updated __all__ attributes in modules

pywafo/src/wafo/__init__.py

@@ -9,6 +9,7 @@ import transform
 import definitions
 import polynomial
 import stats
+import interpolate
 
 try:
     from wafo.version import version as __version__

pywafo/src/wafo/covariance/__init__.py

@@ -2,6 +2,6 @@
 Covariance package in WAFO Toolbox.
 """
 
-from core import CovData1D
+from core import * #CovData1D
 #import models
 #import dispersion_relation

pywafo/src/wafo/gaussian.py

@@ -2,14 +2,15 @@ from numpy import r_, minimum, maximum, atleast_1d, atleast_2d, mod, ones, floor
     random, eye, nonzero, where, repeat, sqrt, exp, inf, diag, zeros, sin, arcsin, nan #@UnresolvedImport
 from numpy import triu #@UnresolvedImport
 from scipy.special import ndtr as cdfnorm, ndtri as invnorm
+from scipy.special import erfc
 from wafo import mvn
 import numpy as np
 import wafo.mvnprdmod as mvnprdmod
 import wafo.rindmod as rindmod
 import warnings
 from wafo.misc import common_shape
-from scipy.stats.stats import erfc
 
+__all__ = ['Rind', 'rindmod', 'mvnprdmod', 'mvn', 'cdflomax' , 'prbnormtndpc', 'prbnormndpc', 'prbnormnd', 'cdfnornd2', 'prbnorm2d','cdfnorm','invnorm']
 class Rind(object):
     '''
     RIND Computes multivariate normal expectations
@@ -595,7 +596,6 @@ _ERRORMESSAGE[6] = '''the input is invalid because:
 
 def  prbnormnd(correl, a, b, abseps=1e-4, releps=1e-3, maxpts=None, method=0):
     '''
-    
     Multivariate Normal probability by Genz' algorithm.
     
     

pywafo/src/wafo/integrate.py

@@ -11,6 +11,9 @@ from wafo.misc import meshgrid
 
 _POINTS_AND_WEIGHTS = {}
 
+__all__ = ['peaks', 'humps', 'is_numlike', 'dea3', 'clencurt', 'romberg', 
+         'h_roots','j_roots', 'la_roots','p_roots','qrule',
+         'gaussq', 'richardson', 'quadgr', 'qdemo']
 def peaks(x=None, y=None, n=51):
     '''
     Return the "well" known MatLab (R) peaks function
@@ -20,7 +23,7 @@ def peaks(x=None, y=None, n=51):
     -------
     >>> import pylab as plt
     >>> x,y,z = peaks()
-    >>> plt.contourf(x,y,z)
+    >>> h = plt.contourf(x,y,z)
     
     '''
     if x is None:
@@ -1164,7 +1167,8 @@ def gaussq(fun, a, b, reltol=1e-3, abstol=1e-3, alpha=0, beta=0, wfun=1,
     return val, abserr
 
 def richardson(Q, k):
-    #% Richardson extrapolation with parameter estimation
+    # license BSD
+    # Richardson extrapolation with parameter estimation
     c = np.real((Q[k - 1] - Q[k - 2]) / (Q[k] - Q[k - 1])) - 1.
     #% The lower bound 0.07 admits the singularity x.^-0.9
     c = max(c, 0.07)
@@ -1212,9 +1216,7 @@ def quadgr(fun, a, b, abseps=1e-5):
     QUAD,
     QUADGK
     '''
-    #%   Author: jonas.lundgren@saabgroup.com, 2009.
-
-
+    # Author: jonas.lundgren@saabgroup.com, 2009. license BSD
     # Order limits (required if infinite limits)
     if a == b:
         Q = b - a

pywafo/src/wafo/interpolate.py

@@ -19,6 +19,8 @@ from numpy.lib.shape_base import vstack
 from numpy.lib.function_base import linspace
 import polynomial as pl
 
+__all__ =['PPform','SmoothSpline']
+
 class PPform(object):
     """The ppform of the piecewise polynomials is given in terms of coefficients
     and breaks.  The polynomial in the ith interval is

pywafo/src/wafo/kdetools.py

@@ -12,7 +12,7 @@
 from __future__ import division
 from itertools import product
 from misc import tranproc #, trangood
-from numpy import pi, sqrt, atleast_2d, exp, newaxis, array #@UnresolvedImport
+from numpy import pi, sqrt, atleast_2d, exp, newaxis #@UnresolvedImport
 from scipy import interpolate, linalg
 from scipy.special import gamma
 from wafo.misc import meshgrid
@@ -32,8 +32,8 @@ _stats_lapl = (2, 1. / 4, np.inf)
 _stats_logi = (pi ** 2 / 3, 1. / 6, 1 / 42)
 _stats_gaus = (1, 1. / (2 * sqrt(pi)), 3. / (8 * sqrt(pi)))
               
-
-
+__all__ =['sphere_volume','TKDE', 'KDE', 'Kernel', 'accum', 'qlevels',
+           'iqrange', 'gridcount', 'kde_demo1', 'kde_demo2']
 def sphere_volume(d, r=1.0):
     """
     Returns volume of  d-dimensional sphere with radius r

pywafo/src/wafo/misc.py

@@ -24,10 +24,12 @@ floatinfo = finfo(float)
 
 
 __all__ = ['JITImport', 'DotDict', 'Bunch', 'printf', 'sub_dict_select',
-    'parse_kwargs', 'ecross', 'findtc', 'findtp', 'findcross',
-    'findextrema', 'findrfc', 'rfcfilter', 'common_shape', 'argsreduce',
+    'parse_kwargs', 'detrendma', 'ecross', 'findcross',
+    'findextrema', 'findpeaks', 'findrfc', 'rfcfilter', 'findtp', 'findtc', 
+    'findoutliers', 'common_shape', 'argsreduce',
     'stirlerr', 'getshipchar', 'betaloge', 'gravity', 'nextpow2',
-    'discretize', 'pol2cart', 'cart2pol', 'ndgrid', 'meshgrid', 'histgrm']
+    'discretize', 'discretize2', 'pol2cart', 'cart2pol',  'meshgrid', 'ndgrid', 
+    'trangood', 'tranproc', 'histgrm', 'num2pistr']
 
 class JITImport(object):
     ''' 
@@ -434,7 +436,7 @@ def findpeaks(data, n=2, min_h=None, min_p=0.0):
         if len(TuP):
             ind = TuP[1::2] #; % extract indices to maxima only
         else: # % did not find any , try maximum
-            ind = S[iy].argmax()
+            ind = np.atleast_1d(S[iy].argmax())
       
         if ndim>1:
             if iy==0:

pywafo/src/wafo/spectrum/__init__.py

@@ -5,6 +5,6 @@ Spectrum package in WAFO Toolbox.
 
 """
 
-from core import SpecData1D, SpecData2D, cltext
+from core import * #SpecData1D, SpecData2D, cltext
 import models
 import dispersion_relation

pywafo/src/wafo/spectrum/core.py

@@ -1,5 +1,5 @@
 from __future__ import division
-from wafo.misc import meshgrid, gravity
+from wafo.misc import meshgrid, gravity, cart2pol, pol2cart
 from wafo.objects import mat2timeseries, TimeSeries
 import warnings
 
@@ -180,6 +180,12 @@ def plotspec(specdata, linetype='b-', flag=1):
      NOTE: - lintype may be given anywhere after S.
     
      Examples
+    >>> import numpy as np
+    >>> import wafo.spectrum.models as sm
+    >>> Sj = sm.Jonswap(Hm0=3, Tp=7)
+    >>> S = Sj.tospecdata()
+    >>> plotspec(S,1)
+
       S = demospec('dir'); S2 = mkdspec(jonswap,spreading);
       plotspec(S,2), hold on
       plotspec(S,3,'g')  % Same as previous fig. due to frequency independent spreading
@@ -250,8 +256,8 @@ def plotspec(specdata, linetype='b-', flag=1):
     spectype = specdata.type.lower()
     stype = spectype[-3::]
     if stype in ('enc','req','k1d') : #1D plot
-        Fn   = freq(-1) # Nyquist frequency
-        indm = findpeaks(data,n=4)
+        Fn   = freq[-1] # Nyquist frequency
+        indm = findpeaks(data, n=4)
         maxS = data.max()
 #        if isfield(S,'CI') && ~isempty(S.CI),
 #          maxS  = maxS*S.CI(2);
@@ -1714,8 +1720,8 @@ class SpecData1D(WafoData):
         >>> x2, x1 = S.sim_nl(ns=20000,cases=20)
         >>> truth1 = [0,np.sqrt(S.moment(1)[0][0])] + S.stats_nl(moments='sk')
         >>> truth1[-1] = truth1[-1]-3
-        >>> truth1
-        [0, 1.7495200310090628, 0.18673120577479821, 0.06198852126241805]
+        >>> np.round(truth1, 3)
+        array([ 0.   ,  1.75 ,  0.187,  0.062])
          
         >>> funs = [np.mean,np.std,st.skew,st.kurtosis]
         >>> for fun,trueval in zip(funs,truth1):
@@ -1736,8 +1742,8 @@ class SpecData1D(WafoData):
         >>> x2 = np.hstack(x)
         >>> truth1 = [0,np.sqrt(S.moment(1)[0][0])] + S.stats_nl(moments='sk')
         >>> truth1[-1] = truth1[-1]-3
-        >>> truth1
-        [0, 1.7495200310090628, 0.18673120577479821, 0.06198852126241805]
+        >>> np.round(truth1,3)
+        array([ 0.   ,  1.75 ,  0.187,  0.062])
          
         >>> funs = [np.mean,np.std,st.skew,st.kurtosis]
         >>> for fun,trueval in zip(funs,truth1):
@@ -2811,10 +2817,10 @@ class SpecData1D(WafoData):
             title = 'Directional Spectrum'
             if self.freqtype.startswith('w'):
                 labels[0] = 'Frequency [rad/s]'
-                labels[2] = 'S(w,\theta) [m^2 s / rad^2]'
+                labels[2] = r'S(w,$\theta$) $[m^2 s / rad^2]$'
             else:
                 labels[0] = 'Frequency [Hz]'
-                labels[2] = 'S(f,\theta) [m^2 s / rad]'
+                labels[2] = r'S(f,$\theta$) $[m^2 s / rad]$'
 
             if self.angletype.startswith('r'):
                 labels[1] = 'Wave directions [rad]'
@@ -2824,18 +2830,18 @@ class SpecData1D(WafoData):
             title = 'Spectral density'
             if self.freqtype.startswith('w'):
                 labels[0] = 'Frequency [rad/s]'
-                labels[1] = 'S(w) [m^2 s/ rad]'
+                labels[1] = r'S(w) $[m^2 s/ rad]$'
             else:
                 labels[0] = 'Frequency [Hz]'
-                labels[1] = 'S(f) [m^2 s]'
+                labels[1] = r'S(f) $[m^2 s]$'
         else:
             title = 'Wave Number Spectrum'
             labels[0] = 'Wave number [rad/m]'
             if self.type.endswith('k1d'):
-                labels[1] = 'S(k) [m^3/ rad]'
+                labels[1] = r'S(k) $[m^3/ rad]$'
             elif self.type.endswith('k2d'):
                 labels[1] = labels[0]
-                labels[2] = 'S(k1,k2) [m^4/ rad^2]'
+                labels[2] = r'S(k1,k2) $[m^4/ rad^2]$'
             else:
                 raise ValueError('Object does not appear to be initialized, it is empty!')
         if self.norm != 0:
@@ -2975,7 +2981,7 @@ class SpecData2D(WafoData):
                     if (self.args[0][0]==-pi):
                         self.data[ntOld,:] = self.data[0,:]
                     else:    
-                        ftype = self.freqtype 
+                        #ftype = self.freqtype 
                         freq  = self.args[1]
                         theta = linspace(-pi,pi,ntOld)
                         [F,T] = meshgrid(freq,theta)
@@ -2985,7 +2991,7 @@ class SpecData2D(WafoData):
                         self.data[nt,:]   = self.data[0,:]
                         self.data = interp2(freq,np.vstack([self.theta[0]-dtheta,self.theta]),
                                             np.vstack([self.data[nt,:],self.data]),F,T,method)
-                        self.args[0] = theta;
+                        self.args[0] = theta
                  
         elif stype=='k2d': 
             #any of the 2D wave number types
@@ -3053,8 +3059,8 @@ class SpecData2D(WafoData):
         >>> SD = D.tospecdata2d(sm.Jonswap().tospecdata(),nt=101)
         >>> m,mtext = SD.moment(nr=2,vari='xyt')
         >>> np.round(m,3),mtext
-        (array([ 3.061,  0.132, -0.   ,  2.13 ,  0.011,  0.008,  1.677, -0.   ,
-                0.109,  0.109]), ['m0', 'mx', 'my', 'mt', 'mxx', 'myy', 'mtt', 'mxy', 'mxt', 'myt'])
+        (array([ 3.061,  0.132,  0.   ,  2.13 ,  0.011,  0.008,  1.677, -0.   ,
+            0.109,  0.109]), ['m0', 'mx', 'my', 'mt', 'mxx', 'myy', 'mtt', 'mxy', 'mxt', 'myt'])
 
         References
         ----------

pywafo/src/wafo/stats/__init__.py

@@ -7,3 +7,4 @@ Statistics package in WAFO Toolbox.
 from scipy.stats import *
 from core import *
 from wafo.stats.distributions import *
+import estimation

pywafo/src/wafo/stats/core.py

@@ -6,11 +6,11 @@ from scipy import special
 import numpy as np
 from numpy import inf
 from numpy import atleast_1d, nan, ndarray, sqrt, vstack, ones, where, zeros
-from numpy import arange, floor, linspace, asarray, reshape, repeat, product
+from numpy import arange, floor, linspace, asarray #, reshape, repeat, product
 
 
 __all__ = ['edf', 'edfcnd','reslife', 'dispersion_idx','decluster','findpot', 
-           'declustering_time','extremal_idx']
+           'declustering_time','interexceedance_times', 'extremal_idx']
 
 arr = asarray
 
@@ -533,8 +533,6 @@ def _find_ok_peaks(Ye, Te, Tmin):
     iOK, = where(1 - isTooClose[oOrder])
     return iOK
 
-
-    
 def declustering_time(t):
     '''
     Returns minimum distance between clusters.