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Aleš Erjavec committed 7e9b4eb

Fixed mixed tab/space indentation.

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  • Parent commits e4b810f

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Orange/classification/logreg.py

 ####################################
 ##  PROBABILITY CALCULATIONS
 
-def lchisqprob(chisq,df):
+def lchisqprob(chisq, df):
     """
     Return the (1-tailed) probability value associated with the provided
     chi-square value and df.  Adapted from chisq.c in Gary Perlman's |Stat.
     """
     BIG = 20.0
+
     def ex(x):
-    	BIG = 20.0
-    	if x < -BIG:
-    	    return 0.0
-    	else:
-    	    return math.exp(x)
-    if chisq <=0 or df < 1:
-    	return 1.0
+        BIG = 20.0
+        if x < -BIG:
+            return 0.0
+        else:
+            return math.exp(x)
+    if chisq <= 0 or df < 1:
+        return 1.0
     a = 0.5 * chisq
-    if df%2 == 0:
-    	even = 1
+    if df % 2 == 0:
+        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))
     if (df > 2):
             z = 0.5
         if a > BIG:
             if even:
-            	e = 0.0
+                e = 0.0
             else:
-            	e = math.log(math.sqrt(math.pi))
+                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
+                e = math.log(z) + e
+                s = s + ex(c * z - a - e)
+                z = z + 1.0
             return s
         else:
             if even:
                 e = 1.0 / math.sqrt(math.pi) / math.sqrt(a)
             c = 0.0
             while (z <= chisq):
-                e = e * (a/float(z))
+                e = e * (a / float(z))
                 c = c + e
                 z = z + 1.0
-            return (c*y+s)
+            return (c * y + s)
     else:
         return s
 
 def zprob(z):
     """
     Returns the area under the normal curve 'to the left of' the given z value.
-    Thus:: 
+    Thus::
 
     for z<0, zprob(z) = 1-tail probability
     for z>0, 1.0-zprob(z) = 1-tail probability
     """
     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