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fight with formatting and add german abstract

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Physics_Thesis_Template/content/chapter-gui.tex
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@@ -6,12 +6,15 @@ In this chapter the usage of the newly developed GUI application is explained. I
\section{Data download}
\label{sec:gui:data_download}
During the first startup the GUI window (e.g. in figure \ref{fig:full_gui_normal_selection}) is nearly completely empty. An empty local database will be created with SQLite3 \citep{sqlite}. To show lightcurves, data need to be downloaded first. For that, the "Add" button has to be clicked and a new dialog window appears. This can be seen in figure \ref{fig:download_new_star_data_gui}. This GUI uses the astroquery \citep{astroquery} python package to fetch metadata and download flexible image transport system (fits) files from the Mikulski Archive for Space Telescopes (MAST).\\
The first step is to enter the identifier of the star(s). In case of multiple identifiers, they have to be seperated by a semicolon. Then the missions from which the data should be fetched can be selected. The supported missions are TESS and Kepler/K2. For Kepler and K2 short and/or long cadence can be selected. The differences are described in section \ref{sec:intro:space_missions}. After the selection has been made, the fetch button needs to be pressed. The program will then request metadata matching the star identifier(s) and selected missions from the MAST archive. The found mission data is then displayed in the preview field. It can then be downloaded by pressing the "Ok" button. The program then proceeds to download the corresponding "fits" files. The filename and TESS sector or Kepler/K2 target table ID is appended to the previously fetched metadata and handed back to the main GUI.\\
During the first startup the GUI window (e.g. in figure \ref{fig:full_gui_normal_selection}) is nearly completely empty. An empty local database will be created with SQLite3 \citep{sqlite}. To show lightcurves, data need to be downloaded first. For that, the "Add" button has to be clicked and a new dialog window appears. This can be seen in figure \ref{fig:download_new_star_data_gui}. This GUI uses the astroquery \citep{astroquery} python package to fetch metadata and download flexible image transport system (fits) files from the Mikulski Archive for Space Telescopes (MAST).
The first step is to enter the identifier of the star(s). In case of multiple identifiers, they have to be seperated by a semicolon. Then the missions from which the data should be fetched can be selected. The supported missions are TESS and Kepler/K2. For Kepler and K2 short and/or long cadence can be selected. The differences are described in section \ref{sec:intro:space_missions}. After the selection has been made, the fetch button needs to be pressed. The program will then request metadata matching the star identifier(s) and selected missions from the MAST archive. The found mission data is then displayed in the preview field. It can then be downloaded by pressing the "Ok" button. The program then proceeds to download the corresponding "fits" files. The filename and TESS sector or Kepler/K2 target table ID is appended to the previously fetched metadata and handed back to the main GUI.
There a request to SIMBAD is made to fetch additional metadata. First the alternative identifiers are fetched from SIMBAD, which also have a MAIN\_ID attribute. This is to make sure we only have one entry in the local database per star and no duplicates. Afterwards additional data is fetched from SIMBAD \citep{simbad} like spectral type, radial velocity and distance. After the data is gathered, the main identifier, the alternative identifiers, spectral type, rotational velocity and distance (and their respective units) as well as the file path, source (TESS, Kepler or K2), and sector/target table ID are saved as an unique identifier into a local database using SQLite3 \citep{sqlite}. For Kepler/K2 the target table ID was chosen instead of the quarter, as the target table ID is a unique number, whereas there can be multiple "fits" files for the same star and the same quarter.
\begin{figure}[pt!]
\includegraphics[width=\linewidth]{gui/download_star_data_gui.png}
\centering
\includegraphics[width=.9\linewidth]{gui/download_star_data_gui.png}
\caption{GUI window for downloading new "fits" files with astroquery designed using the Qt5 designer shipped with PyQt5 \citep{pyqt5}. The star identifier field supports one or more (separated by a semicolon) identifiers. There are checkboxes to select TESS, Kepler (long and/or short cadence) and K2 (long and/or short cadence) data. The preview field shows metadata (Identifier, TESS sector or Kepler/K2 target table ID) to check the data which was found and which can be downloaded. The "Ok" button then proceeds to download the data and hands information back to the main GUI.}
\label{fig:download_new_star_data_gui}
\end{figure}
@@ -19,10 +22,14 @@ There a request to SIMBAD is made to fetch additional metadata. First the altern
\section{Data display and manipulation}
\label{sec:gui:data_display}
Afterwards the list of stars seen in figure \ref{fig:full_gui_normal_selection} will be refreshed. It shows the alphabetically sorted main identifier determined from SIMBAD.\\
When one of the stars in the list is selected, the program will show the additionally saved information. This includes all known identifiers for the star (categorized as alternative identifiers in the Alt. IDs list seen in the "Star infos" section of the GUI), the spectral type, its rotational velocity and its distance (from SIMBAD). Additionally a preferred fitting type for the folded lightcurves (which are described in section \ref{sec:data:data_reduction}) can be selected. The default value for this is "sine". The list to the right of the information section shows the available "fits" files. The formating for the list entries is "TESS - <sequence>" and "Kepler/K2 - <target table id>". The "combine" button combines temporary multiple "fits" files into one, which is then plotted. Selecting one or combining multiple "fits" files, enables the plot options.\\
The main plot options allow the user to change the type of flux that is plotted. This is either "SAP\_FLUX" (simple aperture photometry) or "PDCSAP\_FLUX" (presearch data conditioning simple aperture photometry) \citep{lightkurve} with the latter being the default option. The PDCSAP\_FLUX has parts of its data removed depending on the quality flags (e.g. indicating systematic errors like an attitude tweak or a cosmic ray \citep{tess_science_data_products,kepler_archive_manual}) as well as corrected long-term brightness changes \citep{lightkurve}. An example of a PDCSAP\_FLUX is shown in figure \ref{fig:full_gui_normal_selection}.\\
The lightkurve python package also supports normalizing (to unscaled, percent, parts per thousands (ppt) or parts per million (ppm)) which can be seen in figure \ref{fig:full_gui_normal_selection_normalize_options}. Flattened lightcurves (see figure \ref{fig:full_gui_normal_selection_flattened} as an example for $BD-08\ 995$) are used to identify flares. The "remove outliers", "remove nans/infs" and "bin" features are available in the GUI, but are not actively used in this thesis.\\
Afterwards the list of stars seen in figure \ref{fig:full_gui_normal_selection} will be refreshed. It shows the alphabetically sorted main identifier determined from SIMBAD.
When one of the stars in the list is selected, the program will show the additionally saved information. This includes all known identifiers for the star (categorized as alternative identifiers in the Alt. IDs list seen in the "Star infos" section of the GUI), the spectral type, its rotational velocity and its distance (from SIMBAD). Additionally a preferred fitting type for the folded lightcurves (which are described in section \ref{sec:data:data_reduction}) can be selected. The default value for this is "sine". The list to the right of the information section shows the available "fits" files. The formating for the list entries is "TESS - <sequence>" and "Kepler/K2 - <target table id>". The "combine" button combines temporary multiple "fits" files into one, which is then plotted. Selecting one or combining multiple "fits" files, enables the plot options.
The main plot options allow the user to change the type of flux that is plotted. This is either "SAP\_FLUX" (simple aperture photometry) or "PDCSAP\_FLUX" (presearch data conditioning simple aperture photometry) \citep{lightkurve} with the latter being the default option. The PDCSAP\_FLUX has parts of its data removed depending on the quality flags (e.g. indicating systematic errors like an attitude tweak or a cosmic ray \citep{tess_science_data_products,kepler_archive_manual}) as well as corrected long-term brightness changes \citep{lightkurve}. An example of a PDCSAP\_FLUX is shown in figure \ref{fig:full_gui_normal_selection}.
The lightkurve python package also supports normalizing (to unscaled, percent, parts per thousands (ppt) or parts per million (ppm)) which can be seen in figure \ref{fig:full_gui_normal_selection_normalize_options}. Flattened lightcurves (see figure \ref{fig:full_gui_normal_selection_flattened} as an example for $BD-08\ 995$) are used to identify flares. The "remove outliers", "remove nans/infs" and "bin" features are available in the GUI, but are not actively used in this thesis.
The checkboxes to flatten the lightcurve, meaning removing all longterm trends like spot/rotational modulation but leaving short term events intact (figure \ref{fig:full_gui_normal_selection_flattened}), folding the lightcurve (figure \ref{fig:full_gui_normal_selection_folded}) and showing the periodogram (figures \ref{fig:full_gui_normal_selection_periodogram_lombscargle} and \ref{fig:full_gui_normal_selection_periodogram_boxleastsquares}) are exclusive of each other. Only one can be used at a time. The values for "Period" and "Epoch Time" are automatically calculated and used as default for the selected lightcurve. If "Optimize" in the "Fold" options is unchecked, the "Epoch Time" represents the first found minimum in the lightcurve, and the "Period" is set to the period of the highest peak found in the Lomb-Scargle periodogram. If "Optimize" is checked, it will use the found rotational period of the optimize fold algorithm described in \ref{sec:data:data_reduction:lightcurve_folding}. If "Show Spot Modulation" is selected, it will use the found spot modulation period instead of the rotational period (see section \ref{sec:data:data_reduction:lightcurve_folding}).
\begin{landscape}