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Provide functionality of interpolating real and imaginary parts and calculate the tridiagonal covariance matrix all at once #112

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BjoernLudwigPTB opened this issue Apr 27, 2020 · 1 comment
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@BjoernLudwigPTB
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For some cases of complex interpolations we need this functionality to avoid (unwanted or unthought-of) side effects of zero padding or similar methods. As a first step we prepare now for leaving the covariance calculation to the user by providing the sensitivity coefficients (see #111), but we could as well go the full distance and provide the covariance matrix as well.

In this case we might have to reformulate the uncertainty equations to take care of the correlation between timestamps and real and imaginary parts. We could tackle that by writing the according linear equations in (block) matrix form.

@BjoernLudwigPTB BjoernLudwigPTB added this to To do in PyDynamic Roadmap via automation Apr 28, 2020
@BjoernLudwigPTB BjoernLudwigPTB self-assigned this Apr 28, 2020
@BjoernLudwigPTB
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@eichstaedtPTB Your suggestion was tackle this by wrapping the according calls of interp1d_unc() in propagateDFT() where this will be needed, right?

@BjoernLudwigPTB BjoernLudwigPTB changed the title Provide functionality of interpolation real and imaginary parts and calculate the tridiagonal covariance matrix all at once Provide functionality of interpolating real and imaginary parts and calculate the tridiagonal covariance matrix all at once Jun 23, 2020
@BjoernLudwigPTB BjoernLudwigPTB removed this from To do in PyDynamic Roadmap Jun 23, 2020
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