Markup adjustments.
diff --git a/Doc/lib/librandom.tex b/Doc/lib/librandom.tex
index ab4527f..66fda8d 100644
--- a/Doc/lib/librandom.tex
+++ b/Doc/lib/librandom.tex
@@ -9,66 +9,68 @@
uniform and von Mises distributions are available.
The module exports the following functions, which are exactly
-equivalent to those in the \code{whrandom} module: \code{choice},
-\code{randint}, \code{random}, \code{uniform}. See the documentation
-for the \code{whrandom} module for these functions.
+equivalent to those in the \module{whrandom} module:
+\function{choice()}, \function{randint()}, \function{random()} and
+\function{uniform()}. See the documentation for the \module{whrandom}
+module for these functions.
-The following functions specific to the \code{random} module are also
+The following functions specific to the \module{random} module are also
defined, and all return real values. Function parameters are named
after the corresponding variables in the distribution's equation, as
used in common mathematical practice; most of these equations can be
found in any statistics text.
\setindexsubitem{(in module random)}
-\begin{funcdesc}{betavariate}{alpha\, beta}
-Beta distribution. Conditions on the parameters are \code{alpha>-1}
-and \code{beta>-1}.
+\begin{funcdesc}{betavariate}{alpha, beta}
+Beta distribution. Conditions on the parameters are
+\code{\var{alpha}>-1} and \code{\var{beta}>-1}.
Returned values will range between 0 and 1.
\end{funcdesc}
-\begin{funcdesc}{cunifvariate}{mean\, arc}
+\begin{funcdesc}{cunifvariate}{mean, arc}
Circular uniform distribution. \var{mean} is the mean angle, and
\var{arc} is the range of the distribution, centered around the mean
angle. Both values must be expressed in radians, and can range
between 0 and \code{pi}. Returned values will range between
-\code{mean - arc/2} and \code{mean + arc/2}.
+\code{\var{mean} - \var{arc}/2} and \code{\var{mean} + \var{arc}/2}.
\end{funcdesc}
\begin{funcdesc}{expovariate}{lambd}
-Exponential distribution. \var{lambd} is 1.0 divided by the desired mean.
-(The parameter would be called ``lambda'', but that's also a reserved
-word in Python.) Returned values will range from 0 to positive infinity.
+Exponential distribution. \var{lambd} is 1.0 divided by the desired
+mean. (The parameter would be called ``lambda'', but that is a
+reserved word in Python.) Returned values will range from 0 to
+positive infinity.
\end{funcdesc}
-\begin{funcdesc}{gamma}{alpha\, beta}
-Gamma distribution. (\emph{Not} the gamma function!)
-Conditions on the parameters are \code{alpha>-1} and \code{beta>0}.
+\begin{funcdesc}{gamma}{alpha, beta}
+Gamma distribution. (\emph{Not} the gamma function!) Conditions on
+the parameters are \code{\var{alpha}>-1} and \code{\var{beta}>0}.
\end{funcdesc}
-\begin{funcdesc}{gauss}{mu\, sigma}
+\begin{funcdesc}{gauss}{mu, sigma}
Gaussian distribution. \var{mu} is the mean, and \var{sigma} is the
standard deviation. This is slightly faster than the
-\code{normalvariate} function defined below.
+\function{normalvariate()} function defined below.
\end{funcdesc}
-\begin{funcdesc}{lognormvariate}{mu\, sigma}
+\begin{funcdesc}{lognormvariate}{mu, sigma}
Log normal distribution. If you take the natural logarithm of this
distribution, you'll get a normal distribution with mean \var{mu} and
-standard deviation \var{sigma} \var{mu} can have any value, and \var{sigma}
+standard deviation \var{sigma}. \var{mu} can have any value, and \var{sigma}
must be greater than zero.
\end{funcdesc}
-\begin{funcdesc}{normalvariate}{mu\, sigma}
+\begin{funcdesc}{normalvariate}{mu, sigma}
Normal distribution. \var{mu} is the mean, and \var{sigma} is the
standard deviation.
\end{funcdesc}
-\begin{funcdesc}{vonmisesvariate}{mu\, kappa}
+\begin{funcdesc}{vonmisesvariate}{mu, kappa}
\var{mu} is the mean angle, expressed in radians between 0 and pi,
and \var{kappa} is the concentration parameter, which must be greater
then or equal to zero. If \var{kappa} is equal to zero, this
distribution reduces to a uniform random angle over the range 0 to
-\code{2*pi}.
+$2\pi$.
\end{funcdesc}
\begin{funcdesc}{paretovariate}{alpha}
@@ -76,7 +78,7 @@
\end{funcdesc}
\begin{funcdesc}{weibullvariate}{alpha, beta}
-Weibull distribution. \var{alpha} is the scale parameter, and
+Weibull distribution. \var{alpha} is the scale parameter and
\var{beta} is the shape parameter.
\end{funcdesc}