Added test for estimation.py

pywafo/src/wafo/stats/estimation.py

@@ -385,7 +385,7 @@ class Profile(object):
         mphat = self._par.copy()
         mphat[self.i_notfixed] = phatnotfixed
         logSF = self.fit_dist.dist.logsf(self.x, *mphat) 
-        return np.where(np.isfinite(logSF), logSF, -np.inf)
+        return np.where(np.isfinite(logSF), logSF, np.nan)
 
 
     def _nlogfun(self, free_par, fix_par):

pywafo/src/wafo/stats/tests/test_estimation.py

@@ -0,0 +1,65 @@
+'''
+Created on 19. nov. 2010
+
+@author: pab
+'''
+
+import  wafo.stats as ws
+from wafo.stats.estimation import Profile, FitDistribution
+from numpy import log, array
+def test_profile():
+    '''
+     # MLE 
+    import wafo.stats as ws
+    R = ws.weibull_min.rvs(1,size=100)
+    >>> R = array([ 1.11214852,  0.55730247,  0.88241032,  0.13421021,  0.21939628,
+    ...        0.93901239,  4.55065051,  0.06728561,  1.65808964,  3.31725493,
+    ...        1.26022136,  0.48707756,  1.04600817,  3.45064509,  0.23478845,
+    ...        0.73197928,  0.78702608,  1.10566899,  0.08770387,  0.29773143,
+    ...        0.442589  ,  0.06017045,  0.99086215,  0.36520787,  0.55931192,
+    ...        0.02220038,  0.09683231,  0.2407798 ,  1.5550326 ,  1.21834857,
+    ...        0.51317074,  3.12672982,  2.01984527,  1.42837289,  1.60665276,
+    ...        0.07643233,  0.97254151,  0.71870616,  0.15669964,  0.7647863 ,
+    ...        2.15586998,  1.03167507,  0.66384501,  0.26824186,  0.25953582,
+    ...        0.52773641,  0.3371869 ,  1.17897776,  0.36094868,  0.49593992,
+    ...       0.12124638,  0.13178139,  0.28325022,  1.2189952 ,  2.85895075,
+    ...        1.94868469,  1.5216953 ,  0.77066953,  0.42610845,  1.52848366,
+    ...        0.26570905,  0.52072509,  1.03106309,  0.34430637,  1.36386879,
+    ...        1.05857501,  0.66754409,  3.18836655,  0.40063524,  0.40696207,
+    ...        1.24167978,  0.27927484,  3.95644924,  1.34793436,  0.66225993,
+    ...        0.46567866,  0.09325875,  1.90895739,  1.23831713,  0.29819745,
+    ...        1.10528719,  0.01973962,  0.56370415,  0.66831751,  1.33781636,
+    ...        0.53985288,  0.85251279,  1.75369891,  0.08066507,  0.29273944,
+    ...        0.38886539,  0.20961546,  0.93814728,  0.08732068,  1.6336713 ,
+    ...        1.38893923,  2.05882459,  0.51709862,  0.37553027,  0.06829269])
+    
+    >>> phat = FitDistribution(ws.weibull_min, R, 1, scale=1, floc=0.0)
+    >>> phat.par
+    array([ 1.07424857,  0.        ,  0.96282996])
+    
+    # Better CI for phat.par[i=0]
+    >>> Lp = Profile(phat, i=0)
+    >>> Lp.get_bounds(alpha=0.1)
+    array([ 0.94231243,  1.21444458])
+    
+    >>> SF = 1./990
+    >>> x = phat.isf(SF)
+    >>> x
+    5.8114656626008818
+    
+    # CI for x
+    >>> Lx = phat.profile(i=0, x=x, link=phat.dist.link)
+    >>> Lx.get_bounds(alpha=0.2)
+    array([ 4.91172017,  7.08081584])
+    
+    # CI for logSF=log(SF)
+    >>> Lsf = phat.profile(i=0, logSF=log(SF), link=phat.dist.link)
+    >>> Lsf.get_bounds(alpha=0.2)
+    array([-8.37580767, -5.66897775])
+    '''
+    pass
+
+
+if __name__ == "__main__":
+    import doctest
+    doctest.testmod()