# Commits

committed 7e9b4eb

Fixed mixed tab/space indentation.

• Participants
• Parent commits e4b810f

# 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`
` `
` `