0. Aquifer parameters
      • 1. Kraijenhoff van de Leur Parameters
      • 2. Exponential Parameters
      • 3. Hantush Parameters
      • 4. Theis Parameters
    • Using a Modflow model as a stressmodel in Pastas
      • Packages
      • Download MODFLOW executable
      • Data
      • Time series models
        • Standard exponential model
        • Uncalibrated MODFLOW time series model
      • Calibrated MODFLOW time series model
      • Results
        • Parameters
        • Plots
    • Using a Modflow UZF model as a stressmodel in Pastas
      • Data Groundwater Article
        • Standard exponential model
      • FLEX model
        • UZF model
        • UZF model calibrated
        • Compare
      • Synthetic data
        • UZF model with parameters we “know” from USG
        • UZF model calibrated
    • Using a Modflow DRN model as a stressmodel in Pastas
      • Try to model TARSO with a one cell MODFLOW model
      • Try to model ThresholdTransform with a one cell MODFLOW model
    • Benchmark Problem Series J
      • Packages
      • Dataset
      • Cross correlation and autocorrelation
      • Prewhitening
      • Impulse response function
      • Cross-correlation overview plot
    • Linear Regression with PEST++ GLM
      • Packages
      • Create data
      • Scipy Linear Regression
      • Pest Linear Regression
        • Define run function
        • Setup PEST++ GLM files with Pyemu
      • Compare result
    • Linear Regression with PEST++ iES
      • Setup
        • Packages
        • Linear regression model
        • Linear regression solver
        • PEST++ iES PostProcessor
      • Case 1: no noise on observations
        • Solve model
        • Results
      • Case 2: noise on observations
        • Solve model
        • Results
      • Case 3: noise on observations but not on iES realizations
        • Solve model
        • Results
    • Test notebook for Pastas with PEST++ GLM and PEST HP Solver
      • Packages
      • Load Data
      • Create Model
        • Solve with Pest GLM
        • Solve with Pest HP
        • Solve with SciPy Least Squares
      • Compare Results
        • Plot
        • Fit metrics
        • Parameters (and stderr)
        • Covariance matrices
    • Test notebook for Pastas with PEST++ iES Solver
      • Packages
      • Load Data
      • Create Model
      • Solve with SciPy Least Squares
      • Pest-IES
      • Compare
    • Test notebook for Pastas parameter sensitivity analysis with PEST++ SEN Solver
    • Randomized Maximum Likelihood Solver
      • Setup
        • Packages
        • Data
        • Helper functions
        • Constants
        • Create a synthetic head series
      • Models
        • Least Squares
        • RML with finite difference jacobian
        • RML with empirical jacobian
      • Compare CI
    • Response functions
    • Modflow StressModel
    • Cross-Correlation
    • PEST Solver
    • Randomized Maximum Likelihood
  • Developers
    • How do I create my own plugin for Pastas?
    • Requirements
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