a lot of tiny changes and fixes

plotting/lecture/plotting.tex

@@ -419,14 +419,14 @@ output format (box\,\ref{graphicsformatbox}).
     \end{tabular}
   \end{minipage}
 
-  It is often meaningful to store of data plots generated by \matlab{}
-  using a vector graphics format. When in doubt they can usually be
+  It is advisable to store of data plots generated by \matlab{}
+  using a vector graphics format. In doubt they can usually be
   easily converted to a bitmap format. The way from a bitmap to a
   vector graphic is not possible without a loss in quality. Storing a
-  plot that contains a very large set of graphical elements (e.g.\,a
+  plot that contains very large sets of graphical elements (e.g.\,a
   raster-plot showing thousands of action potentials) may, on the
   other hand, lead to very large files that can be hard to
-  handle. Saving such a plot using a bitmap format may be more
+  handle. Saving such plots using a bitmap format may be more
   efficient.
 \end{ibox}
 
@@ -584,24 +584,24 @@ its properties. See the \matlab{} help for more information.
 
 \begin{figure}[ht]
   \includegraphics[width=0.9\linewidth]{errorbars}
-  \titlecaption{Adding error bars to a line plot}{\textbf{A}
+  \titlecaption{Indicating the estimation error in plots.}{\textbf{A}
     symmetrical error around the mean (e.g.\ using the standard
     deviation). \textbf{B} Errorbars of an asymmetrical distribution
     of the data (note: the average value is now the median and the
     errors are the lower and upper quartiles). \textbf{C} A shaded
     area is used to illustrate the spread of the data. See
-    listing\,\ref{errorbarlisting}}\label{errorbarplot}
+    listing\,\ref{errorbarlisting} for A and C and listing\,\ref{errorbarlisting2} }\label{errorbarplot}
 \end{figure}
 
-\lstinputlisting[caption={Illustrating estimation errors. Script that
-    creates \figref{errorbarplot}.},
+\lstinputlisting[caption={Illustrating estimation errors using error bars. Script that
+    creates \figref{errorbarplot}. A, B},
   label=errorbarlisting, firstline=13, lastline=29,
   basicstyle=\ttfamily\scriptsize]{errorbarplot.m}
 
 \subsubsection{Fill}
 For a few years now it has become fancy to illustrate the error not
 using errorbars but by drawing a shaded area around the mean. Beside
-their fancyness there is also a real argument in favor of using error
+the fancyness there is also a real argument in favor of using error
 areas instead of errorbars: In case you have a lot of data points with
 respective errorbars such that they would merge in the figure it is
 cleaner and probably easier to read and handle if one uses an error
@@ -613,8 +613,8 @@ with the vertex points of the polygon. For each x-value we now have
 two y-values (average minus error and average plus error). Further, we
 want the vertices to be connected in a defined order. One can achieve
 this by going back and forth on the x-axis; we append a reversed
-version of the x-values to the original x-values using the \code{cat}
-and inversion is done using the \code{fliplr} command (line 3 in
+version of the x-values to the original x-values using \code{cat} and
+\code{fliplr} for concatenation and inversion, respectively (line 3 in
 listing \ref{errorbarlisting2}; Depending on the layout of your data
 you may need concatenate along a different dimension of the data and
 use \code{flipud} instead). The y-coordinates of the polygon vertices
@@ -625,27 +625,26 @@ property defines the transparency (or rather the opaqueness) of the
 area. The provided alpha value is a number between 0 and 1 with zero
 leading to invisibility and a value of one to complete
 opaqueness. Finally, we use the normal plot command to draw a line
-connecting the average values.
+connecting the average values (line 12).
 
-\lstinputlisting[caption={Illustrating estimation errors. Script that
-    creates \figref{errorbarplot}.}, label=errorbarlisting2,
+\lstinputlisting[caption={Illustrating estimation errors using a shaded area. Script that
+    creates \figref{errorbarplot} C.}, label=errorbarlisting2,
   firstline=30,
   basicstyle=\ttfamily\scriptsize]{errorbarplot.m}
 
 \subsection{Annotations, text}
 
-Sometimes want to highlight certain parts of a plot or simply add an
-annotation that does not fit or belong to the legend. In these cases
-we can use the \code[text()]{text()} or
-\code[annotation()]{annotation()} function to add this information to
-the plot. While \varcode{text} simply prints out the given text string
-at the defined position (for example line in
+The \code[text()]{text()} or \code[annotation()]{annotation()} are
+used for highlighting certain parts of a plot or simply adding an
+annotation that does not fit or does not belong into the legend.
+While \varcode{text} simply prints out the given text string at the
+defined position (for example line in
 listing\,\ref{regularsubplotlisting}) the \varcode{annotation}
 function allows to add some more advanced highlights like arrows,
 lines, ellipses, or rectangles. Figure\,\ref{annotationsplot} shows
 some examples, the respective code can be found in
 listing\,\ref{annotationsplotlisting}. For more options consult the
-documentation.
+\matlab{} help.
 
 \begin{figure}[ht]
   \includegraphics[width=0.5\linewidth]{annotations}
@@ -716,18 +715,16 @@ Lissajous figure. The basic steps are:
 
 
 
-
-
 \section{Summary}
 A good plot of scientific data displays the data completely and
 seriously without too many distractions. Misleading or suggestive
 plots as may result from perspective presentations, inappropriate
-scaling of axes of symbols should be avoided.
+scaling of axes and symbols should be avoided.
 
 \noindent When combining several line plots within the same figure one should
 consider adapting color \textbf{and} line style (solid, dashed,
 dotted. etc.) to make the distinguishable even in black-and-white
-prints. Combinations of red and green are no good choice since they
+prints. Combinations of red and green are not a good choice since they
 cannot be distinguished by people with red-green blindness.
 
 \vspace{2ex}
@@ -737,6 +734,8 @@ Key ingredients for a good data plot:
 \item Complete labeling.
 \item Plotted lines and curves must be distinguishable.
 \item No suggestive or misleading presentation.
-\item The right balance of line width, font size and size of the figure.
+\item The right balance of line width, font size and size of the
+  figure, this may depend on the purpose, for presentations slightly
+  thicker lines help.
 \item Error bars wherever they are appropriate.
 \end{itemize}