commit 34a3e6beebccc225dadd3fa7a2c65d0a39fe6086 parent 59a042190f69fe9d4ba146e26d0769c500d18680 Author: miksa <milutin@popovic.xyz> Date: Sun, 18 Apr 2021 11:03:15 +0200 done my part Diffstat:
23 files changed, 260 insertions(+), 188 deletions(-)
diff --git a/sesh1/prog/t0-method/__pycache__/method.cpython-39.pyc b/sesh1/prog/t0-method/__pycache__/method.cpython-39.pyc Binary files differ. diff --git a/sesh1/prog/t0-method/method.py b/sesh1/prog/t0-method/method.py @@ -24,7 +24,7 @@ def t0_fit(model, var_str, x_data, y_data,\ if way == 0: # consider D'Agostini bias P = np.linalg.inv(cov_relsyst @ np.outer(f2, f2) + cov_stat) else: # don't consider D'Agostini bias - P = np.linalg.inv(cov_relsyst * (p0@p0) + cov_stat) + P = np.linalg.inv(cov_relsyst * (y_data@y_data) + cov_stat) delta_p = np.linalg.inv(A.T @ P @ A) @ A.T @ P @ (y_data - f2) p0 = p0 + alpha*delta_p diff --git a/sesh1/prog/t0-method/plots/wrong-BABAR.png b/sesh1/prog/t0-method/plots/wrong-BABAR.png Binary files differ. diff --git a/sesh1/prog/t0-method/plots/wrong-CMD2.png b/sesh1/prog/t0-method/plots/wrong-CMD2.png Binary files differ. diff --git a/sesh1/prog/t0-method/plots/wrong-KLOE.png b/sesh1/prog/t0-method/plots/wrong-KLOE.png Binary files differ. diff --git a/sesh1/prog/t0-method/plots/wrong-SND.png b/sesh1/prog/t0-method/plots/wrong-SND.png Binary files differ. diff --git a/sesh1/prog/t0-method/results/wrong-BABAR.txt b/sesh1/prog/t0-method/results/wrong-BABAR.txt @@ -0,0 +1,10 @@ +773.42 \pm 0.54 +149.29 \pm 1.01 +782.18 \pm 0.07 +8.18 \pm 0.18 +1.94 \pm 0.04 +440.67 \pm 138.61 +-289.03 \pm 409.31 +211.86 \pm 311.26 +chi_sq_min_dof = 1.1172391440233365 +p_value = 0.09869201926400895 diff --git a/sesh1/prog/t0-method/results/wrong-CMD2.txt b/sesh1/prog/t0-method/results/wrong-CMD2.txt @@ -0,0 +1,10 @@ +774.51 \pm 2.59 +145.18 \pm 5.83 +782.09 \pm 0.32 +8.58 \pm 1.5 +1.85 \pm 0.38 +480.53 \pm 583.22 +-546.52 \pm 1896.02 +385.74 \pm 1434.8 +chi_sq_min_dof = 0.12492919312415478 +p_value = 0.9999999999967275 diff --git a/sesh1/prog/t0-method/results/wrong-KLOE.txt b/sesh1/prog/t0-method/results/wrong-KLOE.txt @@ -0,0 +1,10 @@ +774.09 \pm 0.44 +149.89 \pm 0.84 +782.79 \pm 0.18 +11.11 \pm 0.7 +2.15 \pm 0.08 +382.54 \pm 212.24 +-66.44 \pm 664.67 +-83.95 \pm 561.51 +chi_sq_min_dof = 0.9026827026948364 +p_value = 0.8384168423262796 diff --git a/sesh1/prog/t0-method/results/wrong-SND.txt b/sesh1/prog/t0-method/results/wrong-SND.txt @@ -0,0 +1,10 @@ +773.21 \pm 4.97 +151.26 \pm 13.11 +782.03 \pm 0.47 +8.96 \pm 2.25 +2.14 \pm 0.68 +123.14 \pm 920.59 +711.92 \pm 3129.05 +-536.69 \pm 2422.92 +chi_sq_min_dof = 0.015874857326323925 +p_value = 0.9999999996289746 diff --git a/sesh1/prog/t0-method/single_fit.py b/sesh1/prog/t0-method/single_fit.py @@ -16,10 +16,10 @@ def SND(): var_str = "m_q g_q m_w g_w e_w a b c" p, dp, chi_sq = t0_fit(model, var_str, x_data, y_data, p0, cov_stat,\ - cov_relsyst) + cov_relsyst, way=1) sigma = np.diag(cov_stat) - my_plot('SND', x_data, y_data, p, dp, chi_sq, sigma) + my_plot('wrong-SND', x_data, y_data, p, dp, chi_sq, sigma) def CMD2(): data = np.loadtxt('../data/CMD2-VFF.txt') @@ -40,10 +40,10 @@ def CMD2(): var_str = "m_q g_q m_w g_w e_w a b c" p, dp, chi_sq = t0_fit(model, var_str, x_data, y_data, p0, cov_stat,\ - cov_relsyst) + cov_relsyst, way=1) sigma = np.sqrt(np.diag(cov_stat)) - my_plot('CMD2', x_data, y_data, p, dp, chi_sq, sigma) + my_plot('wrong-CMD2', x_data, y_data, p, dp, chi_sq, sigma) def KLOE(): data = np.loadtxt('../data/KLOE-VFF.txt') @@ -54,10 +54,10 @@ def KLOE(): var_str = "m_q g_q m_w g_w e_w a b c" p, dp, chi_sq = t0_fit(model, var_str, x_data, y_data, p0, cov_stat,\ - cov_relsyst) + cov_relsyst, way=1) sigma = np.sqrt(np.diag(cov_stat)) - my_plot('KLOE', x_data, y_data, p, dp, chi_sq, sigma) + my_plot('wrong-KLOE', x_data, y_data, p, dp, chi_sq, sigma) def BABAR(): data = np.loadtxt('../data/BABAR-VFF.txt') @@ -68,10 +68,10 @@ def BABAR(): var_str = "m_q g_q m_w g_w e_w a b c" p, dp, chi_sq = t0_fit(model, var_str, x_data, y_data, p0, cov_stat,\ - cov_relsyst) + cov_relsyst, way=1) sigma = np.sqrt(np.diag(cov_stat)) - my_plot('BABAR', x_data, y_data, p, dp, chi_sq, sigma) + my_plot('wrong-BABAR', x_data, y_data, p, dp, chi_sq, sigma) def main(): 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PDF statistics: - 233 PDF objects out of 1000 (max. 8388607) - 184 compressed objects within 2 object streams - 47 named destinations out of 1000 (max. 500000) - 160 words of extra memory for PDF output out of 10000 (max. 10000000) + 263 PDF objects out of 1000 (max. 8388607) + 203 compressed objects within 3 object streams + 55 named destinations out of 1000 (max. 500000) + 188 words of extra memory for PDF output out of 10000 (max. 10000000) diff --git a/sesh1/tex/main.out b/sesh1/tex/main.out @@ -10,4 +10,5 @@ \BOOKMARK [2][-]{subsection.4.1}{Single Experiment Fits under consideration of the D'Agostini bias}{section.4}% 10 \BOOKMARK [2][-]{subsection.4.2}{Multi Experiment Fits under consideration of the D'Agostini bias}{section.4}% 11 \BOOKMARK [2][-]{subsection.4.3}{Litrature comparison}{section.4}% 12 -\BOOKMARK [3][-]{subsubsection.4.3.1}{Plots}{subsection.4.3}% 13 +\BOOKMARK [2][-]{subsection.4.4}{Fitting with D'Agostini bias}{section.4}% 13 +\BOOKMARK [3][-]{subsubsection.4.4.1}{Plots}{subsection.4.4}% 14 diff --git a/sesh1/tex/main.pdf b/sesh1/tex/main.pdf Binary files differ. diff --git a/sesh1/tex/main.tex b/sesh1/tex/main.tex @@ -106,11 +106,12 @@ provided by \texttt{scipy}. \begin{align} \vec{p_0} = \begin{pmatrix} - 0.9,\; 0.2,\; 0.81,\; 0.04,\; 0.02,\; -1,\; 0.84,\; 1.55 + 900,\; 200,\; 810,\; 40,\; 20,\; -1000,\; 840,\; 1550 \end{pmatrix} \end{align} -The code can be viewed and/or downloaded from here \cite{code} (including the calculation of the guess parameters). +The code can be viewed and/or downloaded from here \cite{code} +(including the calculation of the guess parameters). \section{Results} @@ -124,17 +125,17 @@ the literature values. The plots of the given data and fitted models can be foun \subsection{Single Experiment Fits under consideration of the D'Agostini bias} In this section the data is fitted under consideration of the D'Agostini bias of all experiments separately. \begin{table}[h!] - \caption{Results of all experiment data fitted separately} + \caption{Results of all experiment data fitted separately\label{tabs}} \centering - \begin{tabular}{|l|c|c|c|c|} + \begin{tabular}{|c|c|c|c|c|} \hline $\vec{p}$ & SND & CMD2 & KLOE & BABAR \\ \hline - $M_{\rho}$ & $772.72 \pm 0.59$ & $773.93 \pm 0.67$ &$773.91 \pm 0.25 $&$773.33 \pm 0.43$ \\ - $\Gamma_{\rho}$ & $149.53 \pm 1.15$ & $147.67 \pm 1.32$ &$149.72 \pm 0.37 $&$149.19 \pm 0.81$\\ - $M_{\omega}$ & $781.94 \pm 0.09$ & $782.32 \pm 0.07$ &$782.44 \pm 0.11 $&$782.18 \pm 0.07$\\ - $\Gamma_{\omega}$ & $8.55 \pm 0.33 $ & $8.65 \pm 0.44$ &$9.66 \pm 0.33 $&$8.17 \pm 0.16$\\ - $\varepsilon_{\omega}$ & $2.02 \pm 0.09 $ & $1.92 \pm 0.12$ &$2.07 \pm 0.05 $&$1.95 \pm 0.03$\\ - \hline + $M_{\rho}$ [MeV] & $772.72 \pm 0.59$ & $773.93 \pm 0.67$ &$773.91 \pm 0.25 $&$773.33 \pm 0.43$ \\ + $\Gamma_{\rho}$ [MeV] & $149.53 \pm 1.15$ & $147.67 \pm 1.32$ &$149.72 \pm 0.37 $&$149.19 \pm 0.81$\\ + $M_{\omega}$ [MeV] & $781.94 \pm 0.09$ & $782.32 \pm 0.07$ &$782.44 \pm 0.11 $&$782.18 \pm 0.07$\\ + $\Gamma_{\omega}$ [MeV] & $8.55 \pm 0.33 $ & $8.65 \pm 0.44$ &$9.66 \pm 0.33 $&$8.17 \pm 0.16$\\ + $\varepsilon_{\omega}$ [] & $2.02 \pm 0.09 $ & $1.92 \pm 0.12$ &$2.07 \pm 0.05 $&$1.95 \pm 0.03$\\ + \hline \hline $\chi^2_{min}/dof$ & $1.001$&$ 1.054$&$ 1.443$&$ 1.031$\\ $p\text{-value}$ & $0.530$&$ 0.395$&$ 0.001$&$ 0.377$\\ \hline @@ -148,15 +149,15 @@ two experiments together then the data of all experiments. \begin{table}[h!] \caption{Results of data fits of experimental data fitted in pairs} \centering - \begin{tabular}{|l|c|c|c|} + \begin{tabular}{|c|c|c|c|} \hline $\vec{p}$ & SND-CMD2 & SND-KLOE & SND-BABAR \\ \hline - $M_{\rho}$ & $772.72 \pm 0.42$ & $773.92 \pm 0.23$ &$773.17 \pm 0.36 $ \\ - $\Gamma_{\rho}$ & $149.53 \pm 0.81$ & $149.42 \pm 0.35$ &$149.70 \pm 0.64 $\\ - $M_{\omega}$ & $781.95 \pm 0.07$ & $782.39 \pm 0.07$ &$782.07 \pm 0.06 $\\ - $\Gamma_{\omega}$ & $8.56 \pm 0.24 $ & $9.42 \pm 0.20$ &$8.27 \pm 0.13 $\\ - $\varepsilon_{\omega}$ & $2.02 \pm 0.07 $ & $2.07 \pm 0.05$ &$1.96 \pm 0.03 $\\ - \hline + $M_{\rho}$[MeV] & $772.72 \pm 0.42$ & $773.92 \pm 0.23$ &$773.17 \pm 0.36 $ \\ + $\Gamma_{\rho}$[MeV] & $149.53 \pm 0.81$ & $149.42 \pm 0.35$ &$149.70 \pm 0.64 $\\ + $M_{\omega}$ [MeV] & $781.95 \pm 0.07$ & $782.39 \pm 0.07$ &$782.07 \pm 0.06 $\\ + $\Gamma_{\omega}$ [MeV] & $8.56 \pm 0.24 $ & $9.42 \pm 0.20$ &$8.27 \pm 0.13 $\\ + $\varepsilon_{\omega}$[] & $2.02 \pm 0.07 $ & $2.07 \pm 0.05$ &$1.96 \pm 0.03 $\\ + \hline \hline $\chi^2_{min}/dof$ & $0.904$&$ 1.839$&$ 0.945$\\ $p\text{-value}$ & $0.754$&$ 0.001$&$ 0.763$\\ \hline @@ -164,18 +165,19 @@ two experiments together then the data of all experiments. \end{tabular} \end{table} + \begin{table}[h!] \caption{Results of data fits of experimental data fitted in pairs} \centering - \begin{tabular}{|l|c|c|c|} + \begin{tabular}{|c|c|c|c|} \hline $\vec{p}$ & CMD2-KLOE & CMD2-BABAR & KLOE-BABAR \\ \hline - $M_{\rho}$ & $773.92 \pm 0.23$ & $773.17 \pm 0.36$ &$773.66 \pm 0.20 $ \\ - $\Gamma_{\rho}$ & $149.42 \pm 0.35$ & $149.70 \pm 0.64$ &$149.41 \pm 0.32 $\\ - $M_{\omega}$ & $782.39 \pm 0.07$ & $782.07 \pm 0.06$ &$782.49 \pm 0.06 $\\ - $\Gamma_{\omega}$ & $9.42 \pm 0.02 $ & $8.27 \pm 0.13$ &$8.98 \pm 0.12 $\\ - $\varepsilon_{\omega}$ & $2.07 \pm 0.05 $ & $1.96 \pm 0.03$ &$1.98 \pm 0.02 $\\ - \hline + $M_{\rho}$ [MeV] & $773.92 \pm 0.23$ & $773.17 \pm 0.36$ &$773.66 \pm 0.20 $ \\ + $\Gamma_{\rho}$ [MeV] & $149.42 \pm 0.35$ & $149.70 \pm 0.64$ &$149.41 \pm 0.32 $\\ + $M_{\omega}$ [MeV] & $782.39 \pm 0.07$ & $782.07 \pm 0.06$ &$782.49 \pm 0.06 $\\ + $\Gamma_{\omega}$ [MeV] & $9.42 \pm 0.02 $ & $8.27 \pm 0.13$ &$8.98 \pm 0.12 $\\ + $\varepsilon_{\omega}$ [] & $2.07 \pm 0.05 $ & $1.96 \pm 0.03$ &$1.98 \pm 0.02 $\\ + \hline \hline $\chi^2_{min}/dof$ & $1.838$&$ 0.943$&$ 1.470$\\ $p\text{-value}$ & $0.001$&$ 0.772$&$ 0.001$\\ \hline @@ -186,14 +188,16 @@ two experiments together then the data of all experiments. \begin{table}[h!] \caption{Results of data fit of all experimental data fitted together\label{tabmulti}} \centering - \begin{tabular}{|l|c|} + \begin{tabular}{|c|c|} \hline - $M_{\rho}$ & $773.62 \pm 0.18$ \\ - $\Gamma_{\rho}$ & $149.42 \pm 0.29$ \\ - $M_{\omega}$ & $782.36 \pm 0.08$ \\ - $\Gamma_{\omega}$ & $8.75 \pm 0.08 $ \\ - $\varepsilon_{\omega}$ & $1.96 \pm 0.02 $ \\ + $\vec{p}$ & Multi-Fit\\ \hline + $M_{\rho}$ [MeV] & $773.62 \pm 0.18$ \\ + $\Gamma_{\rho}$ [MeV] & $149.42 \pm 0.29$ \\ + $M_{\omega}$ [MeV] & $782.36 \pm 0.08$ \\ + $\Gamma_{\omega}$ [MeV] & $8.75 \pm 0.08 $ \\ + $\varepsilon_{\omega}$[] & $1.96 \pm 0.02 $ \\ + \hline \hline $\chi^2_{min}/dof$ & $1.735$\\ $p\text{-value}$ & $0.000$\\ \hline @@ -202,21 +206,51 @@ two experiments together then the data of all experiments. \end{table} \subsection{Litrature comparison} -In the following table \ref{tabref}, we took the results of all experimental data fitted together -in table \ref{tabmulti} and compared them with the literature values \cite{particleref}. +In this section the fitted parameters of CMD2-BABAR and the literature values\cite{particleref} are compared. +The reason why CMD2-BABAR was chosen, is that it has a value of $\chi^2_{min}$ close to $1$. \begin{table}[ht!] \caption{Result comparison with literature\label{tabref}} \centering - \begin{tabular}{|l|c|} + \begin{tabular}{|l|c|c|c|} + \hline + $\vec{p}$ & Literature & CMD2-BABAR & Relative error \\ \hline - $M_{\rho}$ & $775.26 \pm 0.25$ \\ - $\Gamma_{\rho}$ & $147.8 \pm 0.9$ \\ - $M_{\omega}$ & $782.65 \pm 0.12$ \\ - $\Gamma_{\omega}$ & $8.49 \pm 0.08 $\\ + $M_{\rho}$ [MeV] & $775.26 \pm 0.25$ & $773.17 \pm 0.36$ & $ 0.02 \%$\\ + $\Gamma_{\rho}$ [MeV] & $147.80 \pm 0.90$ & $149.70 \pm 0.64$ & $ 1.02 \%$ \\ + $M_{\omega}$ [MeV] & $782.65 \pm 0.12$ & $782.07 \pm 0.06$ & $ 0.0008\% $ \\ + $\Gamma_{\omega}$ [MeV] & $8.49 \pm 0.08 $ & $8.27 \pm 0.13$ & $ 0.03 \%$\\ \hline \end{tabular} \end{table} +\subsection{Fitting with D'Agostini bias} +Furthermore here we compare the results of the t0-method, with the incorrect method of +multiplying the relative systematic uncertainties with the data provided, instead of +calculating the systematic uncertainties in regards of the newly calculated parameters in +every iteration. For demonstrational purposes only the single fitted experiments are pulled. +Again we would like to reference the plots in Section \ref{plots}. In the following table +the results of the incorrect method applied to fitting are shown. + +\begin{table}[h!] + \caption{Results of all experiment data wrongly fitted separately} + \centering + \begin{tabular}{|c|c|c|c|c|} + \hline + $\vec{p}$ & SND & CMD2 & KLOE & BABAR \\ \hline + $M_{\rho}$ [MeV] & $772.21 \pm 4.97$ & $774.51 \pm 2.59$ &$774.09 \pm 0.25 $&$773.42 \pm 0.54$ \\ + $\Gamma_{\rho}$ [MeV] & $151.26 \pm 13.11$ & $145.18 \pm 5.83$ &$149.89 \pm 0.84 $&$149.29 \pm 1.01$\\ + $M_{\omega}$ [MeV] & $781.03 \pm 0.47$ & $782.09 \pm 0.32$ &$782.79 \pm 0.18 $&$782.18 \pm 0.07$\\ + $\Gamma_{\omega}$ [MeV] & $8.96 \pm 2.25 $ & $8.58 \pm 0.15$ &$11.11 \pm 0.70 $&$8.18 \pm 0.18$\\ + $\varepsilon_{\omega}$[] & $2.14 \pm 0.68 $ & $1.85 \pm 0.38$ &$2.15 \pm 0.08 $&$1.94 \pm 0.04$\\ + \hline \hline + $\chi^2_{min}/dof$ & $0.016$&$ 0.125$&$ 0.903$&$ 1.118$\\ + $p\text{-value}$ & $1.000$&$ 1.000$&$ 0.839$&$ 0.099$\\ + \hline + \end{tabular} +\end{table} + +Obviously the results are much worse than in Table \ref{tabs}. + \subsubsection{Plots\label{plots}} \begin{figure}[H] \centering @@ -280,6 +314,27 @@ in table \ref{tabmulti} and compared them with the literature values \cite{parti \caption{SND, CMD, KLOE and BABAR fitted togther \label{fig10}} \end{figure} +\begin{figure}[H] + \centering + \includegraphics[width=0.8\textwidth]{./plots/wrong-SND.png} + \caption{Wrong method, SND data fit\label{fig1}} +\end{figure} +\begin{figure}[H] + \centering + \includegraphics[width=0.8\textwidth]{./plots/wrong-CMD2.png} + \caption{Wrong method, CMD2 data fit\label{fig2}} +\end{figure} +\begin{figure}[H] + \centering + \includegraphics[width=0.8\textwidth]{./plots/wrong-KLOE.png} + \caption{Wrong method, KLOE data fit\label{fig3}} +\end{figure} +\begin{figure}[H] + \centering + \includegraphics[width=0.8\textwidth]{./plots/wrong-BABAR.png} + \caption{Wrong method, BABAR data fit\label{fig4}} +\end{figure} + \printbibliography \end{document} diff --git a/sesh1/tex/main.toc b/sesh1/tex/main.toc @@ -24,4 +24,6 @@ \defcounter {refsection}{0}\relax \contentsline {subsection}{\numberline {4.3}Litrature comparison}{5}{subsection.4.3}% \defcounter {refsection}{0}\relax -\contentsline {subsubsection}{\numberline {4.3.1}Plots}{6}{subsubsection.4.3.1}% +\contentsline {subsection}{\numberline {4.4}Fitting with D'Agostini bias}{6}{subsection.4.4}% +\defcounter {refsection}{0}\relax +\contentsline {subsubsection}{\numberline {4.4.1}Plots}{7}{subsubsection.4.4.1}% diff --git a/sesh1/tex/plots/wrong-BABAR.png b/sesh1/tex/plots/wrong-BABAR.png Binary files differ. diff --git a/sesh1/tex/plots/wrong-CMD2.png b/sesh1/tex/plots/wrong-CMD2.png Binary files differ. diff --git a/sesh1/tex/plots/wrong-KLOE.png b/sesh1/tex/plots/wrong-KLOE.png Binary files differ. diff --git a/sesh1/tex/plots/wrong-SND.png b/sesh1/tex/plots/wrong-SND.png Binary files differ. diff --git a/sesh1/tex/solutions.md b/sesh1/tex/solutions.md @@ -1,56 +0,0 @@ -# Findings - -## Code -The code is structured as follows: - - * Construct statistical covariance matrix - * Construct Jacobi matrix of model function in terms of the parameters - * Guess parameters p0 - -Then we iterate the following: - - * Construct System covariance matrix with the guess p0 - * Fill Jacobi matrix with p0 = Design Matrix - * Claculate dp - * p0 = p0 + alpha*dp; alpha \in [0, 1] - * (calculate the chi^2 function) - -Additionally we can calculate the chi^2 function at each iteration. - -The guess used for all fits was determined by standard least-square fit -provided by 'scipy'. p0 = [0.9, 0.2, 0.81, 0.04, 0.02, -1, 0.84, 1.55] # in GeV -First let us look at results of single experiments fitted separately: - - SND -------> Pictures - CMD2 - KLOE - BABAR - - Table with fits and chisq, pvalue - -Then we can fit multiple experiments togehter if we align the given data and -construct block diagonal system covariance matricies. 4 experiments fited with -2 together gives 6 combinations. - - SND-CMD2 - SND-KLOE - SND-BABAR - CMD2-KLOE - CMD2-BABAR - KLOE-BABAR - 6 Picturs - - Table with fits and chisq, pvalue - - -Here we fitted all experiments together. - - ALL EXPERIMENTS - 1 Picture - - Table with fits and chisq, pvalue - - -Discussion schau ma mal was rauskommt - -Reference code git://popovic.xyz/tprak.git
