savepoint
This commit is contained in:
parent
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@ -202,3 +202,37 @@
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url = {http://graphics.uni-bielefeld.de/publications/disclaimer.php?dlurl=vmv15.pdf},
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ISBN = {978-3-905674-95-8},
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}
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@article{hauke2011comparison,
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title={Comparison of values of Pearson's and Spearman's correlation coefficients on the same sets of data},
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author={Hauke, Jan and Kossowski, Tomasz},
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journal={Quaestiones geographicae},
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volume={30},
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number={2},
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pages={87},
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year={2011},
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publisher={De Gruyter Open Sp. z oo},
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url={https://www.degruyter.com/downloadpdf/j/quageo.2011.30.issue-2/v10117-011-0021-1/v10117-011-0021-1.pdf},
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}
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@article{weir2015spearman,
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title={Spearman’s correlation},
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author={Weir, I},
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journal={Retrieved from statstutor},
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year={2015},
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url={http://www.statstutor.ac.uk/resources/uploaded/spearmans.pdf},
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}
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@Article{shark08,
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author = {Christian Igel and Verena Heidrich-Meisner and Tobias Glasmachers},
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title = {Shark},
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journal = {Journal of Machine Learning Research},
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year = {2008},
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volume = {9},
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pages = {993-996},
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url={http://image.diku.dk/shark/index.html},
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}
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@article{hansen2016cma,
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title={The CMA evolution strategy: A tutorial},
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author={Hansen, Nikolaus},
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journal={arXiv preprint arXiv:1604.00772},
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year={2016},
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url={https://arxiv.org/abs/1604.00772}
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}
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155
arbeit/ma.md
155
arbeit/ma.md
@ -660,6 +660,7 @@ can compute the analytic solution $\vec{p^{*}} = \vec{U^+}\vec{t}$, yielding us
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the correct gradient in which the evolutionary optimizer should move.
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## Procedure: 1D Function Approximation
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\label{sec:proc:1d}
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For our setup we first compute the coefficients of the deformation--matrix and
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use then the formulas for *variability* and *regularity* to get our predictions.
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@ -696,6 +697,7 @@ dimension and shrink the distance to the neighbours (the smaller neighbour for
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$r < 0$, the larger for $r > 0$) by the factor $r$^[Note: On the Edges this
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displacement is only applied outwards by flipping the sign of $r$, if
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appropriate.].
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\improvement[inline]{update!! gaussian, not uniform!!}
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An Example of such a testcase can be seen for a $7 \times 4$--grid in figure
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\ref{fig:example1d_grid}.
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@ -806,20 +808,148 @@ control-points.
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# Evaluation of Scenarios
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\label{sec:res}
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## Spearman/Pearson--Metriken
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To compare our results to the ones given by Richter et al.\cite{anrichterEvol},
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we also use Spearman's rank correlation coefficient. Opposed to other popular
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coefficients, like the Pearson correlation coefficient, which measures a linear
|
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relationship between variables, the Spearmans's coefficient assesses \glqq how
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well an arbitrary monotonic function can descripbe the relationship between two
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variables, without making any assumptions about the frequency distribution of
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the variables\grqq\cite{hauke2011comparison}.
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- Was ist das?
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- Wieso sollte uns das interessieren?
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- Wieso reicht Monotonie?
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- Haben wir das gezeigt?
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- Statistik, Bilder, blah!
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As we don't have any prior knowledge if any of the criteria is linear and we are
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just interested in a monotonic relation between the criteria and their
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predictive power, the Spearman's coefficient seems to fit out scenario best.
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For interpretation of these values we follow the same interpretation used in
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\cite{anrichterEvol}, based on \cite{weir2015spearman}: The coefficient
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intervals $r_S \in [0,0.2[$, $[0.2,0.4[$, $[0.4,0.6[$, $[0.6,0.8[$, and $[0.8,1]$ are
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classified as *very weak*, *weak*, *moderate*, *strong* and *very strong*. We
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interpret p--values smaller than $0.1$ as *significant* and cut off the
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precision of p--values after four decimal digits (thus often having a p--value
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of $0$ given for p--values $< 10^{-4}$).
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As we are looking for anti--correlation (i.e. our criterion should be maximized
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indicating a minimal result in --- for example --- the reconstruction--error)
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instead of correlation we flip the sign of the correlation--coefficient for
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readability and to have the correlation--coefficients be in the
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classification--range given above.
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For the evolutionary optimization we employ the CMA--ES (covariance matrix
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adaptation evolution strategy) of the shark3.1 library \cite{shark08}, as this
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algorithm was used by \cite{anrichterEvol} as well. We leave the parameters at
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their sensible defaults as further explained in
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\cite[Appendix~A: Table~1]{hansen2016cma}.
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## Results of 1D Function Approximation
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\begin{figure}[!ht]
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\includegraphics[width=\textwidth]{img/evolution1d/20171005-all_appended.png}
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\caption{Results 1D}
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In the case of our 1D--Optimization--problem, we have the luxury of knowing the
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analytical solution to the given problem--set. We use this to experimentally
|
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evaluate the quality criteria we introduced before. As an evolutional
|
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optimization is partially a random process, we use the analytical solution as a
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stopping-criteria. We measure the convergence speed as number of iterations the
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evolutional algorithm needed to get within $1.05\%$ of the optimal solution.
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We used different regular grids that we manipulated as explained in Section
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\ref{sec:proc:1d} with a different number of control points. As our grids have
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to be the product of two integers, we compared a $5 \times 5$--grid with $25$
|
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control--points to a $4 \times 7$ and $7 \times 4$--grid with $28$
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control--points. This was done to measure the impact an \glqq improper\grqq
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setup could have and how well this is displayed in the criteria we are
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examining.
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Additionally we also measured the effect of increasing the total resolution of
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the grid by taking a closer look at $5 \times 5$, $7 \times 7$ and $10 \times 10$ grids.
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\begin{figure}[ht]
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\centering
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\includegraphics[width=0.7\textwidth]{img/evolution1d/variability_boxplot.png}
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\caption[1D Fitting Errors for various grids]{The squared error for the various
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grids we examined.\newline
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Note that $7 \times 4$ and $4 \times 7$ have the same number of control--points.}
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\label{fig:1dvar}
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\end{figure}
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### Variability
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Variability should characterize the potential for design space exploration and
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is defined in terms of the normalized rank of the deformation matrix $\vec{U}$:
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$V(\vec{U}) := \frac{\textrm{rank}(\vec{U})}{n}$, whereby $n$ is the number of
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vertices.
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As all our tested matrices had a constant rank (being $m = x \cdot y$ for a $x \times y$
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grid), we have merely plotted the errors in the boxplot in figure
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\ref{fig:1dvar}
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It is also noticeable, that although the $7 \times 4$ and $4 \times 7$ grids
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have a higher variability, they perform not better than the $5 \times 5$ grid.
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Also the $7 \times 4$ and $4 \times 7$ grids differ distinctly from each other,
|
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although they have the same number of control--points. This is an indication the
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impact a proper or improper grid--setup can have. We do not draw scientific
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conclusions from these findings, as more research on non-squared grids seem
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necessary.\todo{machen wir die noch? :D}
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Leaving the issue of the grid--layout aside we focused on grids having the same
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number of prototypes in every dimension. For the $5 \times 5$, $7 \times 7$ and
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$10 \times 10$ grids we found a *very strong* correlation ($-r_S = 0.94, p = 0$)
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between the variability and the evolutionary error.
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### Regularity
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\begin{table}[bht]
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\centering
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\begin{tabular}{c|c|c|c|c}
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$5 \times 5$ & $7 \times 4$ & $4 \times 7$ & $7 \times 7$ & $10 \times 10$\\
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\hline
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$0.28$ ($0.0045$) & \textcolor{red}{$0.21$} ($0.0396$) & \textcolor{red}{$0.1$} ($0.3019$) & \textcolor{red}{$0.01$} ($0.9216$) & \textcolor{red}{$0.01$} ($0.9185$)
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\end{tabular}
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\caption[Correlation 1D Regularity/Steps]{Spearman's correlation (and p-values)
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between regularity and convergence speed for the 1D function approximation
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problem.\newline
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Not significant entries are marked in red.
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}
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\label{tab:1dreg}
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\end{table}
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\begin{figure}[ht]
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\centering
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\includegraphics[width=\textwidth]{img/evolution1d/55_to_1010_steps.png}
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\caption[Improvement potential and regularity vs. steps]{\newline
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Left: Improvement potential against steps until convergence\newline
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Right: Regularity against steps until convergence\newline
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Coloured by their grid--resolution, both with a linear fit over the whole
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dataset.}
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\label{fig:1dreg}
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\end{figure}
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Regularity should correspond to the convergence speed (measured in
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iteration--steps of the evolutionary algorithm), and is computed as inverse
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condition number $\kappa(\vec{U})$ of the deformation--matrix.
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As can be seen from table \ref{tab:1dreg}, we could only show a *weak* correlation
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in the case of a $5 \times 5$ grid. As we increment the number of
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control--points the correlation gets worse until it is completely random in a
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single dataset. Taking all presented datasets into account we even get a *strong*
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correlation of $- r_S = -0.72, p = 0$, that is opposed to our expectations.
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To explain this discrepancy we took a closer look at what caused these high number
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of iterations. In figure \ref{fig:1dreg} we also plotted the
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improvement-potential against the steps next to the regularity--plot. Our theory
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is that the *very strong* correlation ($-r_S = -0.82, p=0$) between
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improvement--potential and number of iterations hints that the employed
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algorithm simply takes longer to converge on a better solution (as seen in
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figure \ref{fig:1dvar} and \ref{fig:1dimp}) offsetting any gain the regularity--measurement could
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achieve.
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### Improvement Potential
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- Alle Spearman 1 und p-value 0.
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\begin{figure}[ht]
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\centering
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\includegraphics[width=0.8\textwidth]{img/evolution1d/55_to_1010_improvement-vs-evo-error.png}
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\caption[Correlation 1D Improvement vs. Error]{Improvement potential plotted
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against the error yielded by the evolutionary optimization for different
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grid--resolutions}
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\label{fig:1dimp}
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\end{figure}
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<!--  -->
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@ -841,6 +971,11 @@ control-points.
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\caption{Results 3D for Xx4x4}
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\end{figure}
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\begin{figure}[!ht]
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\includegraphics[width=\textwidth]{img/evolution3d/YxYxY_montage.png}
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\caption{Results 3D for YxYxY for Y $\in [4,5,6]$}
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\end{figure}
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<!--  -->
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<!-- -->
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<!-- ![Improvement potential vs evolutional -->
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@ -851,7 +986,7 @@ control-points.
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# Schluss
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\label{sec:dis}
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HAHA .. als ob -.-
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- Regularity ist kacke für unser setup. Bessere Vorschläge? EW/EV?
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\improvement[inline]{Bibliotheksverzeichnis links anpassen. DOI überschreibt
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Direktlinks des Autors.}
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BIN
arbeit/ma.pdf
BIN
arbeit/ma.pdf
Binary file not shown.
189
arbeit/ma.tex
189
arbeit/ma.tex
@ -3,7 +3,7 @@
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\documentclass[
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a4paper, % default
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12pt, % default = 11pt
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BCOR6mm, % Bindungskorrektur bei Klebebindung 6mm, bei Lochen BCOR8.25mm
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BCOR10mm, % Bindungskorrektur bei Klebebindung 6mm, bei Lochen BCOR8.25mm
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twoside, % default, 2seitig
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titlepage,
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% pagesize=auto
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@ -31,10 +31,10 @@ xcolor=dvipsnames,
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%%%%%%%%%%%%%%% Globale Einstellungen %%%%%%%%%%%%%%%
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\input{settings/commands}
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\input{settings/environments}
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%\setlength{\parindent}{0pt} % kein einzug bei absaetzen
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%\setlength{\lineskip}{1ex plus0.5ex minus0.5ex} % dafr abstand zwischen abs<62>zen (funktioniert noch nicht)
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\setlength{\parindent}{0pt} % kein einzug bei absaetzen
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\setlength{\parskip}{12pt plus6pt minus2pt} % dafür abstand zwischen absäzen
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% \renewcommand{\familydefault}{\sfdefault}
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\setstretch{1.44} % 1.5-facher zeilenabstand
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\setstretch{1.5} % 1.5-facher zeilenabstand
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%%%%%%%%%%%%%%% Header - Footer %%%%%%%%%%%%%%%
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% ### Fr 2 Seitig (option twopage):
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@ -850,6 +850,8 @@ should move.
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\section{Procedure: 1D Function
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Approximation}\label{procedure-1d-function-approximation}
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\label{sec:proc:1d}
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|
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For our setup we first compute the coefficients of the
|
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deformation--matrix and use then the formulas for \emph{variability} and
|
||||
\emph{regularity} to get our predictions. Afterwards we solve the
|
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@ -886,6 +888,7 @@ neighbours (the smaller neighbour for \(r < 0\), the larger for
|
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\(r > 0\)) by the factor \(r\)\footnote{Note: On the Edges this
|
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displacement is only applied outwards by flipping the sign of \(r\),
|
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if appropriate.}.
|
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\improvement[inline]{update!! gaussian, not uniform!!}
|
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|
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An Example of such a testcase can be seen for a \(7 \times 4\)--grid in
|
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figure \ref{fig:example1d_grid}.
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@ -1004,29 +1007,162 @@ predict a suboptimal placement of these control-points.
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\label{sec:res}
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\section{Spearman/Pearson--Metriken}\label{spearmanpearsonmetriken}
|
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To compare our results to the ones given by Richter et
|
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al.\cite{anrichterEvol}, we also use Spearman's rank correlation
|
||||
coefficient. Opposed to other popular coefficients, like the Pearson
|
||||
correlation coefficient, which measures a linear relationship between
|
||||
variables, the Spearmans's coefficient assesses \glqq how well an
|
||||
arbitrary monotonic function can descripbe the relationship between two
|
||||
variables, without making any assumptions about the frequency
|
||||
distribution of the variables\grqq\cite{hauke2011comparison}.
|
||||
|
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\begin{itemize}
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\tightlist
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\item
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Was ist das?
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\item
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Wieso sollte uns das interessieren?
|
||||
\item
|
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Wieso reicht Monotonie?
|
||||
\item
|
||||
Haben wir das gezeigt?
|
||||
\item
|
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Statistik, Bilder, blah!
|
||||
\end{itemize}
|
||||
As we don't have any prior knowledge if any of the criteria is linear
|
||||
and we are just interested in a monotonic relation between the criteria
|
||||
and their predictive power, the Spearman's coefficient seems to fit out
|
||||
scenario best.
|
||||
|
||||
For interpretation of these values we follow the same interpretation
|
||||
used in \cite{anrichterEvol}, based on \cite{weir2015spearman}: The
|
||||
coefficient intervals \(r_S \in [0,0.2[\), \([0.2,0.4[\), \([0.4,0.6[\),
|
||||
\([0.6,0.8[\), and \([0.8,1]\) are classified as \emph{very weak},
|
||||
\emph{weak}, \emph{moderate}, \emph{strong} and \emph{very strong}. We
|
||||
interpret p--values smaller than \(0.1\) as \emph{significant} and cut
|
||||
off the precision of p--values after four decimal digits (thus often
|
||||
having a p--value of \(0\) given for p--values \(< 10^{-4}\)).
|
||||
|
||||
As we are looking for anti--correlation (i.e.~our criterion should be
|
||||
maximized indicating a minimal result in --- for example --- the
|
||||
reconstruction--error) instead of correlation we flip the sign of the
|
||||
correlation--coefficient for readability and to have the
|
||||
correlation--coefficients be in the classification--range given above.
|
||||
|
||||
For the evolutionary optimization we employ the CMA--ES (covariance
|
||||
matrix adaptation evolution strategy) of the shark3.1 library
|
||||
\cite{shark08}, as this algorithm was used by \cite{anrichterEvol} as
|
||||
well. We leave the parameters at their sensible defaults as further
|
||||
explained in \cite[Appendix~A: Table~1]{hansen2016cma}.
|
||||
|
||||
\section{Results of 1D Function
|
||||
Approximation}\label{results-of-1d-function-approximation}
|
||||
|
||||
\begin{figure}[!ht]
|
||||
\includegraphics[width=\textwidth]{img/evolution1d/20171005-all_appended.png}
|
||||
\caption{Results 1D}
|
||||
In the case of our 1D--Optimization--problem, we have the luxury of
|
||||
knowing the analytical solution to the given problem--set. We use this
|
||||
to experimentally evaluate the quality criteria we introduced before. As
|
||||
an evolutional optimization is partially a random process, we use the
|
||||
analytical solution as a stopping-criteria. We measure the convergence
|
||||
speed as number of iterations the evolutional algorithm needed to get
|
||||
within \(1.05\%\) of the optimal solution.
|
||||
|
||||
We used different regular grids that we manipulated as explained in
|
||||
Section \ref{sec:proc:1d} with a different number of control points. As
|
||||
our grids have to be the product of two integers, we compared a
|
||||
\(5 \times 5\)--grid with \(25\) control--points to a \(4 \times 7\) and
|
||||
\(7 \times 4\)--grid with \(28\) control--points. This was done to
|
||||
measure the impact an \glqq improper\grqq
|
||||
setup could have and how well this is displayed in the criteria we are
|
||||
examining.
|
||||
|
||||
Additionally we also measured the effect of increasing the total
|
||||
resolution of the grid by taking a closer look at \(5 \times 5\),
|
||||
\(7 \times 7\) and \(10 \times 10\) grids.
|
||||
|
||||
\begin{figure}[ht]
|
||||
\centering
|
||||
\includegraphics[width=0.7\textwidth]{img/evolution1d/variability_boxplot.png}
|
||||
\caption[1D Fitting Errors for various grids]{The squared error for the various
|
||||
grids we examined.\newline
|
||||
Note that $7 \times 4$ and $4 \times 7$ have the same number of control--points.}
|
||||
\label{fig:1dfiterr}
|
||||
\end{figure}
|
||||
|
||||
\subsection{Variability}\label{variability-1}
|
||||
|
||||
Variability should characterize the potential for design space
|
||||
exploration and is defined in terms of the normalized rank of the
|
||||
deformation matrix \(\vec{U}\):
|
||||
\(V(\vec{U}) := \frac{\textrm{rank}(\vec{U})}{n}\), whereby \(n\) is the
|
||||
number of vertices. As all our tested matrices had a constant rank
|
||||
(being \(m = x \cdot y\) for a \(x \times y\) grid), we have merely
|
||||
plotted the errors in the boxplot in figure \ref{fig:1dfiterr}
|
||||
|
||||
It is also noticeable, that although the \(7 \times 4\) and
|
||||
\(4 \times 7\) grids have a higher variability, they perform not better
|
||||
than the \(5 \times 5\) grid. Also the \(7 \times 4\) and \(4 \times 7\)
|
||||
grids differ distinctly from each other, although they have the same
|
||||
number of control--points. This is an indication the impact a proper or
|
||||
improper grid--setup can have. We do not draw scientific conclusions
|
||||
from these findings, as more research on non-squared grids seem
|
||||
necessary.\todo{machen wir die noch? :D}
|
||||
|
||||
Leaving the issue of the grid--layout aside we focused on grids having
|
||||
the same number of prototypes in every dimension. For the
|
||||
\(5 \times 5\), \(7 \times 7\) and \(10 \times 10\) grids we found a
|
||||
\emph{very strong} correlation (\(-r_S = 0.94, p = 0\)) between the
|
||||
variability and the evolutionary error.
|
||||
|
||||
\subsection{Regularity}\label{regularity-1}
|
||||
|
||||
\begin{table}[bht]
|
||||
\centering
|
||||
\begin{tabular}{c|c|c|c|c}
|
||||
$5 \times 5$ & $7 \times 4$ & $4 \times 7$ & $7 \times 7$ & $10 \times 10$\\
|
||||
\hline
|
||||
$0.28$ ($0.0045$) & \textcolor{red}{$0.21$} ($0.0396$) & \textcolor{red}{$0.1$} ($0.3019$) & \textcolor{red}{$0.01$} ($0.9216$) & \textcolor{red}{$0.01$} ($0.9185$)
|
||||
\end{tabular}
|
||||
\caption[Correlation 1D Regularity/Steps]{Spearman's correlation (and p-values)
|
||||
between regularity and convergence speed for the 1D function approximation
|
||||
problem.\newline
|
||||
Not significant entries are marked in red.
|
||||
}
|
||||
\label{tab:1dreg}
|
||||
\end{table}
|
||||
|
||||
\begin{figure}[ht]
|
||||
\centering
|
||||
\includegraphics[width=\textwidth]{img/evolution1d/55_to_1010_steps.png}
|
||||
\caption[Improvement potential and regularity vs. steps]{\newline
|
||||
Left: Improvement potential against steps until convergence\newline
|
||||
Right: Regularity against steps until convergence\newline
|
||||
Coloured by their grid--resolution, both with a linear fit over the whole
|
||||
dataset.}
|
||||
\label{fig:1dreg}
|
||||
\end{figure}
|
||||
|
||||
Regularity should correspond to the convergence speed (measured in
|
||||
iteration--steps of the evolutionary algorithm), and is computed as
|
||||
inverse condition number \(\kappa(\vec{U})\) of the deformation--matrix.
|
||||
|
||||
As can be seen from table \ref{tab:1dreg}, we could only show a
|
||||
\emph{weak} correlation in the case of a \(5 \times 5\) grid. As we
|
||||
increment the number of control--points the correlation gets worse until
|
||||
it is completely random in a single dataset. Taking all presented
|
||||
datasets into account we even get a \emph{strong} correlation of
|
||||
\(- r_S = -0.72, p = 0\), that is opposed to our expectations.
|
||||
|
||||
To explain this discrepancy we took a closer look at what caused these
|
||||
high number of iterations. In figure \ref{fig:1dreg} we also plotted the
|
||||
improvement-potential against the steps next to the regularity--plot.
|
||||
Our theory is that the \emph{very strong} correlation
|
||||
(\(-r_S = -0.82, p=0\)) between improvement--potential and number of
|
||||
iterations hints that the employed algorithm simply takes longer to
|
||||
converge on a better solution (as seen in figure \ref{fig:1dimp})
|
||||
offsetting any gain the regularity--measurement could achieve.
|
||||
|
||||
\subsection{Improvement Potential}\label{improvement-potential-1}
|
||||
|
||||
\begin{itemize}
|
||||
\tightlist
|
||||
\item
|
||||
Alle Spearman 1 und p-value 0.
|
||||
\end{itemize}
|
||||
|
||||
\begin{figure}[ht]
|
||||
\centering
|
||||
\includegraphics[width=0.8\textwidth]{img/evolution1d/55_to_1010_improvement-vs-evo-error.png}
|
||||
\caption[Correlation 1D Improvement vs. Error]{Improvement potential plotted
|
||||
against the error yielded by the evolutionary optimization for different
|
||||
grid--resolutions}
|
||||
\label{fig:1dimp}
|
||||
\end{figure}
|
||||
|
||||
\section{Results of 3D Function
|
||||
@ -1042,11 +1178,20 @@ Approximation}\label{results-of-3d-function-approximation}
|
||||
\caption{Results 3D for Xx4x4}
|
||||
\end{figure}
|
||||
|
||||
\begin{figure}[!ht]
|
||||
\includegraphics[width=\textwidth]{img/evolution3d/YxYxY_montage.png}
|
||||
\caption{Results 3D for YxYxY for Y $\in [4,5,6]$}
|
||||
\end{figure}
|
||||
|
||||
\chapter{Schluss}\label{schluss}
|
||||
|
||||
\label{sec:dis}
|
||||
|
||||
HAHA .. als ob -.-
|
||||
\begin{itemize}
|
||||
\tightlist
|
||||
\item
|
||||
Regularity ist kacke für unser setup. Bessere Vorschläge? EW/EV?
|
||||
\end{itemize}
|
||||
|
||||
\improvement[inline]{Bibliotheksverzeichnis links anpassen. DOI überschreibt
|
||||
Direktlinks des Autors.}
|
||||
|
||||
@ -3,7 +3,7 @@
|
||||
\documentclass[
|
||||
a4paper, % default
|
||||
$if(fontsize)$$fontsize$,$endif$ % default = 11pt
|
||||
BCOR6mm, % Bindungskorrektur bei Klebebindung 6mm, bei Lochen BCOR8.25mm
|
||||
BCOR10mm, % Bindungskorrektur bei Klebebindung 6mm, bei Lochen BCOR8.25mm
|
||||
twoside, % default, 2seitig
|
||||
titlepage,
|
||||
% pagesize=auto
|
||||
@ -31,10 +31,10 @@ xcolor=dvipsnames,
|
||||
%%%%%%%%%%%%%%% Globale Einstellungen %%%%%%%%%%%%%%%
|
||||
\input{settings/commands}
|
||||
\input{settings/environments}
|
||||
%\setlength{\parindent}{0pt} % kein einzug bei absaetzen
|
||||
%\setlength{\lineskip}{1ex plus0.5ex minus0.5ex} % dafr abstand zwischen abs<62>zen (funktioniert noch nicht)
|
||||
\setlength{\parindent}{0pt} % kein einzug bei absaetzen
|
||||
\setlength{\parskip}{12pt plus6pt minus2pt} % dafür abstand zwischen absäzen
|
||||
% \renewcommand{\familydefault}{\sfdefault}
|
||||
\setstretch{1.44} % 1.5-facher zeilenabstand
|
||||
\setstretch{1.5} % 1.5-facher zeilenabstand
|
||||
|
||||
%%%%%%%%%%%%%%% Header - Footer %%%%%%%%%%%%%%%
|
||||
% ### Fr 2 Seitig (option twopage):
|
||||
|
||||
@ -0,0 +1,101 @@
|
||||
"Evolution error"
|
||||
207.886
|
||||
245.873
|
||||
209.253
|
||||
236.693
|
||||
237.512
|
||||
217.347
|
||||
206.725
|
||||
218.216
|
||||
208.831
|
||||
199.805
|
||||
195.163
|
||||
193.258
|
||||
181.901
|
||||
183.091
|
||||
215.233
|
||||
210.992
|
||||
226.197
|
||||
230.55
|
||||
201.997
|
||||
227.649
|
||||
192.577
|
||||
221.454
|
||||
236.59
|
||||
224.637
|
||||
201.263
|
||||
218.685
|
||||
256.401
|
||||
228.137
|
||||
203.421
|
||||
228.677
|
||||
239.173
|
||||
203.783
|
||||
243.217
|
||||
204.188
|
||||
211.535
|
||||
229.573
|
||||
225.773
|
||||
235.748
|
||||
208.659
|
||||
220.83
|
||||
191.357
|
||||
224.938
|
||||
216.195
|
||||
218.868
|
||||
230.63
|
||||
186.89
|
||||
218.199
|
||||
217.047
|
||||
223.644
|
||||
213.801
|
||||
205.631
|
||||
210.824
|
||||
230.178
|
||||
257.369
|
||||
243.262
|
||||
229.047
|
||||
221.493
|
||||
177.905
|
||||
241.468
|
||||
243.443
|
||||
233.782
|
||||
205.347
|
||||
268.384
|
||||
230.853
|
||||
226.312
|
||||
209.55
|
||||
233.426
|
||||
210.991
|
||||
219.415
|
||||
260.926
|
||||
229.786
|
||||
194.888
|
||||
193.57
|
||||
211.086
|
||||
237.989
|
||||
217.102
|
||||
194.775
|
||||
244.384
|
||||
211.814
|
||||
212.073
|
||||
187.619
|
||||
205.625
|
||||
210.781
|
||||
191.55
|
||||
178.258
|
||||
194.329
|
||||
212.217
|
||||
200.944
|
||||
227.453
|
||||
264.972
|
||||
202.656
|
||||
201.39
|
||||
236.882
|
||||
214.712
|
||||
194.569
|
||||
195.513
|
||||
262.158
|
||||
251.577
|
||||
193.849
|
||||
224.14
|
||||
@ -1,7 +1,7 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sun Oct 1 19:59:33 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 2:5
|
||||
@ -47,7 +47,7 @@ b -0.996 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sun Oct 1 19:59:33 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:5
|
||||
@ -93,7 +93,7 @@ bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sun Oct 1 19:59:33 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:6
|
||||
|
||||
@ -2,19 +2,19 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 2:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Iterations'
|
||||
set output "20170830-evolution1D_5x5_100Times-added_one_regularity-vs-steps.png"
|
||||
plot "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 2:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Iterations'
|
||||
set output "20170830-evolution1D_5x5_100Times-added_one_improvement-vs-steps.png"
|
||||
plot "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:6 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Fitting error'
|
||||
set output "20170830-evolution1D_5x5_100Times-added_one_improvement-vs-evo-error.png"
|
||||
plot "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
|
||||
@ -0,0 +1,37 @@
|
||||
[1] "================ Analyzing 20170830-evolution1D_5x5_100Times-added_one.csv"
|
||||
[1] "spearman for improvement-potential vs. evolution-error"
|
||||
x y
|
||||
x 1 -1
|
||||
y -1 1
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0
|
||||
y 0
|
||||
[1] "spearman for regularity vs. steps"
|
||||
x y
|
||||
x 1.00 -0.34
|
||||
y -0.34 1.00
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 5e-04
|
||||
y 5e-04
|
||||
[1] "spearman for variability vs. evolution-error"
|
||||
x y
|
||||
x 1 NaN
|
||||
y NaN 1
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x
|
||||
y
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 5.7 KiB After Width: | Height: | Size: 5.6 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 5.7 KiB After Width: | Height: | Size: 5.8 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 6.0 KiB After Width: | Height: | Size: 6.1 KiB |
@ -0,0 +1,201 @@
|
||||
"Evolution error"
|
||||
192.44
|
||||
240.171
|
||||
249.883
|
||||
197.529
|
||||
201.143
|
||||
212.978
|
||||
187.236
|
||||
241.13
|
||||
222.511
|
||||
256.592
|
||||
236.693
|
||||
221.694
|
||||
224.469
|
||||
234.382
|
||||
243.433
|
||||
194.032
|
||||
234.567
|
||||
213.401
|
||||
201.428
|
||||
207.224
|
||||
224.585
|
||||
221.895
|
||||
194.499
|
||||
208.589
|
||||
215.456
|
||||
234.028
|
||||
214.716
|
||||
241.431
|
||||
206.599
|
||||
204.769
|
||||
204.23
|
||||
222.938
|
||||
185.355
|
||||
218.429
|
||||
219.886
|
||||
219.696
|
||||
203.581
|
||||
226.759
|
||||
221.819
|
||||
236.226
|
||||
217.553
|
||||
213.564
|
||||
195.759
|
||||
247.931
|
||||
233.713
|
||||
234.013
|
||||
223.628
|
||||
194.983
|
||||
226.437
|
||||
214.086
|
||||
186.419
|
||||
196.416
|
||||
235.058
|
||||
244.587
|
||||
255.376
|
||||
226.808
|
||||
241.372
|
||||
225.08
|
||||
210.821
|
||||
206.672
|
||||
201.399
|
||||
246.066
|
||||
253.875
|
||||
259.741
|
||||
207.655
|
||||
238.654
|
||||
213.147
|
||||
210.34
|
||||
273.684
|
||||
200.321
|
||||
230.127
|
||||
210.898
|
||||
224.914
|
||||
208.711
|
||||
233.241
|
||||
203.658
|
||||
227.058
|
||||
219.89
|
||||
212.877
|
||||
215.439
|
||||
191.017
|
||||
170.069
|
||||
204.348
|
||||
195.049
|
||||
207.186
|
||||
225.229
|
||||
230.466
|
||||
212.578
|
||||
190.496
|
||||
262.382
|
||||
215.988
|
||||
206.934
|
||||
250.737
|
||||
205.827
|
||||
212.891
|
||||
201.034
|
||||
212.53
|
||||
208.545
|
||||
206.327
|
||||
199.413
|
||||
207.886
|
||||
245.873
|
||||
209.253
|
||||
236.693
|
||||
237.512
|
||||
217.347
|
||||
206.725
|
||||
218.216
|
||||
208.831
|
||||
199.805
|
||||
195.163
|
||||
193.258
|
||||
181.901
|
||||
183.091
|
||||
215.233
|
||||
210.992
|
||||
226.197
|
||||
230.55
|
||||
201.997
|
||||
227.649
|
||||
192.577
|
||||
221.454
|
||||
236.59
|
||||
224.637
|
||||
201.263
|
||||
218.685
|
||||
256.401
|
||||
228.137
|
||||
203.421
|
||||
228.677
|
||||
239.173
|
||||
203.783
|
||||
243.217
|
||||
204.188
|
||||
211.535
|
||||
229.573
|
||||
225.773
|
||||
235.748
|
||||
208.659
|
||||
220.83
|
||||
191.357
|
||||
224.938
|
||||
216.195
|
||||
218.868
|
||||
230.63
|
||||
186.89
|
||||
218.199
|
||||
217.047
|
||||
223.644
|
||||
213.801
|
||||
205.631
|
||||
210.824
|
||||
230.178
|
||||
257.369
|
||||
243.262
|
||||
229.047
|
||||
221.493
|
||||
177.905
|
||||
241.468
|
||||
243.443
|
||||
233.782
|
||||
205.347
|
||||
268.384
|
||||
230.853
|
||||
226.312
|
||||
209.55
|
||||
233.426
|
||||
210.991
|
||||
219.415
|
||||
260.926
|
||||
229.786
|
||||
194.888
|
||||
193.57
|
||||
211.086
|
||||
237.989
|
||||
217.102
|
||||
194.775
|
||||
244.384
|
||||
211.814
|
||||
212.073
|
||||
187.619
|
||||
205.625
|
||||
210.781
|
||||
191.55
|
||||
178.258
|
||||
194.329
|
||||
212.217
|
||||
200.944
|
||||
227.453
|
||||
264.972
|
||||
202.656
|
||||
201.39
|
||||
236.882
|
||||
214.712
|
||||
194.569
|
||||
195.513
|
||||
262.158
|
||||
251.577
|
||||
193.849
|
||||
224.14
|
||||
@ -1,7 +1,7 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sun Oct 1 20:05:21 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20170830-evolution1D_5x5_100Times-all.csv" every ::1 using 2:5
|
||||
@ -47,7 +47,7 @@ b -0.995 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sun Oct 1 20:05:21 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20170830-evolution1D_5x5_100Times-all.csv" every ::1 using 4:5
|
||||
@ -93,7 +93,7 @@ bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sun Oct 1 20:05:21 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20170830-evolution1D_5x5_100Times-all.csv" every ::1 using 4:6
|
||||
|
||||
@ -2,19 +2,19 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20170830-evolution1D_5x5_100Times-all.csv" every ::1 using 2:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Iterations'
|
||||
set output "20170830-evolution1D_5x5_100Times-all_regularity-vs-steps.png"
|
||||
plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 2:5 title "20170830-evolution1D_5x5_100Times.csv", "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 2:5 title "20170830-evolution1D_5x5_100Times-added_one.csv", f(x) title "lin. fit" lc rgb "black"
|
||||
plot "20170830-evolution1D_5x5_100Times-all.csv" every ::1 using 2:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20170830-evolution1D_5x5_100Times-all.csv" every ::1 using 4:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Iterations'
|
||||
set output "20170830-evolution1D_5x5_100Times-all_improvement-vs-steps.png"
|
||||
plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:5 title "20170830-evolution1D_5x5_100Times.csv", "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:5 title "20170830-evolution1D_5x5_100Times-added_one.csv", g(x) title "lin. fit" lc rgb "black"
|
||||
plot "20170830-evolution1D_5x5_100Times-all.csv" every ::1 using 4:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20170830-evolution1D_5x5_100Times-all.csv" every ::1 using 4:6 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Fitting error'
|
||||
set output "20170830-evolution1D_5x5_100Times-all_improvement-vs-evo-error.png"
|
||||
plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:6 title "20170830-evolution1D_5x5_100Times.csv", "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:6 title "20170830-evolution1D_5x5_100Times-added_one.csv", h(x) title "lin. fit" lc rgb "black"
|
||||
plot "20170830-evolution1D_5x5_100Times-all.csv" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
|
||||
@ -0,0 +1,37 @@
|
||||
[1] "================ Analyzing 20170830-evolution1D_5x5_100Times-all.csv"
|
||||
[1] "spearman for improvement-potential vs. evolution-error"
|
||||
x y
|
||||
x 1 -1
|
||||
y -1 1
|
||||
|
||||
n= 200
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0
|
||||
y 0
|
||||
[1] "spearman for regularity vs. steps"
|
||||
x y
|
||||
x 1.00 -0.31
|
||||
y -0.31 1.00
|
||||
|
||||
n= 200
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0
|
||||
y 0
|
||||
[1] "spearman for variability vs. evolution-error"
|
||||
x y
|
||||
x 1 NaN
|
||||
y NaN 1
|
||||
|
||||
n= 200
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x
|
||||
y
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 7.1 KiB After Width: | Height: | Size: 5.5 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 8.1 KiB After Width: | Height: | Size: 6.5 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 8.2 KiB After Width: | Height: | Size: 6.7 KiB |
@ -0,0 +1,101 @@
|
||||
"Evolution error"
|
||||
192.44
|
||||
240.171
|
||||
249.883
|
||||
197.529
|
||||
201.143
|
||||
212.978
|
||||
187.236
|
||||
241.13
|
||||
222.511
|
||||
256.592
|
||||
236.693
|
||||
221.694
|
||||
224.469
|
||||
234.382
|
||||
243.433
|
||||
194.032
|
||||
234.567
|
||||
213.401
|
||||
201.428
|
||||
207.224
|
||||
224.585
|
||||
221.895
|
||||
194.499
|
||||
208.589
|
||||
215.456
|
||||
234.028
|
||||
214.716
|
||||
241.431
|
||||
206.599
|
||||
204.769
|
||||
204.23
|
||||
222.938
|
||||
185.355
|
||||
218.429
|
||||
219.886
|
||||
219.696
|
||||
203.581
|
||||
226.759
|
||||
221.819
|
||||
236.226
|
||||
217.553
|
||||
213.564
|
||||
195.759
|
||||
247.931
|
||||
233.713
|
||||
234.013
|
||||
223.628
|
||||
194.983
|
||||
226.437
|
||||
214.086
|
||||
186.419
|
||||
196.416
|
||||
235.058
|
||||
244.587
|
||||
255.376
|
||||
226.808
|
||||
241.372
|
||||
225.08
|
||||
210.821
|
||||
206.672
|
||||
201.399
|
||||
246.066
|
||||
253.875
|
||||
259.741
|
||||
207.655
|
||||
238.654
|
||||
213.147
|
||||
210.34
|
||||
273.684
|
||||
200.321
|
||||
230.127
|
||||
210.898
|
||||
224.914
|
||||
208.711
|
||||
233.241
|
||||
203.658
|
||||
227.058
|
||||
219.89
|
||||
212.877
|
||||
215.439
|
||||
191.017
|
||||
170.069
|
||||
204.348
|
||||
195.049
|
||||
207.186
|
||||
225.229
|
||||
230.466
|
||||
212.578
|
||||
190.496
|
||||
262.382
|
||||
215.988
|
||||
206.934
|
||||
250.737
|
||||
205.827
|
||||
212.891
|
||||
201.034
|
||||
212.53
|
||||
208.545
|
||||
206.327
|
||||
199.413
|
||||
@ -1,7 +1,7 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sun Oct 1 19:58:40 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20170830-evolution1D_5x5_100Times.csv" every ::1 using 2:5
|
||||
@ -47,7 +47,7 @@ b -0.995 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sun Oct 1 19:58:40 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:5
|
||||
@ -93,7 +93,7 @@ bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Sun Oct 1 19:58:40 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:6
|
||||
|
||||
@ -2,19 +2,19 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20170830-evolution1D_5x5_100Times.csv" every ::1 using 2:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Iterations'
|
||||
set output "20170830-evolution1D_5x5_100Times_regularity-vs-steps.png"
|
||||
plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 2:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Iterations'
|
||||
set output "20170830-evolution1D_5x5_100Times_improvement-vs-steps.png"
|
||||
plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:6 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Fitting error'
|
||||
set output "20170830-evolution1D_5x5_100Times_improvement-vs-evo-error.png"
|
||||
plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
|
||||
@ -0,0 +1,37 @@
|
||||
[1] "================ Analyzing 20170830-evolution1D_5x5_100Times.csv"
|
||||
[1] "spearman for improvement-potential vs. evolution-error"
|
||||
x y
|
||||
x 1 -1
|
||||
y -1 1
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0
|
||||
y 0
|
||||
[1] "spearman for regularity vs. steps"
|
||||
x y
|
||||
x 1.00 -0.28
|
||||
y -0.28 1.00
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0.0045
|
||||
y 0.0045
|
||||
[1] "spearman for variability vs. evolution-error"
|
||||
x y
|
||||
x 1 NaN
|
||||
y NaN 1
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x
|
||||
y
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 5.5 KiB After Width: | Height: | Size: 5.4 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 5.7 KiB After Width: | Height: | Size: 5.8 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 5.5 KiB After Width: | Height: | Size: 5.6 KiB |
501
dokumentation/evolution1d/20171005-all.error
Normal file
501
dokumentation/evolution1d/20171005-all.error
Normal file
@ -0,0 +1,501 @@
|
||||
"Evolution error"
|
||||
192.44
|
||||
240.171
|
||||
249.883
|
||||
197.529
|
||||
201.143
|
||||
212.978
|
||||
187.236
|
||||
241.13
|
||||
222.511
|
||||
256.592
|
||||
236.693
|
||||
221.694
|
||||
224.469
|
||||
234.382
|
||||
243.433
|
||||
194.032
|
||||
234.567
|
||||
213.401
|
||||
201.428
|
||||
207.224
|
||||
224.585
|
||||
221.895
|
||||
194.499
|
||||
208.589
|
||||
215.456
|
||||
234.028
|
||||
214.716
|
||||
241.431
|
||||
206.599
|
||||
204.769
|
||||
204.23
|
||||
222.938
|
||||
185.355
|
||||
218.429
|
||||
219.886
|
||||
219.696
|
||||
203.581
|
||||
226.759
|
||||
221.819
|
||||
236.226
|
||||
217.553
|
||||
213.564
|
||||
195.759
|
||||
247.931
|
||||
233.713
|
||||
234.013
|
||||
223.628
|
||||
194.983
|
||||
226.437
|
||||
214.086
|
||||
186.419
|
||||
196.416
|
||||
235.058
|
||||
244.587
|
||||
255.376
|
||||
226.808
|
||||
241.372
|
||||
225.08
|
||||
210.821
|
||||
206.672
|
||||
201.399
|
||||
246.066
|
||||
253.875
|
||||
259.741
|
||||
207.655
|
||||
238.654
|
||||
213.147
|
||||
210.34
|
||||
273.684
|
||||
200.321
|
||||
230.127
|
||||
210.898
|
||||
224.914
|
||||
208.711
|
||||
233.241
|
||||
203.658
|
||||
227.058
|
||||
219.89
|
||||
212.877
|
||||
215.439
|
||||
191.017
|
||||
170.069
|
||||
204.348
|
||||
195.049
|
||||
207.186
|
||||
225.229
|
||||
230.466
|
||||
212.578
|
||||
190.496
|
||||
262.382
|
||||
215.988
|
||||
206.934
|
||||
250.737
|
||||
205.827
|
||||
212.891
|
||||
201.034
|
||||
212.53
|
||||
208.545
|
||||
206.327
|
||||
199.413
|
||||
207.886
|
||||
245.873
|
||||
209.253
|
||||
236.693
|
||||
237.512
|
||||
217.347
|
||||
206.725
|
||||
218.216
|
||||
208.831
|
||||
199.805
|
||||
195.163
|
||||
193.258
|
||||
181.901
|
||||
183.091
|
||||
215.233
|
||||
210.992
|
||||
226.197
|
||||
230.55
|
||||
201.997
|
||||
227.649
|
||||
192.577
|
||||
221.454
|
||||
236.59
|
||||
224.637
|
||||
201.263
|
||||
218.685
|
||||
256.401
|
||||
228.137
|
||||
203.421
|
||||
228.677
|
||||
239.173
|
||||
203.783
|
||||
243.217
|
||||
204.188
|
||||
211.535
|
||||
229.573
|
||||
225.773
|
||||
235.748
|
||||
208.659
|
||||
220.83
|
||||
191.357
|
||||
224.938
|
||||
216.195
|
||||
218.868
|
||||
230.63
|
||||
186.89
|
||||
218.199
|
||||
217.047
|
||||
223.644
|
||||
213.801
|
||||
205.631
|
||||
210.824
|
||||
230.178
|
||||
257.369
|
||||
243.262
|
||||
229.047
|
||||
221.493
|
||||
177.905
|
||||
241.468
|
||||
243.443
|
||||
233.782
|
||||
205.347
|
||||
268.384
|
||||
230.853
|
||||
226.312
|
||||
209.55
|
||||
233.426
|
||||
210.991
|
||||
219.415
|
||||
260.926
|
||||
229.786
|
||||
194.888
|
||||
193.57
|
||||
211.086
|
||||
237.989
|
||||
217.102
|
||||
194.775
|
||||
244.384
|
||||
211.814
|
||||
212.073
|
||||
187.619
|
||||
205.625
|
||||
210.781
|
||||
191.55
|
||||
178.258
|
||||
194.329
|
||||
212.217
|
||||
200.944
|
||||
227.453
|
||||
264.972
|
||||
202.656
|
||||
201.39
|
||||
236.882
|
||||
214.712
|
||||
194.569
|
||||
195.513
|
||||
262.158
|
||||
251.577
|
||||
193.849
|
||||
224.14
|
||||
280.917
|
||||
315.729
|
||||
264.639
|
||||
275.922
|
||||
323.159
|
||||
300.933
|
||||
264.541
|
||||
264.875
|
||||
286.999
|
||||
314.771
|
||||
254.996
|
||||
270.99
|
||||
336.401
|
||||
249.761
|
||||
310.473
|
||||
282.476
|
||||
301.45
|
||||
304.67
|
||||
300.451
|
||||
315.122
|
||||
302.947
|
||||
262.796
|
||||
272.873
|
||||
291.472
|
||||
280.073
|
||||
274.973
|
||||
277.642
|
||||
266.096
|
||||
300.458
|
||||
281.797
|
||||
287.84
|
||||
270.181
|
||||
304.713
|
||||
301.015
|
||||
250.936
|
||||
327.876
|
||||
267.093
|
||||
266.032
|
||||
293.5
|
||||
274.145
|
||||
302.284
|
||||
296.447
|
||||
290.496
|
||||
326.409
|
||||
252.376
|
||||
285.256
|
||||
261.023
|
||||
273.732
|
||||
287.211
|
||||
246.715
|
||||
317.892
|
||||
265.825
|
||||
259.862
|
||||
273.217
|
||||
269.759
|
||||
314.394
|
||||
314.765
|
||||
284.627
|
||||
262.319
|
||||
269.132
|
||||
259.973
|
||||
296.171
|
||||
264.153
|
||||
307.381
|
||||
248.894
|
||||
312.436
|
||||
273.599
|
||||
286.954
|
||||
313.315
|
||||
290.546
|
||||
317.095
|
||||
289.397
|
||||
293.925
|
||||
273.573
|
||||
248.052
|
||||
282.84
|
||||
286.257
|
||||
284.314
|
||||
321.302
|
||||
260.894
|
||||
278.436
|
||||
274.697
|
||||
269.428
|
||||
287.274
|
||||
281.924
|
||||
263.843
|
||||
298.757
|
||||
275.521
|
||||
269.146
|
||||
273.475
|
||||
273.666
|
||||
298.125
|
||||
305.642
|
||||
297.086
|
||||
317.845
|
||||
274.586
|
||||
332.413
|
||||
301.147
|
||||
354.08
|
||||
266.461
|
||||
211.096
|
||||
233.828
|
||||
205.276
|
||||
261.016
|
||||
205.753
|
||||
244.494
|
||||
236.857
|
||||
243.624
|
||||
227.071
|
||||
228.254
|
||||
219.293
|
||||
235.159
|
||||
240.691
|
||||
232.853
|
||||
243.665
|
||||
242.766
|
||||
243.618
|
||||
238.051
|
||||
224.685
|
||||
206.919
|
||||
266.62
|
||||
229.771
|
||||
241.243
|
||||
228.75
|
||||
246.415
|
||||
245.936
|
||||
234.603
|
||||
230.971
|
||||
246.319
|
||||
235.173
|
||||
250.199
|
||||
240.854
|
||||
233.456
|
||||
216.659
|
||||
240.033
|
||||
244.108
|
||||
216.874
|
||||
242.058
|
||||
221.484
|
||||
222.485
|
||||
239.78
|
||||
232.709
|
||||
230.785
|
||||
229.968
|
||||
235.149
|
||||
233.462
|
||||
241.027
|
||||
229.139
|
||||
210.309
|
||||
222.927
|
||||
236.762
|
||||
244.312
|
||||
225.283
|
||||
228.831
|
||||
234.735
|
||||
222.154
|
||||
215.144
|
||||
247.533
|
||||
242.563
|
||||
231.706
|
||||
245.743
|
||||
233.422
|
||||
221.213
|
||||
223.48
|
||||
234.243
|
||||
246.759
|
||||
225.232
|
||||
233.179
|
||||
256.94
|
||||
237.977
|
||||
238.547
|
||||
254.967
|
||||
223.3
|
||||
243.823
|
||||
240.056
|
||||
220.234
|
||||
242.633
|
||||
244.981
|
||||
244.803
|
||||
241.898
|
||||
222.32
|
||||
232.013
|
||||
228.661
|
||||
241.097
|
||||
225.772
|
||||
243.746
|
||||
209.245
|
||||
235.881
|
||||
241.881
|
||||
231.035
|
||||
220.946
|
||||
212.015
|
||||
234.886
|
||||
234.38
|
||||
250.999
|
||||
229.239
|
||||
222.041
|
||||
208.038
|
||||
217.716
|
||||
220.769
|
||||
126.241
|
||||
110.962
|
||||
125.853
|
||||
140.195
|
||||
126.647
|
||||
154.539
|
||||
107.206
|
||||
128.558
|
||||
136.77
|
||||
145.941
|
||||
171.996
|
||||
118.437
|
||||
143.556
|
||||
120.873
|
||||
105.887
|
||||
154.67
|
||||
154.182
|
||||
116.314
|
||||
113.496
|
||||
159.92
|
||||
158.727
|
||||
108.387
|
||||
148.334
|
||||
112.767
|
||||
139.428
|
||||
124.479
|
||||
106.309
|
||||
139.721
|
||||
133.951
|
||||
135.062
|
||||
133.884
|
||||
120.051
|
||||
101.318
|
||||
135.279
|
||||
110.051
|
||||
136.437
|
||||
134.697
|
||||
113.78
|
||||
122.484
|
||||
114.487
|
||||
127.55
|
||||
125.629
|
||||
162.041
|
||||
156.364
|
||||
113.788
|
||||
138.26
|
||||
109.996
|
||||
164.442
|
||||
105.711
|
||||
156.553
|
||||
116.304
|
||||
113.339
|
||||
118.637
|
||||
164.957
|
||||
97.1774
|
||||
137.814
|
||||
158.652
|
||||
128.639
|
||||
144.853
|
||||
136.728
|
||||
100.103
|
||||
129.972
|
||||
134.171
|
||||
102.086
|
||||
137.823
|
||||
120.165
|
||||
121.511
|
||||
110.067
|
||||
112.614
|
||||
105.271
|
||||
140.821
|
||||
124.285
|
||||
158.103
|
||||
140.515
|
||||
101.64
|
||||
129.887
|
||||
167.194
|
||||
110.881
|
||||
146.669
|
||||
118.035
|
||||
150.583
|
||||
143.211
|
||||
114.785
|
||||
146.421
|
||||
130.875
|
||||
107.373
|
||||
152.164
|
||||
129.282
|
||||
98.1416
|
||||
129.997
|
||||
117
|
||||
111.092
|
||||
114.087
|
||||
107.558
|
||||
144.45
|
||||
118.484
|
||||
109.701
|
||||
126.593
|
||||
168.971
|
||||
143.838
|
||||
@ -1,7 +1,7 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:24:23 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-all.csv" every ::1 using 2:5
|
||||
@ -10,12 +10,19 @@ FIT: data read from "20171005-all.csv" every ::1 using 2:5
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: f(x)
|
||||
f(x)=a*x+b
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda a b
|
||||
0 2.2819584538e+07 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
4 9.2387072945e+05 -3.77e-04 7.07e-05 5.253352e+02 1.999370e+02
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 2.28196e+07 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707253
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 923871
|
||||
@ -27,17 +34,20 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 1855.16
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = 525.335 +/- 371.3 (70.69%)
|
||||
b = 199.937 +/- 7.551 (3.777%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
a b
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.967 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:24:23 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-all.csv" every ::1 using 4:5
|
||||
@ -46,12 +56,19 @@ FIT: data read from "20171005-all.csv" every ::1 using 4:5
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: g(x)
|
||||
g(x)=aa*x+bb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aa bb
|
||||
0 2.2629211027e+07 0.00e+00 9.66e-01 1.000000e+00 1.000000e+00
|
||||
4 8.9631538551e+05 -2.78e-05 9.66e-05 4.610660e+02 -2.189272e+02
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 2.26292e+07 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.96613
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 896315
|
||||
@ -63,17 +80,20 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 1799.83
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 461.066 +/- 110.6 (23.99%)
|
||||
bb = -218.927 +/- 103 (47.04%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aa bb
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:24:23 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-all.csv" every ::1 using 4:6
|
||||
@ -82,16 +102,23 @@ FIT: data read from "20171005-all.csv" every ::1 using 4:6
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: h(x)
|
||||
h(x)=aaa*x+bbb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
0 2.4597834778e+07 0.00e+00 9.66e-01 1.000000e+00 1.000000e+00
|
||||
5 4.4603658393e+01 -1.73e-08 9.66e-06 -3.139922e+03 3.139954e+03
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 2.45978e+07 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.96613
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 44.6037
|
||||
rel. change during last iteration : -1.72842e-13
|
||||
rel. change during last iteration : -1.73479e-13
|
||||
|
||||
degrees of freedom (FIT_NDF) : 498
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.299275
|
||||
@ -99,46 +126,13 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 0.0895656
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -3139.92 +/- 0.7803 (0.02485%)
|
||||
bbb = 3139.95 +/- 0.7265 (0.02314%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:24:23 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-all.csv" every ::1 using 3:6
|
||||
format = x:z
|
||||
#datapoints = 500
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: i(x)
|
||||
i(x)=aaaa*x+bbbb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aaaa bbbb
|
||||
0 2.4797348325e+07 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
5 6.2575820484e+05 -6.78e-01 7.07e-06 -1.004063e+05 3.554273e+02
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 625758
|
||||
rel. change during last iteration : -6.77885e-06
|
||||
|
||||
degrees of freedom (FIT_NDF) : 498
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 35.4477
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1256.54
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aaaa = -100406 +/- 3920 (3.904%)
|
||||
bbbb = 355.427 +/- 5.629 (1.584%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -0.960 1.000
|
||||
|
||||
@ -1,10 +1,58 @@
|
||||
iter chisq delta/lim lambda a b
|
||||
0 2.2819584538e+07 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
1 9.2734539506e+05 -2.36e+06 7.07e-02 1.872894e+01 2.096890e+02
|
||||
2 9.2412450892e+05 -3.49e+02 7.07e-03 3.879916e+02 2.026375e+02
|
||||
3 9.2387073294e+05 -2.75e+01 7.07e-04 5.248262e+02 1.999470e+02
|
||||
4 9.2387072945e+05 -3.77e-04 7.07e-05 5.253352e+02 1.999370e+02
|
||||
iter chisq delta/lim lambda a b
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 2.28196e+07 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707253
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 927345 delta(WSSR)/WSSR : -23.6074
|
||||
delta(WSSR) : -2.18922e+07 limit for stopping : 1e-05
|
||||
lambda : 0.0707253
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = 18.7289
|
||||
b = 209.689
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 924125 delta(WSSR)/WSSR : -0.00348534
|
||||
delta(WSSR) : -3220.89 limit for stopping : 1e-05
|
||||
lambda : 0.00707253
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = 387.992
|
||||
b = 202.637
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 923871 delta(WSSR)/WSSR : -0.000274688
|
||||
delta(WSSR) : -253.776 limit for stopping : 1e-05
|
||||
lambda : 0.000707253
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = 524.826
|
||||
b = 199.947
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 923871 delta(WSSR)/WSSR : -3.77204e-09
|
||||
delta(WSSR) : -0.00348488 limit for stopping : 1e-05
|
||||
lambda : 7.07253e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = 525.335
|
||||
b = 199.937
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 923871
|
||||
@ -16,20 +64,71 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 1855.16
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = 525.335 +/- 371.3 (70.69%)
|
||||
b = 199.937 +/- 7.551 (3.777%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
a b
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.967 1.000
|
||||
iter chisq delta/lim lambda aa bb
|
||||
0 2.2629211027e+07 0.00e+00 9.66e-01 1.000000e+00 1.000000e+00
|
||||
1 9.1220178149e+05 -2.38e+06 9.66e-02 1.325557e+02 8.671371e+01
|
||||
2 8.9649334140e+05 -1.75e+03 9.66e-03 4.262842e+02 -1.865447e+02
|
||||
3 8.9631538576e+05 -1.99e+01 9.66e-04 4.610248e+02 -2.188888e+02
|
||||
4 8.9631538551e+05 -2.78e-05 9.66e-05 4.610660e+02 -2.189272e+02
|
||||
iter chisq delta/lim lambda aa bb
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 2.26292e+07 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.96613
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 912202 delta(WSSR)/WSSR : -23.8072
|
||||
delta(WSSR) : -2.1717e+07 limit for stopping : 1e-05
|
||||
lambda : 0.096613
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 132.556
|
||||
bb = 86.7137
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 896493 delta(WSSR)/WSSR : -0.0175221
|
||||
delta(WSSR) : -15708.4 limit for stopping : 1e-05
|
||||
lambda : 0.0096613
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 426.284
|
||||
bb = -186.545
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 896315 delta(WSSR)/WSSR : -0.000198541
|
||||
delta(WSSR) : -177.956 limit for stopping : 1e-05
|
||||
lambda : 0.00096613
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 461.025
|
||||
bb = -218.889
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 896315 delta(WSSR)/WSSR : -2.77934e-10
|
||||
delta(WSSR) : -0.000249116 limit for stopping : 1e-05
|
||||
lambda : 9.6613e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 461.066
|
||||
bb = -218.927
|
||||
|
||||
After 4 iterations the fit converged.
|
||||
final sum of squares of residuals : 896315
|
||||
@ -41,25 +140,86 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 1799.83
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 461.066 +/- 110.6 (23.99%)
|
||||
bb = -218.927 +/- 103 (47.04%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aa bb
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
0 2.4597834778e+07 0.00e+00 9.66e-01 1.000000e+00 1.000000e+00
|
||||
1 1.3196790874e+06 -1.76e+06 9.66e-02 -1.448795e+02 3.513002e+02
|
||||
2 1.4846794008e+04 -8.79e+06 9.66e-03 -2.822704e+03 2.844618e+03
|
||||
3 4.4624379637e+01 -3.32e+07 9.66e-04 -3.139547e+03 3.139604e+03
|
||||
4 4.4603658393e+01 -4.65e+01 9.66e-05 -3.139922e+03 3.139954e+03
|
||||
5 4.4603658393e+01 -1.73e-08 9.66e-06 -3.139922e+03 3.139954e+03
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 2.45978e+07 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.96613
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 1.31968e+06 delta(WSSR)/WSSR : -17.6393
|
||||
delta(WSSR) : -2.32782e+07 limit for stopping : 1e-05
|
||||
lambda : 0.096613
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -144.879
|
||||
bbb = 351.3
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 14846.8 delta(WSSR)/WSSR : -87.8865
|
||||
delta(WSSR) : -1.30483e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0096613
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -2822.7
|
||||
bbb = 2844.62
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 44.6244 delta(WSSR)/WSSR : -331.706
|
||||
delta(WSSR) : -14802.2 limit for stopping : 1e-05
|
||||
lambda : 0.00096613
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3139.55
|
||||
bbb = 3139.6
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 44.6037 delta(WSSR)/WSSR : -0.000464564
|
||||
delta(WSSR) : -0.0207212 limit for stopping : 1e-05
|
||||
lambda : 9.6613e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3139.92
|
||||
bbb = 3139.95
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 44.6037 delta(WSSR)/WSSR : -1.73479e-13
|
||||
delta(WSSR) : -7.73781e-12 limit for stopping : 1e-05
|
||||
lambda : 9.6613e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3139.92
|
||||
bbb = 3139.95
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 44.6037
|
||||
rel. change during last iteration : -1.72842e-13
|
||||
rel. change during last iteration : -1.73479e-13
|
||||
|
||||
degrees of freedom (FIT_NDF) : 498
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.299275
|
||||
@ -67,36 +227,13 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 0.0895656
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -3139.92 +/- 0.7803 (0.02485%)
|
||||
bbb = 3139.95 +/- 0.7265 (0.02314%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
iter chisq delta/lim lambda aaaa bbbb
|
||||
0 2.4797348325e+07 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
1 1.4499765510e+06 -1.61e+06 7.07e-02 -1.512219e+01 2.168949e+02
|
||||
2 1.4236400853e+06 -1.85e+03 7.07e-03 -1.630660e+03 2.193366e+02
|
||||
3 7.4062425817e+05 -9.22e+04 7.07e-04 -6.292829e+04 3.037910e+02
|
||||
4 6.2576244676e+05 -1.84e+04 7.07e-05 -1.001785e+05 3.551135e+02
|
||||
5 6.2575820484e+05 -6.78e-01 7.07e-06 -1.004063e+05 3.554273e+02
|
||||
iter chisq delta/lim lambda aaaa bbbb
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 625758
|
||||
rel. change during last iteration : -6.77885e-06
|
||||
|
||||
degrees of freedom (FIT_NDF) : 498
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 35.4477
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1256.54
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
aaaa = -100406 +/- 3920 (3.904%)
|
||||
bbbb = 355.427 +/- 5.629 (1.584%)
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaaa bbbb
|
||||
aaaa 1.000
|
||||
bbbb -0.960 1.000
|
||||
|
||||
@ -2,25 +2,19 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171005-all.csv" every ::1 using 2:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171005-all_regularity-vs-steps.png"
|
||||
plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 2:5 title "20170830-evolution1D_5x5_100Times.csv", "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 2:5 title "20170830-evolution1D_5x5_100Times-added_one.csv", "20171005-evolution1D_4x7_100Times.csv" every ::1 using 2:5 title "20171005-evolution1D_4x7_100Times.csv", "20171005-evolution1D_7x4_100Times.csv" every ::1 using 2:5 title "20171005-evolution1D_7x4_100Times.csv", "20171005-evolution1D_7x7_100Times.csv" every ::1 using 2:5 title "20171005-evolution1D_7x7_100Times.csv", f(x) title "lin. fit" lc rgb "black"
|
||||
plot "20171005-all.csv" every ::1 using 2:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171005-all.csv" every ::1 using 4:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171005-all_improvement-vs-steps.png"
|
||||
plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:5 title "20170830-evolution1D_5x5_100Times.csv", "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:5 title "20170830-evolution1D_5x5_100Times-added_one.csv", "20171005-evolution1D_4x7_100Times.csv" every ::1 using 4:5 title "20171005-evolution1D_4x7_100Times.csv", "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4:5 title "20171005-evolution1D_7x4_100Times.csv", "20171005-evolution1D_7x7_100Times.csv" every ::1 using 4:5 title "20171005-evolution1D_7x7_100Times.csv", g(x) title "lin. fit" lc rgb "black"
|
||||
plot "20171005-all.csv" every ::1 using 4:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171005-all.csv" every ::1 using 4:6 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Fitting error'
|
||||
set output "20171005-all_improvement-vs-evo-error.png"
|
||||
plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 4:6 title "20170830-evolution1D_5x5_100Times.csv", "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 4:6 title "20170830-evolution1D_5x5_100Times-added_one.csv", "20171005-evolution1D_4x7_100Times.csv" every ::1 using 4:6 title "20171005-evolution1D_4x7_100Times.csv", "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4:6 title "20171005-evolution1D_7x4_100Times.csv", "20171005-evolution1D_7x7_100Times.csv" every ::1 using 4:6 title "20171005-evolution1D_7x7_100Times.csv", h(x) title "lin. fit" lc rgb "black"
|
||||
i(x)=aaaa*x+bbbb
|
||||
fit i(x) "20171005-all.csv" every ::1 using 3:6 via aaaa,bbbb
|
||||
set xlabel 'variability'
|
||||
set ylabel 'evolution error'
|
||||
set output "20171005-all_variability-vs-evo-error.png"
|
||||
plot "20170830-evolution1D_5x5_100Times.csv" every ::1 using 3:6 title "20170830-evolution1D_5x5_100Times.csv", "20170830-evolution1D_5x5_100Times-added_one.csv" every ::1 using 3:6 title "20170830-evolution1D_5x5_100Times-added_one.csv", "20171005-evolution1D_4x7_100Times.csv" every ::1 using 3:6 title "20171005-evolution1D_4x7_100Times.csv", "20171005-evolution1D_7x4_100Times.csv" every ::1 using 3:6 title "20171005-evolution1D_7x4_100Times.csv", "20171005-evolution1D_7x7_100Times.csv" every ::1 using 3:6 title "20171005-evolution1D_7x7_100Times.csv", i(x) title "lin. fit" lc rgb "black"
|
||||
plot "20171005-all.csv" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
|
||||
37
dokumentation/evolution1d/20171005-all.spearman
Normal file
37
dokumentation/evolution1d/20171005-all.spearman
Normal file
@ -0,0 +1,37 @@
|
||||
[1] "================ Analyzing 20171005-all.csv"
|
||||
[1] "spearman for improvement-potential vs. evolution-error"
|
||||
x y
|
||||
x 1 -1
|
||||
y -1 1
|
||||
|
||||
n= 500
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0
|
||||
y 0
|
||||
[1] "spearman for regularity vs. steps"
|
||||
x y
|
||||
x 1.00 -0.02
|
||||
y -0.02 1.00
|
||||
|
||||
n= 500
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0.693
|
||||
y 0.693
|
||||
[1] "spearman for variability vs. evolution-error"
|
||||
x y
|
||||
x 1.00 -0.21
|
||||
y -0.21 1.00
|
||||
|
||||
n= 500
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0
|
||||
y 0
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 7.6 KiB After Width: | Height: | Size: 5.6 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 12 KiB After Width: | Height: | Size: 8.6 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 11 KiB After Width: | Height: | Size: 8.0 KiB |
@ -0,0 +1,101 @@
|
||||
"Evolution error"
|
||||
280.917
|
||||
315.729
|
||||
264.639
|
||||
275.922
|
||||
323.159
|
||||
300.933
|
||||
264.541
|
||||
264.875
|
||||
286.999
|
||||
314.771
|
||||
254.996
|
||||
270.99
|
||||
336.401
|
||||
249.761
|
||||
310.473
|
||||
282.476
|
||||
301.45
|
||||
304.67
|
||||
300.451
|
||||
315.122
|
||||
302.947
|
||||
262.796
|
||||
272.873
|
||||
291.472
|
||||
280.073
|
||||
274.973
|
||||
277.642
|
||||
266.096
|
||||
300.458
|
||||
281.797
|
||||
287.84
|
||||
270.181
|
||||
304.713
|
||||
301.015
|
||||
250.936
|
||||
327.876
|
||||
267.093
|
||||
266.032
|
||||
293.5
|
||||
274.145
|
||||
302.284
|
||||
296.447
|
||||
290.496
|
||||
326.409
|
||||
252.376
|
||||
285.256
|
||||
261.023
|
||||
273.732
|
||||
287.211
|
||||
246.715
|
||||
317.892
|
||||
265.825
|
||||
259.862
|
||||
273.217
|
||||
269.759
|
||||
314.394
|
||||
314.765
|
||||
284.627
|
||||
262.319
|
||||
269.132
|
||||
259.973
|
||||
296.171
|
||||
264.153
|
||||
307.381
|
||||
248.894
|
||||
312.436
|
||||
273.599
|
||||
286.954
|
||||
313.315
|
||||
290.546
|
||||
317.095
|
||||
289.397
|
||||
293.925
|
||||
273.573
|
||||
248.052
|
||||
282.84
|
||||
286.257
|
||||
284.314
|
||||
321.302
|
||||
260.894
|
||||
278.436
|
||||
274.697
|
||||
269.428
|
||||
287.274
|
||||
281.924
|
||||
263.843
|
||||
298.757
|
||||
275.521
|
||||
269.146
|
||||
273.475
|
||||
273.666
|
||||
298.125
|
||||
305.642
|
||||
297.086
|
||||
317.845
|
||||
274.586
|
||||
332.413
|
||||
301.147
|
||||
354.08
|
||||
266.461
|
||||
@ -1,7 +1,7 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:02:32 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_4x7_100Times.csv" every ::1 using 2:5
|
||||
@ -10,16 +10,23 @@ FIT: data read from "20171005-evolution1D_4x7_100Times.csv" every ::1 using 2
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: f(x)
|
||||
f(x)=a*x+b
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda a b
|
||||
0 4.8453053176e+06 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
5 1.6409518325e+05 -9.52e-05 7.07e-06 -3.129336e+03 2.663203e+02
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.84531e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707195
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 164095
|
||||
rel. change during last iteration : -9.51616e-10
|
||||
rel. change during last iteration : -9.51617e-10
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 40.9199
|
||||
@ -27,17 +34,20 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 1674.44
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -3129.34 +/- 2384 (76.19%)
|
||||
b = 266.32 +/- 37.57 (14.11%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
a b
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.994 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:02:32 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_4x7_100Times.csv" every ::1 using 4:5
|
||||
@ -46,16 +56,23 @@ FIT: data read from "20171005-evolution1D_4x7_100Times.csv" every ::1 using 4
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: g(x)
|
||||
g(x)=aa*x+bb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aa bb
|
||||
0 4.8067339365e+06 0.00e+00 9.56e-01 1.000000e+00 1.000000e+00
|
||||
5 1.5824530732e+05 -3.08e-07 9.56e-06 1.317597e+03 -9.801188e+02
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.80673e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.955501
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 158245
|
||||
rel. change during last iteration : -3.0782e-12
|
||||
rel. change during last iteration : -3.07783e-12
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 40.1839
|
||||
@ -63,17 +80,20 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 1614.75
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 1317.6 +/- 566.5 (43%)
|
||||
bb = -980.119 +/- 514.9 (52.53%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aa bb
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:02:32 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_4x7_100Times.csv" every ::1 using 4:6
|
||||
@ -82,12 +102,19 @@ FIT: data read from "20171005-evolution1D_4x7_100Times.csv" every ::1 using 4
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: h(x)
|
||||
h(x)=aaa*x+bbb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
0 8.1385601354e+06 0.00e+00 9.56e-01 1.000000e+00 1.000000e+00
|
||||
5 2.1970491829e+01 -1.63e-02 9.56e-06 -3.136035e+03 3.136342e+03
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 8.13856e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.955501
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 21.9705
|
||||
@ -99,10 +126,13 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 0.224189
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -3136.04 +/- 6.675 (0.2129%)
|
||||
bbb = 3136.34 +/- 6.067 (0.1934%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
@ -1,15 +1,73 @@
|
||||
iter chisq delta/lim lambda a b
|
||||
0 4.8453053176e+06 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
1 1.6709987683e+05 -2.80e+06 7.07e-02 2.525913e+00 2.161942e+02
|
||||
2 1.6667175206e+05 -2.57e+02 7.07e-03 -1.715968e+02 2.199973e+02
|
||||
3 1.6414949666e+05 -1.54e+03 7.07e-04 -2.699906e+03 2.595947e+02
|
||||
4 1.6409518341e+05 -3.31e+01 7.07e-05 -3.128608e+03 2.663089e+02
|
||||
5 1.6409518325e+05 -9.52e-05 7.07e-06 -3.129336e+03 2.663203e+02
|
||||
iter chisq delta/lim lambda a b
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.84531e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707195
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 167100 delta(WSSR)/WSSR : -27.9965
|
||||
delta(WSSR) : -4.67821e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0707195
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = 2.52591
|
||||
b = 216.194
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 166672 delta(WSSR)/WSSR : -0.00256867
|
||||
delta(WSSR) : -428.125 limit for stopping : 1e-05
|
||||
lambda : 0.00707195
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -171.597
|
||||
b = 219.997
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 164149 delta(WSSR)/WSSR : -0.0153656
|
||||
delta(WSSR) : -2522.26 limit for stopping : 1e-05
|
||||
lambda : 0.000707195
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -2699.91
|
||||
b = 259.595
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 164095 delta(WSSR)/WSSR : -0.000330986
|
||||
delta(WSSR) : -54.3133 limit for stopping : 1e-05
|
||||
lambda : 7.07195e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -3128.61
|
||||
b = 266.309
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 164095 delta(WSSR)/WSSR : -9.51617e-10
|
||||
delta(WSSR) : -0.000156156 limit for stopping : 1e-05
|
||||
lambda : 7.07195e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -3129.34
|
||||
b = 266.32
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 164095
|
||||
rel. change during last iteration : -9.51616e-10
|
||||
rel. change during last iteration : -9.51617e-10
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 40.9199
|
||||
@ -17,25 +75,86 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 1674.44
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -3129.34 +/- 2384 (76.19%)
|
||||
b = 266.32 +/- 37.57 (14.11%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
a b
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.994 1.000
|
||||
iter chisq delta/lim lambda aa bb
|
||||
0 4.8067339365e+06 0.00e+00 9.56e-01 1.000000e+00 1.000000e+00
|
||||
1 1.6567425140e+05 -2.80e+06 9.56e-02 1.113320e+02 1.150902e+02
|
||||
2 1.6256126289e+05 -1.91e+03 9.56e-03 3.913863e+02 -1.383578e+02
|
||||
3 1.5824974701e+05 -2.72e+03 9.56e-04 1.287890e+03 -9.531211e+02
|
||||
4 1.5824530732e+05 -2.81e+00 9.56e-05 1.317587e+03 -9.801098e+02
|
||||
5 1.5824530732e+05 -3.08e-07 9.56e-06 1.317597e+03 -9.801188e+02
|
||||
iter chisq delta/lim lambda aa bb
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.80673e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.955501
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 165674 delta(WSSR)/WSSR : -28.0132
|
||||
delta(WSSR) : -4.64106e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0955501
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 111.332
|
||||
bb = 115.09
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 162561 delta(WSSR)/WSSR : -0.0191496
|
||||
delta(WSSR) : -3112.99 limit for stopping : 1e-05
|
||||
lambda : 0.00955501
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 391.386
|
||||
bb = -138.358
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 158250 delta(WSSR)/WSSR : -0.027245
|
||||
delta(WSSR) : -4311.52 limit for stopping : 1e-05
|
||||
lambda : 0.000955501
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 1287.89
|
||||
bb = -953.121
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 158245 delta(WSSR)/WSSR : -2.80558e-05
|
||||
delta(WSSR) : -4.43969 limit for stopping : 1e-05
|
||||
lambda : 9.55501e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 1317.59
|
||||
bb = -980.11
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 158245 delta(WSSR)/WSSR : -3.07783e-12
|
||||
delta(WSSR) : -4.87053e-07 limit for stopping : 1e-05
|
||||
lambda : 9.55501e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 1317.6
|
||||
bb = -980.119
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 158245
|
||||
rel. change during last iteration : -3.0782e-12
|
||||
rel. change during last iteration : -3.07783e-12
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 40.1839
|
||||
@ -43,21 +162,82 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 1614.75
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 1317.6 +/- 566.5 (43%)
|
||||
bb = -980.119 +/- 514.9 (52.53%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aa bb
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
0 8.1385601354e+06 0.00e+00 9.56e-01 1.000000e+00 1.000000e+00
|
||||
1 5.3975388072e+04 -1.50e+07 9.56e-02 1.319509e+02 1.649079e+02
|
||||
2 3.1741255515e+04 -7.00e+04 9.56e-03 -6.251153e+02 8.543613e+02
|
||||
3 5.4599157975e+01 -5.80e+07 9.56e-04 -3.055503e+03 3.063152e+03
|
||||
4 2.1970495409e+01 -1.49e+05 9.56e-05 -3.136008e+03 3.136318e+03
|
||||
5 2.1970491829e+01 -1.63e-02 9.56e-06 -3.136035e+03 3.136342e+03
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 8.13856e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.955501
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 53975.4 delta(WSSR)/WSSR : -149.783
|
||||
delta(WSSR) : -8.08458e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0955501
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = 131.951
|
||||
bbb = 164.908
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 31741.3 delta(WSSR)/WSSR : -0.700481
|
||||
delta(WSSR) : -22234.1 limit for stopping : 1e-05
|
||||
lambda : 0.00955501
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -625.115
|
||||
bbb = 854.361
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 54.5992 delta(WSSR)/WSSR : -580.351
|
||||
delta(WSSR) : -31686.7 limit for stopping : 1e-05
|
||||
lambda : 0.000955501
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3055.5
|
||||
bbb = 3063.15
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 21.9705 delta(WSSR)/WSSR : -1.48511
|
||||
delta(WSSR) : -32.6287 limit for stopping : 1e-05
|
||||
lambda : 9.55501e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3136.01
|
||||
bbb = 3136.32
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 21.9705 delta(WSSR)/WSSR : -1.62953e-07
|
||||
delta(WSSR) : -3.58016e-06 limit for stopping : 1e-05
|
||||
lambda : 9.55501e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3136.04
|
||||
bbb = 3136.34
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 21.9705
|
||||
@ -69,10 +249,13 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 0.224189
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -3136.04 +/- 6.675 (0.2129%)
|
||||
bbb = 3136.34 +/- 6.067 (0.1934%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
@ -2,19 +2,19 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171005-evolution1D_4x7_100Times.csv" every ::1 using 2:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171005-evolution1D_4x7_100Times_regularity-vs-steps.png"
|
||||
plot "20171005-evolution1D_4x7_100Times.csv" every ::1 using 2:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171005-evolution1D_4x7_100Times.csv" every ::1 using 4:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171005-evolution1D_4x7_100Times_improvement-vs-steps.png"
|
||||
plot "20171005-evolution1D_4x7_100Times.csv" every ::1 using 4:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171005-evolution1D_4x7_100Times.csv" every ::1 using 4:6 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Fitting error'
|
||||
set output "20171005-evolution1D_4x7_100Times_improvement-vs-evo-error.png"
|
||||
plot "20171005-evolution1D_4x7_100Times.csv" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
|
||||
@ -0,0 +1,37 @@
|
||||
[1] "================ Analyzing 20171005-evolution1D_4x7_100Times.csv"
|
||||
[1] "spearman for improvement-potential vs. evolution-error"
|
||||
x y
|
||||
x 1 -1
|
||||
y -1 1
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0
|
||||
y 0
|
||||
[1] "spearman for regularity vs. steps"
|
||||
x y
|
||||
x 1.0 -0.1
|
||||
y -0.1 1.0
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0.3019
|
||||
y 0.3019
|
||||
[1] "spearman for variability vs. evolution-error"
|
||||
x y
|
||||
x 1 NaN
|
||||
y NaN 1
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x
|
||||
y
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 5.8 KiB After Width: | Height: | Size: 5.6 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 5.5 KiB After Width: | Height: | Size: 5.5 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 5.2 KiB After Width: | Height: | Size: 5.4 KiB |
@ -0,0 +1,101 @@
|
||||
"Evolution error"
|
||||
211.096
|
||||
233.828
|
||||
205.276
|
||||
261.016
|
||||
205.753
|
||||
244.494
|
||||
236.857
|
||||
243.624
|
||||
227.071
|
||||
228.254
|
||||
219.293
|
||||
235.159
|
||||
240.691
|
||||
232.853
|
||||
243.665
|
||||
242.766
|
||||
243.618
|
||||
238.051
|
||||
224.685
|
||||
206.919
|
||||
266.62
|
||||
229.771
|
||||
241.243
|
||||
228.75
|
||||
246.415
|
||||
245.936
|
||||
234.603
|
||||
230.971
|
||||
246.319
|
||||
235.173
|
||||
250.199
|
||||
240.854
|
||||
233.456
|
||||
216.659
|
||||
240.033
|
||||
244.108
|
||||
216.874
|
||||
242.058
|
||||
221.484
|
||||
222.485
|
||||
239.78
|
||||
232.709
|
||||
230.785
|
||||
229.968
|
||||
235.149
|
||||
233.462
|
||||
241.027
|
||||
229.139
|
||||
210.309
|
||||
222.927
|
||||
236.762
|
||||
244.312
|
||||
225.283
|
||||
228.831
|
||||
234.735
|
||||
222.154
|
||||
215.144
|
||||
247.533
|
||||
242.563
|
||||
231.706
|
||||
245.743
|
||||
233.422
|
||||
221.213
|
||||
223.48
|
||||
234.243
|
||||
246.759
|
||||
225.232
|
||||
233.179
|
||||
256.94
|
||||
237.977
|
||||
238.547
|
||||
254.967
|
||||
223.3
|
||||
243.823
|
||||
240.056
|
||||
220.234
|
||||
242.633
|
||||
244.981
|
||||
244.803
|
||||
241.898
|
||||
222.32
|
||||
232.013
|
||||
228.661
|
||||
241.097
|
||||
225.772
|
||||
243.746
|
||||
209.245
|
||||
235.881
|
||||
241.881
|
||||
231.035
|
||||
220.946
|
||||
212.015
|
||||
234.886
|
||||
234.38
|
||||
250.999
|
||||
229.239
|
||||
222.041
|
||||
208.038
|
||||
217.716
|
||||
220.769
|
||||
@ -1,7 +1,7 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:02:37 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_7x4_100Times.csv" every ::1 using 2:5
|
||||
@ -10,12 +10,19 @@ FIT: data read from "20171005-evolution1D_7x4_100Times.csv" every ::1 using 2
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: f(x)
|
||||
f(x)=a*x+b
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda a b
|
||||
0 4.2059624024e+06 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
5 1.6157855782e+05 -1.28e-04 7.07e-06 -3.703035e+03 2.609538e+02
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.20596e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707197
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 161579
|
||||
@ -27,17 +34,20 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 1648.76
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -3703.04 +/- 2343 (63.28%)
|
||||
b = 260.954 +/- 37.51 (14.38%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
a b
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.994 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:02:37 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4:5
|
||||
@ -46,12 +56,19 @@ FIT: data read from "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: g(x)
|
||||
g(x)=aa*x+bb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aa bb
|
||||
0 4.1694597860e+06 0.00e+00 9.64e-01 1.000000e+00 1.000000e+00
|
||||
5 1.6088124752e+05 -2.98e-05 9.64e-06 1.779074e+03 -1.445031e+03
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.16946e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.963614
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 160881
|
||||
@ -63,17 +80,20 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 1641.65
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 1779.07 +/- 1039 (58.39%)
|
||||
bb = -1445.03 +/- 961.8 (66.56%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aa bb
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:02:37 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4:6
|
||||
@ -82,12 +102,19 @@ FIT: data read from "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: h(x)
|
||||
h(x)=aaa*x+bbb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
0 5.3588910602e+06 0.00e+00 9.64e-01 1.000000e+00 1.000000e+00
|
||||
6 5.4694656646e+00 -5.96e-09 9.64e-07 -3.141932e+03 3.141867e+03
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 5.35889e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.963614
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 5.46947
|
||||
@ -99,10 +126,13 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 0.0558109
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -3141.93 +/- 6.057 (0.1928%)
|
||||
bbb = 3141.87 +/- 5.608 (0.1785%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
@ -1,11 +1,69 @@
|
||||
iter chisq delta/lim lambda a b
|
||||
0 4.2059624024e+06 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
1 1.6580035617e+05 -2.44e+06 7.07e-02 1.958416e+00 2.009886e+02
|
||||
2 1.6524678185e+05 -3.35e+02 7.07e-03 -2.078184e+02 2.053272e+02
|
||||
3 1.6165337078e+05 -2.22e+03 7.07e-04 -3.203881e+03 2.530098e+02
|
||||
4 1.6157855802e+05 -4.63e+01 7.07e-05 -3.702205e+03 2.609406e+02
|
||||
5 1.6157855782e+05 -1.28e-04 7.07e-06 -3.703035e+03 2.609538e+02
|
||||
iter chisq delta/lim lambda a b
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.20596e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707197
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 165800 delta(WSSR)/WSSR : -24.3676
|
||||
delta(WSSR) : -4.04016e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0707197
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = 1.95842
|
||||
b = 200.989
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 165247 delta(WSSR)/WSSR : -0.00334999
|
||||
delta(WSSR) : -553.574 limit for stopping : 1e-05
|
||||
lambda : 0.00707197
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -207.818
|
||||
b = 205.327
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 161653 delta(WSSR)/WSSR : -0.0222291
|
||||
delta(WSSR) : -3593.41 limit for stopping : 1e-05
|
||||
lambda : 0.000707197
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -3203.88
|
||||
b = 253.01
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 161579 delta(WSSR)/WSSR : -0.000463012
|
||||
delta(WSSR) : -74.8128 limit for stopping : 1e-05
|
||||
lambda : 7.07197e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -3702.21
|
||||
b = 260.941
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 161579 delta(WSSR)/WSSR : -1.2809e-09
|
||||
delta(WSSR) : -0.000206966 limit for stopping : 1e-05
|
||||
lambda : 7.07197e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -3703.04
|
||||
b = 260.954
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 161579
|
||||
@ -17,21 +75,82 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 1648.76
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -3703.04 +/- 2343 (63.28%)
|
||||
b = 260.954 +/- 37.51 (14.38%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
a b
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.994 1.000
|
||||
iter chisq delta/lim lambda aa bb
|
||||
0 4.1694597860e+06 0.00e+00 9.64e-01 1.000000e+00 1.000000e+00
|
||||
1 1.6525762522e+05 -2.42e+06 9.64e-02 1.017401e+02 1.068470e+02
|
||||
2 1.6449315575e+05 -4.65e+02 9.64e-03 2.381672e+02 -1.846147e+01
|
||||
3 1.6091869157e+05 -2.22e+03 9.64e-04 1.622183e+03 -1.299781e+03
|
||||
4 1.6088124757e+05 -2.33e+01 9.64e-05 1.778896e+03 -1.444867e+03
|
||||
5 1.6088124752e+05 -2.98e-05 9.64e-06 1.779074e+03 -1.445031e+03
|
||||
iter chisq delta/lim lambda aa bb
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.16946e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.963614
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 165258 delta(WSSR)/WSSR : -24.2301
|
||||
delta(WSSR) : -4.0042e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0963614
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 101.74
|
||||
bb = 106.847
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 164493 delta(WSSR)/WSSR : -0.00464742
|
||||
delta(WSSR) : -764.469 limit for stopping : 1e-05
|
||||
lambda : 0.00963614
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 238.167
|
||||
bb = -18.4615
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 160919 delta(WSSR)/WSSR : -0.0222129
|
||||
delta(WSSR) : -3574.46 limit for stopping : 1e-05
|
||||
lambda : 0.000963614
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 1622.18
|
||||
bb = -1299.78
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 160881 delta(WSSR)/WSSR : -0.000232743
|
||||
delta(WSSR) : -37.444 limit for stopping : 1e-05
|
||||
lambda : 9.63614e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 1778.9
|
||||
bb = -1444.87
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 160881 delta(WSSR)/WSSR : -2.98408e-10
|
||||
delta(WSSR) : -4.80083e-05 limit for stopping : 1e-05
|
||||
lambda : 9.63614e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 1779.07
|
||||
bb = -1445.03
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 160881
|
||||
@ -43,22 +162,93 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 1641.65
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 1779.07 +/- 1039 (58.39%)
|
||||
bb = -1445.03 +/- 961.8 (66.56%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aa bb
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
0 5.3588910602e+06 0.00e+00 9.64e-01 1.000000e+00 1.000000e+00
|
||||
1 1.6257651642e+04 -3.29e+07 9.64e-02 1.127845e+02 1.275042e+02
|
||||
2 1.3617851160e+04 -1.94e+04 9.64e-03 -1.505284e+02 3.724288e+02
|
||||
3 1.4658675724e+02 -9.19e+06 9.64e-04 -2.837355e+03 2.859890e+03
|
||||
4 5.4696465957e+00 -2.58e+06 9.64e-05 -3.141588e+03 3.141548e+03
|
||||
5 5.4694656646e+00 -3.31e+00 9.64e-06 -3.141932e+03 3.141867e+03
|
||||
6 5.4694656646e+00 -5.96e-09 9.64e-07 -3.141932e+03 3.141867e+03
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 5.35889e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.963614
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 16257.7 delta(WSSR)/WSSR : -328.623
|
||||
delta(WSSR) : -5.34263e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0963614
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = 112.784
|
||||
bbb = 127.504
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 13617.9 delta(WSSR)/WSSR : -0.193849
|
||||
delta(WSSR) : -2639.8 limit for stopping : 1e-05
|
||||
lambda : 0.00963614
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -150.528
|
||||
bbb = 372.429
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 146.587 delta(WSSR)/WSSR : -91.8996
|
||||
delta(WSSR) : -13471.3 limit for stopping : 1e-05
|
||||
lambda : 0.000963614
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -2837.35
|
||||
bbb = 2859.89
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 5.46965 delta(WSSR)/WSSR : -25.8
|
||||
delta(WSSR) : -141.117 limit for stopping : 1e-05
|
||||
lambda : 9.63614e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3141.59
|
||||
bbb = 3141.55
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 5.46947 delta(WSSR)/WSSR : -3.30802e-05
|
||||
delta(WSSR) : -0.000180931 limit for stopping : 1e-05
|
||||
lambda : 9.63614e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3141.93
|
||||
bbb = 3141.87
|
||||
/
|
||||
|
||||
Iteration 6
|
||||
WSSR : 5.46947 delta(WSSR)/WSSR : -5.95966e-14
|
||||
delta(WSSR) : -3.25961e-13 limit for stopping : 1e-05
|
||||
lambda : 9.63614e-07
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3141.93
|
||||
bbb = 3141.87
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 5.46947
|
||||
@ -70,10 +260,13 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 0.0558109
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -3141.93 +/- 6.057 (0.1928%)
|
||||
bbb = 3141.87 +/- 5.608 (0.1785%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
@ -2,19 +2,19 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171005-evolution1D_7x4_100Times.csv" every ::1 using 2:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171005-evolution1D_7x4_100Times_regularity-vs-steps.png"
|
||||
plot "20171005-evolution1D_7x4_100Times.csv" every ::1 using 2:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171005-evolution1D_7x4_100Times_improvement-vs-steps.png"
|
||||
plot "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4:6 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Fitting error'
|
||||
set output "20171005-evolution1D_7x4_100Times_improvement-vs-evo-error.png"
|
||||
plot "20171005-evolution1D_7x4_100Times.csv" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
|
||||
@ -0,0 +1,37 @@
|
||||
[1] "================ Analyzing 20171005-evolution1D_7x4_100Times.csv"
|
||||
[1] "spearman for improvement-potential vs. evolution-error"
|
||||
x y
|
||||
x 1 -1
|
||||
y -1 1
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0
|
||||
y 0
|
||||
[1] "spearman for regularity vs. steps"
|
||||
x y
|
||||
x 1.00 -0.21
|
||||
y -0.21 1.00
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0.0396
|
||||
y 0.0396
|
||||
[1] "spearman for variability vs. evolution-error"
|
||||
x y
|
||||
x 1 NaN
|
||||
y NaN 1
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x
|
||||
y
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 6.0 KiB After Width: | Height: | Size: 5.9 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 5.5 KiB After Width: | Height: | Size: 5.6 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 5.1 KiB After Width: | Height: | Size: 5.2 KiB |
@ -0,0 +1,101 @@
|
||||
"Evolution error"
|
||||
126.241
|
||||
110.962
|
||||
125.853
|
||||
140.195
|
||||
126.647
|
||||
154.539
|
||||
107.206
|
||||
128.558
|
||||
136.77
|
||||
145.941
|
||||
171.996
|
||||
118.437
|
||||
143.556
|
||||
120.873
|
||||
105.887
|
||||
154.67
|
||||
154.182
|
||||
116.314
|
||||
113.496
|
||||
159.92
|
||||
158.727
|
||||
108.387
|
||||
148.334
|
||||
112.767
|
||||
139.428
|
||||
124.479
|
||||
106.309
|
||||
139.721
|
||||
133.951
|
||||
135.062
|
||||
133.884
|
||||
120.051
|
||||
101.318
|
||||
135.279
|
||||
110.051
|
||||
136.437
|
||||
134.697
|
||||
113.78
|
||||
122.484
|
||||
114.487
|
||||
127.55
|
||||
125.629
|
||||
162.041
|
||||
156.364
|
||||
113.788
|
||||
138.26
|
||||
109.996
|
||||
164.442
|
||||
105.711
|
||||
156.553
|
||||
116.304
|
||||
113.339
|
||||
118.637
|
||||
164.957
|
||||
97.1774
|
||||
137.814
|
||||
158.652
|
||||
128.639
|
||||
144.853
|
||||
136.728
|
||||
100.103
|
||||
129.972
|
||||
134.171
|
||||
102.086
|
||||
137.823
|
||||
120.165
|
||||
121.511
|
||||
110.067
|
||||
112.614
|
||||
105.271
|
||||
140.821
|
||||
124.285
|
||||
158.103
|
||||
140.515
|
||||
101.64
|
||||
129.887
|
||||
167.194
|
||||
110.881
|
||||
146.669
|
||||
118.035
|
||||
150.583
|
||||
143.211
|
||||
114.785
|
||||
146.421
|
||||
130.875
|
||||
107.373
|
||||
152.164
|
||||
129.282
|
||||
98.1416
|
||||
129.997
|
||||
117
|
||||
111.092
|
||||
114.087
|
||||
107.558
|
||||
144.45
|
||||
118.484
|
||||
109.701
|
||||
126.593
|
||||
168.971
|
||||
143.838
|
||||
@ -1,7 +1,7 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:22:52 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_7x7_100Times.csv" every ::1 using 2:5
|
||||
@ -10,16 +10,23 @@ FIT: data read from "20171005-evolution1D_7x7_100Times.csv" every ::1 using 2
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: f(x)
|
||||
f(x)=a*x+b
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda a b
|
||||
0 5.1103239746e+06 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
5 1.3279798348e+05 -2.35e-06 7.07e-06 -5.771314e+02 2.408587e+02
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 5.11032e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707405
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 132798
|
||||
rel. change during last iteration : -2.35102e-11
|
||||
rel. change during last iteration : -2.35098e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 36.8114
|
||||
@ -27,17 +34,20 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 1355.08
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -577.131 +/- 1945 (337%)
|
||||
b = 240.859 +/- 56.49 (23.46%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
a b
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.998 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:22:52 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_7x7_100Times.csv" every ::1 using 4:5
|
||||
@ -46,12 +56,19 @@ FIT: data read from "20171005-evolution1D_7x7_100Times.csv" every ::1 using 4
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: g(x)
|
||||
g(x)=aa*x+bb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aa bb
|
||||
0 5.0689010815e+06 0.00e+00 9.80e-01 1.000000e+00 1.000000e+00
|
||||
5 9.8040471485e+04 -1.51e-05 9.80e-06 3.134345e+03 -2.780953e+03
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 5.0689e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.979606
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 98040.5
|
||||
@ -63,17 +80,20 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 1000.41
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 3134.35 +/- 530.8 (16.94%)
|
||||
bb = -2780.95 +/- 509 (18.3%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aa bb
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Thu Oct 5 14:22:52 2017
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171005-evolution1D_7x7_100Times.csv" every ::1 using 4:6
|
||||
@ -82,12 +102,19 @@ FIT: data read from "20171005-evolution1D_7x7_100Times.csv" every ::1 using 4
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: h(x)
|
||||
h(x)=aaa*x+bbb
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
0 1.6606716013e+06 0.00e+00 9.80e-01 1.000000e+00 1.000000e+00
|
||||
5 3.7498507724e+00 -4.46e-01 9.80e-06 -3.142464e+03 3.142323e+03
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 1.66067e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.979606
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 3.74985
|
||||
@ -99,10 +126,13 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 0.0382638
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -3142.46 +/- 3.283 (0.1045%)
|
||||
bbb = 3142.32 +/- 3.148 (0.1002%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
@ -1,15 +1,73 @@
|
||||
iter chisq delta/lim lambda a b
|
||||
0 5.1103239746e+06 0.00e+00 7.07e-01 1.000000e+00 1.000000e+00
|
||||
1 1.3304344126e+05 -3.74e+06 7.07e-02 7.011364e+00 2.228167e+02
|
||||
2 1.3290446272e+05 -1.05e+02 7.07e-03 -3.195295e+01 2.250561e+02
|
||||
3 1.3279958538e+05 -7.90e+01 7.07e-04 -5.102627e+02 2.389204e+02
|
||||
4 1.3279798349e+05 -1.21e+00 7.07e-05 -5.770380e+02 2.408559e+02
|
||||
5 1.3279798348e+05 -2.35e-06 7.07e-06 -5.771314e+02 2.408587e+02
|
||||
iter chisq delta/lim lambda a b
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 5.11032e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707405
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 133043 delta(WSSR)/WSSR : -37.4109
|
||||
delta(WSSR) : -4.97728e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0707405
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = 7.01136
|
||||
b = 222.817
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 132904 delta(WSSR)/WSSR : -0.0010457
|
||||
delta(WSSR) : -138.979 limit for stopping : 1e-05
|
||||
lambda : 0.00707405
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -31.953
|
||||
b = 225.056
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 132800 delta(WSSR)/WSSR : -0.000789741
|
||||
delta(WSSR) : -104.877 limit for stopping : 1e-05
|
||||
lambda : 0.000707405
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -510.263
|
||||
b = 238.92
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 132798 delta(WSSR)/WSSR : -1.20626e-05
|
||||
delta(WSSR) : -1.60189 limit for stopping : 1e-05
|
||||
lambda : 7.07405e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -577.038
|
||||
b = 240.856
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 132798 delta(WSSR)/WSSR : -2.35098e-11
|
||||
delta(WSSR) : -3.12206e-06 limit for stopping : 1e-05
|
||||
lambda : 7.07405e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -577.131
|
||||
b = 240.859
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 132798
|
||||
rel. change during last iteration : -2.35102e-11
|
||||
rel. change during last iteration : -2.35098e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 36.8114
|
||||
@ -17,21 +75,82 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 1355.08
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -577.131 +/- 1945 (337%)
|
||||
b = 240.859 +/- 56.49 (23.46%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
a b
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.998 1.000
|
||||
iter chisq delta/lim lambda aa bb
|
||||
0 5.0689010815e+06 0.00e+00 9.80e-01 1.000000e+00 1.000000e+00
|
||||
1 1.3046686978e+05 -3.79e+06 9.80e-02 1.172773e+02 1.106372e+02
|
||||
2 1.2074716009e+05 -8.05e+03 9.80e-03 6.053195e+02 -3.561808e+02
|
||||
3 9.8095704395e+04 -2.31e+04 9.80e-04 3.009614e+03 -2.661363e+03
|
||||
4 9.8040471500e+04 -5.63e+01 9.80e-05 3.134281e+03 -2.780891e+03
|
||||
5 9.8040471485e+04 -1.51e-05 9.80e-06 3.134345e+03 -2.780953e+03
|
||||
iter chisq delta/lim lambda aa bb
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 5.0689e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.979606
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 130467 delta(WSSR)/WSSR : -37.852
|
||||
delta(WSSR) : -4.93843e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0979606
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 117.277
|
||||
bb = 110.637
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 120747 delta(WSSR)/WSSR : -0.0804964
|
||||
delta(WSSR) : -9719.71 limit for stopping : 1e-05
|
||||
lambda : 0.00979606
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 605.319
|
||||
bb = -356.181
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 98095.7 delta(WSSR)/WSSR : -0.230912
|
||||
delta(WSSR) : -22651.5 limit for stopping : 1e-05
|
||||
lambda : 0.000979606
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 3009.61
|
||||
bb = -2661.36
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 98040.5 delta(WSSR)/WSSR : -0.000563368
|
||||
delta(WSSR) : -55.2329 limit for stopping : 1e-05
|
||||
lambda : 9.79606e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 3134.28
|
||||
bb = -2780.89
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 98040.5 delta(WSSR)/WSSR : -1.51467e-10
|
||||
delta(WSSR) : -1.48499e-05 limit for stopping : 1e-05
|
||||
lambda : 9.79606e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 3134.35
|
||||
bb = -2780.95
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 98040.5
|
||||
@ -43,21 +162,82 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 1000.41
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 3134.35 +/- 530.8 (16.94%)
|
||||
bb = -2780.95 +/- 509 (18.3%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aa bb
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
0 1.6606716013e+06 0.00e+00 9.80e-01 1.000000e+00 1.000000e+00
|
||||
1 3.6419319985e+04 -4.46e+06 9.80e-02 5.817813e+01 7.298767e+01
|
||||
2 2.5572102437e+04 -4.24e+04 9.80e-03 -4.588023e+02 5.692906e+02
|
||||
3 6.5943618679e+01 -3.87e+07 9.80e-04 -3.010106e+03 3.015422e+03
|
||||
4 3.7498674938e+00 -1.66e+06 9.80e-05 -3.142395e+03 3.142258e+03
|
||||
5 3.7498507724e+00 -4.46e-01 9.80e-06 -3.142464e+03 3.142323e+03
|
||||
iter chisq delta/lim lambda aaa bbb
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 1.66067e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.979606
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 36419.3 delta(WSSR)/WSSR : -44.5986
|
||||
delta(WSSR) : -1.62425e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0979606
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = 58.1781
|
||||
bbb = 72.9877
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 25572.1 delta(WSSR)/WSSR : -0.424182
|
||||
delta(WSSR) : -10847.2 limit for stopping : 1e-05
|
||||
lambda : 0.00979606
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -458.802
|
||||
bbb = 569.291
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 65.9436 delta(WSSR)/WSSR : -386.787
|
||||
delta(WSSR) : -25506.2 limit for stopping : 1e-05
|
||||
lambda : 0.000979606
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3010.11
|
||||
bbb = 3015.42
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 3.74987 delta(WSSR)/WSSR : -16.5856
|
||||
delta(WSSR) : -62.1938 limit for stopping : 1e-05
|
||||
lambda : 9.79606e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3142.4
|
||||
bbb = 3142.26
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 3.74985 delta(WSSR)/WSSR : -4.45921e-06
|
||||
delta(WSSR) : -1.67214e-05 limit for stopping : 1e-05
|
||||
lambda : 9.79606e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3142.46
|
||||
bbb = 3142.32
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 3.74985
|
||||
@ -69,10 +249,13 @@ variance of residuals (reduced chisquare) = WSSR/ndf : 0.0382638
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -3142.46 +/- 3.283 (0.1045%)
|
||||
bbb = 3142.32 +/- 3.148 (0.1002%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
aaa bbb
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
|
||||
@ -2,19 +2,19 @@ set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171005-evolution1D_7x7_100Times.csv" every ::1 using 2:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'regularity'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171005-evolution1D_7x7_100Times_regularity-vs-steps.png"
|
||||
plot "20171005-evolution1D_7x7_100Times.csv" every ::1 using 2:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171005-evolution1D_7x7_100Times.csv" every ::1 using 4:5 via aa,bb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'steps'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171005-evolution1D_7x7_100Times_improvement-vs-steps.png"
|
||||
plot "20171005-evolution1D_7x7_100Times.csv" every ::1 using 4:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171005-evolution1D_7x7_100Times.csv" every ::1 using 4:6 via aaa,bbb
|
||||
set xlabel 'improvement potential'
|
||||
set ylabel 'evolution error'
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Fitting error'
|
||||
set output "20171005-evolution1D_7x7_100Times_improvement-vs-evo-error.png"
|
||||
plot "20171005-evolution1D_7x7_100Times.csv" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
|
||||
@ -0,0 +1,37 @@
|
||||
[1] "================ Analyzing 20171005-evolution1D_7x7_100Times.csv"
|
||||
[1] "spearman for improvement-potential vs. evolution-error"
|
||||
x y
|
||||
x 1 -1
|
||||
y -1 1
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0
|
||||
y 0
|
||||
[1] "spearman for regularity vs. steps"
|
||||
x y
|
||||
x 1.00 -0.01
|
||||
y -0.01 1.00
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0.9216
|
||||
y 0.9216
|
||||
[1] "spearman for variability vs. evolution-error"
|
||||
x y
|
||||
x 1 NaN
|
||||
y NaN 1
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x
|
||||
y
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 5.4 KiB After Width: | Height: | Size: 5.3 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 5.8 KiB After Width: | Height: | Size: 5.9 KiB |
Binary file not shown.
|
Before Width: | Height: | Size: 5.5 KiB After Width: | Height: | Size: 5.7 KiB |
@ -0,0 +1,111 @@
|
||||
"Least squares",regularity,variability,improvement,steps,"Evolution error",sigma
|
||||
284.365,0.0136315,0.00124444,0.967997,202,298.423,0.0463019
|
||||
271.226,0.0124703,0.00124444,0.969475,286,284.695,0.0232577
|
||||
321.902,0.0116571,0.00124444,0.963772,203,337.628,0.0416545
|
||||
265.327,0.0106321,0.00124444,0.970139,254,278.241,0.0468512
|
||||
252.821,0.0130542,0.00124444,0.971547,185,264.793,0.0375129
|
||||
245.664,0.0125761,0.00124444,0.972353,248,257.7,0.0374176
|
||||
261.824,0.0118357,0.00124444,0.970567,202,274.784,0.0273035
|
||||
274.7,0.0100903,0.00124444,0.969116,291,287.743,0.0552393
|
||||
291.863,0.0131507,0.00124444,0.967199,186,306.328,0.0467986
|
||||
269.959,0.01103,0.00124444,0.969618,259,283.047,0.0412
|
||||
275.979,0.0134071,0.00124444,0.96894,273,289.659,0.0307383
|
||||
238.92,0.0128211,0.00124444,0.973138,242,250.664,0.0280029
|
||||
249.451,0.0146911,0.00124444,0.971926,295,261.859,0.0169273
|
||||
305.491,0.014604,0.00124444,0.965637,194,320.352,0.0577861
|
||||
288.014,0.0139405,0.00124444,0.967586,196,302.292,0.0452684
|
||||
338.043,0.0131414,0.00124444,0.961956,291,354.924,0.0488456
|
||||
278.968,0.0128255,0.00124444,0.968604,263,292.181,0.0350694
|
||||
272.195,0.0122229,0.00124444,0.969373,222,285.759,0.0382185
|
||||
240.208,0.0129601,0.00124444,0.972996,260,252.184,0.034162
|
||||
301.799,0.0137701,0.00124444,0.966034,209,316.796,0.0310414
|
||||
269.092,0.0138025,0.00124444,0.969715,237,282.546,0.0347684
|
||||
296.74,0.0105778,0.00124444,0.966604,231,311.274,0.0300026
|
||||
232.041,0.0140952,0.00124444,0.973885,249,242.707,0.0435354
|
||||
253.458,0.0111011,0.00124444,0.971475,227,265.12,0.0549504
|
||||
279.053,0.0121752,0.00124444,0.968594,189,292.53,0.0338526
|
||||
357.783,0.0144251,0.00124444,0.959734,173,373.645,0.062108
|
||||
253.292,0.0133291,0.00124444,0.971494,169,265.231,0.0491994
|
||||
323.812,0.0122242,0.00124444,0.963557,220,339.851,0.0301496
|
||||
316.499,0.0118804,0.00124444,0.96438,240,331.492,0.0588588
|
||||
283.24,0.0116293,0.00124444,0.968123,211,296.143,0.054793
|
||||
255.606,0.0122573,0.00124444,0.971233,304,267.902,0.0353475
|
||||
295.028,0.010363,0.00124444,0.966796,178,309.679,0.0482631
|
||||
257.028,0.0083189,0.00124444,0.971073,225,269.797,0.0344004
|
||||
258.367,0.0117439,0.00124444,0.970922,220,269.874,0.0401674
|
||||
299.638,0.0160765,0.00124444,0.966278,199,314.378,0.0648766
|
||||
261.133,0.0133491,0.00124444,0.970655,217,273.406,0.0612996
|
||||
258.095,0.0131587,0.00124444,0.970953,316,270.657,0.056618
|
||||
295.711,0.010812,0.00124444,0.96672,225,310.459,0.0473272
|
||||
235.913,0.0147284,0.00124444,0.973449,266,247.483,0.0249892
|
||||
261.455,0.013335,0.00124444,0.970575,283,274.461,0.016123
|
||||
260.914,0.0130128,0.00124444,0.970639,228,273.334,0.0454057
|
||||
274.414,0.0122356,0.00124444,0.969116,268,288.058,0.0308934
|
||||
286.019,0.0115339,0.00124444,0.96781,227,299.622,0.0403952
|
||||
277.458,0.0105674,0.00124444,0.968774,264,291.267,0.0356097
|
||||
240.979,0.0120099,0.00124444,0.972879,236,252.976,0.0191082
|
||||
262.478,0.0115369,0.00124444,0.97046,309,275.311,0.0367373
|
||||
267.337,0.0112152,0.00124444,0.969913,361,280.607,0.0321421
|
||||
257.301,0.0132868,0.00124444,0.971042,270,270.017,0.0269151
|
||||
288.91,0.0148347,0.00124444,0.967485,254,303.237,0.0235924
|
||||
272.936,0.0113799,0.00124444,0.969283,295,286.265,0.0316973
|
||||
341.566,0.010463,0.00124444,0.961559,258,358.606,0.0274781
|
||||
286.135,0.0124676,0.00124444,0.967797,229,300.357,0.0354075
|
||||
248.633,0.0129678,0.00124444,0.972018,175,260.384,0.0565796
|
||||
260.903,0.0127077,0.00124444,0.970637,211,271.183,0.0558095
|
||||
262.906,0.0141616,0.00124444,0.970412,283,275.937,0.0282904
|
||||
325.249,0.0119214,0.00124444,0.963395,212,340.822,0.0349593
|
||||
326.696,0.0107315,0.00124444,0.963232,263,342.87,0.026237
|
||||
235.383,0.00721808,0.00124444,0.973509,285,247.036,0.0280001
|
||||
291.26,0.00941284,0.00124444,0.96722,231,305.313,0.0373272
|
||||
346.221,0.0115527,0.00124444,0.961148,143,362.535,0.0570737
|
||||
278.604,0.0119867,0.00124444,0.968757,237,292.104,0.0510293
|
||||
257.624,0.015389,0.00124444,0.971008,187,270.485,0.0472684
|
||||
310.128,0.0117237,0.00124444,0.965098,294,325.329,0.0283465
|
||||
262.715,0.00991148,0.00124444,0.970433,312,275.62,0.0275899
|
||||
233.759,0.0120007,0.00124444,0.973692,251,245.371,0.0331032
|
||||
283.341,0.0167926,0.00124444,0.968112,202,296.747,0.049088
|
||||
273.407,0.0118834,0.00124444,0.96923,192,285.701,0.0599774
|
||||
301.436,0.00911246,0.00124444,0.966075,207,315.472,0.0515595
|
||||
249.385,0.0134275,0.00124444,0.971933,202,261.363,0.0456747
|
||||
275.337,0.0146336,0.00124444,0.969013,246,288.343,0.0325241
|
||||
242.551,0.0118938,0.00124444,0.972703,259,253.537,0.0439554
|
||||
336.977,0.0123799,0.00124444,0.962078,328,353.546,0.0416258
|
||||
259.907,0.0130097,0.00124444,0.970749,231,272.705,0.0296309
|
||||
255.45,0.015162,0.00124444,0.971251,164,267.961,0.0854988
|
||||
258.502,0.0125001,0.00124444,0.970907,247,269.917,0.0547566
|
||||
289.38,0.0139735,0.00124444,0.967432,166,303.207,0.075952
|
||||
267.126,0.00824213,0.00124444,0.969937,292,280.342,0.0378409
|
||||
275.035,0.00992348,0.00124444,0.969047,257,288.78,0.0253235
|
||||
315.806,0.0120417,0.00124444,0.964458,283,330.349,0.0701877
|
||||
284.213,0.0120468,0.00124444,0.968014,211,297.971,0.0406944
|
||||
287.896,0.0128398,0.00124444,0.967712,225,302.104,0.03425
|
||||
272.258,0.0107615,0.00124444,0.969359,270,285.659,0.0413873
|
||||
297.724,0.0160692,0.00124444,0.966494,184,311.745,0.0386387
|
||||
226.48,0.0145919,0.00124444,0.974512,289,237.277,0.026509
|
||||
270.479,0.012833,0.00124444,0.969559,206,283.579,0.0290488
|
||||
269.589,0.0127376,0.00124444,0.969659,224,282.437,0.0528172
|
||||
280.521,0.0132416,0.00124444,0.968429,220,294.507,0.0378721
|
||||
275.907,0.0131407,0.00124444,0.968948,230,289.471,0.0382769
|
||||
249.457,0.0118344,0.00124444,0.971925,273,261.243,0.0274762
|
||||
277.053,0.0111192,0.00124444,0.968872,263,290.359,0.0620501
|
||||
251.523,0.0152724,0.00124444,0.971693,256,263.942,0.0346986
|
||||
267.086,0.0131384,0.00124444,0.969941,209,279.455,0.0422156
|
||||
269.944,0.0132077,0.00124444,0.96962,185,283.11,0.0468952
|
||||
286.474,0.0134134,0.00124444,0.967759,320,300.758,0.0229568
|
||||
261.21,0.0122179,0.00124444,0.970602,229,273.678,0.042026
|
||||
271.748,0.0122565,0.00124444,0.969416,227,284.549,0.0369429
|
||||
278.334,0.00939272,0.00124444,0.968675,325,291.625,0.0419345
|
||||
258.829,0.0143853,0.00124444,0.970871,294,271.551,0.0349143
|
||||
247.163,0.00928993,0.00124444,0.972183,232,259.444,0.0304895
|
||||
289.958,0.01276,0.00124444,0.967367,211,304.274,0.0585419
|
||||
302.262,0.0110498,0.00124444,0.965982,235,317.339,0.0429466
|
||||
266.697,0.0141856,0.00124444,0.969985,257,279.883,0.027867
|
||||
279.365,0.0132202,0.00124444,0.968559,309,292.823,0.0333579
|
||||
269.457,0.013538,0.00124444,0.969674,268,282.633,0.0292981
|
||||
266.753,0.0126111,0.00124444,0.969985,224,278.892,0.0530028
|
||||
248.308,0.0152383,0.00124444,0.972054,165,260.591,0.0615863
|
||||
261.957,0.0114572,0.00124444,0.970518,193,274.925,0.0212163
|
||||
337.165,0.0107314,0.00124444,0.962054,228,353.899,0.0526597
|
||||
314.063,0.0125739,0.00124444,0.964654,275,329.705,0.0259226
|
||||
270.826,0.0146448,0.00124444,0.96952,348,284.285,0.0177896
|
||||
|
@ -0,0 +1,111 @@
|
||||
"Evolution error"
|
||||
298.423
|
||||
284.695
|
||||
337.628
|
||||
278.241
|
||||
264.793
|
||||
257.7
|
||||
274.784
|
||||
287.743
|
||||
306.328
|
||||
283.047
|
||||
289.659
|
||||
250.664
|
||||
261.859
|
||||
320.352
|
||||
302.292
|
||||
354.924
|
||||
292.181
|
||||
285.759
|
||||
252.184
|
||||
316.796
|
||||
282.546
|
||||
311.274
|
||||
242.707
|
||||
265.12
|
||||
292.53
|
||||
373.645
|
||||
265.231
|
||||
339.851
|
||||
331.492
|
||||
296.143
|
||||
267.902
|
||||
309.679
|
||||
269.797
|
||||
269.874
|
||||
314.378
|
||||
273.406
|
||||
270.657
|
||||
310.459
|
||||
247.483
|
||||
274.461
|
||||
273.334
|
||||
288.058
|
||||
299.622
|
||||
291.267
|
||||
252.976
|
||||
275.311
|
||||
280.607
|
||||
270.017
|
||||
303.237
|
||||
286.265
|
||||
358.606
|
||||
300.357
|
||||
260.384
|
||||
271.183
|
||||
275.937
|
||||
340.822
|
||||
342.87
|
||||
247.036
|
||||
305.313
|
||||
362.535
|
||||
292.104
|
||||
270.485
|
||||
325.329
|
||||
275.62
|
||||
245.371
|
||||
296.747
|
||||
285.701
|
||||
315.472
|
||||
261.363
|
||||
288.343
|
||||
253.537
|
||||
353.546
|
||||
272.705
|
||||
267.961
|
||||
269.917
|
||||
303.207
|
||||
280.342
|
||||
288.78
|
||||
330.349
|
||||
297.971
|
||||
302.104
|
||||
285.659
|
||||
311.745
|
||||
237.277
|
||||
283.579
|
||||
282.437
|
||||
294.507
|
||||
289.471
|
||||
261.243
|
||||
290.359
|
||||
263.942
|
||||
279.455
|
||||
283.11
|
||||
300.758
|
||||
273.678
|
||||
284.549
|
||||
291.625
|
||||
271.551
|
||||
259.444
|
||||
304.274
|
||||
317.339
|
||||
279.883
|
||||
292.823
|
||||
282.633
|
||||
278.892
|
||||
260.591
|
||||
274.925
|
||||
353.899
|
||||
329.705
|
||||
284.285
|
||||
@ -0,0 +1,138 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171020-evolution1D_4x7_100Times_addedOne.csv" every ::1 using 2:5
|
||||
format = x:z
|
||||
#datapoints = 110
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: f(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 6.53142e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707163
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 199691
|
||||
rel. change during last iteration : -1.72988e-09
|
||||
|
||||
degrees of freedom (FIT_NDF) : 108
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 42.9999
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1848.99
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -5255.52 +/- 2401 (45.69%)
|
||||
b = 306.262 +/- 30.21 (9.863%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.991 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171020-evolution1D_4x7_100Times_addedOne.csv" every ::1 using 4:5
|
||||
format = x:z
|
||||
#datapoints = 110
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: g(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 6.48107e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.984575
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 204796
|
||||
rel. change during last iteration : -1.36705e-09
|
||||
|
||||
degrees of freedom (FIT_NDF) : 108
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 43.5461
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1896.26
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 1953.98 +/- 1389 (71.09%)
|
||||
bb = -1652.44 +/- 1346 (81.45%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171020-evolution1D_4x7_100Times_addedOne.csv" every ::1 using 4:6
|
||||
format = x:z
|
||||
#datapoints = 110
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: h(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 9.19699e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.984575
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 25.9742
|
||||
rel. change during last iteration : -3.36475e-14
|
||||
|
||||
degrees of freedom (FIT_NDF) : 108
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.49041
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.240502
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -9329.24 +/- 15.64 (0.1677%)
|
||||
bbb = 9328.88 +/- 15.16 (0.1625%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
@ -0,0 +1,272 @@
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 6.53142e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707163
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 208679 delta(WSSR)/WSSR : -30.2988
|
||||
delta(WSSR) : -6.32274e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0707163
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = 0.604107
|
||||
b = 239.671
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 207515 delta(WSSR)/WSSR : -0.00561318
|
||||
delta(WSSR) : -1164.82 limit for stopping : 1e-05
|
||||
lambda : 0.00707163
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -316.066
|
||||
b = 244.702
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 199833 delta(WSSR)/WSSR : -0.0384382
|
||||
delta(WSSR) : -7681.23 limit for stopping : 1e-05
|
||||
lambda : 0.000707163
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -4589.04
|
||||
b = 297.956
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 199691 delta(WSSR)/WSSR : -0.000713282
|
||||
delta(WSSR) : -142.436 limit for stopping : 1e-05
|
||||
lambda : 7.07163e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -5254.48
|
||||
b = 306.249
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 199691 delta(WSSR)/WSSR : -1.72988e-09
|
||||
delta(WSSR) : -0.000345441 limit for stopping : 1e-05
|
||||
lambda : 7.07163e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -5255.52
|
||||
b = 306.262
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 199691
|
||||
rel. change during last iteration : -1.72988e-09
|
||||
|
||||
degrees of freedom (FIT_NDF) : 108
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 42.9999
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1848.99
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -5255.52 +/- 2401 (45.69%)
|
||||
b = 306.262 +/- 30.21 (9.863%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.991 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 6.48107e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.984575
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 208225 delta(WSSR)/WSSR : -30.1253
|
||||
delta(WSSR) : -6.27284e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0984575
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 120.76
|
||||
bb = 122.686
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 207777 delta(WSSR)/WSSR : -0.00215751
|
||||
delta(WSSR) : -448.28 limit for stopping : 1e-05
|
||||
lambda : 0.00984575
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 212.362
|
||||
bb = 35.0135
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 204873 delta(WSSR)/WSSR : -0.0141739
|
||||
delta(WSSR) : -2903.84 limit for stopping : 1e-05
|
||||
lambda : 0.000984575
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 1674.36
|
||||
bb = -1381.52
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 204796 delta(WSSR)/WSSR : -0.000375155
|
||||
delta(WSSR) : -76.8303 limit for stopping : 1e-05
|
||||
lambda : 9.84575e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 1953.44
|
||||
bb = -1651.93
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 204796 delta(WSSR)/WSSR : -1.36705e-09
|
||||
delta(WSSR) : -0.000279966 limit for stopping : 1e-05
|
||||
lambda : 9.84575e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 1953.98
|
||||
bb = -1652.44
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 204796
|
||||
rel. change during last iteration : -1.36705e-09
|
||||
|
||||
degrees of freedom (FIT_NDF) : 108
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 43.5461
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1896.26
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 1953.98 +/- 1389 (71.09%)
|
||||
bb = -1652.44 +/- 1346 (81.45%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 9.19699e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.984575
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 88322.9 delta(WSSR)/WSSR : -103.129
|
||||
delta(WSSR) : -9.10867e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0984575
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = 139.208
|
||||
bbb = 153.55
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 79597.9 delta(WSSR)/WSSR : -0.109614
|
||||
delta(WSSR) : -8725.02 limit for stopping : 1e-05
|
||||
lambda : 0.00984575
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -330.642
|
||||
bbb = 610.091
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 2077.04 delta(WSSR)/WSSR : -37.3227
|
||||
delta(WSSR) : -77520.9 limit for stopping : 1e-05
|
||||
lambda : 0.000984575
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -7884.52
|
||||
bbb = 7929.08
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 25.9817 delta(WSSR)/WSSR : -78.9426
|
||||
delta(WSSR) : -2051.06 limit for stopping : 1e-05
|
||||
lambda : 9.84575e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -9326.48
|
||||
bbb = 9326.2
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 25.9742 delta(WSSR)/WSSR : -0.000287746
|
||||
delta(WSSR) : -0.00747396 limit for stopping : 1e-05
|
||||
lambda : 9.84575e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -9329.24
|
||||
bbb = 9328.88
|
||||
/
|
||||
|
||||
Iteration 6
|
||||
WSSR : 25.9742 delta(WSSR)/WSSR : -3.36475e-14
|
||||
delta(WSSR) : -8.73968e-13 limit for stopping : 1e-05
|
||||
lambda : 9.84575e-07
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -9329.24
|
||||
bbb = 9328.88
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 25.9742
|
||||
rel. change during last iteration : -3.36475e-14
|
||||
|
||||
degrees of freedom (FIT_NDF) : 108
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.49041
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.240502
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -9329.24 +/- 15.64 (0.1677%)
|
||||
bbb = 9328.88 +/- 15.16 (0.1625%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
@ -0,0 +1,20 @@
|
||||
set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171020-evolution1D_4x7_100Times_addedOne.csv" every ::1 using 2:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171020-evolution1D_4x7_100Times_addedOne_regularity-vs-steps.png"
|
||||
plot "20171020-evolution1D_4x7_100Times_addedOne.csv" every ::1 using 2:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171020-evolution1D_4x7_100Times_addedOne.csv" every ::1 using 4:5 via aa,bb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171020-evolution1D_4x7_100Times_addedOne_improvement-vs-steps.png"
|
||||
plot "20171020-evolution1D_4x7_100Times_addedOne.csv" every ::1 using 4:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171020-evolution1D_4x7_100Times_addedOne.csv" every ::1 using 4:6 via aaa,bbb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Fitting error'
|
||||
set output "20171020-evolution1D_4x7_100Times_addedOne_improvement-vs-evo-error.png"
|
||||
plot "20171020-evolution1D_4x7_100Times_addedOne.csv" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
File diff suppressed because it is too large
Load Diff
@ -0,0 +1,37 @@
|
||||
[1] "================ Analyzing 20171020-evolution1D_4x7_100Times_addedOne.csv"
|
||||
[1] "spearman for improvement-potential vs. evolution-error"
|
||||
x y
|
||||
x 1 -1
|
||||
y -1 1
|
||||
|
||||
n= 110
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0
|
||||
y 0
|
||||
[1] "spearman for regularity vs. steps"
|
||||
x y
|
||||
x 1.00 -0.19
|
||||
y -0.19 1.00
|
||||
|
||||
n= 110
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0.0503
|
||||
y 0.0503
|
||||
[1] "spearman for variability vs. evolution-error"
|
||||
x y
|
||||
x 1 NaN
|
||||
y NaN 1
|
||||
|
||||
n= 110
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x
|
||||
y
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 5.6 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 5.7 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 5.6 KiB |
@ -0,0 +1,101 @@
|
||||
"Least squares",regularity,variability,improvement,steps,"Evolution error",sigma
|
||||
187.745,0.0182483,0.00111111,0.97887,227,196.94,0.0221641
|
||||
199.804,0.0152344,0.00111111,0.977513,206,209.683,0.0142768
|
||||
186.97,0.0181411,0.00111111,0.978958,227,196.045,0.0300805
|
||||
182.366,0.019132,0.00111111,0.979476,245,191.37,0.0263319
|
||||
181.893,0.0197913,0.00111111,0.979529,238,190.84,0.0243627
|
||||
184.832,0.0161942,0.00111111,0.979198,192,193.974,0.0217357
|
||||
192.909,0.0193693,0.00111111,0.978289,205,202.544,0.0319747
|
||||
226.472,0.0204366,0.00111111,0.974512,240,237.786,0.0250503
|
||||
208.156,0.0183033,0.00111111,0.976573,251,218.4,0.0217521
|
||||
198.122,0.0213555,0.00111111,0.977703,216,207.719,0.0239459
|
||||
218.91,0.0234253,0.00111111,0.975363,190,229.721,0.0230034
|
||||
182.072,0.0200981,0.00111111,0.979509,215,191.136,0.0384825
|
||||
203.83,0.0176375,0.00111111,0.97706,191,213.927,0.0294044
|
||||
187.971,0.0162914,0.00111111,0.978845,305,197.336,0.0135234
|
||||
198.237,0.0184512,0.00111111,0.97769,150,207.431,0.0484778
|
||||
233.46,0.0203856,0.00111111,0.973726,179,245.039,0.0178918
|
||||
209.599,0.0177202,0.00111111,0.976411,250,220.043,0.0280449
|
||||
204.434,0.0187668,0.00111111,0.976992,203,214.432,0.0211949
|
||||
234.718,0.0161043,0.00111111,0.973584,160,246.42,0.0239583
|
||||
192.939,0.0228069,0.00111111,0.978286,261,202.553,0.0205101
|
||||
234.394,0.0169807,0.00111111,0.97362,139,245.306,0.0336572
|
||||
183.73,0.0159035,0.00111111,0.979322,237,192.882,0.0172048
|
||||
187.186,0.0202169,0.00111111,0.978933,204,196.329,0.0395863
|
||||
194.01,0.0195768,0.00111111,0.978165,244,203.052,0.035514
|
||||
195.111,0.0170059,0.00111111,0.978041,157,204.662,0.0231966
|
||||
225.331,0.0236187,0.00111111,0.97464,160,236.452,0.0301883
|
||||
239.538,0.0189427,0.00111111,0.973042,114,251.484,0.0470329
|
||||
181.805,0.0212591,0.00111111,0.979539,268,190.782,0.0340786
|
||||
186.244,0.0207094,0.00111111,0.979039,190,195.503,0.0288453
|
||||
246.843,0.0173713,0.00111111,0.972219,193,259.133,0.0198506
|
||||
203.277,0.0181449,0.00111111,0.977123,211,213.431,0.0257039
|
||||
214.842,0.0200148,0.00111111,0.975821,238,225.349,0.038947
|
||||
196.658,0.0187428,0.00111111,0.977867,168,205.744,0.0424655
|
||||
212.094,0.0177129,0.00111111,0.97613,122,222.595,0.0428265
|
||||
230.135,0.0196257,0.00111111,0.9741,151,241.582,0.0438331
|
||||
206.85,0.0177107,0.00111111,0.97672,266,217.141,0.0213643
|
||||
237.733,0.0201347,0.00111111,0.973245,168,249.588,0.0356283
|
||||
175.754,0.017217,0.00111111,0.98022,241,184.459,0.028533
|
||||
201.986,0.0218777,0.00111111,0.977268,179,212.03,0.0387742
|
||||
184.105,0.0176688,0.00111111,0.97928,289,193.133,0.0333076
|
||||
199.825,0.0193904,0.00111111,0.977511,190,209.808,0.0321669
|
||||
205.585,0.0179865,0.00111111,0.976863,258,215.712,0.027105
|
||||
240.325,0.0198335,0.00111111,0.972953,166,251.883,0.0356981
|
||||
184.794,0.0187189,0.00111111,0.979203,236,193.995,0.0258967
|
||||
180.454,0.0186822,0.00111111,0.979691,263,189.447,0.0269632
|
||||
238.932,0.0212528,0.00111111,0.97311,117,250.443,0.0437906
|
||||
221.165,0.0193828,0.00111111,0.975109,134,231.057,0.0497979
|
||||
189.713,0.0180015,0.00111111,0.978649,201,199.026,0.0212137
|
||||
197.758,0.0185375,0.00111111,0.977744,151,207.409,0.044357
|
||||
201.952,0.0195493,0.00111111,0.977272,260,211.962,0.0261682
|
||||
188.56,0.0159997,0.00111111,0.978779,180,197.951,0.035823
|
||||
243.499,0.0199009,0.00111111,0.972596,207,255.613,0.0301646
|
||||
239.081,0.0196769,0.00111111,0.973093,157,250.788,0.0312726
|
||||
203.299,0.0212421,0.00111111,0.97712,273,213.319,0.0212051
|
||||
206.534,0.0186378,0.00111111,0.976756,198,216.537,0.0220651
|
||||
187.968,0.0201035,0.00111111,0.978845,207,197.095,0.0399027
|
||||
213.453,0.0168292,0.00111111,0.975977,190,224.087,0.0288318
|
||||
219.024,0.017168,0.00111111,0.97535,254,229.948,0.0190611
|
||||
199.468,0.0196977,0.00111111,0.977551,260,209.414,0.0308103
|
||||
238.393,0.0213402,0.00111111,0.97317,187,250.101,0.0195628
|
||||
209.099,0.0198555,0.00111111,0.976467,194,219.433,0.0317749
|
||||
194.13,0.0196069,0.00111111,0.978152,278,203.824,0.0172456
|
||||
200.102,0.0209277,0.00111111,0.97748,199,209.167,0.0328509
|
||||
183.427,0.0199804,0.00111111,0.979356,220,192.511,0.0297735
|
||||
191.681,0.0192451,0.00111111,0.978428,238,201.236,0.0205511
|
||||
213.367,0.0190531,0.00111111,0.975987,154,223.476,0.0399578
|
||||
212.537,0.0153109,0.00111111,0.97608,186,223.119,0.0415867
|
||||
240.507,0.0213148,0.00111111,0.972932,163,252.503,0.0222976
|
||||
211.405,0.0165473,0.00111111,0.976208,263,221.844,0.0324297
|
||||
225.422,0.0187176,0.00111111,0.97463,234,236.373,0.0366055
|
||||
211.011,0.0148638,0.00111111,0.976252,182,221.486,0.0206502
|
||||
210.256,0.0174415,0.00111111,0.976337,160,220.727,0.0204222
|
||||
217.209,0.019323,0.00111111,0.975554,204,228.05,0.0191575
|
||||
210.209,0.0225558,0.00111111,0.976342,184,220.544,0.0239447
|
||||
206.081,0.017393,0.00111111,0.976807,185,216.377,0.0093842
|
||||
221.445,0.0146833,0.00111111,0.975078,161,232.445,0.0262917
|
||||
242.088,0.0181286,0.00111111,0.972755,178,254.12,0.0180639
|
||||
213.359,0.0188093,0.00111111,0.975988,149,224,0.0393936
|
||||
219.037,0.018868,0.00111111,0.975349,173,229.801,0.035486
|
||||
201.648,0.0148883,0.00111111,0.977306,247,211.671,0.0210672
|
||||
197.345,0.0182581,0.00111111,0.97779,203,206.763,0.0345867
|
||||
199.057,0.019515,0.00111111,0.977597,178,208.842,0.0272527
|
||||
230.708,0.0170428,0.00111111,0.974035,145,241.647,0.0284395
|
||||
191.615,0.0211321,0.00111111,0.978435,220,200.545,0.0302029
|
||||
200.996,0.0198848,0.00111111,0.977379,148,210.728,0.0297074
|
||||
204.71,0.022276,0.00111111,0.976961,176,214.662,0.0238206
|
||||
204.41,0.0188267,0.00111111,0.976995,200,214.432,0.0297072
|
||||
212.194,0.0178961,0.00111111,0.976119,218,222.734,0.0288567
|
||||
195.299,0.0217078,0.00111111,0.97802,230,204.888,0.0335442
|
||||
217.03,0.0183731,0.00111111,0.975575,313,227.646,0.0197123
|
||||
207.129,0.0208927,0.00111111,0.976689,177,217.056,0.03195
|
||||
181.67,0.019443,0.00111111,0.979554,209,190.336,0.0231579
|
||||
187.536,0.0197584,0.00111111,0.978894,222,196.872,0.0199832
|
||||
207.254,0.0183979,0.00111111,0.976675,152,217.488,0.0372997
|
||||
188.784,0.0198524,0.00111111,0.978754,251,198.201,0.0188279
|
||||
187.669,0.0189986,0.00111111,0.978879,239,196.713,0.0255703
|
||||
177.618,0.0201662,0.00111111,0.98001,137,186.056,0.0372483
|
||||
204.647,0.0199072,0.00111111,0.976968,164,213.683,0.0293019
|
||||
257.265,0.0189825,0.00111111,0.971046,121,270.03,0.0289929
|
||||
192.284,0.02033,0.00111111,0.97836,252,201.837,0.0218422
|
||||
|
@ -0,0 +1,101 @@
|
||||
"Evolution error"
|
||||
196.94
|
||||
209.683
|
||||
196.045
|
||||
191.37
|
||||
190.84
|
||||
193.974
|
||||
202.544
|
||||
237.786
|
||||
218.4
|
||||
207.719
|
||||
229.721
|
||||
191.136
|
||||
213.927
|
||||
197.336
|
||||
207.431
|
||||
245.039
|
||||
220.043
|
||||
214.432
|
||||
246.42
|
||||
202.553
|
||||
245.306
|
||||
192.882
|
||||
196.329
|
||||
203.052
|
||||
204.662
|
||||
236.452
|
||||
251.484
|
||||
190.782
|
||||
195.503
|
||||
259.133
|
||||
213.431
|
||||
225.349
|
||||
205.744
|
||||
222.595
|
||||
241.582
|
||||
217.141
|
||||
249.588
|
||||
184.459
|
||||
212.03
|
||||
193.133
|
||||
209.808
|
||||
215.712
|
||||
251.883
|
||||
193.995
|
||||
189.447
|
||||
250.443
|
||||
231.057
|
||||
199.026
|
||||
207.409
|
||||
211.962
|
||||
197.951
|
||||
255.613
|
||||
250.788
|
||||
213.319
|
||||
216.537
|
||||
197.095
|
||||
224.087
|
||||
229.948
|
||||
209.414
|
||||
250.101
|
||||
219.433
|
||||
203.824
|
||||
209.167
|
||||
192.511
|
||||
201.236
|
||||
223.476
|
||||
223.119
|
||||
252.503
|
||||
221.844
|
||||
236.373
|
||||
221.486
|
||||
220.727
|
||||
228.05
|
||||
220.544
|
||||
216.377
|
||||
232.445
|
||||
254.12
|
||||
224
|
||||
229.801
|
||||
211.671
|
||||
206.763
|
||||
208.842
|
||||
241.647
|
||||
200.545
|
||||
210.728
|
||||
214.662
|
||||
214.432
|
||||
222.734
|
||||
204.888
|
||||
227.646
|
||||
217.056
|
||||
190.336
|
||||
196.872
|
||||
217.488
|
||||
198.201
|
||||
196.713
|
||||
186.056
|
||||
213.683
|
||||
270.03
|
||||
201.837
|
||||
@ -0,0 +1,138 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171020-evolution1D_5x5_100Times-addedOne.csv" every ::1 using 2:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: f(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.26528e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707236
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 191085
|
||||
rel. change during last iteration : -3.5658e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 44.157
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1949.84
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -801.741 +/- 2391 (298.2%)
|
||||
b = 218.088 +/- 45.62 (20.92%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.995 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171020-evolution1D_5x5_100Times-addedOne.csv" every ::1 using 4:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: g(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.2267e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.988459
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 147724
|
||||
rel. change during last iteration : -4.79728e-07
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 38.8251
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1507.39
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 9976.22 +/- 1855 (18.6%)
|
||||
bb = -9541.71 +/- 1812 (18.99%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171020-evolution1D_5x5_100Times-addedOne.csv" every ::1 using 4:6
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: h(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.63731e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.988459
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 5.78147
|
||||
rel. change during last iteration : -2.12322e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.242888
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.0589946
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -9327.12 +/- 11.61 (0.1244%)
|
||||
bbb = 9326.98 +/- 11.34 (0.1216%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
@ -0,0 +1,272 @@
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.26528e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707236
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 191407 delta(WSSR)/WSSR : -21.2838
|
||||
delta(WSSR) : -4.07388e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0707236
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = 4.26373
|
||||
b = 201.775
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 191279 delta(WSSR)/WSSR : -0.000670419
|
||||
delta(WSSR) : -128.237 limit for stopping : 1e-05
|
||||
lambda : 0.00707236
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -47.1714
|
||||
b = 203.756
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 191088 delta(WSSR)/WSSR : -0.00100002
|
||||
delta(WSSR) : -191.092 limit for stopping : 1e-05
|
||||
lambda : 0.000707236
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -705.237
|
||||
b = 216.255
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 191085 delta(WSSR)/WSSR : -1.66293e-05
|
||||
delta(WSSR) : -3.17761 limit for stopping : 1e-05
|
||||
lambda : 7.07236e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -801.6
|
||||
b = 218.086
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 191085 delta(WSSR)/WSSR : -3.5658e-11
|
||||
delta(WSSR) : -6.8137e-06 limit for stopping : 1e-05
|
||||
lambda : 7.07236e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -801.741
|
||||
b = 218.088
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 191085
|
||||
rel. change during last iteration : -3.5658e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 44.157
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1949.84
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -801.741 +/- 2391 (298.2%)
|
||||
b = 218.088 +/- 45.62 (20.92%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.995 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.2267e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.988459
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 190503 delta(WSSR)/WSSR : -21.1871
|
||||
delta(WSSR) : -4.0362e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0988459
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 103.189
|
||||
bb = 101.089
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 188511 delta(WSSR)/WSSR : -0.0105682
|
||||
delta(WSSR) : -1992.23 limit for stopping : 1e-05
|
||||
lambda : 0.00988459
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 325.036
|
||||
bb = -114.608
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 151484 delta(WSSR)/WSSR : -0.244426
|
||||
delta(WSSR) : -37026.6 limit for stopping : 1e-05
|
||||
lambda : 0.000988459
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 7045.82
|
||||
bb = -6679.35
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 147724 delta(WSSR)/WSSR : -0.0254538
|
||||
delta(WSSR) : -3760.13 limit for stopping : 1e-05
|
||||
lambda : 9.88459e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 9963.5
|
||||
bb = -9529.28
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 147724 delta(WSSR)/WSSR : -4.79728e-07
|
||||
delta(WSSR) : -0.0708672 limit for stopping : 1e-05
|
||||
lambda : 9.88459e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 9976.22
|
||||
bb = -9541.71
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 147724
|
||||
rel. change during last iteration : -4.79728e-07
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 38.8251
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 1507.39
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 9976.22 +/- 1855 (18.6%)
|
||||
bb = -9541.71 +/- 1812 (18.99%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.63731e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.988459
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 39084.3 delta(WSSR)/WSSR : -117.649
|
||||
delta(WSSR) : -4.59823e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0988459
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = 105.492
|
||||
bbb = 112.304
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 37242.9 delta(WSSR)/WSSR : -0.0494443
|
||||
delta(WSSR) : -1841.45 limit for stopping : 1e-05
|
||||
lambda : 0.00988459
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -105.47
|
||||
bbb = 319.436
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 3438.73 delta(WSSR)/WSSR : -9.8304
|
||||
delta(WSSR) : -33804.1 limit for stopping : 1e-05
|
||||
lambda : 0.000988459
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -6527.14
|
||||
bbb = 6592.01
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 5.84617 delta(WSSR)/WSSR : -587.203
|
||||
delta(WSSR) : -3432.89 limit for stopping : 1e-05
|
||||
lambda : 9.88459e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -9314.96
|
||||
bbb = 9315.1
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 5.78147 delta(WSSR)/WSSR : -0.0111909
|
||||
delta(WSSR) : -0.0646996 limit for stopping : 1e-05
|
||||
lambda : 9.88459e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -9327.12
|
||||
bbb = 9326.98
|
||||
/
|
||||
|
||||
Iteration 6
|
||||
WSSR : 5.78147 delta(WSSR)/WSSR : -2.12322e-11
|
||||
delta(WSSR) : -1.22753e-10 limit for stopping : 1e-05
|
||||
lambda : 9.88459e-07
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -9327.12
|
||||
bbb = 9326.98
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 5.78147
|
||||
rel. change during last iteration : -2.12322e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.242888
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.0589946
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -9327.12 +/- 11.61 (0.1244%)
|
||||
bbb = 9326.98 +/- 11.34 (0.1216%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
@ -0,0 +1,20 @@
|
||||
set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171020-evolution1D_5x5_100Times-addedOne.csv" every ::1 using 2:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171020-evolution1D_5x5_100Times-addedOne_regularity-vs-steps.png"
|
||||
plot "20171020-evolution1D_5x5_100Times-addedOne.csv" every ::1 using 2:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171020-evolution1D_5x5_100Times-addedOne.csv" every ::1 using 4:5 via aa,bb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171020-evolution1D_5x5_100Times-addedOne_improvement-vs-steps.png"
|
||||
plot "20171020-evolution1D_5x5_100Times-addedOne.csv" every ::1 using 4:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171020-evolution1D_5x5_100Times-addedOne.csv" every ::1 using 4:6 via aaa,bbb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Fitting error'
|
||||
set output "20171020-evolution1D_5x5_100Times-addedOne_improvement-vs-evo-error.png"
|
||||
plot "20171020-evolution1D_5x5_100Times-addedOne.csv" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
File diff suppressed because it is too large
Load Diff
@ -0,0 +1,37 @@
|
||||
[1] "================ Analyzing 20171020-evolution1D_5x5_100Times-addedOne.csv"
|
||||
[1] "spearman for improvement-potential vs. evolution-error"
|
||||
x y
|
||||
x 1 -1
|
||||
y -1 1
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0
|
||||
y 0
|
||||
[1] "spearman for regularity vs. steps"
|
||||
x y
|
||||
x 1.00 -0.02
|
||||
y -0.02 1.00
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0.8461
|
||||
y 0.8461
|
||||
[1] "spearman for variability vs. evolution-error"
|
||||
x y
|
||||
x 1 NaN
|
||||
y NaN 1
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x
|
||||
y
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 5.9 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 6.3 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 5.8 KiB |
101
dokumentation/evolution1d/20171020-evolution1D_5x5_100Times.csv
Normal file
101
dokumentation/evolution1d/20171020-evolution1D_5x5_100Times.csv
Normal file
@ -0,0 +1,101 @@
|
||||
"Least squares",regularity,variability,improvement,steps,"Evolution error",sigma
|
||||
211.698,0.0203679,0.00111111,0.929303,218,222.265,0.0304584
|
||||
200.554,0.0211861,0.00111111,0.933025,215,210.496,0.019554
|
||||
209.312,0.0193559,0.00111111,0.9301,198,219.661,0.0276531
|
||||
206.148,0.0172566,0.00111111,0.931157,208,216.396,0.0235405
|
||||
217.079,0.0195466,0.00111111,0.927506,141,227.519,0.0433189
|
||||
229.411,0.0196263,0.00111111,0.923388,215,240.74,0.0228817
|
||||
199.52,0.0203185,0.00111111,0.93337,234,208.51,0.0291453
|
||||
186.604,0.0212737,0.00111111,0.937683,259,195.805,0.0213456
|
||||
225.306,0.0213791,0.00111111,0.924759,236,236.503,0.0252631
|
||||
248.528,0.0193633,0.00111111,0.917004,221,260.935,0.0160484
|
||||
189.883,0.0191517,0.00111111,0.936588,136,198.559,0.0362213
|
||||
212.6,0.0166038,0.00111111,0.929002,208,222.573,0.031822
|
||||
220.85,0.0161934,0.00111111,0.926247,205,231.708,0.0293863
|
||||
210.742,0.0191138,0.00111111,0.929622,230,220.944,0.0260993
|
||||
221.447,0.0184165,0.00111111,0.926047,262,232.462,0.0200636
|
||||
190.705,0.0171791,0.00111111,0.936314,201,200.196,0.0282271
|
||||
221.909,0.0209993,0.00111111,0.925893,190,232.786,0.0333187
|
||||
211.712,0.0165509,0.00111111,0.929298,243,222.289,0.0160656
|
||||
217.07,0.0231196,0.00111111,0.927509,182,227.732,0.0261153
|
||||
197.775,0.0203953,0.00111111,0.933953,252,207.181,0.0323614
|
||||
219.904,0.0168872,0.00111111,0.926563,120,230.616,0.0328043
|
||||
204.335,0.0180441,0.00111111,0.931762,192,214.185,0.0296326
|
||||
231.939,0.018535,0.00111111,0.922544,128,243.327,0.0304083
|
||||
211.724,0.0185923,0.00111111,0.929295,270,222.254,0.0414344
|
||||
214.148,0.0206654,0.00111111,0.928485,234,224.844,0.0317975
|
||||
185.847,0.0204202,0.00111111,0.937936,165,194.744,0.034174
|
||||
232.03,0.0193975,0.00111111,0.922513,92,243.161,0.0396967
|
||||
223.982,0.0236268,0.00111111,0.925201,208,234.626,0.0255705
|
||||
226.077,0.01857,0.00111111,0.924501,115,236.939,0.0416214
|
||||
197.984,0.0164528,0.00111111,0.933883,150,207.489,0.0291136
|
||||
176.084,0.0198163,0.00111111,0.941197,258,184.696,0.0302269
|
||||
195.22,0.0163427,0.00111111,0.934806,230,204.904,0.0349146
|
||||
202.893,0.0217023,0.00111111,0.932244,172,212.168,0.0292404
|
||||
191.762,0.0176933,0.00111111,0.935961,203,201.279,0.0218102
|
||||
208.412,0.0212612,0.00111111,0.930401,201,218.814,0.0210822
|
||||
221.844,0.0210909,0.00111111,0.925915,173,232.892,0.0258153
|
||||
219.113,0.0184739,0.00111111,0.926827,173,230.05,0.0414932
|
||||
224.465,0.0246122,0.00111111,0.92504,183,235.508,0.0250082
|
||||
206.774,0.0198917,0.00111111,0.930947,186,216.939,0.0310308
|
||||
225.859,0.0172615,0.00111111,0.924574,203,236.479,0.0398825
|
||||
212.461,0.0204119,0.00111111,0.929048,149,222.522,0.0337725
|
||||
224.924,0.0217016,0.00111111,0.924886,130,236.154,0.0354094
|
||||
232.115,0.0210782,0.00111111,0.922485,198,243.686,0.0172863
|
||||
228.396,0.0196268,0.00111111,0.923727,238,239.488,0.0184422
|
||||
196.881,0.019569,0.00111111,0.934251,255,206.689,0.0295242
|
||||
204.716,0.0180094,0.00111111,0.931635,155,213.904,0.0298783
|
||||
209.447,0.0191448,0.00111111,0.930055,118,219.704,0.0312759
|
||||
221.317,0.0189707,0.00111111,0.926091,230,231.945,0.0391334
|
||||
215.094,0.0199488,0.00111111,0.928169,216,225.771,0.0197891
|
||||
184.929,0.01736,0.00111111,0.938243,213,194.167,0.0307934
|
||||
178.666,0.0198813,0.00111111,0.940334,187,187.585,0.0149118
|
||||
174.929,0.0189218,0.00111111,0.941582,195,183.471,0.0197701
|
||||
179.673,0.0165947,0.00111111,0.939998,237,188.175,0.0268256
|
||||
204.903,0.0174921,0.00111111,0.931572,176,214.811,0.0341155
|
||||
198.996,0.0198215,0.00111111,0.933545,174,208.903,0.022187
|
||||
239.497,0.0229021,0.00111111,0.920019,145,251.345,0.0363502
|
||||
197.617,0.0190836,0.00111111,0.934006,264,207.332,0.0225783
|
||||
213.541,0.0182262,0.00111111,0.928688,171,223.93,0.024467
|
||||
205.246,0.018593,0.00111111,0.931458,200,215.194,0.0259352
|
||||
192.01,0.021189,0.00111111,0.935878,187,201.523,0.0356566
|
||||
207.623,0.0200966,0.00111111,0.930664,162,217.973,0.0237469
|
||||
207.124,0.0203329,0.00111111,0.930831,275,217.381,0.0377496
|
||||
207.6,0.015955,0.00111111,0.930672,313,217.963,0.034054
|
||||
196.464,0.0215318,0.00111111,0.934391,148,206.197,0.0255094
|
||||
225.291,0.0188696,0.00111111,0.924764,253,236.455,0.0269747
|
||||
236.139,0.0195817,0.00111111,0.921141,208,247.922,0.0181545
|
||||
218.667,0.0236608,0.00111111,0.926976,261,229.254,0.0200224
|
||||
214.905,0.0183248,0.00111111,0.928232,232,225.179,0.0317272
|
||||
222.269,0.0210694,0.00111111,0.925773,217,232.89,0.0322418
|
||||
193.848,0.0176874,0.00111111,0.935264,251,203.276,0.0293206
|
||||
210.394,0.0173601,0.00111111,0.929739,205,220.572,0.023589
|
||||
240.818,0.0172322,0.00111111,0.919578,201,252.661,0.037452
|
||||
223.163,0.0214412,0.00111111,0.925474,173,234.239,0.030632
|
||||
218.88,0.0208812,0.00111111,0.926905,110,229.098,0.0257352
|
||||
203.933,0.0179055,0.00111111,0.931896,229,213.754,0.0315607
|
||||
175.337,0.0219549,0.00111111,0.941446,169,184.029,0.0185983
|
||||
191.342,0.0173847,0.00111111,0.936101,233,200.827,0.0293542
|
||||
192.271,0.0211125,0.00111111,0.935791,185,201.758,0.022909
|
||||
217.045,0.0184074,0.00111111,0.927518,143,227.599,0.021528
|
||||
204.268,0.0199404,0.00111111,0.931784,263,214.25,0.0243066
|
||||
262.346,0.0165844,0.00111111,0.912389,190,275.187,0.0384815
|
||||
213.393,0.0220227,0.00111111,0.928737,122,223.6,0.031075
|
||||
210.514,0.0189866,0.00111111,0.929698,219,220.599,0.034692
|
||||
205.999,0.0198525,0.00111111,0.931206,143,215.885,0.0323366
|
||||
180.234,0.0208046,0.00111111,0.93981,234,189.174,0.0261096
|
||||
194.507,0.0183817,0.00111111,0.935044,133,204.135,0.0318449
|
||||
215.956,0.0189058,0.00111111,0.927881,330,226.485,0.0239564
|
||||
203.924,0.017231,0.00111111,0.931899,235,213.99,0.0323069
|
||||
235.067,0.0189216,0.00111111,0.921499,234,246.78,0.0289497
|
||||
202.496,0.0204575,0.00111111,0.932376,235,212.614,0.0216976
|
||||
263.952,0.0199218,0.00111111,0.911853,154,277.143,0.0245278
|
||||
207.128,0.0216716,0.00111111,0.930829,209,217.224,0.0321473
|
||||
244.798,0.019198,0.00111111,0.918249,260,256.629,0.0334971
|
||||
209.179,0.020316,0.00111111,0.930144,341,219.57,0.0166192
|
||||
245.103,0.0189129,0.00111111,0.918147,230,257.111,0.0263794
|
||||
226.778,0.0168544,0.00111111,0.924267,233,237.927,0.0176314
|
||||
207.236,0.0195923,0.00111111,0.930793,211,217.288,0.0189774
|
||||
192.594,0.0198456,0.00111111,0.935683,226,201.924,0.0274001
|
||||
197.183,0.0185432,0.00111111,0.93415,285,206.962,0.0215739
|
||||
222.895,0.0181898,0.00111111,0.925564,181,233.737,0.0213808
|
||||
|
@ -0,0 +1,101 @@
|
||||
"Evolution error"
|
||||
222.265
|
||||
210.496
|
||||
219.661
|
||||
216.396
|
||||
227.519
|
||||
240.74
|
||||
208.51
|
||||
195.805
|
||||
236.503
|
||||
260.935
|
||||
198.559
|
||||
222.573
|
||||
231.708
|
||||
220.944
|
||||
232.462
|
||||
200.196
|
||||
232.786
|
||||
222.289
|
||||
227.732
|
||||
207.181
|
||||
230.616
|
||||
214.185
|
||||
243.327
|
||||
222.254
|
||||
224.844
|
||||
194.744
|
||||
243.161
|
||||
234.626
|
||||
236.939
|
||||
207.489
|
||||
184.696
|
||||
204.904
|
||||
212.168
|
||||
201.279
|
||||
218.814
|
||||
232.892
|
||||
230.05
|
||||
235.508
|
||||
216.939
|
||||
236.479
|
||||
222.522
|
||||
236.154
|
||||
243.686
|
||||
239.488
|
||||
206.689
|
||||
213.904
|
||||
219.704
|
||||
231.945
|
||||
225.771
|
||||
194.167
|
||||
187.585
|
||||
183.471
|
||||
188.175
|
||||
214.811
|
||||
208.903
|
||||
251.345
|
||||
207.332
|
||||
223.93
|
||||
215.194
|
||||
201.523
|
||||
217.973
|
||||
217.381
|
||||
217.963
|
||||
206.197
|
||||
236.455
|
||||
247.922
|
||||
229.254
|
||||
225.179
|
||||
232.89
|
||||
203.276
|
||||
220.572
|
||||
252.661
|
||||
234.239
|
||||
229.098
|
||||
213.754
|
||||
184.029
|
||||
200.827
|
||||
201.758
|
||||
227.599
|
||||
214.25
|
||||
275.187
|
||||
223.6
|
||||
220.599
|
||||
215.885
|
||||
189.174
|
||||
204.135
|
||||
226.485
|
||||
213.99
|
||||
246.78
|
||||
212.614
|
||||
277.143
|
||||
217.224
|
||||
256.629
|
||||
219.57
|
||||
257.111
|
||||
237.927
|
||||
217.288
|
||||
201.924
|
||||
206.962
|
||||
233.737
|
||||
@ -0,0 +1,138 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171020-evolution1D_5x5_100Times.csv" every ::1 using 2:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: f(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.34137e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707241
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 224042
|
||||
rel. change during last iteration : -6.22481e-10
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 47.8136
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 2286.14
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -3382.99 +/- 2656 (78.52%)
|
||||
b = 269.51 +/- 51.79 (19.22%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.996 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171020-evolution1D_5x5_100Times.csv" every ::1 using 4:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: g(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.30453e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.965399
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 224312
|
||||
rel. change during last iteration : -4.70138e-12
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 47.8425
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 2288.9
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 991.364 +/- 809 (81.6%)
|
||||
bb = -717.625 +/- 752 (104.8%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171020-evolution1D_5x5_100Times.csv" every ::1 using 4:6
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: h(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.85341e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.965399
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 4.99405
|
||||
rel. change during last iteration : -2.82643e-06
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.225743
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.0509597
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -3144.45 +/- 3.817 (0.1214%)
|
||||
bbb = 3144.19 +/- 3.548 (0.1128%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
@ -0,0 +1,261 @@
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.34137e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707241
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 227857 delta(WSSR)/WSSR : -18.053
|
||||
delta(WSSR) : -4.11351e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0707241
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = 2.72407
|
||||
b = 202.778
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 227318 delta(WSSR)/WSSR : -0.00237422
|
||||
delta(WSSR) : -539.701 limit for stopping : 1e-05
|
||||
lambda : 0.00707241
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -203.128
|
||||
b = 207.783
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 224101 delta(WSSR)/WSSR : -0.0143554
|
||||
delta(WSSR) : -3217.05 limit for stopping : 1e-05
|
||||
lambda : 0.000707241
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -2957.55
|
||||
b = 261.251
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 224042 delta(WSSR)/WSSR : -0.000261723
|
||||
delta(WSSR) : -58.6368 limit for stopping : 1e-05
|
||||
lambda : 7.07241e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -3382.33
|
||||
b = 269.497
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 224042 delta(WSSR)/WSSR : -6.22481e-10
|
||||
delta(WSSR) : -0.000139462 limit for stopping : 1e-05
|
||||
lambda : 7.07241e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -3382.99
|
||||
b = 269.51
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 224042
|
||||
rel. change during last iteration : -6.22481e-10
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 47.8136
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 2286.14
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -3382.99 +/- 2656 (78.52%)
|
||||
b = 269.51 +/- 51.79 (19.22%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.996 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.30453e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.965399
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 227170 delta(WSSR)/WSSR : -17.9485
|
||||
delta(WSSR) : -4.07736e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0965399
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 102.981
|
||||
bb = 107.131
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 226223 delta(WSSR)/WSSR : -0.00418859
|
||||
delta(WSSR) : -947.555 limit for stopping : 1e-05
|
||||
lambda : 0.00965399
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 252.273
|
||||
bb = -30.6331
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 224317 delta(WSSR)/WSSR : -0.0084976
|
||||
delta(WSSR) : -1906.15 limit for stopping : 1e-05
|
||||
lambda : 0.000965399
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 956.388
|
||||
bb = -685.114
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 224312 delta(WSSR)/WSSR : -1.90727e-05
|
||||
delta(WSSR) : -4.27823 limit for stopping : 1e-05
|
||||
lambda : 9.65399e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 991.346
|
||||
bb = -717.608
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 224312 delta(WSSR)/WSSR : -4.70138e-12
|
||||
delta(WSSR) : -1.05458e-06 limit for stopping : 1e-05
|
||||
lambda : 9.65399e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 991.364
|
||||
bb = -717.625
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 224312
|
||||
rel. change during last iteration : -4.70138e-12
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 47.8425
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 2288.9
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 991.364 +/- 809 (81.6%)
|
||||
bb = -717.625 +/- 752 (104.8%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.85341e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.965399
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 37027.2 delta(WSSR)/WSSR : -130.077
|
||||
delta(WSSR) : -4.81638e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0965399
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = 103.355
|
||||
bbb = 124.231
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 25575.9 delta(WSSR)/WSSR : -0.447736
|
||||
delta(WSSR) : -11451.3 limit for stopping : 1e-05
|
||||
lambda : 0.00965399
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -440.459
|
||||
bbb = 630.803
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 62.2579 delta(WSSR)/WSSR : -409.806
|
||||
delta(WSSR) : -25513.7 limit for stopping : 1e-05
|
||||
lambda : 0.000965399
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3016.49
|
||||
bbb = 3025.25
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 4.99407 delta(WSSR)/WSSR : -11.4664
|
||||
delta(WSSR) : -57.2638 limit for stopping : 1e-05
|
||||
lambda : 9.65399e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3144.39
|
||||
bbb = 3144.13
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 4.99405 delta(WSSR)/WSSR : -2.82643e-06
|
||||
delta(WSSR) : -1.41153e-05 limit for stopping : 1e-05
|
||||
lambda : 9.65399e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3144.45
|
||||
bbb = 3144.19
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 4.99405
|
||||
rel. change during last iteration : -2.82643e-06
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.225743
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.0509597
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -3144.45 +/- 3.817 (0.1214%)
|
||||
bbb = 3144.19 +/- 3.548 (0.1128%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
@ -0,0 +1,20 @@
|
||||
set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171020-evolution1D_5x5_100Times.csv" every ::1 using 2:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171020-evolution1D_5x5_100Times_regularity-vs-steps.png"
|
||||
plot "20171020-evolution1D_5x5_100Times.csv" every ::1 using 2:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171020-evolution1D_5x5_100Times.csv" every ::1 using 4:5 via aa,bb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171020-evolution1D_5x5_100Times_improvement-vs-steps.png"
|
||||
plot "20171020-evolution1D_5x5_100Times.csv" every ::1 using 4:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171020-evolution1D_5x5_100Times.csv" every ::1 using 4:6 via aaa,bbb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Fitting error'
|
||||
set output "20171020-evolution1D_5x5_100Times_improvement-vs-evo-error.png"
|
||||
plot "20171020-evolution1D_5x5_100Times.csv" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
2131
dokumentation/evolution1d/20171020-evolution1D_5x5_100Times.log
Normal file
2131
dokumentation/evolution1d/20171020-evolution1D_5x5_100Times.log
Normal file
File diff suppressed because it is too large
Load Diff
@ -0,0 +1,37 @@
|
||||
[1] "================ Analyzing 20171020-evolution1D_5x5_100Times.csv"
|
||||
[1] "spearman for improvement-potential vs. evolution-error"
|
||||
x y
|
||||
x 1 -1
|
||||
y -1 1
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0
|
||||
y 0
|
||||
[1] "spearman for regularity vs. steps"
|
||||
x y
|
||||
x 1.00 -0.13
|
||||
y -0.13 1.00
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0.1926
|
||||
y 0.1926
|
||||
[1] "spearman for variability vs. evolution-error"
|
||||
x y
|
||||
x 1 NaN
|
||||
y NaN 1
|
||||
|
||||
n= 100
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x
|
||||
y
|
||||
@ -0,0 +1,106 @@
|
||||
"Least squares",regularity,variability,improvement,steps,"Evolution error",sigma
|
||||
185.647,0.014356,0.00111111,0.979107,223,194.608,0.0251885
|
||||
228.278,0.0166674,0.00111111,0.974309,96,239.386,0.0587051
|
||||
210.224,0.0156879,0.00111111,0.976341,148,220.631,0.0169237
|
||||
210.616,0.0124586,0.00111111,0.976305,233,220.99,0.0228667
|
||||
273.644,0.0178481,0.00111111,0.969203,121,286.984,0.0348054
|
||||
201.39,0.0178169,0.00111111,0.977335,204,211.406,0.0303567
|
||||
209.903,0.0171999,0.00111111,0.976489,120,219.459,0.0409589
|
||||
222.808,0.0168139,0.00111111,0.975037,225,233.543,0.0401666
|
||||
203.319,0.0169448,0.00111111,0.977118,210,213.447,0.0235074
|
||||
211.049,0.0176901,0.00111111,0.976248,254,221.233,0.0277544
|
||||
198.649,0.015557,0.00111111,0.977661,191,208.084,0.0312838
|
||||
202.965,0.0155469,0.00111111,0.977161,259,212.582,0.0351323
|
||||
243.06,0.0154777,0.00111111,0.972653,237,254.405,0.0356981
|
||||
222.078,0.0145561,0.00111111,0.975006,288,232.994,0.0325273
|
||||
193.881,0.0199094,0.00111111,0.97818,162,203.263,0.0298737
|
||||
193.987,0.0130592,0.00111111,0.97828,268,203.409,0.0286171
|
||||
188.631,0.0165446,0.00111111,0.978771,202,197.35,0.028157
|
||||
180.679,0.0149728,0.00111111,0.97972,125,189.628,0.0401607
|
||||
206.926,0.015751,0.00111111,0.976712,251,217.243,0.0365136
|
||||
213.045,0.0114715,0.00111111,0.976023,338,223.551,0.0298777
|
||||
172.678,0.0158423,0.00111111,0.980585,271,181.247,0.0182507
|
||||
218.003,0.0148428,0.00111111,0.975519,147,228.391,0.0452333
|
||||
211.195,0.0164286,0.00111111,0.976231,270,221.701,0.0321599
|
||||
240.495,0.0161571,0.00111111,0.972934,133,252.128,0.0552674
|
||||
200.698,0.0163158,0.00111111,0.977414,186,210.65,0.0215938
|
||||
215.725,0.0173088,0.00111111,0.975722,187,226.253,0.0289603
|
||||
202.49,0.0125383,0.00111111,0.977211,261,212.413,0.0283027
|
||||
205.788,0.0132712,0.00111111,0.97684,200,215.916,0.0308076
|
||||
214.682,0.0143839,0.00111111,0.975862,268,225.395,0.0220344
|
||||
231.114,0.0165792,0.00111111,0.97399,251,242.464,0.0253499
|
||||
185.386,0.0164515,0.00111111,0.979136,313,194.468,0.0304484
|
||||
214.335,0.0174143,0.00111111,0.975878,130,223.975,0.0362177
|
||||
183.317,0.0161095,0.00111111,0.979376,304,191.243,0.0582229
|
||||
212.715,0.0167311,0.00111111,0.97606,170,223.213,0.0342458
|
||||
196.845,0.0167791,0.00111111,0.977846,206,206.498,0.0199106
|
||||
191.37,0.0180067,0.00111111,0.978463,314,200.508,0.0321382
|
||||
221.813,0.013384,0.00111111,0.975036,195,232.713,0.0482562
|
||||
222.851,0.0160286,0.00111111,0.974955,263,233.455,0.0344433
|
||||
208.666,0.0159447,0.00111111,0.976516,223,218.831,0.0246139
|
||||
265.843,0.0164659,0.00111111,0.970081,149,278.472,0.0469066
|
||||
192.914,0.0143679,0.00111111,0.978289,254,202.505,0.0297481
|
||||
226.46,0.0175878,0.00111111,0.974514,185,237.611,0.0232642
|
||||
212.488,0.0185853,0.00111111,0.976086,230,222.704,0.0292529
|
||||
205.052,0.0176342,0.00111111,0.976923,291,215.068,0.0339813
|
||||
232.184,0.0173967,0.00111111,0.973869,219,243.65,0.0304632
|
||||
266.267,0.0147618,0.00111111,0.970033,216,279.577,0.0343761
|
||||
177.08,0.0167556,0.00111111,0.980071,241,185.929,0.0259968
|
||||
191.049,0.0138796,0.00111111,0.978499,356,200.348,0.0335199
|
||||
202.329,0.0147324,0.00111111,0.977236,258,212.262,0.0388334
|
||||
206.74,0.0177026,0.00111111,0.976733,201,216.56,0.0439213
|
||||
210.328,0.0130898,0.00111111,0.976329,231,220.799,0.0262093
|
||||
193.897,0.0201275,0.00111111,0.978178,248,203.551,0.0232533
|
||||
204.982,0.0172087,0.00111111,0.976931,319,215.113,0.0316795
|
||||
240.961,0.014936,0.00111111,0.972881,183,252.985,0.0219308
|
||||
180.8,0.0158388,0.00111111,0.979652,268,189.53,0.0263405
|
||||
235.065,0.0141919,0.00111111,0.973545,209,246.286,0.0246108
|
||||
191.202,0.0155234,0.00111111,0.978482,240,200.739,0.0320649
|
||||
261.864,0.0162687,0.00111111,0.970529,104,274.27,0.045422
|
||||
197.479,0.0145463,0.00111111,0.977775,226,207.251,0.0213115
|
||||
213.281,0.0154231,0.00111111,0.975997,260,223.877,0.0288002
|
||||
208.048,0.0179031,0.00111111,0.976585,224,218.369,0.0181026
|
||||
176.232,0.0184922,0.00111111,0.980166,336,184.794,0.0301405
|
||||
217.44,0.0162194,0.00111111,0.975528,223,228.064,0.0268147
|
||||
231.411,0.0166529,0.00111111,0.973956,146,242.68,0.0381561
|
||||
197.923,0.0162844,0.00111111,0.977726,315,207.781,0.019324
|
||||
171.524,0.0131308,0.00111111,0.980697,288,180.093,0.0370283
|
||||
229.186,0.0166106,0.00111111,0.974207,230,240.421,0.0268132
|
||||
233.517,0.0149928,0.00111111,0.973719,233,244.614,0.0333904
|
||||
219.952,0.0155735,0.00111111,0.975246,229,230.875,0.019978
|
||||
158.326,0.0151468,0.00111111,0.982181,248,166.147,0.0285648
|
||||
233.011,0.0175349,0.00111111,0.973785,156,244.438,0.0464821
|
||||
226.006,0.0157648,0.00111111,0.974564,124,236.881,0.033025
|
||||
256.376,0.0131813,0.00111111,0.971156,268,269.08,0.0278261
|
||||
215.825,0.0159012,0.00111111,0.975712,189,226.565,0.026596
|
||||
199.66,0.0178054,0.00111111,0.977533,224,209.625,0.0232476
|
||||
220.113,0.0137952,0.00111111,0.975287,154,230.205,0.0519984
|
||||
174.879,0.0144725,0.00111111,0.980319,211,183.499,0.026459
|
||||
213.68,0.00982581,0.00111111,0.975952,359,224.238,0.0258146
|
||||
244.965,0.0129242,0.00111111,0.972431,129,255.764,0.0440628
|
||||
231.825,0.015597,0.00111111,0.97391,298,243.406,0.0291375
|
||||
193.252,0.0131953,0.00111111,0.978363,242,202.853,0.0196507
|
||||
225.094,0.0168805,0.00111111,0.974667,183,236.104,0.0230592
|
||||
232.684,0.01661,0.00111111,0.973813,184,244.282,0.0342288
|
||||
235.095,0.0178999,0.00111111,0.973542,128,246.25,0.0391641
|
||||
233.933,0.0170346,0.00111111,0.973687,235,245.252,0.0270962
|
||||
211.237,0.0146474,0.00111111,0.976227,205,221.375,0.0361901
|
||||
239.651,0.0120497,0.00111111,0.97303,293,250.708,0.0436588
|
||||
188.131,0.0181584,0.00111111,0.978827,203,197.442,0.021137
|
||||
206.368,0.0144154,0.00111111,0.976775,341,216.343,0.0302359
|
||||
195.677,0.0175799,0.00111111,0.977978,184,205.377,0.0308378
|
||||
188.007,0.0150014,0.00111111,0.978841,257,197.24,0.0269627
|
||||
203.558,0.0164905,0.00111111,0.977091,182,213.491,0.01867
|
||||
231.787,0.0159009,0.00111111,0.973917,251,242.953,0.0340664
|
||||
192.961,0.0164376,0.00111111,0.978283,285,202.597,0.0333827
|
||||
246.133,0.0126244,0.00111111,0.972299,150,257.093,0.0542747
|
||||
257.313,0.0166456,0.00111111,0.971041,134,269.909,0.0314991
|
||||
229.079,0.0200458,0.00111111,0.974331,144,240.485,0.0269038
|
||||
184.348,0.0140723,0.00111111,0.979253,299,193.523,0.0332981
|
||||
210.198,0.0166009,0.00111111,0.976344,187,220.534,0.0242483
|
||||
229.809,0.0162801,0.00111111,0.974136,169,241.175,0.0226505
|
||||
237.845,0.0166568,0.00111111,0.97328,215,249.694,0.0358862
|
||||
209.702,0.0169816,0.00111111,0.976399,337,220.167,0.0178628
|
||||
249.535,0.0171186,0.00111111,0.971916,134,261.211,0.0522281
|
||||
189.733,0.0132482,0.00111111,0.978647,235,199.087,0.0225015
|
||||
190.886,0.0131875,0.00111111,0.978517,194,200.364,0.0240832
|
||||
|
@ -0,0 +1,106 @@
|
||||
"Evolution error"
|
||||
194.608
|
||||
239.386
|
||||
220.631
|
||||
220.99
|
||||
286.984
|
||||
211.406
|
||||
219.459
|
||||
233.543
|
||||
213.447
|
||||
221.233
|
||||
208.084
|
||||
212.582
|
||||
254.405
|
||||
232.994
|
||||
203.263
|
||||
203.409
|
||||
197.35
|
||||
189.628
|
||||
217.243
|
||||
223.551
|
||||
181.247
|
||||
228.391
|
||||
221.701
|
||||
252.128
|
||||
210.65
|
||||
226.253
|
||||
212.413
|
||||
215.916
|
||||
225.395
|
||||
242.464
|
||||
194.468
|
||||
223.975
|
||||
191.243
|
||||
223.213
|
||||
206.498
|
||||
200.508
|
||||
232.713
|
||||
233.455
|
||||
218.831
|
||||
278.472
|
||||
202.505
|
||||
237.611
|
||||
222.704
|
||||
215.068
|
||||
243.65
|
||||
279.577
|
||||
185.929
|
||||
200.348
|
||||
212.262
|
||||
216.56
|
||||
220.799
|
||||
203.551
|
||||
215.113
|
||||
252.985
|
||||
189.53
|
||||
246.286
|
||||
200.739
|
||||
274.27
|
||||
207.251
|
||||
223.877
|
||||
218.369
|
||||
184.794
|
||||
228.064
|
||||
242.68
|
||||
207.781
|
||||
180.093
|
||||
240.421
|
||||
244.614
|
||||
230.875
|
||||
166.147
|
||||
244.438
|
||||
236.881
|
||||
269.08
|
||||
226.565
|
||||
209.625
|
||||
230.205
|
||||
183.499
|
||||
224.238
|
||||
255.764
|
||||
243.406
|
||||
202.853
|
||||
236.104
|
||||
244.282
|
||||
246.25
|
||||
245.252
|
||||
221.375
|
||||
250.708
|
||||
197.442
|
||||
216.343
|
||||
205.377
|
||||
197.24
|
||||
213.491
|
||||
242.953
|
||||
202.597
|
||||
257.093
|
||||
269.909
|
||||
240.485
|
||||
193.523
|
||||
220.534
|
||||
241.175
|
||||
249.694
|
||||
220.167
|
||||
261.211
|
||||
199.087
|
||||
200.364
|
||||
@ -0,0 +1,138 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171020-evolution1D_5x5_100Times_2-addedOne.csv" every ::1 using 2:5
|
||||
format = x:z
|
||||
#datapoints = 105
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: f(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 5.50446e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707196
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 357529
|
||||
rel. change during last iteration : -2.04772e-09
|
||||
|
||||
degrees of freedom (FIT_NDF) : 103
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 58.9165
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 3471.16
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -8895.71 +/- 3121 (35.09%)
|
||||
b = 362.23 +/- 49.61 (13.7%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.993 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171020-evolution1D_5x5_100Times_2-addedOne.csv" every ::1 using 4:5
|
||||
format = x:z
|
||||
#datapoints = 105
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: g(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 5.46001e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.988111
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 313329
|
||||
rel. change during last iteration : -7.67387e-08
|
||||
|
||||
degrees of freedom (FIT_NDF) : 103
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 55.1546
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 3042.03
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 10277.4 +/- 2107 (20.5%)
|
||||
bb = -9809.71 +/- 2056 (20.96%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171020-evolution1D_5x5_100Times_2-addedOne.csv" every ::1 using 4:6
|
||||
format = x:z
|
||||
#datapoints = 105
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: h(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 5.18982e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.988111
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 12.9217
|
||||
rel. change during last iteration : -9.78104e-13
|
||||
|
||||
degrees of freedom (FIT_NDF) : 103
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.354194
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.125453
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -9289.92 +/- 13.53 (0.1456%)
|
||||
bbb = 9290.67 +/- 13.21 (0.1421%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
@ -0,0 +1,272 @@
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 5.50446e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707196
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 385823 delta(WSSR)/WSSR : -13.2668
|
||||
delta(WSSR) : -5.11864e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0707196
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -1.86573
|
||||
b = 220.792
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 382086 delta(WSSR)/WSSR : -0.0097808
|
||||
delta(WSSR) : -3737.11 limit for stopping : 1e-05
|
||||
lambda : 0.00707196
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -593.106
|
||||
b = 231.171
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 357901 delta(WSSR)/WSSR : -0.067574
|
||||
delta(WSSR) : -24184.8 limit for stopping : 1e-05
|
||||
lambda : 0.000707196
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -7873.39
|
||||
b = 346.092
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 357529 delta(WSSR)/WSSR : -0.00104138
|
||||
delta(WSSR) : -372.325 limit for stopping : 1e-05
|
||||
lambda : 7.07196e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -8894.28
|
||||
b = 362.207
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 357529 delta(WSSR)/WSSR : -2.04772e-09
|
||||
delta(WSSR) : -0.000732119 limit for stopping : 1e-05
|
||||
lambda : 7.07196e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -8895.71
|
||||
b = 362.23
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 357529
|
||||
rel. change during last iteration : -2.04772e-09
|
||||
|
||||
degrees of freedom (FIT_NDF) : 103
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 58.9165
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 3471.16
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -8895.71 +/- 3121 (35.09%)
|
||||
b = 362.23 +/- 49.61 (13.7%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.993 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 5.46001e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.988111
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 384230 delta(WSSR)/WSSR : -13.2103
|
||||
delta(WSSR) : -5.07578e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0988111
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 114.034
|
||||
bb = 109.495
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 379288 delta(WSSR)/WSSR : -0.0130279
|
||||
delta(WSSR) : -4941.33 limit for stopping : 1e-05
|
||||
lambda : 0.00988111
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 467.204
|
||||
bb = -234.184
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 316453 delta(WSSR)/WSSR : -0.198559
|
||||
delta(WSSR) : -62834.8 limit for stopping : 1e-05
|
||||
lambda : 0.000988111
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 8142.31
|
||||
bb = -7725.68
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 313329 delta(WSSR)/WSSR : -0.00997133
|
||||
delta(WSSR) : -3124.31 limit for stopping : 1e-05
|
||||
lambda : 9.88111e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 10271.5
|
||||
bb = -9803.93
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 313329 delta(WSSR)/WSSR : -7.67387e-08
|
||||
delta(WSSR) : -0.0240445 limit for stopping : 1e-05
|
||||
lambda : 9.88111e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 10277.4
|
||||
bb = -9809.71
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 313329
|
||||
rel. change during last iteration : -7.67387e-08
|
||||
|
||||
degrees of freedom (FIT_NDF) : 103
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 55.1546
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 3042.03
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 10277.4 +/- 2107 (20.5%)
|
||||
bb = -9809.71 +/- 2056 (20.96%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 5.18982e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.988111
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 60660.8 delta(WSSR)/WSSR : -84.5548
|
||||
delta(WSSR) : -5.12916e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0988111
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = 107.576
|
||||
bbb = 116.947
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 56417.5 delta(WSSR)/WSSR : -0.0752119
|
||||
delta(WSSR) : -4243.27 limit for stopping : 1e-05
|
||||
lambda : 0.00988111
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -218.01
|
||||
bbb = 435.791
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 2684.68 delta(WSSR)/WSSR : -20.0146
|
||||
delta(WSSR) : -53732.8 limit for stopping : 1e-05
|
||||
lambda : 0.000988111
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -7315.5
|
||||
bbb = 7363.48
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 12.9423 delta(WSSR)/WSSR : -206.435
|
||||
delta(WSSR) : -2671.74 limit for stopping : 1e-05
|
||||
lambda : 9.88111e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -9284.44
|
||||
bbb = 9285.32
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 12.9217 delta(WSSR)/WSSR : -0.00159124
|
||||
delta(WSSR) : -0.0205615 limit for stopping : 1e-05
|
||||
lambda : 9.88111e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -9289.92
|
||||
bbb = 9290.67
|
||||
/
|
||||
|
||||
Iteration 6
|
||||
WSSR : 12.9217 delta(WSSR)/WSSR : -9.78104e-13
|
||||
delta(WSSR) : -1.26388e-11 limit for stopping : 1e-05
|
||||
lambda : 9.88111e-07
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -9289.92
|
||||
bbb = 9290.67
|
||||
|
||||
After 6 iterations the fit converged.
|
||||
final sum of squares of residuals : 12.9217
|
||||
rel. change during last iteration : -9.78104e-13
|
||||
|
||||
degrees of freedom (FIT_NDF) : 103
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.354194
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.125453
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -9289.92 +/- 13.53 (0.1456%)
|
||||
bbb = 9290.67 +/- 13.21 (0.1421%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
@ -0,0 +1,20 @@
|
||||
set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171020-evolution1D_5x5_100Times_2-addedOne.csv" every ::1 using 2:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171020-evolution1D_5x5_100Times_2-addedOne_regularity-vs-steps.png"
|
||||
plot "20171020-evolution1D_5x5_100Times_2-addedOne.csv" every ::1 using 2:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171020-evolution1D_5x5_100Times_2-addedOne.csv" every ::1 using 4:5 via aa,bb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171020-evolution1D_5x5_100Times_2-addedOne_improvement-vs-steps.png"
|
||||
plot "20171020-evolution1D_5x5_100Times_2-addedOne.csv" every ::1 using 4:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171020-evolution1D_5x5_100Times_2-addedOne.csv" every ::1 using 4:6 via aaa,bbb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Fitting error'
|
||||
set output "20171020-evolution1D_5x5_100Times_2-addedOne_improvement-vs-evo-error.png"
|
||||
plot "20171020-evolution1D_5x5_100Times_2-addedOne.csv" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
File diff suppressed because it is too large
Load Diff
@ -0,0 +1,37 @@
|
||||
[1] "================ Analyzing 20171020-evolution1D_5x5_100Times_2-addedOne.csv"
|
||||
[1] "spearman for improvement-potential vs. evolution-error"
|
||||
x y
|
||||
x 1 -1
|
||||
y -1 1
|
||||
|
||||
n= 105
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0
|
||||
y 0
|
||||
[1] "spearman for regularity vs. steps"
|
||||
x y
|
||||
x 1.00 -0.26
|
||||
y -0.26 1.00
|
||||
|
||||
n= 105
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x 0.0069
|
||||
y 0.0069
|
||||
[1] "spearman for variability vs. evolution-error"
|
||||
x y
|
||||
x 1 NaN
|
||||
y NaN 1
|
||||
|
||||
n= 105
|
||||
|
||||
|
||||
P
|
||||
x y
|
||||
x
|
||||
y
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 5.6 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 6.0 KiB |
Binary file not shown.
|
After Width: | Height: | Size: 5.6 KiB |
@ -0,0 +1,101 @@
|
||||
"Least squares",regularity,variability,improvement,steps,"Evolution error",sigma
|
||||
208.251,0.0156103,0.00111111,0.930454,219,218.554,0.0237623
|
||||
205.745,0.0164894,0.00111111,0.931291,284,215.888,0.0246676
|
||||
262.299,0.0141122,0.00111111,0.912515,129,274.375,0.0565738
|
||||
224.957,0.0152828,0.00111111,0.924875,200,236.199,0.0374467
|
||||
210.151,0.0132398,0.00111111,0.92982,261,220.524,0.025062
|
||||
187.467,0.0159945,0.00111111,0.937395,202,196.458,0.0294108
|
||||
243.284,0.0186985,0.00111111,0.918838,151,255.181,0.0419001
|
||||
205.644,0.0179346,0.00111111,0.931659,219,215.837,0.0289177
|
||||
218.884,0.0197365,0.00111111,0.926907,215,229.777,0.0268596
|
||||
188.388,0.0155439,0.00111111,0.937088,226,197.728,0.0254865
|
||||
211.745,0.0161295,0.00111111,0.929349,204,222.315,0.0222368
|
||||
194.615,0.0159007,0.00111111,0.935011,185,204.324,0.0209588
|
||||
178.431,0.0163466,0.00111111,0.940413,212,187.221,0.0280782
|
||||
276.203,0.0190878,0.00111111,0.907762,141,289.253,0.0332024
|
||||
199.444,0.0152092,0.00111111,0.933395,309,209.38,0.0332999
|
||||
192.346,0.0155373,0.00111111,0.935766,255,201.838,0.0300946
|
||||
223.725,0.0166533,0.00111111,0.925287,120,234.713,0.0389049
|
||||
185.109,0.0160023,0.00111111,0.938243,357,194.356,0.0158333
|
||||
198.016,0.0166753,0.00111111,0.933872,293,207.713,0.0261414
|
||||
211.251,0.0190468,0.00111111,0.929452,246,221.794,0.0255768
|
||||
221.043,0.0134399,0.00111111,0.926182,151,231.891,0.0345185
|
||||
240.075,0.016048,0.00111111,0.919837,235,252.009,0.0217227
|
||||
207.312,0.016896,0.00111111,0.930912,223,217.426,0.0276136
|
||||
211.082,0.0172862,0.00111111,0.929509,294,221.445,0.0443438
|
||||
245.321,0.0191785,0.00111111,0.918077,167,257.465,0.0351721
|
||||
244.739,0.0157521,0.00111111,0.918333,226,256.592,0.0373863
|
||||
223.619,0.0162014,0.00111111,0.925322,160,234.339,0.0383885
|
||||
219.046,0.0157983,0.00111111,0.926849,187,229.724,0.0289253
|
||||
197.268,0.014696,0.00111111,0.934122,278,207.016,0.0270345
|
||||
187.175,0.0148869,0.00111111,0.937493,182,196.505,0.0329261
|
||||
193.197,0.0159364,0.00111111,0.935524,155,202.122,0.0380707
|
||||
202.731,0.0167975,0.00111111,0.932298,200,212.556,0.029387
|
||||
188.371,0.0129935,0.00111111,0.937093,280,197.783,0.0235418
|
||||
229.724,0.0168458,0.00111111,0.923357,135,240.317,0.0404449
|
||||
229.376,0.0175321,0.00111111,0.9234,185,240.693,0.0362523
|
||||
246.277,0.0130564,0.00111111,0.917755,121,258.116,0.0559509
|
||||
211.323,0.0147458,0.00111111,0.929428,267,221.524,0.0350329
|
||||
206.252,0.0154743,0.00111111,0.931122,131,216.335,0.0506455
|
||||
204.337,0.0195766,0.00111111,0.931761,141,214.214,0.0304005
|
||||
194.742,0.0171276,0.00111111,0.934979,262,204.095,0.0245503
|
||||
223.878,0.0151602,0.00111111,0.925236,180,234.645,0.0330038
|
||||
217.188,0.0136059,0.00111111,0.927472,142,227.992,0.0236646
|
||||
226.019,0.0175302,0.00111111,0.924521,167,237.221,0.0200143
|
||||
195.306,0.0147572,0.00111111,0.934777,288,205.039,0.0302338
|
||||
218.29,0.0169948,0.00111111,0.927102,216,228.952,0.0268954
|
||||
209.079,0.0185921,0.00111111,0.930178,171,219.368,0.0175072
|
||||
208.333,0.0166852,0.00111111,0.930544,185,218.239,0.0267055
|
||||
215.551,0.0156959,0.00111111,0.928115,239,226.308,0.0307541
|
||||
210.163,0.0143026,0.00111111,0.929816,212,220.379,0.0314692
|
||||
196.156,0.0158837,0.00111111,0.934493,265,205.943,0.0334331
|
||||
209.587,0.0140575,0.00111111,0.930062,172,219.746,0.041743
|
||||
206.029,0.0161449,0.00111111,0.931196,262,216.152,0.0287446
|
||||
214.555,0.018111,0.00111111,0.928683,233,225.258,0.0465493
|
||||
204.087,0.0156288,0.00111111,0.931845,319,214.278,0.0280257
|
||||
182.573,0.0131847,0.00111111,0.939033,301,191.56,0.0271354
|
||||
184.499,0.0150507,0.00111111,0.938386,208,193.72,0.0290137
|
||||
245.41,0.0185819,0.00111111,0.918045,188,257.562,0.026555
|
||||
205.876,0.0141595,0.00111111,0.931247,175,216.097,0.0299926
|
||||
220.681,0.0166829,0.00111111,0.926304,246,231.642,0.0226254
|
||||
246.441,0.0204901,0.00111111,0.917701,141,258.616,0.024422
|
||||
204.64,0.016331,0.00111111,0.93166,225,214.487,0.0355979
|
||||
204.459,0.012116,0.00111111,0.931721,237,214.517,0.018181
|
||||
207.989,0.0186847,0.00111111,0.930542,112,217.707,0.0454783
|
||||
221.608,0.0140767,0.00111111,0.925994,193,231.438,0.0494232
|
||||
234.879,0.0164438,0.00111111,0.921562,248,246.342,0.0216915
|
||||
232.335,0.0143684,0.00111111,0.922412,186,243.702,0.0454547
|
||||
240.425,0.0191828,0.00111111,0.91971,152,252.271,0.0374549
|
||||
223.711,0.0173486,0.00111111,0.925291,203,234.365,0.0416848
|
||||
189.186,0.0177615,0.00111111,0.936821,157,197.813,0.0354675
|
||||
225.668,0.0149183,0.00111111,0.924638,161,236.785,0.0294055
|
||||
190.516,0.013475,0.00111111,0.936377,194,199.476,0.0368492
|
||||
181.448,0.0190386,0.00111111,0.939426,172,190.418,0.0197871
|
||||
174.893,0.013657,0.00111111,0.941595,209,183.54,0.0249911
|
||||
239.432,0.0167526,0.00111111,0.920148,112,251.338,0.0424673
|
||||
216.12,0.0177558,0.00111111,0.927826,230,226.87,0.0131177
|
||||
199.419,0.0165644,0.00111111,0.933404,180,209.377,0.0360779
|
||||
214.187,0.015712,0.00111111,0.928472,334,224.776,0.0236814
|
||||
220.124,0.0146528,0.00111111,0.926489,195,231.062,0.0221922
|
||||
213.278,0.0117894,0.00111111,0.928798,306,223.872,0.0196314
|
||||
232.559,0.0143261,0.00111111,0.922671,143,243.782,0.03507
|
||||
226.85,0.0130241,0.00111111,0.924243,191,237.917,0.0356397
|
||||
239.534,0.0175992,0.00111111,0.920007,153,251.363,0.0250786
|
||||
189.334,0.0168291,0.00111111,0.936772,220,198.154,0.0291626
|
||||
222.884,0.0167893,0.00111111,0.925568,173,234.026,0.0286739
|
||||
217.705,0.0123857,0.00111111,0.927326,205,228.503,0.0233835
|
||||
219.242,0.0186138,0.00111111,0.926784,146,230.184,0.0161714
|
||||
229.813,0.0169982,0.00111111,0.923254,253,241.123,0.030569
|
||||
252.056,0.0140714,0.00111111,0.915826,244,264.597,0.0308211
|
||||
189.176,0.0138221,0.00111111,0.936824,186,198.256,0.0382027
|
||||
191.39,0.0157992,0.00111111,0.936419,266,200.756,0.02373
|
||||
190.972,0.0143532,0.00111111,0.936225,207,200.251,0.0285909
|
||||
238.237,0.0134806,0.00111111,0.92044,220,250.132,0.0133152
|
||||
188.447,0.0164881,0.00111111,0.937068,249,197.721,0.0347174
|
||||
220.511,0.0147817,0.00111111,0.92636,200,231.451,0.0277416
|
||||
227.83,0.0181621,0.00111111,0.923938,269,238.912,0.029632
|
||||
195.281,0.0171527,0.00111111,0.934786,246,204.402,0.0286607
|
||||
194.106,0.0150671,0.00111111,0.935193,209,203.589,0.0364586
|
||||
193.872,0.0118606,0.00111111,0.935256,186,203.051,0.0436481
|
||||
268.274,0.018024,0.00111111,0.910409,120,281.253,0.0400486
|
||||
256.839,0.0147597,0.00111111,0.914228,165,269.672,0.0250823
|
||||
|
@ -0,0 +1,101 @@
|
||||
"Evolution error"
|
||||
218.554
|
||||
215.888
|
||||
274.375
|
||||
236.199
|
||||
220.524
|
||||
196.458
|
||||
255.181
|
||||
215.837
|
||||
229.777
|
||||
197.728
|
||||
222.315
|
||||
204.324
|
||||
187.221
|
||||
289.253
|
||||
209.38
|
||||
201.838
|
||||
234.713
|
||||
194.356
|
||||
207.713
|
||||
221.794
|
||||
231.891
|
||||
252.009
|
||||
217.426
|
||||
221.445
|
||||
257.465
|
||||
256.592
|
||||
234.339
|
||||
229.724
|
||||
207.016
|
||||
196.505
|
||||
202.122
|
||||
212.556
|
||||
197.783
|
||||
240.317
|
||||
240.693
|
||||
258.116
|
||||
221.524
|
||||
216.335
|
||||
214.214
|
||||
204.095
|
||||
234.645
|
||||
227.992
|
||||
237.221
|
||||
205.039
|
||||
228.952
|
||||
219.368
|
||||
218.239
|
||||
226.308
|
||||
220.379
|
||||
205.943
|
||||
219.746
|
||||
216.152
|
||||
225.258
|
||||
214.278
|
||||
191.56
|
||||
193.72
|
||||
257.562
|
||||
216.097
|
||||
231.642
|
||||
258.616
|
||||
214.487
|
||||
214.517
|
||||
217.707
|
||||
231.438
|
||||
246.342
|
||||
243.702
|
||||
252.271
|
||||
234.365
|
||||
197.813
|
||||
236.785
|
||||
199.476
|
||||
190.418
|
||||
183.54
|
||||
251.338
|
||||
226.87
|
||||
209.377
|
||||
224.776
|
||||
231.062
|
||||
223.872
|
||||
243.782
|
||||
237.917
|
||||
251.363
|
||||
198.154
|
||||
234.026
|
||||
228.503
|
||||
230.184
|
||||
241.123
|
||||
264.597
|
||||
198.256
|
||||
200.756
|
||||
200.251
|
||||
250.132
|
||||
197.721
|
||||
231.451
|
||||
238.912
|
||||
204.402
|
||||
203.589
|
||||
203.051
|
||||
281.253
|
||||
269.672
|
||||
@ -0,0 +1,138 @@
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171020-evolution1D_5x5_100Times_2.csv" every ::1 using 2:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: f(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.55694e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707198
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 271763
|
||||
rel. change during last iteration : -1.01351e-09
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 52.6602
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 2773.1
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -5580.61 +/- 2768 (49.6%)
|
||||
b = 296.806 +/- 44.49 (14.99%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.993 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171020-evolution1D_5x5_100Times_2.csv" every ::1 using 4:5
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: g(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.51925e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.964973
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 233709
|
||||
rel. change during last iteration : -1.76515e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 48.8343
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 2384.79
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 3176.73 +/- 698.5 (21.99%)
|
||||
bb = -2742.16 +/- 648.7 (23.65%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
*******************************************************************************
|
||||
Tue Oct 24 02:24:04 2017
|
||||
|
||||
|
||||
FIT: data read from "20171020-evolution1D_5x5_100Times_2.csv" every ::1 using 4:6
|
||||
format = x:z
|
||||
#datapoints = 100
|
||||
residuals are weighted equally (unit weight)
|
||||
|
||||
function used for fitting: h(x)
|
||||
fitted parameters initialized with current variable values
|
||||
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.99472e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.964973
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 10.1354
|
||||
rel. change during last iteration : -4.55776e-07
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.321593
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.103422
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -3140.1 +/- 4.6 (0.1465%)
|
||||
bbb = 3140.23 +/- 4.272 (0.136%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
@ -0,0 +1,261 @@
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.55694e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.707198
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
a = 1
|
||||
b = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 283142 delta(WSSR)/WSSR : -15.0942
|
||||
delta(WSSR) : -4.27379e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0707198
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = 0.244292
|
||||
b = 206.717
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 281566 delta(WSSR)/WSSR : -0.00559538
|
||||
delta(WSSR) : -1575.47 limit for stopping : 1e-05
|
||||
lambda : 0.00707198
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -376.256
|
||||
b = 213.754
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 271908 delta(WSSR)/WSSR : -0.0355197
|
||||
delta(WSSR) : -9658.1 limit for stopping : 1e-05
|
||||
lambda : 0.000707198
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -4948.6
|
||||
b = 286.721
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 271763 delta(WSSR)/WSSR : -0.000531939
|
||||
delta(WSSR) : -144.561 limit for stopping : 1e-05
|
||||
lambda : 7.07198e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -5579.74
|
||||
b = 296.792
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 271763 delta(WSSR)/WSSR : -1.01351e-09
|
||||
delta(WSSR) : -0.000275435 limit for stopping : 1e-05
|
||||
lambda : 7.07198e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
a = -5580.61
|
||||
b = 296.806
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 271763
|
||||
rel. change during last iteration : -1.01351e-09
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 52.6602
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 2773.1
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
a = -5580.61 +/- 2768 (49.6%)
|
||||
b = 296.806 +/- 44.49 (14.99%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
a b
|
||||
a 1.000
|
||||
b -0.993 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.51925e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.964973
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aa = 1
|
||||
bb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 279714 delta(WSSR)/WSSR : -15.1567
|
||||
delta(WSSR) : -4.23953e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0964973
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 111.794
|
||||
bb = 102.988
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 261643 delta(WSSR)/WSSR : -0.0690668
|
||||
delta(WSSR) : -18070.9 limit for stopping : 1e-05
|
||||
lambda : 0.00964973
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 786.112
|
||||
bb = -522.176
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 233742 delta(WSSR)/WSSR : -0.119368
|
||||
delta(WSSR) : -27901.4 limit for stopping : 1e-05
|
||||
lambda : 0.000964973
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 3094.82
|
||||
bb = -2666.1
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 233709 delta(WSSR)/WSSR : -0.000140322
|
||||
delta(WSSR) : -32.7945 limit for stopping : 1e-05
|
||||
lambda : 9.64973e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 3176.7
|
||||
bb = -2742.13
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 233709 delta(WSSR)/WSSR : -1.76515e-11
|
||||
delta(WSSR) : -4.12532e-06 limit for stopping : 1e-05
|
||||
lambda : 9.64973e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aa = 3176.73
|
||||
bb = -2742.16
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 233709
|
||||
rel. change during last iteration : -1.76515e-11
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 48.8343
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 2384.79
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aa = 3176.73 +/- 698.5 (21.99%)
|
||||
bb = -2742.16 +/- 648.7 (23.65%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aa bb
|
||||
aa 1.000
|
||||
bb -1.000 1.000
|
||||
|
||||
|
||||
Iteration 0
|
||||
WSSR : 4.99472e+06 delta(WSSR)/WSSR : 0
|
||||
delta(WSSR) : 0 limit for stopping : 1e-05
|
||||
lambda : 0.964973
|
||||
|
||||
initial set of free parameter values
|
||||
|
||||
aaa = 1
|
||||
bbb = 1
|
||||
/
|
||||
|
||||
Iteration 1
|
||||
WSSR : 51532.4 delta(WSSR)/WSSR : -95.9239
|
||||
delta(WSSR) : -4.94319e+06 limit for stopping : 1e-05
|
||||
lambda : 0.0964973
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = 102.17
|
||||
bbb = 128.276
|
||||
/
|
||||
|
||||
Iteration 2
|
||||
WSSR : 31291.4 delta(WSSR)/WSSR : -0.646854
|
||||
delta(WSSR) : -20241 limit for stopping : 1e-05
|
||||
lambda : 0.00964973
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -610.313
|
||||
bbb = 791.01
|
||||
/
|
||||
|
||||
Iteration 3
|
||||
WSSR : 46.8594 delta(WSSR)/WSSR : -666.773
|
||||
delta(WSSR) : -31244.6 limit for stopping : 1e-05
|
||||
lambda : 0.000964973
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3053.42
|
||||
bbb = 3059.74
|
||||
/
|
||||
|
||||
Iteration 4
|
||||
WSSR : 10.1354 delta(WSSR)/WSSR : -3.62335
|
||||
delta(WSSR) : -36.724 limit for stopping : 1e-05
|
||||
lambda : 9.64973e-05
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3140.07
|
||||
bbb = 3140.21
|
||||
/
|
||||
|
||||
Iteration 5
|
||||
WSSR : 10.1354 delta(WSSR)/WSSR : -4.55776e-07
|
||||
delta(WSSR) : -4.61945e-06 limit for stopping : 1e-05
|
||||
lambda : 9.64973e-06
|
||||
|
||||
resultant parameter values
|
||||
|
||||
aaa = -3140.1
|
||||
bbb = 3140.23
|
||||
|
||||
After 5 iterations the fit converged.
|
||||
final sum of squares of residuals : 10.1354
|
||||
rel. change during last iteration : -4.55776e-07
|
||||
|
||||
degrees of freedom (FIT_NDF) : 98
|
||||
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 0.321593
|
||||
variance of residuals (reduced chisquare) = WSSR/ndf : 0.103422
|
||||
|
||||
Final set of parameters Asymptotic Standard Error
|
||||
======================= ==========================
|
||||
|
||||
aaa = -3140.1 +/- 4.6 (0.1465%)
|
||||
bbb = 3140.23 +/- 4.272 (0.136%)
|
||||
|
||||
|
||||
correlation matrix of the fit parameters:
|
||||
|
||||
aaa bbb
|
||||
aaa 1.000
|
||||
bbb -1.000 1.000
|
||||
@ -0,0 +1,20 @@
|
||||
set datafile separator ","
|
||||
f(x)=a*x+b
|
||||
fit f(x) "20171020-evolution1D_5x5_100Times_2.csv" every ::1 using 2:5 via a,b
|
||||
set terminal png
|
||||
set xlabel 'Regularity'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171020-evolution1D_5x5_100Times_2_regularity-vs-steps.png"
|
||||
plot "20171020-evolution1D_5x5_100Times_2.csv" every ::1 using 2:5 title "data", f(x) title "lin. fit" lc rgb "black"
|
||||
g(x)=aa*x+bb
|
||||
fit g(x) "20171020-evolution1D_5x5_100Times_2.csv" every ::1 using 4:5 via aa,bb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Iterations'
|
||||
set output "20171020-evolution1D_5x5_100Times_2_improvement-vs-steps.png"
|
||||
plot "20171020-evolution1D_5x5_100Times_2.csv" every ::1 using 4:5 title "data", g(x) title "lin. fit" lc rgb "black"
|
||||
h(x)=aaa*x+bbb
|
||||
fit h(x) "20171020-evolution1D_5x5_100Times_2.csv" every ::1 using 4:6 via aaa,bbb
|
||||
set xlabel 'Improvement potential'
|
||||
set ylabel 'Fitting error'
|
||||
set output "20171020-evolution1D_5x5_100Times_2_improvement-vs-evo-error.png"
|
||||
plot "20171020-evolution1D_5x5_100Times_2.csv" every ::1 using 4:6 title "data", h(x) title "lin. fit" lc rgb "black"
|
||||
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Loading…
Reference in New Issue
Block a user