fix formatting of old readme to rst format

README.rst

@@ -11,58 +11,70 @@ icence, cf. the GNU General Public License (GPL) and contain tools for:
         
 Fatigue Analysis
 ----------------
--Fatigue life prediction for random loads
--Theoretical density of rainflow cycles
+
+- Fatigue life prediction for random loads
+- Theoretical density of rainflow cycles
 
 Sea modelling
 -------------
--Simulation of linear and non-linear Gaussian waves
--Estimation of seamodels (spectrums)
--Joint wave height, wave steepness, wave period distributions
+
+- Simulation of linear and non-linear Gaussian waves
+- Estimation of seamodels (spectrums)
+- Joint wave height, wave steepness, wave period distributions
 
 Statistics
 ------------
--Extreme value analysis
--Kernel density estimation
--Hidden markov models
-
-WAFO consists of several subpackages and classes with short descriptions given
-below.
-
-Classes:
-TimeSeries  - Data analysis of time series. Example: extraction of
-              turning points, estimation of spectrum and covariance function.
-              Estimation transformation used in transformed Gaussian model.
-CovData     - Computation of spectral functions, linear
-              and non-linear time series simulation.
-SpecData    - Computation of spectral moments and covariance functions, linear
-              and non-linear time series simulation.
-              Ex: common spectra implemented, directional spectra,
-              bandwidth measures, exact distributions for wave characteristics.
-
-CyclePairs  - Cycle counting, discretization, and crossings, calculation of
-              damage. Simulation of discrete Markov chains, switching Markov
-              chains, harmonic oscillator. Ex:  Rainflow cycles and matrix,
-              discretization of loads. Damage of a rainflow count or
-              matrix, damage matrix, S-N plot.
-
-
-Subpackages:
-TRANSFORM  - Modelling with linear or transformed Gaussian waves. Ex:
-STATS      - Statistical tools and extreme-value distributions.
-              Ex: generation of random numbers, estimation of parameters,
-              evaluation of pdf and cdf
-KDETOOLS   - Kernel-density estimation.
-MISC       - Miscellaneous routines.
-DOCS       - Documentation of toolbox, definitions. An overview is given
-              in the routine wafomenu.
-DATA       - Measurements from marine applications.
+
+- Extreme value analysis
+- Kernel density estimation
+- Hidden markov models
+
+Classes
+-------
+
+* TimeSeries:
+    Data analysis of time series. Example: extraction of turning points,
+    estimation of spectrum and covariance function. Estimation transformation
+    used in transformed Gaussian model.
+
+* CovData:
+    Computation of spectral functions, linear and non-linear time series
+    simulation.
+
+* SpecData:
+    Computation of spectral moments and covariance functions, linear and
+    non-linear time series simulation. Ex: common spectra implemented, 
+    directional spectra, bandwidth measures, exact distributions for wave
+    characteristics.
+
+* CyclePairs:
+    Cycle counting, discretization, and crossings, calculation of damage.
+    Simulation of discrete Markov chains, switching Markov chains,
+    harmonic oscillator. Ex:  Rainflow cycles and matrix, discretization of
+    loads. Damage of a rainflow count or matrix, damage matrix, S-N plot.
+
+
+Subpackages
+-----------
+
+* TRANSFORM
+    Modelling with linear or transformed Gaussian waves.
+* STATS
+    Statistical tools and extreme-value distributions. Ex: generation of random
+    numbers, estimation of parameters, evaluation of pdf and cdf
+* KDETOOLS
+    Kernel-density estimation.
+* MISC
+    Miscellaneous routines.
+* DOCS
+    Documentation of toolbox, definitions. An overview is given in the routine
+    wafomenu.
+* DATA
+    Measurements from marine applications.
 
 WAFO homepage: <http://www.maths.lth.se/matstat/wafo/>
 On the WAFO home page you will find:
 - The WAFO Tutorial
-- New versions of WAFO to download.
-- Reported bugs.
 - List of publications related to WAFO.