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Provides useful functions for signal processing such as Fast Fourier Transform, windowing (apodization), variance/standard deviation and others.

Smart Signal Processing #

What the package can do for you #

This package provides frequently used functions for signal processing:

  • Computes mean values, variance, standard deviation.
  • Applies windowing (apodization functions) with exponential or Gaussian shapes to an array
  • Applies the Fast Fourier Transform to an array.
  • Calculates the power or magnitude of a complex-valued array.
  • Phase-shifts (rotates in the complex plane) a complex-valued array.

The major API functionalities #

  • classes Sigma, BaseLine, WinFunc,FFT, Phase.

Examples:

  • Multiplication with an exponential:

    WinFunc.expMult(array, decayFactor, false, "0");

  • Compute Fourier Transform:

    FFT.transform(reals, imags);

  • Compute magnitude:

    Phase.magnitude(reals, imags, true)

  • Compute variance in a region:
    Sigma.variance(array, ixstart, ixend)

Detailed API

Please view the detailed API documentation in the API reference of this package (sidebar at the right of this page).

smart_arrays_base: Basic functions for 1D and 2D arrays

smart_arrays_numerics: Numerics with 1D and 2D arrays

smart_arrays_compress: Compress 1D and 2D arrays to a smaller size.

smart_arrays_dbstore: Store 1D and 2D arrays along with metadata on the local device.

smart_arrays_peaks: Detect peaks in 1D and 2D arrays.

smart_arrays_lmfit: Fits (x, y) data given as arrays to a specified model function using the Levenberg-Marquardt algorithm.

smart_lorentz-gauss: Compute Lorentz-Gauss (pseudo-Voigt) line shapes.

smart_dialogs: Easy-to-use dialogs in Web applications

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Publisher

verified publisherhiveright.tech

Provides useful functions for signal processing such as Fast Fourier Transform, windowing (apodization), variance/standard deviation and others.

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License

unknown (license)

Dependencies

build_runner, build_web_compilers, pedantic, smart_arrays_base

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