Greatly simplify MarkovChain implementation

earwigbot/wiki/copyvios/markov.py

@@ -20,7 +20,6 @@
 # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 # SOFTWARE.
 
-from collections import defaultdict
 from re import sub, UNICODE
 
 __all__ = ["EMPTY", "EMPTY_INTERSECTION", "MarkovChain",
@@ -34,23 +33,27 @@ class MarkovChain(object):
 
     def __init__(self, text):
         self.text = text
-        self.chain = defaultdict(lambda: defaultdict(lambda: 0))
-        words = sub(r"[^\w\s-]", "", text.lower(), flags=UNICODE).split()
+        self.chain = self._build()
+        self.size = self._get_size()
 
+    def _build(self):
+        """Build and return the Markov chain from the input text."""
         padding = self.degree - 1
+        words = sub(r"[^\w\s-]", "", self.text.lower(), flags=UNICODE).split()
         words = ([self.START] * padding) + words + ([self.END] * padding)
-        for i in range(len(words) - self.degree + 1):
-            last = i + self.degree - 1
-            self.chain[tuple(words[i:last])][words[last]] += 1
-        self.size = self._get_size()
+        chain = {}
+
+        for i in xrange(len(words) - self.degree + 1):
+            phrase = tuple(words[i:i+self.degree])
+            if phrase in chain:
+                chain[phrase] += 1
+            else:
+                chain[phrase] = 1
+        return chain
 
     def _get_size(self):
         """Return the size of the Markov chain: the total number of nodes."""
-        size = 0
-        for node in self.chain.itervalues():
-            for hits in node.itervalues():
-                size += hits
-        return size
+        return sum(self.chain.itervalues())
 
     def __repr__(self):
         """Return the canonical string representation of the MarkovChain."""
@@ -65,20 +68,21 @@ class MarkovChainIntersection(MarkovChain):
     """Implements the intersection of two chains (i.e., their shared nodes)."""
 
     def __init__(self, mc1, mc2):
-        self.chain = defaultdict(lambda: defaultdict(lambda: 0))
         self.mc1, self.mc2 = mc1, mc2
-        c1 = mc1.chain
-        c2 = mc2.chain
-
-        for word, nodes1 in c1.iteritems():
-            if word in c2:
-                nodes2 = c2[word]
-                for node, count1 in nodes1.iteritems():
-                    if node in nodes2:
-                        count2 = nodes2[node]
-                        self.chain[word][node] = min(count1, count2)
+        self.chain = self._build()
         self.size = self._get_size()
 
+    def _build(self):
+        """Build and return the Markov chain from the input chains."""
+        c1 = self.mc1.chain
+        c2 = self.mc2.chain
+        chain = {}
+
+        for phrase in c1:
+            if phrase in c2:
+                chain[phrase] = min(c1[phrase], c2[phrase])
+        return chain
+
     def __repr__(self):
         """Return the canonical string representation of the intersection."""
         res = "MarkovChainIntersection(mc1={0!r}, mc2={1!r})"