Menu
▾
▴
[Salstat-svn] SF.net SVN: salstat:[31] salstat_stats.py
|
From: <mli...@us...> - 2010-11-01 02:17:02
|
Revision: 31
http://salstat.svn.sourceforge.net/salstat/?rev=31&view=rev
Author: mlivingstone
Date: 2010-11-01 02:16:56 +0000 (Mon, 01 Nov 2010)
Log Message:
-----------
Fix regression I caused some time ago by non-Python space-delimited blocking aware editor
Modified Paths:
--------------
salstat_stats.py
Modified: salstat_stats.py
===================================================================
--- salstat_stats.py 2010-10-25 03:57:16 UTC (rev 30)
+++ salstat_stats.py 2010-11-01 02:16:56 UTC (rev 31)
@@ -68,7 +68,7 @@
itemp = ivec[j]
ivec[j] = ivec[j+gap]
ivec[j+gap] = itemp
- gap = gap / 2 # integer division needed
+ gap = gap / 2 # integer division needed
# svec is now sorted inlist, and ivec has the order svec[i] = vec[ivec[i]]
return svec, ivec
@@ -145,55 +145,55 @@
"""
BIG = 20.0
def ex(x):
- BIG = 20.0
- if x < -BIG:
- return 0.0
- else:
- return math.exp(x)
+ BIG = 20.0
+ if x < -BIG:
+ return 0.0
+ else:
+ return math.exp(x)
- if chisq <=0 or df < 1:
- return 1.0
+ if chisq <= 0 or df < 1:
+ return 1.0
a = 0.5 * chisq
if df%2 == 0:
- even = 1
+ even = 1
else:
- even = 0
+ even = 0
if df > 1:
- y = ex(-a)
+ y = ex(-a)
if even:
- s = y
+ s = y
else:
- s = 2.0 * zprob(-math.sqrt(chisq))
+ s = 2.0 * zprob(-math.sqrt(chisq))
if (df > 2):
- chisq = 0.5 * (df - 1.0)
- if even:
- z = 1.0
- else:
- z = 0.5
- if a > BIG:
- if even:
- e = 0.0
- else:
- e = math.log(math.sqrt(math.pi))
- c = math.log(a)
- while (z <= chisq):
- e = math.log(z) + e
- s = s + ex(c*z-a-e)
- z = z + 1.0
- return s
- else:
- if even:
- e = 1.0
- else:
- e = 1.0 / math.sqrt(math.pi) / math.sqrt(a)
- c = 0.0
- while (z <= chisq):
- e = e * (a/float(z))
- c = c + e
- z = z + 1.0
- return (c*y+s)
+ chisq = 0.5 * (df - 1.0)
+ if even:
+ z = 1.0
+ else:
+ z = 0.5
+ if a > BIG:
+ if even:
+ e = 0.0
+ else:
+ e = math.log(math.sqrt(math.pi))
+ c = math.log(a)
+ while (z <= chisq):
+ e = math.log(z) + e
+ s = s + ex(c*z-a-e)
+ z = z + 1.0
+ return s
+ else:
+ if even:
+ e = 1.0
+ else:
+ e = 1.0 / math.sqrt(math.pi) / math.sqrt(a)
+ c = 0.0
+ while (z <= chisq):
+ e = e * (a/float(z))
+ c = c + e
+ z = z + 1.0
+ return (c*y+s)
else:
- return s
+ return s
def inversechi(prob, df):
"""This function calculates the inverse of the chi square function. Given
@@ -249,32 +249,32 @@
"""
Z_MAX = 6.0 # maximum meaningful z-value
if z == 0.0:
- x = 0.0
+ x = 0.0
else:
- y = 0.5 * math.fabs(z)
- if y >= (Z_MAX*0.5):
- x = 1.0
- elif (y < 1.0):
- w = y*y
- x = ((((((((0.000124818987 * w
- -0.001075204047) * w +0.005198775019) * w
- -0.019198292004) * w +0.059054035642) * w
- -0.151968751364) * w +0.319152932694) * w
- -0.531923007300) * w +0.797884560593) * y * 2.0
- else:
- y = y - 2.0
- x = (((((((((((((-0.000045255659 * y
- +0.000152529290) * y -0.000019538132) * y
- -0.000676904986) * y +0.001390604284) * y
- -0.000794620820) * y -0.002034254874) * y
- +0.006549791214) * y -0.010557625006) * y
- +0.011630447319) * y -0.009279453341) * y
- +0.005353579108) * y -0.002141268741) * y
- +0.000535310849) * y +0.999936657524
+ y = 0.5 * math.fabs(z)
+ if y >= (Z_MAX*0.5):
+ x = 1.0
+ elif (y < 1.0):
+ w = y*y
+ x = ((((((((0.000124818987 * w
+ -0.001075204047) * w +0.005198775019) * w
+ -0.019198292004) * w +0.059054035642) * w
+ -0.151968751364) * w +0.319152932694) * w
+ -0.531923007300) * w +0.797884560593) * y * 2.0
+ else:
+ y = y - 2.0
+ x = (((((((((((((-0.000045255659 * y
+ +0.000152529290) * y -0.000019538132) * y
+ -0.000676904986) * y +0.001390604284) * y
+ -0.000794620820) * y -0.002034254874) * y
+ +0.006549791214) * y -0.010557625006) * y
+ +0.011630447319) * y -0.009279453341) * y
+ +0.005353579108) * y -0.002141268741) * y
+ +0.000535310849) * y +0.999936657524
if z > 0.0:
- prob = ((x+1.0)*0.5)
+ prob = ((x+1.0)*0.5)
else:
- prob = ((1.0-x)*0.5)
+ prob = ((1.0-x)*0.5)
return prob
def ksprob(alam):
@@ -289,12 +289,12 @@
termbf = 0.0
a2 = -2.0*alam*alam
for j in range(1,201):
- term = fac*math.exp(a2*j*j)
- ksum = ksum + term
- if math.fabs(term)<=(0.001*termbf) or math.fabs(term)<(1.0e-8*ksum):
- return ksum
- fac = -fac
- termbf = math.fabs(term)
+ term = fac*math.exp(a2*j*j)
+ ksum = ksum + term
+ if math.fabs(term)<=(0.001*termbf) or math.fabs(term)<(1.0e-8*ksum):
+ return ksum
+ fac = -fac
+ termbf = math.fabs(term)
return 1.0 # Get here only if fails to converge; was 0.0!!
def fprob (dfnum, dfden, F):
This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.
|