[Spambayes-checkins] spambayes hammiesrv.py,NONE,1.1 runtest.sh,1.2,1.3

[Neale Pickett]

Update of /cvsroot/spambayes/spambayes
In directory usw-pr-cvs1:/tmp/cvs-serv26022

Modified Files:
	runtest.sh 
Added Files:
	hammiesrv.py 
Log Message:
* runtest now supports targets and a -r option to force re-rebal-ing

* new hammiesrv, with a nice clean Hammie class I probably ought to
  move to hammie.py before anything new code imports it



--- NEW FILE: hammiesrv.py ---
#! /usr/bin/env python

# A server version of hammie.py

# Server code

import SimpleXMLRPCServer
import email
import hammie
from tokenizer import tokenize

# Default header to add
DFL_HEADER = "X-Hammie-Disposition"

# Default spam cutoff
DFL_CUTOFF = 0.9

class Hammie:
    def __init__(self, bayes):
        self.bayes = bayes

    def _scoremsg(self, msg, evidence=False):
        """Score an email.Message.

        Returns the probability the message is spam.  If evidence is
        true, returns a tuple: (probability, clues), where clues is a
        list of the words which contributed to the score.

        """

        return self.bayes.spamprob(tokenize(msg), evidence)
        
    def score(self, msg, evidence=False):
        """Score (judge) a message.

        Pass in a message as a string.

        Returns the probability the message is spam.  If evidence is
        true, returns a tuple: (probability, clues), where clues is a
        list of the words which contributed to the score.

        """
        
        return self._scoremsg(email.message_from_string(msg), evidence)

    def filter(self, msg, header=DFL_HEADER, cutoff=DFL_CUTOFF):
        """Score (judge) a message and add a disposition header.

        Pass in a message as a string.  Optionally, set header to the
        name of the header to add, and/or cutoff to the probability
        value which must be met or exceeded for a message to get a 'Yes'
        disposition.
        
        Returns the same message with a new disposition header.

        """

        msg = email.message_from_string(msg)
        prob, clues = self._scoremsg(msg, True)
        if prob < cutoff:
            disp = "No"
        else:
            disp = "Yes"
        disp += "; %.2f" % prob
        disp += "; " + hammie.formatclues(clues)
        msg.add_header(header, disp)
        return msg.as_string(unixfrom=(msg.get_unixfrom() is not None))

    def train(self, msg, is_spam):
        """Train bayes with a message.

        msg should be the message as a string, and is_spam should be 1
        if the message is spam, 0 if not.

        Probabilities are not updated after this call is made; to do
        that, call update_probabilities().
        
        """
        
        self.bayes.learn(tokenize(msg), is_spam, False)

    def train_ham(self, msg):
        """Train bayes with ham.

        msg should be the message as a string.

        Probabilities are not updated after this call is made; to do
        that, call update_probabilities().

        """

        self.train(msg, False)

    def train_spam(self, msg):
        """Train bayes with spam.

        msg should be the message as a string.

        Probabilities are not updated after this call is made; to do
        that, call update_probabilities().

        """

        self.train(msg, True)

    def update_probabilities(self):
        """Update probability values.

        You would want to call this after a training session.  It's
        pretty slow, so if you have a lot of messages to train, wait
        until you're all done before calling this.

        """
        
        self.bayes.update_probabilites()
        
def main():
    usedb = True
    pck = "/home/neale/lib/hammie.db"
    
    if usedb:
        bayes = hammie.PersistentGrahamBayes(pck)
    else:
        bayes = None
        try:
            fp = open(pck, 'rb')
        except IOError, e:
            if e.errno <> errno.ENOENT: raise
        else:
            bayes = pickle.load(fp)
            fp.close()
        if bayes is None:
            import classifier
            bayes = classifier.GrahamBayes()

    server = SimpleXMLRPCServer.SimpleXMLRPCServer(("localhost", 7732))
    server.register_instance(Hammie(bayes))
    server.serve_forever()

if __name__ == "__main__":
    main()


Index: runtest.sh
===================================================================
RCS file: /cvsroot/spambayes/spambayes/runtest.sh,v
retrieving revision 1.2
retrieving revision 1.3
diff -C2 -d -r1.2 -r1.3
*** runtest.sh	18 Sep 2002 17:44:25 -0000	1.2
--- runtest.sh	19 Sep 2002 00:17:41 -0000	1.3
***************
*** 16,20 ****
  ##
  
! # Test to run
  TEST=${1:-robinson1}
  
--- 16,25 ----
  ##
  
! if [ "$1" = "-r" ]; then
!     REBAL=1
!     shift
! fi
! 
! # Which test to run
  TEST=${1:-robinson1}
  
***************
*** 25,36 ****
  SETS=5
  
! # Put them all into reservoirs
! python rebal.py -r Data/Ham/reservoir -s Data/Ham/Set -n 0 -Q
! python rebal.py -r Data/Spam/reservoir -s Data/Spam/Set -n 0 -Q
! # Rebalance
! python rebal.py -r Data/Ham/reservoir -s Data/Ham/Set -n $RNUM -Q
! python rebal.py -r Data/Spam/reservoir -s Data/Spam/Set -n $RNUM -Q
  
  case "$TEST" in
      robinson1)
  	# This test requires you have an appropriately-modified
--- 30,50 ----
  SETS=5
  
! if [ -n "$REBAL" ]; then
!     # Put them all into reservoirs
!     python rebal.py -r Data/Ham/reservoir -s Data/Ham/Set -n 0 -Q
!     python rebal.py -r Data/Spam/reservoir -s Data/Spam/Set -n 0 -Q
!     # Rebalance
!     python rebal.py -r Data/Ham/reservoir -s Data/Ham/Set -n $RNUM -Q
!     python rebal.py -r Data/Spam/reservoir -s Data/Spam/Set -n $RNUM -Q
! fi
  
  case "$TEST" in
+     run2|useold)
+ 	python timcv.py -n $SETS > run2.txt
+ 
+         python rates.py run1 run2 > runrates.txt
+ 
+         python cmp.py run1s run2s | tee results.txt
+ 	;;
      robinson1)
  	# This test requires you have an appropriately-modified