Standardize imports for edist.py ocropus-archive#176

ocrolib/edist.py

@@ -1,7 +1,8 @@
-from scipy.ndimage import filters
-from pylab import *
 import re
 
+import numpy as np
+from scipy.ndimage import filters
+
 def levenshtein(a,b):
     """Calculates the Levenshtein distance between a and b. 
     (Clever compact Pythonic implementation from hetland.org)"""
@@ -23,10 +24,10 @@ def xlevenshtein(a,b,context=1):
     n, m = len(a), len(b)
     assert m>0 # xlevenshtein should only be called with non-empty b string (ground truth)
     if a == b: return 0,[] # speed up for the easy case
-    sources = empty((m+1,n+1),object)
+    sources = np.empty((m+1,n+1),object)
     sources[:,:] = None
-    dists = 99999*ones((m+1,n+1))
-    dists[0,:] = arange(n+1)
+    dists = np.full((m+1,n+1),99999)
+    dists[0,:] = np.arange(n+1)
     for i in range(1,m+1):
         previous = dists[i-1,:]
         current = dists[i,:]
@@ -70,7 +71,7 @@ def xlevenshtein(a,b,context=1):
     al = " "*context+al+" "*context
     bl = " "*context+bl+" "*context
     assert "~" not in al and "~" not in bl
-    same = array([al[i]==bl[i] for i in range(len(al))],'i')
+    same = np.array([al[i]==bl[i] for i in range(len(al))],'i')
     same = filters.minimum_filter(same,1+2*context)
     als = "".join([al[i] if not same[i] else "~" for i in range(len(al))])
     bls = "".join([bl[i] if not same[i] else "~" for i in range(len(bl))])