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Fixed a bug in nlogps when ties occuring in the data.

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master
per.andreas.brodtkorb 14 years ago
parent bb9a2392c9
commit 67c005341d
4 changed files with 42 additions and 25 deletions
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2
pywafo/src/wafo/source/mreg/quadrmod.mod
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@ -1,4 +1,4 @@
GFORTRAN module version '0' created from mregmodule.f on Wed Aug 05 19:15:05 2009
GFORTRAN module version '0' created from mregmodule.f on Tue Jan 25 23:52:18 2011
MD5:447301769c212f228b6cfa086ba1d48a -- If you edit this, you'll get what you deserve.
(() () () () () () () () () () () () () () () () () () () () () () () ()

40
pywafo/src/wafo/source/mreg/svd.mod
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@ -1,5 +1,5 @@
GFORTRAN module version '0' created from dsvdc.f on Wed Aug 05 19:15:05 2009
MD5:06f4ab5dbb3a45df847b6d37183b2196 -- If you edit this, you'll get what you deserve.
GFORTRAN module version '0' created from dsvdc.f on Tue Jan 25 20:12:18 2011
MD5:504db75f3667c360354623f37288fa05 -- If you edit this, you'll get what you deserve.
(() () () () () () () () () () () () () () () () () () () () () () () ()
() () ())
@ -32,19 +32,22 @@ PROCEDURE UNKNOWN-INTENT UNKNOWN-PROC UNKNOWN UNKNOWN FUNCTION) (
UNKNOWN 0 0 0 UNKNOWN ()) 0 0 () () 32 () () () 0 0)
33 'svd' 'svd' 'svd' 1 ((MODULE UNKNOWN-INTENT UNKNOWN-PROC UNKNOWN
UNKNOWN) (UNKNOWN 0 0 0 UNKNOWN ()) 0 0 () () 0 () () () 0 0)
15 'ds' '' 'ds' 11 ((VARIABLE OUT UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY) (
REAL 8 0 0 REAL ()) 0 0 () () 0 () () () 0 0)
12 'da' '' 'da' 11 ((VARIABLE INOUT UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY)
(REAL 8 0 0 REAL ()) 0 0 () () 0 () () () 0 0)
13 'db' '' 'db' 11 ((VARIABLE INOUT UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY)
(REAL 8 0 0 REAL ()) 0 0 () () 0 () () () 0 0)
14 'dc' '' 'dc' 11 ((VARIABLE OUT UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY) (
REAL 8 0 0 REAL ()) 0 0 () () 0 () () () 0 0)
15 'ds' '' 'ds' 11 ((VARIABLE OUT UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY) (
REAL 8 0 0 REAL ()) 0 0 () () 0 () () () 0 0)
29 'n' '' 'n' 28 ((VARIABLE IN UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY) (
INTEGER 4 0 0 INTEGER ()) 0 0 () () 0 () () () 0 0)
30 'dx' '' 'dx' 28 ((VARIABLE INOUT UNKNOWN-PROC UNKNOWN UNKNOWN
DIMENSION DUMMY) (REAL 8 0 0 REAL ()) 0 0 () (1 ASSUMED_SIZE (CONSTANT (
INTEGER 4 0 0 INTEGER ()) 0 '1') ()) 0 () () () 0 0)
31 'dy' '' 'dy' 28 ((VARIABLE INOUT UNKNOWN-PROC UNKNOWN UNKNOWN
DIMENSION DUMMY) (REAL 8 0 0 REAL ()) 0 0 () (1 ASSUMED_SIZE (CONSTANT (
INTEGER 4 0 0 INTEGER ()) 0 '1') ()) 0 () () () 0 0)
5 'n' '' 'n' 4 ((VARIABLE IN UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY) (
INTEGER 4 0 0 INTEGER ()) 0 0 () () 0 () () () 0 0)
6 'dx' '' 'dx' 4 ((VARIABLE INOUT UNKNOWN-PROC UNKNOWN UNKNOWN DIMENSION
@ -53,6 +56,18 @@ DUMMY) (REAL 8 0 0 REAL ()) 0 0 () (1 ASSUMED_SIZE (CONSTANT (INTEGER 4
7 'dy' '' 'dy' 4 ((VARIABLE INOUT UNKNOWN-PROC UNKNOWN UNKNOWN DIMENSION
DUMMY) (REAL 8 0 0 REAL ()) 0 0 () (1 ASSUMED_SIZE (CONSTANT (INTEGER 4
0 0 INTEGER ()) 0 '1') ()) 0 () () () 0 0)
8 'c' '' 'c' 4 ((VARIABLE IN UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY) (REAL 8
0 0 REAL ()) 0 0 () () 0 () () () 0 0)
9 's' '' 's' 4 ((VARIABLE IN UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY) (REAL 8
0 0 REAL ()) 0 0 () () 0 () () () 0 0)
18 'x' '' 'x' 17 ((VARIABLE INOUT UNKNOWN-PROC UNKNOWN UNKNOWN DIMENSION
DUMMY) (REAL 8 0 0 REAL ()) 0 0 () (2 ASSUMED_SHAPE (CONSTANT (INTEGER 4
0 0 INTEGER ()) 0 '1') () (CONSTANT (INTEGER 4 0 0 INTEGER ()) 0 '1') ())
0 () () () 0 0)
19 'n' '' 'n' 17 ((VARIABLE IN UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY) (
INTEGER 4 0 0 INTEGER ()) 0 0 () () 0 () () () 0 0)
20 'p' '' 'p' 17 ((VARIABLE IN UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY) (
INTEGER 4 0 0 INTEGER ()) 0 0 () () 0 () () () 0 0)
21 's' '' 's' 17 ((VARIABLE OUT UNKNOWN-PROC UNKNOWN UNKNOWN DIMENSION
DUMMY) (REAL 8 0 0 REAL ()) 0 0 () (1 ASSUMED_SHAPE (CONSTANT (INTEGER 4
0 0 INTEGER ()) 0 '1') ()) 0 () () () 0 0)
@ -63,29 +78,14 @@ DUMMY) (REAL 8 0 0 REAL ()) 0 0 () (1 ASSUMED_SHAPE (CONSTANT (INTEGER 4
DUMMY) (REAL 8 0 0 REAL ()) 0 0 () (2 ASSUMED_SHAPE (CONSTANT (INTEGER 4
0 0 INTEGER ()) 0 '1') () (CONSTANT (INTEGER 4 0 0 INTEGER ()) 0 '1') ())
0 () () () 0 0)
25 'job' '' 'job' 17 ((VARIABLE IN UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY) (
INTEGER 4 0 0 INTEGER ()) 0 0 () () 0 () () () 0 0)
24 'v' '' 'v' 17 ((VARIABLE OUT UNKNOWN-PROC UNKNOWN UNKNOWN DIMENSION
DUMMY) (REAL 8 0 0 REAL ()) 0 0 () (2 ASSUMED_SHAPE (CONSTANT (INTEGER 4
0 0 INTEGER ()) 0 '1') () (CONSTANT (INTEGER 4 0 0 INTEGER ()) 0 '1') ())
0 () () () 0 0)
18 'x' '' 'x' 17 ((VARIABLE INOUT UNKNOWN-PROC UNKNOWN UNKNOWN DIMENSION
DUMMY) (REAL 8 0 0 REAL ()) 0 0 () (2 ASSUMED_SHAPE (CONSTANT (INTEGER 4
0 0 INTEGER ()) 0 '1') () (CONSTANT (INTEGER 4 0 0 INTEGER ()) 0 '1') ())
0 () () () 0 0)
19 'n' '' 'n' 17 ((VARIABLE IN UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY) (
INTEGER 4 0 0 INTEGER ()) 0 0 () () 0 () () () 0 0)
20 'p' '' 'p' 17 ((VARIABLE IN UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY) (
25 'job' '' 'job' 17 ((VARIABLE IN UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY) (
INTEGER 4 0 0 INTEGER ()) 0 0 () () 0 () () () 0 0)
26 'info' '' 'info' 17 ((VARIABLE OUT UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY)
(INTEGER 4 0 0 INTEGER ()) 0 0 () () 0 () () () 0 0)
31 'dy' '' 'dy' 28 ((VARIABLE INOUT UNKNOWN-PROC UNKNOWN UNKNOWN
DIMENSION DUMMY) (REAL 8 0 0 REAL ()) 0 0 () (1 ASSUMED_SIZE (CONSTANT (
INTEGER 4 0 0 INTEGER ()) 0 '1') ()) 0 () () () 0 0)
8 'c' '' 'c' 4 ((VARIABLE IN UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY) (REAL 8
0 0 REAL ()) 0 0 () () 0 () () () 0 0)
9 's' '' 's' 4 ((VARIABLE IN UNKNOWN-PROC UNKNOWN UNKNOWN DUMMY) (REAL 8
0 0 REAL ()) 0 0 () () 0 () () () 0 0)
)
('dp' 0 2 'drot1' 0 3 'drotg' 0 10 'dsvdc' 0 16 'dswap1' 0 27

4
pywafo/src/wafo/stats/distributions.py
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@ -2032,7 +2032,7 @@ class rv_continuous(rv_generic):
if (any(cond0)):
return inf
else:
linfo = numpy.finfo(float)
#linfo = numpy.finfo(float)
realmax = floatinfo.machar.xmax
lowertail = True
@ -2059,7 +2059,7 @@ class rv_continuous(rv_generic):
i_tie = nonzero(tie)
tiedata = x[i_tie]
logD[i_tie + 1] = log(self._pdf(tiedata, *args)) + log(scale)
logD[i_tie + 1] = log(self._pdf(tiedata, *args)) - log(scale)
finiteD = numpy.isfinite(logD)
nonfiniteD = 1 - finiteD

21
pywafo/src/wafo/stats/estimation.py
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@ -901,8 +901,25 @@ class FitDistribution(rv_frozen):
If so the histogram should resemble the model density.
Other distribution types will introduce deviations in the plot.
'''
bin, limits = numpy.histogram(self.data, normed=True) #, new=True)
odd = False
x = np.atleast_1d(self.data)
n = np.ceil(4 * np.sqrt(np.sqrt(len(x))))
mn = x.min()
mx = x.max()
d = (mx - mn) / n * 2
e = np.floor(np.log(d) / np.log(10));
m = np.floor(d / 10 ** e)
if m > 5:
m = 5
elif m > 2:
m = 2
d = m * 10 ** e
mn = (np.floor(mn / d) - 1) * d - odd * d / 2
mx = (np.ceil(mx / d) + 1) * d + odd * d / 2
limits = np.arange(mn, mx, d)
bin, limits = numpy.histogram(self.data, bins=limits, normed=True) #, new=True)
limits.shape = (-1, 1)
xx = limits.repeat(3, axis=1)
xx.shape = (-1,)

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