Reorganiced pywafo

gendocwafo.py

@@ -1,4 +0,0 @@
-
-import os
-
-os.system('epydoc --html -o html --name wafo --graph all src/wafo')

manifest

@@ -1,22 +0,0 @@
-setup.py
-src\wafo\__init__.py
-src\wafo\dctpack.py
-src\wafo\definitions.py
-src\wafo\demo_sg.py
-src\wafo\info.py
-src\wafo\interpolate.py
-src\wafo\kdetools.py
-src\wafo\misc.py
-src\wafo\namedtuple.py
-src\wafo\objects.py
-src\wafo\plotbackend.py
-src\wafo\polynomial.py
-src\wafo\polynomial_old.py
-src\wafo\sg_filter.py
-src\wafo\data\__init__.py
-src\wafo\data\info.py
-src\wafo\spectrum\__init__.py
-src\wafo\spectrum\dispersion_relation.py
-src\wafo\spectrum\models.py
-src\wafo\transform\__init__.py
-src\wafo\transform\models.py

setup.py

@@ -1,56 +0,0 @@
-"""
-Install wafo
-
-Usage:
-
-python setup.py install [, --prefix=$PREFIX]
-
-python setup.py develop
-python setup.py bdist_wininst
-"""
-#!/usr/bin/env python
-import os, sys
-
-# make sure we import from WAFO in this package, not an installed one:
-sys.path.insert(0, os.path.join('src'))
-import wafo
-
-if  __file__ == 'setupegg.py':
-    # http://peak.telecommunity.com/DevCenter/setuptools
-    from setuptools import setup, Extension
-else:
-    from distutils.core import setup
-
-package_name = "wafo"
-subpackages = ('spectrum','data','transform','covariance')
-subpackagesfull = [os.path.join(package_name,f) for f in subpackages]
-subtests = [os.path.join(subpkg,'test') for subpkg in subpackages]
-
-testscripts = [os.path.join(subtst, f) for subtst in subtests
-    for f in os.listdir(os.path.join('src',package_name,subtst))
-               if not (f.startswith('.') or f.endswith('~') or
-                       f.endswith('.old') or f.endswith('.bak'))]
-datadir = 'data'
-datafiles = [os.path.join(datadir, f)   for f in os.listdir(os.path.join('src',package_name,datadir))
-				if  not (f.endswith('.py') or f.endswith('test') )]
-#docs = [os.path.join('doc', f) for f in os.listdir('doc')]
-packagedata = testscripts + datafiles + ['c_library.pyd'] #,'disufq1.c','diffsumfunq.pyd','diffsumfunq.pyf','findrfc.c','rfc.pyd','rfc.pyf']
-
-
-setup(
-    version = '0.11',
-    author='WAFO-group',
-    author_email='wafo@maths.lth.se',
-    description = wafo.__doc__,
-    license = "GPL",
-    url='http://www.maths.lth.se/matstat/wafo/',
-	name = package_name.upper(),
-    package_dir = {'': 'src'},
-    packages = [package_name,] + list(subpackagesfull),
-    package_data = {package_name: packagedata},
-    #package_data = {'': ['wafo.cfg']},
-    #scripts = [os.path.join('bin', f)
-    #           for f in os.listdir('bin')
-    #           if not (f.startswith('.') or f.endswith('~') or
-    #                   f.endswith('.old') or f.endswith('.bak'))],
-    )

src/Wafo.egg-info/PKG-INFO

@@ -0,0 +1,92 @@
+Metadata-Version: 1.0
+Name: WAFO
+Version: 0.11
+Summary: 
+WAFO
+=====
+   WAFO is a toolbox Python routines for statistical analysis and simulation of random waves and random loads. 
+   WAFO is freely redistributable software, see WAFO licence, cf. the GNU General Public License (GPL) and
+   contain tools for:
+
+Fatigue Analysis
+----------------
+-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
+
+Statistics
+------------
+-Extreme value analysis
+-Kernel density estimation
+-Hidden markov models
+
+ WAFO consists of several modules with short descriptions below.
+ The modules SPECTRUM, COVARIANCE, TRANSFORM, WAVEMODELS, and MULTIDIM are 
+ mainly for oceanographic applications.
+ The modules CYCLES, MARKOV, and DAMAGE are mainly for fatigue problems. 
+ The contents file for each module is shown by typing 'help module-name' 
+ Type 'help fatigue' for a presentation of all routines related to fatigue.
+
+ The paths to the modules are initiated by the function 'initwafo'.
+
+ ONEDIM     - Data analysis of time series. Example: extraction of 
+              turning points, estimation of spectrum and covariance function. 
+              Estimation transformation used in transformed Gaussian model.
+ COVARIANCE - Computation of spectral functions, linear 
+              and non-linear time series simulation. 
+ SPECTRUM   - 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.
+ TRANSFORM  - Modelling with linear or transformed Gaussian waves. Ex: 
+              
+ WAVEMODELS - Models for distributions of wave characteristics found in 
+              the literature. Ex: parametric models for breaking 
+              limited wave heights.
+ MULTIDIM   - Multi-dimensional time series analysis.  (Under construction)
+ CYCLES     - 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.
+ MARKOV     - Routines for Markov loads, switching Markov loads, and 
+              their connection to rainflow cycles.
+ DAMAGE     - Calculation of damage. Ex: Damage of a rainflow count or 
+              matrix, damage matrix, S-N plot.
+ SIMTOOLS   - Simulation of random processes. Ex: spectral simulation, 
+              simulation of discrete Markov chains, switching Markov
+              chains, harmonic oscillator
+ STATISTICS - 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. Ex: numerical integration, smoothing 
+              spline, binomial coefficient, water density.
+ WDEMOS     - WAFO demos. 
+ DOCS       - Documentation of toolbox, definitions. An overview is given 
+              in the routine wafomenu. 
+ DATA       - Measurements from marine applications.
+ PAPERS     - Commands that generate figures in selected scientific 
+              publications.
+ SOURCE     - Fortran and C files. Information on compilation.
+ EXEC       - Executable files (cf. SOURCE), pre-compiled for Solaris, 
+              Alpha-Dec or Windows. 
+ 
+ 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.
+
+Home-page: http://www.maths.lth.se/matstat/wafo/
+Author: WAFO-group
+Author-email: wafo@maths.lth.se
+License: GPL
+Description: UNKNOWN
+Platform: UNKNOWN

src/Wafo.egg-info/SOURCES.txt

@@ -0,0 +1,39 @@
+setup.py
+setup_old.py
+src/WAFO.egg-info/SOURCES.txt
+src/Wafo.egg-info/PKG-INFO
+src/Wafo.egg-info/SOURCES.txt
+src/Wafo.egg-info/dependency_links.txt
+src/Wafo.egg-info/top_level.txt
+src/wafo/__init__.py
+src/wafo/data_structures.py
+src/wafo/dctpack.py
+src/wafo/definitions.py
+src/wafo/demo_sg.py
+src/wafo/gaussian.py
+src/wafo/info.py
+src/wafo/integrate.py
+src/wafo/interpolate.py
+src/wafo/kdetools.py
+src/wafo/meshgrid.py
+src/wafo/misc.py
+src/wafo/namedtuple.py
+src/wafo/objects.py
+src/wafo/plotbackend.py
+src/wafo/polynomial.py
+src/wafo/polynomial_old.py
+src/wafo/sg_filter.py
+src/wafo/wafodata.py
+src/wafo.egg-info/SOURCES.txt
+src/wafo/covariance/__init__.py
+src/wafo/covariance/core.py
+src/wafo/data/__init__.py
+src/wafo/data/info.py
+src/wafo/spectrum/__init__.py
+src/wafo/spectrum/core.py
+src/wafo/spectrum/dispersion_relation.py
+src/wafo/spectrum/models.py
+src/wafo/test/__init__.py
+src/wafo/transform/__init__.py
+src/wafo/transform/core.py
+src/wafo/transform/models.py

src/Wafo.egg-info/dependency_links.txt

@@ -0,0 +1 @@
+

src/Wafo.egg-info/top_level.txt

@@ -0,0 +1,5 @@
+wafo\spectrum
+wafo\covariance
+wafo
+wafo\data
+wafo\transform

src/epydoc_wafo.prj

@@ -0,0 +1,64 @@
+(dp0
+S'show_imports'
+p1
+I0
+sS'private_css'
+p2
+S'default'
+p3
+sS'prj_name'
+p4
+S'WAFO'
+p5
+sS'docformat'
+p6
+S'restructuredtext'
+p7
+sS'inheritance'
+p8
+S'grouped'
+p9
+sS'help'
+p10
+NsS'modules'
+p11
+(S'C:/pab/workspace/PYWAFO/src/wafo/objects.py'
+p12
+S'C:/pab/workspace/PYWAFO/src/wafo/__init__.py'
+p13
+S'C:/pab/workspace/PYWAFO/src/wafo/info.py'
+p14
+S'C:/pab/workspace/PYWAFO/src/wafo/plotbackend.py'
+p15
+S'C:/pab/workspace/PYWAFO/src/wafo/spectrum/__init__.py'
+p16
+S'C:/pab/workspace/PYWAFO/src/wafo/spectrum/dispersion_relation.py'
+p17
+S'C:/pab/workspace/PYWAFO/src/wafo/spectrum/models.py'
+p18
+S'C:/pab/workspace/PYWAFO/src/wafo/data/info.py'
+p19
+S'C:/pab/workspace/PYWAFO/src/wafo/transform/__init__.py'
+p20
+S'C:/pab/workspace/PYWAFO/src/wafo/transform/models.py'
+p21
+tp22
+sS'private'
+p23
+I1
+sS'prj_url'
+p24
+S'http://www.maths.lth.se/matstat/wafo/'
+p25
+sS'frames'
+p26
+I1
+sS'css'
+p27
+S'default'
+p28
+sS'outdir'
+p29
+S'html'
+p30
+s.

src/wafo/data/info.~py

@@ -0,0 +1,456 @@
+"""
+Data package in WAFO Toolbox.
+
+Contents
+--------
+atlantic - Significant wave-height data recorded in the Atlantic Ocean
+gfaks89  - Surface elevation measured at Gullfaks C 24.12.1989
+gfaksr89 - Reconstructed surface elevation measured at Gullfaks C 24.12.1989.
+japansea - coastline map of The Japan Sea
+northsea - coastline map of The Nortsea
+sea      - Surface elevation dataset used in WAT version 1.1.
+sfa89    - Wind measurements at Statfjord A 24.12.1989
+sn       - Fatigue experiment, constant-amplitude loading.
+yura87   - Surface elevation measured off the coast of Yura
+
+
+
+This module gives gives detailed information and easy access to all datasets
+included in WAFO
+
+"""
+#from pylab import load
+#from scipy.io import read_array
+from numpy import (loadtxt,nan)
+import os
+__path2data = os.path.dirname( os.path.realpath(__file__))
+
+__all__ =['atlantic','gfaks89','gfaksr89','japansea','northsea','sea','sfa89',
+            'sn','yura87']
+
+def _load(file):
+    """ local load function
+    """
+    return loadtxt(os.path.join(__path2data,file))
+
+def _tofloat(x):
+    if x=='nan' or x=='NaN':
+        y = nan
+    else:
+        y = float(x or 0)
+    return y
+def _loadnan(file):
+    """ local load function accepting nan's
+    """
+    myconverter = {0: _tofloat, 1: _tofloat}
+    return loadtxt(os.path.join(__path2data,file),converters=myconverter)
+
+def atlantic():
+    """
+    Return Significant wave-height data recorded in the Atlantic Ocean
+
+    Data summary
+    ------------
+    Size             :     582 X 1
+    Sampling Rate    :     ~ 14 times a month
+    Device           :
+    Source           :
+    Format           :    ascii
+
+    Description
+    ------------
+    atlantic.dat contains average significant wave-height data recorded
+    approximately 14 times a month in December-February during 7 years and
+    at 2 locations in the Atlantic Ocean
+
+    Example
+    --------
+    >>> import pylab
+    >>> import wafo
+    >>> Hs = wafo.data.atlantic()
+    >>> h = pylab.plot(Hs)
+
+    Acknowledgement:
+    ---------------
+    This dataset were made available by Dr. David Carter
+    and Dr. David Cotton, Satellite Observing Systems, UK.
+    """
+    return _load('atlantic.dat')
+def gfaks89():
+    """
+    Return Surface elevation measured at Gullfaks C 24.12.1989
+
+    Data summary
+    ------------
+    Size             :    39000 X 2
+    Sampling Rate    :    2.5 Hz
+    Device           :    EMI laser
+    Source           :    STATOIL
+    Format           :    ascii, c1: time c2: surface elevation
+
+    Description
+    ------------
+    The wave data was measured 24th December 1989 at the Gullfaks C platform
+    in the North Sea from 17.00 to 21.20. The period from 20.00 to 20.20
+    is missing and contains NaNs.  The water depth of 218 m is
+    regarded as deep water for the most important wave components.
+    There are two EMI laser sensors named 219 and 220. This data set is
+    obtained from sensor 219, which is located in the Northwest
+    corner approximately two platform leg diameters away from
+    the closest leg.
+    Thus the wave elevation is not expected to be significantly
+    affected by diffraction effects for incoming waves in the western sector.
+    The wind direction for this period is from the south.
+    Some difficulties in calibration of the instruments have been reported
+    resulting in several consecutive measured values being equal or almost equal
+    in the observed data set.
+
+    This dataset is for non-commercial use only.
+
+    Hm0 = 6.8m, Tm02 = 8s, Tp = 10.5
+
+    Example
+    -------
+    >>> import pylab
+    >>> import wafo
+    >>> x = wafo.data.gfaks89()
+    >>> h = pylab.plot(x[:,0],x[:,1])
+
+    Acknowledgement:
+    ---------------
+    This dataset were prepared and made available by Dr. S. Haver,
+    STATOIL, Norway
+
+    See also
+    --------
+    gfaksr89, northsea
+
+    """
+    return _loadnan('gfaks89.dat')
+def gfaksr89():
+    """
+    Return a reconstruction of surface elevation measured at Gullfaks C 24.12.1989.
+
+
+    Data summary
+    ------------
+    Size             :    39000 X 2
+    Sampling Rate    :    2.5 Hz
+    Device           :    EMI laser
+    Source           :    STATOIL
+    Format           :    ascii, c1: time c2: surface elevation
+
+    Description
+    -----------
+    This is a reconstructed version of the data in the GFAKS89.DAT file.
+    The following calls were made to reconstruct the data:
+
+                inds = findoutliers(gfaks89,.02,2,1.23);
+            gfaksr89 = reconstruct(gfaks89,inds,6);
+
+    The wave data was measured 24th December 1989 at the Gullfaks C platform
+    in the North Sea from 17.00 to 21.20. The period from 20.00 to 20.20
+    is missing in the original data.  The  water depth of 218 m is
+    regarded as deep water for the most important wave components.
+    There are two EMI laser sensors named 219 and 220. This data set is
+    obtained from sensor 219, which is located in the Northwest
+    corner approximately two platform leg diameters away from
+    the closest leg.
+    Thus the wave elevation is not expected to be significantly
+    affected by diffraction effects for incoming waves in the western sector.
+    The wind direction for this period is from the south.
+    Some difficulties in calibration of the instruments have been reported
+    resulting in several consecutive measured values being equal or almost equal
+    in the observed data set.
+
+    Hm0 = 6.8m, Tm02 = 8s, Tp = 10.5
+
+
+    Example
+    -------
+    >>> import pylab
+    >>> import wafo
+    >>> x = wafo.data.gfaksr89()
+    >>> h = pylab.plot(x[:,0],x[:,1])
+
+
+    See also
+    --------
+    gfaks89
+    """
+    return _loadnan('gfaksr89.dat')
+def japansea():
+    """
+    Return coastline map of The Japan Sea
+
+
+    Data summary
+    ------------
+    Size             :     692 X 2
+    Sampling Rate    :
+    Device           :
+    Source           :    http://crusty.er.usgs.gov/coast/getcoast.html
+    Format           :    ascii, c1: longitude c2: latitude
+
+    Description
+    -----------
+    JAPANSEA.DAT contains data for plotting a map of The Japan Sea.
+    The data is obtained from USGS coastline extractor.
+
+    Example:
+    -------
+    #the map is seen by
+
+    >>> import pylab
+    >>> import wafo
+    >>> map1 = wafo.data.japansea()
+    >>> h = pylab.plot(map1[:,0],map1[:,1])
+    >>> lon_loc = [131,132,132,135,139.5,139]
+    >>> lat_loc = [46, 43, 40, 35, 38.3, 35.7]
+    >>> loc = ['China','Vladivostok','Japan Sea', 'Japan', 'Yura','Tokyo']
+    >>> algn = 'right'
+    >>> for lon, lat, name in zip(lon_loc,lat_loc,loc):
+            pylab.text(lon,lat,name,horizontalalignment=algn)
+
+
+    # If you have the m_map toolbox (see http://www.ocgy.ubc.ca/~rich/):
+    m_proj('lambert','long',[130 148],'lat',[30 48]);
+    m_line(map(:,1),map(:,2));
+    m_grid('box','fancy','tickdir','out');
+    m_text(131,46,'China');
+    m_text(132,43,'Vladivostok');
+    m_text(132,40,'Japan Sea');
+    m_text(135,35,'Japan');
+    m_text(139.5,38.3,'Yura');
+    m_text(139,35.7,'Tokyo');
+    """
+    return _loadnan('japansea.dat')
+def northsea():
+    """
+    NORTHSEA  coastline map of The Nortsea
+
+    Data summary
+    -------------
+    Size             :     60646 X 2
+    Sampling Rate    :
+    Device           :
+    Source           :    http://crusty.er.usgs.gov/coast/getcoast.html
+    Format           :    ascii, c1: longitude c2: latitude
+
+    Description
+    -----------
+    NORTHSEA.DAT contains data for plotting a map of The Northsea.
+    The data is obtained from USGS coastline extractor.
+
+    Example
+    -------
+    # the map is seen by
+
+    >>> import pylab
+    >>> import wafo
+    >>> map1 = wafo.data.northsea()
+    >>> h = pylab.plot(map1[:,0],map1[:,1])
+    >>> lon_pltfrm = [1.8,   2.3,  2.,  1.9, 2.6]
+    >>> lat_pltfrm = [61.2, 61.2, 59.9, 58.4, 57.7]
+    >>> pltfrm = ['Statfjord A', 'Gullfaks C', 'Frigg', 'Sleipner', 'Draupner']
+    >>> h = pylab.scatter(lon_pltfrm,lat_pltfrm);
+    >>> algn = 'right'
+    >>> for lon, lat, name in zip(lon_pltfrm,lat_pltfrm,pltfrm):
+            pylab.text(lon,lat,name,horizontalalignment=algn); algn = 'left'
+
+
+    >>> lon_city = [10.8, 10.8, 5.52, 5.2]
+    >>> lat_city = [59.85, 63.4, 58.9, 60.3]
+    >>> city = ['Oslo','Trondheim','Stavanger', 'Bergen']
+    >>> h = pylab.scatter(lon_city,lat_city);
+    >>> algn = 'right'
+    >>> for lon, lat, name in zip(lon_city,lat_city,city):
+            pylab.text(lon,lat,name,horizontalalignment=algn)
+
+    >>> from mpl_toolkits.basemap import Basemap
+    >>> import matplotlib.pyplot as plt
+
+    # setup Lambert Conformal basemap.
+    >>> m = Basemap(width=1200000,height=900000,projection='lcc',
+            resolution='f',lat_1=56.,lat_2=64,lat_0=58,lon_0=5.)
+    # draw coastlines.
+    >>> m.drawcoastlines()
+    >>> h = m.scatter(lon_pltfrm,lat_pltfrm);
+    >>> algn = 'right'
+    >>> for lon, lat, name in zip(lon_pltfrm,lat_pltfrm,pltfrm):
+            m.text(lon,lat,name,horizontalalignment=algn); algn = 'left'
+    >>> m.scatter(lon_city,lat_city)
+    >>> m.scatter()
+
+    # If you have the m_map toolbox (see http://www.ocgy.ubc.ca/~rich/):
+    m_proj('lambert','long',[-2 12],'lat',[56 64]);
+    m_line(map(:,1),map(:,2));
+    m_grid('box','fancy','tickdir','out');
+    m_text( 1,62     ,'Statfjord A') ;
+    m_line([1.8, 1.8], [62  ,61.2 ]);
+    m_text(1.7,61.2,'x') ;
+    m_text(1,59.5,'Gullfaks C') ;
+    m_line([1.8, 2.3 ], [59.50 ,61.20 ]);
+    m_text(2.20,61.20,'x') ;
+    m_text(10.10,60.05,'Oslo');
+    m_text(8.5,63.5,'Trondheim');
+    m_text(4.00,58.80,'Stavanger');
+    m_text(3.50,60.30,'Bergen') ;
+    m_text(8,61,'Norway');
+    """
+    return _loadnan('northsea.dat')
+def sea():
+    """
+    Return Surface elevation dataset used in WAT version 1.1.
+
+    Data summary
+    ------------
+    Size             :    9524    X    2
+    Sampling Rate    :    4.0 Hz
+    Device           :    unknown
+    Source           :    unknown
+    Format           :    ascii, c1: time c2: surface elevation
+
+    Description
+    -----------
+    The wave data was used in one of WAFO predecessors, i.e. the Wave
+    Analysis Toolbox version 1.1 (WAT)
+    Hm0 = 1.9m, Tm02 = 4.0s, Tp2 = 11.5s Tp1=5.6s
+
+    Example
+    -------
+    >>> import pylab
+    >>> import wafo
+    >>> x = wafo.data.sea()
+    >>> h = pylab.plot(x[:,0],x[:,1])
+    """
+    return _load('sea.dat')
+def sfa89():
+    """
+    Return Wind measurements at Statfjord A 24.12.1989
+
+    Data summary
+    ------------
+    Size             :    144 X 3
+    Sampling Rate    :     1/600 Hz
+    Device           :
+    Source           :    DNMI (The Norwegian Meteorological Institute)
+    Format           :    ascii, c1: time     (hours)
+                              c2: velocity (m/s)
+                              c3: direction (degrees)
+    Description
+    -----------
+    The registration of wind speeds at the Gullfaks field
+    started up on Statfjord A in 1978 and continued until 1990.
+    The dataregistration was transferred to Gullfaks C in Nov 1989.
+    Due to some difficulties of the windregistration on Gullfaks C in
+    the beginning, they continued to use the registered data from
+    Statfjord A.
+    The windspeed is measured in  (meter/second), 110 m above mean water
+    level (MWL) and the wind direction is given in degrees for the data.
+    The data are a mean value of every 10 minutes.
+    Wind directions are defined in the meteorological convention, i.e.,
+    0 degrees = wind approaching from North, 90 degrees = wind from East, etc.
+    This dataset is for non-commercial use only.
+
+     Example
+    -------
+    >>> import pylab
+    >>> import wafo
+    >>> x = wafo.data.sfa89()
+    >>> h = pylab.plot(x[:,0],x[:,1])
+
+    Acknowledgement
+    ----------------
+    These data are made available by Knut A. Iden, DNMI.
+
+    See also
+    --------
+    northsea
+    """
+    return _load('sfa89.dat')
+def sn():
+    """
+    Return SN Fatigue experiment, constant-amplitude loading.
+
+
+    Data summary
+    ------------
+    Size             :    40    X    2
+    Source           :    unknown
+    Format           :    ascii, c1: Amplitude MPa c2: Number of cycles
+
+    Description
+    -----------
+    A fatigue experiment with constant amplitudes at five levels:
+    10,15,20,25 and 30 MPa. For each level is related 8 observations of
+    the number of cycles to failure.
+
+    The origin of the data is unknown.
+
+     Example
+    -------
+    >>> import pylab
+    >>> import wafo
+    >>> x = wafo.data.sn()
+    >>> h = pylab.plot(x[:,0],x[:,1])
+
+    See also
+    --------
+    The same data appear in the directory wdemos/itmkurs/
+    as SN.mat.
+
+    """
+    return _load('sn.dat')
+def yura87():
+    """
+    Return Surface elevation measured off the coast of Yura.
+
+
+    Data summary
+    -----------
+      Size             :    85547 X 4
+      Sampling Rate    :    1 Hz
+      Device           :    ultrasonic wave gauges
+      Source           :    SRI, Ministry of Transport, Japan
+      Format           :    ascii, c1: time (sec) c2-4: surface elevation (m)
+
+    Description
+    -----------
+    The wave data was measured at the Poseidon platform
+    in the Japan Sea from 24th November 1987 08.12 hours to 25th November
+    1987 07.57 hours. Poseidon was located 3 km off the coast of Yura
+    in the Yamagata prefecture, in the Japan Sea during the measurements.
+    The most important wave components are to some extent influenced by the
+    water depth of 42 m. The data are measured with three ultrasonic wave
+    gauges located at the sea floor and the relative coordinates of the
+    gauges are as follows (x-axis points to the East, y-axis points to
+    the North):
+                 X (m)    Y (m)
+          c2:   -4.93,    25.02
+          c3:    5.80,    92.12
+          c4:    0.00,     0.00
+
+        This dataset is for non-commercial use only.
+
+        Hm0 = 5.1m, Tm02 = 7.7s, Tp = 12.8s
+    Example
+    -------
+    >>> import pylab
+    >>> import wafo
+    >>> x = wafo.data.yura87()
+    >>> h = pylab.plot(x[:,0],x[:,1])
+
+    Acknowledgement:
+    -----------------
+    This dataset were prepared and made available by Dr. Sc. H. Tomita,
+    Ship Research Institute, Ministry of Transport, Japan.
+
+    See also
+    --------
+    japansea
+    """
+    return _load('yura87.dat')
+if __name__=='__main__':
+    import doctest
+    doctest.testmod()

src/wafo/gaussian.py

@@ -2,7 +2,7 @@ import numpy as np
 from numpy import (r_, minimum, maximum, atleast_1d, atleast_2d, mod, zeros, #@UnresolvedImport
         ones, floor, random, eye, nonzero, repeat, sqrt, inf, diag, triu) #@UnresolvedImport
 from scipy.special import ndtri as invnorm
-import rindmod
+import wafo.rindmod as rindmod
 
 
 class Rind(object):

src/wafo/source/c_codes/build_all.py

@@ -8,7 +8,7 @@ def compile_all():
     #compile_format = 'f2py %s %s -c --fcompiler=gnu95 --compiler=mingw32 -lmsvcr71'
 
     # Install microsoft visual c++ .NET 2003 and run the following to build the module:
-    compile_format = 'f2py %s %s -c'
+    compile_format = 'f2py.py %s %s -c'
     pyfs = ('c_library.pyf',)
     files =('c_functions.c',)