Closed hubmayr closed 3 years ago
chi-square only tells you that the data deviates from the model. So it will be indistinguishable from the other common errors, like the poor-fits of double resonators. Further, chi-squared is guaranteed to trace linearly with the yet-unquantified v-phi weirdness. I would suggest using principle component analysis, Subtract the model from the data, look at what remains. From this a classification system could be developed, the v-phi weirdness will look like a wave packet, fit the wave packet, use the amplitude of the wave packet as a fair descriptor of the amount v-phi weirdness.
Perhaps you should open a new issues request and simply request a chi-squared. This larger issue will take longer and is probably the subject for research paper.
chi square has been implemented. Contest have been added by also plotting the lambda fits residuals on the rug plot frame.
Report a metric that quantifies if a flux-response has the sharp peaks in the v-phi response. Suggest reporting the chi-squared of lambda fit.