API and modules

The dyson_equalizer package provides a class functions implementing the algorithms needed to compute the Dyson Equalizer [1] and related auxiliary functions.

The functions may be used to build specialized implementation of the Dyson Equalizer.

Examples

See Examples

References

[1]

Landa B., Kluger Y., “The Dyson Equalizer: Adaptive Noise Stabilization for Low-Rank Signal Detection and Recovery,” arXiv, https://arxiv.org/abs/2306.11263

Submodules

• dyson_equalizer.algorithm module
  • compute_low_rank_approximation_mp()
  • compute_scaling_factors()
  • marchenko_pastur()
  • marchenko_pastur_cdf()
  • scale_matrix()
• dyson_equalizer.dyson_equalizer module
  • DysonEqualizer
    • DysonEqualizer.S
    • DysonEqualizer.S_hat
    • DysonEqualizer.X_bar
    • DysonEqualizer.Y
    • DysonEqualizer.Y_hat
    • DysonEqualizer.compute()
    • DysonEqualizer.compute_iteratively()
    • DysonEqualizer.iteration_statistics
    • DysonEqualizer.ks_Y()
    • DysonEqualizer.ks_Y_hat()
    • DysonEqualizer.ks_pvalue_Y()
    • DysonEqualizer.ks_pvalue_Y_hat()
    • DysonEqualizer.plot_mp_density_Y()
    • DysonEqualizer.plot_mp_density_Y_hat()
    • DysonEqualizer.plot_mp_eigenvalues_Y()
    • DysonEqualizer.plot_mp_eigenvalues_Y_hat()
    • DysonEqualizer.plot_mp_eigenvalues_and_densities()
    • DysonEqualizer.r_hat
    • DysonEqualizer.x_hat
    • DysonEqualizer.y_hat
  • IterationStatistics
    • IterationStatistics.delta_Y_hat
    • IterationStatistics.ks_pvalue
    • IterationStatistics.kstest_result
    • IterationStatistics.x_hat_mean
    • IterationStatistics.y_hat_mean
• dyson_equalizer.examples module
  • generate_X()
  • generate_Y_with_almost_homoskedastic_noise()
  • generate_Y_with_heteroskedastic_noise()
• dyson_equalizer.plots module
  • plot_mp_density()
  • plot_mp_eigenvalues()
• dyson_equalizer.validation module
  • validate_matrix()
  • validate_svd()