What grafity does

  • Simple 2D line and scatter plots.
  • Operations on curves (move, scale, derivative/integral, interpolate/extrapolate, smoothing, denoise using wavelets, Fourier transform, add/subtract/multiply with another dataset).
Operations can be individually enabled/disabled, modified and removed.
  • Nonlinear curve fitting:
    • Fit with a sum of terms which can be independently added and enabled/disabled.
    • Easily fit multiple curves sharing fit parameters.
    • ODR (orthogonal distance regression) for data with both X and Y uncertainties.
    • Parameter dependencies, to identify redundant parameters.
    • Easy graphical setting of initial values by dragging the fit curves.
  • Additional analysis tools such as: find peaks, analyze peak, analyze step (e.g. glass transition), find onset point.

  • Do calculations and define fit functions using Python. All the functions in NumPy are available.

  • Unlimited undo/redo of all operations.

  • Cross-platform: runs on Windows, Mac OS X and Linux.

Dielectric Spectroscopy

Grafity has some features that are useful for fitting dielectric spectroscopy data:

  • Built-in fit functions for DRS such as: Havriliak-Negami (various forms), KWW in freq. domain, Rouse model, VTF, Arrhenius.
  • Easily fit real and imaginary part of dielectric permittivity simultaneously.
  • Fast and accurate KWW function in the frequency domain (based on code from LEVMW).
  • On-the-fly transform from time to frequency domain (based on F.I. Mopsik, J. Res. NIST, 104, 189 (1999)). This allows directly fitting frequency domain data with functions defined in the time domain (e.g. “Williams ansatz”) without needing to transform your data.

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